scholarly journals Fine-mapping of an expanded set of type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps

2018 ◽  
Author(s):  
Anubha Mahajan ◽  
Daniel Taliun ◽  
Matthias Thurner ◽  
Neil R Robertson ◽  
Jason M Torres ◽  
...  
Keyword(s):  
Sample Size ◽  
Fine Mapping ◽  
Low Frequency ◽  
High Density ◽  
Regulatory Sequence ◽  
Polygenic Risk Score ◽  
Risk Alleles ◽  
Genome Wide ◽  
Credible Set ◽  
Size Heterogeneity

We aggregated genome-wide genotyping data from 32 European-descent GWAS (74,124 T2D cases, 824,006 controls) imputed to high-density reference panels of >30,000 sequenced haplotypes. Analysis of ˜27M variants (˜21M with minor allele frequency [MAF]<5%), identified 243 genome-wide significant loci (p<5×10−8; MAF 0.02%-50%; odds ratio [OR] 1.04-8.05), 135 not previously-implicated in T2D-predisposition. Conditional analyses revealed 160 additional distinct association signals (p<10−5) within the identified loci. The combined set of 403 T2D-risk signals includes 56 low-frequency (0.5%≤MAF<5%) and 24 rare (MAF<0.5%) index SNPs at 60 loci, including 14 with estimated allelic OR>2. Forty-one of the signals displayed effect-size heterogeneity between BMI-unadjusted and adjusted analyses. Increased sample size and improved imputation led to substantially more precise localisation of causal variants than previously attained: at 51 signals, the lead variant after fine-mapping accounted for >80% posterior probability of association (PPA) and at 18 of these, PPA exceeded 99%. Integration with islet regulatory annotations enriched for T2D association further reduced median credible set size (from 42 variants to 32) and extended the number of index variants with PPA>80% to 73. Although most signals mapped to regulatory sequence, we identified 18 genes as human validated therapeutic targets through coding variants that are causal for disease. Genome wide chip heritability accounted for 18% of T2D-risk, and individuals in the 2.5% extremes of a polygenic risk score generated from the GWAS data differed >9-fold in risk. Our observations highlight how increases in sample size and variant diversity deliver enhanced discovery and single-variant resolution of causal T2D-risk alleles, and the consequent impact on mechanistic insights and clinical translation.

scholarly journals Trans-ancestry genome-wide association study identifies novel genetic mechanisms in rheumatoid arthritis

2021 ◽  
Author(s):  
Kazuyoshi Ishigaki ◽  
Saori Sakaue ◽  
Chikashi Terao ◽  
Yang Luo ◽  
Kyuto Sonehara ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Association Study ◽  
Fine Mapping ◽  
Large Scale ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Genetic Research ◽  
Genome Wide Association ◽  
Polygenic Risk Score ◽  
Genome Wide

AbstractTrans-ancestry genetic research promises to improve power to detect genetic signals, fine-mapping resolution, and performances of polygenic risk score (PRS). We here present a large-scale genome-wide association study (GWAS) of rheumatoid arthritis (RA) which includes 276,020 samples of five ancestral groups. We conducted a trans-ancestry meta-analysis and identified 124 loci (P < 5 × 10-8), of which 34 were novel. Candidate genes at the novel loci suggested essential roles of the immune system (e.g., TNIP2 and TNFRSF11A) and joint tissues (e.g., WISP1) in RA etiology. Trans-ancestry fine mapping identified putatively causal variants with biological insights (e.g., LEF1). Moreover, PRS based on trans-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between European and East Asian populations. Our study provides multiple insights into the etiology of RA and improves genetic predictability of RA.

scholarly journals Validation and Disease Risk Assessment of Previously Reported Genome-Wide Genetic Variants Associated With Brugada Syndrome

2020 ◽  
Vol 13 (4) ◽  
Author(s):  
Jyh-Ming Jimmy Juang ◽  
Yen-Bin Liu ◽  
Ching-Yu Julius Chen ◽  
Qi-You Yu ◽  
Amrita Chattopadhyay ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Risk Score ◽  
Brugada Syndrome ◽  
Odds Ratio ◽  
Disease Risk ◽  
Sudden Cardiac Arrest ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Risk Alleles ◽  
Genome Wide

Background: Brugada syndrome (BrS) is an oligogenic arrhythmic disease with increased risk of sudden cardiac arrest. Several BrS or ECG traits-related single-nucleotide polymorphisms (SNPs) were identified through previous genome-wide association studies in white patients. We aimed to validate these SNPs in BrS patients in the Taiwanese population, assessing the cumulative effect of risk alleles and the BrS-polygenic risk score in predicting cardiac events. Methods: We genotyped 190 unrelated BrS patients using the TWB Array, and Taiwan Biobank was used as controls. SNPs not included in the array were imputed by IMPUTE2. Cox proportional hazards model was used to evaluate the associations between each particular SNP, the collective BrS-polygenic risk score, and clinical outcomes. Results: Of the 88 previously reported SNPs, 22 were validated in Taiwanese BrS patients ( P <0.05). Of the 22 SNPs, 2 (rs10428132 and rs9388451) were linked with susceptibility to BrS, 10 were SNPs previously reaching genome-wide significance, and 10 were SNPs associated with ECG traits. For the 3 most commonly reported SNPs, disease risk increased consistently with the number of risk alleles (odds ratio, 3.54; P trend =1.38×10 −9 for 5 risk alleles versus 1). Similar patterns were observed in both SCN5A mutation+ (odds ratio, 3.66; P trend =0.049) and SCN5A mutation− (odds ratio, 3.75; P trend =8.54×10 −9 ) subgroups. Furthermore, BrS patients without SCN5A mutations had more risk alleles than BrS patients with SCN5A mutations regardless of the range of polygenic risk scores. Three SNPs (rs4687718, rs7784776, and rs2968863) showed significant associations with the composite outcome (sudden cardiac arrest plus syncope, hazard ratio, 2.13, 1.48, and 0.41; P =0.02, 0.006, and 0.008, respectively). Conclusions: Our findings suggested that some SNPs associated with BrS or ECG traits exist across multiple populations. The cumulative risk of the BrS-related SNPs is similar to that in white BrS patients, but it appears to correlate with the absence of SCN5A mutations.

scholarly journals Fine mapping of genome-wide association study signals to identify genetic markers of the plasma triglyceride response to an omega-3 fatty acid supplementation

2019 ◽  
Vol 109 (1) ◽  
pp. 176-185 ◽  
Author(s):  
Bastien Vallée Marcotte ◽  
Frédéric Guénard ◽  
Simone Lemieux ◽  
Patrick Couture ◽  
Iwona Rudkowska ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Association Study ◽  
Fine Mapping ◽  
Genome Wide Association Study ◽  
Plasma Triglyceride ◽  
Genome Wide Association ◽  
Omega 3 ◽  
Risk Alleles ◽  
Response Variance ◽  
Genome Wide

ABSTRACT Background Using a genome-wide association study (GWAS) approach, our group previously computed a genetic risk score (GRS) from single nucleotide polymorphisms (SNPs) of 10 loci that affect the plasma triglyceride (TG) response to an omega-3 (n–3) fatty acid (FA) supplementation. Objectives The objective was to compute a novel and more refined GRS using fine mapping to include a large number of genetic variants. Methods A total of 208 participants of the Fatty Acid Sensor (FAS) Study received 5 g fish oil/d, containing 1.9–2.2 g eicosapentaenoic acid and 1.1 g docosahexanoic acid, for 6 wk. Plasma TG concentrations were measured before and after supplementation. Dense genotyping and genotype imputation were used to refine mapping around GWAS hits. A GRS was computed by summing the number of at-risk alleles of tagging SNPs. Analyses were replicated in samples of the FINGEN study. Results A total of 31 tagging SNPs associated with the TG response were used for GRS calculation in the FAS study. In a general linear model adjusted for age, sex, and body mass index, the GRS explained 49.73% of TG response variance (P < 0.0001). Nonresponders to the n–3 FA supplementation had a higher GRS than did responders. In the FINGEN replication study, the GRS explained 3.67% of TG response variance (P = 0.0006). Conclusions Fine mapping proved to be effective to refine the previous GRS. Carrying increasing numbers of at-risk alleles of 31 SNPs confers a higher risk of being nonresponsive to n–3 FAs. The genetic profile therefore appears to be an important determinant of the plasma TG response to an n–3 FA supplementation and could be used to target those most likely to gain clinical benefit. This trial was registered at http://www.clinicaltrials.gov as NCT01343342.

P6017 A high density genome-wide scan for genetic risk factors of insect bite hypersensitivity (IBH): A Horsegene Project Initiative

2016 ◽  
Vol 94 (suppl_4) ◽  
pp. 156-157
Author(s):  
B. D. Velie ◽  
M. Shrestha ◽  
L. Francois ◽  
A. Schurink ◽  
A. Stinckens ◽  
...  
Keyword(s):  
Risk Factors ◽  
Genetic Risk ◽  
Genetic Risk Factors ◽  
High Density ◽  
Genome Wide ◽  
Insect Bite Hypersensitivity ◽  
Genome Wide Scan

scholarly journals Genetic analysis of amyotrophic lateral sclerosis identifies contributing pathways and cell types

2021 ◽  
Vol 7 (3) ◽  
pp. eabd9036
Author(s):  
Sara Saez-Atienzar ◽  
Sara Bandres-Ciga ◽  
Rebekah G. Langston ◽  
Jonggeol J. Kim ◽  
Shing Wan Choi ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Membrane Trafficking ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Polygenic Risk Score ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Data Driven Approach ◽  
Single Nucleus ◽  
Lateral Sclerosis

Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely, neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated six differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, MAPKAPK3, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

scholarly journals Genomic prediction for growth using a low-density SNP panel in dromedary camels

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Morteza Bitaraf Sani ◽  
Javad Zare Harofte ◽  
Mohammad Hossein Banabazi ◽  
Saeid Esmaeilkhanian ◽  
Ali Shafei Naderi ◽  
...  
Keyword(s):  
Body Weight ◽  
Birth Weight ◽  
Sample Size ◽  
Genetic Improvement ◽  
Growth Traits ◽  
P Value ◽  
Dromedary Camels ◽  
Genome Wide ◽  
A Genome ◽  
Daily Gain

AbstractFor thousands of years, camels have produced meat, milk, and fiber in harsh desert conditions. For a sustainable development to provide protein resources from desert areas, it is necessary to pay attention to genetic improvement in camel breeding. By using genotyping-by-sequencing (GBS) method we produced over 14,500 genome wide markers to conduct a genome- wide association study (GWAS) for investigating the birth weight, daily gain, and body weight of 96 dromedaries in the Iranian central desert. A total of 99 SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.002). Genomic breeding values (GEBVs) were estimated with the BGLR package using (i) all 14,522 SNPs and (ii) the 99 SNPs by GWAS. Twenty-eight SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.001). Annotation of the genomic region (s) within ± 100 kb of the associated SNPs facilitated prediction of 36 candidate genes. The accuracy of GEBVs was more than 0.65 based on all 14,522 SNPs, but the regression coefficients for birth weight, daily gain, and body weight were 0.39, 0.20, and 0.23, respectively. Because of low sample size, the GEBVs were predicted using the associated SNPs from GWAS. The accuracy of GEBVs based on the 99 associated SNPs was 0.62, 0.82, and 0.57 for birth weight, daily gain, and body weight. This report is the first GWAS using GBS on dromedary camels and identifies markers associated with growth traits that could help to plan breeding program to genetic improvement. Further researches using larger sample size and collaboration of the camel farmers and more profound understanding will permit verification of the associated SNPs identified in this project. The preliminary results of study show that genomic selection could be the appropriate way to genetic improvement of body weight in dromedary camels, which is challenging due to a long generation interval, seasonal reproduction, and lack of records and pedigrees.

scholarly journals Joint association between education and polygenic risk score for incident coronary heart disease events: a longitudinal population-based study of 26 203 men and women

2021 ◽  
pp. jech-2020-214358
Author(s):  
Pekka Martikainen ◽  
Kaarina Korhonen ◽  
Aline Jelenkovic ◽  
Hannu Lahtinen ◽  
Aki Havulinna ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Risk Score ◽  
Density Lipoprotein ◽  
Population Based ◽  
Polygenic Risk Score ◽  
Genome Wide ◽  
Increased Risk ◽  
Region Of Residence

BackgroundGenetic vulnerability to coronary heart disease (CHD) is well established, but little is known whether these effects are mediated or modified by equally well-established social determinants of CHD. We estimate the joint associations of the polygenetic risk score (PRS) for CHD and education on CHD events.MethodsThe data are from the 1992, 1997, 2002, 2007 and 2012 surveys of the population-based FINRISK Study including measures of social, behavioural and metabolic factors and genome-wide genotypes (N=26 203). Follow-up of fatal and non-fatal incident CHD events (N=2063) was based on nationwide registers.ResultsAllowing for age, sex, study year, region of residence, study batch and principal components, those in the highest quartile of PRS for CHD had strongly increased risk of CHD events compared with the lowest quartile (HR=2.26; 95% CI: 1.97 to 2.59); associations were also observed for low education (HR=1.58; 95% CI: 1.32 to 1.89). These effects were largely independent of each other. Adjustment for baseline smoking, alcohol use, body mass index, igh-density lipoprotein (HDL) and total cholesterol, blood pressure and diabetes attenuated the PRS associations by 10% and the education associations by 50%. We do not find strong evidence of interactions between PRS and education.ConclusionsPRS and education predict CHD events, and these associations are independent of each other. Both can improve CHD prediction beyond behavioural risks. The results imply that observational studies that do not have information on genetic risk factors for CHD do not provide confounded estimates for the association between education and CHD.

scholarly journals CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies

2019 ◽  
Author(s):  
Jianhua Wang ◽  
Dandan Huang ◽  
Yao Zhou ◽  
Hongcheng Yao ◽  
Huanhuan Liu ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Genetic Variants ◽  
Association Studies ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Genome Wide ◽  
Credible Sets ◽  
Causal Variants

Abstract Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.

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