Biology subjects

Adkins, D. E.

Publications and source records attributed to Adkins, D. E..

5 recordsLinked to original sources

bioRxiv2018

Physical illness, social disadvantage, and risky sexual behavior in adolescence and young adulthood

This study investigated the influence of illness on sexual risk behavior in adolescence and the transition to adulthood, both directly and through moderation of the impact of social disadvantage. We hypothesized positive effects for social disadvantages and illness on sexual risk behavior, consistent with the development of faster life history strategies among young people facing greater life adversity. Using the first two waves of the National Longitudinal Study of Adolescent Health, we developed a mixed effects multinomial logistic regression model predicting sexual risk behavior in three comparisons, risky nonmonogamous sex vs. 1) safer nonmonogamous sex, 2) monogamous sex, and 3) abstinence, by social characteristics, illness, interactions thereof, and control covariates. Multiple imputation was used to address a modest amount of missing data. Subjects reporting higher levels of illness had lower odds of having safer nonmonogamous sex (OR = 0.84, p < .001), monogamous sex (OR = 0.82, p < .001), and abstinence (OR = 0.74, p < .001) vs. risky nonmonogamous sex, relative to individuals in better health. Illness significantly moderated the sex (OR = 0.88, p < .01), race/ethnicity (e.g., OR = 1.21, p < .001), and childhood SES (OR = 0.94; p < .01) effects for the abstinent vs. risky nonmonogamous sex comparison. Substantive findings were generally robust across waves and in various sensitivity analyses. These findings offer general support for the predictions of life history theory. Illness and various social disadvantages are associated with increased sexual risk behavior in adolescence and the transition to adulthood. Analyses indicate that the buffering effects of several protective social statuses against sexual risk-taking are substantially eroded by illness.

epidemiology↗

bioRxiv2017

Genome-wide association study of suicide death:Results from the first wave of Utah completed suicide data

ObjectiveSuicide death is a highly preventable, yet growing, worldwide health crisis. To date, there has been a lack of adequately powered genomic studies of suicide, with no sizeable suicide death cohorts available for study. To address this limitation, we conducted the first comprehensive genomic analysis of suicide death, using a previously unpublished suicide cohort. MethodsThe analysis sample consisted of 3,413 population-ascertained cases of European ancestry and 14,810 ancestrally matched controls. Analytical methods included principle components analysis for ancestral matching and adjusting for population stratification, linear mixed model genome-wide association testing (conditional on genetic relatedness matrix), gene and gene set enrichment testing, polygenic score analyses, as well as SNP heritability and genetic correlation estimation using LD score regression. ResultsGWAS identified two genome-wide significant loci (6 SNPs, p<5x10-8). Gene-based analyses implicated 19 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide heritability was estimated h2 =0.2463, SE = 0.0356 using summary statistics from a multivariate logistic GWAS adjusting for ancestry. Notably, suicide polygenic scores were robustly predictive of out of sample suicide death, as were polygenic scores for several other psychiatric disorders and psychological traits, particularly behavioral disinhibition and major depressive disorder. ConclusionsIn this report, we identify multiple genome-wide significant loci/genes, and demonstrate robust polygenic score prediction of suicide death case-control status, adjusting for ancestry, in independent training and test sets. Additionally, we report that suicide death cases have increased genetic risk for behavioral disinhibition, major depression, autism spectrum disorder, psychosis, and alcohol use disorder relative to controls. Results demonstrate the ability of polygenic scores to robustly, and multidimensionally, predict suicide death case-control status.

genomics↗

bioRxiv2017

Pathway-based polygenic risk implicates GO: 17144 drug metabolism in recurrent depressive disorder

The Psychiatric Genomics Consortium (PGC) has made major advances in the molecular etiology of MDD, confirming that MDD is highly polygenic, with any top risk loci conferring a very small proportion of variance in case-control status (1). Pathway enrichment results from PGC meta-analyses can also be used to help inform molecular drug targets. Prior to any knowledge of molecular biomarkers for MDD, drugs targeting molecular pathways have proved successful in treating MDD. However, it is possible that with information from PGC analyses, examining specific molecular pathway(s) implicated in MDD can further inform our study of molecular drug targets. Using a large case-control GWAS based on low-coverage whole genome sequencing (N = 10,640), we derived polygenic risk scores for MDD and for MDD specific to each of over 300 molecular pathways. We then used these data to identify sets of scores significantly predictive of case status, accounting for critical covariates. Over and above global polygenic risk for MDD, polygenic risk within the GO: 17144 drug metabolism pathway significantly predicted recurrent depression. In transcriptomic analyses, two pathway genes yielded suggestive signals at FDR q-values = .054: CYP2C19 (family of Cytochrome P450) and CBR1 (Carbonyl Reductase 1). Because the neuroleptic carbamazepine is a known inducer of CYP2C19, future research might examine whether drug metabolism PRS has any influence on clinical presentation and treatment response. Overall, results indicate that pathway-based risk might inform treatment of severe depression. We discuss limitations to the generalizability of these preliminary findings, and urge replication in future research.

genetics↗

bioRxiv2017

Proof Of Concept: Molecular Prediction Of Schizophrenia Risk

Key PointsO_ST_ABSQuestionC_ST_ABSTo what extent do global polygenic risk scores (PRS), molecular pathway-specific PRS, complement component (C4) gene expression, MHC loci, sex, and ancestry jointly contribute to risk for schizophrenia-spectrum disorders (SZ)?\n\nFindingsGlobal polygenic risk for schizophrenia, sex, and their interaction most robustly predict risk in a classification and regression tree model, with highest risk groups having 50/50 chance of SZ.\n\nMeaningPsychometric risk indicators, such as prodromal symptom assessments, may be enhanced by the examination of genetic risk metrics. Preliminary results suggest that of genetic risk metrics, global polygenic information has the most potential to significantly aide in the prediction of SZ.\n\nAbstractO_ST_ABSImportanceC_ST_ABSSchizophrenia (SZ) has a complex, heterogeneous symptom presentation with limited established associations between biological markers and illness onset. Many (gene) molecular pathways (MPs) are enriched for SZ signal, but it is still unclear how these MPs, global PRS, major histocompatibility complex (MHC) complement component (C4) gene expression, and MHC loci might jointly contribute to SZ and its clinical presentation. It is also unclear whether sex or ancestry interacts with these metrics to increase risk in certain individuals.\n\nObjectiveTo examine multiple genetic metrics, sex, and their interactions as possible predictors of SZ risk. Genetic information could aid in the clinical prediction of risk, but it is still unclear which genetic metrics are most promising, and how sex interacts with genetic risk metrics.\n\nDesign, Setting, and ParticipantsTo examine molecular risk in a proof-of-concept study, we used the Wellcome Trust case-control cohort and classified cases as a function of 1) polygenic risk score (PRS) for both whole genome and for 345 implicated molecular pathways, 2) predicted C4 expression, 3) SZ-relevant MHC loci, 4) sex, and 5) ancestry.\n\nMain Outcomes and MeasuresPRSs, C4 expression, SZ-relevant MHC loci, sex, and ancestry as joint risk factors for SZ.\n\nResultsRecursive partitioning yielded 15 molecular risk classes and retained as significant psychosis classifiers only sex, genome-wide SZ polygenic risk, and one MP PRS. Sex was the most robust classifier in a stepwise regression, and there was a significant interaction of sex with SZ PRS on case status, suggesting males have a lower polygenic risk threshold. By down-sampling case proportion to 1% and 1.4% population base rates in males and females, respectively, high-risk subtypes defined by this model had roughly a 52% odds of developing SZ (individuals with SZ PRS elevated by 2.6 SDs; incidence = 51.8%).\n\nConclusions and RelevanceThis proof-of-concept suggests that global SZ PRS, sex, and their interaction are robust predictors of risk and that males have a lower PRS threshold for onset. Implications for the integration of these metrics with psychometrically-identified risk are discussed.

genomics↗

bioRxiv2017

Polygenic prediction of the phenome, across ancestry, in emerging adulthood

BackgroundIdentifying genetic relationships between complex traits in emerging adulthood can provide useful etiological insights into risk for psychopathology. College-age individuals are under-represented in genomic analyses thus far, and the majority of work has focused on clinical disorder or cognitive abilities rather than normal-range behavioral outcomes.\n\nMethodsThis study examined a sample of emerging adults 18-22 years of age (N = 5,947) to construct an atlas of polygenic risk for 33 traits predicting relevant phenotypic outcomes. Twenty-eight hypotheses were tested based on the previous literature on samples of European ancestry, and the availability of rich assessment data allowed for polygenic predictions across 55 psychological and medical phenotypes.\n\nResultsPolygenic risk for schizophrenia in emerging adults predicted anxiety, depression, nicotine use, trauma, and family history of psychological disorders. Polygenic risk for neuroticism predicted anxiety, depression, phobia, panic, neuroticism, and was correlated with polygenic risk for cardiovascular disease.\n\nConclusionsThese results demonstrate the extensive impact of genetic risk for schizophrenia, neuroticism, and major depression on a range of health outcomes in early adulthood. Minimal cross-ancestry replication of these phenomic patterns of polygenic influence underscores the need for more genome-wide association studies of non-European populations.

genomics↗