Towards personalized medicine in psychiatry : focus on suicide

Indiana University-Purdue University Indianapolis (IUPUI)Psychiatric disorders cost an estimated $273 billion annually. This cost comes largely in the form of lost income and the chronic disability that often strikes people when they are young and can last decades. While the monetary costs are quantifiable, the suffering of each individual patient is no less vital. As many as 1 in 5 persons diagnosed with mental illness will commit suicide, a contributing factor in suicide being the second leading cause of death of people age 15-34. There is a critical need to find better ways to identify and help those who are at risk. Understanding mental illness and improving treatment has been difficult due to the heterogeneous and complex etiology of these illnesses. A significant challenge for the field is integrating findings from diverse laboratories all over the world contributing to the ever expanding literature and translating them into actionable treatment. Our lab employs a convergent functional genomics approach which incorporates multiple independent lines of evidence provided by genetic and functional genomic data published in the primary literature as a Bayesian strategy to prioritize experimental findings. Heritability and genetics clearly play an important role in psychiatric disorders. We looked at schizophrenia and alcoholism in separate case-control analyses in order to identify and prioritize genes related to these disorders. We were able to reproduce these findings in additional independent cohorts using polygenic risk scores. We found overlap in these disorders, and identified possible underlying biological processes. Genetics play an important role in identifying clinical risk, particularly at the population level. At the level of the individual, gene expression may provide more proximal association to disease state, assimilating environmental, genetic, as well as epigenetic influence. We undertook N of 1 analyses in a longitudinally followed cohort of psychiatric participants, identifying genes which change in expression tracking an individual’s change in suicidal ideation. These genes were able to predict suicidal behavior in independent cohorts. When combined with simple clinical instruments these predictions were improved. This work shows how multi level integration of genetic, gene expression, and clinical data could be used to enable precision medicine in psychiatry

Genetic Decomposition of the Heritable Component of Reported Childhood Maltreatment

BACKGROUND: Decades of research have shown that environmental exposures, including self-reports of trauma, are partly heritable. Heritable characteristics may influence exposure to and interpretations of environmental factors. Identifying heritable factors associated with self-reported trauma could improve our understanding of vulnerability to exposure and the interpretation of life events. METHODS: We used genome-wide association study summary statistics of childhood maltreatment, defined as reporting of abuse (emotional, sexual, and physical) and neglect (emotional and physical) (N = 185,414 participants). We calculated genetic correlations (rg) between reported childhood maltreatment and 576 traits to identify phenotypes that might explain the heritability of reported childhood maltreatment, retaining those with |rg| > 0.25. We specified multiple regression models using genomic structural equation modeling to detect residual genetic variance in childhood maltreatment after accounting for genetically correlated traits. RESULTS: In 2 separate models, the shared genetic component of 12 health and behavioral traits and 7 psychiatric disorders accounted for 59% and 56% of heritability due to common genetic variants (single nucleotide polymorphism–based heritability [h2SNP]) of childhood maltreatment, respectively. Genetic influences on h2SNP of childhood maltreatment were generally accounted for by a shared genetic component across traits. The exceptions to this were general risk tolerance, subjective well-being, posttraumatic stress disorder, and autism spectrum disorder, identified as independent contributors to h2SNP of childhood maltreatment. These 4 traits alone were sufficient to explain 58% of h2SNP of childhood maltreatment. CONCLUSIONS: We identified putative traits that reflect h2SNP of childhood maltreatment. Elucidating the mechanisms underlying these associations may improve trauma prevention and posttraumatic intervention strategies

Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration

Sleep duration has been linked to a wide range of negative health outcomes and to reduced life expectancy. We present genome-wide association studies of short ( ≤ 5 h) and long ( ≥ 10 h) sleep duration in adults of European (N = 445,966), African (N = 27,785), East Asian (N = 3141), and admixed-American (N = 16,250) ancestry from UK Biobank and the Million Veteran Programme. In a cross-population meta-analysis, we identify 84 independent loci for short sleep and 1 for long sleep. We estimate SNP-based heritability for both sleep traits in each ancestry based on population derived linkage disequilibrium (LD) scores using cov-LDSC. We identify positive genetic correlation between short and long sleep traits (rg = 0.16 ± 0.04; p = 0.0002), as well as similar patterns of genetic correlation with other psychiatric and cardiometabolic phenotypes. Mendelian randomisation reveals a directional causal relationship between short sleep and depression, and a bidirectional causal relationship between long sleep and depression

Collective genomic segments with differential pleiotropic patterns between cognitive dimensions and psychopathology

Cognitive deficits are known to be related to most forms of psychopathology. Here, we perform local genetic correlation analysis as a means of identifying independent segments of the genome that show biologically interpretable pleiotropic associations between cognitive dimensions and psychopathology. We identify collective segments of the genome, which we call meta-loci , showing differential pleiotropic patterns for psychopathology relative to either cognitive task performance (CTP) or performance on a non-cognitive factor (NCF) derived from educational attainment. We observe that neurodevelopmental gene sets expressed during the prenatal-early childhood period predominate in CTP-relevant meta-loci, while post-natal gene sets are more involved in NCF-relevant meta-loci. Further, we demonstrate that neurodevelopmental gene sets are dissociable across CTP meta-loci with respect to their spatial distribution across the brain. Additionally, we find that GABA-ergic, cholinergic, and glutamatergic genes drive pleiotropic relationships within dissociable meta-loci

Collective genomic segments with differential pleiotropic patterns between cognitive dimensions and psychopathology

Cognitive deficits are known to be related to most forms of psychopathology. Here, we perform local genetic correlation analysis as a means of identifying independent segments of the genome that show biologically interpretable pleiotropic associations between cognitive dimensions and psychopathology. We identify collective segments of the genome, which we call “meta-loci”, showing differential pleiotropic patterns for psychopathology relative to either cognitive task performance (CTP) or performance on a non-cognitive factor (NCF) derived from educational attainment. We observe that neurodevelopmental gene sets expressed during the prenatal-early childhood period predominate in CTP-relevant meta-loci, while post-natal gene sets are more involved in NCF-relevant meta-loci. Further, we demonstrate that neurodevelopmental gene sets are dissociable across CTP meta-loci with respect to their spatial distribution across the brain. Additionally, we find that GABA-ergic, cholinergic, and glutamatergic genes drive pleiotropic relationships within dissociable meta-loci

B-Type Natriuretic Peptide and Cardiac Troponin I Are Associated With Adverse Outcomes in Stable Kidney Transplant Recipients

Approximately 200,000 kidney transplant recipients are living in the US; they are at increased risk for cardiovascular and other adverse outcomes. Biomarkers predicting these outcomes are needed. Using specimens collected during the FAVORIT (Folic Acid for Vascular Outcome Reduction In Transplantation) trial, we determined whether plasma levels of B-type natriuretic peptide (BNP) and cardiac troponin I are associated with adverse outcomes in stable kidney transplant recipients

International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci.

The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations

Circulating adiponectin levels are lower in Latino versus non-Latino white patients at risk for cardiovascular disease, independent of adiposity measures

<p>Abstract</p> <p>Background</p> <p>Latinos in the United States have a higher prevalence of type 2 diabetes than non-Latino whites, even after controlling for adiposity. Decreased adiponectin is associated with insulin resistance and predicts T2DM, and therefore may mediate this ethnic difference. We compared total and high-molecular-weight (HMW) adiponectin in Latino versus white individuals, identified factors associated with adiponectin in each ethnic group, and measured the contribution of adiponectin to ethnic differences in insulin resistance.</p> <p>Methods</p> <p>We utilized cross-sectional data from subjects in the Latinos Using Cardio Health Actions to reduce Risk study. Participants were Latino (n = 119) and non-Latino white (n = 60) men and women with hypertension and at least one other risk factor for CVD (age 61 ± 10 yrs, 49% with T2DM), seen at an integrated community health and hospital system in Denver, Colorado. Total and HMW adiponectin was measured by RIA and ELISA respectively. Fasting glucose and insulin were used to calculate the homeostasis model insulin resistance index (HOMA-IR). Variables independently associated with adiponectin levels were identified by linear regression analyses. Adiponectin's contribution to ethnic differences in insulin resistance was assessed in multivariate linear regression models of Latino ethnicity, with logHOMA-IR as a dependent variable, adjusting for possible confounders including age, gender, adiposity, and renal function.</p> <p>Results</p> <p>Mean adiponectin levels were lower in Latino than white patients (beta estimates: -4.5 (-6.4, -2.5), p < 0.001 and -1.6 (-2.7, -0.5), p < 0.005 for total and HMW adiponectin), independent of age, gender, BMI/waist circumference, thiazolidinedione use, diabetes status, and renal function. An expected negative association between adiponectin and waist circumference was seen among women and non-Latino white men, but no relationship between these two variables was observed among Latino men. Ethnic differences in logHOMA-IR were no longer observed after controlling for adiponectin levels.</p> <p>Conclusions</p> <p>Among patients with CVD risk, total and HMW adiponectin is lower in Latinos, independent of adiposity and other known regulators of adiponectin. Ethnic differences in adiponectin regulation may exist and future research in this area is warranted. Adiponectin levels accounted for the observed variability in insulin resistance, suggesting a contribution of decreased adiponectin to insulin resistance in Latino populations.</p

A Multiancestral Genome-Wide Exome Array Study of Alzheimer Disease, Frontotemporal Dementia, and Progressive Supranuclear Palsy

Importance Previous studies have indicated a heritable component of the etiology of neurodegenerative diseases such as Alzheimer disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP). However, few have examined the contribution of low-frequency coding variants on a genome-wide level. Objective To identify low-frequency coding variants that affect susceptibility to AD, FTD, and PSP. Design, Setting, and Participants We used the Illumina HumanExome BeadChip array to genotype a large number of variants (most of which are low-frequency coding variants) in a cohort of patients with neurodegenerative disease (224 with AD, 168 with FTD, and 48 with PSP) and in 224 control individuals without dementia enrolled between 2005-2012 from multiple centers participating in the Genetic Investigation in Frontotemporal Dementia and Alzheimer’s Disease (GIFT) Study. An additional multiancestral replication cohort of 240 patients with AD and 240 controls without dementia was used to validate suggestive findings. Variant-level association testing and gene-based testing were performed. Main Outcomes and Measures Statistical association of genetic variants with clinical diagnosis of AD, FTD, and PSP. Results Genetic variants typed by the exome array explained 44%, 53%, and 57% of the total phenotypic variance of AD, FTD, and PSP, respectively. An association with the known AD gene ABCA7 was replicated in several ancestries (discovery P = .0049, European P = .041, African American P = .043, and Asian P = .027), suggesting that exonic variants within this gene modify AD susceptibility. In addition, 2 suggestive candidate genes, DYSF (P = 5.53 × 10−5) and PAXIP1 (P = 2.26 × 10−4), were highlighted in patients with AD and differentially expressed in AD brain. Corroborating evidence from other exome array studies and gene expression data points toward potential involvement of these genes in the pathogenesis of AD. Conclusions and Relevance Low-frequency coding variants with intermediate effect size may account for a significant fraction of the genetic susceptibility to AD and FTD. Furthermore, we found evidence that coding variants in the known susceptibility gene ABCA7, as well as candidate genes DYSF and PAXIP1, confer risk for AD