Predicting Polygenic Risk of Psychiatric Disorders

[1]  Melissa J. Green,et al.  The genetics of the mood disorder spectrum: genome-wide association analyses of over 185,000 cases and 439,000 controls , 2018, bioRxiv.

[2]  Chia-Yen Chen,et al.  Assessment of Bidirectional Relationships Between Physical Activity and Depression Among Adults: A 2-Sample Mendelian Randomization Study , 2019, JAMA psychiatry.

[3]  Alicia R. Martin,et al.  Clinical use of current polygenic risk scores may exacerbate health disparities , 2019, Nature Genetics.

[4]  John P. Rice,et al.  Identification of common genetic risk variants for autism spectrum disorder , 2019, Nature Genetics.

[5]  Alkes L. Price,et al.  Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection , 2019, Nature Communications.

[6]  Brielin C. Brown,et al.  Comparative genetic architectures of schizophrenia in East Asian and European populations , 2018, Nature Genetics.

[7]  A. Reiner,et al.  Generalizing polygenic risk scores from Europeans to Hispanics/Latinos , 2018, Genetic epidemiology.

[8]  Joan,et al.  Prevalence and architecture of de novo mutations in developmental disorders , 2017, Nature.

[9]  Alicia R. Martin,et al.  Hidden ‘risk’ in polygenic scores: clinical use today could exacerbate health disparities , 2018, bioRxiv.

[10]  Alicia R. Martin,et al.  Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder , 2018, Nature Genetics.

[11]  M. Feldman,et al.  Analysis of Polygenic Score Usage and Performance in Diverse Human Populations , 2018, bioRxiv.

[12]  Jonathan P. Beauchamp,et al.  Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals , 2018, Nature Genetics.

[13]  Tyrone D. Cannon,et al.  Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence , 2018, Nature Genetics.

[14]  John P. Rice,et al.  Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes , 2017, Cell.

[15]  Stuart J. Ritchie,et al.  Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function , 2018, Nature Communications.

[16]  Caroline F. Wright,et al.  Common genetic variants contribute to risk of rare severe neurodevelopmental disorders , 2018, Nature.

[17]  Alicia R. Martin,et al.  Haplotype sharing provides insights into fine-scale population history and disease in Finland , 2017, bioRxiv.

[18]  B. Neale,et al.  Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases , 2018, Nature Genetics.

[19]  Valeriia Haberland,et al.  The MR-Base platform supports systematic causal inference across the human phenome , 2018, eLife.

[20]  J. Flint,et al.  22 MOLECULAR GENETIC ANALYSIS SUBDIVIDED BY ADVERSITY EXPOSURE SUGGESTS ETIOLOGIC HETEROGENEITY IN MAJOR DEPRESSION , 2018, European Neuropsychopharmacology.

[21]  E. Green,et al.  Prioritizing diversity in human genomics research , 2017, Nature Reviews Genetics.

[22]  Warren W. Kretzschmar,et al.  Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression , 2017, Nature Genetics.

[23]  Sonja W. Scholz,et al.  Investigating the genetic architecture of dementia with Lewy bodies: a two-stage genome-wide association study , 2018, The Lancet Neurology.

[24]  Dan J Stein,et al.  Largest GWAS of PTSD (N=20 070) yields genetic overlap with schizophrenia and sex differences in heritability , 2017, Molecular Psychiatry.

[25]  D. Skuse,et al.  ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social communication difficulties , 2017, Molecular Psychiatry.

[26]  Nick C Fox,et al.  Analysis of shared heritability in common disorders of the brain , 2018, Science.

[27]  Stephan Ripke,et al.  Improving genetic prediction by leveraging genetic correlations among human diseases and traits , 2018, Nature Communications.

[28]  Po-Ru Loh,et al.  Multi-ethnic polygenic risk scores improve risk prediction in diverse populations , 2016, bioRxiv.

[29]  P. Visscher,et al.  Multi-trait analysis of genome-wide association summary statistics using MTAG , 2017, Nature Genetics.

[30]  Michael J. T. Stubbington,et al.  The Human Cell Atlas: from vision to reality , 2017, Nature.

[31]  A. Price,et al.  Distinguishing genetic correlation from causation across 52 diseases and complex traits , 2017, Nature Genetics.

[32]  M. Kanai,et al.  Genome-wide association study identifies 112 new loci for body mass index in the Japanese population , 2017, Nature Genetics.

[33]  John M Hickey,et al.  Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery , 2017, Nature Genetics.

[34]  Jian Yang,et al.  Concepts, estimation and interpretation of SNP-based heritability , 2017, Nature Genetics.

[35]  Matti Pirinen,et al.  Fine-Scale Genetic Structure in Finland , 2017, G3: Genes, Genomes, Genetics.

[36]  Jakob Grove,et al.  Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder , 2017, bioRxiv.

[37]  Themistocles L Assimes,et al.  Leveraging Multi-ethnic Evidence for Risk Assessment of Quantitative Traits in Minority Populations. , 2017, American journal of human genetics.

[38]  P. Visscher,et al.  10 Years of GWAS Discovery: Biology, Function, and Translation. , 2017, American journal of human genetics.

[39]  G. Smith,et al.  Mendelian randomization in cardiometabolic disease: challenges in evaluating causality , 2017, Nature Reviews Cardiology.

[40]  Robert Plomin,et al.  Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence , 2017, Nature Genetics.

[41]  Raymond Walters,et al.  Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa. , 2017, The American journal of psychiatry.

[42]  G. Davey Smith,et al.  Genetic epidemiology and Mendelian randomization for informing disease therapeutics: Conceptual and methodological challenges , 2017, bioRxiv.

[43]  G. Paré,et al.  Polygenic risk score predicts prevalence of cardiovascular disease in patients with familial hypercholesterolemia. , 2017, Journal of clinical lipidology.

[44]  Laura W. Harris,et al.  A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog , 2018, Genome Biology.

[45]  Christopher R. Gignoux,et al.  Human demographic history impacts genetic risk prediction across diverse populations , 2016, bioRxiv.

[46]  D. Skuse,et al.  Shared genetic influences between dimensional ASD and ADHD symptoms during child and adolescent development , 2017, Molecular Autism.

[47]  P. O’Reilly,et al.  An Examination of Polygenic Score Risk Prediction in Individuals With First-Episode Psychosis , 2017, Biological Psychiatry.

[48]  Dermot F. Reilly,et al.  Polygenic Risk Score Identifies Subgroup With Higher Burden of Atherosclerosis and Greater Relative Benefit From Statin Therapy in the Primary Prevention Setting , 2017, Circulation.

[49]  Arianna M. Gard,et al.  Heterogeneity in polygenic scores for common human traits , 2017, bioRxiv.

[50]  T. Montine,et al.  Neuropathological and genetic correlates of survival and dementia onset in synucleinopathies: a retrospective analysis , 2017, The Lancet Neurology.

[51]  Deciphering Developmental Disorders Study,et al.  Prevalence and architecture of de novo mutations in developmental disorders , 2017, Nature.

[52]  E. Topol,et al.  Moving Beyond Clinical Risk Scores with a Mobile App for the Genomic Risk of Coronary Artery Disease , 2017, bioRxiv.

[53]  Jakob Grove,et al.  Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders , 2016, Nature Genetics.

[54]  Barbara Maughan,et al.  Schizophrenia risk alleles and neurodevelopmental outcomes in childhood: a population-based cohort study. , 2017, The lancet. Psychiatry.

[55]  E. Boerwinkle,et al.  Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease. , 2016, The New England journal of medicine.

[56]  S. Fullerton,et al.  Genomics is failing on diversity , 2016, Nature.

[57]  Brielin C. Brown,et al.  Transethnic genetic correlation estimates from summary statistics , 2016, bioRxiv.

[58]  B. Pasaniuc,et al.  Contrasting the genetic architecture of 30 complex traits from summary association data , 2016, bioRxiv.

[59]  Jianxin Shi,et al.  Developing and evaluating polygenic risk prediction models for stratified disease prevention , 2016, Nature Reviews Genetics.

[60]  Robert M. Maier,et al.  High loading of polygenic risk in cases with chronic schizophrenia , 2016, Molecular Psychiatry.

[61]  Joseph K. Pickrell,et al.  Detection and interpretation of shared genetic influences on 42 human traits , 2015, Nature Genetics.

[62]  M. O’Donovan,et al.  Association of Genetic Risk for Schizophrenia With Nonparticipation Over Time in a Population-Based Cohort Study , 2016, American journal of epidemiology.

[63]  Tom R. Gaunt,et al.  LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis , 2016, bioRxiv.

[64]  F. Dudbridge.  Polygenic Epidemiology , 2016, Genetic epidemiology.

[65]  Michael J. Keiser,et al.  Polygenic overlap between schizophrenia risk and antipsychotic response: a genomic medicine approach. , 2016, The lancet. Psychiatry.

[66]  Jonathan P. Beauchamp,et al.  Genome-wide association study identifies 74 loci associated with educational attainment , 2016, Nature.

[67]  R. Green,et al.  Incorporating a Genetic Risk Score Into Coronary Heart Disease Risk Estimates: Effect on Low-Density Lipoprotein Cholesterol Levels (the MI-GENES Clinical Trial). , 2016, Circulation.

[68]  Po-Ru Loh,et al.  A Robust Example of Collider Bias in a Genetic Association Study. , 2016, American journal of human genetics.

[69]  Stuart J. Ritchie,et al.  Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia , 2015, Molecular Psychiatry.

[70]  Jakob Grove,et al.  Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population , 2015, Nature Genetics.

[71]  D. Balding,et al.  Using Genetic Distance to Infer the Accuracy of Genomic Prediction , 2015, PLoS genetics.

[72]  Christine Van Broeckhoven,et al.  The genetic landscape of Alzheimer disease: clinical implications and perspectives , 2015, Genetics in Medicine.

[73]  M J Wright,et al.  Common polygenic risk for autism spectrum disorder (ASD) is associated with cognitive ability in the general population , 2015, Molecular Psychiatry.

[74]  F SullivanPatrick,et al.  Polygenic Risk Score, Parental Socioeconomic Status, Family History of Psychiatric Disorders, and the Risk for Schizophrenia , 2016 .

[75]  M. Daly,et al.  Natural Selection and Neuropsychiatric Disease: Theory, Observation, and Emerging Genetic Findings , 2016 .

[76]  R. Plomin,et al.  Discontinuity in the genetic and environmental causes of the intellectual disability spectrum , 2015, Proceedings of the National Academy of Sciences.

[77]  P. Visscher,et al.  Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores , 2015, bioRxiv.

[78]  Christopher S. Poultney,et al.  Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci , 2015, Neuron.

[79]  Yakir A Reshef,et al.  Partitioning heritability by functional annotation using genome-wide association summary statistics , 2015, Nature Genetics.

[80]  B. Pasaniuc,et al.  Leveraging Functional-Annotation Data in Trans-ethnic Fine-Mapping Studies. , 2015, American journal of human genetics.

[81]  Esben Agerbo,et al.  Polygenic Risk Score, Parental Socioeconomic Status, Family History of Psychiatric Disorders, and the Risk for Schizophrenia: A Danish Population-Based Study and Meta-analysis. , 2015, JAMA psychiatry.

[82]  A. Hofman,et al.  Polygenic risk scores for schizophrenia and bipolar disorder predict creativity , 2015, Nature Neuroscience.

[83]  P. Visscher,et al.  Simultaneous Discovery, Estimation and Prediction Analysis of Complex Traits Using a Bayesian Mixture Model , 2015, PLoS genetics.

[84]  Ross M. Fraser,et al.  Genetic studies of body mass index yield new insights for obesity biology , 2015, Nature.

[85]  Laura J. Scott,et al.  Joint Analysis of Psychiatric Disorders Increases Accuracy of Risk Prediction for Schizophrenia, Bipolar Disorder, and Major Depressive Disorder , 2015, American journal of human genetics.

[86]  Jack Euesden,et al.  PRSice: Polygenic Risk Score software , 2014, Bioinform..

[87]  Tomas W. Fitzgerald,et al.  Large-scale discovery of novel genetic causes of developmental disorders , 2014, Nature.

[88]  B. Berger,et al.  Efficient Bayesian mixed model analysis increases association power in large cohorts , 2014, Nature Genetics.

[89]  M. Daly,et al.  LD Score regression distinguishes confounding from polygenicity in genome-wide association studies , 2014, Nature Genetics.

[90]  A. Price,et al.  Explicit modeling of ancestry improves polygenic risk scores and BLUP prediction , 2014, bioRxiv.

[91]  S. Rosset,et al.  Measuring missing heritability: Inferring the contribution of common variants , 2014, Proceedings of the National Academy of Sciences.

[92]  Han Xu,et al.  Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. , 2014, American journal of human genetics.

[93]  M. O’Donovan,et al.  Genetic Risk for Attention-Deficit/Hyperactivity Disorder Contributes to Neurodevelopmental Traits in the General Population , 2014, Biological Psychiatry.

[94]  M. Daly,et al.  Autism spectrum disorder severity reflects the average contribution of de novo and familial influences , 2014, Proceedings of the National Academy of Sciences.

[95]  N. Wray,et al.  Research review: Polygenic methods and their application to psychiatric traits. , 2014, Journal of child psychology and psychiatry, and allied disciplines.

[96]  Ross M. Fraser,et al.  Defining the role of common variation in the genomic and biological architecture of adult human height , 2014, Nature Genetics.

[97]  C. Spencer,et al.  Biological Insights From 108 Schizophrenia-Associated Genetic Loci , 2014, Nature.

[98]  Saharon Rosset,et al.  Effective genetic-risk prediction using mixed models. , 2014, American journal of human genetics.

[99]  Tanya M. Teslovich,et al.  Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility , 2014, Nature Genetics.

[100]  Tanya M. Teslovich,et al.  Common variants associated with plasma triglycerides and risk for coronary artery disease , 2013, Nature Genetics.

[101]  M. Jarvelin,et al.  Deletion of TOP3β, a component of FMRP-containing mRNPs, contributes to neurodevelopmental disorders , 2013, Nature Neuroscience.

[102]  C. Carlson,et al.  Generalization and Dilution of Association Results from European GWAS in Populations of Non-European Ancestry: The PAGE Study , 2013, PLoS biology.

[103]  P. Visscher,et al.  Pitfalls of predicting complex traits from SNPs , 2013, Nature Reviews Genetics.

[104]  Nilanjan Chatterjee,et al.  Projecting the performance of risk prediction based on polygenic analyses of genome-wide association studies , 2013, Nature Genetics.

[105]  F. Dudbridge.  Power and Predictive Accuracy of Polygenic Risk Scores , 2013, PLoS genetics.

[106]  Justin Zobel,et al.  Performance and Robustness of Penalized and Unpenalized Methods for Genetic Prediction of Complex Human Disease , 2013, Genetic epidemiology.

[107]  Xiang Zhou,et al.  Polygenic Modeling with Bayesian Sparse Linear Mixed Models , 2012, PLoS genetics.

[108]  P. McGuffin,et al.  Fecundity of patients with schizophrenia, autism, bipolar disorder, depression, anorexia nervosa, or substance abuse vs their unaffected siblings. , 2013, JAMA psychiatry.

[109]  John Spertus,et al.  Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study , 2012, The Lancet.

[110]  M Erbe,et al.  Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels. , 2012, Journal of dairy science.

[111]  Evan T. Geller,et al.  Patterns and rates of exonic de novo mutations in autism spectrum disorders , 2012, Nature.

[112]  D. Linden.  The Challenges and Promise of Neuroimaging in Psychiatry , 2012, Neuron.

[113]  E. Lander,et al.  The mystery of missing heritability: Genetic interactions create phantom heritability , 2012, Proceedings of the National Academy of Sciences.

[114]  Markus Perola,et al.  Common Variants Show Predicted Polygenic Effects on Height in the Tails of the Distribution, Except in Extremely Short Individuals , 2011, PLoS genetics.

[115]  Matthew C Keller,et al.  A critical review of the first 10 years of candidate gene-by-environment interaction research in psychiatry. , 2011, The American journal of psychiatry.

[116]  Francisco M. De La Vega,et al.  Genomics for the world , 2011, Nature.

[117]  D. Allison,et al.  Beyond Missing Heritability: Prediction of Complex Traits , 2011, PLoS genetics.

[118]  P. Visscher,et al.  Common SNPs explain a large proportion of heritability for human height , 2011 .

[119]  Eran Halperin,et al.  Leveraging genetic variability across populations for the identification of causal variants. , 2010, American journal of human genetics.

[120]  J. Korn,et al.  Family-based genetic risk prediction of multifactorial disease , 2010, Genome Medicine.

[121]  R. Plomin,et al.  Common disorders are quantitative traits , 2009, Nature Reviews Genetics.

[122]  A. Need,et al.  Next generation disparities in human genomics: concerns and remedies. , 2009, Trends in genetics : TIG.

[123]  P. Visscher,et al.  Common polygenic variation contributes to risk of schizophrenia and bipolar disorder , 2009, Nature.

[124]  A. Emond,et al.  Prevalence and characteristics of autistic spectrum disorders in the ALSPAC cohort , 2008, Developmental medicine and child neurology.

[125]  W. G. Hill,et al.  Heritability in the genomics era — concepts and misconceptions , 2008, Nature Reviews Genetics.

[126]  Peter M Visscher,et al.  Prediction of individual genetic risk to disease from genome-wide association studies. , 2007, Genome research.

[127]  Elizabeth L. Ogburn,et al.  Demonstrating stratification in a European American population , 2005, Nature Genetics.

[128]  M. Olivier.  A haplotype map of the human genome. , 2003, Nature.

[129]  The International HapMap Consortium.  A haplotype map of the human genome , 2005 .

[130]  F. Vogel,et al.  Schizophrenia genesis: The origins of madness , 1991 .

[131]  J. Shields,et al.  A polygenic theory of schizophrenia , 1967 .

[132]  D. Falconer.  The inheritance of liability to certain diseases, estimated from the incidence among relatives , 1965 .

[133]  S. Wright,et al.  An Analysis of Variability in Number of Digits in an Inbred Strain of Guinea Pigs. , 1934, Genetics.

[134]  R. Fisher.  XV.—The Correlation between Relatives on the Supposition of Mendelian Inheritance. , 1919, Transactions of the Royal Society of Edinburgh.

[135]  Karl Pearson,et al.  Mathematical Contributions to the Theory of Evolution. VIII. On the Inheritance of Characters not Capable of Exact Quantitative Measurement. Part I. Introductory. Part II. On the Inheritance of Coat-Colour in Horses. Part III. On the Inheritance of Eye-Colour in Man , 1900 .