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Understanding the nature of the genetic regulation of gene expression promises to advance our understanding of the genetic basis of disease. However, the methodological impact of the use of local ancestry on high-dimensional omics analyses, including, most prominently, expression quantitative trait loci (eQTL) mapping and trait heritability estimation, in admixed populations remains critically underexplored. Here, we develop a statistical framework that characterizes the relationships among the determinants of the genetic architecture of an important class of molecular traits. We provide a computationally efficient approach to local ancestry analysis in eQTL mapping while increasing control of type I and type II error over traditional approaches. Applying our method to National Institute of General Medical Sciences (NIGMS) and Genotype-Tissue Expression (GTEx) datasets, we show that the use of local ancestry can improve eQTL mapping in admixed and multiethnic populations, respectively. We estimate the trait variance explained by ancestry by using local admixture relatedness between individuals. By using simulations of diverse genetic architectures and degrees of confounding, we show improved accuracy in estimating heritability when accounting for local ancestry similarity. Furthermore, we characterize the sparse versus polygenic components of gene expression in admixed individuals. Our study has important methodological implications for genetic analysis of omics traits across a range of genomic contexts, from a single variant to a prioritized region to the entire genome. Our findings highlight the importance of using local ancestry to better characterize the heritability of complex traits and to more accurately map genetic associations.
Copyright © 2019 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
The genetic architecture of psychiatric disorders is characterized by a large number of small-effect variants located primarily in non-coding regions, suggesting that the underlying causal effects may influence disease risk by modulating gene expression. We provide comprehensive analyses using transcriptome data from an unprecedented collection of tissues to gain pathophysiological insights into the role of the brain, neuroendocrine factors (adrenal gland) and gastrointestinal systems (colon) in psychiatric disorders. In each tissue, we perform PrediXcan analysis and identify trait-associated genes for schizophrenia (n associations = 499; n unique genes = 275), bipolar disorder (n associations = 17; n unique genes = 13), attention deficit hyperactivity disorder (n associations = 19; n unique genes = 12) and broad depression (n associations = 41; n unique genes = 31). Importantly, both PrediXcan and summary-data-based Mendelian randomization/heterogeneity in dependent instruments analyses suggest potentially causal genes in non-brain tissues, showing the utility of these tissues for mapping psychiatric disease genetic predisposition. Our analyses further highlight the importance of joint tissue approaches as 76% of the genes were detected only in difficult-to-acquire tissues.
PURPOSE - Cisplatin, a commonly used chemotherapeutic, results in tinnitus, the phantom perception of sound. Our purpose was to identify the clinical and genetic determinants of tinnitus among testicular cancer survivors (TCS) following cisplatin-based chemotherapy.
EXPERIMENTAL DESIGN - TCS ( = 762) were dichotomized to cases (moderate/severe tinnitus; = 154) and controls (none; = 608). Logistic regression was used to evaluate associations with comorbidities and SNP dosages in genome-wide association study (GWAS) following quality control and imputation (covariates: age, noise exposure, cisplatin dose, genetic principal components). Pathway over-representation tests and functional studies in mouse auditory cells were performed.
RESULTS - Cisplatin-induced tinnitus (CisIT) significantly associated with age at diagnosis ( = 0.007) and cumulative cisplatin dose ( = 0.007). CisIT prevalence was not significantly greater in 400 mg/m-treated TCS compared with 300 ( = 0.41), but doses >400 mg/m (median 580, range 402-828) increased risk by 2.61-fold ( < 0.0001). CisIT cases had worse hearing at each frequency (0.25-12 kHz, < 0.0001), and reported more vertigo (OR = 6.47; < 0.0001) and problems hearing in a crowd (OR = 8.22; < 0.0001) than controls. Cases reported poorer health ( < 0.0001) and greater psychotropic medication use (OR = 2.4; = 0.003). GWAS suggested a variant near (rs7606353, = 2 × 10) and eQTLs were significantly enriched independently of that SNP ( = 0.018). overexpression in HEI-OC1, a mouse auditory cell line, resulted in resistance to cisplatin-induced cytotoxicity. Pathway analysis implicated potassium ion transport (q = 0.007).
CONCLUSIONS - CisIT associated with several neuro-otological symptoms, increased use of psychotropic medication, and poorer health. , expressed in the cochlear lateral wall, was implicated as protective. Future studies should investigate otoprotective targets in supporting cochlear cells.
©2019 American Association for Cancer Research.
Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.
BACKGROUND - The relation between burden of risk factors, familial coronary artery disease (CAD), and known genetic variants underlying CAD and low-density lipoprotein cholesterol (LDL-C) levels is not well-explored in clinical samples. We aimed to investigate the association of these measures with age at onset of CAD requiring revascularizations in a clinical sample of patients undergoing first-time coronary angiography.
METHODS - 1599 individuals (mean age 64 years [min-max 29-96 years], 28% women) were genotyped (from blood drawn as part of usual clinical care) in the Copenhagen area (2010-2014). The burden of common genetic variants was measured as aggregated genetic risk scores (GRS) of single nucleotide polymorphisms (SNPs) discovered in genome-wide association studies.
RESULTS - Self-reported familial CAD (prevalent in 41% of the sample) was associated with -3.2 years (95% confidence interval -4.5, -2.2, p<0.0001) earlier need of revascularization in sex-adjusted models. Patients with and without familial CAD had similar mean values of CAD-GRS (unweighted scores 68.4 vs. 68.0, p = 0.10, weighted scores 67.7 vs. 67.5, p = 0.49) and LDL-C-GRS (unweighted scores 58.5 vs. 58.3, p = 0.34, weighted scores 63.3 vs. 61.1, p = 0.41). The correlation between the CAD-GRS and LDL-C-GRS was low (r = 0.14, p<0.001). In multivariable adjusted regression models, each 1 standard deviation higher values of LDL-C-GRS and CAD-GRS were associated with -0.70 years (95% confidence interval -1.25, -0.14, p = 0.014) and -0.51 years (-1.07, 0.04, p = 0.07) earlier need for revascularization, respectively.
CONCLUSIONS - Young individuals presenting with CAD requiring surgical interventions had a higher genetic burden of SNPs relating to LDL-C and CAD (although the latter was statistically non-significant), compared with older individuals. However, the absolute difference was modest, suggesting that genetic screening can currently not be used as an effective prediction tool of when in life a person will develop CAD. Whether undiscovered genetic variants can still explain a "missing heritability" in early-onset CAD warrants more research.
Importance - Thyroid hormone levels are tightly regulated through feedback inhibition by thyrotropin, produced by the pituitary gland. Hyperthyroidism is overwhelmingly due to thyroid disorders and is well recognized to contribute to a wide spectrum of cardiovascular morbidity, particularly the increasingly common arrhythmia atrial fibrillation (AF).
Objective - To determine the association between genetically determined thyrotropin levels and AF.
Design, Setting, and Participants - This phenome-wide association study scanned 1318 phenotypes associated with a polygenic predictor of thyrotropin levels identified by a previously published genome-wide association study that included participants of European ancestry. North American individuals of European ancestry with longitudinal electronic health records were analyzed from May 2008 to November 2016. Analysis began March 2018.
Main Outcomes and Measures - Clinical diagnoses associated with a polygenic predictor of thyrotropin levels.
Exposures - Genetically determined thyrotropin levels.
Results - Of 37 154 individuals, 19 330 (52%) were men. The thyrotropin polygenic predictor was positively associated with hypothyroidism (odds ratio [OR], 1.10; 95% CI, 1.07-1.14; P = 5 × 10-11) and inversely associated with diagnoses related to hyperthyroidism (OR, 0.64; 95% CI, 0.54-0.74; P = 2 × 10-8 for toxic multinodular goiter). Among nonthyroid associations, the top association was AF/flutter (OR, 0.93; 95% CI, 0.9-0.95; P = 9 × 10-7). When the analyses were repeated excluding 9801 individuals with any diagnoses of a thyroid-related disease, the AF association persisted (OR, 0.91; 95% CI, 0.88-0.95; P = 2.9 × 10-6). To replicate this association, we conducted an inverse-variance weighted average meta-analysis using AF single-nucleotide variant weights from a genome-wide association study of 17 931 AF cases and 115 142 controls. As in the discovery analyses, each SD increase in predicted thyrotropin was associated with a decreased risk of AF (OR, 0.86; 95% CI, 0.79-0.93; P = 4.7 × 10-4). In a set of AF cases (n = 745) and controls (n = 1680) older than 55 years, directly measured thyrotropin levels that fell within the normal range were inversely associated with AF risk (OR, 0.91; 95% CI, 0.83-0.99; P = .04).
Conclusions and Relevance - This study suggests a role for genetically determined variation in thyroid function within a physiologically accepted normal range as a risk factor for AF. The clinical decision to treat subclinical thyroid disease should incorporate the risk for AF as antithyroid medications to treat hyperthyroidism may reduce AF risk and thyroid hormone replacement for hypothyroidism may increase AF risk.
Interpretation of genetic association results is difficult because signals often lack biological context. To generate hypotheses of the functional genetic etiology of complex cardiometabolic traits, we estimated the genetically determined component of gene expression from common variants using PrediXcan (1) and determined genes with differential predicted expression by trait. PrediXcan imputes tissue-specific expression levels from genetic variation using variant-level effect on gene expression in transcriptome data. To explore the value of imputed genetically regulated gene expression (GReX) models across different ancestral populations, we evaluated imputed expression levels for predictive accuracy genome-wide in RNA sequence data in samples drawn from European-ancestry and African-ancestry populations and identified substantial predictive power using European-derived models in a non-European target population. We then tested the association of GReX on 15 cardiometabolic traits including blood lipid levels, body mass index, height, blood pressure, fasting glucose and insulin, RR interval, fibrinogen level, factor VII level and white blood cell and platelet counts in 15 755 individuals across three ancestry groups, resulting in 20 novel gene-phenotype associations reaching experiment-wide significance across ancestries. In addition, we identified 18 significant novel gene-phenotype associations in our ancestry-specific analyses. Top associations were assessed for additional support via query of S-PrediXcan (2) results derived from publicly available genome-wide association studies summary data. Collectively, these findings illustrate the utility of transcriptome-based imputation models for discovery of cardiometabolic effect genes in a diverse dataset.
© The Author(s) 2019. Published by Oxford University Press.
In this trans-ethnic multi-omic study, we reinterpret the genetic architecture of blood pressure to identify genes, tissues, phenomes and medication contexts of blood pressure homeostasis. We discovered 208 novel common blood pressure SNPs and 53 rare variants in genome-wide association studies of systolic, diastolic and pulse pressure in up to 776,078 participants from the Million Veteran Program (MVP) and collaborating studies, with analysis of the blood pressure clinical phenome in MVP. Our transcriptome-wide association study detected 4,043 blood pressure associations with genetically predicted gene expression of 840 genes in 45 tissues, and mouse renal single-cell RNA sequencing identified upregulated blood pressure genes in kidney tubule cells.
BACKGROUND - Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a "virtual proteomic" approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals.
METHODS - We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651).
RESULTS - In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-β predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08-1.58; P=0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66-0.94; P=0.008) per 1-SD increment in platelet-derived growth factor receptor-β.
CONCLUSIONS - We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.
BACKGROUND - Recent GWAS studies have identified more than 300 SNPs associated with variation in blood pressure. We investigated whether a genetic risk score constructed from these variants is associated with burden of coronary heart disease.
METHODS - From 2010-2014, 4,809 individuals admitted to coronary angiography in Capital Region of Copenhagen were genotyped. We calculated hypertension GRS comprised of GWAS identified SNPs associated with blood pressure. We performed logistic regression analyses to estimate the risk of hypertension and prevalent CHD. We also assessed the severity of CHD associated with the GRS. The analyses were performed using GRS quartiles. We used the Inter99 cohort to validate our results and to investigate for possible pleiotropy for the GRS with other CHD risk factors.
RESULTS - In COGEN, adjusted odds ratios comparing the 2nd, 3rd and 4th cumulative GRS quartiles with the reference were 1.12(95% CI 0.95-1.33), 1.35(95% CI 1.14-1.59) and 1.29(95% CI 1.09-1.53) respectively, for prevalent CHD. The adjusted multinomial logistic regression showed that 3rd and 4th GRS quartiles were associated with increased odds of developing two(OR 1.33, 95% CI 1.04-1.71 and OR 1.36, 95% CI 1.06-1.75, respectively) and three coronary vessel disease(OR 1.77, 95% CI 1.36-2.30 and OR 1.65, 95% CI 1.26-2.15, respectively). Similar results for incident CHD were observed in the Inter99 cohort. The hypertension GRS did not associate with type 2 diabetes, smoking, BMI or hyperlipidemia.
CONCLUSION - Hypertension GRS quartiles were associated with an increased risk of hypertension, prevalent CHD, and burden of coronary vessel disease in a dose-response pattern. We showed no evidence for pleiotropy with other risk factors for CHD.