scholarly journals Identification of Genetic Loci Simultaneously Associated with Multiple Cardiometabolic Traits

2021 ◽  
Author(s):  
Alexis C. Wood ◽  
Amit Arora ◽  
Michelle Newell ◽  
Victoria L. Bland ◽  
Jin Zhou ◽  
...  
Keyword(s):  
Association Studies ◽  
Density Lipoprotein ◽  
Independent Set ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Full Spectrum ◽  
Genome Wide ◽  
Cardiometabolic Disorders ◽  
The Uk ◽  
Meta Analyses

Background and Aims: Cardiometabolic disorders (CMD) arise from a constellation of features such as increased adiposity, hyperlipidemia, hypertension and compromised glucose control. Many genetic loci have shown associations with individual CMD-related traits, but no investigations have focused on simultaneously identifying loci showing associations across all domains. We therefore sought to identify loci associated with risk across seven continuous CMD-related traits. Methods and Results: We conducted separate genome-wide association studies (GWAS) for systolic and diastolic blood pressure (SBP/DBP), hemoglobin A1c (HbA1c), low- and high- density lipoprotein cholesterol (LDL-C/HDL-C), waist-to-hip-ratio (WHR), and triglycerides (TGs) in the UK Biobank (N= 356,574-456,823). Multiple loci reached genome-wide levels of significance (N=145-333) for each trait, but only four loci (in/near VEGFA, GRB14-COBLL1, KLF14, and RGS19-OPRL1) were associated with risk across all seven traits (P<5×10-8). We sought replication of these four loci in an independent set of seven trait-specific GWAS meta-analyses. GRB14-COBLL1 showed the most consistent replication, revealing nominally significant associations (p<0.05) with all traits except DBP. Conclusions: Our analyses suggest that very few loci are associated in the same direction of risk with traits representing the full spectrum of CMD features. We identified four such loci, and an understanding of the pathways between these loci and CMD risk may eventually identify factors that can be used to identify pathologic disturbances that represent broadly beneficial therapeutic targets.

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 Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Daniel L. McCartney ◽  
Josine L. Min ◽  
Rebecca C. Richmond ◽  
Ake T. Lu ◽  
Maria K. Sobczyk ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Biological Aging ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Biomarkers Of Aging ◽  
Genome Wide ◽  
Shared Genetic

Abstract Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

scholarly journals The Genetic Basis of Hypertriglyceridemia

2021 ◽  
Vol 23 (8) ◽  
Author(s):  
Germán D. Carrasquilla ◽  
Malene Revsbech Christiansen ◽  
Tuomas O. Kilpeläinen
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Cumulative Effect ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Risk Variants ◽  
Genome Wide ◽  
Severe Hypertriglyceridemia ◽  
Increased Risk ◽  
Polygenic Scores

Abstract Purpose of Review Hypertriglyceridemia is a common dyslipidemia associated with an increased risk of cardiovascular disease and pancreatitis. Severe hypertriglyceridemia may sometimes be a monogenic condition. However, in the vast majority of patients, hypertriglyceridemia is due to the cumulative effect of multiple genetic risk variants along with lifestyle factors, medications, and disease conditions that elevate triglyceride levels. In this review, we will summarize recent progress in the understanding of the genetic basis of hypertriglyceridemia. Recent Findings More than 300 genetic loci have been identified for association with triglyceride levels in large genome-wide association studies. Studies combining the loci into polygenic scores have demonstrated that some hypertriglyceridemia phenotypes previously attributed to monogenic inheritance have a polygenic basis. The new genetic discoveries have opened avenues for the development of more effective triglyceride-lowering treatments and raised interest towards genetic screening and tailored treatments against hypertriglyceridemia. Summary The discovery of multiple genetic loci associated with elevated triglyceride levels has led to improved understanding of the genetic basis of hypertriglyceridemia and opened new translational opportunities.

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&lt;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

26-OR: Meta-analyses of Genome-Wide Association Studies for Proinsulin Provide Insight into Glycemic Trait Dysregulation

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 26-OR
Author(s):  
K. ALAINE BROADAWAY ◽  
XIANYONOG YIN ◽  
ALICE WILLIAMSON ◽  
EMMA WILSON ◽  
MAGIC INVESTIGATORS
Keyword(s):  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Meta Analyses ◽  
Insight Into

scholarly journals Reproducibility in the UK Biobank of Genome-Wide Significant Signals Discovered in Earlier Genome-wide Association Studies

2020 ◽  
Author(s):  
Jack W. O’Sullivan ◽  
John P. A. Ioannidis
Keyword(s):  
Effect Size ◽  
Association Studies ◽  
Genome Wide Association ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Single Nucleotide ◽  
Genome Wide ◽  
The Uk ◽  
Open Question

AbstractWith the establishment of large biobanks, discovery of single nucleotide polymorphism (SNPs) that are associated with various phenotypes has been accelerated. An open question is whether SNPs identified with genome-wide significance in earlier genome-wide association studies (GWAS) are replicated also in later GWAS conducted in biobanks. To address this question, the authors examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, replication GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNPs (of which 6,289 had reached p<5e-8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0% and it was lower for binary than for quantitative phenotypes (58.1% versus 94.8% respectively). There was a18.0% decrease in SNP effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNP effect size, phenotype trait (binary or quantitative), and discovery p-value, we built and validated a model that predicted SNP replication with area under the Receiver Operator Curve = 0.90. While non-replication may often reflect lack of power rather than genuine false-positive findings, these results provide insights about which discovered associations are likely to be seen again across subsequent GWAS.

scholarly journals Genetic overlap between idiopathic pulmonary fibrosis and COVID−19

2021 ◽  
Author(s):  
Richard J Allen ◽  
Beatriz Guillen-Guio ◽  
Emma Croot ◽  
Luke M Kraven ◽  
Samuel Moss ◽  
...  
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Biological Processes ◽  
Genetic Loci ◽  
Genome Wide ◽  
Genetic Overlap ◽  
Causal Variants ◽  
Shared Genetic

AbstractGenome-wide association studies (GWAS) of coronavirus disease 2019 (COVID-19) and idiopathic pulmonary fibrosis (IPF) have identified genetic loci associated with both traits, suggesting possible shared biological mechanisms. Using updated GWAS of COVID-19 and IPF, we evaluated the genetic overlap between these two diseases and identified four genetic loci (including one novel) with likely shared causal variants between severe COVID-19 and IPF. Although there was a positive genetic correlation between COVID-19 and IPF, two of these four shared genetic loci had an opposite direction of effect. IPF-associated genetic variants related to telomere dysfunction and spindle assembly showed no association with COVID-19 phenotypes. Together, these results suggest there are both shared and distinct biological processes driving IPF and severe COVID-19 phenotypes.

Abstract P260: Large-scale Meta-analysis of Diverse Ancestry Genome-wide Association Studies to Identify Pharmacogenomic Interactions of Sulfonylureas and ECG Phenotypes

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
James S Floyd ◽  
Colleen Sitlani ◽  
Christy L Avery ◽  
Eric A Whitsel ◽  
Leslie Lange ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Qt Interval ◽  
Association Studies ◽  
Meta Analysis ◽  
Small Sample ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Meta Analyses

Introduction: Sulfonylureas are a commonly-used class of diabetes medication that can prolong the QT-interval, which is a leading cause of drug withdrawals from the market given the possible risk of life-threatening arrhythmias. Previously, we conducted a meta-analysis of genome-wide association studies of sulfonylurea-genetic interactions on QT interval among 9 European-ancestry (EA) cohorts using cross-sectional data, with null results. To improve our power to identify novel drug-gene interactions, we have included repeated measures of medication use and QT interval and expanded our study to include several additional cohorts, including African-American (AA) and Hispanic-ancestry (HA) cohorts with a high prevalence of sulfonylurea use. To identify potentially differential effects on cardiac depolarization and repolarization, we have also added two phenotypes - the JT and QRS intervals, which together comprise the QT interval. Hypothesis: The use of repeated measures and expansion of our meta-analysis to include diverse ancestry populations will allow us to identify novel pharmacogenomic interactions for sulfonylureas on the ECG phenotypes QT, JT, and QRS. Methods: Cohorts with unrelated individuals used generalized estimating equations to estimate interactions; cohorts with related individuals used mixed effect models clustered on family. For each ECG phenotype (QT, JT, QRS), we conducted ancestry-specific (EA, AA, HA) inverse variance weighted meta-analyses using standard errors based on the t-distribution to correct for small sample inflation in the test statistic. Ancestry-specific summary estimates were combined using MANTRA, an analytic method that accounts for differences in local linkage disequilibrium between ethnic groups. Results: Our study included 65,997 participants from 21 cohorts, including 4,020 (6%) sulfonylurea users, a substantial increase from the 26,986 participants and 846 sulfonylureas users in the previous meta-analysis. Preliminary ancestry-specific meta-analyses have identified genome-wide significant associations (P < 5х10–8) for each ECG phenotype, and analyses with MANTRA are in progress. Conclusions: In the setting of the largest collection of pharmacogenomic studies to date, we used repeated measurements and leveraged diverse ancestry populations to identify new pharmacogenomic loci for ECG traits associated with cardiovascular risk.

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