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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.
Differential gene expression defines individual neuron types and determines how each contributes to circuit physiology and responds to injury and disease. The C. elegans Neuronal Gene Expression Map & Network (CeNGEN) will establish a comprehensive gene expression atlas of an entire nervous system at single-neuron resolution.
Copyright © 2018. Published by Elsevier Inc.
We performed a whole-genome scan of genetic variants in splicing regulatory elements (SREs) and evaluated the extent to which natural selection has shaped extant patterns of variation in SREs. We investigated the degree of differentiation of single nucleotide polymorphisms (SNPs) in SREs among human populations and applied long-range haplotype- and multilocus allelic differentiation-based methods to detect selection signatures. We describe an approach, sampling a large number of loci across the genome from functional classes and using the consensus from multiple tests, for identifying candidates for selection signals. SRE SNPs in various SNP functional classes show different patterns of population differentiation compared with their non-SRE counterparts. Intronic regions display a greater enrichment for extreme population differentiation among the potentially tissue-dependent transcript ratio quantitative trait loci (trQTLs) than SRE SNPs in general and includ outlier trQTLs for cross-population composite likelihood ratio, suggesting that incorporation of context annotation for regulatory variation may lead to improved detection of signature of selection on these loci. The proportion of extremely rare SNPs disrupting SREs is significantly higher in European than in African samples. The approach developed here will be broadly useful for studies of function and disease-associated variation in the human genome.
Race, specifically African ancestry, and obesity are important risk factors for uterine fibroids, and likely interact to provide the right conditions for fibroid growth. However, existing studies largely focus on the main-effects rather than their interaction. Here, we firstly provide evidence for interaction between categories of body mass index (BMI) and reported-race in relation to uterine fibroids. We then investigate whether the association between inferred local European ancestry and fibroid risk is modified by BMI in African American (AA) women in the Vanderbilt University Medical Center bio-repository (BioVU) (539 cases and 794 controls) and the Coronary Artery Risk Development in Young Adults study (CARDIA, 264 cases and 173 controls). We used multiple logistic regression to evaluate interactions between local European ancestry and BMI in relation to fibroid risk, then performed fixed effects meta-analysis. Statistical significance threshold for local-ancestry and BMI interactions was empirically estimated with 10,000 permutations (p-value = 1.18x10-4). Admixture mapping detected an association between European ancestry and fibroid risk which was modified by BMI (continuous-interaction p-value = 3.75x10-5) around ADTRP (chromosome 6p24); the strongest association was found in the obese category (ancestry odds ratio (AOR) = 0.51, p-value = 2.23x10-5). Evaluation of interaction between genotyped/imputed variants and BMI in this targeted region suggested race-specific interaction, present in AAs only; strongest evidence was found for insertion/deletion variant (6:11946435), again in the obese category (OR = 1.66, p-value = 1.72x10-6). We found nominal evidence for interaction between local ancestry and BMI at a previously reported region in chromosome 2q31-32, which includes COL5A2, and TFPI, an immediate downstream target of ADTRP. Interactions between BMI and SNPs (single nucleotide polymorphisms) found in this region in AA women were also detected in an independent European American population of 1,195 cases and 1,164 controls. Findings from our study provide an example of how modifiable and non-modifiable factors may interact to influence fibroid risk and suggest a biological role for BMI in fibroid etiology.
Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations.
Over the past 20 years, high-penetrance pathogenic mutations in genes BRCA1, BRCA2, TP53, PTEN, STK11 and CDH1 and moderate-penetrance mutations in genes CHEK2, ATM, BRIP1, PALB2, RAD51C, RAD50 and NBN have been identified for breast cancer. In this study, we investigated whether there are additional variants in these 13 genes associated with breast cancer among women of Asian ancestry. We analyzed up to 654 single nucleotide polymorphisms (SNPs) from 6269 cases and 6624 controls of Asian descent included in the Breast Cancer Association Consortium (BCAC), and up to 236 SNPs from 5794 cases and 5529 controls included in the Shanghai Breast Cancer Genetics Study (SBCGS). We found three missense variants with minor allele frequency (MAF) <0.05: rs80358978 (Gly2508Ser), rs80359065 (Lys2729Asn) and rs11571653 (Met784Val) in the BRCA2 gene, showing statistically significant associations with breast cancer risk, with P-values of 1.2 × 10-4, 1.0 × 10-3 and 5.0 × 10-3, respectively. In addition, we found four low-frequency variants (rs8176085, rs799923, rs8176173 and rs8176258) in the BRCA1 gene, one common variant in the CHEK2 gene (rs9620817), and one common variant in the PALB2 gene (rs13330119) associated with breast cancer risk at P < 0.01. Our study identified several new risk variants in BRCA1, BRCA2, CHEK2, and PALB2 genes in relation to breast cancer risk in Asian women. These results provide further insights that, in addition to the high/moderate penetrance mutations, other low-penetrance variants in these genes may also contribute to breast cancer risk.
© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: email@example.com.
Genome-wide association studies have identified approximately 100 common genetic variants associated with breast cancer risk, the majority of which were discovered in women of European ancestry. Because of different patterns of linkage disequilibrium, many of these genetic markers may not represent signals in populations of African ancestry. We tested 74 breast cancer risk variants and conducted fine-mapping of these susceptibility regions in 6,522 breast cancer cases and 7,643 controls of African ancestry from three genetic consortia (AABC, AMBER, and ROOT). Fifty-four of the 74 variants (73%) were found to have ORs that were directionally consistent with those previously reported, of which 12 were nominally statistically significant ( < 0.05). Through fine-mapping, in six regions (), we observed seven markers that better represent the underlying risk variant for overall breast cancer or breast cancer subtypes, whereas in another two regions (), we identified suggestive evidence of signals that are independent of the reported index variant. Overlapping chromatin features and regulatory elements suggest that many of the risk alleles lie in regions with biological functionality. Through fine-mapping of known susceptibility regions, we have revealed alleles that better characterize breast cancer risk in women of African ancestry. The risk alleles identified represent genetic markers for modeling and stratifying breast cancer risk in women of African ancestry. .
©2017 American Association for Cancer Research.
MUFAs are unsaturated FAs with one double bond and are derived from endogenous synthesis and dietary intake. Accumulating evidence has suggested that plasma and erythrocyte MUFA levels are associated with cardiometabolic disorders, including CVD, T2D, and metabolic syndrome (MS). Previous genome-wide association studies (GWASs) have identified seven loci for plasma and erythrocyte palmitoleic and oleic acid levels in populations of European origin. To identify additional MUFA-associated loci and the potential functional variant at each locus, we performed ethnic-specific GWAS meta-analyses and trans-ethnic meta-analyses in more than 15,000 participants of Chinese and European ancestry. We identified novel genome-wide significant associations for vaccenic acid at and [log(Bayes factor) ≥ 8.07] and for gondoic acid at and [log(Bayes factor) ≥ 6.22], and also observed improved fine-mapping resolutions at and loci. The greatest improvement was observed at , where the number of variants in the 99% credible set was reduced from 16 (covering 94.8 kb) to 5 (covering 19.6 kb, including a missense variant rs1260326) after trans-ethnic meta-analysis. We also confirmed the previously reported associations of , , , and with palmitoleic acid and of and with oleic acid in the Chinese-specific GWAS and the trans-ethnic meta-analyses. Pathway-based analyses suggested that the identified loci were in unsaturated FA metabolism and signaling pathways. Our findings provide novel insight into the genetic basis relevant to MUFA metabolism and biology.
Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.
Genetic suppression occurs when the phenotypic defects caused by a mutation in a particular gene are rescued by a mutation in a second gene. To explore the principles of genetic suppression, we examined both literature-curated and unbiased experimental data, involving systematic genetic mapping and whole-genome sequencing, to generate a large-scale suppression network among yeast genes. Most suppression pairs identified novel relationships among functionally related genes, providing new insights into the functional wiring diagram of the cell. In addition to suppressor mutations, we identified frequent secondary mutations,in a subset of genes, that likely cause a delay in the onset of stationary phase, which appears to promote their enrichment within a propagating population. These findings allow us to formulate and quantify general mechanisms of genetic suppression.
Copyright © 2016, American Association for the Advancement of Science.
A substantial number of mutations have been identified in voltage-gated sodium channel genes that result in various forms of human epilepsy. SCN1A mutations result in a spectrum of severity ranging from mild febrile seizures to Dravet syndrome, an infant-onset epileptic encephalopathy. Dravet syndrome patients experience multiple seizures types that are often refractory to treatment, developmental delays, and elevated risk for SUDEP. The same sodium channel mutation can produce epilepsy phenotypes of varying clinical severity. This suggests that other factors, including genetic, modify the primary mutation and change disease severity. Mouse models provide a useful tool in studying the genetic basis of epilepsy. The mouse strain background can alter phenotype severity, supporting a contribution of genetic modifiers in epilepsy. The Scn1a+/- mouse model has a strain-dependent epilepsy phenotype. Scn1a+/- mice on the 129S6/SvEvTac (129) strain have a normal phenotype and lifespan, while [129xC57BL/6J]F1-Scn1a+/- mice experience spontaneous seizures, hyperthermia-induced seizures and high rates of premature death. We hypothesize the phenotypic differences are due to strain-specific genetic modifiers that influence expressivity of the Scn1a+/- phenotype. Low resolution mapping of Scn1a+/- identified several Dravet syndrome modifier (Dsm) loci responsible for the strain-dependent difference in survival. One locus of interest, Dsm1 located on chromosome 5, was fine mapped to a 9 Mb region using interval specific congenics. RNA-Seq was then utilized to identify candidate modifier genes within this narrowed region. Three genes with significant total gene expression differences between 129S6/SvEvTac and [129xC57BL/6J]F1 were identified, including the GABAA receptor subunit, Gabra2. Further analysis of Gabra2 demonstrated allele-specific expression. Pharmological manipulation by clobazam, a common anticonvulsant with preferential affinity for the GABRA2 receptor, revealed dose-dependent protection against hyperthermia-induced seizures in Scn1a+/- mice. These findings support Gabra2 as a genetic modifier of the Scn1a+/- mouse model of Dravet syndrome.