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1. Trans-ancestry epigenome-wide association meta-analysis of DNA methylation with lifetime cannabis use

Author

Fang, Fang, Quach, Bryan, Lawrence, Kaitlyn G., van Dongen, Jenny, Marks, Jesse A., Lundgren, Sara, Lin, Mingkuan, Odintsova, Veronika V., Costeira, Ricardo, Xu, Zongli, Zhou, Linran, Mandal, Meisha, Xia, Yujing, Vink, Jacqueline M., Bierut, Laura J., Ollikainen, Miina, Taylor, Jack A., Bell, Jordana T., Kaprio, Jaakko, Boomsma, Dorret I., Xu, Ke, Sandler, Dale P., Hancock, Dana B., and Johnson, Eric O.

Published
2024
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3. Metabolomic biomarkers of habitual B vitamin intakes unveil novel differentially methylated positions in the human epigenome

Author

Costeira, Ricardo, Evangelista, Laila, Wilson, Rory, Yan, Xinyu, Hellbach, Fabian, Sinke, Lucy, Christiansen, Colette, Villicaña, Sergio, Masachs, Olatz M., Tsai, Pei-Chien, Mangino, Massimo, Menni, Cristina, Berry, Sarah E., Beekman, Marian, van Heemst, Diana, Slagboom, P. Eline, Heijmans, Bastiaan T., Suhre, Karsten, Kastenmüller, Gabi, Gieger, Christian, Peters, Annette, Small, Kerrin S., Linseisen, Jakob, Waldenberger, Melanie, and Bell, Jordana T.

Published
2023
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5. Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes

Author

McAllan, Liam, Baranasic, Damir, Villicaña, Sergio, Brown, Scarlett, Zhang, Weihua, Lehne, Benjamin, Adamo, Marco, Jenkinson, Andrew, Elkalaawy, Mohamed, Mohammadi, Borzoueh, Hashemi, Majid, Fernandes, Nadia, Lambie, Nathalie, Williams, Richard, Christiansen, Colette, Yang, Youwen, Zudina, Liudmila, Lagou, Vasiliki, Tan, Sili, Castillo-Fernandez, Juan, King, James W. D., Soong, Richie, Elliott, Paul, Scott, James, Prokopenko, Inga, Cebola, Inês, Loh, Marie, Lenhard, Boris, Batterham, Rachel L., Bell, Jordana T., Chambers, John C., Kooner, Jaspal S., and Scott, William R.

Published
2023
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6. Enhanced resolution profiling in twins reveals differential methylation signatures of type 2 diabetes with links to its complications

Author

Christiansen, Colette, Potier, Louis, Martin, Tiphaine C., Villicaña, Sergio, Castillo-Fernandez, Juan E., Mangino, Massimo, Menni, Cristina, Tsai, Pei-Chien, Campbell, Purdey J., Mullin, Shelby, Ordoñana, Juan R., Monteagudo, Olga, Sachdev, Perminder S., Mather, Karen A., Trollor, Julian N., Pietilainen, Kirsi H., Ollikainen, Miina, Dalgård, Christine, Kyvik, Kirsten, Christensen, Kaare, van Dongen, Jenny, Willemsen, Gonneke, Boomsma, Dorret I., Magnusson, Patrik K.E., Pedersen, Nancy L., Wilson, Scott G., Grundberg, Elin, Spector, Tim D., and Bell, Jordana T.

Published
2024
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8. 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

9. Pooled analysis of epigenome-wide association studies of food consumption in KORA, TwinsUK and LLS

Author

Hellbach, Fabian, Sinke, Lucy, Costeira, Ricardo, Baumeister, Sebastian-Edgar, Beekman, Marian, Louca, Panayiotis, Leeming, Emily R., Mompeo, Olatz, Berry, Sarah, Wilson, Rory, Wawro, Nina, Freuer, Dennis, Hauner, Hans, Peters, Annette, Winkelmann, Juliane, Koenig, Wolfgang, Meisinger, Christa, Waldenberger, Melanie, Heijmans, Bastiaan T., Slagboom, P. Eline, Bell, Jordana T., and Linseisen, Jakob

Published
2023
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10. Epigenome-wide association study of diet quality in the Women's Health Initiative and TwinsUK cohort.

Author

Do, Whitney L, Whitsel, Eric A, Costeira, Ricardo, Masachs, Olatz M, Le Roy, Caroline I, Bell, Jordana T, Staimez, Lisa R, Stein, Aryeh D, Smith, Alicia K, Horvath, Steve, Assimes, Themistocles L, Liu, Simin, Manson, JoAnn E, Shadyab, Aladdin H, Li, Yun, Hou, Lifang, Bhatti, Parveen, Jordahl, Kristina, Narayan, KM Venkat, and Conneely, Karen N

Subjects
Human Genome, Obesity, Prevention, Nutrition, Genetics, 2.2 Factors relating to the physical environment, Aetiology, Cancer, Cardiovascular, CpG Islands, DNA Methylation, Diet, Epigenesis, Genetic, Epigenome, Female, Genome-Wide Association Study, Humans, Proteins, Women's Health, diet quality, dietary epigenetics, EWAS, Women's Health Initiative, Women’s Health Initiative, Statistics, Public Health and Health Services, Epidemiology
Abstract

BackgroundDiet quality is a risk factor for chronic disease and mortality. Differential DNA methylation across the epigenome has been associated with chronic disease risk. Whether diet quality is associated with differential methylation is unknown. This study assessed whether diet quality was associated with differential DNA methylation measured across 445 548 loci in the Women's Health Initiative (WHI) and the TwinsUK cohort.DesignThe discovery cohort consisted of 4355 women from the WHI. The replication cohort consisted of 571 mono- and dizygotic twins from the TwinsUK cohort. DNA methylation was measured in whole blood using the Illumina Infinium HumanMethylation450 Beadchip. Diet quality was assessed using the Alternative Healthy Eating Index 2010 (AHEI-2010). A meta-analysis, stratified by study cohort, was performed using generalized linear models that regressed methylation on AHEI-2010, adjusting for cell composition, chip number and location, study characteristics, principal components of genetic relatedness, age, smoking status, race/ethnicity and body mass index (BMI). Statistical significance was defined as a false discovery rate < 0.05. Significant sites were tested for replication in the TwinsUK cohort, with significant replication defined by P

Published
2021

11. 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

12. DNA methylation aging clocks: challenges and recommendations

Author

Bell, Christopher G, Lowe, Robert, Adams, Peter D, Baccarelli, Andrea A, Beck, Stephan, Bell, Jordana T, Christensen, Brock C, Gladyshev, Vadim N, Heijmans, Bastiaan T, Horvath, Steve, Ideker, Trey, Issa, Jean-Pierre J, Kelsey, Karl T, Marioni, Riccardo E, Reik, Wolf, Relton, Caroline L, Schalkwyk, Leonard C, Teschendorff, Andrew E, Wagner, Wolfgang, Zhang, Kang, and Rakyan, Vardhman K

Subjects
Human Genome, Genetics, Aging, Generic health relevance, Animals, Biological Clocks, DNA Methylation, Epigenesis, Genetic, Genome, Human, Genome-Wide Association Study, Humans, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

Epigenetic clocks comprise a set of CpG sites whose DNA methylation levels measure subject age. These clocks are acknowledged as a highly accurate molecular correlate of chronological age in humans and other vertebrates. Also, extensive research is aimed at their potential to quantify biological aging rates and test longevity or rejuvenating interventions. Here, we discuss key challenges to understand clock mechanisms and biomarker utility. This requires dissecting the drivers and regulators of age-related changes in single-cell, tissue- and disease-specific models, as well as exploring other epigenomic marks, longitudinal and diverse population studies, and non-human models. We also highlight important ethical issues in forensic age determination and predicting the trajectory of biological aging in an individual.

Published
2019

13. DNA methylation analysis is used to identify novel genetic loci associated with circulating fibrinogen levels in blood

Author

Hahn, Julie, Bressler, Jan, Domingo-Relloso, Arce, Chen, Ming-Huei, McCartney, Daniel L., Teumer, Alexander, van Dongen, Jenny, Kleber, Marcus E., Aïssi, Dylan, Swenson, Brenton R., Yao, Jie, Zhao, Wei, Huang, Jian, Xia, Yujing, Brown, Michael R., Costeira, Ricardo, de Geus, Eco J.C., Delgado, Graciela E., Dobson, Dre'Von A., Elliott, Paul, Grabe, Hans J., Guo, Xiuqing, Harris, Sarah E., Huffman, Jennifer E., Kardia, Sharon L.R., Liu, Yongmei, Lorkowski, Stefan, Marioni, Riccardo E., Nauck, Matthias, Ratliff, Scott M., Sabater-Lleal, Maria, Spector, Tim D., Suchon, Pierre, Taylor, Kent D., Thibord, Florian, Trégouët, David-Alexandre, Wiggins, Kerri L., Willemsen, Gonneke, Bell, Jordana T., Boomsma, Dorret I., Cole, Shelley A., Cox, Simon R., Dehghan, Abbas, Greinacher, Andreas, Haack, Karin, März, Winfried, Morange, Pierre-Emmanuel, Rotter, Jerome I., Sotoodehnia, Nona, Tellez-Plaza, Maria, Navas-Acien, Ana, Smith, Jennifer A., Johnson, Andrew D., Fornage, Myriam, Smith, Nicholas L., Wolberg, Alisa S., Morrison, Alanna C., and de Vries, Paul S.

Published
2023
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15. ACE2 expression in adipose tissue is associated with cardio-metabolic risk factors and cell type composition—implications for COVID-19

Author

El-Sayed Moustafa, Julia S., Jackson, Anne U., Brotman, Sarah M., Guan, Li, Villicaña, Sergio, Roberts, Amy L., Zito, Antonino, Bonnycastle, Lori, Erdos, Michael R., Narisu, Narisu, Stringham, Heather M., Welch, Ryan, Yan, Tingfen, Lakka, Timo, Parker, Stephen, Tuomilehto, Jaakko, Seow, Jeffrey, Graham, Carl, Huettner, Isabella, Acors, Sam, Kouphou, Neophytos, Wadge, Samuel, Duncan, Emma L., Steves, Claire J., Doores, Katie J., Malim, Michael H., Collins, Francis S., Pajukanta, Päivi, Boehnke, Michael, Koistinen, Heikki A., Laakso, Markku, Falchi, Mario, Bell, Jordana T., Scott, Laura J., Mohlke, Karen L., and Small, Kerrin S.

Published
2022
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16. Author Correction: 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, de Wit, Harriet, Davis, Lea K, MacKillop, James, 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, Drug Abuse (NIDA only), Human Genome, Brain Disorders, Serious Mental Illness, Genetics, Schizophrenia, Substance Misuse, Mental Health, 2.1 Biological and endogenous factors, Aetiology, Mental health, 23andMe Research Team, Substance Use Disorders Working Group of the Psychiatric Genomics Consortium, International Cannabis Consortium, Neurosciences, Cognitive Sciences, Neurology & Neurosurgery, Biological psychology
Abstract

Several occurrences of the word 'schizophrenia' have been re-worded as 'liability to schizophrenia' or 'schizophrenia risk', including in the title, which should have been "GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability," as well as in Supplementary Figures 1-10 and Supplementary Tables 7-10, to more accurately reflect the findings of the work.

Published
2019

17. 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

18. Adipose methylome integrative-omic analyses reveal genetic and dietary metabolic health drivers and insulin resistance classifiers

Author

Christiansen, Colette, Tomlinson, Max, Eliot, Melissa, Nilsson, Emma, Costeira, Ricardo, Xia, Yujing, Villicaña, Sergio, Mompeo, Olatz, Wells, Philippa, Castillo-Fernandez, Juan, Potier, Louis, Vohl, Marie-Claude, Tchernof, Andre, Moustafa, Julia El-Sayed, Menni, Cristina, Steves, Claire J., Kelsey, Karl, Ling, Charlotte, Grundberg, Elin, Small, Kerrin S., and Bell, Jordana T.

Published
2022
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19. DNA methylation signature of chronic low-grade inflammation and its role in cardio-respiratory diseases

Author

Wielscher, Matthias, Mandaviya, Pooja R., Kuehnel, Brigitte, Joehanes, Roby, Mustafa, Rima, Robinson, Oliver, Zhang, Yan, Bodinier, Barbara, Walton, Esther, Mishra, Pashupati P., Schlosser, Pascal, Wilson, Rory, Tsai, Pei-Chien, Palaniswamy, Saranya, Marioni, Riccardo E., Fiorito, Giovanni, Cugliari, Giovanni, Karhunen, Ville, Ghanbari, Mohsen, Psaty, Bruce M., Loh, Marie, Bis, Joshua C., Lehne, Benjamin, Sotoodehnia, Nona, Deary, Ian J., Chadeau-Hyam, Marc, Brody, Jennifer A., Cardona, Alexia, Selvin, Elizabeth, Smith, Alicia K., Miller, Andrew H., Torres, Mylin A., Marouli, Eirini, Gào, Xin, van Meurs, Joyce B. J., Graf-Schindler, Johanna, Rathmann, Wolfgang, Koenig, Wolfgang, Peters, Annette, Weninger, Wolfgang, Farlik, Matthias, Zhang, Tao, Chen, Wei, Xia, Yujing, Teumer, Alexander, Nauck, Matthias, Grabe, Hans J., Doerr, Macus, Lehtimäki, Terho, Guan, Weihua, Milani, Lili, Tanaka, Toshiko, Fisher, Krista, Waite, Lindsay L., Kasela, Silva, Vineis, Paolo, Verweij, Niek, van der Harst, Pim, Iacoviello, Licia, Sacerdote, Carlotta, Panico, Salvatore, Krogh, Vittorio, Tumino, Rosario, Tzala, Evangelia, Matullo, Giuseppe, Hurme, Mikko A., Raitakari, Olli T., Colicino, Elena, Baccarelli, Andrea A., Kähönen, Mika, Herzig, Karl-Heinz, Li, Shengxu, Conneely, Karen N., Kooner, Jaspal S., Köttgen, Anna, Heijmans, Bastiaan T., Deloukas, Panos, Relton, Caroline, Ong, Ken K., Bell, Jordana T., Boerwinkle, Eric, Elliott, Paul, Brenner, Hermann, Beekman, Marian, Levy, Daniel, Waldenberger, Melanie, Chambers, John C., Dehghan, Abbas, and Järvelin, Marjo-Riitta

Published
2022
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20. 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

21. 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

22. GWAS of epigenetic aging rates in blood reveals a critical role for TERT.

Author

Lu, Ake T, Xue, Luting, Salfati, Elias L, Chen, Brian H, Ferrucci, Luigi, Levy, Daniel, Joehanes, Roby, Murabito, Joanne M, Kiel, Douglas P, Tsai, Pei-Chien, Yet, Idil, Bell, Jordana T, Mangino, Massimo, Tanaka, Toshiko, McRae, Allan F, Marioni, Riccardo E, Visscher, Peter M, Wray, Naomi R, Deary, Ian J, Levine, Morgan E, Quach, Austin, Assimes, Themistocles, Tsao, Philip S, Absher, Devin, Stewart, James D, Li, Yun, Reiner, Alex P, Hou, Lifang, Baccarelli, Andrea A, Whitsel, Eric A, Aviv, Abraham, Cardona, Alexia, Day, Felix R, Wareham, Nicholas J, Perry, John RB, Ong, Ken K, Raj, Kenneth, Lunetta, Kathryn L, and Horvath, Steve

Subjects
Leukocytes, Cells, Cultured, Telomere, Fibroblasts, Humans, Telomerase, DNA Methylation, Epigenesis, Genetic, CpG Islands, Aging, Menopause, Menarche, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Female, Male, Genome-Wide Association Study, Young Adult, Mendelian Randomization Analysis, Cells, Cultured, Epigenesis, Genetic, and over
Abstract

DNA methylation age is an accurate biomarker of chronological age and predicts lifespan, but its underlying molecular mechanisms are unknown. In this genome-wide association study of 9907 individuals, we find gene variants mapping to five loci associated with intrinsic epigenetic age acceleration (IEAA) and gene variants in three loci associated with extrinsic epigenetic age acceleration (EEAA). Mendelian randomization analysis suggests causal influences of menarche and menopause on IEAA and lipoproteins on IEAA and EEAA. Variants associated with longer leukocyte telomere length (LTL) in the telomerase reverse transcriptase gene (TERT) paradoxically confer higher IEAA (P

Published
2018

23. 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, BIOS Consortium, 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, Paus, Tomáš, Horvath, Steve, O'Connell, Jeffrey R, Guo, Xiuqing, Pausova, Zdenka, Assimes, Themistocles L, Sotoodehnia, Nona, Smith, Jennifer A, Arnett, Donna K, Deary, Ian J, Baccarelli, Andrea A, Bell, Jordana T, Whitsel, Eric, Dehghan, Abbas, Levy, Daniel, and Fornage, Myriam

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

24. Meta-analysis of epigenome-wide association studies of carotid intima-media thickness

Author

Portilla-Fernández, Eliana, Hwang, Shih-Jen, Wilson, Rory, Maddock, Jane, Hill, W. David, Teumer, Alexander, Mishra, Pashupati P., Brody, Jennifer A., Joehanes, Roby, Ligthart, Symen, Ghanbari, Mohsen, Kavousi, Maryam, Roks, Anton J. M., Danser, A. H. Jan, Levy, Daniel, Peters, Annette, Ghasemi, Sahar, Schminke, Ulf, Dörr, Marcus, Grabe, Hans J., Lehtimäki, Terho, Kähönen, Mika, Hurme, Mikko A., Bartz, Traci M., Sotoodehnia, Nona, Bis, Joshua C., Thiery, Joachim, Koenig, Wolfgang, Ong, Ken K., Bell, Jordana T., Meisinger, Christine, Wardlaw, Joanna M., Starr, John M., Seissler, Jochen, Then, Cornelia, Rathmann, Wolfgang, Ikram, M. Arfan, Psaty, Bruce M., Raitakari, Olli T., Völzke, Henry, Deary, Ian J., Wong, Andrew, Waldenberger, Melanie, O’Donnell, Christopher J., and Dehghan, Abbas

Published
2021
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25. Heritable components of the human fecal microbiome are associated with visceral fat

Author

Beaumont, Michelle, Goodrich, Julia K, Jackson, Matthew A, Yet, Idil, Davenport, Emily R, Vieira-Silva, Sara, Debelius, Justine, Pallister, Tess, Mangino, Massimo, Raes, Jeroen, Knight, Rob, Clark, Andrew G, Ley, Ruth E, Spector, Tim D, and Bell, Jordana T

Subjects
Human Genome, Aging, Genetics, Clinical Research, Obesity, Nutrition, Prevention, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Oral and gastrointestinal, Metabolic and endocrine, Cancer, Stroke, Fecal microbiome, Visceral fat, Heritability, Genetic association, Twins, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

BackgroundVariation in the human fecal microbiota has previously been associated with body mass index (BMI). Although obesity is a global health burden, the accumulation of abdominal visceral fat is the specific cardio-metabolic disease risk factor. Here, we explore links between the fecal microbiota and abdominal adiposity using body composition as measured by dual-energy X-ray absorptiometry in a large sample of twins from the TwinsUK cohort, comparing fecal 16S rRNA diversity profiles with six adiposity measures.ResultsWe profile six adiposity measures in 3666 twins and estimate their heritability, finding novel evidence for strong genetic effects underlying visceral fat and android/gynoid ratio. We confirm the association of lower diversity of the fecal microbiome with obesity and adiposity measures, and then compare the association between fecal microbial composition and the adiposity phenotypes in a discovery subsample of twins. We identify associations between the relative abundances of fecal microbial operational taxonomic units (OTUs) and abdominal adiposity measures. Most of these results involve visceral fat associations, with the strongest associations between visceral fat and Oscillospira members. Using BMI as a surrogate phenotype, we pursue replication in independent samples from three population-based cohorts including American Gut, Flemish Gut Flora Project and the extended TwinsUK cohort. Meta-analyses across the replication samples indicate that 8 OTUs replicate at a stringent threshold across all cohorts, while 49 OTUs achieve nominal significance in at least one replication sample. Heritability analysis of the adiposity-associated microbial OTUs prompted us to assess host genetic-microbe interactions at obesity-associated human candidate loci. We observe significant associations of adiposity-OTU abundances with host genetic variants in the FHIT, TDRG1 and ELAVL4 genes, suggesting a potential role for host genes to mediate the link between the fecal microbiome and obesity.ConclusionsOur results provide novel insights into the role of the fecal microbiota in cardio-metabolic disease with clear potential for prevention and novel therapies.

Published
2016

29. DNA methylation-based measures of biological age: meta-analysis predicting time to death

Author

Chen, Brian H, Marioni, Riccardo E, Colicino, Elena, Peters, Marjolein J, Ward-Caviness, Cavin K, Tsai, Pei-Chien, Roetker, Nicholas S, Just, Allan C, Demerath, Ellen W, Guan, Weihua, Bressler, Jan, Fornage, Myriam, Studenski, Stephanie, Vandiver, Amy R, Moore, Ann Zenobia, Tanaka, Toshiko, Kiel, Douglas P, Liang, Liming, Vokonas, Pantel, Schwartz, Joel, Lunetta, Kathryn L, Murabito, Joanne M, Bandinelli, Stefania, Hernandez, Dena G, Melzer, David, Nalls, Michael, Pilling, Luke C, Price, Timothy R, Singleton, Andrew B, Gieger, Christian, Holle, Rolf, Kretschmer, Anja, Kronenberg, Florian, Kunze, Sonja, Linseisen, Jakob, Meisinger, Christine, Rathmann, Wolfgang, Waldenberger, Melanie, Visscher, Peter M, Shah, Sonia, Wray, Naomi R, McRae, Allan F, Franco, Oscar H, Hofman, Albert, Uitterlinden, André G, Absher, Devin, Assimes, Themistocles, Levine, Morgan E, Lu, Ake T, Tsao, Philip S, Hou, Lifang, Manson, JoAnn E, Carty, Cara L, LaCroix, Andrea Z, Reiner, Alexander P, Spector, Tim D, Feinberg, Andrew P, Levy, Daniel, Baccarelli, Andrea, van Meurs, Joyce, Bell, Jordana T, Peters, Annette, Deary, Ian J, Pankow, James S, Ferrucci, Luigi, and Horvath, Steve

Subjects
Biological Sciences, Genetics, Clinical Research, Prevention, Good Health and Well Being, Aging, DNA Methylation, Epigenesis, Genetic, Female, Humans, Logistic Models, Male, Mortality, Racial Groups, Risk Factors, Survival Analysis, T-Lymphocyte Subsets, all-cause mortality, lifespan, epigenetics, epigenetic clock, DNA methylation, mortality, Biochemistry and cell biology, Clinical sciences
Abstract

Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2x10-9), independent of chronological age, even after adjusting for additional risk factors (p

Published
2016

30. Genetic Determinants of the Gut Microbiome in UK Twins

Author

Goodrich, Julia K, Davenport, Emily R, Beaumont, Michelle, Jackson, Matthew A, Knight, Rob, Ober, Carole, Spector, Tim D, Bell, Jordana T, Clark, Andrew G, and Ley, Ruth E

Subjects
Microbiology, Biological Sciences, Genetics, Biotechnology, Clinical Research, Nutrition, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Base Sequence, Female, Gastrointestinal Microbiome, Genetic Variation, Humans, Male, Microbial Consortia, Twins, United Kingdom, Medical Microbiology, Immunology, Biochemistry and cell biology, Medical microbiology
Abstract

Studies in mice and humans have revealed intriguing associations between host genetics and the microbiome. Here we report a 16S rRNA-based analysis of the gut microbiome in 1,126 twin pairs, a subset of which was previously reported. Tripling the sample narrowed the confidence intervals around heritability estimates and uncovered additional heritable taxa, some of which are validated in other studies. Repeat sampling of subjects showed heritable taxa to be temporally stable. A candidate gene approach uncovered associations between heritable taxa and genes related to diet, metabolism, and olfaction. We replicate an association between Bifidobacterium and the lactase (LCT) gene locus and identify an association between the host gene ALDH1L1 and the bacteria SHA-98, suggesting a link between formate production and blood pressure. Additional genes detected are involved in barrier defense and self/non-self recognition. Our results indicate that diet-sensing, metabolism, and immune defense are important drivers of human-microbiome co-evolution.

Published
2016

31. Identical twins carry a persistent epigenetic signature of early genome programming

Author

van Dongen, Jenny, Gordon, Scott D., McRae, Allan F., Odintsova, Veronika V., Mbarek, Hamdi, Breeze, Charles E., Sugden, Karen, Lundgren, Sara, Castillo-Fernandez, Juan E., Hannon, Eilis, Moffitt, Terrie E., Hagenbeek, Fiona A., van Beijsterveldt, Catharina E. M., Jan Hottenga, Jouke, Tsai, Pei-Chien, Min, Josine L., Hemani, Gibran, Ehli, Erik A., Paul, Franziska, Stern, Claudio D., Heijmans, Bastiaan T., Slagboom, P. Eline, Daxinger, Lucia, van der Maarel, Silvère M., de Geus, Eco J. C., Willemsen, Gonneke, Montgomery, Grant W., Reversade, Bruno, Ollikainen, Miina, Kaprio, Jaakko, Spector, Tim D., Bell, Jordana T., Mill, Jonathan, Caspi, Avshalom, Martin, Nicholas G., and Boomsma, Dorret I.

Published
2021
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32. Validating biomarkers and models for epigenetic inference of alcohol consumption from blood

Author

Maas, Silvana C. E., Vidaki, Athina, Teumer, Alexander, Costeira, Ricardo, Wilson, Rory, van Dongen, Jenny, Beekman, Marian, Völker, Uwe, Grabe, Hans J., Kunze, Sonja, Ladwig, Karl-Heinz, van Meurs, Joyce B. J., Uitterlinden, André G., Voortman, Trudy, Boomsma, Dorret I., Slagboom, P. Eline, van Heemst, Diana, van der Kallen, Carla J. H., van den Berg, Leonard H., Waldenberger, Melanie, Völzke, Henry, Peters, Annette, Bell, Jordana T., Ikram, M. Arfan, Ghanbari, Mohsen, and Kayser, Manfred

Published
2021
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33. Epigenome-wide association meta-analysis of DNA methylation with coffee and tea consumption

Author

Karabegović, Irma, Portilla-Fernandez, Eliana, Li, Yang, Ma, Jiantao, Maas, Silvana C. E., Sun, Daokun, Hu, Emily A., Kühnel, Brigitte, Zhang, Yan, Ambatipudi, Srikant, Fiorito, Giovanni, Huang, Jian, Castillo-Fernandez, Juan E., Wiggins, Kerri L., de Klein, Niek, Grioni, Sara, Swenson, Brenton R., Polidoro, Silvia, Treur, Jorien L., Cuenin, Cyrille, Tsai, Pei-Chien, Costeira, Ricardo, Chajes, Veronique, Braun, Kim, Verweij, Niek, Kretschmer, Anja, Franke, Lude, van Meurs, Joyce B. J., Uitterlinden, André G., de Knegt, Robert J., Ikram, M. Arfan, Dehghan, Abbas, Peters, Annette, Schöttker, Ben, Gharib, Sina A., Sotoodehnia, Nona, Bell, Jordana T., Elliott, Paul, Vineis, Paolo, Relton, Caroline, Herceg, Zdenko, Brenner, Hermann, Waldenberger, Melanie, Rebholz, Casey M., Voortman, Trudy, Pan, Qiuwei, Fornage, Myriam, Levy, Daniel, Kayser, Manfred, and Ghanbari, Mohsen

Published
2021
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35. A multi-ethnic epigenome-wide association study of leukocyte DNA methylation and blood lipids

Author

Jhun, Min-A, Mendelson, Michael, Wilson, Rory, Gondalia, Rahul, Joehanes, Roby, Salfati, Elias, Zhao, Xiaoping, Braun, Kim Valeska Emilie, Do, Anh Nguyet, Hedman, Åsa K., Zhang, Tao, Carnero-Montoro, Elena, Shen, Jincheng, Bartz, Traci M., Brody, Jennifer A., Montasser, May E., O’Connell, Jeff R., Yao, Chen, Xia, Rui, Boerwinkle, Eric, Grove, Megan, Guan, Weihua, Liliane, Pfeiffer, Singmann, Paula, Müller-Nurasyid, Martina, Meitinger, Thomas, Gieger, Christian, Peters, Annette, Zhao, Wei, Ware, Erin B., Smith, Jennifer A., Dhana, Klodian, van Meurs, Joyce, Uitterlinden, Andre, Ikram, Mohammad Arfan, Ghanbari, Mohsen, Zhi, Deugi, Gustafsson, Stefan, Lind, Lars, Li, Shengxu, Sun, Dianjianyi, Spector, Tim D., Chen, Yii-der Ida, Damcott, Coleen, Shuldiner, Alan R., Absher, Devin M., Horvath, Steve, Tsao, Philip S., Kardia, Sharon, Psaty, Bruce M., Sotoodehnia, Nona, Bell, Jordana T., Ingelsson, Erik, Chen, Wei, Dehghan, Abbas, Arnett, Donna K., Waldenberger, Melanie, Hou, Lifang, Whitsel, Eric A., Baccarelli, Andrea, Levy, Daniel, Fornage, Myriam, Irvin, Marguerite R., and Assimes, Themistocles L.

Published
2021
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38. Publisher Correction: A multi-ethnic epigenome-wide association study of leukocyte DNA methylation and blood lipids

Author

Jhun, Min-A, Mendelson, Michael, Wilson, Rory, Gondalia, Rahul, Joehanes, Roby, Salfati, Elias, Zhao, Xiaoping, Braun, Kim Valeska Emilie, Do, Anh Nguyet, Hedman, Åsa K., Zhang, Tao, Carnero-Montoro, Elena, Shen, Jincheng, Bartz, Traci M., Brody, Jennifer A., Montasser, May E., O’Connell, Jeff R., Yao, Chen, Xia, Rui, Boerwinkle, Eric, Grove, Megan, Guan, Weihua, Liliane, Pfeiffer, Singmann, Paula, Müller-Nurasyid, Martina, Meitinger, Thomas, Gieger, Christian, Peters, Annette, Zhao, Wei, Ware, Erin B., Smith, Jennifer A., Dhana, Klodian, van Meurs, Joyce, Uitterlinden, Andre, Ikram, Mohammad Arfan, Ghanbari, Mohsen, Zhi, Deugi, Gustafsson, Stefan, Lind, Lars, Li, Shengxu, Sun, Dianjianyi, Spector, Tim D., Chen, Yii-der Ida, Damcott, Coleen, Shuldiner, Alan R., Absher, Devin M., Horvath, Steve, Tsao, Philip S., Kardia, Sharon, Psaty, Bruce M., Sotoodehnia, Nona, Bell, Jordana T., Ingelsson, Erik, Chen, Wei, Dehghan, Abbas, Arnett, Donna K., Waldenberger, Melanie, Hou, Lifang, Whitsel, Eric A., Baccarelli, Andrea, Levy, Daniel, Fornage, Myriam, Irvin, Marguerite R., and Assimes, Themistocles L.

Published
2021
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40. Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements

Author

Zhang, Weiwei, Spector, Tim D, Deloukas, Panos, Bell, Jordana T, and Engelhardt, Barbara E

Subjects
Quantitative Biology - Genomics
Abstract

Background: Recent assays for individual-specific genome-wide DNA methylation profiles have enabled epigenome-wide association studies to identify specific CpG sites associated with a phenotype. Computational prediction of CpG site-specific methylation levels is important, but current approaches tackle average methylation within a genomic locus and are often limited to specific genomic regions. Results: We characterize genome-wide DNA methylation patterns, and show that correlation among CpG sites decays rapidly, making predictions solely based on neighboring sites challenging. We built a random forest classifier to predict CpG site methylation levels using as features neighboring CpG site methylation levels and genomic distance, and co-localization with coding regions, CGIs, and regulatory elements from the ENCODE project, among others. Our approach achieves 91% -- 94% prediction accuracy of genome-wide methylation levels at single CpG site precision. The accuracy increases to 98% when restricted to CpG sites within CGIs. Our classifier outperforms state-of-the-art methylation classifiers and identifies features that contribute to prediction accuracy: neighboring CpG site methylation status, CpG island status, co-localized DNase I hypersensitive sites, and specific transcription factor binding sites were found to be most predictive of methylation levels. Conclusions: Our observations of DNA methylation patterns led us to develop a classifier to predict site-specific methylation levels that achieves the best DNA methylation predictive accuracy to date. Furthermore, our method identified genomic features that interact with DNA methylation, elucidating mechanisms involved in DNA methylation modification and regulation, and linking different epigenetic processes.

Published
2013
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42. Contributors

Author

Abramson, Michael J., primary, Armstrong, Nicola J., additional, Barrès, Romain, additional, Bell, Jordana T., additional, Boomsma, Dorret I., additional, Calais-Ferreira, Lucas, additional, Candler, T., additional, Cao, Weihua, additional, Christiansen, Colette, additional, Cortessis, Victoria K., additional, Cozen, Wendy, additional, van Dongen, Jenny, additional, Forgo, Bianka, additional, Gao, Wenjing, additional, Guo, Yuming, additional, Hernyes, Anita, additional, Hopper, John L., additional, Investigators, kConFab, additional, Jokkel, Zsofia, additional, Kim, Eunae, additional, Kim, Hakyung, additional, Kühnen, P., additional, Kurushima, Yuko, additional, Lam, Esther, additional, Lee, Soo Ji, additional, Li, Liming, additional, Li, Shuai, additional, Minică, Camelia C., additional, Neale, Michael C., additional, Odintsova, Veronika V., additional, Persely, Aliz, additional, Piroska, Marton, additional, Potier, Louis, additional, Prentice, A.M., additional, Scurrah, Katrina, additional, Silva, Mihiri J., additional, Silver, M.J., additional, Sørensen, Thorkild I.A., additional, Southey, Melissa C., additional, Stirzaker, Clare, additional, Sung, Joohon, additional, Szabo, Helga, additional, Szalontai, Laszlo, additional, Tarnoki, Adam Domonkos, additional, Tarnoki, David Laszlo, additional, Wu, Zhentian, additional, Xu, Rongbin, additional, and Ye, Zhoufeng, additional

Published
2021
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43. Human Genetics Shape the Gut Microbiome

Author

Goodrich, Julia K, Waters, Jillian L, Poole, Angela C, Sutter, Jessica L, Koren, Omry, Blekhman, Ran, Beaumont, Michelle, Van Treuren, William, Knight, Rob, Bell, Jordana T, Spector, Timothy D, Clark, Andrew G, and Ley, Ruth E

Subjects
Microbiology, Biological Sciences, Genetics, Human Genome, Obesity, Nutrition, 2.1 Biological and endogenous factors, Aetiology, Oral and gastrointestinal, Animals, Bacteria, Body Mass Index, Feces, Female, Gastrointestinal Tract, Germ-Free Life, Humans, Male, Mice, Microbiota, Twins, Dizygotic, Twins, Monozygotic, Medical and Health Sciences, Developmental Biology, Biological sciences, Biomedical and clinical sciences
Abstract

Host genetics and the gut microbiome can both influence metabolic phenotypes. However, whether host genetic variation shapes the gut microbiome and interacts with it to affect host phenotype is unclear. Here, we compared microbiotas across >1,000 fecal samples obtained from the TwinsUK population, including 416 twin pairs. We identified many microbial taxa whose abundances were influenced by host genetics. The most heritable taxon, the family Christensenellaceae, formed a co-occurrence network with other heritable Bacteria and with methanogenic Archaea. Furthermore, Christensenellaceae and its partners were enriched in individuals with low body mass index (BMI). An obese-associated microbiome was amended with Christensenella minuta, a cultured member of the Christensenellaceae, and transplanted to germ-free mice. C. minuta amendment reduced weight gain and altered the microbiome of recipient mice. Our findings indicate that host genetics influence the composition of the human gut microbiome and can do so in ways that impact host metabolism.

Published
2014

44. Epigenome-wide Association Study Shows Differential DNA Methylation of MDC1, KLF9, and CUTA in Autoimmune Thyroid Disease.

Author

Lafontaine, Nicole, Shore, Christopher J, Campbell, Purdey J, Mullin, Benjamin H, Brown, Suzanne J, Panicker, Vijay, Dudbridge, Frank, Brix, Thomas H, Hegedüs, Laszlo, Wilson, Scott G, Bell, Jordana T, and Walsh, John P

Abstract

Context Autoimmune thyroid disease (AITD) includes Graves disease (GD) and Hashimoto disease (HD), which often run in the same family. AITD etiology is incompletely understood: Genetic factors may account for up to 75% of phenotypic variance, whereas epigenetic effects (including DNA methylation [DNAm]) may contribute to the remaining variance (eg, why some individuals develop GD and others HD). Objective This work aimed to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) comparing GD to HD. Methods Whole-blood DNAm was measured across the genome using the Infinium MethylationEPIC array in 32 Australian patients with GD and 30 with HD (discovery cohort) and 32 Danish patients with GD and 32 with HD (replication cohort). Linear mixed models were used to test for differences in quantile-normalized β values of DNAm between GD and HD and data were later meta-analyzed. Comb-p software was used to identify DMRs. Results We identified epigenome-wide significant differences (P < 9E-8) and replicated (P <.05) 2 DMPs between GD and HD (cg06315208 within MDC1 and cg00049440 within KLF9). We identified and replicated a DMR within CUTA (5 CpGs at 6p21.32). We also identified 64 DMPs and 137 DMRs in the meta-analysis. Conclusion Our study reveals differences in DNAm between GD and HD, which may help explain why some people develop GD and others HD and provide a link to environmental risk factors. Additional research is needed to advance understanding of the role of DNAm in AITD and investigate its prognostic and therapeutic potential. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Epigenome-wide Association Study Shows Differential DNA Methylation of MDC1, KLF9, and CUTA in Autoimmune Thyroid Disease

Author

Lafontaine, Nicole, primary, Shore, Christopher J, additional, Campbell, Purdey J, additional, Mullin, Benjamin H, additional, Brown, Suzanne J, additional, Panicker, Vijay, additional, Dudbridge, Frank, additional, Brix, Thomas H, additional, Hegedüs, Laszlo, additional, Wilson, Scott G, additional, Bell, Jordana T, additional, and Walsh, John P, additional

Published
2023
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46. Trans-ancestry epigenome-wide association meta-analysis of DNA methylation with lifetime cannabis use

Author

Fang, Fang, primary, Quach, Bryan, additional, Lawrence, Kaitlyn G., additional, van Dongen, Jenny, additional, Marks, Jesse A., additional, Lundgren, Sara, additional, Lin, Mingkuan, additional, Odintsova, Veronika V., additional, Costeira, Ricardo, additional, Xu, Zongli, additional, Zhou, Linran, additional, Mandal, Meisha, additional, Xia, Yujing, additional, Vink, Jacqueline M., additional, Bierut, Laura J., additional, Ollikainen, Miina, additional, Taylor, Jack A., additional, Bell, Jordana T., additional, Kaprio, Jaakko, additional, Boomsma, Dorret I., additional, Xu, Ke, additional, Sandler, Dale P., additional, Hancock, Dana B., additional, and Johnson, Eric O., additional

Published
2023
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47. A Fecal Metabolite Signature of Impaired Fasting Glucose: Results From Two Independent Population-Based Cohorts

Author

Nogal, Ana, primary, Tettamanzi, Francesca, additional, Dong, Qiuling, additional, Louca, Panayiotis, additional, Visconti, Alessia, additional, Christiansen, Colette, additional, Breuninger, Taylor, additional, Linseisen, Jakob, additional, Grallert, Harald, additional, Wawro, Nina, additional, Asnicar, Francesco, additional, Wong, Kari, additional, Baleanu, Andrei-Florin, additional, Michelotti, Gregory A., additional, Segata, Nicola, additional, Falchi, Mario, additional, Peters, Annette, additional, Franks, Paul W., additional, Bagnardi, Vincenzo, additional, Spector, Tim D., additional, Bell, Jordana T., additional, Gieger, Christian, additional, Valdes, Ana M., additional, and Menni, Cristina, additional

Published
2023
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48. The human gut and groundwater harbor non-photosynthetic bacteria belonging to a new candidate phylum sibling to Cyanobacteria.

Author

Di Rienzi, Sara C, Sharon, Itai, Wrighton, Kelly C, Koren, Omry, Hug, Laura A, Thomas, Brian C, Goodrich, Julia K, Bell, Jordana T, Spector, Timothy D, Banfield, Jillian F, and Ley, Ruth E

Subjects
Intestines, Humans, Cyanobacteria, RNA, Ribosomal, 16S, Phylogeny, Photosynthesis, Anaerobiosis, Fermentation, Genes, Bacterial, Light, Groundwater, Human, Melainabacteria, Other, human gut, nitrogen fixation, photosynthesis, subsurface, RNA, Ribosomal, 16S, Genes, Bacterial, Biochemistry and Cell Biology
Abstract

Cyanobacteria were responsible for the oxygenation of the ancient atmosphere; however, the evolution of this phylum is enigmatic, as relatives have not been characterized. Here we use whole genome reconstruction of human fecal and subsurface aquifer metagenomic samples to obtain complete genomes for members of a new candidate phylum sibling to Cyanobacteria, for which we propose the designation 'Melainabacteria'. Metabolic analysis suggests that the ancestors to both lineages were non-photosynthetic, anaerobic, motile, and obligately fermentative. Cyanobacterial light sensing may have been facilitated by regulators present in the ancestor of these lineages. The subsurface organism has the capacity for nitrogen fixation using a nitrogenase distinct from that in Cyanobacteria, suggesting nitrogen fixation evolved separately in the two lineages. We hypothesize that Cyanobacteria split from Melainabacteria prior or due to the acquisition of oxygenic photosynthesis. Melainabacteria remained in anoxic zones and differentiated by niche adaptation, including for symbiosis in the mammalian gut. DOI:http://dx.doi.org/10.7554/eLife.01102.001.

Published
2013

49. Leveraging osteoclast genetic regulatory data to identify genes with a role in osteoarthritis

Author

Mullin, Benjamin H, primary, Zhu, Kun, additional, Brown, Suzanne J, additional, Mullin, Shelby, additional, Dudbridge, Frank, additional, Pavlos, Nathan J, additional, Richards, J Brent, additional, Grundberg, Elin, additional, Bell, Jordana T, additional, Zeggini, Eleftheria, additional, Walsh, John P, additional, Xu, Jiake, additional, and Wilson, Scott G, additional

Published
2023
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