Research into the causes of psychopathology has largely focused on two broad etiologic factors: genetic vulnerability and environmental stressors. An important role for familial/heritable factors in ...the etiology of a broad range of psychiatric disorders was established well before the modern era of genomic research. This review focuses on the genetic basis of three disorder categories-posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and the anxiety disorders-for which environmental stressors and stress responses are understood to be central to pathogenesis. Each of these disorders aggregates in families and is moderately heritable. More recently, molecular genetic approaches, including genome-wide studies of genetic variation, have been applied to identify specific risk variants. In this review, I summarize evidence for genetic contributions to PTSD, MDD, and the anxiety disorders including genetic epidemiology, the role of common genetic variation, the role of rare and structural variation, and the role of gene-environment interaction. Available data suggest that stress-related disorders are highly complex and polygenic and, despite substantial progress in other areas of psychiatric genetics, few risk loci have been identified for these disorders. Progress in this area will likely require analysis of much larger sample sizes than have been reported to date. The phenotypic complexity and genetic overlap among these disorders present further challenges. The review concludes with a discussion of prospects for clinical translation of genetic findings and future directions for research.
The widespread adoption of electronic health record (EHRs) in healthcare systems has created a vast and continuously growing resource of clinical data and provides new opportunities for ...population‐based research. In particular, the linking of EHRs to biospecimens and genomic data in biobanks may help address what has become a rate‐limiting study for genetic research: the need for large sample sizes. The principal roadblock to capitalizing on these resources is the need to establish the validity of phenotypes extracted from the EHR. For psychiatric genetic research, this represents a particular challenge given that diagnosis is based on patient reports and clinician observations that may not be well‐captured in billing codes or narrative records. This review addresses the opportunities and pitfalls in EHR‐based phenotyping with a focus on their application to psychiatric genetic research. A growing number of studies have demonstrated that diagnostic algorithms with high positive predictive value can be derived from EHRs, especially when structured data are supplemented by text mining approaches. Such algorithms enable semi‐automated phenotyping for large‐scale case‐control studies. In addition, the scale and scope of EHR databases have been used successfully to identify phenotypic subgroups and derive algorithms for longitudinal risk prediction. EHR‐based genomics are particularly well‐suited to rapid look‐up replication of putative risk genes, studies of pleiotropy (phenomewide association studies or PheWAS), investigations of genetic networks and overlap across the phenome, and pharmacogenomic research. EHR phenotyping has been relatively under‐utilized in psychiatric genomic research but may become a key component of efforts to advance precision psychiatry.
Polygenic risk scores (PRS) have shown promise in predicting human complex traits and diseases. Here, we present PRS-CS, a polygenic prediction method that infers posterior effect sizes of single ...nucleotide polymorphisms (SNPs) using genome-wide association summary statistics and an external linkage disequilibrium (LD) reference panel. PRS-CS utilizes a high-dimensional Bayesian regression framework, and is distinct from previous work by placing a continuous shrinkage (CS) prior on SNP effect sizes, which is robust to varying genetic architectures, provides substantial computational advantages, and enables multivariate modeling of local LD patterns. Simulation studies using data from the UK Biobank show that PRS-CS outperforms existing methods across a wide range of genetic architectures, especially when the training sample size is large. We apply PRS-CS to predict six common complex diseases and six quantitative traits in the Partners HealthCare Biobank, and further demonstrate the improvement of PRS-CS in prediction accuracy over alternative methods.
For over a century, psychiatric disorders have been defined by expert opinion and clinical observation. The modern DSM has relied on a consensus of experts to define categorical syndromes based on ...clusters of symptoms and signs, and, to some extent, external validators, such as longitudinal course and response to treatment. In the absence of an established etiology, psychiatry has struggled to validate these descriptive syndromes, and to define the boundaries between disorders and between normal and pathologic variation. Recent advances in genomic research, coupled with large-scale collaborative efforts like the Psychiatric Genomics Consortium, have identified hundreds of common and rare genetic variations that contribute to a range of neuropsychiatric disorders. At the same time, they have begun to address deeper questions about the structure and classification of mental disorders: To what extent do genetic findings support or challenge our clinical nosology? Are there genetic boundaries between psychiatric and neurologic illness? Do the data support a boundary between disorder and normal variation? Is it possible to envision a nosology based on genetically informed disease mechanisms? This review provides an overview of conceptual issues and genetic findings that bear on the relationships among and boundaries between psychiatric disorders and other conditions. We highlight implications for the evolving classification of psychopathology and the challenges for clinical translation.
Heritability estimation provides important information about the relative contribution of genetic and environmental factors to phenotypic variation, and provides an upper bound for the utility of ...genetic risk prediction models. Recent technological and statistical advances have enabled the estimation of additive heritability attributable to common genetic variants (SNP heritability) across a broad phenotypic spectrum. Here, we present a computationally and memory efficient heritability estimation method that can handle large sample sizes, and report the SNP heritability for 551 complex traits derived from the interim data release (152,736 subjects) of the large-scale, population-based UK Biobank, comprising both quantitative phenotypes and disease codes. We demonstrate that common genetic variation contributes to a broad array of quantitative traits and human diseases in the UK population, and identify phenotypes whose heritability is moderated by age (e.g., a majority of physical measures including height and body mass index), sex (e.g., blood pressure related traits) and socioeconomic status (education). Our study represents the first comprehensive phenome-wide heritability analysis in the UK Biobank, and underscores the importance of considering population characteristics in interpreting heritability.
Genome-wide analyses of common and rare genetic variations have documented the heritability of major psychiatric disorders, established their highly polygenic genetic architecture, and identified ...hundreds of contributing variants. In recent years, these studies have illuminated another key feature of the genetic basis of psychiatric disorders: the important role and pervasive nature of pleiotropy. It is now clear that a substantial fraction of genetic influences on psychopathology transcend clinical diagnostic boundaries. In this review, we summarize evidence in psychiatry for pleiotropy at multiple levels of analysis: from overall genome-wide correlation to biological pathways and down to the level of individual loci. We examine underlying mechanisms of observed pleiotropy, including genetic effects on neurodevelopment, diverse actions of regulatory elements, mediated effects, and spurious associations of genomic variation with multiple phenotypes. We conclude with an exploration of the implications of pleiotropy for understanding the genetic basis of psychiatric disorders, informing nosology, and advancing the aims of precision psychiatry and genomic medicine.
The “All of Us” Research Program Denny, Joshua C; Rutter, Joni L; Goldstein, David B ...
The New England journal of medicine,
08/2019, Letnik:
381, Številka:
7
Journal Article
Recenzirano
Odprti dostop
The U.S. research cohort All of Us was announced in 2015 and launched last year. With more than one fifth of the target enrollment now completed, the investigators report on progress and challenges.
Genome-wide association studies have identified many variants that each affects multiple traits, particularly across autoimmune diseases, cancers and neuropsychiatric disorders, suggesting that ...pleiotropic effects on human complex traits may be widespread. However, systematic detection of such effects is challenging and requires new methodologies and frameworks for interpreting cross-phenotype results. In this Review, we discuss the evidence for pleiotropy in contemporary genetic mapping studies, new and established analytical approaches to identifying pleiotropic effects, sources of spurious cross-phenotype effects and study design considerations. We also outline the molecular and clinical implications of such findings and discuss future directions of research.
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