scholarly journals A genome-wide trans-ethnic interaction study links the PIGR-FCAMR locus to coronary atherosclerosis via interactions between genetic variants and residential exposure to traffic

PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0173880 ◽  
Author(s):  
Cavin K. Ward-Caviness ◽  
Lucas M. Neas ◽  
Colette Blach ◽  
Carol S. Haynes ◽  
Karen LaRocque-Abramson ◽  
...  
2015 ◽  
Vol 240 (2) ◽  
pp. 462-467 ◽  
Author(s):  
Chuanhui Dong ◽  
David Della-Morte ◽  
Ashley Beecham ◽  
Liyong Wang ◽  
Digna Cabral ◽  
...  

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 939-939
Author(s):  
Michael Francis ◽  
Changwei Li ◽  
Yitang Sun ◽  
Jingqi Zhou ◽  
Xiang Li ◽  
...  

Abstract Objectives To identify genetic variants that modify the effect of fish oil supplementation on blood lipids, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol, and triglycerides. Methods We performed a genome-wide interaction study in 73,962 participants of European ancestry from the UK Biobank. Candidate associations were evaluated in a replication study with 7,284 participants from the Atherosclerosis Risk in Communities (ARIC) Study. Meta-analysis was further performed across the two cohorts. Results Four novel interaction loci were identified at genome-wide significance in meta-analysis. The lead variant in the GJB6-GJB2-GJA3 gene cluster, rs112803755 (A > G; minor allele frequency = 0.041), shows an interaction effect but not the main effect, suggesting that it would not have been discovered in a typical association study. Fish oil supplementation is associated with a decreased blood level of triglycerides in individuals carrying the minor allele, but with an increased level in homozygotes of the major allele. This locus is significantly associated with higher GJB2 expression of connexin 26 in adipose tissue, while connexin activity is known to change upon exposure to omega-3 fatty acids. Significant interaction effects were also found in three other loci in the genes SLC12A3 (HDL-C), ABCA6 (LDL-C), and MLXIPL (LDL-C), but highly significant main effects are also present. Conclusions Our study identifies novel interaction effects for four genetic loci and highlights genetic variants in the GJB6-GJB2-GJA3 gene cluster, which modify the effects of fish oil supplementation on lowering blood triglycerides. These findings highlight the need and possibility for personalized nutrition. Funding Sources The University of Georgia Research Foundation


Author(s):  
Wan-Yu Lin

Abstract Background Biological age (BA) can be estimated by phenotypes and is useful for predicting lifespan and healthspan. Levine et al. proposed a PhenoAge and a BioAge to measure BA. Although there have been studies investigating the genetic predisposition to BA acceleration in Europeans, little has been known regarding this topic in Asians. Methods I here estimated PhenoAgeAccel (age-adjusted PhenoAge) and BioAgeAccel (age-adjusted BioAge) of 94,443 Taiwan Biobank (TWB) participants, wherein 25,460 TWB1 subjects formed a discovery cohort and 68,983 TWB2 individuals constructed a replication cohort. Lifestyle factors and genetic variants associated with PhenoAgeAccel and BioAgeAccel were investigated through regression analysis and a genome-wide association study (GWAS). Results A unit (kg/m 2) increase of BMI was associated with a 0.177-year PhenoAgeAccel (95% C.I. = 0.163~0.191, p = 6.0×) and 0.171-year BioAgeAccel (95% C.I. = 0.165~0.177, p = 0). Smokers on average had a 1.134-year PhenoAgeAccel (95% C.I. = 0.966~1.303, p = 1.3×) compared with non-smokers. Drinkers on average had a 0.640-year PhenoAgeAccel (95% C.I. = 0.433~0.847, p = 1.3×) and 0.193-year BioAgeAccel (95% C.I. = 0.107~0.279, p = 1.1×) relative to non-drinkers. A total of 11 and 4 single-nucleotide polymorphisms (SNPs) were associated with PhenoAgeAccel and BioAgeAccel (p<5× in both TWB1 and TWB2), respectively. Conclusions A PhenoAgeAccel-associated SNP (rs1260326 in GCKR) and two BioAgeAccel-associated SNPs (rs7412 in APOE; rs16998073 near FGF5) were consistent with the finding from the UK Biobank. The lifestyle analysis shows that prevention from obesity, cigarette smoking, and alcohol consumption is associated with a slower rate of biological aging.


2020 ◽  
Vol 105 (12) ◽  
pp. 3854-3864
Author(s):  
Jin-Fang Chai ◽  
Shih-Ling Kao ◽  
Chaolong Wang ◽  
Victor Jun-Yu Lim ◽  
Ing Wei Khor ◽  
...  

Abstract Context Glycated hemoglobin A1c (HbA1c) level is used to screen and diagnose diabetes. Genetic determinants of HbA1c can vary across populations and many of the genetic variants influencing HbA1c level were specific to populations. Objective To discover genetic variants associated with HbA1c level in nondiabetic Malay individuals. Design and Participants We conducted a genome-wide association study (GWAS) analysis for HbA1c using 2 Malay studies, the Singapore Malay Eye Study (SiMES, N = 1721 on GWAS array) and the Living Biobank study (N = 983 on GWAS array and whole-exome sequenced). We built a Malay-specific reference panel to impute ethnic-specific variants and validate the associations with HbA1c at ethnic-specific variants. Results Meta-analysis of the 1000 Genomes imputed array data identified 4 loci at genome-wide significance (P < 5 × 10-8). Of the 4 loci, 3 (ADAM15, LINC02226, JUP) were novel for HbA1c associations. At the previously reported HbA1c locus ATXN7L3-G6PC3, association analysis using the exome data fine-mapped the HbA1c associations to a 27-bp deletion (rs769664228) at SLC4A1 that reduced HbA1c by 0.38 ± 0.06% (P = 3.5 × 10-10). Further imputation of this variant in SiMES confirmed the association with HbA1c at SLC4A1. We also showed that these genetic variants influence HbA1c level independent of glucose level. Conclusion We identified a deletion at SLC4A1 associated with HbA1c in Malay. The nonglycemic lowering of HbA1c at rs769664228 might cause individuals carrying this variant to be underdiagnosed for diabetes or prediabetes when HbA1c is used as the only diagnostic test for diabetes.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Boram Park ◽  
Jaehoon An ◽  
Wonji Kim ◽  
Hae Yeon Kang ◽  
Sang Baek Koh ◽  
...  

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