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195 results on '"Boomsma, Dorret I."'

1. Brain‐age prediction: Systematic evaluation of site effects, and sample age range and size

Author

Yu, Yuetong, Cui, Hao‐Qi, Haas, Shalaila S, New, Faye, Sanford, Nicole, Yu, Kevin, Zhan, Denghuang, Yang, Guoyuan, Gao, Jia‐Hong, Wei, Dongtao, Qiu, Jiang, Banaj, Nerisa, Boomsma, Dorret I, Breier, Alan, Brodaty, Henry, Buckner, Randy L, Buitelaar, Jan K, Cannon, Dara M, Caseras, Xavier, Clark, Vincent P, Conrod, Patricia J, Crivello, Fabrice, Crone, Eveline A, Dannlowski, Udo, Davey, Christopher G, de Haan, Lieuwe, de Zubicaray, Greig I, Di Giorgio, Annabella, Fisch, Lukas, Fisher, Simon E, Franke, Barbara, Glahn, David C, Grotegerd, Dominik, Gruber, Oliver, Gur, Raquel E, Gur, Ruben C, Hahn, Tim, Harrison, Ben J, Hatton, Sean, Hickie, Ian B, Pol, Hilleke E Hulshoff, Jamieson, Alec J, Jernigan, Terry L, Jiang, Jiyang, Kalnin, Andrew J, Kang, Sim, Kochan, Nicole A, Kraus, Anna, Lagopoulos, Jim, Lazaro, Luisa, McDonald, Brenna C, McDonald, Colm, McMahon, Katie L, Mwangi, Benson, Piras, Fabrizio, Rodriguez‐Cruces, Raul, Royer, Jessica, Sachdev, Perminder S, Satterthwaite, Theodore D, Saykin, Andrew J, Schumann, Gunter, Sevaggi, Pierluigi, Smoller, Jordan W, Soares, Jair C, Spalletta, Gianfranco, Tamnes, Christian K, Trollor, Julian N, Ent, Dennis Van't, Vecchio, Daniela, Walter, Henrik, Wang, Yang, Weber, Bernd, Wen, Wei, Wierenga, Lara M, Williams, Steven CR, Wu, Mon‐Ju, Zunta‐Soares, Giovana B, Bernhardt, Boris, Thompson, Paul, Frangou, Sophia, Ge, Ruiyang, and Group, ENIGMA‐Lifespan Working

Subjects
Biological Psychology, Psychology, Aging, Clinical Research, Neurosciences, Neurological, Mental health, Humans, Adolescent, Female, Aged, Adult, Child, Young Adult, Male, Brain, Aged, 80 and over, Child, Preschool, Middle Aged, Magnetic Resonance Imaging, Neuroimaging, Sample Size, benchmarking, brain aging, brainAGE, ENIGMA‐Lifespan Working Group, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Published
2024

2. Genetic diversity fuels gene discovery for tobacco and alcohol use

Author

Saunders, Gretchen RB, Wang, Xingyan, Chen, Fang, Jang, Seon-Kyeong, Liu, Mengzhen, Wang, Chen, Gao, Shuang, Jiang, Yu, Khunsriraksakul, Chachrit, Otto, Jacqueline M, Addison, Clifton, Akiyama, Masato, Albert, Christine M, Aliev, Fazil, Alonso, Alvaro, Arnett, Donna K, Ashley-Koch, Allison E, Ashrani, Aneel A, Barnes, Kathleen C, Barr, R Graham, Bartz, Traci M, Becker, Diane M, Bielak, Lawrence F, Benjamin, Emelia J, Bis, Joshua C, Bjornsdottir, Gyda, Blangero, John, Bleecker, Eugene R, Boardman, Jason D, Boerwinkle, Eric, Boomsma, Dorret I, Boorgula, Meher Preethi, Bowden, Donald W, Brody, Jennifer A, Cade, Brian E, Chasman, Daniel I, Chavan, Sameer, Chen, Yii-Der Ida, Chen, Zhengming, Cheng, Iona, Cho, Michael H, Choquet, Hélène, Cole, John W, Cornelis, Marilyn C, Cucca, Francesco, Curran, Joanne E, de Andrade, Mariza, Dick, Danielle M, Docherty, Anna R, Duggirala, Ravindranath, Eaton, Charles B, Ehringer, Marissa A, Esko, Tõnu, Faul, Jessica D, Fernandes Silva, Lilian, Fiorillo, Edoardo, Fornage, Myriam, Freedman, Barry I, Gabrielsen, Maiken E, Garrett, Melanie E, Gharib, Sina A, Gieger, Christian, Gillespie, Nathan, Glahn, David C, Gordon, Scott D, Gu, Charles C, Gu, Dongfeng, Gudbjartsson, Daniel F, Guo, Xiuqing, Haessler, Jeffrey, Hall, Michael E, Haller, Toomas, Harris, Kathleen Mullan, He, Jiang, Herd, Pamela, Hewitt, John K, Hickie, Ian, Hidalgo, Bertha, Hokanson, John E, Hopfer, Christian, Hottenga, JoukeJan, Hou, Lifang, Huang, Hongyan, Hung, Yi-Jen, Hunter, David J, Hveem, Kristian, Hwang, Shih-Jen, Hwu, Chii-Min, Iacono, William, Irvin, Marguerite R, Jee, Yon Ho, Johnson, Eric O, Joo, Yoonjung Y, Jorgenson, Eric, Justice, Anne E, Kamatani, Yoichiro, Kaplan, Robert C, Kaprio, Jaakko, Kardia, Sharon LR, and Keller, Matthew C

Subjects
Genetics, Alcoholism, Alcohol Use and Health, Prevention, Human Genome, Substance Misuse, Aetiology, 2.1 Biological and endogenous factors, Cancer, Good Health and Well Being, Humans, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Multifactorial Inheritance, Risk Factors, Tobacco Use, Alcohol Drinking, Transcriptome, Sample Size, Genetic Loci, Internationality, Europe, 23andMe Research Team, Biobank Japan Project, General Science & Technology
Abstract

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Published
2022

3. Genome-wide Association Meta-analysis of Childhood and Adolescent Internalizing Symptoms

Author

Jami, Eshim S, Hammerschlag, Anke R, Ip, Hill F, Allegrini, Andrea G, Benyamin, Beben, Border, Richard, Diemer, Elizabeth W, Jiang, Chang, Karhunen, Ville, Lu, Yi, Lu, Qing, Mallard, Travis T, Mishra, Pashupati P, Nolte, Ilja M, Palviainen, Teemu, Peterson, Roseann E, Sallis, Hannah M, Shabalin, Andrey A, Tate, Ashley E, Thiering, Elisabeth, Vilor-Tejedor, Natàlia, Wang, Carol, Zhou, Ang, Adkins, Daniel E, Alemany, Silvia, Ask, Helga, Chen, Qi, Corley, Robin P, Ehli, Erik A, Evans, Luke M, Havdahl, Alexandra, Hagenbeek, Fiona A, Hakulinen, Christian, Henders, Anjali K, Hottenga, Jouke Jan, Korhonen, Tellervo, Mamun, Abdullah, Marrington, Shelby, Neumann, Alexander, Rimfeld, Kaili, Rivadeneira, Fernando, Silberg, Judy L, van Beijsterveldt, Catharina E, Vuoksimaa, Eero, Whipp, Alyce M, Tong, Xiaoran, Andreassen, Ole A, Boomsma, Dorret I, Brown, Sandra A, Burt, S Alexandra, Copeland, William, Dick, Danielle M, Harden, K Paige, Harris, Kathleen Mullan, Hartman, Catharina A, Heinrich, Joachim, Hewitt, John K, Hopfer, Christian, Hypponen, Elina, Jarvelin, Marjo-Riitta, Kaprio, Jaakko, Keltikangas-Järvinen, Liisa, Klump, Kelly L, Krauter, Kenneth, Kuja-Halkola, Ralf, Larsson, Henrik, Lehtimäki, Terho, Lichtenstein, Paul, Lundström, Sebastian, Maes, Hermine H, Magnus, Per, Munafò, Marcus R, Najman, Jake M, Njølstad, Pål R, Oldehinkel, Albertine J, Pennell, Craig E, Plomin, Robert, Reichborn-Kjennerud, Ted, Reynolds, Chandra, Rose, Richard J, Smolen, Andrew, Snieder, Harold, Stallings, Michael, Standl, Marie, Sunyer, Jordi, Tiemeier, Henning, Wadsworth, Sally J, Wall, Tamara L, Whitehouse, Andrew JO, Williams, Gail M, Ystrøm, Eivind, Nivard, Michel G, Bartels, Meike, and Middeldorp, Christel M

Subjects
Biological Psychology, Psychology, Pediatric Research Initiative, Pediatric, Brain Disorders, Behavioral and Social Science, Human Genome, Mental Health, Biotechnology, Serious Mental Illness, Genetics, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Aetiology, Mental health, Adolescent, Adult, Aggression, Anxiety, Attention Deficit Disorder with Hyperactivity, Autistic Disorder, Bipolar Disorder, Child, Child, Preschool, Depression, Genome-Wide Association Study, Humans, Loneliness, Polymorphism, Single Nucleotide, Schizophrenia, Sleep Initiation and Maintenance Disorders, depression, anxiety, repeated measures, genetic epidemiology, molecular genetics, Medical and Health Sciences, Psychology and Cognitive Sciences, Developmental & Child Psychology, Clinical sciences, Paediatrics, Applied and developmental psychology
Abstract

ObjectiveTo investigate the genetic architecture of internalizing symptoms in childhood and adolescence.MethodIn 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument.ResultsThe meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa.ConclusionGenetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

Published
2022

4. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Author

Howe, Laurence J, Nivard, Michel G, Morris, Tim T, Hansen, Ailin F, Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A, Palviainen, Teemu, van der Zee, Matthijs D, Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M, Bielak, Lawrence F, Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A, Reynolds, Chandra A, Balbona, Jared V, Andreassen, Ole A, Ask, Helga, Baras, Aris, Bauer, Christopher R, Boomsma, Dorret I, Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C, Dokuru, Deepika R, Evans, Luke M, de Geus, Eco JC, Giddaluru, Sudheer, Gordon, Scott D, Harden, K Paige, Hill, W David, Hughes, Amanda, Kerr, Shona M, Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A, Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik KE, Mallard, Travis T, Martikainen, Pekka, Mills, Melinda C, Njølstad, Pål Rasmus, Overton, John D, Pedersen, Nancy L, Porteous, David J, Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C, Stoltenberg, Camilla, Tucker-Drob, Elliot M, Wright, Margaret J, Hewitt, John K, Keller, Matthew C, Stallings, Michael C, Lee, James J, Christensen, Kaare, Kardia, Sharon LR, Peyser, Patricia A, Smith, Jennifer A, Wilson, James F, Hopper, John L, Hägg, Sara, Spector, Tim D, Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G, Oskarsson, Sven, Justice, Anne E, Millwood, Iona Y, Hveem, Kristian, Naess, Øyvind, Willer, Cristen J, Åsvold, Bjørn Olav, Koellinger, Philipp D, Kaprio, Jaakko, Medland, Sarah E, Walters, Robin G, Benjamin, Daniel J, Turley, Patrick, Evans, David M, Davey Smith, George, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, and Davies, Neil M

Subjects
Human Genome, Genetics, Pediatric, 2.1 Biological and endogenous factors, Aetiology, Mental health, Generic health relevance, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Social Science Genetic Association Consortium, Within Family Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.

Published
2022

5. Smoking remains associated with education after controlling for social background and genetic factors in a study of 18 twin cohorts

Author

Silventoinen, Karri, Piirtola, Maarit, Jelenkovic, Aline, Sund, Reijo, Tarnoki, Adam D, Tarnoki, David L, Medda, Emanuela, Nisticò, Lorenza, Toccaceli, Virgilia, Honda, Chika, Inui, Fujio, Tomizawa, Rie, Watanabe, Mikio, Sakai, Norio, Gatz, Margaret, Butler, David A, Lee, Jooyeon, Lee, Soo Ji, Sung, Joohon, Franz, Carol E, Kremen, William S, Lyons, Michael J, Derom, Catherine A, Vlietinck, Robert F, Loos, Ruth JF, Tynelius, Per, Rasmussen, Finn, Martin, Nicholas G, Medland, Sarah E, Montgomery, Grant W, Brandt, Ingunn, Nilsen, Thomas S, Harris, Jennifer R, Tyler, Jessica, Hopper, John L, Magnusson, Patrik KE, Pedersen, Nancy L, Dahl Aslan, Anna K, Ordoñana, Juan R, Sánchez-Romera, Juan F, Colodro-Conde, Lucia, Rebato, Esther, Zhang, Dongfeng, Pang, Zengchang, Tan, Qihua, Silberg, Judy L, Maes, Hermine H, Boomsma, Dorret I, Sørensen, Thorkild IA, Korhonen, Tellervo, and Kaprio, Jaakko

Subjects
Biological Psychology, Psychology, Genetics, Pediatric, Prevention, Tobacco, Tobacco Smoke and Health, Quality Education, Child, Educational Status, Humans, Smoking, Smoking Cessation, Twins, Dizygotic, Twins, Monozygotic
Abstract

We tested the causality between education and smoking using the natural experiment of discordant twin pairs allowing to optimally control for background genetic and childhood social factors. Data from 18 cohorts including 10,527 monozygotic (MZ) and same-sex dizygotic (DZ) twin pairs discordant for education and smoking were analyzed by linear fixed effects regression models. Within twin pairs, education levels were lower among the currently smoking than among the never smoking co-twins and this education difference was larger within DZ than MZ pairs. Similarly, education levels were higher among former smoking than among currently smoking co-twins, and this difference was larger within DZ pairs. Our results support the hypothesis of a causal effect of education on both current smoking status and smoking cessation. However, the even greater intra-pair differences within DZ pairs, who share only 50% of their segregating genes, provide evidence that shared genetic factors also contribute to these associations.

Published
2022

6. Item-Level Genome-Wide Association Study of the Alcohol Use Disorders Identification Test in Three Population-Based Cohorts

Author

Mallard, Travis T, Savage, Jeanne E, Johnson, Emma C, Huang, Yuye, Edwards, Alexis C, Hottenga, Jouke J, Grotzinger, Andrew D, Gustavson, Daniel E, Jennings, Mariela V, Anokhin, Andrey, Dick, Danielle M, Edenberg, Howard J, Kramer, John R, Lai, Dongbing, Meyers, Jacquelyn L, Pandey, Ashwini K, Harden, Kathryn Paige, Nivard, Michel G, de Geus, Eco JC, Boomsma, Dorret I, Agrawal, Arpana, Davis, Lea K, Clarke, Toni-Kim, Palmer, Abraham A, and Sanchez-Roige, Sandra

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Mental Health, Alcoholism, Alcohol Use and Health, Substance Misuse, Brain Disorders, Human Genome, Prevention, Genetics, Cardiovascular, Oral and gastrointestinal, Mental health, Good Health and Well Being, Alcohol Drinking, Alcoholism, Genome-Wide Association Study, Humans, ALSPAC, Alcohol, Alcohol Consumption, GWAS, Genomic Structural Equation Modeling, Substance-Related and Addictive Disorders, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Clinical and health psychology
Abstract

ObjectiveGenome-wide association studies (GWASs) of the Alcohol Use Disorders Identification Test (AUDIT), a 10-item screen for alcohol use disorder (AUD), have elucidated novel loci for alcohol consumption and misuse. However, these studies also revealed that GWASs can be influenced by numerous biases (e.g., measurement error, selection bias), which may have led to inconsistent genetic correlations between alcohol involvement and AUD, as well as paradoxically negative genetic correlations between alcohol involvement and psychiatric disorders and/or medical conditions. The authors used genomic structural equation modeling to elucidate the genetics of alcohol consumption and problematic consequences of alcohol use as measured by AUDIT.MethodsTo explore these unexpected differences in genetic correlations, the authors conducted the first item-level and the largest GWAS of AUDIT items (N=160,824) and applied a multivariate framework to mitigate previous biases.ResultsThe authors identified novel patterns of similarity (and dissimilarity) among the AUDIT items and found evidence of a correlated two-factor structure at the genetic level ("consumption" and "problems," rg=0.80). Moreover, by applying empirically derived weights to each of the AUDIT items, the authors constructed an aggregate measure of alcohol consumption that was strongly associated with alcohol dependence (rg=0.67), moderately associated with several other psychiatric disorders, and no longer positively associated with health and positive socioeconomic outcomes. Lastly, by conducting polygenic analyses in three independent cohorts that differed in their ascertainment and prevalence of AUD, the authors identified novel genetic associations between alcohol consumption, alcohol misuse, and health.ConclusionsThis work further emphasizes the value of AUDIT for both clinical and genetic studies of AUD and the importance of using multivariate methods to study genetic associations that are more closely related to AUD.

Published
2022

7. Effects of copy number variations on brain structure and risk for psychiatric illness: Large‐scale studies from the ENIGMA working groups on CNVs

Author

Sønderby, Ida E, Ching, Christopher RK, Thomopoulos, Sophia I, van der Meer, Dennis, Sun, Daqiang, Villalon‐Reina, Julio E, Agartz, Ingrid, Amunts, Katrin, Arango, Celso, Armstrong, Nicola J, Ayesa‐Arriola, Rosa, Bakker, Geor, Bassett, Anne S, Boomsma, Dorret I, Bülow, Robin, Butcher, Nancy J, Calhoun, Vince D, Caspers, Svenja, Chow, Eva WC, Cichon, Sven, Ciufolini, Simone, Craig, Michael C, Crespo‐Facorro, Benedicto, Cunningham, Adam C, Dale, Anders M, Dazzan, Paola, de Zubicaray, Greig I, Djurovic, Srdjan, Doherty, Joanne L, Donohoe, Gary, Draganski, Bogdan, Durdle, Courtney A, Ehrlich, Stefan, Emanuel, Beverly S, Espeseth, Thomas, Fisher, Simon E, Ge, Tian, Glahn, David C, Grabe, Hans J, Gur, Raquel E, Gutman, Boris A, Haavik, Jan, Håberg, Asta K, Hansen, Laura A, Hashimoto, Ryota, Hibar, Derrek P, Holmes, Avram J, Hottenga, Jouke‐Jan, Pol, Hilleke E Hulshoff, Jalbrzikowski, Maria, Knowles, Emma EM, Kushan, Leila, Linden, David EJ, Liu, Jingyu, Lundervold, Astri J, Martin‐Brevet, Sandra, Martínez, Kenia, Mather, Karen A, Mathias, Samuel R, McDonald‐McGinn, Donna M, McRae, Allan F, Medland, Sarah E, Moberget, Torgeir, Modenato, Claudia, Sánchez, Jennifer Monereo, Moreau, Clara A, Mühleisen, Thomas W, Paus, Tomas, Pausova, Zdenka, Prieto, Carlos, Ragothaman, Anjanibhargavi, Reinbold, Céline S, Marques, Tiago Reis, Repetto, Gabriela M, Reymond, Alexandre, Roalf, David R, Rodriguez‐Herreros, Borja, Rucker, James J, Sachdev, Perminder S, Schmitt, James E, Schofield, Peter R, Silva, Ana I, Stefansson, Hreinn, Stein, Dan J, Tamnes, Christian K, Tordesillas‐Gutiérrez, Diana, Ulfarsson, Magnus O, Vajdi, Ariana, van 't Ent, Dennis, van den Bree, Marianne BM, Vassos, Evangelos, Vázquez‐Bourgon, Javier, Vila‐Rodriguez, Fidel, Walters, G Bragi, Wen, Wei, Westlye, Lars T, Wittfeld, Katharina, Zackai, Elaine H, Stefánsson, Kári, and Jacquemont, Sebastien

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Mental Health, Clinical Research, Pediatric, Genetics, Basic Behavioral and Social Science, Human Genome, Prevention, Brain Disorders, Behavioral and Social Science, Neurosciences, Aetiology, 2.1 Biological and endogenous factors, Mental health, Neurological, Brain, DNA Copy Number Variations, Humans, Magnetic Resonance Imaging, Mental Disorders, Multicenter Studies as Topic, Neurodevelopmental Disorders, Neuroimaging, brain structural imaging, copy number variant, diffusion tensor imaging, evolution, genetics-first approach, neurodevelopmental disorders, psychiatric disorders, ENIGMA-CNV Working Group, ENIGMA 22q11.2 Deletion Syndrome Working Group, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.

Published
2022

8. Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Author

Dima, Danai, Modabbernia, Amirhossein, Papachristou, Efstathios, Doucet, Gaelle E, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N, Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn I, Andersson, Micael, Andreasen, Nancy C, Andreassen, Ole A, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret I, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M, Buitelaar, Jan K, Busatto, Geraldo F, Buckner, Randy L, Calhoun, Vincent, Canales-Rodríguez, Erick J, Cannon, Dara M, Caseras, Xavier, Castellanos, Francisco X, Cervenka, Simon, Chaim-Avancini, Tiffany M, Ching, Christopher RK, Chubar, Victoria, Clark, Vincent P, Conrod, Patricia, Conzelmann, Annette, Crespo-Facorro, Benedicto, Crivello, Fabrice, Crone, Eveline A, Dannlowski, Udo, Dale, Anders M, Davey, Christopher, de Geus, Eco JC, de Haan, Lieuwe, de Zubicaray, Greig I, den Braber, Anouk, Dickie, Erin W, Di Giorgio, Annabella, Doan, Nhat Trung, Dørum, Erlend S, Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fatouros-Bergman, Helena, Fisher, Simon E, Fouche, Jean-Paul, Franke, Barbara, Frodl, Thomas, Fuentes-Claramonte, Paola, Glahn, David C, Gotlib, Ian H, Grabe, Hans-Jörgen, Grimm, Oliver, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Gur, Rachel E, Gur, Ruben C, Hahn, Tim, Harrison, Ben J, Hartman, Catharine A, Hatton, Sean N, Heinz, Andreas, Heslenfeld, Dirk J, Hibar, Derrek P, Hickie, Ian B, Ho, Beng-Choon, Hoekstra, Pieter J, Hohmann, Sarah, Holmes, Avram J, Hoogman, Martine, Hosten, Norbert, Howells, Fleur M, Hulshoff Pol, Hilleke E, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Jernigan, Terry L, Jiang, Jiyang, Jönsson, Erik G, Joska, John A, Kahn, Rene, and Kalnin, Andrew

Subjects
Karolinska Schizophrenia Project, Amygdala, Hippocampus, Thalamus, Corpus Striatum, Humans, Human Development, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Child, Preschool, Female, Male, Young Adult, Neuroimaging, ENIGMA, brain morphometry, longitudinal trajectories, multisite, Neurosciences, Aging, Aetiology, 2.1 Biological and endogenous factors, Mental health, Cognitive Sciences, Experimental Psychology
Abstract

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

Published
2022

9. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3–90 years

Author

Frangou, Sophia, Modabbernia, Amirhossein, Williams, Steven CR, Papachristou, Efstathios, Doucet, Gaelle E, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N, Albajes‐Eizagirre, Anton, Alnæs, Dag, Alpert, Kathryn I, Andersson, Micael, Andreasen, Nancy C, Andreassen, Ole A, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur‐Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret I, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M, Buitelaar, Jan K, Busatto, Geraldo F, Buckner, Randy L, Calhoun, Vincent, Canales‐Rodríguez, Erick J, Cannon, Dara M, Caseras, Xavier, Castellanos, Francisco X, Cervenka, Simon, Chaim‐Avancini, Tiffany M, Ching, Christopher RK, Chubar, Victoria, Clark, Vincent P, Conrod, Patricia, Conzelmann, Annette, Crespo‐Facorro, Benedicto, Crivello, Fabrice, Crone, Eveline A, Dale, Anders M, Dannlowski, Udo, Davey, Christopher, Geus, Eco JC, Haan, Lieuwe, Zubicaray, Greig I, Braber, Anouk, Dickie, Erin W, Di Giorgio, Annabella, Doan, Nhat Trung, Dørum, Erlend S, Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fatouros‐Bergman, Helena, Fisher, Simon E, Fouche, Jean‐Paul, Franke, Barbara, Frodl, Thomas, Fuentes‐Claramonte, Paola, Glahn, David C, Gotlib, Ian H, Grabe, Hans‐Jörgen, Grimm, Oliver, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Gur, Rachel E, Gur, Ruben C, Hahn, Tim, Harrison, Ben J, Hartman, Catharine A, Hatton, Sean N, Heinz, Andreas, Heslenfeld, Dirk J, Hibar, Derrek P, Hickie, Ian B, Ho, Beng‐Choon, Hoekstra, Pieter J, Hohmann, Sarah, Holmes, Avram J, Hoogman, Martine, Hosten, Norbert, Howells, Fleur M, Pol, Hilleke E Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Jernigan, Terry L, Jiang, Jiyang, Jönsson, Erik G, Joska, John A, and Kahn, Rene

Subjects
Behavioral and Social Science, Neurosciences, Aging, Adolescent, Adult, Aged, Aged, 80 and over, Cerebral Cortex, Child, Child, Preschool, Cross-Sectional Studies, Female, Human Development, Humans, Male, Middle Aged, Neuroimaging, Young Adult, aging, cortical thickness, development, trajectories, Karolinska Schizophrenia Project, Cognitive Sciences, Experimental Psychology
Abstract

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Published
2022

10. Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

Author

McCartney, Daniel L, Min, Josine L, Richmond, Rebecca C, Lu, Ake T, Sobczyk, Maria K, Davies, Gail, Broer, Linda, Guo, Xiuqing, Jeong, Ayoung, Jung, Jeesun, Kasela, Silva, Katrinli, Seyma, Kuo, Pei-Lun, Matias-Garcia, Pamela R, Mishra, Pashupati P, Nygaard, Marianne, Palviainen, Teemu, Patki, Amit, Raffield, Laura M, Ratliff, Scott M, Richardson, Tom G, Robinson, Oliver, Soerensen, Mette, Sun, Dianjianyi, Tsai, Pei-Chien, van der Zee, Matthijs D, Walker, Rosie M, Wang, Xiaochuan, Wang, Yunzhang, Xia, Rui, Xu, Zongli, Yao, Jie, Zhao, Wei, Correa, Adolfo, Boerwinkle, Eric, Dugué, Pierre-Antoine, Durda, Peter, Elliott, Hannah R, Gieger, Christian, de Geus, Eco JC, Harris, Sarah E, Hemani, Gibran, Imboden, Medea, Kähönen, Mika, Kardia, Sharon LR, Kresovich, Jacob K, Li, Shengxu, Lunetta, Kathryn L, Mangino, Massimo, Mason, Dan, McIntosh, Andrew M, Mengel-From, Jonas, Moore, Ann Zenobia, Murabito, Joanne M, Ollikainen, Miina, Pankow, James S, Pedersen, Nancy L, Peters, Annette, Polidoro, Silvia, Porteous, David J, Raitakari, Olli, Rich, Stephen S, Sandler, Dale P, Sillanpää, Elina, Smith, Alicia K, Southey, Melissa C, Strauch, Konstantin, Tiwari, Hemant, Tanaka, Toshiko, Tillin, Therese, Uitterlinden, Andre G, Van Den Berg, David J, van Dongen, Jenny, Wilson, James G, Wright, John, Yet, Idil, Arnett, Donna, Bandinelli, Stefania, Bell, Jordana T, Binder, Alexandra M, Boomsma, Dorret I, Chen, Wei, Christensen, Kaare, Conneely, Karen N, Elliott, Paul, Ferrucci, Luigi, Fornage, Myriam, Hägg, Sara, Hayward, Caroline, Irvin, Marguerite, Kaprio, Jaakko, Lawlor, Deborah A, Lehtimäki, Terho, Lohoff, Falk W, Milani, Lili, Milne, Roger L, Probst-Hensch, Nicole, Reiner, Alex P, Ritz, Beate, and Rotter, Jerome I

Subjects
Prevention, Nutrition, Aging, Human Genome, Genetics, Generic health relevance, Inflammatory and immune system, Good Health and Well Being, Adiposity, Biomarkers, C-Reactive Protein, CpG Islands, DNA Methylation, Educational Status, Epigenesis, Genetic, Genetic Loci, Genetic Markers, Genome, Human, Genome-Wide Association Study, Granulocytes, Humans, Immunity, Innate, Lipid Metabolism, Multifactorial Inheritance, Plasminogen Activator Inhibitor 1, DNA methylation, GWAS, Epigenetic clock, Genetics of DNA Methylation Consortium, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

BackgroundBiological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field.ResultsLeveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels.ConclusionThis study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

Published
2021

11. Genetic insights into biological mechanisms governing human ovarian ageing

Author

Ruth, Katherine S, Day, Felix R, Hussain, Jazib, Martínez-Marchal, Ana, Aiken, Catherine E, Azad, Ajuna, Thompson, Deborah J, Knoblochova, Lucie, Abe, Hironori, Tarry-Adkins, Jane L, Gonzalez, Javier Martin, Fontanillas, Pierre, Claringbould, Annique, Bakker, Olivier B, Sulem, Patrick, Walters, Robin G, Terao, Chikashi, Turon, Sandra, Horikoshi, Momoko, Lin, Kuang, Onland-Moret, N Charlotte, Sankar, Aditya, Hertz, Emil Peter Thrane, Timshel, Pascal N, Shukla, Vallari, Borup, Rehannah, Olsen, Kristina W, Aguilera, Paula, Ferrer-Roda, Mònica, Huang, Yan, Stankovic, Stasa, Timmers, Paul RHJ, Ahearn, Thomas U, Alizadeh, Behrooz Z, Naderi, Elnaz, Andrulis, Irene L, Arnold, Alice M, Aronson, Kristan J, Augustinsson, Annelie, Bandinelli, Stefania, Barbieri, Caterina M, Beaumont, Robin N, Becher, Heiko, Beckmann, Matthias W, Benonisdottir, Stefania, Bergmann, Sven, Bochud, Murielle, Boerwinkle, Eric, Bojesen, Stig E, Bolla, Manjeet K, Boomsma, Dorret I, Bowker, Nicholas, Brody, Jennifer A, Broer, Linda, Buring, Julie E, Campbell, Archie, Campbell, Harry, Castelao, Jose E, Catamo, Eulalia, Chanock, Stephen J, Chenevix-Trench, Georgia, Ciullo, Marina, Corre, Tanguy, Couch, Fergus J, Cox, Angela, Crisponi, Laura, Cross, Simon S, Cucca, Francesco, Czene, Kamila, Smith, George Davey, de Geus, Eco JCN, de Mutsert, Renée, De Vivo, Immaculata, Demerath, Ellen W, Dennis, Joe, Dunning, Alison M, Dwek, Miriam, Eriksson, Mikael, Esko, Tõnu, Fasching, Peter A, Faul, Jessica D, Ferrucci, Luigi, Franceschini, Nora, Frayling, Timothy M, Gago-Dominguez, Manuela, Mezzavilla, Massimo, García-Closas, Montserrat, Gieger, Christian, Giles, Graham G, Grallert, Harald, Gudbjartsson, Daniel F, Gudnason, Vilmundur, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hayward, Caroline, He, Chunyan, He, Wei, and Heiss, Gerardo

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Estrogen, Prevention, Women's Health, Contraception/Reproduction, Aging, Infertility, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Good Health and Well Being, Adult, Alleles, Animals, Bone and Bones, Checkpoint Kinase 1, Checkpoint Kinase 2, Diabetes Mellitus, Type 2, Diet, Europe, Asia, Eastern, Female, Fertility, Fragile X Mental Retardation Protein, Genetic Predisposition to Disease, Genome-Wide Association Study, Healthy Aging, Humans, Longevity, Menopause, Menopause, Premature, Mice, Mice, Inbred C57BL, Middle Aged, Ovary, Primary Ovarian Insufficiency, Uterus, Biobank-based Integrative Omics Study (BIOS) Consortium, eQTLGen Consortium, Biobank Japan Project, China Kadoorie Biobank Collaborative Group, kConFab Investigators, LifeLines Cohort Study, InterAct consortium, 23andMe Research Team, General Science & Technology
Abstract

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

Published
2021

12. Genetic risk for major depressive disorder and loneliness in sex-specific associations with coronary artery disease

Author

Dennis, Jessica, Sealock, Julia, Levinson, Rebecca T, Farber-Eger, Eric, Franco, Jacob, Fong, Sarah, Straub, Peter, Hucks, Donald, Song, Wen-Liang, Linton, MacRae F, Fontanillas, Pierre, Elson, Sarah L, Ruderfer, Douglas, Abdellaoui, Abdel, Sanchez-Roige, Sandra, Palmer, Abraham A, Boomsma, Dorret I, Cox, Nancy J, Chen, Guanhua, Mosley, Jonathan D, Wells, Quinn S, and Davis, Lea K

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Brain Disorders, Genetics, Heart Disease - Coronary Heart Disease, Depression, Cardiovascular, Atherosclerosis, Major Depressive Disorder, Prevention, Heart Disease, Mental Health, Human Genome, Mental Illness, Serious Mental Illness, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Coronary Artery Disease, Depressive Disorder, Major, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Loneliness, Male, Multifactorial Inheritance, Risk Factors, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Major depressive disorder (MDD) and loneliness are phenotypically and genetically correlated with coronary artery disease (CAD), but whether these associations are explained by pleiotropic genetic variants or shared comorbidities is unclear. To tease apart these scenarios, we first assessed the medical morbidity pattern associated with genetic risk factors for MDD and loneliness by conducting a phenome-wide association study in 18,385 European-ancestry individuals in the Vanderbilt University Medical Center biobank, BioVU. Polygenic scores for MDD and loneliness were developed for each person using previously published meta-GWAS summary statistics, and were tested for association with 882 clinical diagnoses ascertained via billing codes in electronic health records. We discovered strong associations with heart disease diagnoses, and next embarked on targeted analyses of CAD in 3893 cases and 4197 controls. We found odds ratios of 1.11 (95% CI, 1.04-1.18; P 8.43 × 10-4) and 1.13 (95% CI, 1.07-1.20; P 4.51 × 10-6) per 1-SD increase in the polygenic scores for MDD and loneliness, respectively. Results were similar in patients without psychiatric symptoms, and the increased risk persisted in females even after adjusting for multiple conventional risk factors and a polygenic score for CAD. In a final sensitivity analysis, we statistically adjusted for the genetic correlation between MDD and loneliness and re-computed polygenic scores. The polygenic score unique to loneliness remained associated with CAD (OR 1.09, 95% CI 1.03-1.15; P 0.002), while the polygenic score unique to MDD did not (OR 1.00, 95% CI 0.95-1.06; P 0.97). Our replication sample was the Atherosclerosis Risk in Communities (ARIC) cohort of 7197 European-ancestry participants (1598 incident CAD cases). In ARIC, polygenic scores for MDD and loneliness were associated with hazard ratios of 1.07 (95% CI, 0.99-1.14; P = 0.07) and 1.07 (1.01-1.15; P = 0.03), respectively, and we replicated findings from the BioVU sensitivity analyses. We conclude that genetic risk factors for MDD and loneliness act pleiotropically to increase CAD risk in females.

Published
2021

13. Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group

Author

Jia, Tianye, Chu, Congying, Liu, Yun, van Dongen, Jenny, Papastergios, Evangelos, Armstrong, Nicola J, Bastin, Mark E, Carrillo-Roa, Tania, den Braber, Anouk, Harris, Mathew, Jansen, Rick, Liu, Jingyu, Luciano, Michelle, Ori, Anil PS, Roiz Santiañez, Roberto, Ruggeri, Barbara, Sarkisyan, Daniil, Shin, Jean, Sungeun, Kim, Tordesillas Gutiérrez, Diana, van’t Ent, Dennis, Ames, David, Artiges, Eric, Bakalkin, Georgy, Banaschewski, Tobias, Bokde, Arun LW, Brodaty, Henry, Bromberg, Uli, Brouwer, Rachel, Büchel, Christian, Burke Quinlan, Erin, Cahn, Wiepke, de Zubicaray, Greig I, Ehrlich, Stefan, Ekström, Tomas J, Flor, Herta, Fröhner, Juliane H, Frouin, Vincent, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Hoare, Jacqueline, Ittermann, Bernd, Jahanshad, Neda, Jiang, Jiyang, Kwok, John B, Martin, Nicholas G, Martinot, Jean-Luc, Mather, Karen A, McMahon, Katie L, McRae, Allan F, Nees, Frauke, Papadopoulos Orfanos, Dimitri, Paus, Tomáš, Poustka, Luise, Sämann, Philipp G, Schofield, Peter R, Smolka, Michael N, Stein, Dan J, Strike, Lachlan T, Teeuw, Jalmar, Thalamuthu, Anbupalam, Trollor, Julian, Walter, Henrik, Wardlaw, Joanna M, Wen, Wei, Whelan, Robert, Apostolova, Liana G, Binder, Elisabeth B, Boomsma, Dorret I, Calhoun, Vince, Crespo-Facorro, Benedicto, Deary, Ian J, Hulshoff Pol, Hilleke, Ophoff, Roel A, Pausova, Zdenka, Sachdev, Perminder S, Saykin, Andrew, Wright, Margaret J, Thompson, Paul M, Schumann, Gunter, and Desrivières, Sylvane

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Mental Health, Neurosciences, Genetics, Human Genome, Diabetes, Neurodegenerative, 2.1 Biological and endogenous factors, Aetiology, Neurological, Mental health, CpG Islands, DNA Methylation, Epigenesis, Genetic, Epigenome, Genome-Wide Association Study, Humans, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.

Published
2021

14. Large-scale association analyses identify host factors influencing human gut microbiome composition

Author

Kurilshikov, Alexander, Medina-Gomez, Carolina, Bacigalupe, Rodrigo, Radjabzadeh, Djawad, Wang, Jun, Demirkan, Ayse, Le Roy, Caroline I, Raygoza Garay, Juan Antonio, Finnicum, Casey T, Liu, Xingrong, Zhernakova, Daria V, Bonder, Marc Jan, Hansen, Tue H, Frost, Fabian, Rühlemann, Malte C, Turpin, Williams, Moon, Jee-Young, Kim, Han-Na, Lüll, Kreete, Barkan, Elad, Shah, Shiraz A, Fornage, Myriam, Szopinska-Tokov, Joanna, Wallen, Zachary D, Borisevich, Dmitrii, Agreus, Lars, Andreasson, Anna, Bang, Corinna, Bedrani, Larbi, Bell, Jordana T, Bisgaard, Hans, Boehnke, Michael, Boomsma, Dorret I, Burk, Robert D, Claringbould, Annique, Croitoru, Kenneth, Davies, Gareth E, van Duijn, Cornelia M, Duijts, Liesbeth, Falony, Gwen, Fu, Jingyuan, van der Graaf, Adriaan, Hansen, Torben, Homuth, Georg, Hughes, David A, Ijzerman, Richard G, Jackson, Matthew A, Jaddoe, Vincent WV, Joossens, Marie, Jørgensen, Torben, Keszthelyi, Daniel, Knight, Rob, Laakso, Markku, Laudes, Matthias, Launer, Lenore J, Lieb, Wolfgang, Lusis, Aldons J, Masclee, Ad AM, Moll, Henriette A, Mujagic, Zlatan, Qibin, Qi, Rothschild, Daphna, Shin, Hocheol, Sørensen, Søren J, Steves, Claire J, Thorsen, Jonathan, Timpson, Nicholas J, Tito, Raul Y, Vieira-Silva, Sara, Völker, Uwe, Völzke, Henry, Võsa, Urmo, Wade, Kaitlin H, Walter, Susanna, Watanabe, Kyoko, Weiss, Stefan, Weiss, Frank U, Weissbrod, Omer, Westra, Harm-Jan, Willemsen, Gonneke, Payami, Haydeh, Jonkers, Daisy MAE, Arias Vasquez, Alejandro, de Geus, Eco JC, Meyer, Katie A, Stokholm, Jakob, Segal, Eran, Org, Elin, Wijmenga, Cisca, Kim, Hyung-Lae, Kaplan, Robert C, Spector, Tim D, Uitterlinden, Andre G, Rivadeneira, Fernando, Franke, Andre, Lerch, Markus M, Franke, Lude, Sanna, Serena, D’Amato, Mauro, and Pedersen, Oluf

Subjects
Microbiology, Biological Sciences, Genetics, Human Genome, Biotechnology, Clinical Research, Digestive Diseases, Nutrition, 2.1 Biological and endogenous factors, Aetiology, Oral and gastrointestinal, Adolescent, Adult, Bifidobacterium, Child, Child, Preschool, Cohort Studies, Female, Gastrointestinal Microbiome, Genetic Variation, Genome-Wide Association Study, Humans, Lactase, Linkage Disequilibrium, Male, Mendelian Randomization Analysis, Metabolism, Quantitative Trait Loci, RNA, Ribosomal, 16S, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P

Published
2021

15. Genome-wide association study identifies 48 common genetic variants associated with handedness

Author

Cuellar-Partida, Gabriel, Tung, Joyce Y, Eriksson, Nicholas, Albrecht, Eva, Aliev, Fazil, Andreassen, Ole A, Barroso, Inês, Beckmann, Jacques S, Boks, Marco P, Boomsma, Dorret I, Boyd, Heather A, Breteler, Monique MB, Campbell, Harry, Chasman, Daniel I, Cherkas, Lynn F, Davies, Gail, de Geus, Eco JC, Deary, Ian J, Deloukas, Panos, Dick, Danielle M, Duffy, David L, Eriksson, Johan G, Esko, Tõnu, Feenstra, Bjarke, Geller, Frank, Gieger, Christian, Giegling, Ina, Gordon, Scott D, Han, Jiali, Hansen, Thomas F, Hartmann, Annette M, Hayward, Caroline, Heikkilä, Kauko, Hicks, Andrew A, Hirschhorn, Joel N, Hottenga, Jouke-Jan, Huffman, Jennifer E, Hwang, Liang-Dar, Ikram, M Arfan, Kaprio, Jaakko, Kemp, John P, Khaw, Kay-Tee, Klopp, Norman, Konte, Bettina, Kutalik, Zoltan, Lahti, Jari, Li, Xin, Loos, Ruth JF, Luciano, Michelle, Magnusson, Sigurdur H, Mangino, Massimo, Marques-Vidal, Pedro, Martin, Nicholas G, McArdle, Wendy L, McCarthy, Mark I, Medina-Gomez, Carolina, Melbye, Mads, Melville, Scott A, Metspalu, Andres, Milani, Lili, Mooser, Vincent, Nelis, Mari, Nyholt, Dale R, O’Connell, Kevin S, Ophoff, Roel A, Palmer, Cameron, Palotie, Aarno, Palviainen, Teemu, Pare, Guillaume, Paternoster, Lavinia, Peltonen, Leena, Penninx, Brenda WJH, Polasek, Ozren, Pramstaller, Peter P, Prokopenko, Inga, Raikkonen, Katri, Ripatti, Samuli, Rivadeneira, Fernando, Rudan, Igor, Rujescu, Dan, Smit, Johannes H, Smith, George Davey, Smoller, Jordan W, Soranzo, Nicole, Spector, Tim D, Pourcain, Beate St, Starr, John M, Stefánsson, Hreinn, Steinberg, Stacy, Teder-Laving, Maris, Thorleifsson, Gudmar, Stefánsson, Kári, Timpson, Nicholas J, Uitterlinden, André G, van Duijn, Cornelia M, van Rooij, Frank JA, Vink, Jaqueline M, Vollenweider, Peter, Vuoksimaa, Eero, and Waeber, Gérard

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Human Genome, Mental Health, Brain Disorders, Neurosciences, Schizophrenia, Genetics, 2.1 Biological and endogenous factors, Aetiology, Mental health, Adult, Aged, Female, Functional Laterality, Gene Frequency, Genetic Loci, Genetic Variation, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Sex Factors, Biomedical and clinical sciences, Health sciences
Abstract

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P

Published
2021

16. 1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans

Author

Sønderby, Ida E, van der Meer, Dennis, Moreau, Clara, Kaufmann, Tobias, Walters, G Bragi, Ellegaard, Maria, Abdellaoui, Abdel, Ames, David, Amunts, Katrin, Andersson, Micael, Armstrong, Nicola J, Bernard, Manon, Blackburn, Nicholas B, Blangero, John, Boomsma, Dorret I, Brodaty, Henry, Brouwer, Rachel M, Bülow, Robin, Bøen, Rune, Cahn, Wiepke, Calhoun, Vince D, Caspers, Svenja, Ching, Christopher RK, Cichon, Sven, Ciufolini, Simone, Crespo-Facorro, Benedicto, Curran, Joanne E, Dale, Anders M, Dalvie, Shareefa, Dazzan, Paola, de Geus, Eco JC, de Zubicaray, Greig I, de Zwarte, Sonja MC, Desrivieres, Sylvane, Doherty, Joanne L, Donohoe, Gary, Draganski, Bogdan, Ehrlich, Stefan, Eising, Else, Espeseth, Thomas, Fejgin, Kim, Fisher, Simon E, Fladby, Tormod, Frei, Oleksandr, Frouin, Vincent, Fukunaga, Masaki, Gareau, Thomas, Ge, Tian, Glahn, David C, Grabe, Hans J, Groenewold, Nynke A, Gústafsson, Ómar, Haavik, Jan, Haberg, Asta K, Hall, Jeremy, Hashimoto, Ryota, Hehir-Kwa, Jayne Y, Hibar, Derrek P, Hillegers, Manon HJ, Hoffmann, Per, Holleran, Laurena, Holmes, Avram J, Homuth, Georg, Hottenga, Jouke-Jan, Hulshoff Pol, Hilleke E, Ikeda, Masashi, Jahanshad, Neda, Jockwitz, Christiane, Johansson, Stefan, Jönsson, Erik G, Jørgensen, Niklas R, Kikuchi, Masataka, Knowles, Emma EM, Kumar, Kuldeep, Le Hellard, Stephanie, Leu, Costin, Linden, David EJ, Liu, Jingyu, Lundervold, Arvid, Lundervold, Astri Johansen, Maillard, Anne M, Martin, Nicholas G, Martin-Brevet, Sandra, Mather, Karen A, Mathias, Samuel R, McMahon, Katie L, McRae, Allan F, Medland, Sarah E, Meyer-Lindenberg, Andreas, Moberget, Torgeir, Modenato, Claudia, Sánchez, Jennifer Monereo, Morris, Derek W, Mühleisen, Thomas W, Murray, Robin M, Nielsen, Jacob, Nordvik, Jan E, Nyberg, Lars, Loohuis, Loes M Olde, and Ophoff, Roel A

Subjects
Intellectual and Developmental Disabilities (IDD), Brain Disorders, Genetics, Neurosciences, Behavioral and Social Science, Mental Health, Autism, Schizophrenia, Neurological, Mental health, Brain, Chromosome Deletion, Cognition, DNA Copy Number Variations, Female, Humans, Male, ENIGMA-CNV working group, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Published
2021

17. Age-of-onset information helps identify 76 genetic variants associated with allergic disease.

Author

Ferreira, Manuel AR, Vonk, Judith M, Baurecht, Hansjörg, Marenholz, Ingo, Tian, Chao, Hoffman, Joshua D, Helmer, Quinta, Tillander, Annika, Ullemar, Vilhelmina, Lu, Yi, Grosche, Sarah, Rüschendorf, Franz, Granell, Raquel, Brumpton, Ben M, Fritsche, Lars G, Bhatta, Laxmi, Gabrielsen, Maiken E, Nielsen, Jonas B, Zhou, Wei, Hveem, Kristian, Langhammer, Arnulf, Holmen, Oddgeir L, Løset, Mari, Abecasis, Gonçalo R, Willer, Cristen J, Emami, Nima C, Cavazos, Taylor B, Witte, John S, Szwajda, Agnieszka, 23andMe Research Team, collaborators of the SHARE study, Hinds, David A, Hübner, Norbert, Weidinger, Stephan, Magnusson, Patrik Ke, Jorgenson, Eric, Karlsson, Robert, Paternoster, Lavinia, Boomsma, Dorret I, Almqvist, Catarina, Lee, Young-Ae, and Koppelman, Gerard H

Subjects
23andMe Research Team, collaborators of the SHARE study, Humans, Asthma, Eczema, Age of Onset, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Middle Aged, Child, Female, Rhinitis, Allergic, Seasonal, Male, Genome-Wide Association Study, Genetic Loci, Polymorphism, Single Nucleotide, Rhinitis, Allergic, Seasonal, Developmental Biology, Genetics
Abstract

Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P

Published
2020

18. Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia

Author

Sønderby, Ida E, Gústafsson, Ómar, Doan, Nhat Trung, Hibar, Derrek P, Martin-Brevet, Sandra, Abdellaoui, Abdel, Ames, David, Amunts, Katrin, Andersson, Michael, Armstrong, Nicola J, Bernard, Manon, Blackburn, Nicholas, Blangero, John, Boomsma, Dorret I, Bralten, Janita, Brattbak, Hans-Richard, Brodaty, Henry, Brouwer, Rachel M, Bülow, Robin, Calhoun, Vince, Caspers, Svenja, Cavalleri, Gianpiero, Chen, Chi-Hua, Cichon, Sven, Ciufolini, Simone, Corvin, Aiden, Crespo-Facorro, Benedicto, Curran, Joanne E, Dale, Anders M, Dalvie, Shareefa, Dazzan, Paola, de Geus, Eco JC, de Zubicaray, Greig I, de Zwarte, Sonja MC, Delanty, Norman, den Braber, Anouk, Desrivières, Sylvane, Donohoe, Gary, Draganski, Bogdan, Ehrlich, Stefan, Espeseth, Thomas, Fisher, Simon E, Franke, Barbara, Frouin, Vincent, Fukunaga, Masaki, Gareau, Thomas, Glahn, David C, Grabe, Hans, Groenewold, Nynke A, Haavik, Jan, Håberg, Asta, Hashimoto, Ryota, Hehir-Kwa, Jayne Y, Heinz, Andreas, Hillegers, Manon HJ, Hoffmann, Per, Holleran, Laurena, Hottenga, Jouke-Jan, Hulshoff, Hilleke E, Ikeda, Masashi, Jahanshad, Neda, Jernigan, Terry, Jockwitz, Christiane, Johansson, Stefan, Jonsdottir, Gudrun A, Jönsson, Erik G, Kahn, Rene, Kaufmann, Tobias, Kelly, Sinead, Kikuchi, Masataka, Knowles, Emma EM, Kolskår, Knut K, Kwok, John B, Hellard, Stephanie Le, Leu, Costin, Liu, Jingyu, Lundervold, Astri J, Lundervold, Arvid, Martin, Nicholas G, Mather, Karen, Mathias, Samuel R, McCormack, Mark, McMahon, Katie L, McRae, Allan, Milaneschi, Yuri, Moreau, Clara, Morris, Derek, Mothersill, David, Mühleisen, Thomas W, Murray, Robin, Nordvik, Jan E, Nyberg, Lars, Olde Loohuis, Loes M, Ophoff, Roel, Paus, Tomas, Pausova, Zdenka, Penninx, Brenda, Peralta, Juan M, Pike, Bruce, and Prieto, Carlos

Subjects
Intellectual and Developmental Disabilities (IDD), Neurosciences, Brain Disorders, Autism, Biomedical Imaging, Mental Health, Mental health, Adult, Autism Spectrum Disorder, Autistic Disorder, Basal Ganglia, Brain, Chromosome Deletion, Chromosome Disorders, Chromosome Duplication, Chromosomes, Human, Pair 16, DNA Copy Number Variations, Databases, Factual, Female, Globus Pallidus, Humans, Image Processing, Computer-Assisted, Intellectual Disability, Magnetic Resonance Imaging, Male, Middle Aged, Neurodevelopmental Disorders, Organ Size, Putamen, Schizophrenia, 16p11.2 European Consortium, for the ENIGMA-CNV working group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P

Published
2020

19. Genetic and environmental influences on human height from infancy through adulthood at different levels of parental education

Author

Jelenkovic, Aline, Sund, Reijo, Yokoyama, Yoshie, Latvala, Antti, Sugawara, Masumi, Tanaka, Mami, Matsumoto, Satoko, Freitas, Duarte L, Maia, José Antonio, Knafo-Noam, Ariel, Mankuta, David, Abramson, Lior, Ji, Fuling, Ning, Feng, Pang, Zengchang, Rebato, Esther, Saudino, Kimberly J, Cutler, Tessa L, Hopper, John L, Ullemar, Vilhelmina, Almqvist, Catarina, Magnusson, Patrik KE, Cozen, Wendy, Hwang, Amie E, Mack, Thomas M, Nelson, Tracy L, Whitfield, Keith E, Sung, Joohon, Kim, Jina, Lee, Jooyeon, Lee, Sooji, Llewellyn, Clare H, Fisher, Abigail, Medda, Emanuela, Nisticò, Lorenza, Toccaceli, Virgilia, Baker, Laura A, Tuvblad, Catherine, Corley, Robin P, Huibregtse, Brooke M, Derom, Catherine A, Vlietinck, Robert F, Loos, Ruth JF, Burt, S Alexandra, Klump, Kelly L, Silberg, Judy L, Maes, Hermine H, Krueger, Robert F, McGue, Matt, Pahlen, Shandell, Gatz, Margaret, Butler, David A, Harris, Jennifer R, Brandt, Ingunn, Nilsen, Thomas S, Harden, K Paige, Tucker-Drob, Elliot M, Franz, Carol E, Kremen, William S, Lyons, Michael J, Lichtenstein, Paul, Bartels, Meike, Beijsterveldt, Catharina EM van, Willemsen, Gonneke, Öncel, Sevgi Y, Aliev, Fazil, Jeong, Hoe-Uk, Hur, Yoon-Mi, Turkheimer, Eric, Boomsma, Dorret I, Sørensen, Thorkild IA, Kaprio, Jaakko, and Silventoinen, Karri

Subjects
Biological Psychology, Health Sciences, Psychology, Pediatric, Nutrition, Genetics, Prevention, 2.1 Biological and endogenous factors, Aetiology, Quality Education, Adolescent, Adult, Body Height, Child, Child, Preschool, Environment, Female, Gene-Environment Interaction, Genetic Background, Humans, Infant, Infant, Newborn, Male, Parenting, Parents, Quantitative Trait Loci, Quantitative Trait, Heritable, Young Adult
Abstract

Genetic factors explain a major proportion of human height variation, but differences in mean stature have also been found between socio-economic categories suggesting a possible effect of environment. By utilizing a classical twin design which allows decomposing the variation of height into genetic and environmental components, we tested the hypothesis that environmental variation in height is greater in offspring of lower educated parents. Twin data from 29 cohorts including 65,978 complete twin pairs with information on height at ages 1 to 69 years and on parental education were pooled allowing the analyses at different ages and in three geographic-cultural regions (Europe, North America and Australia, and East Asia). Parental education mostly showed a positive association with offspring height, with significant associations in mid-childhood and from adolescence onwards. In variance decomposition modeling, the genetic and environmental variance components of height did not show a consistent relation to parental education. A random-effects meta-regression analysis of the aggregate-level data showed a trend towards greater shared environmental variation of height in low parental education families. In conclusion, in our very large dataset from twin cohorts around the globe, these results provide only weak evidence for the study hypothesis.

Published
2020

20. Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness

Author

Abdellaoui, Abdel, Sanchez-Roige, Sandra, Sealock, Julia, Treur, Jorien L, Dennis, Jessica, Fontanillas, Pierre, Elson, Sarah, Team, The 23andme Research, Nivard, Michel G, Ip, Hill Fung, van der Zee, Matthijs, Baselmans, Bart ML, Hottenga, Jouke Jan, Willemsen, Gonneke, Mosing, Miriam, Lu, Yi, Pedersen, Nancy L, Denys, Damiaan, Amin, Najaf, van Duijn, Cornelia M, Szilagyi, Ingrid, Tiemeier, Henning, Neumann, Alexander, Verweij, Karin JH, Cacioppo, Stephanie, Cacioppo, John T, Davis, Lea K, Palmer, Abraham A, and Boomsma, Dorret I

Subjects
Biological Sciences, Genetics, Obesity, Human Genome, Mental Health, Prevention, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Cardiovascular, Mental health, Good Health and Well Being, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Health, Humans, Loneliness, Male, Mendelian Randomization Analysis, Mental Disorders, Multifactorial Inheritance, Phenomics, Phenotype, Polymorphism, Single Nucleotide, 23andme Research Team, Medical and Health Sciences, Genetics & Heredity
Abstract

Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. Although the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. Although it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition toward loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we extended the genome-wide association study meta-analysis of loneliness to 511 280 subjects, and detect 19 significant genetic variants from 16 loci, including four novel loci, as well as 58 significantly associated genes. We investigated the genetic overlap with a wide range of physical and mental health traits by computing genetic correlations and by building loneliness polygenic scores in an independent sample of 18 498 individuals with EHR data to conduct a PheWAS with. A genetic predisposition toward loneliness was associated with cardiovascular, psychiatric, and metabolic disorders and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, the effect of both BMI and body fat on loneliness. Our results provide a framework for future studies of the genetic basis of loneliness and its relationship to mental and physical health.

Published
2019

21. Genetic architecture of subcortical brain structures in 38,851 individuals

Author

Satizabal, Claudia L, Adams, Hieab HH, Hibar, Derrek P, White, Charles C, Knol, Maria J, Stein, Jason L, Scholz, Markus, Sargurupremraj, Muralidharan, Jahanshad, Neda, Roshchupkin, Gennady V, Smith, Albert V, Bis, Joshua C, Jian, Xueqiu, Luciano, Michelle, Hofer, Edith, Teumer, Alexander, van der Lee, Sven J, Yang, Jingyun, Yanek, Lisa R, Lee, Tom V, Li, Shuo, Hu, Yanhui, Koh, Jia Yu, Eicher, John D, Desrivières, Sylvane, Arias-Vasquez, Alejandro, Chauhan, Ganesh, Athanasiu, Lavinia, Rentería, Miguel E, Kim, Sungeun, Hoehn, David, Armstrong, Nicola J, Chen, Qiang, Holmes, Avram J, den Braber, Anouk, Kloszewska, Iwona, Andersson, Micael, Espeseth, Thomas, Grimm, Oliver, Abramovic, Lucija, Alhusaini, Saud, Milaneschi, Yuri, Papmeyer, Martina, Axelsson, Tomas, Ehrlich, Stefan, Roiz-Santiañez, Roberto, Kraemer, Bernd, Håberg, Asta K, Jones, Hannah J, Pike, G Bruce, Stein, Dan J, Stevens, Allison, Bralten, Janita, Vernooij, Meike W, Harris, Tamara B, Filippi, Irina, Witte, A Veronica, Guadalupe, Tulio, Wittfeld, Katharina, Mosley, Thomas H, Becker, James T, Doan, Nhat Trung, Hagenaars, Saskia P, Saba, Yasaman, Cuellar-Partida, Gabriel, Amin, Najaf, Hilal, Saima, Nho, Kwangsik, Mirza-Schreiber, Nazanin, Arfanakis, Konstantinos, Becker, Diane M, Ames, David, Goldman, Aaron L, Lee, Phil H, Boomsma, Dorret I, Lovestone, Simon, Giddaluru, Sudheer, Le Hellard, Stephanie, Mattheisen, Manuel, Bohlken, Marc M, Kasperaviciute, Dalia, Schmaal, Lianne, Lawrie, Stephen M, Agartz, Ingrid, Walton, Esther, Tordesillas-Gutierrez, Diana, Davies, Gareth E, Shin, Jean, Ipser, Jonathan C, Vinke, Louis N, Hoogman, Martine, Jia, Tianye, Burkhardt, Ralph, Klein, Marieke, Crivello, Fabrice, Janowitz, Deborah, Carmichael, Owen, Haukvik, Unn K, Aribisala, Benjamin S, and Schmidt, Helena

Subjects
Biological Sciences, Genetics, Neurosciences, Biotechnology, Mental Health, Human Genome, Brain Disorders, Aetiology, 2.1 Biological and endogenous factors, Neurological, Adult, Aged, Animals, Brain, Cohort Studies, Drosophila melanogaster, Genetic Variation, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Middle Aged, Neurodevelopmental Disorders, Organ Size, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

Published
2019

22. Meta-analysis of epigenome-wide association studies in neonates reveals widespread differential DNA methylation associated with birthweight.

Author

Küpers, Leanne K, Monnereau, Claire, Sharp, Gemma C, Yousefi, Paul, Salas, Lucas A, Ghantous, Akram, Page, Christian M, Reese, Sarah E, Wilcox, Allen J, Czamara, Darina, Starling, Anne P, Novoloaca, Alexei, Lent, Samantha, Roy, Ritu, Hoyo, Cathrine, Breton, Carrie V, Allard, Catherine, Just, Allan C, Bakulski, Kelly M, Holloway, John W, Everson, Todd M, Xu, Cheng-Jian, Huang, Rae-Chi, van der Plaat, Diana A, Wielscher, Matthias, Merid, Simon Kebede, Ullemar, Vilhelmina, Rezwan, Faisal I, Lahti, Jari, van Dongen, Jenny, Langie, Sabine AS, Richardson, Tom G, Magnus, Maria C, Nohr, Ellen A, Xu, Zongli, Duijts, Liesbeth, Zhao, Shanshan, Zhang, Weiming, Plusquin, Michelle, DeMeo, Dawn L, Solomon, Olivia, Heimovaara, Joosje H, Jima, Dereje D, Gao, Lu, Bustamante, Mariona, Perron, Patrice, Wright, Robert O, Hertz-Picciotto, Irva, Zhang, Hongmei, Karagas, Margaret R, Gehring, Ulrike, Marsit, Carmen J, Beilin, Lawrence J, Vonk, Judith M, Jarvelin, Marjo-Riitta, Bergström, Anna, Örtqvist, Anne K, Ewart, Susan, Villa, Pia M, Moore, Sophie E, Willemsen, Gonneke, Standaert, Arnout RL, Håberg, Siri E, Sørensen, Thorkild IA, Taylor, Jack A, Räikkönen, Katri, Yang, Ivana V, Kechris, Katerina, Nawrot, Tim S, Silver, Matt J, Gong, Yun Yun, Richiardi, Lorenzo, Kogevinas, Manolis, Litonjua, Augusto A, Eskenazi, Brenda, Huen, Karen, Mbarek, Hamdi, Maguire, Rachel L, Dwyer, Terence, Vrijheid, Martine, Bouchard, Luigi, Baccarelli, Andrea A, Croen, Lisa A, Karmaus, Wilfried, Anderson, Denise, de Vries, Maaike, Sebert, Sylvain, Kere, Juha, Karlsson, Robert, Arshad, Syed Hasan, Hämäläinen, Esa, Routledge, Michael N, Boomsma, Dorret I, Feinberg, Andrew P, Newschaffer, Craig J, Govarts, Eva, Moisse, Matthieu, Fallin, M Daniele, Melén, Erik, and Prentice, Andrew M

Subjects
Fetus, Humans, Prenatal Exposure Delayed Effects, Birth Weight, Folic Acid, DNA, Body Mass Index, Smoking, DNA Methylation, Epigenesis, Genetic, CpG Islands, Fetal Development, Pregnancy, Genome, Human, Adolescent, Adult, Child, Infant, Newborn, Female, Male, Genome-Wide Association Study, Epigenesis, Genetic, Genome, Human, Infant, Newborn
Abstract

Birthweight is associated with health outcomes across the life course, DNA methylation may be an underlying mechanism. In this meta-analysis of epigenome-wide association studies of 8,825 neonates from 24 birth cohorts in the Pregnancy And Childhood Epigenetics Consortium, we find that DNA methylation in neonatal blood is associated with birthweight at 914 sites, with a difference in birthweight ranging from -183 to 178 grams per 10% increase in methylation (PBonferroni

Published
2019

23. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use

Author

Liu, Mengzhen, Jiang, Yu, Wedow, Robbee, Li, Yue, Brazel, David M, Chen, Fang, Datta, Gargi, Davila-Velderrain, Jose, McGuire, Daniel, Tian, Chao, Zhan, Xiaowei, Choquet, Hélène, Docherty, Anna R, Faul, Jessica D, Foerster, Johanna R, Fritsche, Lars G, Gabrielsen, Maiken Elvestad, Gordon, Scott D, Haessler, Jeffrey, Hottenga, Jouke-Jan, Huang, Hongyan, Jang, Seon-Kyeong, Jansen, Philip R, Ling, Yueh, Mägi, Reedik, Matoba, Nana, McMahon, George, Mulas, Antonella, Orrù, Valeria, Palviainen, Teemu, Pandit, Anita, Reginsson, Gunnar W, Skogholt, Anne Heidi, Smith, Jennifer A, Taylor, Amy E, Turman, Constance, Willemsen, Gonneke, Young, Hannah, Young, Kendra A, Zajac, Gregory JM, Zhao, Wei, Zhou, Wei, Bjornsdottir, Gyda, Boardman, Jason D, Boehnke, Michael, Boomsma, Dorret I, Chen, Chu, Cucca, Francesco, Davies, Gareth E, Eaton, Charles B, Ehringer, Marissa A, Esko, Tõnu, Fiorillo, Edoardo, Gillespie, Nathan A, Gudbjartsson, Daniel F, Haller, Toomas, Harris, Kathleen Mullan, Heath, Andrew C, Hewitt, John K, Hickie, Ian B, Hokanson, John E, Hopfer, Christian J, Hunter, David J, Iacono, William G, Johnson, Eric O, Kamatani, Yoichiro, Kardia, Sharon LR, Keller, Matthew C, Kellis, Manolis, Kooperberg, Charles, Kraft, Peter, Krauter, Kenneth S, Laakso, Markku, Lind, Penelope A, Loukola, Anu, Lutz, Sharon M, Madden, Pamela AF, Martin, Nicholas G, McGue, Matt, McQueen, Matthew B, Medland, Sarah E, Metspalu, Andres, Mohlke, Karen L, Nielsen, Jonas B, Okada, Yukinori, Peters, Ulrike, Polderman, Tinca JC, Posthuma, Danielle, Reiner, Alexander P, Rice, John P, Rimm, Eric, Rose, Richard J, Runarsdottir, Valgerdur, Stallings, Michael C, Stančáková, Alena, Stefansson, Hreinn, Thai, Khanh K, Tindle, Hilary A, Tyrfingsson, Thorarinn, and Wall, Tamara L

Subjects
Substance Misuse, Human Genome, Brain Disorders, Tobacco, Tobacco Smoke and Health, Genetics, Alcoholism, Alcohol Use and Health, Prevention, Aetiology, 2.1 Biological and endogenous factors, Stroke, Cancer, Cardiovascular, Good Health and Well Being, Alcohol Drinking, Female, Genetic Variation, Genome-Wide Association Study, Humans, Male, Middle Aged, Phenotype, Risk, Smoking, Tobacco Use Disorder, 23andMe Research Team, HUNT All-In Psychiatry, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures.

Published
2019

24. An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasis

Author

Liu, Jun, Carnero-Montoro, Elena, van Dongen, Jenny, Lent, Samantha, Nedeljkovic, Ivana, Ligthart, Symen, Tsai, Pei-Chien, Martin, Tiphaine C, Mandaviya, Pooja R, Jansen, Rick, Peters, Marjolein J, Duijts, Liesbeth, Jaddoe, Vincent WV, Tiemeier, Henning, Felix, Janine F, Willemsen, Gonneke, de Geus, Eco JC, Chu, Audrey Y, Levy, Daniel, Hwang, Shih-Jen, Bressler, Jan, Gondalia, Rahul, Salfati, Elias L, Herder, Christian, Hidalgo, Bertha A, Tanaka, Toshiko, Moore, Ann Zenobia, Lemaitre, Rozenn N, Jhun, Min A, Smith, Jennifer A, Sotoodehnia, Nona, Bandinelli, Stefania, Ferrucci, Luigi, Arnett, Donna K, Grallert, Harald, Assimes, Themistocles L, Hou, Lifang, Baccarelli, Andrea, Whitsel, Eric A, van Dijk, Ko Willems, Amin, Najaf, Uitterlinden, André G, Sijbrands, Eric JG, Franco, Oscar H, Dehghan, Abbas, Spector, Tim D, Dupuis, Josée, Hivert, Marie-France, Rotter, Jerome I, Meigs, James B, Pankow, James S, van Meurs, Joyce BJ, Isaacs, Aaron, Boomsma, Dorret I, Bell, Jordana T, Demirkan, Ayşe, and van Duijn, Cornelia M

Subjects
Biological Sciences, Genetics, Nutrition, Diabetes, Human Genome, Obesity, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Adult, Aged, Aged, 80 and over, Computer Simulation, CpG Islands, DNA Methylation, Diabetes Mellitus, Type 2, Epigenesis, Genetic, Epigenomics, Female, Gene Expression Profiling, Gene Expression Regulation, Genome-Wide Association Study, Glucose, Homeostasis, Humans, Insulin, Male, Metabolic Networks and Pathways, Middle Aged, Polymorphism, Single Nucleotide, Young Adult
Abstract

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D.

Published
2019

25. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder.

Author

Demontis, Ditte, Walters, Raymond K, Martin, Joanna, Mattheisen, Manuel, Als, Thomas D, Agerbo, Esben, Baldursson, Gísli, Belliveau, Rich, Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Cerrato, Felecia, Chambert, Kimberly, Churchhouse, Claire, Dumont, Ashley, Eriksson, Nicholas, Gandal, Michael, Goldstein, Jacqueline I, Grasby, Katrina L, Grove, Jakob, Gudmundsson, Olafur O, Hansen, Christine S, Hauberg, Mads Engel, Hollegaard, Mads V, Howrigan, Daniel P, Huang, Hailiang, Maller, Julian B, Martin, Alicia R, Martin, Nicholas G, Moran, Jennifer, Pallesen, Jonatan, Palmer, Duncan S, Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Poterba, Timothy, Poulsen, Jesper Buchhave, Ripke, Stephan, Robinson, Elise B, Satterstrom, F Kyle, Stefansson, Hreinn, Stevens, Christine, Turley, Patrick, Walters, G Bragi, Won, Hyejung, Wright, Margaret J, ADHD Working Group of the Psychiatric Genomics Consortium (PGC), Early Lifecourse & Genetic Epidemiology (EAGLE) Consortium, 23andMe Research Team, Andreassen, Ole A, Asherson, Philip, Burton, Christie L, Boomsma, Dorret I, Cormand, Bru, Dalsgaard, Søren, Franke, Barbara, Gelernter, Joel, Geschwind, Daniel, Hakonarson, Hakon, Haavik, Jan, Kranzler, Henry R, Kuntsi, Jonna, Langley, Kate, Lesch, Klaus-Peter, Middeldorp, Christel, Reif, Andreas, Rohde, Luis Augusto, Roussos, Panos, Schachar, Russell, Sklar, Pamela, Sonuga-Barke, Edmund JS, Sullivan, Patrick F, Thapar, Anita, Tung, Joyce Y, Waldman, Irwin D, Medland, Sarah E, Stefansson, Kari, Nordentoft, Merete, Hougaard, David M, Werge, Thomas, Mors, Ole, Mortensen, Preben Bo, Daly, Mark J, Faraone, Stephen V, Børglum, Anders D, and Neale, Benjamin M

Subjects
ADHD Working Group of the Psychiatric Genomics Consortium, Early Lifecourse & Genetic Epidemiology (EAGLE) Consortium, 23andMe Research Team, Brain, Humans, Genetic Predisposition to Disease, Risk, Cohort Studies, Attention Deficit Disorder with Hyperactivity, Gene Expression Regulation, Polymorphism, Single Nucleotide, Adolescent, Child, Child, Preschool, Female, Male, Genome-Wide Association Study, Genetic Loci, Clinical Research, Mental Health, Human Genome, Pediatric, Prevention, Genetics, Brain Disorders, Attention Deficit Hyperactivity Disorder (ADHD), Behavioral and Social Science, Aetiology, 2.1 Biological and endogenous factors, Mental health, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.

Published
2019

26. Genome‐wide association meta‐analysis of age at first cannabis use

Author

Minică, Camelia C, Verweij, Karin JH, van der Most, Peter J, Mbarek, Hamdi, Bernard, Manon, van Eijk, Kristel R, Lind, Penelope A, Liu, Meng Zhen, Maciejewski, Dominique F, Palviainen, Teemu, Sánchez‐Mora, Cristina, Sherva, Richard, Taylor, Michelle, Walters, Raymond K, Abdellaoui, Abdel, Bigdeli, Timothy B, Branje, Susan JT, Brown, Sandra A, Casas, Miguel, Corley, Robin P, Davey‐Smith, George, Davies, Gareth E, Ehli, Erik A, Farrer, Lindsay, Fedko, Iryna O, Garcia‐Martínez, Iris, Gordon, Scott D, Hartman, Catharina A, Heath, Andrew C, Hickie, Ian B, Hickman, Matthew, Hopfer, Christian J, Hottenga, Jouke Jan, Kahn, René S, Kaprio, Jaakko, Korhonen, Tellervo, Kranzler, Henry R, Krauter, Ken, van Lier, Pol AC, Madden, Pamela AF, Medland, Sarah E, Neale, Michael C, Meeus, Wim HJ, Montgomery, Grant W, Nolte, Ilja M, Oldehinkel, Albertine J, Pausova, Zdenka, Ramos‐Quiroga, Josep A, Richarte, Vanesa, Rose, Richard J, Shin, Jean, Stallings, Michael C, Wall, Tamara L, Ware, Jennifer J, Wright, Margaret J, Zhao, Hongyu, Koot, Hans M, Paus, Tomas, Hewitt, John K, Ribasés, Marta, Loukola, Anu, Boks, Marco P, Snieder, Harold, Munafò, Marcus R, Gelernter, Joel, Boomsma, Dorret I, Martin, Nicholas G, Gillespie, Nathan A, Vink, Jacqueline M, and Derks, Eske M

Subjects
Biological Psychology, Epidemiology, Health Sciences, Psychology, Biotechnology, Brain Disorders, Substance Misuse, Genetics, Human Genome, Drug Abuse (NIDA only), Prevention, 2.1 Biological and endogenous factors, Aetiology, Mental health, Good Health and Well Being, Adolescent, Adult, Age of Onset, Calcium-Transporting ATPases, Female, Genome-Wide Association Study, Humans, Male, Marijuana Use, Middle Aged, Polymorphism, Single Nucleotide, Twins, Young Adult, Age at first use, ATP2C2, cannabis initiation, genome-wide association, heritability, substance use, Medical and Health Sciences, Psychology and Cognitive Sciences, Substance Abuse, Public health, Clinical and health psychology
Abstract

Background and aimsCannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes, including multi-substance use and dependence. This study estimated the heritability of age at first cannabis use and identified associations with genetic variants.MethodsA twin-based heritability analysis using 8055 twins from three cohorts was performed. We then carried out a genome-wide association meta-analysis of age at first cannabis use in a discovery sample of 24 953 individuals from nine European, North American and Australian cohorts, and a replication sample of 3735 individuals.ResultsThe twin-based heritability for age at first cannabis use was 38% [95% confidence interval (CI) = 19-60%]. Shared and unique environmental factors explained 39% (95% CI = 20-56%) and 22% (95% CI = 16-29%). The genome-wide association meta-analysis identified five single nucleotide polymorphisms (SNPs) on chromosome 16 within the calcium-transporting ATPase gene (ATP2C2) at P  0.8), with the strongest association at the intronic variant rs1574587 (P = 4.09E-09). Gene-based tests of association identified the ATP2C2 gene on 16q24.1 (P = 1.33e-06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been associated previously with opioid dependence. SNP-based heritability for age at first cannabis use was non-significant.ConclusionAge at cannabis initiation appears to be moderately heritable in western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.

Published
2018

27. GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability

Author

Pasman, Joëlle A, Verweij, Karin JH, Gerring, Zachary, Stringer, Sven, Sanchez-Roige, Sandra, Treur, Jorien L, Abdellaoui, Abdel, Nivard, Michel G, Baselmans, Bart ML, Ong, Jue-Sheng, Ip, Hill F, van der Zee, Matthijs D, Bartels, Meike, Day, Felix R, Fontanillas, Pierre, Elson, Sarah L, the 23andMe Research Team, de Wit, Harriet, Davis, Lea K, MacKillop, James, The Substance Use Disorders Working Group of the Psychiatric Genomics Consortium, International Cannabis Consortium, Derringer, Jaime L, Branje, Susan JT, Hartman, Catharina A, Heath, Andrew C, van Lier, Pol AC, Madden, Pamela AF, Mägi, Reedik, Meeus, Wim, Montgomery, Grant W, Oldehinkel, AJ, Pausova, Zdenka, Ramos-Quiroga, Josep A, Paus, Tomas, Ribases, Marta, Kaprio, Jaakko, Boks, Marco PM, Bell, Jordana T, Spector, Tim D, Gelernter, Joel, Boomsma, Dorret I, Martin, Nicholas G, MacGregor, Stuart, Perry, John RB, Palmer, Abraham A, Posthuma, Danielle, Munafò, Marcus R, Gillespie, Nathan A, Derks, Eske M, and Vink, Jacqueline M

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Prevention, Mental Health, Schizophrenia, Clinical Research, Behavioral and Social Science, Genetics, Mental Illness, Brain Disorders, Serious Mental Illness, Human Genome, Drug Abuse (NIDA only), Women's Health, Cannabinoid Research, Substance Misuse, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Adolescent, Adult, Aged, Aged, 80 and over, Cell Adhesion Molecules, Databases, Genetic, Female, Gene Expression Regulation, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Marijuana Abuse, Mendelian Randomization Analysis, Middle Aged, Polymorphism, Single Nucleotide, Risk-Taking, Young Adult, 23andMe Research Team, Substance Use Disorders Working Group of the Psychiatric Genomics Consortium, International Cannabis Consortium, Neurosciences, Cognitive Sciences, Neurology & Neurosurgery, Biological psychology
Abstract

Cannabis use is a heritable trait that has been associated with adverse mental health outcomes. In the largest genome-wide association study (GWAS) for lifetime cannabis use to date (N = 184,765), we identified eight genome-wide significant independent single nucleotide polymorphisms in six regions. All measured genetic variants combined explained 11% of the variance. Gene-based tests revealed 35 significant genes in 16 regions, and S-PrediXcan analyses showed that 21 genes had different expression levels for cannabis users versus nonusers. The strongest finding across the different analyses was CADM2, which has been associated with substance use and risk-taking. Significant genetic correlations were found with 14 of 25 tested substance use and mental health-related traits, including smoking, alcohol use, schizophrenia and risk-taking. Mendelian randomization analysis showed evidence for a causal positive influence of schizophrenia risk on cannabis use. Overall, our study provides new insights into the etiology of cannabis use and its relation with mental health.

Published
2018

28. GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal influence of schizophrenia.

Author

Pasman, Joëlle A, Verweij, Karin JH, Gerring, Zachary, Stringer, Sven, Sanchez-Roige, Sandra, Treur, Jorien L, Abdellaoui, Abdel, Nivard, Michel G, Baselmans, Bart ML, Ong, Jue-Sheng, Ip, Hill F, van der Zee, Matthijs D, Bartels, Meike, Day, Felix R, Fontanillas, Pierre, Elson, Sarah L, 23andMe Research Team, de Wit, Harriet, Davis, Lea K, MacKillop, James, Substance Use Disorders Working Group of the Psychiatric Genomics Consortium, International Cannabis Consortium, Derringer, Jaime L, Branje, Susan JT, Hartman, Catharina A, Heath, Andrew C, van Lier, Pol AC, Madden, Pamela AF, Mägi, Reedik, Meeus, Wim, Montgomery, Grant W, Oldehinkel, AJ, Pausova, Zdenka, Ramos-Quiroga, Josep A, Paus, Tomas, Ribases, Marta, Kaprio, Jaakko, Boks, Marco PM, Bell, Jordana T, Spector, Tim D, Gelernter, Joel, Boomsma, Dorret I, Martin, Nicholas G, MacGregor, Stuart, Perry, John RB, Palmer, Abraham A, Posthuma, Danielle, Munafò, Marcus R, Gillespie, Nathan A, Derks, Eske M, and Vink, Jacqueline M

Subjects
23andMe Research Team, Substance Use Disorders Working Group of the Psychiatric Genomics Consortium, International Cannabis Consortium, Humans, Marijuana Abuse, Genetic Predisposition to Disease, Cell Adhesion Molecules, Risk-Taking, Mental Health, Schizophrenia, Gene Expression Regulation, Genotype, Polymorphism, Single Nucleotide, Databases, Genetic, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Genome-Wide Association Study, Young Adult, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, Databases, Genetic, and over, Prevention, Human Genome, Brain Disorders, Drug Abuse, Substance Abuse, Genetics, Clinical Research, 2.1 Biological and endogenous factors, Cardiovascular, Neurology & Neurosurgery, Neurosciences, Cognitive Sciences, Psychology
Abstract

Cannabis use is a heritable trait that has been associated with adverse mental health outcomes. In the largest genome-wide association study (GWAS) for lifetime cannabis use to date (N = 184,765), we identified eight genome-wide significant independent single nucleotide polymorphisms in six regions. All measured genetic variants combined explained 11% of the variance. Gene-based tests revealed 35 significant genes in 16 regions, and S-PrediXcan analyses showed that 21 genes had different expression levels for cannabis users versus nonusers. The strongest finding across the different analyses was CADM2, which has been associated with substance use and risk-taking. Significant genetic correlations were found with 14 of 25 tested substance use and mental health-related traits, including smoking, alcohol use, schizophrenia and risk-taking. Mendelian randomization analysis showed evidence for a causal positive influence of schizophrenia risk on cannabis use. Overall, our study provides new insights into the etiology of cannabis use and its relation with mental health.

Published
2018

29. Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

Author

Waage, Johannes, Standl, Marie, Curtin, John A, Jessen, Leon E, Thorsen, Jonathan, Tian, Chao, Schoettler, Nathan, The 23andMe Research Team, AAGC collaborators, Flores, Carlos, Abdellaoui, Abdel, Ahluwalia, Tarunveer S, Alves, Alexessander C, Amaral, Andre FS, Antó, Josep M, Arnold, Andreas, Barreto-Luis, Amalia, Baurecht, Hansjörg, van Beijsterveldt, Catharina EM, Bleecker, Eugene R, Bonàs-Guarch, Sílvia, Boomsma, Dorret I, Brix, Susanne, Bunyavanich, Supinda, Burchard, Esteban G, Chen, Zhanghua, Curjuric, Ivan, Custovic, Adnan, den Dekker, Herman T, Dharmage, Shyamali C, Dmitrieva, Julia, Duijts, Liesbeth, Ege, Markus J, Gauderman, W James, Georges, Michel, Gieger, Christian, Gilliland, Frank, Granell, Raquel, Gui, Hongsheng, Hansen, Torben, Heinrich, Joachim, Henderson, John, Hernandez-Pacheco, Natalia, Holt, Patrick, Imboden, Medea, Jaddoe, Vincent WV, Jarvelin, Marjo-Riitta, Jarvis, Deborah L, Jensen, Kamilla K, Jónsdóttir, Ingileif, Kabesch, Michael, Kaprio, Jaakko, Kumar, Ashish, Lee, Young-Ae, Levin, Albert M, Li, Xingnan, Lorenzo-Diaz, Fabian, Melén, Erik, Mercader, Josep M, Meyers, Deborah A, Myers, Rachel, Nicolae, Dan L, Nohr, Ellen A, Palviainen, Teemu, Paternoster, Lavinia, Pennell, Craig E, Pershagen, Göran, Pino-Yanes, Maria, Probst-Hensch, Nicole M, Rüschendorf, Franz, Simpson, Angela, Stefansson, Kari, Sunyer, Jordi, Sveinbjornsson, Gardar, Thiering, Elisabeth, Thompson, Philip J, Torrent, Maties, Torrents, David, Tung, Joyce Y, Wang, Carol A, Weidinger, Stephan, Weiss, Scott, Willemsen, Gonneke, Williams, L Keoki, Ober, Carole, Hinds, David A, Ferreira, Manuel A, Bisgaard, Hans, Strachan, David P, and Bønnelykke, Klaus

Subjects
Biological Sciences, Genetics, Human Genome, Allergic Rhinitis (Hay Fever), Prevention, Biotechnology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Allergens, Case-Control Studies, Genetic Loci, Genetic Predisposition to Disease, Genetic Variation, Genome, Human, Genome-Wide Association Study, HLA Antigens, Humans, Phenotype, Rhinitis, Allergic, Risk, 23andMe Research Team, AAGC collaborators, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Allergic rhinitis is the most common clinical presentation of allergy, affecting 400 million people worldwide, with increasing incidence in westernized countries1,2. To elucidate the genetic architecture and understand the underlying disease mechanisms, we carried out a meta-analysis of allergic rhinitis in 59,762 cases and 152,358 controls of European ancestry and identified a total of 41 risk loci for allergic rhinitis, including 20 loci not previously associated with allergic rhinitis, which were confirmed in a replication phase of 60,720 cases and 618,527 controls. Functional annotation implicated genes involved in various immune pathways, and fine mapping of the HLA region suggested amino acid variants important for antigen binding. We further performed genome-wide association study (GWAS) analyses of allergic sensitization against inhalant allergens and nonallergic rhinitis, which suggested shared genetic mechanisms across rhinitis-related traits. Future studies of the identified loci and genes might identify novel targets for treatment and prevention of allergic rhinitis.

Published
2018

30. Shared genetic origin of asthma, hay fever and eczema elucidates allergic disease biology

Author

Ferreira, Manuel A, Vonk, Judith M, Baurecht, Hansjörg, Marenholz, Ingo, Tian, Chao, Hoffman, Joshua D, Helmer, Quinta, Tillander, Annika, Ullemar, Vilhelmina, van Dongen, Jenny, Lu, Yi, Rüschendorf, Franz, Esparza-Gordillo, Jorge, Medway, Chris W, Mountjoy, Edward, Burrows, Kimberley, Hummel, Oliver, Grosche, Sarah, Brumpton, Ben M, Witte, John S, Hottenga, Jouke-Jan, Willemsen, Gonneke, Zheng, Jie, Rodríguez, Elke, Hotze, Melanie, Franke, Andre, Revez, Joana A, Beesley, Jonathan, Matheson, Melanie C, Dharmage, Shyamali C, Bain, Lisa M, Fritsche, Lars G, Gabrielsen, Maiken E, Balliu, Brunilda, Nielsen, Jonas B, Zhou, Wei, Hveem, Kristian, Langhammer, Arnulf, Holmen, Oddgeir L, Løset, Mari, Abecasis, Gonçalo R, Willer, Cristen J, Arnold, Andreas, Homuth, Georg, Schmidt, Carsten O, Thompson, Philip J, Martin, Nicholas G, Duffy, David L, Novak, Natalija, Schulz, Holger, Karrasch, Stefan, Gieger, Christian, Strauch, Konstantin, Melles, Ronald B, Hinds, David A, Hübner, Norbert, Weidinger, Stephan, Magnusson, Patrik KE, Jansen, Rick, Jorgenson, Eric, Lee, Young-Ae, Boomsma, Dorret I, Almqvist, Catarina, Karlsson, Robert, Koppelman, Gerard H, and Paternoster, Lavinia

Subjects
Biological Sciences, Genetics, Emerging Infectious Diseases, Lung, Prevention, Asthma, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Good Health and Well Being, Eczema, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hypersensitivity, Phenotype, Polymorphism, Single Nucleotide, Rhinitis, Allergic, Seasonal, Risk Factors, 23andMe Research Team, AAGC collaborators, BIOS consortium, LifeLines Cohort Study, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Asthma, hay fever (or allergic rhinitis) and eczema (or atopic dermatitis) often coexist in the same individuals, partly because of a shared genetic origin. To identify shared risk variants, we performed a genome-wide association study (GWAS; n = 360,838) of a broad allergic disease phenotype that considers the presence of any one of these three diseases. We identified 136 independent risk variants (P < 3 × 10-8), including 73 not previously reported, which implicate 132 nearby genes in allergic disease pathophysiology. Disease-specific effects were detected for only six variants, confirming that most represent shared risk factors. Tissue-specific heritability and biological process enrichment analyses suggest that shared risk variants influence lymphocyte-mediated immunity. Six target genes provide an opportunity for drug repositioning, while for 36 genes CpG methylation was found to influence transcription independently of genetic effects. Asthma, hay fever and eczema partly coexist because they share many genetic risk variants that dysregulate the expression of immune-related genes.

Published
2017

31. DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation

Author

Richard, Melissa A, Huan, Tianxiao, Ligthart, Symen, Gondalia, Rahul, Jhun, Min A, Brody, Jennifer A, Irvin, Marguerite R, Marioni, Riccardo, Shen, Jincheng, Tsai, Pei-Chien, Montasser, May E, Jia, Yucheng, Syme, Catriona, Salfati, Elias L, Boerwinkle, Eric, Guan, Weihua, Mosley, Thomas H, Bressler, Jan, Morrison, Alanna C, Liu, Chunyu, Mendelson, Michael M, Uitterlinden, André G, van Meurs, Joyce B, Consortium, BIOS, Heijmans, Bastiaan T, Hoen, Peter AC ’t, van Meurs, Joyce, Isaacs, Aaron, Jansen, Rick, Franke, Lude, Boomsma, Dorret I, Pool, René, van Dongen, Jenny, Hottenga, Jouke J, van Greevenbroek, Marleen MJ, Stehouwer, Coen DA, van der Kallen, Carla JH, Schalkwijk, Casper G, Wijmenga, Cisca, Zhernakova, Alexandra, Tigchelaar, Ettje F, Slagboom, P Eline, Beekman, Marian, Deelen, Joris, van Heemst, Diana, Veldink, Jan H, van den Berg, Leonard H, van Duijn, Cornelia M, Hofman, Albert, Jhamai, P Mila, Verbiest, Michael, Suchiman, H Eka D, Verkerk, Marijn, van der Breggen, Ruud, van Rooij, Jeroen, Lakenberg, Nico, Mei, Hailiang, van Iterson, Maarten, van Galen, Michiel, Bot, Jan, van ’t Hof, Peter, Deelen, Patrick, Nooren, Irene, Moed, Matthijs, Vermaat, Martijn, Zhernakova, Dasha V, Luijk, René, Bonder, Marc Jan, van Dijk, Freerk, Arindrarto, Wibowo, Kielbasa, Szymon M, Swertz, Morris A, van Zwet, Erik W, Franco, Oscar H, Zhang, Guosheng, Li, Yun, Stewart, James D, Bis, Joshua C, Psaty, Bruce M, Chen, Yii-Der Ida, Kardia, Sharon LR, Zhao, Wei, Turner, Stephen T, Absher, Devin, Aslibekyan, Stella, Starr, John M, McRae, Allan F, Hou, Lifang, Just, Allan C, Schwartz, Joel D, Vokonas, Pantel S, Menni, Cristina, Spector, Tim D, Shuldiner, Alan, Damcott, Coleen M, Rotter, Jerome I, Palmas, Walter, Liu, Yongmei, and Paus, Tomáš

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Aged, Blood Pressure, CpG Islands, Cross-Sectional Studies, DNA Methylation, Epigenesis, Genetic, Genetic Variation, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Middle Aged, Nerve Tissue Proteins, Quantitative Trait Loci, Tetraspanins, BIOS Consortium, DNA methylation, Mendelian randomization, blood pressure, epigenome-wide association study, gene expression, sequence variation, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0 × 10-7; replication: N = 7,182, p  30%) and independent of known BP genetic variants, explaining an additional 1.4% and 2.0% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.

Published
2017

32. Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study

Author

de Vries, Paul S, Sabater-Lleal, Maria, Chasman, Daniel I, Trompet, Stella, Ahluwalia, Tarunveer S, Teumer, Alexander, Kleber, Marcus E, Chen, Ming-Huei, Wang, Jie Jin, Attia, John R, Marioni, Riccardo E, Steri, Maristella, Weng, Lu-Chen, Pool, Rene, Grossmann, Vera, Brody, Jennifer A, Venturini, Cristina, Tanaka, Toshiko, Rose, Lynda M, Oldmeadow, Christopher, Mazur, Johanna, Basu, Saonli, Frånberg, Mattias, Yang, Qiong, Ligthart, Symen, Hottenga, Jouke J, Rumley, Ann, Mulas, Antonella, de Craen, Anton JM, Grotevendt, Anne, Taylor, Kent D, Delgado, Graciela E, Kifley, Annette, Lopez, Lorna M, Berentzen, Tina L, Mangino, Massimo, Bandinelli, Stefania, Morrison, Alanna C, Hamsten, Anders, Tofler, Geoffrey, de Maat, Moniek PM, Draisma, Harmen HM, Lowe, Gordon D, Zoledziewska, Magdalena, Sattar, Naveed, Lackner, Karl J, Völker, Uwe, McKnight, Barbara, Huang, Jie, Holliday, Elizabeth G, McEvoy, Mark A, Starr, John M, Hysi, Pirro G, Hernandez, Dena G, Guan, Weihua, Rivadeneira, Fernando, McArdle, Wendy L, Slagboom, P Eline, Zeller, Tanja, Psaty, Bruce M, Uitterlinden, André G, de Geus, Eco JC, Stott, David J, Binder, Harald, Hofman, Albert, Franco, Oscar H, Rotter, Jerome I, Ferrucci, Luigi, Spector, Tim D, Deary, Ian J, März, Winfried, Greinacher, Andreas, Wild, Philipp S, Cucca, Francesco, Boomsma, Dorret I, Watkins, Hugh, Tang, Weihong, Ridker, Paul M, Jukema, Jan W, Scott, Rodney J, Mitchell, Paul, Hansen, Torben, O'Donnell, Christopher J, Smith, Nicholas L, Strachan, David P, and Dehghan, Abbas

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Genome-Wide Association Study, HapMap Project, Humans, General Science & Technology
Abstract

An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5×10-8 is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5×10-8), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development.

Published
2017

33. KLB is associated with alcohol drinking, and its gene product β-Klotho is necessary for FGF21 regulation of alcohol preference

Author

Schumann, Gunter, Liu, Chunyu, O'Reilly, Paul, Gao, He, Song, Parkyong, Xu, Bing, Ruggeri, Barbara, Amin, Najaf, Jia, Tianye, Preis, Sarah, Segura Lepe, Marcelo, Akira, Shizuo, Barbieri, Caterina, Baumeister, Sebastian, Cauchi, Stephane, Clarke, Toni-Kim, Enroth, Stefan, Fischer, Krista, Hällfors, Jenni, Harris, Sarah E, Hieber, Saskia, Hofer, Edith, Hottenga, Jouke-Jan, Johansson, Åsa, Joshi, Peter K, Kaartinen, Niina, Laitinen, Jaana, Lemaitre, Rozenn, Loukola, Anu, Luan, Jian'an, Lyytikäinen, Leo-Pekka, Mangino, Massimo, Manichaikul, Ani, Mbarek, Hamdi, Milaneschi, Yuri, Moayyeri, Alireza, Mukamal, Kenneth, Nelson, Christopher, Nettleton, Jennifer, Partinen, Eemil, Rawal, Rajesh, Robino, Antonietta, Rose, Lynda, Sala, Cinzia, Satoh, Takashi, Schmidt, Reinhold, Schraut, Katharina, Scott, Robert, Smith, Albert Vernon, Starr, John M, Teumer, Alexander, Trompet, Stella, Uitterlinden, André G, Venturini, Cristina, Vergnaud, Anne-Claire, Verweij, Niek, Vitart, Veronique, Vuckovic, Dragana, Wedenoja, Juho, Yengo, Loic, Yu, Bing, Zhang, Weihua, Zhao, Jing Hua, Boomsma, Dorret I, Chambers, John, Chasman, Daniel I, Daniela, Toniolo, de Geus, Eco, Deary, Ian, Eriksson, Johan G, Esko, Tõnu, Eulenburg, Volker, Franco, Oscar H, Froguel, Philippe, Gieger, Christian, Grabe, Hans J, Gudnason, Vilmundur, Gyllensten, Ulf, Harris, Tamara B, Hartikainen, Anna-Liisa, Heath, Andrew C, Hocking, Lynne, Hofman, Albert, Huth, Cornelia, Jarvelin, Marjo-Riitta, Jukema, J Wouter, Kaprio, Jaakko, Kooner, Jaspal S, Kutalik, Zoltan, Lahti, Jari, Langenberg, Claudia, Lehtimäki, Terho, Liu, Yongmei, Madden, Pamela AF, Martin, Nicholas, Morrison, Alanna, Penninx, Brenda, Pirastu, Nicola, Psaty, Bruce, and Raitakari, Olli

Subjects
Underage Drinking, Genetics, Alcoholism, Alcohol Use and Health, Neurosciences, Substance Misuse, Pediatric, Underpinning research, 1.1 Normal biological development and functioning, Stroke, Cardiovascular, Cancer, Oral and gastrointestinal, Good Health and Well Being, Alcohol Drinking, Animals, Behavior, Animal, Brain, Emotions, Female, Fibroblast Growth Factors, Genome-Wide Association Study, Humans, Klotho Proteins, Liver, Male, Membrane Proteins, Mice, Mice, 129 Strain, Mice, Inbred C57BL, Mice, Knockout, Polymorphism, Single Nucleotide, alcohol consumption, human, beta-Klotho, FGF21, mouse model, β-Klotho
Abstract

Excessive alcohol consumption is a major public health problem worldwide. Although drinking habits are known to be inherited, few genes have been identified that are robustly linked to alcohol drinking. We conducted a genome-wide association metaanalysis and replication study among >105,000 individuals of European ancestry and identified β-Klotho (KLB) as a locus associated with alcohol consumption (rs11940694; P = 9.2 × 10-12). β-Klotho is an obligate coreceptor for the hormone FGF21, which is secreted from the liver and implicated in macronutrient preference in humans. We show that brain-specific β-Klotho KO mice have an increased alcohol preference and that FGF21 inhibits alcohol drinking by acting on the brain. These data suggest that a liver-brain endocrine axis may play an important role in the regulation of alcohol drinking behavior and provide a unique pharmacologic target for reducing alcohol consumption.

Published
2016

34. A high-quality human reference panel reveals the complexity and distribution of genomic structural variants.

Author

Hehir-Kwa, Jayne Y, Marschall, Tobias, Kloosterman, Wigard P, Francioli, Laurent C, Baaijens, Jasmijn A, Dijkstra, Louis J, Abdellaoui, Abdel, Koval, Vyacheslav, Thung, Djie Tjwan, Wardenaar, René, Renkens, Ivo, Coe, Bradley P, Deelen, Patrick, de Ligt, Joep, Lameijer, Eric-Wubbo, van Dijk, Freerk, Hormozdiari, Fereydoun, Genome of the Netherlands Consortium, Uitterlinden, André G, van Duijn, Cornelia M, Eichler, Evan E, de Bakker, Paul IW, Swertz, Morris A, Wijmenga, Cisca, van Ommen, Gert-Jan B, Slagboom, P Eline, Boomsma, Dorret I, Schönhuth, Alexander, Ye, Kai, and Guryev, Victor

Subjects
Genome of the Netherlands Consortium, Chromosomes, Humans, RNA, Polymerase Chain Reaction, Sequence Analysis, DNA, Sequence Analysis, RNA, Computational Biology, Genomics, Gene Deletion, Genotype, Haplotypes, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Genome, Human, Algorithms, Software, Netherlands, INDEL Mutation, Genomic Structural Variation, Sequence Analysis, DNA, Polymorphism, Single Nucleotide, Genome, Human
Abstract

Structural variation (SV) represents a major source of differences between individual human genomes and has been linked to disease phenotypes. However, the majority of studies provide neither a global view of the full spectrum of these variants nor integrate them into reference panels of genetic variation. Here, we analyse whole genome sequencing data of 769 individuals from 250 Dutch families, and provide a haplotype-resolved map of 1.9 million genome variants across 9 different variant classes, including novel forms of complex indels, and retrotransposition-mediated insertions of mobile elements and processed RNAs. A large proportion are previously under reported variants sized between 21 and 100 bp. We detect 4 megabases of novel sequence, encoding 11 new transcripts. Finally, we show 191 known, trait-associated SNPs to be in strong linkage disequilibrium with SVs and demonstrate that our panel facilitates accurate imputation of SVs in unrelated individuals.

Published
2016

35. The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals.

Author

Ehret, Georg B, Ferreira, Teresa, Chasman, Daniel I, Jackson, Anne U, Schmidt, Ellen M, Johnson, Toby, Thorleifsson, Gudmar, Luan, Jian'an, Donnelly, Lousie A, Kanoni, Stavroula, Petersen, Ann-Kristin, Pihur, Vasyl, Strawbridge, Rona J, Shungin, Dmitry, Hughes, Maria F, Meirelles, Osorio, Kaakinen, Marika, Bouatia-Naji, Nabila, Kristiansson, Kati, Shah, Sonia, Kleber, Marcus E, Guo, Xiuqing, Lyytikäinen, Leo-Pekka, Fava, Cristiano, Eriksson, Niclas, Nolte, Ilja M, Magnusson, Patrik K, Salfati, Elias L, Rallidis, Loukianos S, Theusch, Elizabeth, Smith, Andrew JP, Folkersen, Lasse, Witkowska, Kate, Pers, Tune H, Joehanes, Roby, Kim, Stuart K, Lataniotis, Lazaros, Jansen, Rick, Johnson, Andrew D, Warren, Helen, Kim, Young Jin, Zhao, Wei, Wu, Ying, Tayo, Bamidele O, Bochud, Murielle, CHARGE-EchoGen consortium, CHARGE-HF consortium, Wellcome Trust Case Control Consortium, Absher, Devin, Adair, Linda S, Amin, Najaf, Arking, Dan E, Axelsson, Tomas, Baldassarre, Damiano, Balkau, Beverley, Bandinelli, Stefania, Barnes, Michael R, Barroso, Inês, Bevan, Stephen, Bis, Joshua C, Bjornsdottir, Gyda, Boehnke, Michael, Boerwinkle, Eric, Bonnycastle, Lori L, Boomsma, Dorret I, Bornstein, Stefan R, Brown, Morris J, Burnier, Michel, Cabrera, Claudia P, Chambers, John C, Chang, I-Shou, Cheng, Ching-Yu, Chines, Peter S, Chung, Ren-Hua, Collins, Francis S, Connell, John M, Döring, Angela, Dallongeville, Jean, Danesh, John, de Faire, Ulf, Delgado, Graciela, Dominiczak, Anna F, Doney, Alex SF, Drenos, Fotios, Edkins, Sarah, Eicher, John D, Elosua, Roberto, Enroth, Stefan, Erdmann, Jeanette, Eriksson, Per, Esko, Tonu, Evangelou, Evangelos, Evans, Alun, Fall, Tove, Farrall, Martin, Felix, Janine F, Ferrières, Jean, Ferrucci, Luigi, Fornage, Myriam, and Forrester, Terrence

Subjects
CHARGE-EchoGen consortium, CHARGE-HF consortium, Wellcome Trust Case Control Consortium, Cells, Cultured, Humans, Hypertension, Microarray Analysis, Blood Pressure, Polymorphism, Single Nucleotide, African Continental Ancestry Group, Asian Continental Ancestry Group, Genome-Wide Association Study, Cells, Cultured, Polymorphism, Single Nucleotide, Developmental Biology, Biological Sciences, Medical and Health Sciences
Abstract

To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.

Published
2016

36. Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

Author

van Leeuwen, Elisabeth M, Sabo, Aniko, Bis, Joshua C, Huffman, Jennifer E, Manichaikul, Ani, Smith, Albert V, Feitosa, Mary F, Demissie, Serkalem, Joshi, Peter K, Duan, Qing, Marten, Jonathan, van Klinken, Jan B, Surakka, Ida, Nolte, Ilja M, Zhang, Weihua, Mbarek, Hamdi, Li-Gao, Ruifang, Trompet, Stella, Verweij, Niek, Evangelou, Evangelos, Lyytikäinen, Leo-Pekka, Tayo, Bamidele O, Deelen, Joris, van der Most, Peter J, van der Laan, Sander W, Arking, Dan E, Morrison, Alanna, Dehghan, Abbas, Franco, Oscar H, Hofman, Albert, Rivadeneira, Fernando, Sijbrands, Eric J, Uitterlinden, Andre G, Mychaleckyj, Josyf C, Campbell, Archie, Hocking, Lynne J, Padmanabhan, Sandosh, Brody, Jennifer A, Rice, Kenneth M, White, Charles C, Harris, Tamara, Isaacs, Aaron, Campbell, Harry, Lange, Leslie A, Rudan, Igor, Kolcic, Ivana, Navarro, Pau, Zemunik, Tatijana, Salomaa, Veikko, Study, The LifeLines Cohort, Kooner, Angad S, Kooner, Jaspal S, Lehne, Benjamin, Scott, William R, Tan, Sian-Tsung, de Geus, Eco J, Milaneschi, Yuri, Penninx, Brenda WJH, Willemsen, Gonneke, de Mutsert, Renée, Ford, Ian, Gansevoort, Ron T, Segura-Lepe, Marcelo P, Raitakari, Olli T, Viikari, Jorma S, Nikus, Kjell, Forrester, Terrence, McKenzie, Colin A, de Craen, Anton JM, de Ruijter, Hester M, Group, CHARGE Lipids Working, Pasterkamp, Gerard, Snieder, Harold, Oldehinkel, Albertine J, Slagboom, P Eline, Cooper, Richard S, Kähönen, Mika, Lehtimäki, Terho, Elliott, Paul, van der Harst, Pim, Jukema, J Wouter, Mook-Kanamori, Dennis O, Boomsma, Dorret I, Chambers, John C, Swertz, Morris, Ripatti, Samuli, van Dijk, Ko Willems, Vitart, Veronique, Polasek, Ozren, Hayward, Caroline, Wilson, James G, Wilson, James F, Gudnason, Vilmundur, Rich, Stephen S, Psaty, Bruce M, Borecki, Ingrid B, Boerwinkle, Eric, Rotter, Jerome I, Cupples, L Adrienne, and van Duijn, Cornelia M

Subjects
Biological Sciences, Genetics, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Angiopoietin-Like Protein 4, Angiopoietins, Exons, Fasting, Female, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, LifeLines Cohort Study, CHARGE Lipids Working Group, Complex traits, Epidemiology, Genome-wide, circulating lipid levels, Medical and Health Sciences, Genetics & Heredity, Clinical sciences
Abstract

BackgroundSo far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels.MethodsWe used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ∼60 000 individuals in the discovery stage and ∼90 000 samples in the replication stage.ResultsOur study resulted in the identification of five new associations with circulating lipid levels at four loci. All four loci are within genes that can be linked biologically to lipid metabolism. One of the variants, rs116843064, is a damaging missense variant within the ANGPTL4 gene.ConclusionsThis study illustrates that GWAS with high-scale imputation may still help us unravel the biological mechanism behind circulating lipid levels.

Published
2016

37. Integrative approaches for large-scale transcriptome-wide association studies

Author

Gusev, Alexander, Ko, Arthur, Shi, Huwenbo, Bhatia, Gaurav, Chung, Wonil, Penninx, Brenda WJH, Jansen, Rick, de Geus, Eco JC, Boomsma, Dorret I, Wright, Fred A, Sullivan, Patrick F, Nikkola, Elina, Alvarez, Marcus, Civelek, Mete, Lusis, Aldons J, Lehtimäki, Terho, Raitoharju, Emma, Kähönen, Mika, Seppälä, Ilkka, Raitakari, Olli T, Kuusisto, Johanna, Laakso, Markku, Price, Alkes L, Pajukanta, Päivi, and Pasaniuc, Bogdan

Subjects
Biological Sciences, Genetics, Obesity, Human Genome, Cancer, Generic health relevance, Animals, Gene Expression Regulation, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Mice, Phenotype, Quantitative Trait Loci, Transcriptome, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance of one or multiple proteins. Here we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated with complex traits. We leverage expression imputation from genetic data to perform a transcriptome-wide association study (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in ∼ 3,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 new genes significantly associated with obesity-related traits (BMI, lipids and height). Many of these genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits.

Published
2016

38. Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

Author

Horikoshi, Momoko, Mӓgi, Reedik, van de Bunt, Martijn, Surakka, Ida, Sarin, Antti-Pekka, Mahajan, Anubha, Marullo, Letizia, Thorleifsson, Gudmar, Hӓgg, Sara, Hottenga, Jouke-Jan, Ladenvall, Claes, Ried, Janina S, Winkler, Thomas W, Willems, Sara M, Pervjakova, Natalia, Esko, Tõnu, Beekman, Marian, Nelson, Christopher P, Willenborg, Christina, Wiltshire, Steven, Ferreira, Teresa, Fernandez, Juan, Gaulton, Kyle J, Steinthorsdottir, Valgerdur, Hamsten, Anders, Magnusson, Patrik KE, Willemsen, Gonneke, Milaneschi, Yuri, Robertson, Neil R, Groves, Christopher J, Bennett, Amanda J, Lehtimӓki, Terho, Viikari, Jorma S, Rung, Johan, Lyssenko, Valeriya, Perola, Markus, Heid, Iris M, Herder, Christian, Grallert, Harald, Müller-Nurasyid, Martina, Roden, Michael, Hypponen, Elina, Isaacs, Aaron, van Leeuwen, Elisabeth M, Karssen, Lennart C, Mihailov, Evelin, Houwing-Duistermaat, Jeanine J, de Craen, Anton JM, Deelen, Joris, Havulinna, Aki S, Blades, Matthew, Hengstenberg, Christian, Erdmann, Jeanette, Schunkert, Heribert, Kaprio, Jaakko, Tobin, Martin D, Samani, Nilesh J, Lind, Lars, Salomaa, Veikko, Lindgren, Cecilia M, Slagboom, P Eline, Metspalu, Andres, van Duijn, Cornelia M, Eriksson, Johan G, Peters, Annette, Gieger, Christian, Jula, Antti, Groop, Leif, Raitakari, Olli T, Power, Chris, Penninx, Brenda WJH, de Geus, Eco, Smit, Johannes H, Boomsma, Dorret I, Pedersen, Nancy L, Ingelsson, Erik, Thorsteinsdottir, Unnur, Stefansson, Kari, Ripatti, Samuli, Prokopenko, Inga, McCarthy, Mark I, Morris, Andrew P, and ENGAGE Consortium

Subjects
ENGAGE Consortium, Humans, Obesity, Genetic Predisposition to Disease, Glucose-6-Phosphatase, Protein-Serine-Threonine Kinases, Thrombospondins, Body Mass Index, Chromosome Mapping, Glycemic Index, Gene Frequency, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study, Germinal Center Kinases, Polymorphism, Single Nucleotide, Genetics, Developmental Biology
Abstract

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

Published
2015

39. Characteristics of de novo structural changes in the human genome

Author

Kloosterman, Wigard P, Francioli, Laurent C, Hormozdiari, Fereydoun, Marschall, Tobias, Hehir-Kwa, Jayne Y, Abdellaoui, Abdel, Lameijer, Eric-Wubbo, Moed, Matthijs H, Koval, Vyacheslav, Renkens, Ivo, van Roosmalen, Markus J, Arp, Pascal, Karssen, Lennart C, Coe, Bradley P, Handsaker, Robert E, Suchiman, Eka D, Cuppen, Edwin, Thung, Djie Tjwan, McVey, Mitch, Wendl, Michael C, Consortium, Genome of the Netherlands, Uitterlinden, André, van Duijn, Cornelia M, Swertz, Morris A, Wijmenga, Cisca, van Ommen, GertJan B, Slagboom, P Eline, Boomsma, Dorret I, Schönhuth, Alexander, Eichler, Evan E, de Bakker, Paul IW, Ye, Kai, and Guryev, Victor

Subjects
Genetics, Human Genome, Alleles, Amino Acid Sequence, Female, Genetic Variation, Genome, Human, Genomics, Haplotypes, Humans, INDEL Mutation, Male, Molecular Sequence Data, Mutation Rate, Polymorphism, Single Nucleotide, Retroelements, Sequence Alignment, Sequence Analysis, DNA, Genome of Netherlands Consortium, Biological Sciences, Medical and Health Sciences, Bioinformatics
Abstract

Small insertions and deletions (indels) and large structural variations (SVs) are major contributors to human genetic diversity and disease. However, mutation rates and characteristics of de novo indels and SVs in the general population have remained largely unexplored. We report 332 validated de novo structural changes identified in whole genomes of 250 families, including complex indels, retrotransposon insertions, and interchromosomal events. These data indicate a mutation rate of 2.94 indels (1-20 bp) and 0.16 SVs (>20 bp) per generation. De novo structural changes affect on average 4.1 kbp of genomic sequence and 29 coding bases per generation, which is 91 and 52 times more nucleotides than de novo substitutions, respectively. This contrasts with the equal genomic footprint of inherited SVs and substitutions. An excess of structural changes originated on paternal haplotypes. Additionally, we observed a nonuniform distribution of de novo SVs across offspring. These results reveal the importance of different mutational mechanisms to changes in human genome structure across generations.

Published
2015

40. Genome of The Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels.

Author

van Leeuwen, Elisabeth M, Karssen, Lennart C, Deelen, Joris, Isaacs, Aaron, Medina-Gomez, Carolina, Mbarek, Hamdi, Kanterakis, Alexandros, Trompet, Stella, Postmus, Iris, Verweij, Niek, van Enckevort, David J, Huffman, Jennifer E, White, Charles C, Feitosa, Mary F, Bartz, Traci M, Manichaikul, Ani, Joshi, Peter K, Peloso, Gina M, Deelen, Patrick, van Dijk, Freerk, Willemsen, Gonneke, de Geus, Eco J, Milaneschi, Yuri, Penninx, Brenda WJH, Francioli, Laurent C, Menelaou, Androniki, Pulit, Sara L, Rivadeneira, Fernando, Hofman, Albert, Oostra, Ben A, Franco, Oscar H, Mateo Leach, Irene, Beekman, Marian, de Craen, Anton JM, Uh, Hae-Won, Trochet, Holly, Hocking, Lynne J, Porteous, David J, Sattar, Naveed, Packard, Chris J, Buckley, Brendan M, Brody, Jennifer A, Bis, Joshua C, Rotter, Jerome I, Mychaleckyj, Josyf C, Campbell, Harry, Duan, Qing, Lange, Leslie A, Wilson, James F, Hayward, Caroline, Polasek, Ozren, Vitart, Veronique, Rudan, Igor, Wright, Alan F, Rich, Stephen S, Psaty, Bruce M, Borecki, Ingrid B, Kearney, Patricia M, Stott, David J, Adrienne Cupples, L, Genome of The Netherlands Consortium, Jukema, J Wouter, van der Harst, Pim, Sijbrands, Eric J, Hottenga, Jouke-Jan, Uitterlinden, Andre G, Swertz, Morris A, van Ommen, Gert-Jan B, de Bakker, Paul IW, Eline Slagboom, P, Boomsma, Dorret I, Wijmenga, Cisca, and van Duijn, Cornelia M

Subjects
Genome of The Netherlands Consortium, Humans, Cholesterol, ATP-Binding Cassette Transporters, Gene Frequency, Mutation, Missense, Netherlands, Genetic Association Studies, Mutation, Missense
Abstract

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of The Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value

Published
2015

41. Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

Author

O'Dushlaine, Colm, Rossin, Lizzy, Lee, Phil H, Duncan, Laramie, Parikshak, Neelroop N, Newhouse, Stephen, Ripke, Stephan, Neale, Benjamin M, Purcell, Shaun M, Posthuma, Danielle, Nurnberger, John I, Lee, S Hong, Faraone, Stephen V, Perlis, Roy H, Mowry, Bryan J, Thapar, Anita, Goddard, Michael E, Witte, John S, Absher, Devin, Agartz, Ingrid, Akil, Huda, Amin, Farooq, Andreassen, Ole A, Anjorin, Adebayo, Anney, Richard, Anttila, Verneri, Arking, Dan E, Asherson, Philip, Azevedo, Maria H, Backlund, Lena, Badner, Judith A, Bailey, Anthony J, Banaschewski, Tobias, Barchas, Jack D, Barnes, Michael R, Barrett, Thomas B, Bass, Nicholas, Battaglia, Agatino, Bauer, Michael, Bayes, Monica, Bellivier, Frank, Bergen, Sarah E, Berrettini, Wade, Betancur, Catalina, Bettecken, Thomas, Biederman, Joseph, Binder, Elisabeth B, Black, Donald W, Blackwood, Douglas HR, Bloss, Cinnamon S, Boehnke, Michael, Boomsma, Dorret I, Breuer, Rene, Bruggeman, Richard, Cormican, Paul, Buccola, Nancy G, Buitelaar, Jan K, Bunney, William E, Buxbaum, Joseph D, Byerley, William F, Byrne, Enda M, Caesar, Sian, Cahn, Wiepke, Cantor, Rita M, Casas, Miguel, Chakravarti, Aravinda, Chambert, Kimberly, Choudhury, Khalid, Cichon, Sven, Mattheisen, Manuel, Cloninger, C Robert, Collier, David A, Cook, Edwin H, Coon, Hilary, Cormand, Bru, Corvin, Aiden, Coryell, William H, Craig, David W, Craig, Ian W, Crosbie, Jennifer, Cuccaro, Michael L, Curtis, David, Czamara, Darina, Datta, Susmita, Dawson, Geraldine, Day, Richard, De Geus, Eco J, Degenhardt, Franziska, Djurovic, Srdjan, Donohoe, Gary J, Doyle, Alysa E, Duan, Jubao, Dudbridge, Frank, Duketis, Eftichia, Ebstein, Richard P, Edenberg, Howard J, Elia, Josephine, Ennis, Sean, Etain, Bruno, and Fanous, Ayman

Subjects
Human Genome, Brain Disorders, Serious Mental Illness, Schizophrenia, Genetics, Depression, Mental Health, Aetiology, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Brain, Databases, Genetic, Genetic Predisposition to Disease, Genome-Wide Association Study, Histones, Humans, Mental Disorders, Signal Transduction, Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium, Neurosciences, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

Published
2015

42. Effect of genome and environment on metabolic and inflammatory profiles.

Author

Sirota, Marina, Willemsen, Gonneke, Sundar, Purnima, Pitts, Steven J, Potluri, Shobha, Prifti, Edi, Kennedy, Sean, Ehrlich, S Dusko, Neuteboom, Jacoline, Kluft, Cornelis, Malone, Karen E, Cox, David R, de Geus, Eco JC, and Boomsma, Dorret I

Subjects
Humans, Inflammation, Hematologic Tests, Cluster Analysis, Environment, Housing, Twins, Monozygotic, Phenotype, Genome, Human, Adult, Female, Male, Genome, Human, Twins, Monozygotic, General Science & Technology
Abstract

Twin and family studies have established the contribution of genetic factors to variation in metabolic, hematologic and immunological parameters. The majority of these studies analyzed single or combined traits into pre-defined syndromes. In the present study, we explore an alternative multivariate approach in which a broad range of metabolic, hematologic, and immunological traits are analyzed simultaneously to determine the resemblance of monozygotic (MZ) twin pairs, twin-spouse pairs and unrelated, non-cohabiting individuals. A total of 517 participants from the Netherlands Twin Register, including 210 MZ twin pairs and 64 twin-spouse pairs, took part in the study. Data were collected on body composition, blood pressure, heart rate, and multiple biomarkers assessed in fasting blood samples, including lipid levels, glucose, insulin, liver enzymes, hematological measurements and cytokine levels. For all 51 measured traits, pair-wise Pearson correlations, correcting for family relatedness, were calculated across all the individuals in the cohort. Hierarchical clustering techniques were applied to group the measured traits into sub-clusters based on similarity. Sub-clusters were observed among metabolic traits and among inflammatory markers. We defined a phenotypic profile as the collection of all the traits measured for a given individual. Average within-pair similarity of phenotypic profiles was determined for the groups of MZ twin pairs, spouse pairs and pairs of unrelated individuals. The average similarity across the full phenotypic profile was higher for MZ twin pairs than for spouse pairs, and lowest for pairs of unrelated individuals. Cohabiting MZ twins were more similar in their phenotypic profile compared to MZ twins who no longer lived together. The correspondence in the phenotypic profile is therefore determined to a large degree by familial, mostly genetic, factors, while household factors contribute to a lesser degree to profile similarity.

Published
2015

43. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

Author

Thompson, Paul M, Stein, Jason L, Medland, Sarah E, Hibar, Derrek P, Vasquez, Alejandro Arias, Renteria, Miguel E, Toro, Roberto, Jahanshad, Neda, Schumann, Gunter, Franke, Barbara, Wright, Margaret J, Martin, Nicholas G, Agartz, Ingrid, Alda, Martin, Alhusaini, Saud, Almasy, Laura, Almeida, Jorge, Alpert, Kathryn, Andreasen, Nancy C, Andreassen, Ole A, Apostolova, Liana G, Appel, Katja, Armstrong, Nicola J, Aribisala, Benjamin, Bastin, Mark E, Bauer, Michael, Bearden, Carrie E, Bergmann, Ørjan, Binder, Elisabeth B, Blangero, John, Bockholt, Henry J, Bøen, Erlend, Bois, Catherine, Boomsma, Dorret I, Booth, Tom, Bowman, Ian J, Bralten, Janita, Brouwer, Rachel M, Brunner, Han G, Brohawn, David G, Buckner, Randy L, Buitelaar, Jan, Bulayeva, Kazima, Bustillo, Juan R, Calhoun, Vince D, Cannon, Dara M, Cantor, Rita M, Carless, Melanie A, Caseras, Xavier, Cavalleri, Gianpiero L, Chakravarty, M Mallar, Chang, Kiki D, Ching, Christopher RK, Christoforou, Andrea, Cichon, Sven, Clark, Vincent P, Conrod, Patricia, Coppola, Giovanni, Crespo-Facorro, Benedicto, Curran, Joanne E, Czisch, Michael, Deary, Ian J, de Geus, Eco JC, den Braber, Anouk, Delvecchio, Giuseppe, Depondt, Chantal, de Haan, Lieuwe, de Zubicaray, Greig I, Dima, Danai, Dimitrova, Rali, Djurovic, Srdjan, Dong, Hongwei, Donohoe, Gary, Duggirala, Ravindranath, Dyer, Thomas D, Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Emsell, Louise, Erk, Susanne, Espeseth, Thomas, Fagerness, Jesen, Fears, Scott, Fedko, Iryna, Fernández, Guillén, Fisher, Simon E, Foroud, Tatiana, Fox, Peter T, Francks, Clyde, Frangou, Sophia, Frey, Eva Maria, Frodl, Thomas, Frouin, Vincent, Garavan, Hugh, Giddaluru, Sudheer, Glahn, David C, Godlewska, Beata, Goldstein, Rita Z, Gollub, Randy L, and Grabe, Hans J

Subjects
Biological Psychology, Health Sciences, Psychology, Mental Illness, Genetics, Schizophrenia, Brain Disorders, Human Genome, Mental Health, Neurosciences, Biomedical Imaging, 2.1 Biological and endogenous factors, Mental health, Neurological, Good Health and Well Being, Brain Mapping, Cooperative Behavior, Genome-Wide Association Study, Humans, Meta-Analysis as Topic, Neuroimaging, MRI, GWAS, Consortium, Meta-analysis, Multi-site, Alzheimer’s Disease Neuroimaging Initiative, EPIGEN Consortium, IMAGEN Consortium, Saguenay Youth Study (SYS) Group, Medical and Health Sciences, Psychology and Cognitive Sciences, Experimental Psychology, Biomedical and clinical sciences, Health sciences
Abstract

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Published
2014

44. Heritability and genomics of gene expression in peripheral blood

Author

Wright, Fred A, Sullivan, Patrick F, Brooks, Andrew I, Zou, Fei, Sun, Wei, Xia, Kai, Madar, Vered, Jansen, Rick, Chung, Wonil, Zhou, Yi-Hui, Abdellaoui, Abdel, Batista, Sandra, Butler, Casey, Chen, Guanhua, Chen, Ting-Huei, D'Ambrosio, David, Gallins, Paul, Ha, Min Jin, Hottenga, Jouke Jan, Huang, Shunping, Kattenberg, Mathijs, Kochar, Jaspreet, Middeldorp, Christel M, Qu, Ani, Shabalin, Andrey, Tischfield, Jay, Todd, Laura, Tzeng, Jung-Ying, van Grootheest, Gerard, Vink, Jacqueline M, Wang, Qi, Wang, Wei, Wang, Weibo, Willemsen, Gonneke, Smit, Johannes H, de Geus, Eco J, Yin, Zhaoyu, Penninx, Brenda WJH, and Boomsma, Dorret I

Subjects
Biotechnology, Human Genome, Genetics, Blood, Gene Expression Profiling, Gene Expression Regulation, Genotype, Humans, Inheritance Patterns, Likelihood Functions, Netherlands, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

We assessed gene expression profiles in 2,752 twins, using a classic twin design to quantify expression heritability and quantitative trait loci (eQTLs) in peripheral blood. The most highly heritable genes (∼777) were grouped into distinct expression clusters, enriched in gene-poor regions, associated with specific gene function or ontology classes, and strongly associated with disease designation. The design enabled a comparison of twin-based heritability to estimates based on dizygotic identity-by-descent sharing and distant genetic relatedness. Consideration of sampling variation suggests that previous heritability estimates have been upwardly biased. Genotyping of 2,494 twins enabled powerful identification of eQTLs, which we further examined in a replication set of 1,895 unrelated subjects. A large number of non-redundant local eQTLs (6,756) met replication criteria, whereas a relatively small number of distant eQTLs (165) met quality control and replication standards. Our results provide a new resource toward understanding the genetic control of transcription.

Published
2014

45. Genome-wide analyses of ADHD identify 27 risk loci, refine the genetic architecture and implicate several cognitive domains

Author

Demontis, Ditte, Walters, G. Bragi, Athanasiadis, Georgios, Walters, Raymond, Therrien, Karen, Nielsen, Trine Tollerup, Farajzadeh, Leila, Voloudakis, Georgios, Bendl, Jaroslav, Zeng, Biau, Zhang, Wen, Grove, Jakob, Als, Thomas D., Duan, Jinjie, Satterstrom, F. Kyle, Bybjerg-Grauholm, Jonas, Bækved-Hansen, Marie, Gudmundsson, Olafur O., Magnusson, Sigurdur H., Baldursson, Gisli, Davidsdottir, Katrin, Haraldsdottir, Gyda S., Agerbo, Esben, Hoffman, Gabriel E., Dalsgaard, Søren, Martin, Joanna, Ribasés, Marta, Boomsma, Dorret I., Soler Artigas, Maria, Roth Mota, Nina, Howrigan, Daniel, Medland, Sarah E., Zayats, Tetyana, Rajagopal, Veera M., Havdahl, Alexandra, Doyle, Alysa, Reif, Andreas, Thapar, Anita, Cormand, Bru, Liao, Calwing, Burton, Christie, Bau, Claiton H. D., Rovaris, Diego Luiz, Sonuga-Barke, Edmund, Corfield, Elizabeth, Grevet, Eugenio Horacio, Larsson, Henrik, Gizer, Ian R., Waldman, Irwin, Brikell, Isabell, Haavik, Jan, Crosbie, Jennifer, McGough, James, Kuntsi, Jonna, Glessner, Joseph, Langley, Kate, Lesch, Klaus-Peter, Rohde, Luis Augusto, Hutz, Mara H., Klein, Marieke, Bellgrove, Mark, Tesli, Martin, O’Donovan, Michael C., Andreassen, Ole Andreas, Leung, Patrick W. L., Pan, Pedro M., Joober, Ridha, Schachar, Russel, Loo, Sandra, Witt, Stephanie H., Reichborn-Kjennerud, Ted, Banaschewski, Tobias, Hawi, Ziarih, Daly, Mark J., Mors, Ole, Nordentoft, Merete, Hougaard, David M., Mortensen, Preben Bo, Faraone, Stephen V., Stefansson, Hreinn, Roussos, Panos, Franke, Barbara, Werge, Thomas, Neale, Benjamin M., Stefansson, Kari, Børglum, Anders D., APH - Methodology, APH - Mental Health, Amsterdam Reproduction & Development, and Biological Psychology

Subjects
Cognition, All institutes and research themes of the Radboud University Medical Center, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], SDG 3 - Good Health and Well-being, Genetics, Brain, Humans, Genetic Predisposition to Disease, Attention Deficit Disorder with Hyperactivity/genetics, Genome-Wide Association Study
Abstract

Contains fulltext : 290804.pdf (Publisher’s version ) (Closed access) Attention-deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder with a major genetic component. Here, we present a genome-wide association study meta-analysis of ADHD comprising 38,691 individuals with ADHD and 186,843 controls. We identified 27 genome-wide significant loci, highlighting 76 potential risk genes enriched among genes expressed particularly in early brain development. Overall, ADHD genetic risk was associated with several brain-specific neuronal subtypes and midbrain dopaminergic neurons. In exome-sequencing data from 17,896 individuals, we identified an increased load of rare protein-truncating variants in ADHD for a set of risk genes enriched with probable causal common variants, potentially implicating SORCS3 in ADHD by both common and rare variants. Bivariate Gaussian mixture modeling estimated that 84-98% of ADHD-influencing variants are shared with other psychiatric disorders. In addition, common-variant ADHD risk was associated with impaired complex cognition such as verbal reasoning and a range of executive functions, including attention. 01 februari 2023

Published
2023

46. A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

Author

Ramdas, Shweta, Judd, Jonathan, Graham, Sarah E, Kanoni, Stavroula, Wang, Yuxuan, Surakka, Ida, Wenz, Brandon, Clarke, Shoa L, Chesi, Alessandra, Wells, Andrew, Bhatti, Konain Fatima, Vedantam, Sailaja, Winkler, Thomas W, Locke, Adam E, Marouli, Eirini, Zajac, Greg J M, Wu, Kuan-Han H, Ntalla, Ioanna, Hui, Qin, Klarin, Derek, Hilliard, Austin T, Wang, Zeyuan, Xue, Chao, Thorleifsson, Gudmar, Helgadottir, Anna, Gudbjartsson, Daniel F, Holm, Hilma, Olafsson, Isleifur, Hwang, Mi Yeong, Han, Sohee, Akiyama, Masato, Sakaue, Saori, Terao, Chikashi, Kanai, Masahiro, Zhou, Wei, Brumpton, Ben M, Rasheed, Humaira, Havulinna, Aki S, Veturi, Yogasudha, Pacheco, Jennifer Allen, Rosenthal, Elisabeth A, Lingren, Todd, Feng, QiPing, Kullo, Iftikhar J, Narita, Akira, Takayama, Jun, Martin, Hilary C, Hunt, Karen A, Trivedi, Bhavi, Haessler, Jeffrey, Giulianini, Franco, Bradford, Yuki, Miller, Jason E, Campbell, Archie, Lin, Kuang, Millwood, Iona Y, Rasheed, Asif, Hindy, George, Faul, Jessica D, Zhao, Wei, Weir, David R, Turman, Constance, Huang, Hongyan, Graff, Mariaelisa, Choudhury, Ananyo, Sengupta, Dhriti, Mahajan, Anubha, Brown, Michael R, Zhang, Weihua, Yu, Ketian, Schmidt, Ellen M, Pandit, Anita, Gustafsson, Stefan, Yin, Xianyong, Luan, Jian'an, Zhao, Jing-Hua, Matsuda, Fumihiko, Jang, Hye-Mi, Yoon, Kyungheon, Medina-Gomez, Carolina, Pitsillides, Achilleas, Hottenga, Jouke Jan, Wood, Andrew R, Ji, Yingji, Gao, Zishan, Haworth, Simon, Mitchell, Ruth E, Chai, Jin Fang, Aadahl, Mette, Bjerregaard, Anne A, Yao, Jie, Manichaikul, Ani, Lee, Wen-Jane, Hsiung, Chao Agnes, Warren, Helen R, Ramirez, Julia, Bork-Jensen, Jette, Kårhus, Line L, Goel, Anuj, Sabater-Lleal, Maria, Noordam, Raymond, Mauro, Pala, Matteo, Floris, McDaid, Aaron F, Marques-Vidal, Pedro, Wielscher, Matthias, Trompet, Stella, Sattar, Naveed, Møllehave, Line T, Munz, Matthias, Zeng, Lingyao, Huang, Jianfeng, Yang, Bin, Poveda, Alaitz, Kurbasic, Azra, Schönherr, Sebastian, Forer, Lukas, Scholz, Markus, Galesloot, Tessel E, Bradfield, Jonathan P, Ruotsalainen, Sanni E, Daw, E Warwick, Zmuda, Joseph M, Mitchell, Jonathan S, Fuchsberger, Christian, Christensen, Henry, Brody, Jennifer A, Le, Phuong, Feitosa, Mary F, Wojczynski, Mary K, Hemerich, Daiane, Preuss, Michael, Mangino, Massimo, Christofidou, Paraskevi, Verweij, Niek, Benjamins, Jan W, Engmann, Jorgen, Noah, Tsao L, Verma, Anurag, Slieker, Roderick C, Lo, Ken Sin, Zilhao, Nuno R, Kleber, Marcus E, Delgado, Graciela E, Huo, Shaofeng, Ikeda, Daisuke D, Iha, Hiroyuki, Yang, Jian, Liu, Jun, Demirkan, Ayşe, Leonard, Hampton L, Marten, Jonathan, Emmel, Carina, Schmidt, Börge, Smyth, Laura J, Cañadas-Garre, Marisa, Wang, Chaolong, Nakatochi, Masahiro, Wong, Andrew, Hutri-Kähönen, Nina, Sim, Xueling, Xia, Rui, Huerta-Chagoya, Alicia, Fernandez-Lopez, Juan Carlos, Lyssenko, Valeriya, Nongmaithem, Suraj S, Sankareswaran, Alagu, Irvin, Marguerite R, Oldmeadow, Christopher, Kim, Han-Na, Ryu, Seungho, Timmers, Paul R H J, Arbeeva, Liubov, Dorajoo, Rajkumar, Lange, Leslie A, Prasad, Gauri, Lorés-Motta, Laura, Pauper, Marc, Long, Jirong, Li, Xiaohui, Theusch, Elizabeth, Takeuchi, Fumihiko, Spracklen, Cassandra N, Loukola, Anu, Bollepalli, Sailalitha, Warner, Sophie C, Wang, Ya Xing, Wei, Wen B, Nutile, Teresa, Ruggiero, Daniela, Sung, Yun Ju, Chen, Shufeng, Liu, Fangchao, Yang, Jingyun, Kentistou, Katherine A, Banas, Bernhard, Morgan, Anna, Meidtner, Karina, Bielak, Lawrence F, Smith, Jennifer A, Hebbar, Prashantha, Farmaki, Aliki-Eleni, Hofer, Edith, Lin, Maoxuan, Concas, Maria Pina, Vaccargiu, Simona, van der Most, Peter J, Pitkänen, Niina, Cade, Brian E, van der Laan, Sander W, Chitrala, Kumaraswamy Naidu, Weiss, Stefan, Bentley, Amy R, Doumatey, Ayo P, Adeyemo, Adebowale A, Lee, Jong Young, Petersen, Eva R B, Nielsen, Aneta A, Choi, Hyeok Sun, Nethander, Maria, Freitag-Wolf, Sandra, Southam, Lorraine, Rayner, Nigel W, Wang, Carol A, Lin, Shih-Yi, Wang, Jun-Sing, Couture, Christian, Lyytikäinen, Leo-Pekka, Nikus, Kjell, Cuellar-Partida, Gabriel, Vestergaard, Henrik, Hidalgo, Bertha, Giannakopoulou, Olga, Cai, Qiuyin, Obura, Morgan O, van Setten, Jessica, He, Karen Y, Tang, Hua, Terzikhan, Natalie, Shin, Jae Hun, Jackson, Rebecca D, Reiner, Alexander P, Martin, Lisa Warsinger, Chen, Zhengming, Li, Liming, Kawaguchi, Takahisa, Thiery, Joachim, Bis, Joshua C, Launer, Lenore J, Li, Huaixing, Nalls, Mike A, Raitakari, Olli T, Ichihara, Sahoko, Wild, Sarah H, Nelson, Christopher P, Campbell, Harry, Jäger, Susanne, Nabika, Toru, Al-Mulla, Fahd, Niinikoski, Harri, Braund, Peter S, Kolcic, Ivana, Kovacs, Peter, Giardoglou, Tota, Katsuya, Tomohiro, de Kleijn, Dominique, de Borst, Gert J, Kim, Eung Kweon, Adams, Hieab H H, Ikram, M Arfan, Zhu, Xiaofeng, Asselbergs, Folkert W, Kraaijeveld, Adriaan O, Beulens, Joline W J, Shu, Xiao-Ou, Rallidis, Loukianos S, Pedersen, Oluf, Hansen, Torben, Mitchell, Paul, Hewitt, Alex W, Kähönen, Mika, Pérusse, Louis, Bouchard, Claude, Tönjes, Anke, Ida Chen, Yii-Der, Pennell, Craig E, Mori, Trevor A, Lieb, Wolfgang, Franke, Andre, Ohlsson, Claes, Mellström, Dan, Cho, Yoon Shin, Lee, Hyejin, Yuan, Jian-Min, Koh, Woon-Puay, Rhee, Sang Youl, Woo, Jeong-Taek, Heid, Iris M, Stark, Klaus J, Zimmermann, Martina E, Völzke, Henry, Homuth, Georg, Evans, Michele K, Zonderman, Alan B, Polasek, Ozren, Pasterkamp, Gerard, Hoefer, Imo E, Redline, Susan, Pahkala, Katja, Oldehinkel, Albertine J, Snieder, Harold, Biino, Ginevra, Schmidt, Reinhold, Schmidt, Helena, Bandinelli, Stefania, Dedoussis, George, Thanaraj, Thangavel Alphonse, Peyser, Patricia A, Kato, Norihiro, Schulze, Matthias B, Girotto, Giorgia, Böger, Carsten A, Jung, Bettina, Joshi, Peter K, Bennett, David A, De Jager, Philip L, Lu, Xiangfeng, Mamakou, Vasiliki, Brown, Morris, Caulfield, Mark J, Munroe, Patricia B, Guo, Xiuqing, Ciullo, Marina, Jonas, Jost B, Samani, Nilesh J, Kaprio, Jaakko, Pajukanta, Päivi, Tusié-Luna, Teresa, Aguilar-Salinas, Carlos A, Adair, Linda S, Bechayda, Sonny Augustin, de Silva, H Janaka, Wickremasinghe, Ananda R, Krauss, Ronald M, Wu, Jer-Yuarn, Zheng, Wei, den Hollander, Anneke I, Bharadwaj, Dwaipayan, Correa, Adolfo, Wilson, James G, Lind, Lars, Heng, Chew-Kiat, Nelson, Amanda E, Golightly, Yvonne M, Wilson, James F, Penninx, Brenda, Kim, Hyung-Lae, Attia, John, Scott, Rodney J, Rao, D C, Arnett, Donna K, Walker, Mark, Scott, Laura J, Koistinen, Heikki A, Chandak, Giriraj R, Mercader, Josep M, Villalpando, Clicerio Gonzalez, Orozco, Lorena, Fornage, Myriam, Tai, E Shyong, van Dam, Rob M, Lehtimäki, Terho, Chaturvedi, Nish, Yokota, Mitsuhiro, Liu, Jianjun, Reilly, Dermot F, McKnight, Amy Jayne, Kee, Frank, Jöckel, Karl-Heinz, McCarthy, Mark I, Palmer, Colin N A, Vitart, Veronique, Hayward, Caroline, Simonsick, Eleanor, van Duijn, Cornelia M, Jin, Zi-Bing, Lu, Fan, Hishigaki, Haretsugu, Lin, Xu, März, Winfried, Gudnason, Vilmundur, Tardif, Jean-Claude, Lettre, Guillaume, T Hart, Leen M, Elders, Petra J M, Rader, Daniel J, Damrauer, Scott M, Kumari, Meena, Kivimaki, Mika, van der Harst, Pim, Spector, Tim D, Loos, Ruth J F, Province, Michael A, Parra, Esteban J, Cruz, Miguel, Psaty, Bruce M, Brandslund, Ivan, Pramstaller, Peter P, Rotimi, Charles N, Christensen, Kaare, Ripatti, Samuli, Widén, Elisabeth, Hakonarson, Hakon, Grant, Struan F A, Kiemeney, Lambertus, de Graaf, Jacqueline, Loeffler, Markus, Kronenberg, Florian, Gu, Dongfeng, Erdmann, Jeanette, Schunkert, Heribert, Franks, Paul W, Linneberg, Allan, Jukema, J Wouter, Khera, Amit V, Männikkö, Minna, Jarvelin, Marjo-Riitta, Kutalik, Zoltan, Francesco, Cucca, Mook-Kanamori, Dennis O, Willems van Dijk, Ko, Watkins, Hugh, Strachan, David P, Grarup, Niels, Sever, Peter, Poulter, Neil, Huey-Herng Sheu, Wayne, Rotter, Jerome I, Dantoft, Thomas M, Karpe, Fredrik, Neville, Matt J, Timpson, Nicholas J, Cheng, Ching-Yu, Wong, Tien-Yin, Khor, Chiea Chuen, Li, Hengtong, Sabanayagam, Charumathi, Peters, Annette, Gieger, Christian, Hattersley, Andrew T, Pedersen, Nancy L, Magnusson, Patrik K E, Boomsma, Dorret I, de Geus, Eco J C, Cupples, L Adrienne, van Meurs, Joyce B J, Ikram, Arfan, Ghanbari, Mohsen, Gordon-Larsen, Penny, Huang, Wei, Kim, Young Jin, Tabara, Yasuharu, Wareham, Nicholas J, Langenberg, Claudia, Zeggini, Eleftheria, Tuomilehto, Jaakko, Kuusisto, Johanna, Laakso, Markku, Ingelsson, Erik, Abecasis, Goncalo, Chambers, John C, Kooner, Jaspal S, de Vries, Paul S, Morrison, Alanna C, Hazelhurst, Scott, Ramsay, Michèle, North, Kari E, Daviglus, Martha, Kraft, Peter, Martin, Nicholas G, Whitfield, John B, Abbas, Shahid, Saleheen, Danish, Walters, Robin G, Holmes, Michael V, Black, Corri, Smith, Blair H, Baras, Aris, Justice, Anne E, Buring, Julie E, Ridker, Paul M, Chasman, Daniel I, Kooperberg, Charles, Tamiya, Gen, Yamamoto, Masayuki, van Heel, David A, Trembath, Richard C, Wei, Wei-Qi, Jarvik, Gail P, Namjou, Bahram, Hayes, M Geoffrey, Ritchie, Marylyn D, Jousilahti, Pekka, Salomaa, Veikko, Hveem, Kristian, Åsvold, Bjørn Olav, Kubo, Michiaki, Kamatani, Yoichiro, Okada, Yukinori, Murakami, Yoshinori, Kim, Bong-Jo, Thorsteinsdottir, Unnur, Stefansson, Kari, Zhang, Jifeng, Chen, Y Eugene, Ho, Yuk-Lam, Lynch, Julie A, Tsao, Philip S, Chang, Kyong-Mi, Cho, Kelly, O'Donnell, Christopher J, Gaziano, John M, Wilson, Peter, Mohlke, Karen L, Frayling, Timothy M, Hirschhorn, Joel N, Kathiresan, Sekar, Boehnke, Michael, Million Veterans Program, Global Lipids Genetics Consortium, Struan Grant, Natarajan, Pradeep, Sun, Yan V, Morris, Andrew P, Deloukas, Panos, Peloso, Gina, Assimes, Themistocles L, Willer, Cristen J, Zhu, Xiang, Brown, Christopher D, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Life Course Epidemiology (LCE), Cardiovascular Centre (CVC), Tampere University, Clinical Medicine, Department of Clinical Chemistry, TAYS Heart Centre, Department of Clinical Physiology and Nuclear Medicine, Ramdas, Shweta, Judd, Jonathan, Graham, Sarah E, Kanoni, Stavroula, Wang, Yuxuan, Surakka, Ida, Wenz, Brandon, Clarke, Shoa L, Chesi, Alessandra, Wells, Andrew, Bhatti, Konain Fatima, Vedantam, Sailaja, Winkler, Thomas W, Locke, Adam E, Marouli, Eirini, Zajac, Greg J M, Wu, Kuan-Han H, Ntalla, Ioanna, Hui, Qin, Klarin, Derek, Hilliard, Austin T, Wang, Zeyuan, Xue, Chao, Thorleifsson, Gudmar, Helgadottir, Anna, Gudbjartsson, Daniel F, Holm, Hilma, Olafsson, Isleifur, Hwang, Mi Yeong, Han, Sohee, Akiyama, Masato, Sakaue, Saori, Terao, Chikashi, Kanai, Masahiro, Zhou, Wei, Brumpton, Ben M, Rasheed, Humaira, Havulinna, Aki S, Veturi, Yogasudha, Pacheco, Jennifer Allen, Rosenthal, Elisabeth A, Lingren, Todd, Feng, Qiping, Kullo, Iftikhar J, Narita, Akira, Takayama, Jun, Martin, Hilary C, Hunt, Karen A, Trivedi, Bhavi, Haessler, Jeffrey, Giulianini, Franco, Bradford, Yuki, Miller, Jason E, Campbell, Archie, Lin, Kuang, Millwood, Iona Y, Rasheed, Asif, Hindy, George, Faul, Jessica D, Zhao, Wei, Weir, David R, Turman, Constance, Huang, Hongyan, Graff, Mariaelisa, Choudhury, Ananyo, Sengupta, Dhriti, Mahajan, Anubha, Brown, Michael R, Zhang, Weihua, Yu, Ketian, Schmidt, Ellen M, Pandit, Anita, Gustafsson, Stefan, Yin, Xianyong, Luan, Jian'An, Zhao, Jing-Hua, Matsuda, Fumihiko, Jang, Hye-Mi, Yoon, Kyungheon, Medina-Gomez, Carolina, Pitsillides, Achillea, Hottenga, Jouke Jan, Wood, Andrew R, Ji, Yingji, Gao, Zishan, Haworth, Simon, Mitchell, Ruth E, Chai, Jin Fang, Aadahl, Mette, Bjerregaard, Anne A, Yao, Jie, Manichaikul, Ani, Lee, Wen-Jane, Hsiung, Chao Agne, Warren, Helen R, Ramirez, Julia, Bork-Jensen, Jette, Kårhus, Line L, Goel, Anuj, Sabater-Lleal, Maria, Noordam, Raymond, Mauro, Pala, Matteo, Flori, Mcdaid, Aaron F, Marques-Vidal, Pedro, Wielscher, Matthia, Trompet, Stella, Sattar, Naveed, Møllehave, Line T, Munz, Matthia, Zeng, Lingyao, Huang, Jianfeng, Yang, Bin, Poveda, Alaitz, Kurbasic, Azra, Schönherr, Sebastian, Forer, Luka, Scholz, Marku, Galesloot, Tessel E, Bradfield, Jonathan P, Ruotsalainen, Sanni E, Daw, E Warwick, Zmuda, Joseph M, Mitchell, Jonathan S, Fuchsberger, Christian, Christensen, Henry, Brody, Jennifer A, Le, Phuong, Feitosa, Mary F, Wojczynski, Mary K, Hemerich, Daiane, Preuss, Michael, Mangino, Massimo, Christofidou, Paraskevi, Verweij, Niek, Benjamins, Jan W, Engmann, Jorgen, Noah, Tsao L, Verma, Anurag, Slieker, Roderick C, Lo, Ken Sin, Zilhao, Nuno R, Kleber, Marcus E, Delgado, Graciela E, Huo, Shaofeng, Ikeda, Daisuke D, Iha, Hiroyuki, Yang, Jian, Liu, Jun, Demirkan, Ayşe, Leonard, Hampton L, Marten, Jonathan, Emmel, Carina, Schmidt, Börge, Smyth, Laura J, Cañadas-Garre, Marisa, Wang, Chaolong, Nakatochi, Masahiro, Wong, Andrew, Hutri-Kähönen, Nina, Sim, Xueling, Xia, Rui, Huerta-Chagoya, Alicia, Fernandez-Lopez, Juan Carlo, Lyssenko, Valeriya, Nongmaithem, Suraj S, Sankareswaran, Alagu, Irvin, Marguerite R, Oldmeadow, Christopher, Kim, Han-Na, Ryu, Seungho, Timmers, Paul R H J, Arbeeva, Liubov, Dorajoo, Rajkumar, Lange, Leslie A, Prasad, Gauri, Lorés-Motta, Laura, Pauper, Marc, Long, Jirong, Li, Xiaohui, Theusch, Elizabeth, Takeuchi, Fumihiko, Spracklen, Cassandra N, Loukola, Anu, Bollepalli, Sailalitha, Warner, Sophie C, Wang, Ya Xing, Wei, Wen B, Nutile, Teresa, Ruggiero, Daniela, Sung, Yun Ju, Chen, Shufeng, Liu, Fangchao, Yang, Jingyun, Kentistou, Katherine A, Banas, Bernhard, Morgan, Anna, Meidtner, Karina, Bielak, Lawrence F, Smith, Jennifer A, Hebbar, Prashantha, Farmaki, Aliki-Eleni, Hofer, Edith, Lin, Maoxuan, Concas, Maria Pina, Vaccargiu, Simona, van der Most, Peter J, Pitkänen, Niina, Cade, Brian E, van der Laan, Sander W, Chitrala, Kumaraswamy Naidu, Weiss, Stefan, Bentley, Amy R, Doumatey, Ayo P, Adeyemo, Adebowale A, Lee, Jong Young, Petersen, Eva R B, Nielsen, Aneta A, Choi, Hyeok Sun, Nethander, Maria, Freitag-Wolf, Sandra, Southam, Lorraine, Rayner, Nigel W, Wang, Carol A, Lin, Shih-Yi, Wang, Jun-Sing, Couture, Christian, Lyytikäinen, Leo-Pekka, Nikus, Kjell, Cuellar-Partida, Gabriel, Vestergaard, Henrik, Hidalgo, Bertha, Giannakopoulou, Olga, Cai, Qiuyin, Obura, Morgan O, van Setten, Jessica, He, Karen Y, Tang, Hua, Terzikhan, Natalie, Shin, Jae Hun, Jackson, Rebecca D, Reiner, Alexander P, Martin, Lisa Warsinger, Chen, Zhengming, Li, Liming, Kawaguchi, Takahisa, Thiery, Joachim, Bis, Joshua C, Launer, Lenore J, Li, Huaixing, Nalls, Mike A, Raitakari, Olli T, Ichihara, Sahoko, Wild, Sarah H, Nelson, Christopher P, Campbell, Harry, Jäger, Susanne, Nabika, Toru, Al-Mulla, Fahd, Niinikoski, Harri, Braund, Peter S, Kolcic, Ivana, Kovacs, Peter, Giardoglou, Tota, Katsuya, Tomohiro, de Kleijn, Dominique, de Borst, Gert J, Kim, Eung Kweon, Adams, Hieab H H, Ikram, M Arfan, Zhu, Xiaofeng, Asselbergs, Folkert W, Kraaijeveld, Adriaan O, Beulens, Joline W J, Shu, Xiao-Ou, Rallidis, Loukianos S, Pedersen, Oluf, Hansen, Torben, Mitchell, Paul, Hewitt, Alex W, Kähönen, Mika, Pérusse, Loui, Bouchard, Claude, Tönjes, Anke, Ida Chen, Yii-Der, Pennell, Craig E, Mori, Trevor A, Lieb, Wolfgang, Franke, Andre, Ohlsson, Clae, Mellström, Dan, Cho, Yoon Shin, Lee, Hyejin, Yuan, Jian-Min, Koh, Woon-Puay, Rhee, Sang Youl, Woo, Jeong-Taek, Heid, Iris M, Stark, Klaus J, Zimmermann, Martina E, Völzke, Henry, Homuth, Georg, Evans, Michele K, Zonderman, Alan B, Polasek, Ozren, Pasterkamp, Gerard, Hoefer, Imo E, Redline, Susan, Pahkala, Katja, Oldehinkel, Albertine J, Snieder, Harold, Biino, Ginevra, Schmidt, Reinhold, Schmidt, Helena, Bandinelli, Stefania, Dedoussis, George, Thanaraj, Thangavel Alphonse, Peyser, Patricia A, Kato, Norihiro, Schulze, Matthias B, Girotto, Giorgia, Böger, Carsten A, Jung, Bettina, Joshi, Peter K, Bennett, David A, De Jager, Philip L, Lu, Xiangfeng, Mamakou, Vasiliki, Brown, Morri, Caulfield, Mark J, Munroe, Patricia B, Guo, Xiuqing, Ciullo, Marina, Jonas, Jost B, Samani, Nilesh J, Kaprio, Jaakko, Pajukanta, Päivi, Tusié-Luna, Teresa, Aguilar-Salinas, Carlos A, Adair, Linda S, Bechayda, Sonny Augustin, de Silva, H Janaka, Wickremasinghe, Ananda R, Krauss, Ronald M, Wu, Jer-Yuarn, Zheng, Wei, den Hollander, Anneke I, Bharadwaj, Dwaipayan, Correa, Adolfo, Wilson, James G, Lind, Lar, Heng, Chew-Kiat, Nelson, Amanda E, Golightly, Yvonne M, Wilson, James F, Penninx, Brenda, Kim, Hyung-Lae, Attia, John, Scott, Rodney J, Rao, D C, Arnett, Donna K, Walker, Mark, Scott, Laura J, Koistinen, Heikki A, Chandak, Giriraj R, Mercader, Josep M, Villalpando, Clicerio Gonzalez, Orozco, Lorena, Fornage, Myriam, Tai, E Shyong, van Dam, Rob M, Lehtimäki, Terho, Chaturvedi, Nish, Yokota, Mitsuhiro, Liu, Jianjun, Reilly, Dermot F, Mcknight, Amy Jayne, Kee, Frank, Jöckel, Karl-Heinz, Mccarthy, Mark I, Palmer, Colin N A, Vitart, Veronique, Hayward, Caroline, Simonsick, Eleanor, van Duijn, Cornelia M, Jin, Zi-Bing, Lu, Fan, Hishigaki, Haretsugu, Lin, Xu, März, Winfried, Gudnason, Vilmundur, Tardif, Jean-Claude, Lettre, Guillaume, T Hart, Leen M, Elders, Petra J M, Rader, Daniel J, Damrauer, Scott M, Kumari, Meena, Kivimaki, Mika, van der Harst, Pim, Spector, Tim D, Loos, Ruth J F, Province, Michael A, Parra, Esteban J, Cruz, Miguel, Psaty, Bruce M, Brandslund, Ivan, Pramstaller, Peter P, Rotimi, Charles N, Christensen, Kaare, Ripatti, Samuli, Widén, Elisabeth, Hakonarson, Hakon, Grant, Struan F A, Kiemeney, Lambertu, de Graaf, Jacqueline, Loeffler, Marku, Kronenberg, Florian, Gu, Dongfeng, Erdmann, Jeanette, Schunkert, Heribert, Franks, Paul W, Linneberg, Allan, Jukema, J Wouter, Khera, Amit V, Männikkö, Minna, Jarvelin, Marjo-Riitta, Kutalik, Zoltan, Francesco, Cucca, Mook-Kanamori, Dennis O, Willems van Dijk, Ko, Watkins, Hugh, Strachan, David P, Grarup, Niel, Sever, Peter, Poulter, Neil, Huey-Herng Sheu, Wayne, Rotter, Jerome I, Dantoft, Thomas M, Karpe, Fredrik, Neville, Matt J, Timpson, Nicholas J, Cheng, Ching-Yu, Wong, Tien-Yin, Khor, Chiea Chuen, Li, Hengtong, Sabanayagam, Charumathi, Peters, Annette, Gieger, Christian, Hattersley, Andrew T, Pedersen, Nancy L, Magnusson, Patrik K E, Boomsma, Dorret I, de Geus, Eco J C, Cupples, L Adrienne, van Meurs, Joyce B J, Ikram, Arfan, Ghanbari, Mohsen, Gordon-Larsen, Penny, Huang, Wei, Kim, Young Jin, Tabara, Yasuharu, Wareham, Nicholas J, Langenberg, Claudia, Zeggini, Eleftheria, Tuomilehto, Jaakko, Kuusisto, Johanna, Laakso, Markku, Ingelsson, Erik, Abecasis, Goncalo, Chambers, John C, Kooner, Jaspal S, de Vries, Paul S, Morrison, Alanna C, Hazelhurst, Scott, Ramsay, Michèle, North, Kari E, Daviglus, Martha, Kraft, Peter, Martin, Nicholas G, Whitfield, John B, Abbas, Shahid, Saleheen, Danish, Walters, Robin G, Holmes, Michael V, Black, Corri, Smith, Blair H, Baras, Ari, Justice, Anne E, Buring, Julie E, Ridker, Paul M, Chasman, Daniel I, Kooperberg, Charle, Tamiya, Gen, Yamamoto, Masayuki, van Heel, David A, Trembath, Richard C, Wei, Wei-Qi, Jarvik, Gail P, Namjou, Bahram, Hayes, M Geoffrey, Ritchie, Marylyn D, Jousilahti, Pekka, Salomaa, Veikko, Hveem, Kristian, Åsvold, Bjørn Olav, Kubo, Michiaki, Kamatani, Yoichiro, Okada, Yukinori, Murakami, Yoshinori, Kim, Bong-Jo, Thorsteinsdottir, Unnur, Stefansson, Kari, Zhang, Jifeng, Chen, Y Eugene, Ho, Yuk-Lam, Lynch, Julie A, Tsao, Philip S, Chang, Kyong-Mi, Cho, Kelly, O'Donnell, Christopher J, Gaziano, John M, Wilson, Peter, Mohlke, Karen L, Frayling, Timothy M, Hirschhorn, Joel N, Kathiresan, Sekar, Boehnke, Michael, Struan Grant, Null, Natarajan, Pradeep, Sun, Yan V, Morris, Andrew P, Deloukas, Pano, Peloso, Gina, Assimes, Themistocles L, Willer, Cristen J, Zhu, Xiang, Brown, Christopher D, Epidemiology and Data Science, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, APH - Health Behaviors & Chronic Diseases, Psychiatry, APH - Mental Health, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, General practice, APH - Aging & Later Life, APH - Digital Health, Million Veterans Program, Global Lipids Genetics Consortium, Radiology & Nuclear Medicine, Internal Medicine, Epidemiology, Biological Psychology, APH - Personalized Medicine, APH - Methodology, AMS - Ageing & Vitality, and AMS - Sports

Subjects
regulatory mechanism, Vascular damage Radboud Institute for Health Sciences [Radboudumc 16], post-GWAS, Medizin, complex traits, fine-mapping, functional genomics, lipid biology, variant prioritization, Medical and Health Sciences, Polymorphism, Single Nucleotide, Sensory disorders Donders Center for Medical Neuroscience [Radboudumc 12], Article, INTEGRATIVE ANALYSIS, WIDE ASSOCIATION, 3D GENOME, VARIANTS, CHOLESTEROL, ANNOTATION, OBESITY, COMMON, LOCI, EXPRESSION, functional genomic, Genetics, 2.1 Biological and endogenous factors, Humans, Genetics(clinical), Polymorphism, Aetiology, Genetics (clinical), Genetics & Heredity, Chromatin/genetics, Genome-Wide Association Study, Genomics, Lipids/genetics, Polymorphism, Single Nucleotide/genetics, Human Genome, Million Veterans Program, Global Lipids Genetics Consortium, Single Nucleotide, Biological Sciences, Lipids, Chromatin, complex trait, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], 3111 Biomedicine, Biotechnology
Abstract

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology. Xiang Zhu is supported by the Stein Fellowship from Stanford University and Institute for Computational and Data Sciences Seed Grant from The Pennsylvania State University. C.D.B. is supported by the NIH (R01-HL133218). Funding for the Global Lipids Genetics Consortium was provided by the NIH (R01-HL127564). This research was conducted using the UK Biobank Resource under application number 24460. This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by awards 2I01BX003362-03A1 and 1I01BX004821-01A1. This publication does not represent the views of the Department of Veteran Affairs or the United States Government. We thank Bethany Klunder for administrative support. Study-specific acknowledgments are provided in the supplemental information.

Published
2022

47. Genome-wide analysis identifies genetic effects on reproductive success and ongoing natural selection at the FADS locus

Author

Mathieson, Iain, Day, Felix R, Barban, Nicola, Tropf, Felix C, Brazel, David M, EQTLGen Consortium, BIOS Consortium, Vaez, Ahmad, Van Zuydam, Natalie, Bitarello, Bárbara D, Gardner, Eugene J, Akimova, Evelina T, Azad, Ajuna, Bergmann, Sven, Bielak, Lawrence F, Boomsma, Dorret I, Bosak, Kristina, Brumat, Marco, Buring, Julie E, Cesarini, David, Chasman, Daniel I, Chavarro, Jorge E, Cocca, Massimiliano, Concas, Maria Pina, Davey Smith, George, Davies, Gail, Deary, Ian J, Esko, Tõnu, Faul, Jessica D, FinnGen Study, Franco, Oscar, Ganna, Andrea, Gaskins, Audrey J, Gelemanovic, Andrea, De Geus, Eco JC, Gieger, Christian, Girotto, Giorgia, Gopinath, Bamini, Grabe, Hans Jörgen, Gunderson, Erica P, Hayward, Caroline, He, Chunyan, Van Heemst, Diana, Hill, W David, Hoffmann, Eva R, Homuth, Georg, Hottenga, Jouke Jan, Huang, Hongyang, Hyppӧnen, Elina, Ikram, M Arfan, Jansen, Rick, Johannesson, Magnus, Kamali, Zoha, Kardia, Sharon LR, Kavousi, Maryam, Kifley, Annette, Kiiskinen, Tuomo, Kraft, Peter, Kühnel, Brigitte, Langenberg, Claudia, Liew, Gerald, Lifelines Cohort Study, Lind, Penelope A, Luan, Jian'an, Mägi, Reedik, Magnusson, Patrik KE, Mahajan, Anubha, Martin, Nicholas G, Mbarek, Hamdi, McCarthy, Mark I, McMahon, George, Medland, Sarah E, Meitinger, Thomas, Metspalu, Andres, Mihailov, Evelin, Milani, Lili, Missmer, Stacey A, Mitchell, Paul, Møllegaard, Stine, Mook-Kanamori, Dennis O, Morgan, Anna, Van Der Most, Peter J, De Mutsert, Renée, Nauck, Matthias, Nolte, Ilja M, Noordam, Raymond, Penninx, Brenda WJH, Peters, Annette, Peyser, Patricia A, Polašek, Ozren, Power, Chris, Pribisalic, Ajka, Redmond, Paul, Rich-Edwards, Janet W, Ridker, Paul M, Rietveld, Cornelius A, Ring, Susan M, Rose, Lynda M, Rueedi, Rico, Shukla, Vallari, Smith, Jennifer A, Stankovic, Stasa, Stefánsson, Kári, Stöckl, Doris, Strauch, Konstantin, Swertz, Morris A, Teumer, Alexander, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Thurik, A Roy, Timpson, Nicholas J, Turman, Constance, Uitterlinden, André G, Waldenberger, Melanie, Wareham, Nicholas J, Weir, David R, Willemsen, Gonneke, Zhao, Jing Hau, Zhao, Wei, Zhao, Yajie, Snieder, Harold, Den Hoed, Marcel, Ong, Ken K, Mills, Melinda C, Perry, John RB, Mathieson, Iain [0000-0002-4256-3982], Day, Felix R [0000-0003-3789-7651], Vaez, Ahmad [0000-0001-9048-3795], Bitarello, Bárbara D [0000-0001-7676-9367], Gardner, Eugene J [0000-0001-9671-1533], Akimova, Evelina T [0000-0001-8733-3745], Bergmann, Sven [0000-0002-6785-9034], Bielak, Lawrence F [0000-0002-3443-8030], Boomsma, Dorret I [0000-0002-7099-7972], Chasman, Daniel I [0000-0003-3357-0862], Chavarro, Jorge E [0000-0002-4436-9630], Cocca, Massimiliano [0000-0002-1127-7596], Concas, Maria Pina [0000-0003-3598-2537], Davey Smith, George [0000-0002-1407-8314], Davies, Gail [0000-0003-1120-7026], Franco, Oscar [0000-0002-4606-4929], Ganna, Andrea [0000-0002-8147-240X], Gaskins, Audrey J [0000-0001-9195-646X], Gieger, Christian [0000-0001-6986-9554], Girotto, Giorgia [0000-0003-4507-6589], Grabe, Hans Jörgen [0000-0003-3684-4208], Gunderson, Erica P [0000-0002-2039-1964], He, Chunyan [0000-0001-9443-4368], Hoffmann, Eva R [0000-0002-2588-0652], Homuth, Georg [0000-0001-6839-0605], Hottenga, Jouke Jan [0000-0002-5668-2368], Hyppӧnen, Elina [0000-0003-3670-9399], Ikram, M Arfan [0000-0003-0372-8585], Jansen, Rick [0000-0002-3333-6737], Johannesson, Magnus [0000-0001-8759-6393], Kamali, Zoha [0000-0001-6492-5887], Kavousi, Maryam [0000-0001-5976-6519], Kifley, Annette [0000-0002-3764-4905], Kiiskinen, Tuomo [0000-0002-6306-8227], Kraft, Peter [0000-0002-4472-8103], Langenberg, Claudia [0000-0002-5017-7344], Lind, Penelope A [0000-0002-3887-2598], Luan, Jian'an [0000-0003-3137-6337], Magnusson, Patrik KE [0000-0002-7315-7899], Mahajan, Anubha [0000-0001-5585-3420], Mbarek, Hamdi [0000-0002-1108-0371], Metspalu, Andres [0000-0002-3718-796X], Milani, Lili [0000-0002-5323-3102], Møllegaard, Stine [0000-0001-5676-2248], Morgan, Anna [0000-0001-6290-445X], van der Most, Peter J [0000-0001-8450-3518], Nauck, Matthias [0000-0002-6678-7964], Nolte, Ilja M [0000-0001-5047-4077], Noordam, Raymond [0000-0001-7801-809X], Peters, Annette [0000-0001-6645-0985], Peyser, Patricia A [0000-0002-9717-8459], Pribisalic, Ajka [0000-0002-3725-3728], Rietveld, Cornelius A [0000-0003-4053-1861], Ring, Susan M [0000-0003-3103-9330], Smith, Jennifer A [0000-0002-3575-5468], Stankovic, Stasa [0000-0002-6602-1379], Teumer, Alexander [0000-0002-8309-094X], Thurik, A Roy [0000-0002-0242-6908], Timpson, Nicholas J [0000-0002-7141-9189], Uitterlinden, André G [0000-0002-7276-3387], Waldenberger, Melanie [0000-0003-0583-5093], Wareham, Nicholas J [0000-0003-1422-2993], Weir, David R [0000-0002-1661-2402], Zhao, Wei [0000-0001-7388-0692], Zhao, Yajie [0000-0002-2747-0219], Snieder, Harold [0000-0003-1949-2298], den Hoed, Marcel [0000-0001-8081-428X], Ong, Ken K [0000-0003-4689-7530], Mills, Melinda C [0000-0003-1704-0001], Perry, John RB [0000-0001-6483-3771], and Apollo - University of Cambridge Repository

Subjects
Aging, Fertility, Reproduction, Humans, Female, Menopause, Selection, Genetic, FOS: Medical biotechnology, Child
Abstract

Identifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and identify alleles under present-day selection. Using data in 785,604 individuals of European ancestry, we identified 43 genomic loci associated with either number of children ever born (NEB) or childlessness. These loci span diverse aspects of reproductive biology, including puberty timing, age at first birth, sex hormone regulation, endometriosis and age at menopause. Missense variants in ARHGAP27 were associated with higher NEB but shorter reproductive lifespan, suggesting a trade-off at this locus between reproductive ageing and intensity. Other genes implicated by coding variants include PIK3IP1, ZFP82 and LRP4, and our results suggest a new role for the melanocortin 1 receptor (MC1R) in reproductive biology. As NEB is one component of evolutionary fitness, our identified associations indicate loci under present-day natural selection. Integration with data from historical selection scans highlighted an allele in the FADS1/2 gene locus that has been under selection for thousands of years and remains so today. Collectively, our findings demonstrate that a broad range of biological mechanisms contribute to reproductive success.

Published
2023

48. A genome-wide association meta-analysis identifies new childhood obesity loci

Author

Bradfield, Jonathan P, Taal, H Rob, Timpson, Nicholas J, Scherag, Andre, Lecoeur, Cecile, Warrington, Nicole M, Hypponen, Elina, Holst, Claus, Valcarcel, Beatriz, Thiering, Elisabeth, Salem, Rany M, Schumacher, Fredrick R, Cousminer, Diana L, Sleiman, Patrick MA, Zhao, Jianhua, Berkowitz, Robert I, Vimaleswaran, Karani S, Jarick, Ivonne, Pennell, Craig E, Evans, David M, St Pourcain, Beate, Berry, Diane J, Mook-Kanamori, Dennis O, Hofman, Albert, Rivadeneira, Fernando, Uitterlinden, Andre G, van Duijn, Cornelia M, van der Valk, Ralf JP, de Jongste, Johan C, Postma, Dirkje S, Boomsma, Dorret I, Gauderman, W James, Hassanein, Mohamed T, Lindgren, Cecilia M, Magi, Reedik, Boreham, Colin AG, Neville, Charlotte E, Moreno, Luis A, Elliott, Paul, Pouta, Anneli, Hartikainen, Anna-Liisa, Li, Mingyao, Raitakari, Olli, Lehtimaki, Terho, Eriksson, Johan G, Palotie, Aarno, Dallongeville, Jean, Das, Shikta, Deloukas, Panos, McMahon, George, Ring, Susan M, Kemp, John P, Buxton, Jessica L, Blakemore, Alexandra IF, Bustamante, Mariona, Guxens, Monica, Hirschhorn, Joel N, Gillman, Matthew W, Kreiner-Moller, Eskil, Bisgaard, Hans, Gilliland, Frank D, Heinrich, Joachim, Wheeler, Eleanor, Barroso, Ines, O'Rahilly, Stephen, Meirhaeghe, Aline, Sorensen, Thorkild IA, Power, Chris, Palmer, Lyle J, Hinney, Anke, Widen, Elisabeth, Farooqi, I Sadaf, McCarthy, Mark I, Froguel, Philippe, Meyre, David, Hebebrand, Johannes, Jarvelin, Marjo-Riitta, Jaddoe, Vincent WV, Smith, George Davey, Hakonarson, Hakon, and Grant, Struan FA

Subjects
Biological Sciences, Genetics, Pediatric, Nutrition, Obesity, Human Genome, Metabolic and endocrine, Oral and gastrointestinal, Stroke, Cancer, Cardiovascular, Adolescent, Adult, Body Mass Index, Case-Control Studies, Genetic Loci, Genetic Markers, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Young Adult, Early Growth Genetics Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Multiple genetic variants have been associated with adult obesity and a few with severe obesity in childhood; however, less progress has been made in establishing genetic influences on common early-onset obesity. We performed a North American, Australian and European collaborative meta-analysis of 14 studies consisting of 5,530 cases (≥95th percentile of body mass index (BMI)) and 8,318 controls (

Published
2012

49. A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol.

Author

Surakka, Ida, Isaacs, Aaron, Karssen, Lennart C, Laurila, Pirkka-Pekka P, Middelberg, Rita PS, Tikkanen, Emmi, Ried, Janina S, Lamina, Claudia, Mangino, Massimo, Igl, Wilmar, Hottenga, Jouke-Jan, Lagou, Vasiliki, van der Harst, Pim, Mateo Leach, Irene, Esko, Tõnu, Kutalik, Zoltán, Wainwright, Nicholas W, Struchalin, Maksim V, Sarin, Antti-Pekka, Kangas, Antti J, Viikari, Jorma S, Perola, Markus, Rantanen, Taina, Petersen, Ann-Kristin, Soininen, Pasi, Johansson, Asa, Soranzo, Nicole, Heath, Andrew C, Papamarkou, Theodore, Prokopenko, Inga, Tönjes, Anke, Kronenberg, Florian, Döring, Angela, Rivadeneira, Fernando, Montgomery, Grant W, Whitfield, John B, Kähönen, Mika, Lehtimäki, Terho, Freimer, Nelson B, Willemsen, Gonneke, de Geus, Eco JC, Palotie, Aarno, Sandhu, Manj S, Waterworth, Dawn M, Metspalu, Andres, Stumvoll, Michael, Uitterlinden, André G, Jula, Antti, Navis, Gerjan, Wijmenga, Cisca, Wolffenbuttel, Bruce HR, Taskinen, Marja-Riitta, Ala-Korpela, Mika, Kaprio, Jaakko, Kyvik, Kirsten O, Boomsma, Dorret I, Pedersen, Nancy L, Gyllensten, Ulf, Wilson, James F, Rudan, Igor, Campbell, Harry, Pramstaller, Peter P, Spector, Tim D, Witteman, Jacqueline CM, Eriksson, Johan G, Salomaa, Veikko, Oostra, Ben A, Raitakari, Olli T, Wichmann, H-Erich, Gieger, Christian, Järvelin, Marjo-Riitta, Martin, Nicholas G, Hofman, Albert, McCarthy, Mark I, Peltonen, Leena, van Duijn, Cornelia M, Aulchenko, Yurii S, Ripatti, Samuli, and ENGAGE Consortium

Subjects
ENGAGE Consortium, Adipose Tissue, Chromosomes, Human, Pair 4, Humans, Cholesterol, Lipids, Triglycerides, Lipoproteins, Cadherins, Waist-Hip Ratio, Risk Factors, Chromosome Mapping, Genotype, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, European Continental Ancestry Group, Body Fat Distribution, Genome-Wide Association Study, Chromosomes, Human, Pair 4, Polymorphism, Single Nucleotide, Genetics, Developmental Biology
Abstract

Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10(-9). There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.

Published
2011

50. Genetic variants associated with longitudinal changes in brain structure across the lifespan

Author

Brouwer, Rachel M, Klein, Marieke, Kremen, William S, Guimaraes, Joao P O F T, Homuth, Georg, Hottenga, Jouke-Jan, Knol, Maria J, Kwok, John B J, Le Hellard, Stephanie, Mather, Karen A, Milaneschi, Yuri, Morris, Derek W, Nöthen, Markus M., Panizzon, Matthew S, Papiol, Sergi, Rietschel, Marcella, Santoro, Marcos L, Steen, Vidar M, Stein, Jason L, Streit, Fabian, Tankard, Rick M, Teumer, Alexander, van 't Ent, Dennis, van der Meer, Dennis, Olde Loohuis, Loes M, van Eijk, Kristel R, Vassos, Evangelos, Vázquez-Bourgon, Javier, Witt, Stephanie H, Consortium, IMAGEN, Adams, Hieab H H, Agartz, Ingrid, Ames, David, Amunts, Katrin, Andreassen, Ole A, Whelan, Christopher D, Arango, Celso, Banaschewski, Tobias, Baune, Bernhard T, Belangero, Sintia I, Bokde, Arun L W, Boomsma, Dorret I, Bressan, Rodrigo A, Brodaty, Henry, Buitelaar, Jan K, Cahn, Wiepke, Aghajani, Moji, Caspers, Svenja, Cichon, Sven, Crespo-Facorro, Benedicto, Cox, Simon R, Dannlowski, Udo, Elvsåshagen, Torbjørn, Espeseth, Thomas, Falkai, Peter, Fisher, Simon E, Flor, Herta, Alloza, Clara, Fullerton, Janice M, Garavan, Hugh, Gowland, Penny A, Grabe, Hans, Hahn, Tim, Heinz, Andreas, Hillegers, Manon, Hoare, Jacqueline, Hoekstra, Pieter J, Ikram, Mohammad A, Alnæs, Dag, Jackowski, Andrea P, Jansen, Andreas, Jönsson, Erik G, Kahn, Rene S, Kircher, Tilo, Korgaonkar, Mayuresh S, Krug, Axel, Lemaitre, Herve, Malt, Ulrik F, Martinot, Jean-Luc, Artiges, Eric, McDonald, Colm, Mitchell, Philip B, Muetzel, Ryan L, Murray, Robin M, Nees, Frauke, Nenadić, Igor, Oosterlaan, Jaap, Ophoff, Roel A, Pan, Pedro M, Penninx, Brenda W J H, Ayesa-Arriola, Rosa, Poustka, Luise, Sachdev, Perminder S, Salum, Giovanni A, Schofield, Peter R, Schumann, Gunter, Shaw, Philip, Sim, Kang, Smolka, Michael N, Stein, Dan J, Trollor, Julian N, Barker, Gareth J, van den Berg, Leonard H, Veldink, Jan H, Walter, Henrik, Westlye, Lars T, Whelan, Robert, White, Tonya, Wright, Margaret J, Medland, Sarah E, Franke, Barbara, Thompson, Paul M, Grasby, Katrina L, Bastin, Mark E, Hulshoff Pol, Hilleke E, Brühl, Rüdiger, Papadopoulos Orfanos, Dimitri, Paus, Tomáš, Millenet, Sabina, Blok, Elisabet, Bøen, Erlend, Breukelaar, Isabella A, Bright, Joanna K, Buimer, Elizabeth E L, Bülow, Robin, Cannon, Dara M, Ciufolini, Simone, Crossley, Nicolas A, Schnack, Hugo G, Damatac, Christienne G, Dazzan, Paola, de Mol, Casper L, de Zwarte, Sonja M C, Desrivières, Sylvane, Díaz-Caneja, Covadonga M, Doan, Nhat Trung, Dohm, Katharina, Fröhner, Juliane H, Goltermann, Janik, Jahanshad, Neda, Grigis, Antoine, Grotegerd, Dominik, Han, Laura K M, Harris, Mathew, Hartman, Catharina A, Heany, Sarah J, Heindel, Walter, Heslenfeld, Dirk J., Hohmann, Sarah, Ittermann, Bernd, Teeuw, Jalmar, Jansen, Philip R, Janssen, Joost, Jia, Tianye, Jiang, Jiyang, Jockwitz, Christiane, Karali, Temmuz, Keeser, Daniel, Koevoets, Martijn G J C, Lenroot, Rhoshel K, Malchow, Berend, Thomopoulos, Sophia I, Mandl, René C W, Medel, Vicente, Meinert, Susanne, Morgan, Catherine A, Mühleisen, Thomas W, Nabulsi, Leila, Opel, Nils, de la Foz, Víctor Ortiz-García, Overs, Bronwyn J, Paillère Martinot, Marie-Laure, Sprooten, Emma, Redlich, Ronny, Marques, Tiago Reis, Repple, Jonathan, Roberts, Gloria, Roshchupkin, Gennady V, Setiaman, Nikita, Shumskaya, Elena, Stein, Frederike, Sudre, Gustavo, Takahashi, Shun, Franz, Carol E, Thalamuthu, Anbupalam, Tordesillas-Gutiérrez, Diana, van der Lugt, Aad, van Haren, Neeltje E M, Wardlaw, Joanna M, Wen, Wei, Westeneng, Henk-Jan, Wittfeld, Katharina, Zhu, Alyssa H, Zugman, Andre, Gogtay, Nitin, Armstrong, Nicola J, Bonfiglio, Gaia, Bralten, Janita, Dalvie, Shareefa, Davies, Gail, Di Forti, Marta, Ding, Linda, Donohoe, Gary, Forstner, Andreas J, Gonzalez-Peñas, Javier, Child and Adolescent Psychiatry / Psychology, Erasmus MC other, Anesthesiology, Epidemiology, Radiology & Nuclear Medicine, Clinical Genetics, Psychiatry, the IMAGEN Consortium, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Pediatric surgery, APH - Aging & Later Life, APH - Mental Health, APH - Digital Health, European Commission, European Research Council, Comunidad de Madrid, Instituto de Salud Carlos III, Fundación Mutua Madrileña, Fundación Alicia Koplowitz, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Clinical Cognitive Neuropsychiatry Research Program (CCNP), Psychiatry 2, RS: MHeNs - R2 - Mental Health, Psychiatrie & Neuropsychologie, Complex Trait Genetics, Cognitive Psychology, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, APH - Methodology, Clinical Neuropsychology, IBBA, General Paediatrics, ARD - Amsterdam Reproduction and Development, and Paediatrics

Subjects
Neuroinformatics, EXPRESSION, Aging, SUSCEPTIBILITY LOCI, Longevity, SURFACE-AREA, INDIVIDUAL-DIFFERENCES, All institutes and research themes of the Radboud University Medical Center, SDG 3 - Good Health and Well-being, Aging/genetics, Humans, ddc:610, GENOME-WIDE ASSOCIATION, METAANALYSIS, RISK, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], General Neuroscience, 220 Statistical Imaging Neuroscience, Longevity/genetics, Brain, Magnetic Resonance Imaging, genetics [Aging], VOLUME, RELIABILITY, sense organs, CORTICAL THICKNESS, genetics [Longevity], Genome-Wide Association Study
Abstract

et al., Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging., The ENIGMA-Plasticity Working Group is part of the ENIGMA World Aging Center, funded by NIA grants R56 AG058854 and R01 AG058854. The ENIGMA Consortium core funding was supported by NIH Consortium Grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centers of Excellence. 1000BRAINS: 1000BRAINS is a population-based cohort based on the Heinz-Nixdorf Recall Study and is supported, in part, by the German National Cohort. We thank the Heinz Nixdorf Foundation (Germany) for their generous support in terms of the Heinz Nixdorf Study. The authors are supported by the Initiative and Networking Fund of the Helmholtz Association (Svenja Caspers) and the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 785907 (Human Brain Project SGA2; Svenja Caspers, Sven Cichon and Katrin Amunts). This work was further supported by the German Federal Ministry of Education and Research (BMBF) through the Integrated Network IntegraMent (Integrated Understanding of Causes and Mechanisms in Mental Disorders) under the auspices of the e:Med Program (grant 01ZX1314A; Sven Cichon) and by the Swiss National Science Foundation (SNSF, grant 156791; Sven Cichon). The authors acknowledge grants supporting their work from the European Union’s Horizon 2020 Research and Innovation Programme (H2020/2014–2020) under grant agreements 667302 (CoCA), 728018 (Eat2beNICE), 785907 (HBP SGA2) and 772376 (EScORIAL) and the Netherlands ALS Foundation.Additional support is received from the European Community’s Seventh Framework Programme (FP7/2007—2013) under grant agreements n° 602805 (Aggressotype), n° 603016 (MATRICS), n° 602450 (IMAGEMEND) and n° 278948 (TACTICS) and from the European Community’s Horizon 2020 Programme (H2020/2014—2020) under grant agreements n° 643051 (MiND) and n° 667302 (CoCA). FP7 Ideas: the European Research Council (ERC-230374 to D.B.). This work was supported by Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012 and PI19/024), co-financed by ERDF Funds from the European Commission, ‘A way of making Europe’, CIBERSAM; Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds; European Union Seventh Framework Program under grant agreements FP7- HEALTH-2013-2.2.1-2-603196 (Project PSYSCAN) and European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement 115916, Project PRISM and grant agreement 777394, Project AIMS-2-TRIALS), Fundación Familia Alonso, Fundación Alicia Koplowitz and Fundación Mutua Madrileña. The Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313). The FP7 project MATRICS (603016). The research leading to these results also received support from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement 278948 (TACTICS), 602805 (Aggressotype), 603016 (MATRICS) and 602450 (Imagemend) and the Innovation Medicine Initiative grants 115300 (EU-AIMS) and 777394 (AIMS-2-TRIALS).PAFIP: PAFIP was supported by the Instituto de Salud Carlos III (PI14/00639, PI14/00918 and PI17/01056) and Fundación Instituto de Investigación Marqués de Valdecilla (NCT0235832 and NCT025KG Jebsen Stiftelsen and H2020 CoMorMent (847776).34363). European Union Marie Curie Research Training Network (MRTN-CT-2006-035987).

Published
2022

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