scholarly journals Multi-trait GWAS of atherosclerosis detects novel pleiotropic loci

2021 ◽  
Author(s):  
Tiffany R Bellomo ◽  
William P Bone ◽  
Brian Y Chen ◽  
Katerina A. B. Gawronski ◽  
David Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Vascular Diseases ◽  
Smoking Initiation ◽  
Joint Analysis ◽  
Genome Wide Association Studies ◽  
Human Liver Tissue ◽  
Genome Wide ◽  
Artery Disease

Rationale: Although affecting different arterial territories, the related atherosclerotic vascular diseases coronary artery disease (CAD) and peripheral artery disease (PAD) share similar risk factors and have shared pathobiology. Analysis of their shared genetic architecture, along with that of common risk factors, may identify novel common biology. Objective: To identify novel pleiotropic genetic loci associated with atherosclerosis and provide a better understanding of biological pathways underlying atherosclerosis. Methods and Results: Summary statistics from genome wide association studies (GWAS) of nine known atherosclerotic (CAD, PAD) or atherosclerosis risk factors (body mass index, smoking initiation, type 2 diabetes, low density lipoprotein (LDL), high density lipoprotein, total cholesterol, and triglycerides) were combined to perform 15 separate multi-trait genetic association scans which resulted in 31 unique novel pleiotropic loci not yet reported as genome-wide significant for their respective traits. Colocalization with single-tissue eQTLs identified 34 candidate causal genes across 14 of the detected signals. Notably, the signal between PAD and CAD at the VDAC2 locus (rs7088974) colocalized with VDAC2 expression in aorta and tibial artery tissues. Additionally, the signal between PAD and LDL at the PCSK6 locus (rs1531817) affects PCSK6 splicing in human liver tissue and induced pluripotent derived hepatocyte like cells. Conclusions: Joint analysis of related atherosclerotic disease traits and their risk factors allowed identification of unified biology that may offer the opportunity for therapeutic manipulation. VDAC2 and PCSK6 represent possible shared causal biology where existing inhibitors may be able to be leveraged for novel therapies.

scholarly journals M88. EVIDENCE FOR INFLAMMATION AS A PUTATIVE SHARED MECHANISM FOR INSULIN RESISTANCE AND SCHIZOPHRENIA

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S168-S168
Author(s):  
Benjamin Perry ◽  
Stephen Burgess ◽  
Hannah Jones ◽  
Stanley Zammit ◽  
Rachel Upthegrove ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Genetic Variants ◽  
Cardiometabolic Risk ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Cardiometabolic Risk Factors ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Cardiometabolic Disorders

Abstract Background Insulin Resistance (IR) predisposes to cardiometabolic disorders, which are common in schizophrenia and are associated with excess morbidity and mortality. The mechanisms of association remain unknown. We aimed 1) To use genetic data to examine the direction of association between IR and related cardiometabolic risk factors, and schizophrenia; 2) To examine whether inflammation could be a shared mechanism for IR and schizophrenia. Methods We used two-sample uni-variable Mendelian randomization (MR) to examine whether genetically-predicted IR-related cardiometabolic risk factors (Fasting insulin (FI), high-density lipoprotein (HDL), triglycerides (TG), low-density lipoprotein, fasting plasma glucose, glycated haemoglobin, leptin, body mass index, glucose tolerance and type 2 diabetes) may be causally associated with schizophrenia. We used the most recent summary statistics for genetic variants associated with schizophrenia and IR-related cardiometabolic risk factors from publicly-available large genome-wide association studies (GWAS). We used bi-directional MR to examine direction of association. To examine whether inflammation could be a shared mechanism for IR and schizophrenia, we first conducted a sensitivity analysis by performing MR using only cardiometabolic genetic variants that were also associated with inflammation, at genome-wide significance. Second, we used multi-variable MR (MVMR) to examine associations between cardiometabolic risk factors and schizophrenia after adjusting for genetically-predicted levels of C-reactive protein. Results In analyses using all associated genetic variants, genetically predicted levels of leptin were associated with risk of schizophrenia (OR=2.54 per SD increase in leptin; 95% CI, 1.02–6.31). In analyses using inflammation-related variants, genetically predicted levels of FI (OR=2.76 per SD increase in FI; 95% C.I., 1.31–6.17), TG (OR=2.90 per SD increase in TG; 95% C.I., 1.36–6.17), and HDL (OR=0.56 per SD increase in HDL; 95% C.I., 0.37–0.83) were associated with schizophrenia. The associations completely attenuated in MVMR analyses controlling for CRP. There was no evidence of an association between genetically-predicted schizophrenia liability and cardiometabolic factors. Discussion The IR phenotype of FI, TG and HDL could be associated with schizophrenia over and above common sociodemographic and lifestyle factors. This association is likely explained by a common inflammatory mechanism. Interventional studies are required to test whether inflammation could represent a putative therapeutic target for the treatment and prevention of cardiometabolic disorders in schizophrenia.

scholarly journals A large-scale genome-wide enrichment analysis identifies new trait-associated genes, pathways and tissues across 31 human phenotypes*

2017 ◽  
Author(s):  
Xiang Zhu ◽  
Matthew Stephens
Keyword(s):  
Complex Traits ◽  
Large Scale ◽  
Late Onset ◽  
Association Studies ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Enrichment Analysis ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Artery Disease

Genome-wide association studies (GWAS) aim to identify genetic factors that are associated with complex traits. Standard analyses test individual genetic variants, one at a time, for association with a trait. However, variant-level associations are hard to identify (because of small effects) and can be difficult to interpret biologically. “Enrichment analyses” help address both these problems by focusing on sets of biologically-related variants. Here we introduce a new model-based enrichment analysis method that requires only GWAS summary statistics, and has several advantages over existing methods. Applying this method to interrogate 3,913 biological pathways and 113 tissue-based gene sets in 31 human phenotypes identifies many previously-unreported enrichments. These include enrichments of the endochondral ossification pathway for adult height, the NFAT-dependent transcription pathway for rheumatoid arthritis, brain-related genes for coronary artery disease, and liver-related genes for late-onset Alzheimer’s disease. A key feature of our method is that inferred enrichments automatically help identify new trait-associated genes. For example, accounting for enrichment in lipid transport genes yields strong evidence for association between MTTP and low-density lipoprotein levels, whereas conventional analyses of the same data found no significant variants near this gene.

Identification of six novel susceptibility loci for dyslipidemia by longitudinal exome-wide association studies in Japanese

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
M Oguri ◽  
K Kato ◽  
H Horibe ◽  
T Fujimaki ◽  
J Sakuma ◽  
...  
Keyword(s):  
Serum Lipid ◽  
Ldl Cholesterol ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Hdl Cholesterol ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Susceptibility Loci ◽  
Cross Sectional ◽  
Genome Wide

Abstract Background The circulating concentrations of triglycerides, high density lipoprotein (HDL)-cholesterol, and low density lipoprotein (LDL)-cholesterol have a substantial genetic component. Although previous genome-wide association studies identified various genes and loci related to plasma lipid levels, those studies were conducted in a cross-sectional manner. Purpose The purpose of the study was to identify genetic variants that confer susceptibility to hypertriglyceridemia, hypo-HDL-cholesterolemia, and hyper-LDL-cholesterolemia in Japanese. We have now performed longitudinal exome-wide association studies (EWASs) to identify novel loci for dyslipidemia by examining temporal changes in serum lipid profiles. Methods Longitudinal EWASs (mean follow-up period, 5 years) for hypertriglyceridemia (2056 case, 3966 controls), hypo-HDL-cholesterolemia (698 cases, 5324 controls), and hyper-LDL-cholesterolemia (2769 cases, 3251 controls) were performed with Illumina Human Exome arrays. The relation of genotypes of 24,691 single nucleotide polymorphisms (SNPs) that passed quality control to dyslipidemia-related traits was examined with the generalized estimating equation (GEE). To compensate for multiple comparisons of genotypes with each of the three conditions, we applied Bonferroni's correction for statistical significance of association. Replication studies with cross-sectional data were performed for hypertriglyceridemia (2685 cases, 4703 controls), hypo-HDL-cholesterolemia (1947 cases, 6146 controls), and hyper-LDL-cholesterolemia (1719 cases, 5833 controls). Results Longitudinal EWASs revealed that 30 SNPs were significantly (P<2.03 × 10–6 by GEE) associated with hypertriglyceridemia, 46 SNPs with hypo-HDL-cholesterolemia, and 25 SNPs with hyper-LDL-cholesterolemia. After examination of the relation of identified SNPs to serum lipid profiles, linkage disequilibrium, and results of the previous genome-wide association studies, we newly identified rs74416240 of TCHP, rs925368 of GIT2, rs7969300 of ATXN2, and rs12231744 of NAA25 as a susceptibility loci for hypo-HDL-cholesterolemia; and rs34902660 of SLC17A3 and rs1042127 of CDSN for hyper-LDL-cholesterolemia. These SNPs were not in linkage disequilibrium with those previously reported to be associated with dyslipidemia, indicating independent effects of the SNPs identified in the present study on serum concentrations of HDL-cholesterol or LDL-cholesterol in Japanese. According to allele frequency data from the 1000 Genomes project database, five of the six identified SNPs were monomorphic or rare variants in European populations. In the replication study, all six SNPs were associated with dyslipidemia-related phenotypes. Conclusion We have thus identified six novel loci that confer susceptibility to hypo-HDL-cholesterolemia or hyper-LDL-cholesterolemia. Determination of genotypes for these SNPs at these loci may prove informative for assessment of the genetic risk for dyslipidemia in Japanese. Funding Acknowledgement Type of funding source: None

scholarly journals Cigarette smoking and personality: interrogating causality using Mendelian randomisation

2018 ◽  
Vol 49 (13) ◽  
pp. 2197-2205 ◽  
Author(s):  
Hannah M. Sallis ◽  
George Davey Smith ◽  
Marcus R. Munafò
Keyword(s):  
Personality Traits ◽  
Association Studies ◽  
Smoking Initiation ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Individual Level ◽  
Causal Pathways ◽  
Genome Wide ◽  
Level Data ◽  
Causal Nature

AbstractBackgroundDespite the well-documented association between smoking and personality traits such as neuroticism and extraversion, little is known about the potential causal nature of these findings. If it were possible to unpick the association between personality and smoking, it may be possible to develop tailored smoking interventions that could lead to both improved uptake and efficacy.MethodsRecent genome-wide association studies (GWAS) have identified variants robustly associated with both smoking phenotypes and personality traits. Here we use publicly available GWAS summary statistics in addition to individual-level data from UK Biobank to investigate the link between smoking and personality. We first estimate genetic overlap between traits using LD score regression and then use bidirectional Mendelian randomisation methods to unpick the nature of this relationship.ResultsWe found clear evidence of a modest genetic correlation between smoking behaviours and both neuroticism and extraversion. We found some evidence that personality traits are causally linked to certain smoking phenotypes: among current smokers each additional neuroticism risk allele was associated with smoking an additional 0.07 cigarettes per day (95% CI 0.02–0.12, p = 0.009), and each additional extraversion effect allele was associated with an elevated odds of smoking initiation (OR 1.015, 95% CI 1.01–1.02, p = 9.6 × 10−7).ConclusionWe found some evidence for specific causal pathways from personality to smoking phenotypes, and weaker evidence of an association from smoking initiation to personality. These findings could be used to inform future smoking interventions or to tailor existing schemes.

scholarly journals Evaluating the effects of alcohol and tobacco use on cardiovascular disease using multivariable Mendelian randomization

2019 ◽  
Author(s):  
Daniel B. Rosoff ◽  
George Davey Smith ◽  
Nehal Mehta ◽  
Toni-Kim Clarke ◽  
Falk W. Lohoff
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Alcohol Use ◽  
Tobacco Use ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Genome Wide Association Studies ◽  
Cvd Risk ◽  
Increased Risk

ABSTRACTAlcohol and tobacco use, two major modifiable risk factors for cardiovascular disease (CVD), are often consumed together. Using large publicly available genome-wide association studies (results from > 940,000 participants), we conducted two-sample multivariable Mendelian randomization (MR) to simultaneously assess the independent effects of alcohol and tobacco use on CVD risk factors and events. We found genetic instruments associated with increased alcohol use, controlling for tobacco use, associated with increased high-density-lipoprotein-cholesterol (HDL-C), decreased triglycerides, but not with coronary heart disease (CHD), myocardial infarction (MI), nor stroke; and instruments for increased tobacco use, controlling for alcohol use, associated with decreased HDL-C, increased triglycerides, and increased risk of CHD and MI. Exploratory analysis found associations with HDL-C, LDL-C, and intermediate-density-lipoprotein metabolites. Consistency of results across complementary methods accommodating different MR assumptions strengthened causal inference, providing strong genetic evidence for the causal effects of modifiable lifestyle risk factors on CVD risk.

scholarly journals CONVERGENT AGING LOCI: PATHWAYS THAT TRANSCEND INDIVIDUAL DISEASES

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S221-S221
Author(s):  
Luke C Pilling ◽  
Luigi Ferrucci ◽  
David Melzer
Keyword(s):  
Disease Risk ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Telomere Shortening ◽  
Chronic Disease Risk ◽  
Trade Offs ◽  
Age Related ◽  
Genome Wide ◽  
Artery Disease

Abstract Thousands of loci across the genome have been identified for specific diseases in genome-wide association studies (GWAS), yet very few are associated with lifespan itself. We hypothesized that specific biological pathways transcend individual diseases and affect health and lifespan more broadly. Using the published results for the most recent GWAS for 10 key age-related diseases (including coronary artery disease, type-2 diabetes, and several cancers) we identified 22 loci with a strong genetic association with at least three of the diseases. These multi-trait aging loci include known genes affecting multiple diverse health end points, such as CDKN2A/B (9p21.3) and APOE. There are also novel multi-trait genes including SH2B3 and CASC8, likely involved in hallmark pathways of aging biology, including telomere shortening and inflammation. Several of these loci involve trade-offs between chronic disease risk and cancer.

scholarly journals Critical Analysis of Genome-Wide Association Studies: Triple Negative Breast Cancer Quae Exempli Causa

2020 ◽  
Vol 21 (16) ◽  
pp. 5835
Author(s):  
Maria-Ancuta Jurj ◽  
Mihail Buse ◽  
Alina-Andreea Zimta ◽  
Angelo Paradiso ◽  
Schuyler S. Korban ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Genetic Risk ◽  
Triple Negative ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Breast Cancer Susceptibility ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genome Wide

Genome-wide association studies (GWAS) are useful in assessing and analyzing either differences or variations in DNA sequences across the human genome to detect genetic risk factors of diseases prevalent within a target population under study. The ultimate goal of GWAS is to predict either disease risk or disease progression by identifying genetic risk factors. These risk factors will define the biological basis of disease susceptibility for the purposes of developing innovative, preventative, and therapeutic strategies. As single nucleotide polymorphisms (SNPs) are often used in GWAS, their relevance for triple negative breast cancer (TNBC) will be assessed in this review. Furthermore, as there are different levels and patterns of linkage disequilibrium (LD) present within different human subpopulations, a plausible strategy to evaluate known SNPs associated with incidence of breast cancer in ethnically different patient cohorts will be presented and discussed. Additionally, a description of GWAS for TNBC will be presented, involving various identified SNPs correlated with miRNA sites to determine their efficacies on either prognosis or progression of TNBC in patients. Although GWAS have identified multiple common breast cancer susceptibility variants that individually would result in minor risks, it is their combined effects that would likely result in major risks. Thus, one approach to quantify synergistic effects of such common variants is to utilize polygenic risk scores. Therefore, studies utilizing predictive risk scores (PRSs) based on known breast cancer susceptibility SNPs will be evaluated. Such PRSs are potentially useful in improving stratification for screening, particularly when combining family history, other risk factors, and risk prediction models. In conclusion, although interpretation of the results from GWAS remains a challenge, the use of SNPs associated with TNBC may elucidate and better contextualize these studies.

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