Biology subjects

Gelernter, J.

Publications and source records attributed to Gelernter, J..

23 records · Page 2Linked to original sources

bioRxiv2018

Economic status mediates the relationship between educational attainment and posttraumatic stress disorder: a multivariable Mendelian randomization study

ObjectivesTo investigate the genetic overlap and causal relationship between posttraumatic stress disorder (PTSD) and traits related to educational attainment.\n\nDesignGenetic correlation, polygenic risk scoring, and causal inference via multivariable Mendelian randomization (MR).\n\nSettingPsychiatric Genomics Consortium for PTSD, UK Biobank, 23andMe, and Social Science Genetic Association Consortium.\n\nParticipants23,185 PTSD cases and 151,309 controls; up to 1,131,881 individuals assessed for educational attainment and related traits.\n\nMain outcome measuresGenetic correlation obtained from linkage disequilibrium score regression, phenotypic variance explained by polygenic risk scores, and casual effects (beta values) estimated with MR\n\nResultsPTSD showed strong negative genetic correlations with educational attainment (EdAtt; rg=-0.26, p=4.6x10-8). PRS based on genome-wide significant variants associated with EdAtt significantly predicted PTSD (p=6.16x10-4), but PRS based on variants associated with PTSD did not predict EdAtt (p>0.05). MR analysis indicated that EdAtt has negative causal effects on PTSD (beta=-0.23, p=0.004). Investigating potential mediators of the EdAtt-PTSD relationship, we observed that propensity for trauma exposure and risk-taking behaviors are risk factors for PTSD independently from EdAtt (beta = 0.36, p = 2.57x10-5 and beta = 0.76, p = 6.75x10-4, respectively), while income fully mediates the causal effect of EdAtt on PSTD (MR: Income - beta = -0.18, p =0.001; EdAtt - beta =-0.23, p=0.004; multivariable MR: Income - beta = -0.32, p = 0.017; EdAtt - beta = -0.04, p = 0.786).\n\nConclusionsWe report novel findings based on large-scale datasets regarding the relationship between educational attainment and PTSD, supporting the role of economic status as the key mediator in the causal relationship observed.\n\nWhat is already known on this topicThere is a well-established negative association of educational attainment and other traits related to cognitive ability with posttraumatic stress disorders (PTSD). However, the findings of these previous studies support various possible causal explanations: 1) individuals with high educational attainment are more resilient with respect to developing PTSD, 2) PTSD negatively impacts cognitive ability, or 3) PTSD and educational attainment share some underlying determinants, including relevant molecular mechanisms.\n\nA key obstacle to disentangling the complex association between educational attainment and PTSD is reverse causation, i.e. the situation in which the outcome precedes and causes the exposure instead of the other way around.\n\nWhat this study addsWe conducted a causal-inference investigation based on large-scale information from the investigation of more than one million individuals. Our main assumption is that genetic information can strongly minimize the bias of reverse causation, because genetic variants are determined at conception and do not change throughout life.\n\nOur findings indicate 1) the effect of traits related to educational attainment on PTSD, 2) no reverse effect of PTSD on educational attainment, and 3) economic status mediates the relationship between educational attainment and PTSD, independently from the brain mechanisms related to educational attainment.

genetics↗

bioRxiv2018

DRD2 and FOXP2 are implicated in the associations between computerized device use and psychiatric disorders

1.The societal health effects of ubiquitous computerized device use (CDU) is mostly unknown. Epidemiological evidence supports associations between CDU and psychiatric traits, but the underlying biological mechanisms are unclear. We investigated genetic overlaps, causal relationships, and molecular pathways shared between these traits using genome-wide data regarding CDU (UK Biobank; up to N=361,194 individuals) and Psychiatric Genomics Consortium phenotypes (14,477<N<150,064). The strongest genetic correlations were between \"weekly usage of mobile phone in last 3 months\" (PhoneUse) vs. attention deficit hyperactivity disorder (ADHD) (rg=0.425, p=4.59x10-11) and \"plays computer games\" (CompGaming) vs. schizophrenia (SCZ) (rg=-0.271, p=7.16x10-26). Latent causal variable analysis did not support causal relationships between these traits, but the observed genetic overlap was related to shared molecular pathways, including: dopamine transport (Gene Ontology:0015872, pSCZvsCompGaming=2.74x10-10) and DRD2 association (pSCZ=7.94x10-8; pCompGaming=3.98x10-25), and FOXP2 association (pADHD=9.32x10-7; pPhoneUse=9.00x10-11). Our results support epidemiological observations with genetic data, and uncover biological mechanisms underlying psychiatric disorders contribution to CDUs.

genomics↗

bioRxiv2018

Evidence of causal effect of major depression on alcohol dependence: Findings from the Psychiatric Genomics Consortium

BackgroundDespite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood.\n\nMethodsThis study was conducted using genome-wide data from the Psychiatric Genomics Consortium (MD: 135,458 cases and 344,901 controls; AD: 10,206 cases and 28,480 controls) and UK Biobank (AC-Frequency: from \"daily or almost daily\" to \"never\", 438,308 individuals; AC-Quantity: total units of alcohol per week, 307,098 individuals). Linkage disequilibrium score regression and Mendelian Randomization (MR) analyses were applied to investigate shared genetic mechanisms (horizontal pleiotropy) and causal relationships (mediated pleiotropy) among these traits.\n\nOutcomesPositive genetic correlation was observed between MD and AD (rgMD-AD=+0.47, P=6.6x10-10). AC-Quantity showed positive genetic correlation with both AD (rgAD-AC-Quantity=+0.75, P=1.8x10-14) and MD (rgMD-AC-Quantity=+0.14, P=2.9x10-7), while there was negative correlation of AC-Frequency with MD (rgMD-AC-Frequency=-0.17, P=1.5x10-10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e., causal relationship) with a causal role of MD on AD (beta=0.28, P=1.29x10-6) that does not appear to be biased by confounding such as horizontal pleiotropy. No evidence of reverse causation was observed as the AD genetic instrument did not show a causal effect on MD.\n\nInterpretationResults support a causal role for MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity not only addresses important public health concerns but also has the potential to facilitate prevention and intervention efforts.\n\nFundingNational Institute of Mental Health and National Institute on Drug Abuse.\n\nPutting data into contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed up to August 24, 2018, for research studies that investigated causality among alcohol-and depression related phenotypes using Mendelian randomization approaches. We used the search terms \"alcohol\" AND \"depression\" AND \"Mendelian Randomization\". No restrictions were applied to language, date, or article type. Ten articles were retrieved, but only two were focused on alcohol consumption and depression-related traits. The studies were based on genetic variants in alcohol dehydrogenase (ADH) genes only, did not find evidence for a causal effect of alcohol consumption on depression phenotypes, with one study finding a causal effect of alcohol consumption on alcoholism. Both studies noted that future studies are needed with increased sample sizes and clinically derived phenotypes. To our knowledge, no previous study has applied two-sample Mendelian randomization to investigate causal relationships between alcohol dependence and major depression.\n\nTwin studies show genetic factors influence susceptibility to MD, AD, and alcohol consumption. Differently from observational approaches where several studies have investigated the relationship between alcohol-and depression-related phenotypes, very limited use of molecular genetic data has been applied to investigate this issue. Additionally, the use of genetic information has been shown to be less biased by confounders and reverse causation than observation data. However, genetic approaches, like Mendelian randomization, require large sample sizes to be informative.\n\nAdded value of this studyIn this study, we used genome-wide data from the Psychiatric Genomic Consortium and UK Biobank, which include information regarding hundred thousands of individuals, to test the presence of shared genetic mechanisms and causal relationships among major depression, alcohol dependence, and alcohol consumption. The results support a causal influence of MD on AD, while alcohol consumption showed shared genetic mechanisms with respect to both major depression and alcohol dependence.\n\nImplications of all the available evidenceGiven the significant morbidity and mortality associated with MD, AD, and the comorbid condition, understanding mechanisms underlying these associations not only address important public health concerns but also has the potential to facilitate prevention and intervention efforts.

genetics↗

bioRxiv2018

Alcohol-responsive genes identified in human iPSC-derived neural cultures

Alcohol use contributes to numerous diseases and injuries. The nervous system is affected by alcohol in diverse ways, though the molecular mechanisms of these effects are not clearly understood. Using human-induced pluripotent stem cells (iPSCs), we developed a neural cell culture model to identify the mechanisms of alcohols effects. iPSCs were generated from fibroblasts and differentiated into forebrain neural cells cultures that were treated with 50 mM alcohol or sham conditions (same media lacking alcohol) for 7 days. We analyzed gene expression using total RNA sequencing (RNA-seq) for 34 samples derived from 11 subjects and for 10 samples from 5 subjects in an independent experiment that had intermittent exposure to the same dose of alcohol. We also analyzed genetic effects on gene expression and conducted a weighted correlation network analysis. We found that differentiated neural cell cultures have the capacity to recapitulate gene regulatory effects previously observed in specific primary neural tissues and identified 226 genes that were differentially expressed (FDR< 0.1) after alcohol treatment. The effects on expression included decreases in INSIG1 and LDLR, two genes involved in cholesterol homeostasis. We also identified a module of 58 co-expressed genes that were uniformly decreased following alcohol exposure. The majority of these effects were supported in the independent alcohol exposure experiment. Enrichment analysis linked the alcohol responsive genes to cell cycle, notch signaling, and cholesterol biosynthesis pathways, which are disrupted in several neurological disorders. Our findings suggest that there is convergence between these disorders and the effects of alcohol exposure.

neuroscience↗

bioRxiv2017

Psychiatric Genomics: An Update and an Agenda

The Psychiatric Genomics Consortium (PGC) is the largest consortium in the history of psychiatry. In the past decade, this global effort has delivered a rapidly increasing flow of new knowledge about the fundamental basis of common psychiatric disorders, particularly given its dedication to rapid progress and open science. The PGC has recently commenced a program of research designed to deliver \"actionable\" findings - genomic results that (a) reveal the fundamental biology, (b) inform clinical practice, and (c) deliver new therapeutic targets. This is the central idea of the PGC: to convert the family history risk factor into biologically, clinically, and therapeutically meaningful insights. The emerging findings suggest that we are entering into a phase of accelerated translation of genetic discoveries to impact psychiatric practice within a precision medicine framework.\n\nCollaboratorsPGC Coordinating Committee: Mark Daly, Michael Gill, John Kelsoe, Karestan Koenen, Douglas Levinson, Cathryn Lewis, Ben Neale, Danielle Posthuma, Jonathan Sebat, and Pamela Sklar.

genetics↗