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1. Absence of association between maternal adverse events and long-term gut microbiome outcomes in the Australian autism biobank

Author

Svetlina Vasileva, Chloe X. Yap, Andrew J.O. Whitehouse, Jacob Gratten, and Darryl Eyles

Subjects
Gut microbiome, Maternal immune activation, Maternal stress, Prenatal risk factors, Autism spectrum disorders, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Introduction: Maternal immune activation (MIA) and prenatal maternal stress (MatS) are well-studied risk factors for psychiatric conditions such as autism and schizophrenia. Animal studies have proposed the gut microbiome as a mechanism underlying this association and have found that risk factor-related gut microbiome alterations persist in the adult offspring. In this cross-sectional study, we assessed whether maternal immune activation and prenatal maternal stress were associated with long-term gut microbiome alterations in children using shotgun metagenomics. Methods: This cross-sectional study included children diagnosed with autism (N = 92), siblings without a diagnosis (N = 42), and unrelated children (N = 40) without a diagnosis who were recruited into the Australian Autism Biobank and provided a faecal sample. MIA exposure was inferred from self-reported data and included asthma/allergies, complications during pregnancy triggering an immune response, auto-immune conditions, and acute inflammation. Maternal stress included any of up to 9 stressful life events during pregnancy, such as divorce, job loss, and money problems. Data were analysed for a total of 174 children, of whom 63 (36%) were born to mothers with MIA and 84 (48%) were born to mothers who experienced maternal stress during pregnancy (where 33 [19%] experienced both). Gut microbiome data was assessed using shotgun metagenomic sequencing of the children's faecal samples. Results: In our cohort, MIA, but not MatS, was associated with ASD. Variance component analysis revealed no associations between any of the gut microbiome datasets and neither MIA nor MatS. After adjusting for age, sex, diet and autism diagnosis, there was no significant difference between groups for bacterial richness, α-diversity or β-diversity. We found no significant differences in species abundance in the main analyses. However, when stratifying the cohort by age, we found that Faecalibacterium prausnitzii E was significantly decreased in MIA children aged 11–17. Discussion: Consistent with previous findings, we found that children who were born to mothers with MIA were more likely to be diagnosed with autism. Unlike within animal studies, we found negligible microbiome differences associated with MIA and maternal stress. Given the current interest in the microbiome-gut-brain axis, researchers should exercise caution in translating microbiome findings from animal models to human contexts and the clinical setting.

Published
2024
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2. Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia

Author

Yu-Han H. Hsu, Greta Pintacuda, Ruize Liu, Eugeniu Nacu, April Kim, Kalliopi Tsafou, Natalie Petrossian, William Crotty, Jung Min Suh, Jackson Riseman, Jacqueline M. Martin, Julia C. Biagini, Daya Mena, Joshua K.T. Ching, Edyta Malolepsza, Taibo Li, Tarjinder Singh, Tian Ge, Shawn B. Egri, Benjamin Tanenbaum, Caroline R. Stanclift, Annie M. Apffel, Steven A. Carr, Monica Schenone, Jake Jaffe, Nadine Fornelos, Hailiang Huang, Kevin C. Eggan, Kasper Lage, Stephan Ripke, Benjamin M. Neale, Aiden Corvin, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau, Jr., Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberley D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chan, Eric Y.H. Chen, Wei Cheng, Eric FC. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, David Curtis, Michael Davidson, Kenneth L. Davis, Franziska Degenhardt, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Giulio Genovese, Lyudmila Georgieva, Ina Giegling, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Marian L. Hamshere, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Annette M. Hartmann, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, David M. Hougaard, Masashi Ikeda, Inge Joa, Antonio Julià, René S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, James A. Knowles, Bettina Konte, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee, S. Hong Lee, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lönnqvist, Milan Macek, Patrik K.E. Magnusson, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Andrew M. McIntosh, Sandra Meier, Carin J. Meijer, Bela Melegh, Ingrid Melle, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Lili Milani, Vihra Milanova, Younes Mokrab, Derek W. Morris, Ole Mors, Kieran C. Murphy, Robin M. Murray, Inez Myin-Germeys, Bertram Müller-Myhsok, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O'Callaghan, Colm O'Dushlaine, F. Anthony O'Neill, Sang-Yun Oh, Ann Olincy, Line Olsen, Jim Van Os, Christos Pantelis, George N. Papadimitriou, Sergi Papiol, Elena Parkhomenko, Michele T. Pato, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietiläinen, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Alan R. Sanders, Ulrich Schall, Christian R. Schubert, Thomas G. Schulze, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Jianxin Shi, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Jordan W. Smoller, Hon-Cheong So, Chris C.A. Spencer, Eli A. Stahl, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Söderman, Srinivas Thirumalai, Draga Toncheva, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Naomi R. Wray, Kari Stefansson, Peter M. Visscher, Rolf Adolfsson, Ole A. Andreassen, Douglas H.R. Blackwood, Elvira Bramon, Joseph D. Buxbaum, Anders D. Børglum, Sven Cichon, Ariel Darvasi, Enrico Domenici, Hannelore Ehrenreich, Tõnu Esko, Pablo V. Gejman, Michael Gill, Hugh Gurling, Christina M. Hultman, Nakao Iwata, Assen V. Jablensky, Erik G. Jönsson, Kenneth S. Kendler, George Kirov, Jo Knight, Todd Lencz, Douglas F. Levinson, Qingqin S. Li, Jianjun Liu, Anil K. Malhotra, Steven A. McCarroll, Andrew McQuillin, Jennifer L. Moran, Preben B. Mortensen, Bryan J. Mowry, Markus M. Nöthen, Roel A. Ophoff, Michael J. Owen, Aarno Palotie, Carlos N. Pato, Tracey L. Petryshen, Danielle Posthuma, Marcella Rietschel, Brien P. Riley, Dan Rujescu, Pak C. Sham, Pamela Sklar, David St Clair, Daniel R. Weinberger, Jens R. Wendland, Thomas Werge, Mark J. Daly, Patrick F. Sullivan, Michael C. O'Donovan, Shengying Qin, Akira Sawa, Rene Kahn, Kyung Sue Hong, Wenzhao Shi, Ming Tsuang, Masanari Itokawa, Gang Feng, Stephen J. Glatt, Xiancang Ma, Jinsong Tang, Yunfeng Ruan, Feng Zhu, Yasue Horiuchi, Byung Dae Lee, Eun-Jeong Joo, Woojae Myung, Kyooseob Ha, Hong-Hee Won, Ji Hyung Baek, Young Chul Chung, Sung-Wan Kim, Agung Kusumawardhani, Wei J. Chen, Hai-Gwo Hwu, Akitoyo Hishimoto, Ikuo Otsuka, Ichiro Sora, Tomoko Toyota, Takeo Yoshikawa, Hiroshi Kunugi, Kotaro Hattori, Sayuri Ishiwata, Shusuke Numata, Tetsuro Ohmori, Makoto Arai, Yuji Ozeki, Kumiko Fujii, Se Joo Kim, Heon-Jeong Lee, Yong Min Ahn, Se Hyun Kim, Kazufumi Akiyama, Kazutaka Shimoda, and Makoto Kinoshita

Subjects
Molecular interaction, Developmental neuroscience, Cellular neuroscience, Proteomics, Science
Abstract

Summary: Genetics have nominated many schizophrenia risk genes and identified convergent signals between schizophrenia and neurodevelopmental disorders. However, functional interpretation of the nominated genes in the relevant brain cell types is often lacking. We executed interaction proteomics for six schizophrenia risk genes that have also been implicated in neurodevelopment in human induced cortical neurons. The resulting protein network is enriched for common variant risk of schizophrenia in Europeans and East Asians, is down-regulated in layer 5/6 cortical neurons of individuals affected by schizophrenia, and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in individuals with schizophrenia and bipolar disorder. Our findings showcase brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and its related disorders.

Published
2023
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3. The shared genetic landscape of blood cell traits and risk of neurological and psychiatric disorders

Author

Yuanhao Yang, Yuan Zhou, Dale R. Nyholt, Chloe X. Yap, Rudolph K. Tannenberg, Ying Wang, Yang Wu, Zhihong Zhu, Bruce V. Taylor, and Jacob Gratten

Subjects
blood cell traits, neurological and psychiatric disorders, genetic correlation, Mendelian randomization, blood-based biomarkers, platelets, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract

Summary: Phenotypic associations have been reported between blood cell traits (BCTs) and a range of neurological and psychiatric disorders (NPDs), but in most cases, it remains unclear whether these associations have a genetic basis and, if so, to what extent genetic correlations reflect causality. Here, we report genetic correlations and Mendelian randomization analyses between 11 NPDs and 29 BCTs, using genome-wide association study summary statistics. We found significant genetic correlations for four BCT-NPD pairs, all of which have prior evidence for a phenotypic correlation. We identified a previously unreported causal effect of increased platelet distribution width on susceptibility to Parkinson’s disease. We identified multiple functional genes and regulatory elements for specific BCT-NPD pairs, some of which are targets of known drugs. These results enrich our understanding of the shared genetic landscape underlying BCTs and NPDs and provide a robust foundation for future work to improve prognosis and treatment of common NPDs.

Published
2023
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4. Investigating the shared genetic architecture between multiple sclerosis and inflammatory bowel diseases

Author

Yuanhao Yang, Hannah Musco, Steve Simpson-Yap, Zhihong Zhu, Ying Wang, Xin Lin, Jiawei Zhang, Bruce Taylor, Jacob Gratten, and Yuan Zhou

Subjects
Science
Abstract

An epidemiological association between multiple sclerosis (MS) and inflammatory bowel disease (IBD) is well-established, but a genetic link is unclear. Here, the authors investigate the shared genetic architecture between MS and IBD to shed light on the biological basis of comorbidity.

Published
2021
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5. Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders

Author

Marta F. Nabais, Simon M. Laws, Tian Lin, Costanza L. Vallerga, Nicola J. Armstrong, Ian P. Blair, John B. Kwok, Karen A. Mather, George D. Mellick, Perminder S. Sachdev, Leanne Wallace, Anjali K. Henders, Ramona A. J. Zwamborn, Paul J. Hop, Katie Lunnon, Ehsan Pishva, Janou A. Y. Roubroeks, Hilkka Soininen, Magda Tsolaki, Patrizia Mecocci, Simon Lovestone, Iwona Kłoszewska, Bruno Vellas, the Australian Imaging Biomarkers and Lifestyle study, the Alzheimer’s Disease Neuroimaging Initiative, Sarah Furlong, Fleur C. Garton, Robert D. Henderson, Susan Mathers, Pamela A. McCombe, Merrilee Needham, Shyuan T. Ngo, Garth Nicholson, Roger Pamphlett, Dominic B. Rowe, Frederik J. Steyn, Kelly L. Williams, Tim J. Anderson, Steven R. Bentley, John Dalrymple-Alford, Javed Fowder, Jacob Gratten, Glenda Halliday, Ian B. Hickie, Martin Kennedy, Simon J. G. Lewis, Grant W. Montgomery, John Pearson, Toni L. Pitcher, Peter Silburn, Futao Zhang, Peter M. Visscher, Jian Yang, Anna J. Stevenson, Robert F. Hillary, Riccardo E. Marioni, Sarah E. Harris, Ian J. Deary, Ashley R. Jones, Aleksey Shatunov, Alfredo Iacoangeli, Wouter van Rheenen, Leonard H. van den Berg, Pamela J. Shaw, Cristopher E. Shaw, Karen E. Morrison, Ammar Al-Chalabi, Jan H. Veldink, Eilis Hannon, Jonathan Mill, Naomi R. Wray, and Allan F. McRae

Subjects
Neurodegenerative disorders, DNA methylation, Mixed-linear models, Methylation profile score, Out-of-sample classification, Inflammatory markers, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract Background People with neurodegenerative disorders show diverse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer’s disease, amyotrophic lateral sclerosis, and Parkinson’s disease. Results We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson’s disease (and none with Alzheimer’s disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights. Conclusions We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences.

Published
2021
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6. Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank

Author

Chloe X. Yap, Gail A. Alvares, Anjali K. Henders, Tian Lin, Leanne Wallace, Alaina Farrelly, Tiana McLaren, Jolene Berry, Anna A. E. Vinkhuyzen, Maciej Trzaskowski, Jian Zeng, Yuanhao Yang, Dominique Cleary, Rachel Grove, Claire Hafekost, Alexis Harun, Helen Holdsworth, Rachel Jellett, Feroza Khan, Lauren Lawson, Jodie Leslie, Mira Levis Frenk, Anne Masi, Nisha E. Mathew, Melanie Muniandy, Michaela Nothard, Peter M. Visscher, Paul A. Dawson, Cheryl Dissanayake, Valsamma Eapen, Helen S. Heussler, Andrew J. O. Whitehouse, Naomi R. Wray, and Jacob Gratten

Subjects
Autism spectrum disorder, Genetics, Polygenic score, Copy number variation, Australian autism biobank, Neurology. Diseases of the nervous system, RC346-429
Abstract

Abstract Background Autism spectrum disorder (ASD) is a complex neurodevelopmental condition whose biological basis is yet to be elucidated. The Australian Autism Biobank (AAB) is an initiative of the Cooperative Research Centre for Living with Autism (Autism CRC) to establish an Australian resource of biospecimens, phenotypes and genomic data for research on autism. Methods Genome-wide single-nucleotide polymorphism genotypes were available for 2,477 individuals (after quality control) from 546 families (436 complete), including 886 participants aged 2 to 17 years with diagnosed (n = 871) or suspected (n = 15) ASD, 218 siblings without ASD, 1,256 parents, and 117 unrelated children without an ASD diagnosis. The genetic data were used to confirm familial relationships and assign ancestry, which was majority European (n = 1,964 European individuals). We generated polygenic scores (PGS) for ASD, IQ, chronotype and height in the subset of Europeans, and in 3,490 unrelated ancestry-matched participants from the UK Biobank. We tested for group differences for each PGS, and performed prediction analyses for related phenotypes in the AAB. We called copy-number variants (CNVs) in all participants, and intersected these with high-confidence ASD- and intellectual disability (ID)-associated CNVs and genes from the public domain. Results The ASD (p = 6.1e−13), sibling (p = 4.9e−3) and unrelated (p = 3.0e−3) groups had significantly higher ASD PGS than UK Biobank controls, whereas this was not the case for height—a control trait. The IQ PGS was a significant predictor of measured IQ in undiagnosed children (r = 0.24, p = 2.1e−3) and parents (r = 0.17, p = 8.0e−7; 4.0% of variance), but not the ASD group. Chronotype PGS predicted sleep disturbances within the ASD group (r = 0.13, p = 1.9e−3; 1.3% of variance). In the CNV analysis, we identified 13 individuals with CNVs overlapping ASD/ID-associated CNVs, and 12 with CNVs overlapping ASD/ID/developmental delay-associated genes identified on the basis of de novo variants. Limitations This dataset is modest in size, and the publicly-available genome-wide-association-study (GWAS) summary statistics used to calculate PGS for ASD and other traits are relatively underpowered. Conclusions We report on common genetic variation and rare CNVs within the AAB. Prediction analyses using currently available GWAS summary statistics are largely consistent with expected relationships based on published studies. As the size of publicly-available GWAS summary statistics grows, the phenotypic depth of the AAB dataset will provide many opportunities for analyses of autism profiles and co-occurring conditions, including when integrated with other omics datasets generated from AAB biospecimens (blood, urine, stool, hair).

Published
2021
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7. Analysis of DNA methylation associates the cystine–glutamate antiporter SLC7A11 with risk of Parkinson’s disease

Author

Costanza L. Vallerga, Futao Zhang, Javed Fowdar, Allan F. McRae, Ting Qi, Marta F. Nabais, Qian Zhang, Irfahan Kassam, Anjali K. Henders, Leanne Wallace, Grant Montgomery, Yu-Hsuan Chuang, Steve Horvath, Beate Ritz, Glenda Halliday, Ian Hickie, John B. Kwok, John Pearson, Toni Pitcher, Martin Kennedy, Steven R. Bentley, Peter A. Silburn, Jian Yang, Naomi R. Wray, Simon J. G. Lewis, Tim Anderson, John Dalrymple-Alford, George D. Mellick, Peter M. Visscher, and Jacob Gratten

Subjects
Science
Abstract

Parkinson’s disease (PD) is a common neurodegenerative disorder with a complex etiology involving genetics and the environment. Here, Vallerga et al. identify two CpG probes associated with PD in a blood cell type-corrected epigenome-wide meta-analysis, implicating the SLC7A11 gene as a plausible biological target.

Published
2020
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8. Australian Parkinson’s Genetics Study (APGS): pilot (n=1532)

Author

Jacob Gratten, Clemens R Scherzer, Sarah E Medland, Richard Parker, Simone Cross, Nicholas G Martin, Penelope A Lind, George D Mellick, Peter M Visscher, Danuta Z Loesch, Svetlana Bivol, Aoibhe Mulcahy, Philip E Mosley, Peter C Poortvliet, Adrian I Campos, Brittany L Mitchell, Luis M Garcia-Marin, Mary Ferguson, and Miguel E Rentería

Subjects
Medicine
Published
2022
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9. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing

Author

Qian Zhang, Costanza L. Vallerga, Rosie M. Walker, Tian Lin, Anjali K. Henders, Grant W. Montgomery, Ji He, Dongsheng Fan, Javed Fowdar, Martin Kennedy, Toni Pitcher, John Pearson, Glenda Halliday, John B. Kwok, Ian Hickie, Simon Lewis, Tim Anderson, Peter A. Silburn, George D. Mellick, Sarah E. Harris, Paul Redmond, Alison D. Murray, David J. Porteous, Christopher S. Haley, Kathryn L. Evans, Andrew M. McIntosh, Jian Yang, Jacob Gratten, Riccardo E. Marioni, Naomi R. Wray, Ian J. Deary, Allan F. McRae, and Peter M. Visscher

Subjects
DNA methylation, Age prediction, Epigenetic clock, Ageing, Mortality, Medicine, Genetics, QH426-470
Abstract

Abstract Background DNA methylation changes with age. Chronological age predictors built from DNA methylation are termed ‘epigenetic clocks’. The deviation of predicted age from the actual age (‘age acceleration residual’, AAR) has been reported to be associated with death. However, it is currently unclear how a better prediction of chronological age affects such association. Methods In this study, we build multiple predictors based on training DNA methylation samples selected from 13,661 samples (13,402 from blood and 259 from saliva). We use the Lothian Birth Cohorts of 1921 (LBC1921) and 1936 (LBC1936) to examine whether the association between AAR (from these predictors) and death is affected by (1) improving prediction accuracy of an age predictor as its training sample size increases (from 335 to 12,710) and (2) additionally correcting for confounders (i.e., cellular compositions). In addition, we investigated the performance of our predictor in non-blood tissues. Results We found that in principle, a near-perfect age predictor could be developed when the training sample size is sufficiently large. The association between AAR and mortality attenuates as prediction accuracy increases. AAR from our best predictor (based on Elastic Net, https://github.com/qzhang314/DNAm-based-age-predictor) exhibits no association with mortality in both LBC1921 (hazard ratio = 1.08, 95% CI 0.91–1.27) and LBC1936 (hazard ratio = 1.00, 95% CI 0.79–1.28). Predictors based on small sample size are prone to confounding by cellular compositions relative to those from large sample size. We observed comparable performance of our predictor in non-blood tissues with a multi-tissue-based predictor. Conclusions This study indicates that the epigenetic clock can be improved by increasing the training sample size and that its association with mortality attenuates with increased prediction of chronological age.

Published
2019
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10. Study protocol for the Australian autism biobank: an international resource to advance autism discovery research

Author

Gail A. Alvares, Paul A. Dawson, Cheryl Dissanayake, Valsamma Eapen, Jacob Gratten, Rachel Grove, Anjali Henders, Helen Heussler, Lauren Lawson, Anne Masi, Emma Raymond, Felicity Rose, Leanne Wallace, Naomi R. Wray, Andrew J. O. Whitehouse, and the Australian Autism Biobank team

Subjects
Study protocol, Autism spectrum disorder, Genetic, Genomic, Biobank, Pediatrics, RJ1-570
Abstract

Abstract Background The phenotypic and genetic heterogeneity of autism spectrum disorder (ASD) presents considerable challenges in understanding etiological pathways, selecting effective therapies, providing genetic counselling, and predicting clinical outcomes. With advances in genetic and biological research alongside rapid-pace technological innovations, there is an increasing imperative to access large, representative, and diverse cohorts to advance knowledge of ASD. To date, there has not been any single collective effort towards a similar resource in Australia, which has its own unique ethnic and cultural diversity. The Australian Autism Biobank was initiated by the Cooperative Research Centre for Living with Autism (Autism CRC) to establish a large-scale repository of biological samples and detailed clinical information about children diagnosed with ASD to facilitate future discovery research. Methods The primary group of participants were children with a confirmed diagnosis of ASD, aged between 2 and 17 years, recruited through four sites in Australia. No exclusion criteria regarding language level, cognitive ability, or comorbid conditions were applied to ensure a representative cohort was recruited. Both biological parents and siblings were invited to participate, along with children without a diagnosis of ASD, and children who had been queried for an ASD diagnosis but did not meet diagnostic criteria. All children completed cognitive assessments, with probands and parents completing additional assessments measuring ASD symptomatology. Parents completed questionnaires about their child’s medical history and early development. Physical measurements and biological samples (blood, stool, urine, and hair) were collected from children, and physical measurements and blood samples were collected from parents. Samples were sent to a central processing site and placed into long-term storage. Discussion The establishment of this biobank is a valuable international resource incorporating detailed clinical and biological information that will help accelerate the pace of ASD discovery research. Recruitment into this study has also supported the feasibility of large-scale biological sample collection in children diagnosed with ASD with comprehensive phenotyping across a wide range of ages, intellectual abilities, and levels of adaptive functioning. This biological and clinical resource will be open to data access requests from national and international researchers to support future discovery research that will benefit the autistic community.

Published
2018
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11. Age at first birth in women is genetically associated with increased risk of schizophrenia

Author

Guiyan Ni, Jacob Gratten, Naomi R. Wray, Sang Hong Lee, and Schizophrenia Working Group of the Psychiatric Genomics Consortium

Subjects
Medicine, Science
Abstract

Abstract Previous studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is −0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.

Published
2018
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12. Whole-exome sequencing in amyotrophic lateral sclerosis suggests NEK1 is a risk gene in Chinese

Author

Jacob Gratten, Qiongyi Zhao, Beben Benyamin, Fleur Garton, Ji He, Paul J. Leo, Marie Mangelsdorf, Lisa Anderson, Zong-Hong Zhang, Lu Chen, Xiang-Ding Chen, Katie Cremin, Hong-Weng Deng, Janette Edson, Ying-Ying Han, Jessica Harris, Anjali K. Henders, Zi-Bing Jin, Zhongshan Li, Yong Lin, Xiaolu Liu, Mhairi Marshall, Bryan J. Mowry, Shu Ran, David C. Reutens, Sharon Song, Li-Jun Tan, Lu Tang, Robyn H. Wallace, Lawrie Wheeler, Jinyu Wu, Jian Yang, Huji Xu, Peter M. Visscher, Perry F. Bartlett, Matthew A. Brown, Naomi R. Wray, and Dongsheng Fan

Subjects
Medicine, Genetics, QH426-470
Abstract

Abstract Background Amyotrophic lateral sclerosis (ALS) is a progressive neurological disease characterised by the degeneration of motor neurons, which are responsible for voluntary movement. There remains limited understanding of disease aetiology, with median survival of ALS of three years and no effective treatment. Identifying genes that contribute to ALS susceptibility is an important step towards understanding aetiology. The vast majority of published human genetic studies, including for ALS, have used samples of European ancestry. The importance of trans-ethnic studies in human genetic studies is widely recognised, yet a dearth of studies of non-European ancestries remains. Here, we report analyses of novel whole-exome sequencing (WES) data from Chinese ALS and control individuals. Methods WES data were generated for 610 ALS cases and 460 controls drawn from Chinese populations. We assessed evidence for an excess of rare damaging mutations at the gene level and the gene set level, considering only singleton variants filtered to have allele frequency less than 5 × 10–5 in reference databases. To meta-analyse our results with a published study of European ancestry, we used a Cochran–Mantel–Haenszel test to compare gene-level variant counts in cases vs controls. Results No gene passed the genome-wide significance threshold with ALS in Chinese samples alone. Combining rare variant counts in Chinese with those from the largest WES study of European ancestry resulted in three genes surpassing genome-wide significance: TBK1 (p = 8.3 × 10–12), SOD1 (p = 8.9 × 10–9) and NEK1 (p = 1.1 × 10–9). In the Chinese data alone, SOD1 and NEK1 were nominally significantly associated with ALS (p = 0.04 and p = 7 × 10–3, respectively) and the case/control frequencies of rare coding variants in these genes were similar in Chinese and Europeans (SOD1: 1.5%/0.2% vs 0.9%/0.1%, NEK1 1.8%/0.4% vs 1.9%/0.8%). This was also true for TBK1 (1.2%/0.2% vs 1.4%/0.4%), but the association with ALS in Chinese was not significant (p = 0.14). Conclusions While SOD1 is already recognised as an ALS-associated gene in Chinese, we provide novel evidence for association of NEK1 with ALS in Chinese, reporting variants in these genes not previously found in Europeans.

Published
2017
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13. Cross-ethnic meta-analysis identifies association of the GPX3-TNIP1 locus with amyotrophic lateral sclerosis

Author

Beben Benyamin, Ji He, Qiongyi Zhao, Jacob Gratten, Fleur Garton, Paul J. Leo, Zhijun Liu, Marie Mangelsdorf, Ammar Al-Chalabi, Lisa Anderson, Timothy J. Butler, Lu Chen, Xiang-Ding Chen, Katie Cremin, Hong-Weng Deng, Matthew Devine, Janette Edson, Jennifer A. Fifita, Sarah Furlong, Ying-Ying Han, Jessica Harris, Anjali K. Henders, Rosalind L. Jeffree, Zi-Bing Jin, Zhongshan Li, Ting Li, Mengmeng Li, Yong Lin, Xiaolu Liu, Mhairi Marshall, Emily P. McCann, Bryan J. Mowry, Shyuan T. Ngo, Roger Pamphlett, Shu Ran, David C. Reutens, Dominic B. Rowe, Perminder Sachdev, Sonia Shah, Sharon Song, Li-Jun Tan, Lu Tang, Leonard H. van den Berg, Wouter van Rheenen, Jan H. Veldink, Robyn H. Wallace, Lawrie Wheeler, Kelly L. Williams, Jinyu Wu, Xin Wu, Jian Yang, Weihua Yue, Zong-Hong Zhang, Dai Zhang, Peter G. Noakes, Ian P. Blair, Robert D. Henderson, Pamela A. McCombe, Peter M. Visscher, Huji Xu, Perry F. Bartlett, Matthew A. Brown, Naomi R. Wray, and Dongsheng Fan

Subjects
Science
Abstract

Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disease. Here, Wray and colleagues identify association of the GPX3-TNIP1 locus with ALS using cross-ethnic meta-analyses.

Published
2017
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14. Investigating the shared genetic architecture between multiple sclerosis and inflammatory bowel diseases

Author

Yuan Zhou, Hannah Musco, Jacob Gratten, Steve Simpson-Yap, Yuanhao Yang, Ying Wang, Xin Lin, Bruce V. Taylor, Zhihong Zhu, and Jiawei Zhang

Subjects
Multiple Sclerosis, Science, General Physics and Astronomy, Single-nucleotide polymorphism, Genome-wide association study, Disease, Polymorphism, Single Nucleotide, Genome-wide association studies, Inflammatory bowel disease, digestive system, Linkage Disequilibrium, Article, General Biochemistry, Genetics and Molecular Biology, Crohn Disease, Risk Factors, Genetics research, Mendelian randomization, medicine, Humans, SNP, Genetic Predisposition to Disease, Immunological disorders, Multidisciplinary, Genome, Human, business.industry, Multiple sclerosis, General Chemistry, medicine.disease, Comorbidity, Ulcerative colitis, digestive system diseases, Immunology, Colitis, Ulcerative, business, Genome-Wide Association Study
Abstract

An epidemiological association between multiple sclerosis (MS) and inflammatory bowel disease (IBD) is well established, but whether this reflects a shared genetic aetiology, and whether consistent genetic relationships exist between MS and the two predominant IBD subtypes, ulcerative colitis (UC) and Crohn’s disease (CD), remains unclear. Here, we use large-scale genome-wide association study summary data to investigate the shared genetic architecture between MS and IBD overall and UC and CD independently. We find a significantly greater genetic correlation between MS and UC than between MS and CD, and identify three SNPs shared between MS and IBD (rs13428812), UC (rs116555563) and CD (rs13428812, rs9977672) in cross-trait meta-analyses. We find suggestive evidence for a causal effect of MS on UC and IBD using Mendelian randomization, but no or weak and inconsistent evidence for a causal effect of IBD or UC on MS. We observe largely consistent patterns of tissue-specific heritability enrichment for MS and IBDs in lung, spleen, whole blood and small intestine, and identify cell-type-specific enrichment for MS and IBDs in CD4+ T cells in lung and CD8+ cytotoxic T cells in lung and spleen. Our study sheds light on the biological basis of comorbidity between MS and IBD., An epidemiological association between multiple sclerosis (MS) and inflammatory bowel disease (IBD) is well-established, but a genetic link is unclear. Here, the authors investigate the shared genetic architecture between MS and IBD to shed light on the biological basis of comorbidity.

Published
2021

15. Analysis of DNA methylation associates the cystine–glutamate antiporter SLC7A11 with risk of Parkinson’s disease

Author

Anjali K. Henders, Marta F. Nabais, Steven R. Bentley, Ting Qi, John C. Dalrymple-Alford, Jacob Gratten, Glenda M. Halliday, Qian Zhang, Leanne Wallace, Allan F. McRae, Costanza L. Vallerga, Peter A. Silburn, Yu-Hsuan Chuang, Steve Horvath, Tim J. Anderson, Futao Zhang, Jian Yang, Grant W. Montgomery, George D. Mellick, Beate Ritz, Naomi R. Wray, John F. Pearson, Irfahan Kassam, Martin A. Kennedy, John B.J. Kwok, Simon J.G. Lewis, Javed Fowdar, Peter M. Visscher, Ian B. Hickie, and Toni L. Pitcher

Subjects
Epigenomics, Male, 0301 basic medicine, Parkinson's disease, General Physics and Astronomy, SLC7A11, 0302 clinical medicine, Gene expression, lcsh:Science, Aged, 80 and over, Genetics, DNA methylation, Multidisciplinary, biology, Parkinson Disease, Environmental exposure, Middle Aged, Glutathione, Healthy Volunteers, 3. Good health, CpG site, Female, Chromosomes, Human, Pair 4, Adult, Amino Acid Transport System y+, Science, Down-Regulation, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, medicine, Humans, Gene, Aged, Australia, General Chemistry, Mendelian Randomization Analysis, medicine.disease, 030104 developmental biology, Risk factors, Case-Control Studies, biology.protein, CpG Islands, lcsh:Q, 030217 neurology & neurosurgery, New Zealand
Abstract

An improved understanding of etiological mechanisms in Parkinson’s disease (PD) is urgently needed because the number of affected individuals is projected to increase rapidly as populations age. We present results from a blood-based methylome-wide association study of PD involving meta-analysis of 229 K CpG probes in 1,132 cases and 999 controls from two independent cohorts. We identify two previously unreported epigenome-wide significant associations with PD, including cg06690548 on chromosome 4. We demonstrate that cg06690548 hypermethylation in PD is associated with down-regulation of the SLC7A11 gene and show this is consistent with an environmental exposure, as opposed to medications or genetic factors with effects on DNA methylation or gene expression. These findings are notable because SLC7A11 codes for a cysteine-glutamate anti-porter regulating levels of the antioxidant glutathione, and it is a known target of the environmental neurotoxin β-methylamino-L-alanine (BMAA). Our study identifies the SLC7A11 gene as a plausible biological target in PD., Parkinson’s disease (PD) is a common neurodegenerative disorder with a complex etiology involving genetics and the environment. Here, Vallerga et al. identify two CpG probes associated with PD in a blood cell type-corrected epigenome-wide meta-analysis, implicating the SLC7A11 gene as a plausible biological target.

Published
2020

16. Australian Parkinson's Genetics Study (APGS): pilot (n=1532)

Author

Svetlana Bivol, George D Mellick, Jacob Gratten, Richard Parker, Aoibhe Mulcahy, Philip E Mosley, Peter C Poortvliet, Adrian I Campos, Brittany L Mitchell, Luis M Garcia-Marin, Simone Cross, Mary Ferguson, Penelope A Lind, Danuta Z Loesch, Peter M Visscher, Sarah E Medland, Clemens R Scherzer, Nicholas G Martin, and Miguel E Rentería

Subjects
Male, Surveys and Questionnaires, Australia, Humans, Parkinson Disease, General Medicine, Anxiety, Constipation
Abstract

PurposeParkinson’s disease (PD) is a neurodegenerative disorder associated with progressive disability. While the precise aetiology is unknown, there is evidence of significant genetic and environmental influences on individual risk. The Australian Parkinson’s Genetics Study seeks to study genetic and patient-reported data from a large cohort of individuals with PD in Australia to understand the sociodemographic, genetic and environmental basis of PD susceptibility, symptoms and progression.ParticipantsIn the pilot phase reported here, 1819 participants were recruited through assisted mailouts facilitated by Services Australia based on having three or more prescriptions for anti-PD medications in their Pharmaceutical Benefits Scheme records. The average age at the time of the questionnaire was 64±6 years. We collected patient-reported information and sociodemographic variables via an online (93% of the cohort) or paper-based (7%) questionnaire. One thousand five hundred and thirty-two participants (84.2%) met all inclusion criteria, and 1499 provided a DNA sample via traditional post.Findings to date65% of participants were men, and 92% identified as being of European descent. A previous traumatic brain injury was reported by 16% of participants and was correlated with a younger age of symptom onset. At the time of the questionnaire, constipation (36% of participants), depression (34%), anxiety (17%), melanoma (16%) and diabetes (10%) were the most reported comorbid conditions.Future plansWe plan to recruit sex-matched and age-matched unaffected controls, genotype all participants and collect non-motor symptoms and cognitive function data. Future work will explore the role of genetic and environmental factors in the aetiology of PD susceptibility, onset, symptoms, and progression, including as part of international PD research consortia.

Published
2022

17. Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders

Author

Gabriëlla A.M. Blokland, Jakob Grove, Chia-Yen Chen, Chris Cotsapas, Stuart Tobet, Robert Handa, David St Clair, Todd Lencz, Bryan J. Mowry, Sathish Periyasamy, Murray J. Cairns, Paul A. Tooney, Jing Qin Wu, Brian Kelly, George Kirov, Patrick F. Sullivan, Aiden Corvin, Brien P. Riley, Tõnu Esko, Lili Milani, Erik G. Jönsson, Aarno Palotie, Hannelore Ehrenreich, Martin Begemann, Agnes Steixner-Kumar, Pak C. Sham, Nakao Iwata, Daniel R. Weinberger, Pablo V. Gejman, Alan R. Sanders, Joseph D. Buxbaum, Dan Rujescu, Ina Giegling, Bettina Konte, Annette M. Hartmann, Elvira Bramon, Robin M. Murray, Michele T. Pato, Jimmy Lee, Ingrid Melle, Espen Molden, Roel A. Ophoff, Andrew McQuillin, Nicholas J. Bass, Rolf Adolfsson, Anil K. Malhotra, Nicholas G. Martin, Janice M. Fullerton, Philip B. Mitchell, Peter R. Schofield, Andreas J. Forstner, Franziska Degenhardt, Sabrina Schaupp, Ashley L. Comes, Manolis Kogevinas, José Guzman-Parra, Andreas Reif, Fabian Streit, Lea Sirignano, Sven Cichon, Maria Grigoroiu-Serbanescu, Joanna Hauser, Jolanta Lissowska, Fermin Mayoral, Bertram Müller-Myhsok, Beata Świątkowska, Thomas G. Schulze, Markus M. Nöthen, Marcella Rietschel, John Kelsoe, Marion Leboyer, Stéphane Jamain, Bruno Etain, Frank Bellivier, John B. Vincent, Martin Alda, Claire O’Donovan, Pablo Cervantes, Joanna M. Biernacka, Mark Frye, Susan L. McElroy, Laura J. Scott, Eli A. Stahl, Mikael Landén, Marian L. Hamshere, Olav B. Smeland, Srdjan Djurovic, Arne E. Vaaler, Ole A. Andreassen, Bernhard T. Baune, Tracy Air, Martin Preisig, Rudolf Uher, Douglas F. Levinson, Myrna M. Weissman, James B. Potash, Jianxin Shi, James A. Knowles, Roy H. Perlis, Susanne Lucae, Dorret I. Boomsma, Brenda W.J.H. Penninx, Jouke-Jan Hottenga, Eco J.C. de Geus, Gonneke Willemsen, Yuri Milaneschi, Henning Tiemeier, Hans J. Grabe, Alexander Teumer, Sandra Van der Auwera, Uwe Völker, Steven P. Hamilton, Patrik K.E. Magnusson, Alexander Viktorin, Divya Mehta, Niamh Mullins, Mark J. Adams, Gerome Breen, Andrew M. McIntosh, Cathryn M. Lewis, David M. Hougaard, Merete Nordentoft, Ole Mors, Preben B. Mortensen, Thomas Werge, Thomas D. Als, Anders D. Børglum, Tracey L. Petryshen, Jordan W. Smoller, Jill M. Goldstein, Stephan Ripke, Benjamin M. Neale, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberly D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, David Curtis, Michael Davidson, Kenneth L. Davis, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Giulio Genovese, Lyudmila Georgieva, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, Masashi Ikeda, Inge Joa, Antonio Julià, René S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee Chee Keong, S. Hong Lee, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lönnqvist, Milan Macek, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Sandra Meier, Carin J. Meijer, Bela Melegh, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Vihra Milanova, Younes Mokrab, Derek W. Morris, Kieran C. Murphy, Inez Myin-Germeys, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O’Callaghan, Colm O’Dushlaine, F. Anthony O’Neill, Sang-Yun Oh, Ann Olincy, Line Olsen, Jim Van Os, Christos Pantelis, George N. Papadimitriou, Sergi Papiol, Elena Parkhomenko, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietiläinen, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Ulrich Schall, Christian R. Schubert, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Hon-Cheong So, Chris C.A. Spencer, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T. Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Söderman, Srinivas Thirumalai, Draga Toncheva, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Naomi R. Wray, Kari Stefansson, Peter M. Visscher, Douglas H.R. Blackwood, Ariel Darvasi, Enrico Domenici, Michael Gill, Hugh Gurling, Christina M. Hultman, Assen V. Jablensky, Kenneth S. Kendler, Jo Knight, Qingqin S. Li, Jianjun Liu, Steven A. McCarroll, Jennifer L. Moran, Michael J. Owen, Carlos N. Pato, Danielle Posthuma, Pamela Sklar, Jens R. Wendland, Mark J. Daly, Michael C. O’Donovan, Peter Donnelly, Ines Barroso, Jenefer M. Blackwell, Matthew A. Brown, Juan P. Casas, Panos Deloukas, Audrey Duncanson, Janusz Jankowski, Hugh S. Markus, Christopher G. Mathew, Colin N.A. Palmer, Robert Plomin, Anna Rautanen, Stephen J. Sawcer, Richard C. Trembath, Ananth C. Viswanathan, Nicholas W. Wood, Gavin Band, Céline Bellenguez, Colin Freeman, Eleni Giannoulatou, Garrett Hellenthal, Richard Pearson, Matti Pirinen, Amy Strange, Zhan Su, Damjan Vukcevic, Cordelia Langford, Hannah Blackburn, Suzannah J. Bumpstead, Serge Dronov, Sarah Edkins, Matthew Gillman, Emma Gray, Rhian Gwilliam, Naomi Hammond, Sarah E. Hunt, Alagurevathi Jayakumar, Jennifer Liddle, Owen T. McCann, Simon C. Potter, Radhi Ravindrarajah, Michelle Ricketts, Avazeh Tashakkori-Ghanbaria, Matthew Waller, Paul Weston, Pamela Whittaker, Sara Widaa, Mark I. McCarthy, Maria J. Arranz, Steven Bakker, Stephan Bender, Benedicto Crespo-Facorro, Jeremy Hall, Conrad Iyegbe, Stephen Lawrie, Kuang Lin, Don H. Linszen, Ignacio Mata, Muriel Walshe, Matthias Weisbrod, Durk Wiersma, Vassily Trubetskoy, Yunpeng Wang, Jonathan R.I. Coleman, Héléna A. Gaspar, Christiaan A. de Leeuw, Jennifer M. Whitehead Pavlides, Maciej Trzaskowski, Enda M. Byrne, Liam Abbott, Huda Akil, Diego Albani, Ney Alliey-Rodriguez, Adebayo Anjorin, Verneri Antilla, Swapnil Awasthi, Judith A. Badner, Marie Bækvad-Hansen, Jack D. Barchas, Nicholas Bass, Michael Bauer, Richard Belliveau, Carsten Bøcker Pedersen, Erlend Bøen, Marco P. Boks, James Boocock, Monika Budde, William Bunney, Margit Burmeister, Jonas Bybjerg-Grauholm, Miquel Casas, Felecia Cerrato, Kimberly Chambert, Alexander W. Charney, Danfeng Chen, Claire Churchhouse, Toni-Kim Clarke, William Coryell, David W. Craig, Cristiana Cruceanu, Piotr M. Czerski, Anders M. Dale, Simone de Jong, Jurgen Del-Favero, J. Raymond DePaulo, Amanda L. Dobbyn, Ashley Dumont, Torbjørn Elvsåshagen, Chun Chieh Fan, Sascha B. Fischer, Matthew Flickinger, Tatiana M. Foroud, Liz Forty, Christine Fraser, Katrin Gade, Diane Gage, Julie Garnham, Claudia Giambartolomei, Marianne Giørtz Pedersen, Jaqueline Goldstein, Scott D. Gordon, Katherine Gordon-Smith, Elaine K. Green, Melissa J. Green, Tiffany A. Greenwood, Weihua Guan, Martin Hautzinger, Urs Heilbronner, Maria Hipolito, Dominic Holland, Laura Huckins, Jessica S. Johnson, Radhika Kandaswamy, Robert Karlsson, Sarah Kittel-Schneider, Anna C. Koller, Ralph Kupka, Catharina Lavebratt, Jacob Lawrence, William B. Lawson, Markus Leber, Phil H. Lee, Shawn E. Levy, Jun Z. Li, Chunyu Liu, Anna Maaser, Donald J. MacIntyre, Pamela B. Mahon, Lina Martinsson, Steve McCarroll, Peter McGuffin, Melvin G. McInnis, James D. McKay, Helena Medeiros, Sarah E. Medland, Fan Meng, Grant W. Montgomery, Thomas W. Mühleisen, Hoang Nguyen, Caroline M. Nievergelt, Annelie Nordin Adolfsson, Evaristus A. Nwulia, Claire O'Donovan, Loes M. Olde Loohuis, Anil P.S. Ori, Lilijana Oruc, Urban Ösby, Amy Perry, Andrea Pfennig, Eline J. Regeer, Céline S. Reinbold, John P. Rice, Fabio Rivas, Margarita Rivera, Euijung Ryu, Cristina Sánchez-Mora, Alan F. Schatzberg, William A. Scheftner, Nicholas J. Schork, Cynthia Shannon Weickert, Tatyana Shehktman, Paul D. Shilling, Claire Slaney, Janet L. Sobell, Christine Søholm Hansen, Anne T. Spijker, Michael Steffens, John S. Strauss, Szabolcs Szelinger, Robert C. Thompson, Thorgeir E. Thorgeirsson, Jens Treutlein, Helmut Vedder, Weiqing Wang, Stanley J. Watson, Thomas W. Weickert, Simon Xi, Wei Xu, Allan H. Young, Peter Zandi, Peng Zhang, Sebastian Zöllner, Abdel Abdellaoui, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Aartjan T.F. Beekman, Elisabeth B. Binder, Julien Bryois, Henriette N. Buttenschøn, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Gregory E. Crawford, Gail Davies, Ian J. Deary, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Jerome C. Foo, Fernando S. Goes, Lynsey S. Hall, Thomas F. Hansen, Ian B. Hickie, Georg Homuth, Carsten Horn, David M. Howard, Marcus Ising, Rick Jansen, Ian Jones, Lisa A. Jones, Eric Jorgenson, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Dean F. MacKinnon, Robert M. Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Christel M. Middeldorp, Evelin Mihailov, Francis M. Mondimore, Sara Mostafavi, Matthias Nauck, Bernard Ng, Michel G. Nivard, Dale R. Nyholt, Paul F. O'Reilly, Hogni Oskarsson, Jodie N. Painter, Roseann E. Peterson, Wouter J. Peyrot, Giorgio Pistis, Jorge A. Quiroz, Per Qvist, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Stanley I. Shyn, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Katherine E. Tansey, Henning Teismann, Wesley Thompson, Pippa A. Thomson, Matthew Traylor, André G. Uitterlinden, Daniel Umbricht, Albert M. van Hemert, Shantel Marie Weinsheimer, Jürgen Wellmann, Yang Wu, Hualin S. Xi, Jian Yang, Futao Zhang, Volker Arolt, Klaus Berger, Udo Dannlowski, Katharina Domschke, Caroline Hayward, Andrew C. Heath, Stefan Kloiber, Glyn Lewis, Pamela AF. Madden, Patrik K. Magnusson, Preben Bo Mortensen, Michael C. O'Donovan, Sara A. Paciga, Nancy L. Pedersen, David J. Porteous, Catherine Schaefer, Henry Völzke, Marco Bortolato, Janita Bralten, Cynthia M. Bulik, Christie L. Burton, Caitlin E. Carey, Lea K. Davis, Laramie E. Duncan, Howard J. Edenberg, Lauren Erdman, Stephen V. Faraone, Slavina B. Goleva, Wei Guo, Christopher Hübel, Laura M. Huckins, Ekaterina A. Khramtsova, Joanna Martin, Carol A. Mathews, Elise Robinson, Eli Stahl, Barbara E. Stranger, Michela Traglia, Raymond K. Walters, Lauren A. Weiss, Stacey J. Winham, Yin Yao, Kristjar Skajaa, Markus Nöthen, Michael Owen, Robert H. Yolken, Niels Plath, Jonathan Mill, Daniel Geschwind, Psychiatry 1, RS: MHeNs - R2 - Mental Health, Psychiatrie & Neuropsychologie, Centre of Excellence in Complex Disease Genetics, Research Programme of Molecular Medicine, Research Programs Unit, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, Functional Genomics, Biological Psychology, APH - Mental Health, APH - Methodology, Sociology and Social Gerontology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Blokland, Gabriella AM, Grove, Jakob, Chen, Chia Yen, Cotsapas, Chris, Tobet, Stuart, Handa, Robert, Lee, Sang Hong, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Sex Differences Cross-Disorder Analysis Group of the Psychiatric Genomics Consortium, iPSYCH, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Human genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Reproduction & Development (AR&D), Child and Adolescent Psychiatry / Psychology, Adult Psychiatry, ANS - Complex Trait Genetics, and ANS - Mood, Anxiety, Psychosis, Stress & Sleep

Subjects
0301 basic medicine, Male, Bipolar Disorder, Schizophrenia/genetics, LD SCORE REGRESSION, Genome-wide association study, 0302 clinical medicine, Receptors, SCHIZOPHRENIA, Psychotic Disorders/genetics, KYNURENINE PATHWAY METABOLISM, Genetics, RISK, Sex Characteristics, Vascular Endothelial Growth Factor, Bipolar Disorder/genetics, Major/genetics, Single Nucleotide, AFFECTIVE STIMULI IMPACT, Schizophrenia, Sulfurtransferases, Major depressive disorder, Female, Depressive Disorder, Major/genetics, Bipolar disorder, Locus (genetics), Genomics, Biology, Polymorphism, Single Nucleotide, Article, DYSPHORIC MOOD, 03 medical and health sciences, Sex differences, medicine, Humans, Genetic Predisposition to Disease, ddc:610, Polymorphism, GENOME-WIDE ASSOCIATION, Genotype-by-sex interaction, Biological Psychiatry, Depressive Disorder, Major, Depressive Disorder, GENDER-DIFFERENCES, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], PARAVENTRICULAR NUCLEUS, 3112 Neurosciences, Endothelial Cells, MAJOR DEPRESSION, medicine.disease, Genetic architecture, 030104 developmental biology, Mood, Receptors, Vascular Endothelial Growth Factor, Psychotic Disorders, 3111 Biomedicine, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Contains fulltext : 248656.pdf (Publisher’s version ) (Closed access) BACKGROUND: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. METHODS: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. RESULTS: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10(-8)), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10(-6)) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10(-7); rs73033497, p = 8.8 × 10(-7); rs7914279, p = 6.4 × 10(-7)), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10(-7)) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10(-7)), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10(-7)) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). CONCLUSIONS: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.

Published
2022

18. Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank

Author

Alexis Harun, Gail A. Alvares, Chloe X. Yap, Feroza Khan, Leanne Wallace, Helen Holdsworth, Rachel Grove, Jian Zeng, Jolene Berry, Valsamma Eapen, Lauren P. Lawson, Jacob Gratten, Melanie Muniandy, Alaina Farrelly, Helen Heussler, Mira Levis Frenk, Jodie Leslie, Nisha E. Mathew, Andrew J. O. Whitehouse, Rachel Jellett, Maciej Trzaskowski, Cheryl Dissanayake, Tiana McLaren, Dominique Cleary, Anjali K. Henders, Peter M. Visscher, Anna A. E. Vinkhuyzen, Naomi R. Wray, Paul A. Dawson, Tian Lin, Yuanhao Yang, Claire Hafekost, Anne Masi, and Michaela Nothard

Subjects
Multifactorial Inheritance, Australian autism biobank, DNA Copy Number Variations, Autism Spectrum Disorder, Genome-wide association study, Polymorphism, Single Nucleotide, lcsh:RC346-429, 03 medical and health sciences, 0302 clinical medicine, Developmental Neuroscience, Risk Factors, Intellectual disability, Polygenic score, mental disorders, medicine, Genetics, Humans, Genetic Predisposition to Disease, Copy-number variation, Sibling, Autistic Disorder, Molecular Biology, lcsh:Neurology. Diseases of the nervous system, 030304 developmental biology, 1103 Clinical Sciences, 1109 Neurosciences, Biological Specimen Banks, Uncategorized, 0303 health sciences, business.industry, Copy number variation, Research, Australia, Computational Biology, Genetic Variation, Omics, medicine.disease, Biobank, Psychiatry and Mental health, Phenotype, Autism spectrum disorder, Autism, business, 030217 neurology & neurosurgery, Developmental Biology, Clinical psychology, Genome-Wide Association Study
Abstract

Background Autism spectrum disorder (ASD) is a complex neurodevelopmental condition whose biological basis is yet to be elucidated. The Australian Autism Biobank (AAB) is an initiative of the Cooperative Research Centre for Living with Autism (Autism CRC) to establish an Australian resource of biospecimens, phenotypes and genomic data for research on autism. Methods Genome-wide single-nucleotide polymorphism genotypes were available for 2,477 individuals (after quality control) from 546 families (436 complete), including 886 participants aged 2 to 17 years with diagnosed (n = 871) or suspected (n = 15) ASD, 218 siblings without ASD, 1,256 parents, and 117 unrelated children without an ASD diagnosis. The genetic data were used to confirm familial relationships and assign ancestry, which was majority European (n = 1,964 European individuals). We generated polygenic scores (PGS) for ASD, IQ, chronotype and height in the subset of Europeans, and in 3,490 unrelated ancestry-matched participants from the UK Biobank. We tested for group differences for each PGS, and performed prediction analyses for related phenotypes in the AAB. We called copy-number variants (CNVs) in all participants, and intersected these with high-confidence ASD- and intellectual disability (ID)-associated CNVs and genes from the public domain. Results The ASD (p = 6.1e−13), sibling (p = 4.9e−3) and unrelated (p = 3.0e−3) groups had significantly higher ASD PGS than UK Biobank controls, whereas this was not the case for height—a control trait. The IQ PGS was a significant predictor of measured IQ in undiagnosed children (r = 0.24, p = 2.1e−3) and parents (r = 0.17, p = 8.0e−7; 4.0% of variance), but not the ASD group. Chronotype PGS predicted sleep disturbances within the ASD group (r = 0.13, p = 1.9e−3; 1.3% of variance). In the CNV analysis, we identified 13 individuals with CNVs overlapping ASD/ID-associated CNVs, and 12 with CNVs overlapping ASD/ID/developmental delay-associated genes identified on the basis of de novo variants. Limitations This dataset is modest in size, and the publicly-available genome-wide-association-study (GWAS) summary statistics used to calculate PGS for ASD and other traits are relatively underpowered. Conclusions We report on common genetic variation and rare CNVs within the AAB. Prediction analyses using currently available GWAS summary statistics are largely consistent with expected relationships based on published studies. As the size of publicly-available GWAS summary statistics grows, the phenotypic depth of the AAB dataset will provide many opportunities for analyses of autism profiles and co-occurring conditions, including when integrated with other omics datasets generated from AAB biospecimens (blood, urine, stool, hair).

Published
2022
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20. The genetic relationship between female reproductive traits and six psychiatric disorders

Author

Xuan Zhou, Natalie T. Mills, Jacob Gratten, Guiyan Ni, Azmeraw T. Amare, Sang Hong Lee, Ni, Guiyan, Amare, Azmeraw T, Zhou, Xuan, Mills, Natalie, Gratten, Jacob, and Lee, S Hong

Subjects
Male, 0301 basic medicine, Multifactorial Inheritance, lcsh:Medicine, 0302 clinical medicine, Risk Factors, Databases, Genetic, Young adult, lcsh:Science, Reproductive health, 0303 health sciences, Multidisciplinary, Mental Disorders, Reproduction, bipolar affective-disorder, health, Genomics, Middle Aged, 3. Good health, Schizophrenia, Major depressive disorder, Female, Adult, medicine.medical_specialty, Adolescent, Offspring, Biology, Genetic correlation, Article, Young Adult, 03 medical and health sciences, Quantitative Trait, Heritable, medicine, Humans, Genetic Predisposition to Disease, Psychiatry, Genetic Association Studies, 030304 developmental biology, Genetic association study, Aged, Reproductive success, business.industry, lcsh:R, medicine.disease, Genetic architecture, schizophrenia, Sexual intercourse, 030104 developmental biology, maternal age, mendelian randomization, lcsh:Q, business, 030217 neurology & neurosurgery
Abstract

Female reproductive behaviors have an important implication in evolutionary fitness and health of offspring. Previous studies have shown that age at first birth of women (AFB) is genetically associated with schizophrenia (SCZ). However, for most other psychiatric disorders and reproductive traits, the latent shared genetic architecture is largely unknown. Here we used the second wave of UK Biobank data (N=220,685) to evaluate the association between five female reproductive traits and polygenetic risk scores (PRS) projected from genome-wide association study summary statistics of six psychiatric disorders (N=429,178). We found that the PRS of attention-deficit/hyperactivity disorder (ADHD) were strongly associated with AFB (genetic correlation of −0.68 ± 0.03 with p-value = 1.86E-89), age at first sexual intercourse (AFS) (−0.56 ± 0.03 with p-value = 3.42E-60), number of live births (NLB) (0.36 ± 0.04 with p-value = 4.01E-17) and age at menopause (−0.27 ± 0.04 with p-value = 5.71E-13). There were also robustly significant associations between the PRS of eating disorder (ED) and AFB (genetic correlation of 0.35 ± 0.06), ED and AFS (0.19 0.06), Major depressive disorder (MDD) and AFB (−0.27 ± 0.07), MDD and AFS (− 0.27 ± 0.03) and SCZ and AFS (−0.10 ± 0.03). Our findings reveal the shared genetic architecture between the five reproductive traits in women and six psychiatric disorders, which have a potential implication that helps to improve reproductive health in women, hence better child outcomes. Our findings may also explain, at least in part, an evolutionary hypothesis that causal mutations underlying psychiatric disorders have positive effects on reproductive success.

Published
2019

21. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing

Author

Riccardo E. Marioni, Peter A. Silburn, John B.J. Kwok, Ian J. Deary, Simon J.G. Lewis, Dongsheng Fan, Qian Zhang, David J. Porteous, Tian Lin, Alison D. Murray, Ji He, Glenda M. Halliday, Kathryn L. Evans, Sarah E. Harris, Tim J. Anderson, Grant W. Montgomery, John F. Pearson, Toni L. Pitcher, Peter M. Visscher, Chris Haley, Ian B. Hickie, Naomi R. Wray, Andrew M. McIntosh, Javed Fowdar, Anjali K. Henders, George D. Mellick, Costanza L. Vallerga, Allan F. McRae, Martin A. Kennedy, Jian Yang, Paul Redmond, Jacob Gratten, and Rosie M. Walker

Subjects
0301 basic medicine, Oncology, Epigenomics, medicine.medical_specialty, Aging, Epigenetic clock, lcsh:QH426-470, Age prediction, lcsh:Medicine, Epigenesis, Genetic, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Genetics, Medicine, Humans, Genetic Predisposition to Disease, Epigenetics, Mortality, Saliva, Molecular Biology, Genetics (clinical), Proportional Hazards Models, DNA methylation, business.industry, Research, Confounding, lcsh:R, Reproducibility of Results, Small sample, Chronological age, 3. Good health, Ageing, lcsh:Genetics, 030104 developmental biology, Sample size determination, Organ Specificity, 030220 oncology & carcinogenesis, Molecular Medicine, business, Birth cohort, Genome-Wide Association Study
Abstract

Background DNA methylation changes with age. Chronological age predictors built from DNA methylation are termed ‘epigenetic clocks’. The deviation of predicted age from the actual age (‘age acceleration residual’, AAR) has been reported to be associated with death. However, it is currently unclear how a better prediction of chronological age affects such association. Methods In this study, we build multiple predictors based on training DNA methylation samples selected from 13,661 samples (13,402 from blood and 259 from saliva). We use the Lothian Birth Cohorts of 1921 (LBC1921) and 1936 (LBC1936) to examine whether the association between AAR (from these predictors) and death is affected by (1) improving prediction accuracy of an age predictor as its training sample size increases (from 335 to 12,710) and (2) additionally correcting for confounders (i.e., cellular compositions). In addition, we investigated the performance of our predictor in non-blood tissues. Results We found that in principle, a near-perfect age predictor could be developed when the training sample size is sufficiently large. The association between AAR and mortality attenuates as prediction accuracy increases. AAR from our best predictor (based on Elastic Net, https://github.com/qzhang314/DNAm-based-age-predictor) exhibits no association with mortality in both LBC1921 (hazard ratio = 1.08, 95% CI 0.91–1.27) and LBC1936 (hazard ratio = 1.00, 95% CI 0.79–1.28). Predictors based on small sample size are prone to confounding by cellular compositions relative to those from large sample size. We observed comparable performance of our predictor in non-blood tissues with a multi-tissue-based predictor. Conclusions This study indicates that the epigenetic clock can be improved by increasing the training sample size and that its association with mortality attenuates with increased prediction of chronological age. Electronic supplementary material The online version of this article (10.1186/s13073-019-0667-1) contains supplementary material, which is available to authorized users.

Published
2019

22. Parkinson's disease age at onset genome‐wide association study: Defining heritability, genetic loci, and α‐synuclein mechanisms

Author

Lisa M. Shulman, Hirotaka Iwaki, David A. Hinds, Jacob Gratten, Huw R. Morris, Joseph Jankovic, Costanza L. Vallerga, J. Raphael Gibbs, John Hardy, Javier Simón-Sánchez, Johan Marinus, Thomas Gasser, Peter Heutink, Alexis Brice, Andrew B. Singleton, Dena G. Hernandez, Jean-Christophe Corvol, Karl Heilbron, Donald G. Grosset, Manu Sharma, Ari Siitonen, Peter M. Visscher, Sonja W. Scholz, Pentti J. Tienari, Lynne Krohn, Mathias Toft, Manuela Tan, Johanna Eerola-Rautio, Mike A. Nalls, Jacobus J. van Hilten, Lasse Pihlstrøm, Claudia Schulte, Ziv Gan-Or, Sara Bandres-Ciga, Cornelis Blauwendraat, Hampton L. Leonard, Alastair J. Noyce, Kari Majamaa, Rainer von Coelln, N Wood, Joshua M. Shulman, Suzanne Lesage, HUS Neurocenter, Pentti Tienari / Principal Investigator, Neurologian yksikkö, Research Programs Unit, Department of Neurosciences, STEMM - Stem Cells and Metabolism Research Program, University of Helsinki, and University Management

Subjects
Male, GLUCOCEREBROSIDASE, 0301 basic medicine, Parkinson's disease, EFFICIENT, Genome-wide association study, genetics [Glucosylceramidase], 3124 Neurology and psychiatry, 0302 clinical medicine, genetics [Parkinson Disease], STATISTICAL POWER, Databases, Genetic, TMEM175, Age of Onset, LONGEVITY, Aged, 80 and over, Genetics, Parkinson Disease, Middle Aged, 3. Good health, Neurology, alpha-Synuclein, genetics [alpha-Synuclein], Glucosylceramidase, Female, GBA, age at onset, APOE, Adult, EXPRESSION, PENETRANCE, Context (language use), Biology, Leucine-Rich Repeat Serine-Threonine Protein Kinase-2, Polymorphism, Single Nucleotide, Article, Young Adult, 03 medical and health sciences, Genetic variation, Humans, Genetic Predisposition to Disease, ddc:610, Genetic variability, Allele, Alleles, METAANALYSIS, Aged, Genetic association, 3112 Neurosciences, Heritability, RISK LOCI, 030104 developmental biology, Genetic Loci, GBA MUTATIONS, genetics [Leucine-Rich Repeat Serine-Threonine Protein Kinase-2], SNCA, Neurology (clinical), Age of onset, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Background Increasing evidence supports an extensive and complex genetic contribution to PD. Previous genome-wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age at onset are largely unknown. Objectives To identify the genetic determinants of PD age at onset. Methods Using genetic data of 28,568 PD cases, we performed a genome-wide association study based on PD age at onset. Results We estimated that the heritability of PD age at onset attributed to common genetic variation was similar to 0.11, lower than the overall heritability of risk for PD (similar to 0.27), likely, in part, because of the subjective nature of this measure. We found two genome-wide significant association signals, one at SNCA and the other a protein-coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni-corrected significant effect at other known PD risk loci, GBA, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. Notably, SNCA, TMEM175, SCARB2, BAG3, and GBA have all been shown to be implicated in alpha-synuclein aggregation pathways. Remarkably, other well-established PD risk loci, such as GCH1 and MAPT, did not show a significant effect on age at onset of PD. Conclusions Overall, we have performed the largest age at onset of PD genome-wide association studies to date, and our results show that not all PD risk loci influence age at onset with significant differences between risk alleles for age at onset. This provides a compelling picture, both within the context of functional characterization of disease-linked genetic variability and in defining differences between risk alleles for age at onset, or frank risk for disease. (c) 2019 International Parkinson and Movement Disorder Society

Published
2019

23. Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders

Author

Simon J.G. Lewis, Jan H. Veldink, Iwona Kłoszewska, Jonathan Mill, Nicola J. Armstrong, Eilis Hannon, Allan F. McRae, Simon M. Laws, Pamela J. Shaw, Katie Lunnon, Pamela A. McCombe, Ammar Al-Chalabi, Anjali K. Henders, Marta F. Nabais, Alfredo Iacoangeli, Glenda M. Halliday, Susan Mathers, John B.J. Kwok, Ashley R. Jones, Anna J. Stevenson, Ian B. Hickie, Tian Lin, Cristopher E. Shaw, Ian P. Blair, Hilkka Soininen, Wouter van Rheenen, Karen E. Morrison, Jacob Gratten, Toni L. Pitcher, Ian J. Deary, Janou A. Y. Roubroeks, Shyuan T. Ngo, Tim J. Anderson, Sarah Furlong, Merrilee Needham, Peter M. Visscher, Peter A. Silburn, Ramona A. J. Zwamborn, Karen A. Mather, Patrizia Mecocci, Naomi R. Wray, Roger Pamphlett, Paul J. Hop, Garth A. Nicholson, John F. Pearson, Jian Yang, Simon Lovestone, Kelly L. Williams, Costanza L. Vallerga, Magda Tsolaki, Ehsan Pishva, Robert D. Henderson, Futao Zhang, Grant W. Montgomery, Bruno Vellas, Robert F. Hillary, Steven R. Bentley, John C. Dalrymple-Alford, Frederik J. Steyn, Riccardo E. Marioni, Dominic B. Rowe, Leanne Wallace, Leonard H. van den Berg, Aleksey Shatunov, Sarah E. Harris, Perminder S. Sachdev, Fleur C. Garton, George D. Mellick, Javed Fowder, Martin A. Kennedy, and Internal Medicine

Subjects
lcsh:QH426-470, Inflammatory markers, Disease, Biology, Epigenesis, Genetic, Genetic, Methylation profile score, Out-of-sample classification, Genetic variation, Mixed-linear models, medicine, Humans, Genetic Predisposition to Disease, Amyotrophic lateral sclerosis, lcsh:QH301-705.5, Alleles, Genetic association, Genetics, Blood Cells, DNA methylation, Genetic heterogeneity, Research, Gene Expression Profiling, dNaM, Neurodegenerative Diseases, medicine.disease, Human genetics, lcsh:Genetics, lcsh:Biology (General), Genetic Loci, Case-Control Studies, Neurodegenerative disorders, Disease Susceptibility, Biomarkers, Epigenesis, Genome-Wide Association Study
Abstract

Background People with neurodegenerative disorders show diverse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer’s disease, amyotrophic lateral sclerosis, and Parkinson’s disease. Results We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson’s disease (and none with Alzheimer’s disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights. Conclusions We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences.

Published
2021

24. A Comparison of Ten Polygenic Score Methods for Psychiatric Disorders Applied Across Multiple Cohorts

Author

Guiyan Ni, Jian Zeng, Joana A. Revez, Ying Wang, Zhili Zheng, Tian Ge, Restuadi Restuadi, Jacqueline Kiewa, Dale R. Nyholt, Jonathan R.I. Coleman, Jordan W. Smoller, Jian Yang, Peter M. Visscher, Naomi R. Wray, Stephan Ripke, Benjamin M. Neale, Aiden Corvin, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberley D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, Michael Davidson, Kenneth L. Davis, Franziska Degenhardt, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Giulio Genovese, Lyudmila Georgieva, Ina Giegling, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Marian L. Hamshere, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Annette M. Hartmann, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, David M. Hougaard, Masashi Ikeda, Inge Joa, Antonio Julià, René S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, James A. Knowles, Bettina Konte, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee, S. Hong Lee, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lönnqvist, Milan Macek, Patrik K.E. Magnusson, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Andrew M. McIntosh, Sandra Meier, Carin J. Meijer, Bela Melegh, Ingrid Melle, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Lili Milani, Vihra Milanova, Younes Mokrab, Derek W. Morris, Ole Mors, Kieran C. Murphy, Robin M. Murray, Inez Myin-Germeys, Bertram Müller-Myhsok, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O’Callaghan, Colm O’Dushlaine, F. Anthony O’Neill, Sang-Yun Oh, Ann Olincy, Line Olsen, Jim Van Os, Psychosis Endophenotypes International Consortium, Christos Pantelis, George N. Papadimitriou, Sergi Papiol, Elena Parkhomenko, Michele T. Pato, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietiläinen, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Alan R. Sanders, Ulrich Schall, Christian R. Schubert, Thomas G. Schulze, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Jianxin Shi, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Hon-Cheong So, Chris C.A. Spencer, Eli A. Stahl, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T. Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Söderman, Srinivas Thirumalai, Draga Toncheva, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Kari Stefansson, Wellcome Trust Case-Control Consortium, Rolf Adolfsson, Ole A. Andreassen, Douglas H.R. Blackwood, Elvira Bramon, Joseph D. Buxbaum, Anders D. Børglum, Sven Cichon, Ariel Darvasi, Enrico Domenici, Hannelore Ehrenreich, Tõnu Esko, Pablo V. Gejman, Michael Gill, Hugh Gurling, Christina M. Hultman, Nakao Iwata, Assen V. Jablensky, Erik G. Jönsson, Kenneth S. Kendler, George Kirov, Jo Knight, Todd Lencz, Douglas F. Levinson, Qingqin S. Li, Jianjun Liu, Anil K. Malhotra, Steven A. McCarroll, Andrew McQuillin, Jennifer L. Moran, Preben B. Mortensen, Bryan J. Mowry, Markus M. Nöthen, Roel A. Ophoff, Michael J. Owen, Aarno Palotie, Carlos N. Pato, Tracey L. Petryshen, Danielle Posthuma, Marcella Rietschel, Brien P. Riley, Dan Rujescu, Pak C. Sham, Pamela Sklar, David St Clair, Daniel R. Weinberger, Jens R. Wendland, Thomas Werge, Mark J. Daly, Patrick F. Sullivan, Michael C. O’Donovan, Maciej Trzaskowski, Enda M. Byrne, Abdel Abdellaoui, Mark J. Adams, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Elisabeth B. Binder, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, Toni-Kim Clarke, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Gregory E. Crawford, Gail Davies, Ian J. Deary, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Jerome C. Foo, Andreas J. Forstner, Héléna A. Gaspar, Fernando S. Goes, Scott D. Gordon, Jakob Grove, Lynsey S. Hall, Christine Søholm Hansen, Thomas F. Hansen, Ian B. Hickie, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, David M. Howard, Marcus Ising, Rick Jansen, Ian Jones, Lisa A. Jones, Eric Jorgenson, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Donald J. MacIntyre, Dean F. MacKinnon, Robert M. Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Peter McGuffin, Sarah E. Medland, Divya Mehta, Christel M. Middeldorp, Evelin Mihailov, Yuri Milaneschi, Francis M. Mondimore, Grant W. Montgomery, Sara Mostafavi, Niamh Mullins, Matthias Nauck, Bernard Ng, Michel G. Nivard, Paul F. O’Reilly, Hogni Oskarsson, Jodie N. Painter, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Roseann E. Peterson, Wouter J. Peyrot, Giorgio Pistis, Jorge A. Quiroz, Per Qvist, John P. Rice, Margarita Rivera, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Stanley I. Shyn, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Fabian Streit, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, Vassily Trubetskoy, André G. Uitterlinden, Daniel Umbricht, Sandra Van der Auwera, Albert M. van Hemert, Alexander Viktorin, Yunpeng Wang, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Yang Wu, Hualin S. Xi, Futao Zhang, Volker Arolt, Bernhard T. Baune, Klaus Berger, Dorret I. Boomsma, Udo Dannlowski, E.J.C. de Geus, J. Raymond DePaulo, Katharina Domschke, Hans J. Grabe, Steven P. Hamilton, Caroline Hayward, Andrew C. Heath, Stefan Kloiber, Glyn Lewis, Susanne Lucae, Pamela A.F. Madden, Patrik K. Magnusson, Nicholas G. Martin, Preben Bo Mortensen, Merete Nordentoft, Sara A. Paciga, Nancy L. Pedersen, Adult Psychiatry, APH - Mental Health, ANS - Complex Trait Genetics, ANS - Mood, Anxiety, Psychosis, Stress & Sleep, Ni, Guiyan, Zeng, Jian, Revez, Joana A., Wang, Ying, Zhili, Zheng, Ge, Tian, Restuadi, Restuadi, Kiewa, Jacqueline, Nyholt, Dale R, Coleman, Jonathan RI, Smoller, Jordan W, Lee, S Hong, APH - Methodology, Biological Psychology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Econometrics, Psychiatry, Department of Technology and Operations Management, Child and Adolescent Psychiatry / Psychology, Epidemiology, Erasmus MC other, Urology, Internal Medicine, Medical Informatics, Immunology, Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Reproduction & Development (AR&D), and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep

Subjects
0301 basic medicine, Multifactorial Inheritance, medicine.medical_specialty, LDpred2, BF, Genomics, Disease, Major depressive disorder, risk prediction, 03 medical and health sciences, 0302 clinical medicine, MegaPRS, SDG 3 - Good Health and Well-being, medicine, Humans, Genetic Predisposition to Disease, ddc:610, Genetic risk, Psychiatry, Biological Psychiatry, Genetic association, Depressive Disorder, Major, business.industry, Mental Disorders, medicine.disease, Genetic architecture, Polygenic scores, Risk prediction, polygenic scores, PRS-CS, psychiatric disorders, 030104 developmental biology, SBayesR, Schizophrenia, Cohort, Lassosum, RC0321, business, Psychiatric disorders, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

BACKGROUND: Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies. PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors.METHODS: The Psychiatric Genomics Consortium Working Groups for schizophrenia and major depressive disorder bring together many independently collected case-control cohorts. We used these resources (31,328 schizophrenia cases, 41,191 controls; 248,750 major depressive disorder cases, 563,184 controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and 9 methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) were compared.RESULTS: Compared with PC+T, the other 9 methods gave higher prediction statistics, MegaPRS, LDPred2, and SBayesR significantly so, explaining up to 9.2% variance in liability for schizophrenia across 30 target cohorts, an increase of 44%. For major depressive disorder across 26 target cohorts, these statistics were 3.5% and 59%, respectively.CONCLUSIONS: Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparisons and are recommended in applications to psychiatric disorders.

Published
2021

25. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis

Author

Anna A. E. Vinkhuyzen, Frederik J. Steyn, Beben Benyamin, Dominic B. Rowe, Tian Lin, Jan H. Veldink, Kelly L. Williams, Ian P. Blair, Merrilee Needham, Roger Pamphlett, Shyuan T. Ngo, Paul J. Hop, Anna Freydenzon, Allan F. McRae, Anjali K. Henders, Marta F. Nabais, Perminder S. Sachdev, Robert D. Henderson, Eilis Hannon, Futao Zhang, Naomi R. Wray, Pamela A. McCombe, Restuadi Restuadi, Matthew A. Brown, Fleur C. Garton, Nigel G. Laing, Peter M. Visscher, Jonathan Mill, Leanne Wallace, Matthew R. Robinson, Jacob Gratten, Garth A. Nicholson, Jian Yang, Susan Mathers, Karen A. Mather, Ramona A. J. Zwamborn, Costanza L. Vallerga, Nabais, Marta F, Lin, Tian, Benyamin, Beben, Williams, Kelly L, and Wray, Naomi R

Subjects
0301 basic medicine, amyotrophic lateral sclerosis, medicine.medical_specialty, lcsh:QH426-470, lcsh:Medicine, Predictive markers, Gastroenterology, Article, 03 medical and health sciences, 0302 clinical medicine, single nucleotide polymorphism, Internal medicine, Genetics, Medicine, Amyotrophic lateral sclerosis, Molecular Biology, Genetics (clinical), DNA methylation, business.industry, lcsh:R, Confounding, Area under the curve, Methylation, cohort analysis, medicine.disease, lcsh:Genetics, 030104 developmental biology, Out of sample, Cohort, business, 030217 neurology & neurosurgery
Abstract

We conducted DNA methylation association analyses using Illumina 450K data from whole blood for an Australian amyotrophic lateral sclerosis (ALS) case–control cohort (782 cases and 613 controls). Analyses used mixed linear models as implemented in the OSCA software. We found a significantly higher proportion of neutrophils in cases compared to controls which replicated in an independent cohort from the Netherlands (1159 cases and 637 controls). The OSCA MOMENT linear mixed model has been shown in simulations to best account for confounders. When combined in a methylation profile score, the 25 most-associated probes identified by MOMENT significantly classified case–control status in the Netherlands sample (area under the curve, AUC = 0.65, CI95% = [0.62–0.68], p = 8.3 × 10−22). The maximum AUC achieved was 0.69 (CI95% = [0.66–0.71], p = 4.3 × 10−34) when cell-type proportion was included in the predictor.

Published
2020

26. Imprint of assortative mating on the human genome

Author

Maciej Trzaskowski, Michael E. Goddard, Jian Yang, Matthew R. Robinson, Peter M. Visscher, Patrick Turley, Kathryn E. Kemper, Daniel J. Benjamin, David Cesarini, Loic Yengo, Yuanhao Yang, Matthew C. Keller, Jacob Gratten, and Naomi R. Wray

Subjects
Male, 0301 basic medicine, Social Psychology, Experimental and Cognitive Psychology, Single-nucleotide polymorphism, Biology, Population stratification, Polymorphism, Single Nucleotide, Genome, White People, Article, 03 medical and health sciences, Behavioral Neuroscience, Quantitative Trait, Heritable, Humans, Marriage, Alleles, reproductive and urinary physiology, Genome, Human, Assortative mating, Genomic signature, Body Height, 030104 developmental biology, Mate choice, Evolutionary biology, behavior and behavior mechanisms, Trait, Educational Status, Female, Human genome
Abstract

Preference for mates with similar phenotypes; that is, assortative mating, is widely observed in humans1–5 and has evolutionary consequences6–8. Under Fisher's classical theory6, assortative mating is predicted to induce a signature in the genome at trait-associated loci that can be detected and quantified. Here, we develop and apply a method to quantify assortative mating on a specific trait by estimating the correlation (θ) between genetic predictors of the trait from single nucleotide polymorphisms on odd- versus even-numbered chromosomes. We show by theory and simulation that the effect of assortative mating can be quantified in the presence of population stratification. We applied this approach to 32 complex traits and diseases using single nucleotide polymorphism data from ~400,000 unrelated individuals of European ancestry. We found significant evidence of assortative mating for height (θ = 3.2%) and educational attainment (θ = 2.7%), both of which were consistent with theoretical predictions. Overall, our results imply that assortative mating involves multiple traits and affects the genomic architecture of loci that are associated with these traits, and that the consequence of mate choice can be detected from a random sample of genomes. A century after being predicted by theory, the authors detect and quantify the genomic signature of assortative mating in ~400,000 contemporary human genomes, and report new genetic evidence for assortative mating on height and educational attainment.

Published
2018

27. Trans-eQTLs identified in whole blood have limited influence on complex disease biology

Author

Alexander Holloway, Joseph E. Powell, Naomi R. Wray, Peter Smartt, Luke R. Lloyd-Jones, Jacob Gratten, and Chloe X. Yap

Subjects
0301 basic medicine, Genetics, Blood Cells, Quantitative Trait Loci, Gene regulatory network, Single-nucleotide polymorphism, Genome-wide association study, Disease, Biology, Quantitative trait locus, Polymorphism, Single Nucleotide, Phenotype, Article, 03 medical and health sciences, 030104 developmental biology, Polymorphism (computer science), Expression quantitative trait loci, Humans, Genetic Predisposition to Disease, Biomarkers, Genetics (clinical), Genome-Wide Association Study
Abstract

Trans-eQTLs have been implicated in complex traits and common diseases, but many were initially identified on the basis of having an effect in cis, and there has been no assessment of the significance of the overlap in relation to chance expectations. Here, we investigated whether trans-expression quantitative trait loci (eQTL) associations identified in whole blood contribute to variance in complex traits by determining (1) whether genome-wide significant (GWS) single-nucleotide polymorphisms (SNPs) were enriched for trans-eQTL (including trans-only eQTL), and (2) whether the genomic regions surrounding associated trans-genes were enriched for statistical associations in the relevant GWAS. On average for a given phenotype, we identify 4.8% of GWS SNPs overlapping with trans-eQTL present in blood, and show that for the majority of these phenotypes, this observation does not exceed that expected by chance. Likewise, we observe no enrichment for genetic associations with the GWAS phenotype in the regions surrounding the linked trans-genes, with the exception of rheumatoid arthritis. Interestingly, the GWS SNPs for each phenotype were consistently more enriched for unique trans-eQTL SNPs than trans-eQTL SNP-probe pairs (p = 4 × 10−7), with schizophrenia the only exception. This relative enrichment for trans-eQTL SNPs over trans-eQTL SNP-probe pairs implies that trait-associated trans-eQTL SNPs in whole blood are less likely to be 'master regulators' than random trans-eQTL SNPs. Taken together, these results suggest little evidence for the role of blood-based trans-eQTL in complex traits and disease, although this may reflect the finite size of currently available data sets and our findings may not hold for trans-eQTLs in more trait-relevant tissues. All software is publically available at https://github.com/IMB-Computational-Genomics-Lab/eqtlOverlapper .

Published
2018

28. Gene networks associated with non-syndromic intellectual disability

Author

Stephen Rudd, Soohyun Lee, Paul A. Dawson, Peter M. Visscher, Jacob Gratten, and Johannes B. Prins

Subjects
0301 basic medicine, Genetics, Candidate gene, Genetic heterogeneity, Gene regulatory network, Biology, medicine.disease, Phenotype, Genetic architecture, 03 medical and health sciences, Cellular and Molecular Neuroscience, 030104 developmental biology, 0302 clinical medicine, Schizophrenia, Intellectual Disability, Intellectual disability, medicine, Humans, Gene Regulatory Networks, Gene, 030217 neurology & neurosurgery
Abstract

Non-syndromic intellectual disability (NS-ID) is a genetically heterogeneous disorder, with more than 200 candidate genes to date. Despite the increasing number of novel mutations detected, a relatively low number of recurrently mutated genes have been identified, highlighting the complex genetic architecture of the disorder. A systematic search of PubMed and Medline identified 245 genes harbouring non-synonymous variants, insertions or deletions, which were identified as candidate NS-ID genes from case reports or from linkage or pedigree analyses. From this list, 33 genes are common to syndromic intellectual disability (S-ID) and 58 genes are common to certain neurological and neuropsychiatric disorders that often include intellectual disability as a clinical feature. We examined the evolutionary constraint and brain expression of these gene sets, and we performed gene network and protein-protein interaction analyses using GeneGO MetaCoreTM and DAPPLE, respectively. The 245 NS-ID candidate genes were over-represented in axon guidance, synaptogenesis, cell adhesion and neurotransmission pathways, all of which are key neurodevelopmental processes for the establishment of mature neuronal circuitry in the brain. These 245 genes exhibit significantly elevated expression in human brain and are evolutionarily constrained, consistent with expectations for a brain disorder such as NS-ID that is associated with reduced fecundity. In addition, we report enrichment of dopaminergic and glutamatergic pathways for those candidate NS-ID genes that are common to S-ID and/or neurological and neuropsychiatric disorders that exhibit intellectual disability. Collectively, this study provides an overview and analysis of gene networks associated with NS-ID and suggests modulation of neurotransmission, particularly dopaminergic and glutamatergic systems as key contributors to synaptic dysfunction in NS-ID.

Published
2017

29. Autism-related dietary preferences mediate autism-gut microbiome associations

Author

Lorelle Nunn, Anne Masi, Paul M. Thompson, Peter M. Visscher, Mira Levis Frenk, Anjali K. Henders, Alexis Harun, Michaela Nothard, Jacob Gratten, Paul A. Dawson, Lachlan T. Strike, Cheryl Dissanayake, Jodie Leslie, David L. A. Wood, Margaret J. Wright, Gail A. Alvares, Claire Hafekost, Jessica L. Miller, Melanie Muniandy, Lauren P. Lawson, Chloe X. Yap, Allan F. McRae, Gerald Holtmann, Leanne Wallace, Katie L. McMahon, Rachel Grove, Helen Heussler, Valsamma Eapen, Restuadi Restuadi, Rachel Jellett, Nisha E. Mathew, Narelle K. Hansell, Tiana McLaren, Naomi R. Wray, Feroza Khan, Lutz Krause, Dominique Cleary, Helen Holdsworth, Gene W. Tyson, Greig I. de Zubicaray, and Andrew J. O. Whitehouse

Subjects
Stool consistency, Confounding, Biology, medicine.disease, behavioral disciplines and activities, Biobank, General Biochemistry, Genetics and Molecular Biology, Gut microbiome, Autism spectrum disorder, Metagenomics, mental disorders, medicine, Autism, Microbiome, Clinical psychology
Abstract

There is increasing interest in the potential contribution of the gut microbiome to autism spectrum disorder (ASD). However, previous studies have been underpowered and have not been designed to address potential confounding factors in a comprehensive way. We performed a large autism stool metagenomics study (n = 247) based on participants from the Australian Autism Biobank and the Queensland Twin Adolescent Brain project. We found negligible direct associations between ASD diagnosis and the gut microbiome. Instead, our data support a model whereby ASD-related restricted interests are associated with less-diverse diet, and in turn reduced microbial taxonomic diversity and looser stool consistency. In contrast to ASD diagnosis, our dataset was well powered to detect microbiome associations with traits such as age, dietary intake, and stool consistency. Overall, microbiome differences in ASD may reflect dietary preferences that relate to diagnostic features, and we caution against claims that the microbiome has a driving role in ASD.

Published
2021

30. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Author

Patricia T. Michie, Franziska Degenhardt, Brandon Wormley, Paola Giusti-Rodríguez, Mark J. Daly, Raquelle I. Mesholam-Gately, Ingrid Melle, Sibylle G. Schwab, Andrew McQuillin, Benjamin M. Neale, Joshua L. Roffman, Abraham Reichenberg, Pamela Sklar, Diana O. Perkins, Jennifer L. Moran, Donald W. Black, Per Hoffmann, A. Hofman, Hailiang Huang, John L. Waddington, Giulio Genovese, Aaron R. Wolen, Deborah L. Levy, David Curtis, Digby Quested, Carlos N. Pato, Nicholas John Craddock, Stephanie Williams, Kung Yee Liang, Zhouzhi Wang, Tracey L. Petryshen, Ann E. Pulver, Randy L. Buckner, Stephan Ripke, Roel A. Ophoff, Danielle Posthuma, Lili Milani, Jacques Mallet, Menachem Fromer, Christian R. Marshall, Jaana Suvisaari, Jana Strohmaier, Richard Bruggeman, Marcella Rietschel, Ayman H. Fanous, Andrew M. McIntosh, James T.R. Walters, Dimitris Dikeos, Panos Roussos, Veikko Salomaa, Aiden Corvin, Carin J. Meijer, Tiina Paunio, Assen Jablensky, Sarah E. Bergen, Nancy G. Buccola, Annelie Nordin, Wolfgang Maier, Srdjan Djurovic, Naomi R. Wray, Aniket Shetty, Joel Eriksson, Dan Rujescu, Jouko Lönnqvist, Brian Kelly, Wenting Wu, Alexander Richards, Frans Henskens, Rich Belliveau, Bryan J. Mowry, Elodie Drapeau, Andreas J. Forstner, Silviu Alin Bacanu, Jubao Duan, Tõnu Esko, Bernard Lerer, Carmel M. Loughland, Olli Pietiläinen, Michael Conlon O'Donovan, Shaun M. Purcell, Michael Gill, Thomas G. Schulze, Douglas S. Greer, Stephen W. Scherer, Eli A. Stahl, Markus M. Nöthen, Guiqing Cai, William M. Brandler, Kristin K. Nicodemus, Dominique Campion, David A. Collier, Farooq Amin, Joel N. Hirschhorn, Robin M. Murray, Timothy G. Dinan, Mark Reimers, Murray J. Cairns, Rodney J. Scott, Aarno Palotie, Robert Freedman, Nelson B. Freimer, Joshua R. Atkins, Gary Donohoe, Ann Olincy, Jonathan Sebat, Colm McDonald, Srinivas Thirumalai, John Powell, Jo Knight, Vahram Haroutunian, Dieter B. Wildenauer, Tim B. Bigdeli, Lieuwe de Haan, Peter Eichhammer, James J. Crowley, Lynn E. DeLisi, Ulrich Schall, Rolf Adolfsson, Marcelo Bertalan, Thomas Hansen, Eric Strengman, Michael Davidson, Dheeraj Malhotra, Manuel Mattheisen, Jeffrey A. Lieberman, Benedicto Crespo-Facorro, Stephanie Godard, Edward M. Scolnick, Jonathan Pimm, Bertram Müller-Myhsok, Qingqin Li, Michele T. Pato, Wiepke Cahn, Christos Pantelis, Ingrid Agartz, Brendan Bulik-Sullivan, Madhusudan Gujral, Martilias S. Farrell, Brady J. Maher, Laurent Essioux, Karin V Fuentes Fajarado, Andres Metspalu, Stephanie H. Witt, Patrick F. Sullivan, Mark Weiser, Younes Mokrab, Kai How Farh, Line Olsen, Dermot Walsh, Peter Holmans, Hugh Gurling, Joseph I. Friedman, Andrew Pocklington, Daniel P. Howrigan, Lude Franke, Tune H. Pers, Larry J. Seidman, Pablo V. Gejman, Dalila Pinto, Michael John Owen, Inez Myin-Germeys, Steven A. McCarroll, Wei Cheng, Jackie Goldstein, C. Robert Cloninger, Elliot S. Gershon, Deborah A. Nertney, Thomas Werge, Noa Carrera, Kieran C. Murphy, Rita M. Cantor, Ariel Darvasi, Mark Hansen, Annette M. Hartmann, Ole A. Andreassen, Bradley T. Webb, Henrik B. Rasmussen, David Cohen, Elvira Bramon, Erik G. Jönsson, Vaughan J. Carr, Pui Y. Lee, Masashi Ikeda, Daniele Merico, Danny Antaki, Brien P. Riley, Stefan Herms, Igor Nenadic, Bettina Konte, Kimberley D. Chambert, Jurgen Del Favero, George Kirov, Matthew C. Keller, Jacob Gratten, Douglas F. Levinson, Luba Kalaydjieva, Bhooma Thiruvahindrapuram, Alan R. Sanders, Sang-Yun Oh, Alkes L. Price, Vihra Milanova, Juha Veijola, Erik Söderman, Dragan M. Svrakic, David H. Kavanagh, Patrik K. E. Magnusson, Douglas Blackwood, Nakao Iwata, Jim van Os, Jeremy M. Silverman, Elena Parkhomenko, Kenneth L. Davis, Jing Qin Wu, Eadbhard O'Callaghan, Chris C. A. Spencer, Juha Karjalainen, Anna K. Kähler, Clement C. Zai, Nigel Williams, Joseph D. Buxbaum, Jin P. Szatkiewicz, Laura Nisenbaum, Sang Hong Lee, Yunjung Kim, Colm O'Dushlaine, René S. Kahn, Morten Mattingsdal, Inge Joa, Marian L. Hamshere, Frank Dudbridge, Ina Giegling, Sandra Meier, Derek W. Morris, Robert W. McCarley, Douglas M. Ruderfer, Paul Cormican, Lyudmila Georgieva, Sven Cichon, Josef Frank, Jianxin Shi, George N. Papadimitriou, Kenneth S. Kendler, Margot Albus, Enrico Domenici, Claudine Laurent, Francis A. O'Neill, Adam Savitz, Jordan W. Smoller, James L. Kennedy, Peter M. Visscher, Valentina Escott-Price, Christina M. Hultman, T. Scott Stroup, Elizabeth Bevilacqua, James A. Knowles, William Byerley, Paul A. Tooney, Madeline Alexander, Stanley V. Catts, David St Clair, Sophie E. Legge, Gerald Nestadt, Michelle S. Maile, Perceptual and Cognitive Neuroscience (PCN), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Clinical Cognitive Neuropsychiatry Research Program (CCNP), Stem Cell Aging Leukemia and Lymphoma (SALL), Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, MUMC+: Hersen en Zenuw Centrum (3), MUMC+: MA Psychiatrie (3), Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, APH - Mental Health, ANS - Complex Trait Genetics, Adult Psychiatry, Other departments, Marshall, Christian R, Howrigan, Daniel P, Merico, Daniele, Thiruvahindrapuram, Bhooma, Lee, S Hong, Sebat, Jonathan, Psychosis Endophenotypes International Consortium, CNV and Schizophrenia Working Groups of the Psychiatric Genomics Consortium, CNV, Schizophrenia Working Grp, Psychosis Endophenotypes, Rehabilitation Medicine, and Child and Adolescent Psychiatry / Psychology

Subjects
0301 basic medicine, Male, 16P11.2, Duplication, Autism, Rearrangement, Genome-wide association study, Copy number variant, Gene, Medical and Health Sciences, 0302 clinical medicine, DUPLICATIONS, Risk Factors, Gene duplication, Genotype, Disorder, Copy-number variation, Genetics, Genetics & Heredity, RISK, copy number variation, REARRANGEMENTS, Biological Sciences, 16p11.2, 3. Good health, Phenotype, Female, Risk, CNVS, Genetic Markers, genetic etiology, CNV and Schizophrenia Working Groups of the Psychiatric Genomics Consortium, DNA Copy Number Variations, DISORDERS, CNV, Non-allelic homologous recombination, PHENOTYPES, Biology, 03 medical and health sciences, SDG 3 - Good Health and Well-being, genomics, Journal Article, Humans, Comparative Study, Genetic Predisposition to Disease, AUTISM, Psychosis Endophenotypes International Consortium, MUTATIONS, Case-control study, Odds ratio, R1, GENE, 030104 developmental biology, genetics research, Genetic marker, Genetic Loci, Case-Control Studies, Mutation, Schizophrenia, Human medicine, 030217 neurology & neurosurgery, Developmental Biology, Genome-Wide Association Study
Abstract

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 x 10(-15)), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 x 10(-6)). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 x 10(-11)) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 x 10(-5)). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination. Refereed/Peer-reviewed

Published
2017

31. Sizing up whole-genome sequencing studies of common diseases

Author

Naomi R. Wray and Jacob Gratten

Subjects
0301 basic medicine, Whole genome sequencing, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Genetics, Genome-wide association study, Computational biology, Biology, Genome, 030217 neurology & neurosurgery, De novo mutations, Exome sequencing
Abstract

The triplet code underpins analyses of rare and de novo mutations in exome sequencing data, but analysis of the noncoding genome is much more challenging. A new analytical framework for common, complex diseases highlights the need for very large samples to overcome the unavoidable multiple-testing burden and hence provides preemptive warnings against underpowered studies.

Published
2018

32. Evidence for Genetic Overlap Between Schizophrenia and Age at First Birth in Women

Author

Elodie Drapeau, Robert W. McCarley, Jim van Os, Svetlana A. Limborska, Elvira Bramon, Milan Macek, Divya Mehta, Lieuwe de Haan, Christos Pantelis, Inge Joa, Daniel R. Weinberger, Andrew McQuillin, Lynn E. DeLisi, Ulrich Schall, Tõnu Esko, Digby Quested, Jacob Gratten, Gary Donohoe, Kenneth S. Kendler, Derek W. Morris, Ole A. Andreassen, Peter M. Visscher, Valentina Escott-Price, Lyudmila Georgieva, John L. Waddington, Sara Marsal, Naomi R. Wray, Danielle Posthuma, Benedicto Crespo-Facorro, Rita M. Cantor, Ariel Darvasi, Béla Melegh, Jing Qin Wu, Zhihong Zhu, Kieran C. Murphy, Felix C. Tropf, Inez Myin-Germeys, Antonio Julià, Paul A. Tooney, Frans Henskens, C. Robert Cloninger, Bryan J. Mowry, Larry J. Seidman, Bernard Lerer, Andres Metspalu, Carmel M. Loughland, Mark Weiser, Gibran Hemani, Ann Olincy, Joseph D. Buxbaum, Silviu-Alin Bacanu, Srdjan Djurovic, Andrew M. McIntosh, Jian Yang, Patricia T. Michie, Harold Snieder, Richard Bruggeman, John J. McGrath, Nicola Barban, Rodney J. Scott, Nelson B. Freimer, Timothy G. Dinan, Melinda Mills, S. Hong Lee, David Cohen, Andrey Khrunin, Andrew Bakshi, Murray J. Cairns, Patrik K. E. Magnusson, Draga Toncheva, Universidad de Cantabria, Mehta, Divya, Tropf, Felix C, Gratten, Jacob, Bakshi, Andrew, Zhu, Zhihong, Bacanu, Silviu-Alin, Hemani, Gibran, Magnusson, Patrik KE, Barban, Nicola, Esko, Tonu, Metspalu, Andres, Snieder, Harold, Mowry, Bryan J, Kendler, Kenneth S, Yang, Jian, Visscher, Peter M, McGrath, John J, Mills, Melinda C, Wray, Naomi R, Lee, S Hong, Schizophrenia Working Group of the Psychiatric Genomics Consortium, LifeLines Cohort Study, TwinsUK, RS: MHeNs - R2 - Mental Health, MUMC+: MA Psychiatrie (3), MUMC+: Hersen en Zenuw Centrum (3), Psychiatrie & Neuropsychologie, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Adult Psychiatry, Sociology/ICS, Life Course Epidemiology (LCE), Mehta Divya, Tropf Felix C., Gratten Jacob, Bakshi Andrew, Zhu Zhihong, Bacanu Silviu-Alin, Hemani Gibran, Magnusson Patrik K. E., BARBAN N, Esko Tonu, Metspalu Andre, Snieder Harold, Mowry Bryan J., Kendler Kenneth S., Yang Jian, Visscher Peter M., McGrath John J., Mills Melinda C., Wray Naomi R., and Lee S. Hong

Subjects
0301 basic medicine, Denmark, Genome-wide association study, genetic risk, Cohort Studies, 0302 clinical medicine, Pregnancy, GWAS, genetics, Psychiatry, RISK, PSYCHIATRIC-DISORDERS, BIPOLAR DISORDER, 3. Good health, Psychiatry and Mental health, Birth order, Phenotype, PATERNAL AGE, Schizophrenia, Female, Maternal Age, Cohort study, Adult, medicine.medical_specialty, Offspring, Article, 03 medical and health sciences, PSYCHOSIS, medicine, Humans, Genetic Predisposition to Disease, Bipolar disorder, Alleles, Genetic association, genome-wide association study, business.industry, medicine.disease, de novo mutation, schizophrenia, 030104 developmental biology, maternal age, DE-NOVO MUTATIONS, Birth Order, business, 030217 neurology & neurosurgery, Genome-Wide Association Study, Demography, first birth
Abstract

IMPORTANCE: A recently published study of national data by McGrath et al in 2014 showed increased risk of schizophrenia (SCZ) in offspring associated with both early and delayed parental age, consistent with a U-shaped relationship. However, it remains unclear if the risk to the child is due to psychosocial factors associated with parental age or if those at higher risk for SCZ tend to have children at an earlier or later age. OBJECTIVE: To determine if there is a genetic association between SCZ and age at first birth (AFB) using genetically informative but independently ascertained data sets. DESIGN, SETTING, AND PARTICIPANTS: This investigation used multiple independent genome-wide association study data sets. The SCZ sample comprised 18?957 SCZ cases and 22?673 controls in a genome-wide association study from the second phase of the Psychiatric Genomics Consortium, and the AFB sample comprised 12?247 genotyped women measured for AFB from the following 4 community cohorts: Estonia (Estonian Genome Center Biobank, University of Tartu), the Netherlands (LifeLines Cohort Study), Sweden (Swedish Twin Registry), and the United Kingdom (TwinsUK). Schizophrenia genetic risk for each woman in the AFB community sample was estimated using genetic effects inferred from the SCZ genome-wide association study. MAIN OUTCOMES AND MEASURES: We tested if SCZ genetic risk was a significant predictor of response variables based on published polynomial functions that described the relationship between maternal age and SCZ risk in offspring in Denmark. We substituted AFB for maternal age in these functions, one of which was corrected for the age of the father, and found that the fit was superior for the model without adjustment for the father's age. RESULTS: We observed a U-shaped relationship between SCZ risk and AFB in the community cohorts, consistent with the previously reported relationship between SCZ risk in offspring and maternal age when not adjusted for the age of the father. We confirmed that SCZ risk profile scores significantly predicted the response variables (coefficient of determination R2?=?1.1E-03, P?=?4.1E-04), reflecting the published relationship between maternal age and SCZ risk in offspring by McGrath et al in 2014. CONCLUSIONS AND RELEVANCE: This study provides evidence for a significant overlap between genetic factors associated with risk of SCZ and genetic factors associated with AFB. It has been reported that SCZ risk associated with increased maternal age is explained by the age of the father and that de novo mutations that occur more frequently in the germline of older men are the underlying causal mechanism. This explanation may need to be revised if, as suggested herein and if replicated in future studies, there is also increased genetic risk of SCZ in older mothers. This research is supported by grants 613602, 1047956, 1078901, 1080157, 1087889, and 1067795 from the Australian National Health and Medical Research Council and by grants DE130100614 and DP160102126 from the Australian Research Council. Primary analyses of the SchizophreniaWorking Group of the Psychiatric Genomics Consortium data were conducted on the Genetic Cluster Computer (http://www .geneticcluster.org) hosted by SURFsara and supported by grant NOW480-05-003 from the Netherlands Scientific Organization, along with a supplement from the Dutch Brain Foundation and the Vrije Universitiet Amsterdam. TwinsUK was funded by theWellcome Trust, by grant FP7/2007-2013 from the European Community’s Seventh Framework Programme, and by support from the National Institute for Health Research–funded BioResource, Clinical Research Facility, and Biomedical Research Centre based at Guy’s and St Thomas’ National Health Service Foundation Trust in partnership with King’s College London, and single-nucleotide polymorphism genotyping was performed by theWellcome Trust Sanger Institute and National Eye Institute via the National Institute for Health/Center for Inherited Disease Research. Estonian Genome Center Biobank, University of Tartu, received targeted financing by grant IUT20-60 from the Estonian Research Council, Center of Excellence in Genomics, and University of Tartu, and data analyses were carried out in part in the High Performance Computing Center of the University of Tartu. The Swedish Twin Registry is supported by Karolinska Institutet. Mr Tropf received funding from sciencestarter.de for a research visit to The University of Queensland. The research leading to these results received funding from the European Research Council via an ERC Consolidator Grant SOCIOGENOME (grant 615603 awarded to Dr Mills [http://www.sociogenome.com]).

Published
2016

33. Mapping and differential expression analysis from short-read RNA-Seq data in model organisms

Author

Qiongyi Zhao, Xuan Li, Restuadi Restuadi, and Jacob Gratten

Subjects
0301 basic medicine, Genetics, Differential expression analysis, ved/biology, Applied Mathematics, genetic processes, ved/biology.organism_classification_rank.species, RNA, RNA-Seq, Computational biology, Biology, Short read, Biochemistry, Genetics and Molecular Biology (miscellaneous), Computer Science Applications, Transcriptome, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Modeling and Simulation, natural sciences, Differential expression, Model organism, 030217 neurology & neurosurgery, Reference genome
Abstract

Recent advances in next-generation sequencing technology allow high-throughput RNA sequencing (RNA-Seq) to be widely applied in transcriptomic studies. For model organisms with a reference genome, the first step in analysis of RNA-Seq data involves mapping of short-read sequences to the reference genome. Reference-guided transcriptome assembly is an optional step, which is recommended if the aim is to identify novel transcripts. Following read mapping, the primary interest of biologists in many RNA-Seq studies is the investigation of differential expression between experimental groups. In this review, we discuss recent developments in RNA-Seq data analysis applied to model organisms, including methods and algorithms for direct mapping, reference-guided transcriptome assembly and differential expression analysis, and provide insights for the future direction of RNA-Seq.

Published
2016

34. Parkinson disease age of onset GWAS: defining heritability, genetic loci and a-synuclein mechanisms

Author

Joseph Jankovic, Jean-Christophe Corvol, J. Raphael Gibbs, Alexis Brice, Pentti J. Tienari, Rainer von Coelln, Kari Majamaa, Andrew B. Singleton, Mathias Toft, Johan Marinus, Ziv Gan-Or, Javier Simón-Sánchez, Peter Heutink, Lasse Pihlstrøm, Alastair J. Noyce, Thomas Gasser, Lisa M. Shulman, Hirotaka Iwaki, Manuela Tan, John Hardy, Jacobus J. van Hilten, Joshua M. Shulman, Suzanne Lesage, Dena G. Hernandez, Cornelis Blauwendraat, Jacob Gratten, Hampton L. Leonard, Manu Sharma, Ari Siitonen, David A. Hinds, Karl Heilbron, Peter M. Visscher, Lynne Krohn, Mike A. Nalls, Sara Bandres-Ciga, Huw R. Morris, Costanza L. Vallerga, Donald G. Grosset, N Wood, Sonja W. Scholz, and Claudia Schulte

Subjects
Genetics, 0303 health sciences, Locus (genetics), Genome-wide association study, Heritability, Biology, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Genetic variation, Synuclein, Genetic variability, Age of onset, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract

Increasing evidence supports an extensive and complex genetic contribution to Parkinson’s disease (PD). Previous genome-wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age of onset are largely unknown. Here we performed an age of onset GWAS based on 28,568 PD cases. We estimated that the heritability of PD age of onset due to common genetic variation was ~0.11, lower than the overall heritability of risk for PD (~0.27) likely in part because of the subjective nature of this measure. We found two genome-wide significant association signals, one at SNCA and the other a protein-coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni corrected significant effect at other known PD risk loci, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. In addition, we identified that GBA coding variant carriers had an earlier age of onset compared to non-carriers. Notably, SNCA, TMEM175, SCARB2, BAG3 and GBA have all been shown to either directly influence alpha-synuclein aggregation or are implicated in alpha-synuclein aggregation pathways. Remarkably, other well-established PD risk loci such as GCH1, MAPT and RAB7L1/NUCKS1 (PARK16) did not show a significant effect on age of onset of PD. While for some loci, this may be a measure of power, this is clearly not the case for the MAPT locus; thus genetic variability at this locus influences whether but not when an individual develops disease. We believe this is an important mechanistic and therapeutic distinction. Furthermore, these data support a model in which alpha-synuclein and lysosomal mechanisms impact not only PD risk but also age of disease onset and highlights that therapies that target alpha-synuclein aggregation are more likely to be disease-modifying than therapies targeting other pathways.

Published
2018

35. Expanding Parkinson’s disease genetics: novel risk loci, genomic context, causal insights and heritable risk

Author

Sonja W. Scholz, Alastair J. Noyce, Claudia Schulte, Pentti J. Tienari, Huw R. Morris, Karl Heilbron, Angli Xue, Jean-Christophe Corvol, Manuela Tan, N Wood, Dena G. Hernandez, Sara Bandres-Ciga, Lisa M. Shulman, Rainer von Coelln, Faraz Faghri, Andrew B. Singleton, Diana Chang, Demis A. Kia, Jian Yang, John Hardy, Jose Bras, Peter M. Visscher, Lynne Krohn, J. Raphael Gibbs, Tushar Bangale, Mike A. Nalls, Alexis Brice, Hirotaka Iwaki, Cornelis Blauwendraat, Lasse Pihlstrøm, Jacob Gratten, Joseph Jankovic, Ole A. Andreassen, Javier Simón-Sánchez, Kari Majamaa, Hampton L. Leonard, Ziv Gan-Or, Thomas Gasser, Juan A. Botía, Maria Martinez, Costanza L. Vallerga, Robert R. Graham, Joshua M. Shulman, Suzanne Lesage, David A. Hinds, Ari Siitonen, Mathias Toft, Manu Sharma, Emily Young, Peter Heutink, and Margaret Sutherland

Subjects
Genetics, 0303 health sciences, Single-nucleotide polymorphism, Context (language use), Disease, Biology, Biobank, Causality, Genetic architecture, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Mendelian randomization, Gene, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

We performed the largest genome-wide association study of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases, and 1.4M controls. We identified 90 independent genome-wide significant signals across 78 loci, including 38 independent risk signals in 37 novel loci. These variants explained 26-36% of the heritable risk of PD. Tests of causality within a Mendelian randomization framework identified putatively causal genes for 70 risk signals. Tissue expression enrichment analysis suggested that signatures of PD loci were heavily brain-enriched, consistent with specific neuronal cell types being implicated from single cell expression data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. In sum, these data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified.

Published
2018
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36. Improved prediction of chronological age from DNA methylation limits it as a biomarker of ageing

Author

John B.J. Kwok, Jacob Gratten, Ian J. Deary, Javed Fowdar, Tian Lin, Rosie M. Walker, George D. Mellick, John F. Pearson, Naomi R. Wray, Ian B. Hickie, Peter M. Visscher, Peter A. Silburn, Chris Haley, Toni L. Pitcher, Andrew M. McIntosh, Grant W. Montgomery, Simon J.G. Lewis, Sarah E. Harris, Dongsheng Fan, Martin A. Kennedy, Jian Yang, Ji He, Trevor P. Anderson, Kathryn L. Evans, Qian Zhang, Riccardo E. Marioni, Anjali K. Henders, Glenda M. Halliday, Paul Redmond, David J. Porteous, Allan F. McRae, Costanza L. Vallerga, and Alison D. Murray

Subjects
0303 health sciences, Confounding, Contrast (statistics), Chronological age, Best linear unbiased prediction, Biology, 03 medical and health sciences, 0302 clinical medicine, Sample size determination, Ageing, Statistics, DNA methylation, Biomarker (medicine), 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

DNA methylation is associated with age. The deviation of age predicted from DNA methylation from actual age has been proposed as a biomarker for ageing. However, a better prediction of chronological age implies less opportunity for biological age. Here we used 13,661 samples (from blood and saliva) in the age range of 2 to 104 years from 14 cohorts measured on Illumina HumanMethylation450/EPIC arrays to perform prediction analyses. We show that increasing the sample size achieves a smaller prediction error and higher correlations in test datasets. We demonstrate that smaller prediction errors provide a limit to how much variation in biological ageing can be captured by methylation and provide evidence that age predictors from small samples are prone to confounding by cell composition. Our predictor shows a similar or better performance in non-blood tissues including saliva, endometrium, breast, liver, adipose and muscle, compared with Horvath’s across-tissue age predictor.

Published
2018
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37. Imprint of Assortative Mating on the Human Genome

Author

David Cesarini, Daniel J. Benjamin, Matthew C. Keller, Matthew R. Robinson, Jacob Gratten, Loic Yengo, Michael E. Goddard, Maciej Trzaskowski, Naomi R. Wray, Yuanhao Yang, Patrick Turley, Peter M. Visscher, Kathryn E. Kemper, and Jian Yang

Subjects
0303 health sciences, Assortative mating, Single-nucleotide polymorphism, Biology, Population stratification, Genome, Correlation, 03 medical and health sciences, 0302 clinical medicine, Mate choice, Evolutionary biology, Trait, Human genome, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Non-random mate-choice with respect to complex traits is widely observed in humans, but whether this reflects true phenotypic assortment, environment (social homogamy) or convergence after choosing a partner is not known. Understanding the causes of mate choice is important, because assortative mating (AM) if based upon heritable traits, has genetic and evolutionary consequences. AM is predicted under Fisher’s classical theory1to induce a signature in the genome at trait-associated loci that can be detected and quantified. Here, we develop and apply a method to quantify AM on a specific trait by estimating the correlation (θ) between genetic predictors of the trait from SNPs on odd versus even chromosomes. We show by theory and simulation that the effect of AM can be distinguished from population stratification. We applied this approach to 32 complex traits and diseases using SNP data from ∼400,000 unrelated individuals of European ancestry. We found significant evidence of AM for height (θ=3.2%) and educational attainment (θ=2.7%), both consistent with theoretical predictions. Overall, our results imply that AM involves multiple traits, affects the genomic architecture of loci that are associated with these traits and that the consequence of mate choice can be detected from a random sample of genomes.

Published
2018

38. Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences1

Author

Edward Kong, Pascal Timshel, Danielle Posthuma, Tõnu Esko, Maël Lebreton, Kathleen Mullan Harris, Philipp Koellinger, Murray B. Stein, Abraham A. Palmer, Urs Fischbacher, Robert J. Ursano, Erdogan Taskesen, Peter Eibich, Paul R. H. J. Timmers, Anke R. Hammerschlag, Ann H. Caplin, Jian Yang, Sandra Sanchez-Roige, Peter K. Joshi, Matthias Sutter, Pierre Fontanillas, Chia-Yen Chen, Albert Hofman, Patrick Turley, David A. Hinds, Futao Zhang, David Cesarini, Christina M. Lill, Laura Buzdugan, Ville Karhunen, Abdel Abdellaoui, S. Fleur W. Meddens, Henning Tiemeier, Christian L. Zund, Gert G. Wagner, Richard Karlsson Linnér, Lars Bertram, David W. Clark, Roy Thurik, André G. Uitterlinden, Maciej Trzaskowski, Mohammad Arfan Ikram, David Laibson, Cornelius A. Rietveld, Arcadi Navarro, Ernst Fehr, Yang Wu, Matthew B. McQueen, Ronald C. Kessler, Magnus Johannesson, Patrick J. F. Groenen, Gregor Hasler, James F. Wilson, Daniel Schunk, Stephen P. Tino, Pietro Biroli, Mark Alan Fontana, Juan R. González, Meena Kumari, Gerardus A. Meddens, Jonathan P. Beauchamp, Michelle N. Meyer, Jason D. Boardman, James J. Lee, Carlos Morcillo-Suarez, Aaron Kleinman, Minna Männikkö, Andrew Conlin, Adam Auton, Tune H. Pers, Michel G. Nivard, Ronald de Vlaming, Jon White, Robert Karlsson, Daniel J. Benjamin, Maarten Kooyman, Jacob Gratten, Aysu Okbay, Remy Z. Levin, Melissa C. Smart, Harriet de Wit, Conor C. Dolan, Frank J. A. van Rooij, Patrik K. E. Magnusson, Sonia Jain, Rauli Svento, Klaus M. Schmidt, Dorret I. Boomsma, Gerard Muntané, James MacKillop, Robbee Wedow, and Yanchun Bao

Subjects
Genetics, 0303 health sciences, Gabaergic neurotransmission, Single-nucleotide polymorphism, Genome-wide association study, Biology, Phenotype, 03 medical and health sciences, 0302 clinical medicine, SNP, Gene, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract

Humans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. We identified 611 approximately independent genetic loci associated with at least one of our phenotypes, including 124 with general risk tolerance. We report evidence of substantial shared genetic influences across general risk tolerance and risky behaviors: 72 of the 124 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is moderately to strongly genetically correlated (to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near general-risk-tolerance-associated SNPs are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We find no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

Published
2018
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40. 10FIRST GENOME-WIDE ASSOCIATION STUDY OF SCHIZOPHRENIA IN AN INDIAN POPULATION REVEALS A NOVEL SUSCEPTIBILITY LOCUS

Author

Jean Giacomotto, Rangaswamy Thara, Priyadarshini Thirunavukkarasu, Jacob Gratten, Matthew A. Brown, R. Padmavati, Preeti Rajendren, Sathish Periyasamy, Sujit John, Naomi R. Wray, Andrew Bakshi, Elizabeth G. Holliday, Rachel J. Suetani, Lynn B. Jorde, and Bryan J. Mowry

Subjects
Pharmacology, Genetics, Psychiatry and Mental health, Neurology, Schizophrenia (object-oriented programming), Susceptibility locus, Indian population, Pharmacology (medical), Genome-wide association study, Neurology (clinical), Biology, Biological Psychiatry
Published
2019

41. F87COMMON GENETIC VARIATION EXPLAINS A HIGH PROPORTION OF THE ELEVATED RISK OF PSYCHIATRIC DISORDERS IN CHILDREN OF YOUNGER MOTHERS

Author

Allan F. McRae, Jian Yang, Jacob Gratten, Futao Zhang, Kathryn E. Kemper, Yuanhao Yang, Maciej Trzaskowski, Zhihong Zhu, Naomi R. Wray, Zhili Zheng, Peter M. Visscher, and Loic Yengo

Subjects
Pharmacology, Psychiatry and Mental health, medicine.medical_specialty, Neurology, business.industry, Genetic variation, medicine, Pharmacology (medical), Neurology (clinical), Psychiatry, business, Biological Psychiatry
Published
2019

42. Study protocol for the Australian autism biobank: an international resource to advance autism discovery research

Author

Anne Masi, Paul A. Dawson, Rachel Grove, Cheryl Dissanayake, Helen Heussler, Andrew J. O. Whitehouse, Gail A. Alvares, Emma Raymond, Jacob Gratten, Leanne Wallace, Naomi R. Wray, Anjali K. Henders, Valsamma Eapen, Felicity Rose, and Lauren P. Lawson

Subjects
Biomedical Research, Autism Spectrum Disorder, Genetic counseling, Ethnic group, Urinalysis, 03 medical and health sciences, Feces, Study Protocol, 0302 clinical medicine, Clinical Protocols, Genetic, Cultural diversity, Surveys and Questionnaires, mental disorders, Medicine, Humans, 0501 psychology and cognitive sciences, Medical history, Child, Biological Specimen Banks, Biobank, Blood Specimen Collection, Psychological Tests, business.industry, 05 social sciences, lcsh:RJ1-570, Australia, lcsh:Pediatrics, medicine.disease, Phenotype, Autism spectrum disorder, Child, Preschool, Pediatrics, Perinatology and Child Health, Genomic, Autism, Sample collection, business, 030217 neurology & neurosurgery, 050104 developmental & child psychology, Clinical psychology, Hair
Abstract

Background The phenotypic and genetic heterogeneity of autism spectrum disorder (ASD) presents considerable challenges in understanding etiological pathways, selecting effective therapies, providing genetic counselling, and predicting clinical outcomes. With advances in genetic and biological research alongside rapid-pace technological innovations, there is an increasing imperative to access large, representative, and diverse cohorts to advance knowledge of ASD. To date, there has not been any single collective effort towards a similar resource in Australia, which has its own unique ethnic and cultural diversity. The Australian Autism Biobank was initiated by the Cooperative Research Centre for Living with Autism (Autism CRC) to establish a large-scale repository of biological samples and detailed clinical information about children diagnosed with ASD to facilitate future discovery research. Methods The primary group of participants were children with a confirmed diagnosis of ASD, aged between 2 and 17 years, recruited through four sites in Australia. No exclusion criteria regarding language level, cognitive ability, or comorbid conditions were applied to ensure a representative cohort was recruited. Both biological parents and siblings were invited to participate, along with children without a diagnosis of ASD, and children who had been queried for an ASD diagnosis but did not meet diagnostic criteria. All children completed cognitive assessments, with probands and parents completing additional assessments measuring ASD symptomatology. Parents completed questionnaires about their child’s medical history and early development. Physical measurements and biological samples (blood, stool, urine, and hair) were collected from children, and physical measurements and blood samples were collected from parents. Samples were sent to a central processing site and placed into long-term storage. Discussion The establishment of this biobank is a valuable international resource incorporating detailed clinical and biological information that will help accelerate the pace of ASD discovery research. Recruitment into this study has also supported the feasibility of large-scale biological sample collection in children diagnosed with ASD with comprehensive phenotyping across a wide range of ages, intellectual abilities, and levels of adaptive functioning. This biological and clinical resource will be open to data access requests from national and international researchers to support future discovery research that will benefit the autistic community.

Published
2017

43. Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Author

Bjarni J. Vilhjálmsson, Jian Yang, Hilary K. Finucane, Alexander Gusev, Sara Lindström, Stephan Ripke, Giulio Genovese, Po-Ru Loh, Gaurav Bhatia, Ron Do, Tristan Hayeck, Hong-Hee Won, Sekar Kathiresan, Michele Pato, Carlos Pato, Rulla Tamimi, Eli Stahl, Noah Zaitlen, Bogdan Pasaniuc, Gillian Belbin, Eimear E. Kenny, Mikkel H. Schierup, Philip De Jager, Nikolaos A. Patsopoulos, Steve McCarroll, Mark Daly, Shaun Purcell, Daniel Chasman, Benjamin Neale, Michael Goddard, Peter M. Visscher, Peter Kraft, Nick Patterson, Alkes L. Price, Benjamin M. Neale, Aiden Corvin, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberly D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, David Curtis, Michael Davidson, Kenneth L. Davis, Franziska Degenhardt, Jurgen Del Favero, Lynn E. DeLisi, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Lyudmila Georgieva, Elliot S. Gershon, Ina Giegling, Paola Giusti-Rodrguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Jakob Grove, Lieuwe de Haan, Christian Hammer, Marian L. Hamshere, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Annette M. Hartmann, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, David M. Hougaard, Masashi Ikeda, Inge Joa, Antonio Julia, Rene S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, Brian J. Kelly, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, James A. Knowles, Bettina Konte, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kahler, Claudine Laurent, Jimmy Lee Chee Keong, S. Hong Lee, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lnnqvist, Milan Macek, Patrik K.E. Magnusson, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Andrew M. McIntosh, Sandra Meier, Carin J. Meijer, Bela Melegh, Ingrid Melle, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Lili Milani, Vihra Milanova, Younes Mokrab, Derek W. Morris, Ole Mors, Preben B. Mortensen, Kieran C. Murphy, Robin M. Murray, Inez Myin-Germeys, Bertram Mller-Myhsok, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O’Callaghan, Colm O’Dushlaine, F. Anthony O’Neill, Sang-Yun Oh, Ann Olincy, Line Olsen, Jim Van Os, Christos Pantelis, George N. Papadimitriou, Sergi Papiol, Elena Parkhomenko, Michele T. Pato, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietilinen, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Alan R. Sanders, Ulrich Schall, Christian R. Schubert, Thomas G. Schulze, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Jianxin Shi, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Jordan W. Smoller, Hon-Cheong So, Chris C.A. Spencer, Eli A. Stahl, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T. Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Sderman, Srinivas Thirumalai, Draga Toncheva, Paul A. Tooney, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Jing Qin Wu, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Naomi R. Wray, Kari Stefansson, Rolf Adolfsson, Ole A. Andreassen, Douglas H.R. Blackwood, Elvira Bramon, Joseph D. Buxbaum, Anders D. Børglum, Sven Cichon, Ariel Darvasi, Enrico Domenici, Hannelore Ehrenreich, Tonu Esko, Pablo V. Gejman, Michael Gill, Hugh Gurling, Christina M. Hultman, Nakao Iwata, Assen V. Jablensky, Erik G. Jonsson, Kenneth S. Kendler, George Kirov, Jo Knight, Todd Lencz, Douglas F. Levinson, Qingqin S. Li, Jianjun Liu, Anil K. Malhotra, Steven A. McCarroll, Andrew McQuillin, Jennifer L. Moran, Bryan J. Mowry, Markus M. Nthen, Roel A. Ophoff, Michael J. Owen, Aarno Palotie, Carlos N. Pato, Tracey L. Petryshen, Danielle Posthuma, Marcella Rietschel, Brien P. Riley, Dan Rujescu, Pak C. Sham, Pamela Sklar, David St. Clair, Daniel R. Weinberger, Jens R. Wendland, Thomas Werge, Mark J. Daly, Patrick F. Sullivan, Michael C. O’Donovan, David J. Hunter, Muriel Adank, Habibul Ahsan, Kristiina Aittomäki, Laura Baglietto, Sonja Berndt, Carl Blomquist, Federico Canzian, Jenny Chang-Claude, Stephen J. Chanock, Laura Crisponi, Kamila Czene, Norbert Dahmen, Isabel dos Santos Silva, Douglas Easton, A. Heather Eliassen, Jonine Figueroa, Olivia Fletcher, Montserrat Garcia-Closas, Mia M. Gaudet, Lorna Gibson, Christopher A. Haiman, Per Hall, Aditi Hazra, Rebecca Hein, Brian E. Henderson, Albert Hofman, John L. Hopper, Astrid Irwanto, Mattias Johansson, Rudolf Kaaks, Muhammad G. Kibriya, Peter Lichtner, Eiliv Lund, Enes Makalic, Alfons Meindl, Hanne Meijers-Heijboer, Bertram Müller-Myhsok, Taru A. Muranen, Heli Nevanlinna, Petra H. Peeters, Julian Peto, Ross L. Prentice, Nazneen Rahman, María José Sánchez, Daniel F. Schmidt, Rita K. Schmutzler, Melissa C. Southey, Ruth Travis, Clare Turnbull, Andre G. Uitterlinden, Rob B. van der Luijt, Quinten Waisfisz, Zhaoming Wang, Alice S. Whittemore, Rose Yang, Wei Zheng, ANS - Amsterdam Neuroscience, Adult Psychiatry, Other departments, CCA -Cancer Center Amsterdam, ARD - Amsterdam Reproduction and Development, Human Genetics, Grove, Jakob, Complex Trait Genetics, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, Vilhjalmsson, Bjarni J, Yang, Jian, Finucane, Hilary K, Gusev, Alexander, Lee, SH, Price, Alkes L, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) study, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Study, Psychosis Endophenotype International Consortium, Wellcome Trust Case Control Consortium, Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON), Human genetics, NCA - Brain mechanisms in health and disease, CCA - Oncogenesis, CCA - Quality of life, CCA - Cancer biology and immunology, Psychiatry, Department of Technology and Operations Management, Department of Organisation and Personnel Management, Child and Adolescent Psychiatry / Psychology, Clinical Genetics, Cell biology, and Internal Medicine

Subjects
Multifactorial Inheritance, Linkage disequilibrium, Complex disease, heritability, Bioinformatics, Medical and Health Sciences, Linkage Disequilibrium, 0302 clinical medicine, Theoretical, External reference, Models, Statistics, GWAS, Genetics(clinical), Genetics (clinical), Mathematics, Genetics & Heredity, Schizophrenia Working Group of the Psychiatric Genomics Consortium, 0303 health sciences, Single Nucleotide, Biological Sciences, Serious Mental Illness, Prognosis, Thresholding, Regression, Mental Health, Phenotype, polygenic risk scores, Mixed model, Multiple Sclerosis, Genotype, Quantitative Trait Loci, polygenic risk score, schizophrenia, GWAS, Discovery, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Genetics, Humans, p-value, Pruning (decision trees), Polymorphism, Genome-Wide Association Study, Schizophrenia, Models, Theoretical, 030304 developmental biology, genome-wide association study, and Risk of Inherited Variants in Breast Cancer (DRIVE) study, Brain Disorders, Data set, schizophrenia, Sample size determination, polygenic risk score, Polygenic risk score, 030217 neurology & neurosurgery, linkage disequilibrium
Abstract

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R-2 increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase. Refereed/Peer-reviewed

Published
2015

44. Rare variants are common in schizophrenia

Author

Jacob Gratten

Subjects
0301 basic medicine, Genetics, General Neuroscience, Schizophrenia (object-oriented programming), Biology, Polymorphism, Single Nucleotide, Article, DNA sequencing, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Schizophrenia, Humans, Genetic Predisposition to Disease, Gene, 030217 neurology & neurosurgery
Abstract

By analyzing the exomes of 12,332 unrelated Swedish individuals – including 4,877 affected with schizophrenia – in ways informed by exome sequences from 45,376 other individuals, we identified 244,246 coding-sequence and splice-site ultra-rare variants (URVs) that were unique to individual Swedes. We found that gene-disruptive and putatively protein-damaging URVs (but not synonymous URVs) were more abundant in schizophrenia cases than controls (P = 1.3 × 10−10). This elevation of protein-compromising URVs was several times larger than an analogously elevated rate for de novo mutations, suggesting that most rare-variant effects on schizophrenia risk are inherited. Among individuals with schizophrenia, the elevated frequency of protein-compromising URVs was concentrated in brain-expressed genes, particularly in neuronally expressed genes; most of this genetic signal arose from large sets of genes whose RNAs have been found to interact with synaptically localized proteins. Our results suggest that synaptic dysfunction may mediate a large fraction of strong, individually rare genetic influences on schizophrenia risk.

Published
2016

45. Whole-exome sequencing in amyotrophic lateral sclerosis suggests NEK1 is a risk gene in Chinese

Author

Zhongshan Li, Xiang-Ding Chen, Xiaolu Liu, Yingying Han, Robyn H. Wallace, Paul Leo, Zong Hong Zhang, Dongsheng Fan, Qiongyi Zhao, Li-Jun Tan, Matthew A. Brown, Ji He, Naomi R. Wray, Janette Edson, Zi-Bing Jin, Perry F. Bartlett, Sharon Song, Jian Yang, Lawrie Wheeler, Bryan J. Mowry, Jacob Gratten, Fleur C. Garton, Lu Chen, Mhairi Marshall, Huji Xu, Shu Ran, Yong Lin, Lu Tang, Peter M. Visscher, Hong-Weng Deng, Jessica Harris, Lisa Anderson, Anjali K. Henders, David C. Reutens, Jinyu Wu, Marie Mangelsdorf, Katie Cremin, Beben Benyamin, Gratten, Jacob, Zhao, Qiongyi, Benyamin, Beben, Garton, Fleur, and Fan, Dongsheng

Subjects
Risk, 0301 basic medicine, Oncology, amyotrophic lateral sclerosis, medicine.medical_specialty, lcsh:QH426-470, SOD1, lcsh:Medicine, Disease, Biology, whole exome sequencing, 03 medical and health sciences, Asian People, Internal medicine, Exome Sequencing, Genetics, medicine, Humans, Genetic Predisposition to Disease, Amyotrophic lateral sclerosis, Molecular Biology, Allele frequency, Gene, Genetics (clinical), Exome sequencing, Chinese, Research, Amyotrophic Lateral Sclerosis, lcsh:R, medicine.disease, Human genetics, 3. Good health, lcsh:Genetics, NIMA-Related Kinase 1, 030104 developmental biology, Etiology, Molecular Medicine
Abstract

Background Amyotrophic lateral sclerosis (ALS) is a progressive neurological disease characterised by the degeneration of motor neurons, which are responsible for voluntary movement. There remains limited understanding of disease aetiology, with median survival of ALS of three years and no effective treatment. Identifying genes that contribute to ALS susceptibility is an important step towards understanding aetiology. The vast majority of published human genetic studies, including for ALS, have used samples of European ancestry. The importance of trans-ethnic studies in human genetic studies is widely recognised, yet a dearth of studies of non-European ancestries remains. Here, we report analyses of novel whole-exome sequencing (WES) data from Chinese ALS and control individuals. Methods WES data were generated for 610 ALS cases and 460 controls drawn from Chinese populations. We assessed evidence for an excess of rare damaging mutations at the gene level and the gene set level, considering only singleton variants filtered to have allele frequency less than 5 × 10–5 in reference databases. To meta-analyse our results with a published study of European ancestry, we used a Cochran–Mantel–Haenszel test to compare gene-level variant counts in cases vs controls. Results No gene passed the genome-wide significance threshold with ALS in Chinese samples alone. Combining rare variant counts in Chinese with those from the largest WES study of European ancestry resulted in three genes surpassing genome-wide significance: TBK1 (p = 8.3 × 10–12), SOD1 (p = 8.9 × 10–9) and NEK1 (p = 1.1 × 10–9). In the Chinese data alone, SOD1 and NEK1 were nominally significantly associated with ALS (p = 0.04 and p = 7 × 10–3, respectively) and the case/control frequencies of rare coding variants in these genes were similar in Chinese and Europeans (SOD1: 1.5%/0.2% vs 0.9%/0.1%, NEK1 1.8%/0.4% vs 1.9%/0.8%). This was also true for TBK1 (1.2%/0.2% vs 1.4%/0.4%), but the association with ALS in Chinese was not significant (p = 0.14). Conclusions While SOD1 is already recognised as an ALS-associated gene in Chinese, we provide novel evidence for association of NEK1 with ALS in Chinese, reporting variants in these genes not previously found in Europeans. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0487-0) contains supplementary material, which is available to authorized users.

Published
2017

46. Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood

Author

Guiyan Ni, Gerhard Moser, Naomi R. Wray, S. Hong Lee, Stephan Ripke, Benjamin M. Neale, Aiden Corvin, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberly D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, David Curtis, Michael Davidson, Kenneth L. Davis, Franziska Degenhardt, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Giulio Genovese, Lyudmila Georgieva, Ina Giegling, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Marian L. Hamshere, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Annette M. Hartmann, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, David M. Hougaard, Masashi Ikeda, Inge Joa, Antonio Juliá, René S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, James A. Knowles, Bettina Konte, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee Chee Keong, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lönnqvist, Milan Macek, Patrik K.E. Magnusson, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsda, Robert W. McCarley, Colm McDonald, Andrew M. McIntosh, Sandra Meier, Carin J. Meijer, Bela Melegh, Ingrid Melle, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Lili Milani, Vihra Milanova, Younes Mokrab, Derek W. Morris, Ole Mors, Kieran C. Murphy, Robin M. Murray, Inez Myin-Germeys, Bertram Müller-Myhsok, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O’Callaghan, Colm O’Dushlaine, F. Anthony O’Neill, Sang-Yun Oh, Ann Olinc, Line Olsen, Jim Van Os, Christos Pantelis, George N. Papadimitriou, Sergi Papio, Elena Parkhomenko, Michele T. Pato, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietiläinenl, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Alan R. Sanders, Ulrich Schall, Christian R. Schubert, Thomas G. Schulze, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Jianxin Shi, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Jordan W. Smoller, Hon-Cheong So, Chris C.A. Spencer, Eli A. Stah, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T. Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Söderman, Srinivas Thirumalai, Draga Toncheva, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Kari Stefansson, Peter M. Visscher, Rolf Adolfsson, Ole A. Andreassen, Douglas H.R. Blackwood, Elvira Bramon, Joseph D. Buxbaum, Anders D. Børglum, Sven Cichon, Ariel Darvasi, Enrico Domenici, Hannelore Ehrenreich, Tõnu Esko, Pablo V. Gejman, Michael Gill, Hugh Gurling, Christina M. Hultman, Nakao Iwata, Assen V. Jablensky, Erik G. Jönsson, Kenneth S. Kendler, George Kirov, Jo Knight, Todd Lencz, Douglas F. Levinson, Qingqin S. Li, Jianjun Liu, Anil K. Malhotra, Steven A. McCarrol, Andrew McQuillin, Jennifer L. Moran, Preben B. Mortensen, Bryan J. Mowry, Markus M. Nöthen, Roel A. Ophoff, Michael J. Owen, Aarno Palotie, Carlos N. Pato, Tracey L. Petryshen, Danielle Posthuma, Marcella Rietsche, Brien P. Riley, Dan Rujescu, Pak C. Sham, Pamela Sklar, David St Clair, Daniel R. Weinberger, Jens R. Wendland, Thomas Werge, Mark J. Daly, Patrick F. Sullivan, Michael C. O’Donovan, APH - Mental Health, ANS - Complex Trait Genetics, Adult Psychiatry, Ni, Guiyan, Moser, Gerhard, Wray, Naomi R, Lee, S Hong, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Amsterdam Neuroscience - Complex Trait Genetics, Complex Trait Genetics, Clinicum, Department of Psychiatry, and HUS Psychiatry

Subjects
0301 basic medicine, Linkage disequilibrium, Schizophrenia/genetics, INFORMATION, Restricted maximum likelihood, Inheritance Patterns, linkage disequilibrium score regression, Bioinformatics, Medical and Health Sciences, 3124 Neurology and psychiatry, Linkage Disequilibrium, biasedness, 0302 clinical medicine, Statistics, Databases, Genetic, WIDE ASSOCIATION, Genetics(clinical), PARTITIONING HERITABILITY, Genetics (clinical), Genetics & Heredity, education.field_of_study, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Likelihood Functions, Genome, Body Height/genetics, accuracy, Regression analysis, Single Nucleotide, Biological Sciences, Polymorphism, Single Nucleotide/genetics, genetic correlation, Regression, STATISTICS, genomic restricted maximum likelihood, Mental Health, Phenotype, Regression Analysis, COMPLEX HUMAN TRAITS, Single Nucleotide/genetics, Human, Adult, SUSCEPTIBILITY LOCI, Genotype, SNP heritability, body mass index, genome-wide SNPs, height, schizophrenia, Population, Haplotypes/genetics, Biology, Genetic correlation, Polymorphism, Single Nucleotide, 03 medical and health sciences, Databases, Genetic, ddc:570, Report, Genetics, Humans, Linkage Disequilibrium/genetics, Computer Simulation, Polymorphism, education, linkage disequilibrium score regression (LDSC), Genome, Human, Human Genome, genetic architecture, Genetic architecture, Body Height, Brain Disorders, Inheritance Patterns/genetics, BODY-MASS INDEX, 030104 developmental biology, Haplotypes, Sample size determination, Schizophrenia, 3111 Biomedicine, HUMAN HEIGHT, 030217 neurology & neurosurgery
Abstract

J. Lönnqvist on työryhmän Psychiat Genomics Consortium jäsen. Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on similar to 150,000 individuals give a higher accuracy than LDSC estimates based on similar to 400,000 individuals (from combinedmeta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.

Published
2017

47. Age at first birth in women is genetically associated with increased risk of schizophrenia

Author

Fritz Zimprich, Manuel Mattheisen, Edward M. Scolnick, Ayman H. Fanous, Henrik B. Rasmussen, Steven A. McCarroll, Ingrid Agartz, Carmel M. Loughland, Aiden Corvin, Ann Olincy, Anders D. Børglum, F. Anthony O'Neill, T. Scott Stroup, Elizabeth Bevilacqua, Sandra Meier, Ulrich Schall, Jouko Lönnqvist, Jianxin Shi, C. Robert Cloninger, Judit Bene, Veikko Salomaa, George N. Papadimitriou, Milica Pejovic-Milovancevic, Béla Melegh, Kari Stefansson, Brendan Bulik-Sullivan, Janis Klovins, Enrico Domenici, Sibylle G. Schwab, Dai Wang, Assen Jablensky, Mari Nelis, Sang Yun Oh, Peter Holmans, Aaron R. Wolen, Hualin Simon Xi, Eric Strengman, Bryan J. Mowry, Michael Gill, Kung Yee Liang, William Byerley, Rolf Adolfsson, Hugh Gurling, Joseph I. Friedman, Andrew Pocklington, Brien P. Riley, Engilbert Sigurdsson, Benjamin M. Neale, Miaoxin Li, Michael Davidson, Bernard Lerer, Michele T. Pato, Xuebin Zheng, Patrick F. Sullivan, Frans Henskens, Madeline Alexander, Andrew M. McIntosh, Inez Myin-Germeys, Draga Toncheva, Liene Nikitina-Zake, Kenneth S. Kendler, Carin J. Meijer, Robin M. Murray, Richard E. Straub, Ann E. Pulver, Menachem Fromer, Derek W. Morris, Douglas M. Ruderfer, Mythily Subramaniam, Paul Cormican, Lyudmila Georgieva, Giulio Genovese, Brion S. Maher, Stanley V. Catts, David St Clair, Robert W. McCarley, David Cohen, Nancy G. Buccola, Dan Rujescu, Carlos N. Pato, Kristin K. Nicodemus, Josef Frank, Claudine Laurent, Dominique Campion, Guiyan Ni, James L. Kennedy, Sena Karachanak-Yankova, Nicholas John Craddock, Peter M. Visscher, Valentina Escott-Price, Jeffrey A. Lieberman, Deborah A. Nertney, Bertram Müller-Myhsok, Marcella Rietschel, Dimitris Dikeos, Stephanie Godard, Stephanie Williams, Andres Metspalu, John L. Waddington, Sophie E. Legge, Roel A. Ophoff, Jonathan Pimm, Richard Bruggeman, Tim B. Bigdeli, Gerald Nestadt, Mark Weiser, Kieran C. Murphy, Eric F.C. Cheung, Kang Sim, Jordan W. Smoller, David J. Kavanagh, Inge Joa, Jens R. Wendland, Thomas G. Schulze, Richard A. Belliveau, Sarah E. Bergen, Ditte Demontis, David Curtis, Todd Lencz, Danielle Posthuma, René S. Kahn, Lili Milani, Randy L. Buckner, Jianjun Liu, Petr Slominsky, Wiepke Cahn, Hana Kuzelova-Ptackova, Sergi Papiol, Tune H. Pers, Stephan Ripke, Rita M. Cantor, Ariel Darvasi, Christina M. Hultman, Larry J. Seidman, Eli A. Stahl, David A. Collier, Michael Conlon O'Donovan, Svetlana A. Limborska, James T.R. Walters, Farooq Amin, Noa Carrera, Ronald Y.L. Chen, Pablo V. Gejman, Joel N. Hirschhorn, Zita Ausrele Kucinskiene, Michael John Owen, Ina Giegling, Stephanie H. Witt, Timothy G. Dinan, Margot Albus, Wei Cheng, Marian L. Hamshere, Markus M. Nöthen, Thomas Werge, Guiqing Cai, Raquelle I. Mesholam-Gately, Annette M. Hartmann, Ingrid Melle, Ole A. Andreassen, Preben Bo Mortensen, Hannelore Ehrenreich, Tiina Paunio, James A. Knowles, Pak C. Sham, Marion Friedl, Teimuraz Silagadze, Dermot Walsh, Emily H. M. Wong, Igor Nenadic, Matthew C. Keller, John Powell, Naomi R. Wray, Patricia T. Michie, Bradley T. Webb, Lude Franke, Mark Hansen, Masashi Ikeda, Sven Cichon, Elvira Bramon, Frank Dudbridge, Erik G. Jönsson, Annelie Nordin, Wolfgang Maier, Peter Eichhammer, Christian R. Schubert, J. Mallet, Jacob Gratten, Andrey Khrunin, Jacqueline I. Goldstein, Panos Roussos, Pamela Sklar, Diana O. Perkins, Srdjan Djurovic, Phil Lee, Elodie Drapeau, Douglas F. Levinson, Nadine Cohen, Luba Kalaydjieva, Brandon Wormley, Tao Li, Tõnu Esko, Alexander Richards, Srihari Gopal, Jubao Duan, Anil K. Malhotra, Elisabeth Stögmann, Gary Donohoe, Kimberly Chambert, Sara Marsal, Hreinn Stefansson, Jo Knight, Ole Mors, Per Hoffmann, Dieter B. Wildenauer, James J. Crowley, Srinivas Thirumalai, Vahram Haroutunian, A. Hofman, Hailiang Huang, Thomas Hansen, Daniel R. Weinberger, Andrew McQuillin, Vaughan J. Carr, Vaidutis Kučinskas, Jimmy Lee Chee Keong, Digby Quested, Aarno Palotie, Robert Freedman, Hon-Cheong So, Jennifer L. Moran, Donald W. Black, Mark Reimers, Abraham Reichenberg, Jurgen Del Favero, Paola Giusti-Rodríguez, Tracey L. Petryshen, Olli Pietiläinen, Franziska Degenhardt, Laurent Essioux, Esben Agerbo, Qiang Wang, Jana Strohmaier, Siow Ann Chong, Johan G. Eriksson, Martin Begemann, Younes Mokrab, Colm McDonald, Silviu Alin Bacanu, Martilias S. Farrell, Christos Pantelis, Kai How Farh, Line Olsen, Naser Durmishi, Antonio Julià, Stefan Herms, Qingqin S. Li, Bettina Konte, George Kirov, Rodney J. Scott, Nelson B. Freimer, Mads V. Hollegaard, Shaun Purcell, Erik Söderman, Dragan M. Svrakic, Patrik K. E. Magnusson, Douglas Blackwood, Jin P. Szatkiewicz, Sang Hong Lee, Yunjung Kim, Colm O'Dushlaine, Morten Mattingsdal, Jim van Os, Sarah Tosato, Milan Macek, Joshua L. Roffman, Jan Lubinski, Eadbhard O'Callaghan, Juha Karjalainen, Vera Golimbet, Anna K. Kähler, Clement C. Zai, Nigel Williams, Joseph D. Buxbaum, Laura Nisenbaum, Eric Y.H. Chen, David M. Hougaard, Jaana Suvisaari, Chris C. A. Spencer, Alan R. Sanders, Alkes L. Price, Vihra Milanova, Juha Veijola, Christian Hammer, Raymond C.K. Chan, Stacy Steinberg, Nakao Iwata, Jeremy M. Silverman, Mark J. Daly, Elena Parkhomenko, Kenneth L. Davis, Lieuwe de Haan, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Reproduction & Development (AR&D), Kučinskas, Vaidutis, Kučinskienė, Zita Aušrelė, Ni, Guiyan, Gratten, Jacob, Wray, Naomi R, Lee, Sang Hong, Germeys, Inez, Complex Trait Genetics, Háskóli Íslands, University of Iceland, Child and Adolescent Psychiatry / Psychology, Research Programs Unit, Diabetes and Obesity Research Program, Johan Eriksson / Principal Investigator, Department of General Practice and Primary Health Care, University Management, Department of Psychiatry, Center for Population, Health and Society, Department of Public Health, Centre of Excellence in Complex Disease Genetics, Research Programme of Molecular Medicine, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, and Genomics of Neurological and Neuropsychiatric Disorders

Subjects
0301 basic medicine, Multifactorial Inheritance, PATERNAL-AGE, 3124 Neurology and psychiatry, COMMON SNPS, fluids and secretions, 0302 clinical medicine, CHILD, Risk Factors, Pregnancy, 2.1 Biological and endogenous factors, Medicine, Aetiology, Pediatric, PROPORTION, Schizophrenia Working Group of the Psychiatric Genomics Consortium, 0303 health sciences, Multidisciplinary, PSYCHIATRIC-DISORDERS, BIPOLAR DISORDER, Biobank, 3. Good health, AFB, Mental Health, Schizophrenia, Female, Erfðarannsóknir, Psychosocial, TRAITS, schizophrenia, age at birth, AFB, Maternal Age, Adult, age at first birth in women, genetic association, Offspring, Science, Genetic correlation, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Geðklofi, Genetics, age at birth, Humans, Genetic Predisposition to Disease, Bipolar disorder, General, Biology, Genetic association study, 030304 developmental biology, Genetic association, business.industry, Genetic heterogeneity, Prevention, average aged parents, Parturition, SCORE REGRESSION, bacterial infections and mycoses, medicine.disease, Mental health, Brain Disorders, respiratory tract diseases, schizophrenia, Good Health and Well Being, 030104 developmental biology, younger and older parents, DE-NOVO MUTATIONS, ddc:000, Human medicine, business, 030217 neurology & neurosurgery, Demography
Abstract

Publisher's version (útgefin grein), Previous studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is −0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health., This research is supported by the Australian National Health and Medical Research Council (1080157, 1087889, 1103418, 1127440), and the Australian Research Council (DP160102126, FT160100229). This research has been conducted using the UK Biobank Resource. UK Biobank (http://www.ukbiobank.ac.uk) Research Ethics Committee (REC) approval number is 11/NW/0382. Our reference number approved by UK Biobank is 14575.

Published
2017

48. Whole exome sequencing and DNA methylation analysis in a clinical amyotrophic lateral sclerosis cohort

Author

Qiongyi Zhao, Sarah Furlong, Robert D. Henderson, Zong Hong Zhang, Sonia Shah, Pamela A. McCombe, Anjali K. Henders, Perminder S. Sachdev, Zhijun Liu, Kathryn A Thorpe, Beben Benyamin, Fleur C. Garton, Jacob Gratten, Sarah Morgan, Susan Heggie, Matthew R. Robinson, Casey M. M. Pfluger, Janette Edson, Peter M. Visscher, Naomi R. Wray, Allan F. McRae, Karen A. Mather, Marie Mangelsdorf, Garton, FC, Benyamin, B, Zhao, Q, Liu, Z, and McCombe, PA

Subjects
0301 basic medicine, medicine.medical_specialty, Population, next‐generation sequencing, Biology, TARDBP, whole exome sequencing, 03 medical and health sciences, 0302 clinical medicine, C9orf72, Genetics, medicine, Amyotrophic lateral sclerosis, education, Molecular Biology, Genetics (clinical), Exome sequencing, Genetic testing, education.field_of_study, medicine.diagnostic_test, Original Articles, medicine.disease, 3. Good health, 030104 developmental biology, DNA methylation, motor neuron disease, Medical genetics, next-generation sequencing, Original Article, ALS, 030217 neurology & neurosurgery, clinical genetics
Abstract

Background: Gene discovery has provided remarkable biological insights into amyotrophic lateral sclerosis (ALS). One challenge for clinical application of genetic testing is critical evaluation of the significance of reported variants. Methods: We use whole exome sequencing (WES) to develop a clinically relevant approach to identify a subset of ALS patients harboring likely pathogenic mutations. In parallel, we assess if DNA methylation can be used to screen for pathogenicity of novel variants since a methylation signature has been shown to associate with the pathogenic C9orf72 expansion, but has not been explored for other ALS mutations. Australian patients identified with ALS-relevant variants were cross-checked with population databases and case reports to critically assess whether they were “likely causal,” “uncertain significance,” or “unlikely causal.”. Results: Published ALS variants were identified in >10% of patients; however, in only 3% of patients (4/120) could these be confidently considered pathogenic (in SOD1 and TARDBP). We found no evidence for a differential DNA methylation signature in these mutation carriers. Conclusions: The use of WES in a typical ALS clinic demonstrates a critical approach to variant assessment with the capability to combine cohorts to enhance the largely unknown genetic basis of ALS Refereed/Peer-reviewed

Published
2017

49. Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

Author

Cristina Cereda, Jurjen J. Luykx, Sandra Meier, Derek W. Morris, Douglas M. Ruderfer, Mythily Subramaniam, Paul Cormican, Lyudmila Georgieva, John Landers, Silvana Penco, Marian L. Hamshere, Frank Dudbridge, Mari Nelis, Dick Schijven, Jimmy Lee, Sarah E. Bergen, Alessandro Padovani, Nicholas W. Wood, Meraida Polak, Hannelore Ehrenreich, Nancy G. Buccola, Noa Carrera, Stefan Herms, Panos Roussos, Marion Friedl, Teimuraz Silagadze, Jim van Os, Annette M. Hartmann, Ole A. Andreassen, R. Jeroen Pasterkamp, Sibylle G. Schwab, Aleksey Shatunov, Eli A. Stahl, David A. Collier, Farooq Amin, Michael Conlon O'Donovan, Guiqing Cai, Kung-Yee Liang, Denis C. Bauer, Charles Curtis, Brion S. Maher, Ashley R. Jones, Sara L. Pulit, Sarah Tosato, Milan Macek, Vivianna M. Van Deerlin, Vincenzo Silani, Pietro Fratta, Bettina Konte, Rosanna Tortelli, Dan Rujescu, T. Scott Stroup, Elizabeth Bevilacqua, Christian Lunetta, Bradley T. Webb, Christophe Tzourio, Patrick Vourc'h, Joel N. Hirschhorn, Gilbert Bensimon, Timothy G. Dinan, Thomas G. Schulze, Richard A. Belliveau, Daniel R. Weinberger, Andrew McQuillin, Qingqin S. Li, Orla Hardiman, Claudine Laurent, Masashi Ikeda, Tim Kahlke, Rodney J. Scott, Frans Henskens, Tune H. Pers, Wolfgang Lieb, Christian Hammer, Elvira Bramon, Hana Kuzelova-Ptackova, Raquelle I. Mesholam-Gately, Ingrid Melle, Nadine Cohen, David Cohen, Nazli Basak, Elisabeth Stögmann, Nelson B. Freimer, Peter Eichhammer, J. Mallet, Preben Bo Mortensen, Robert H. Brown, Wouter van Rheenen, Roberto Del Bo, Dai Wang, Laurent Essioux, Larry J. Seidman, Hreinn Stefansson, Erik G. Jönsson, Mads V. Hollegaard, Raymond C.K. Chan, Susana Pinto, Alexander Richards, Jubao Duan, Peter Holmans, George Kirov, Pablo V. Gejman, Philippe Amouyel, Stephanie Godard, Dieter B. Wildenauer, Martina Wiedau-Pazos, Stacy Steinberg, Ole Mors, Andres Metspalu, Rolf Adolfsson, Shaun Purcell, Hugh Gurling, Joseph I. Friedman, Erik Söderman, Mark Weiser, Giacomo P. Comi, James A. Knowles, Peter M. Andersen, Brien P. Riley, Nakao Iwata, Jeremy M. Silverman, Mark J. Daly, Elena Parkhomenko, Digby Quested, Srinivas Thirumalai, Ulrich Schall, Jan Lubinski, Dragan M. Svrakic, Aaron R. Wolen, S. Hong Lee, Andrew Pocklington, Bernard Lerer, Vahram Haroutunian, Matthew C. Kiernan, Kenneth L. Davis, Assen Jablensky, William Byerley, Karol Estrada, Aarno Palotie, Cinzia Tiloca, Eadbhard O'Callaghan, Perry T.C. van Doormaal, Colm McDonald, Federico Casale, Thomas Meitinger, Robert Freedman, Gerome Breen, Milena Blagojevic-Radivojkov, Ian P. Blair, Ann E. Pulver, Jan H. Veldink, Giancarlo Logroscino, Miaoxin Li, Abraham Reichenberg, Esben Agerbo, Siddharthan Chandran, Patrik K. E. Magnusson, Andrew M. McIntosh, Gianni Sorarù, Maura Brunetti, Xuebin Zheng, Madeline Alexander, James L. Kennedy, Douglas Blackwood, Menachem Fromer, Martilias S. Farrell, Alan R. Sanders, Dominic B. Rowe, Alexis Brice, Jonathan Pimm, Emily H. M. Wong, Jana Strohmaier, André G. Uitterlinden, Andrea Calvo, Carsten Drepper, John Q. Trojanowski, Marcella Rietschel, Siow Ann Chong, Karen E. Morrison, Sang-Yun Oh, Laura Nisenbaum, Margaret O'Brien, Alkes L. Price, Carin J. Meijer, Michael Davidson, John Powell, Petr Slominsky, Wiepke Cahn, Cinzia Gellera, Vihra Milanova, Peter M. Visscher, Patricia T. Michie, Dimitris Dikeos, Jianxin Shi, Veikko Salomaa, Philip Van Damme, James J. Crowley, Younes Mokrab, Valentina Escott-Price, Jesus S. Mora, Stanley V. Catts, David St Clair, Bernhard Landwehrmeyer, John Hardy, Kristin K. Nicodemus, Dominique Campion, Juha Veijola, Wim Robberecht, Thomas Meyer, Peter Lichtner, Christos Pantelis, Markus Weber, Nilo Riva, Jin P. Szatkiewicz, Michele T. Pato, Cinzia Bertolin, Frank P. Diekstra, Simon Arcuti, Bryan J. Mowry, Hon-Cheong So, Adriano Chiò, Viviana Pensato, Yunjung Kim, Jean-François Dartigues, Zita Ausrele Kucinskiene, Inez Myin-Germeys, Jaana Suvisaari, Sophie E. Legge, Roel A. Ophoff, Philippe Corcia, Gerald Nestadt, Stephan Ripke, Kuang Lin, Paola Giusti-Rodríguez, Michael John Owen, Chris C. A. Spencer, Safa Saker-Delye, Robert W. McCarley, Kimberley D. Chambert, Brandon Wormley, Isabella Fogh, Mamede de Carvalho, Pamela J. Shaw, Tõnu Esko, Ronald Y. L. Chan, Jianjun Liu, Tim B. Bigdeli, Christian R. Andres, David M. Hougaard, Michael Gill, Ammar Al-Chalabi, Colm O'Dushlaine, Rick A.A. van der Spek, Gary Donohoe, Tao Li, Jonathan D. Glass, Christopher Shaw, Draga Toncheva, Leonard H. van den Berg, Liene Nikitina-Zake, Morten Mattingsdal, François Salachas, Andrey Khrunin, Line Olsen, Jochen H. Weishaupt, Jo Knight, Katie Sidle, Filip Eftimov, Massimiliano Filosto, Russell L. McLaughlin, Pak C. Sham, Joshua L. Roffman, Thomas Hansen, Naser Durmishi, Deborah A. Nertney, Juha Karjalainen, Robert Swingler, Ditte Demontis, Vaidutis Kučinskas, Jennifer L. Moran, Leo McCluskey, Donald W. Black, Eric F.C. Cheung, Qiang Wang, Olli Pietilainen, Vera Golimbet, Anna K. Kähler, Clement C. Zai, Nigel Williams, Annelie Nordin, Wolfgang Maier, Bradley N. Smith, Ettore Beghi, Rosa Capozzo, Garth A. Nicholson, Markus M. Nöuthen, Jordan W. Smoller, Eric Y.H. Chen, Joseph D. Buxbaum, Letizia Mazzini, Andrea Malaspina, Antonio Julià, Stephanie Williams, Tracey L. Petryshen, Christine Payan, Johan G. Eriksson, Carmel M. Loughland, Elodie Drapeau, Lieuwe de Haan, Martin Begemann, Lukas Tittmann, Franziska Degenhardt, Mark Reimers, Jurgen Del Favero, Jacqueline I. Goldstein, Annelot M. Dekker, Sergi Papiol, Svetlana A. Limborska, René S. Kahn, Shuna Colville, Kelly L. Williams, Pamela Sklar, Diana O. Perkins, Lili Milani, Ayman H. Fanous, Nicola Ticozzi, Fernando Rivadeneira, Marianne de Visser, P. Nigel Leigh, James T.R. Walters, Josef Frank, Aiden Corvin, Silviu Alin Bacanu, John L. Waddington, Stephanie H. Witt, Tiina Paunio, Margot Albus, Catherine Lomen-Hoerth, Sara Marsal, Per Hoffmann, David Curtis, Cindy Maurel, Todd Lencz, Orietta Pansarasa, Manuel Mattheisen, Anneke J. van der Kooi, A. Hofman, Dermot Walsh, Hailiang Huang, Ann Olincy, Anders D. Børglum, Ricardo Rojas-García, William Sproviero, Albert C. Ludolph, Edward M. Scolnick, Danielle Posthuma, George N. Papadimitriou, Michael A. van Es, Fritz Zimprich, F. Anthony O'Neill, Lude Franke, Jouko Lönnqvist, Daniel G. Bradley, Sven Cichon, Susanna Abdulla, Kristel R. van Eijk, Ingrid Agartz, Elisabetta Pupillo, Milica Pejovic-Milovancevic, Antonia Ratti, Henrik B. Rasmussen, Kari Stefansson, Brendan Bulik-Sullivan, Béla Melegh, Stéphanie Millecamps, Janis Klovins, Enrico Domenici, Michael Sendtner, Kai-How Farh, Randy L. Buckner, Albert Hofman, Benjamin M. Neale, Naomi R. Wray, An Goris, Kang Sim, Lauren Elman, Giulio Genovese, Jens R. Wendland, Rita M. Cantor, Ariel Darvasi, Christina M. Hultman, Sandra D'Alfonso, Cristina Moglia, Carlos N. Pato, Sena Karachanak-Yankova, Nicholas John Craddock, Richard W. Orrell, Richard Bruggeman, Kenneth S. Kendler, Alan M. Pittman, Robin M. Murray, Richard E. Straub, Cathryn M. Lewis, Srdjan Djurovic, Vincent Meininger, Jeffrey A. Lieberman, Bertram Müller-Myhsok, Phil Lee, David J. Kavanagh, Srihari Gopal, Igor Nenadic, Matthew C. Keller, Christian R. Schubert, Jacob Gratten, Alexandra Durr, Roger Pamphlett, Douglas F. Levinson, Luba Kalaydjieva, Chiara Zecca, Anil K. Malhotra, Andre Franke, Vaughan J. Carr, Steven A. McCarroll, C. Robert Cloninger, Judit Bene, Ina Giegling, Wei Cheng, Hualin Simon Xi, Thomas Werge, Eric Strengman, Susanne Petri, Engilbert Sigurdsson, Mark Hansen, Patrick F. Sullivan, Kieran C. Murphy, Inge Joa, Complex Trait Genetics, McLaughlin, Russell L, Schijven, Dick, Van Rheenen, Wouter, Van Eijk, Kristel R, O'Brien, Margaret, Kahn, René S, Ophoff, Roel A, Goris, An, Bradley, Daniel G, Al-Chalabi, Ammar, Van Den Berg, Leonard H, Luykx, Jurjen J, Hardiman, Orla, Veldink, Jan H, Lee, S Hong, Project MinE GWAS Consortium, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, Kučinskas, Vaidutis, Kučinskienė, Zita Aušrelė, Other departments, Neurology, APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Adult Psychiatry, Schizophrenia Working Group of the Psychiatric Genomics Consortiumz, Germeys, Inez, Robberecht, Wim, and Van Damme, Philip

Subjects
0301 basic medicine, Oncology, Genetics and Molecular Biology (all), Linkage disequilibrium, Multifactorial Inheritance, General Physics and Astronomy, Genome-wide association study, Comorbidity, VARIANTS, Neurodegenerative, Biochemistry, DISEASE, 3124 Neurology and psychiatry, Linkage Disequilibrium, Cohort Studies, 0302 clinical medicine, Genetics research, Odds Ratio, 2.1 Biological and endogenous factors, Amyotrophic lateral sclerosis, Aetiology, ARCHITECTURE, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Multidisciplinary, Chemistry (all), Motor neuron disease, Schizophrenia, BIPOLAR DISORDER, Single Nucleotide, Serious Mental Illness, 3. Good health, Mental Health, RC0346, motor neuron disease, Project MinE GWAS Consortium, medicine.medical_specialty, SUSCEPTIBILITY LOCI, Science, European Continental Ancestry Group, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, White People, 03 medical and health sciences, Physics and Astronomy (all), Rare Diseases, SDG 3 - Good Health and Well-being, Clinical Research, Internal medicine, MD Multidisciplinary, mental disorders, medicine, Genetics, Journal Article, Humans, Genetic Predisposition to Disease, Family, Bipolar disorder, GENOME-WIDE ASSOCIATION, Polymorphism, Biology, METAANALYSIS, business.industry, Amyotrophic Lateral Sclerosis, Human Genome, Case-control study, 3112 Neurosciences, Neurosciences, General Chemistry, Odds ratio, medicine.disease, R1, Brain Disorders, 030104 developmental biology, genetics research, Case-Control Studies, RC0321, Linear Models, PLEIOTROPY, Human medicine, 3111 Biomedicine, Biochemistry, Genetics and Molecular Biology (all), ALS, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05–21.6; P=1 × 10−4) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P=8.4 × 10−7). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08–1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies., Relatives of patients with amyotrophic lateral sclerosis have an unexpectedly high incidence of schizophrenia. Here, the authors show a genetic link between the two conditions, suggesting shared neurobiological mechanisms.

Published
2017

50. New mutations, old statistical challenges

Author

Matthew E. Hurles, Bernie Devlin, David J. Cutler, Peter M. Visscher, Daniel G. MacArthur, Jeffrey C. Barrett, Kathryn Roeder, Eric S. Lander, Mark J. Daly, Joseph D. Buxbaum, Jacob Gratten, Jack A. Kosmicki, Naomi R. Wray, and Neale Bm

Subjects
False discovery rate, Genetics, 0303 health sciences, Biology, medicine.disease, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Neurodevelopmental disorder, Control data, Intellectual disability, medicine, Autism, Genomic medicine, Identification (biology), Gene, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Based on targeted sequencing of 208 genes in 11,730 neurodevelopmental disorder cases, Stessman et al. report the identification of 91 genes associated (at a False Discovery Rate [FDR] of 0.1) with autism spectrum disorders (ASD), intellectual disability (ID), and developmental delay (DD)-including what they characterize as 38 novel genes, not previously reported as connected with these diseases. If true, this would represent a substantial step forward. Unfortunately, each of the two discovery analyses (1. De novo mutation analysis and, 2. a comparison of private mutations with public control data) contain critical statistical flaws. When one accounts for these problems, fewer than half of the genes - and very few, if any, of the novel findings - survive. These errors have implications for how future analyses should be conducted, for understanding the genetic basis of these disorders, and for genomic medicine.

Published
2017

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