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. 2020 Nov 12:13:4311-4322.
doi: 10.2147/DMSO.S281529. eCollection 2020.

Identification of Genetic Variants for Female Obesity and Evaluation of the Causal Role of Genetically Defined Obesity in Polycystic Ovarian Syndrome

Yeongseon Ahn  1 , Hyejin Lee  2 , Yoon Shin Cho  1
Affiliations

Identification of Genetic Variants for Female Obesity and Evaluation of the Causal Role of Genetically Defined Obesity in Polycystic Ovarian Syndrome

Yeongseon Ahn et al. Diabetes Metab Syndr Obes. .

Abstract

Purpose: Observational studies have demonstrated an increased risk of polycystic ovarian syndrome (PCOS) in obese women. This study aimed to identify genetic variants influencing obesity in females and to evaluate the causal association between genetically defined obesity and PCOS in Korean women.

Methods: Two-stage GWAS was conducted to identify genetic variants influencing obesity traits (such as body mass index [BMI], waist-hip ratio [WHR], and waist circumference [WC]) in Korean women. Two-sample Mendelian randomization (MR) analysis was employed to evaluate the causal effect of variants as genetic instruments for female obesity on PCOS.

Results: Meta-analysis of 9953 females combining discovery (N = 4658) and replication (N = 5295) stages detected four (rs11162584, rs6760543, rs828104, rs56137030), six (rs139702234, rs2341967, rs73059848, rs5020945, rs550532151, rs61971548), and two genetic variants (rs7722169, rs7206790) suggesting a highly significant association (P < 1×10-6) with BMI, WHR, and WC, respectively. Of these, an intron variant rs56137030 in FTO achieved genome-wide significant association (P = 3.39×10-8) with BMI in females. Using variants for female obesity, their effect on PCOS in 946 cases and 976 controls was evaluated by MR analysis. MR results indicated no significant association between genetically defined obesity and PCOS in Korean women.

Conclusion: This study, for the first time, revealed genetic variants for female obesity in the Korean population and reported no causal association between genetically defined obesity and PCOS in Korean women.

Keywords: Mendelian randomization; causal relation; female obesity; genome-wide association study; polycystic ovarian syndrome.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Regional association plots of rs56137030 (A), rs61971548 (B), and rs7722169 (C), showing the evidence of association in females for BMI, WHR, and WC, respectively. In the top panel of each, each SNP is plotted as a circle along the chromosomal position. Association analysis results represented as −log10P for SNPs (y-axis on left) are shown in a genomic region 400 kb to either side of the lead SNP (shown as a purple diamond). Recombination rates (cM/Mb) within loci are estimated from 1000 Genomes Phase 3 ASN and indicated as blue lines (y-axis on right). The magnitude of pair-wise linkage disequilibrium (LD) between the lead SNP and other SNPs is demonstrated by color, ranging from high (red) to low (blue). In the bottom panels, the locations of known genes are indicated in the region. Genomic positions are based on GRCh37/hg19.
Figure 2
Figure 2
Diagram displaying the components of the Mendelian randomization. Genetic variants as the instrumental variables are associated with biomarker (or exposure), but not with confounding factors as well as with outcome disease. Biomarker is a modifiable risk factor for outcome disease.
Figure 3
Figure 3
The results of the Mendelian randomization (MR) analyses between obesity traits (all (A), BMI (B), WHR (C), WC (D), or visceral fat (E)) and PCOS. The x-axis shows the genetic association with exposure (obesity traits). The y-axis shows the genetic association with outcome (PCOS).
See this image and copyright information in PMC

References

    1. Kyrou I, Randeva HS, Tsigos C, et al. Clinical problems caused by obesity Feingold KR, Anawalt B, Boyce A, editors. In Endotext [Internet]. South Dartmouth (MA): MDText. com, Inc.; 2000 - PubMed
    1. Yengo L, Sidorenko J, Kemper KE, et al. Meta-analysis of genome-wide association studies for height and body mass index in approximately 700000 individuals of European ancestry. Hum Mol Genet. 2018;27(20):3641–3649. doi: 10.1093/hmg/ddy271 - DOI - PMC - PubMed
    1. Akiyama M, Okada Y, Kanai M, et al. Genome-wide association study identifies 112 new loci for body mass index in the Japanese population. Nat Genet. 2017;49(10):1458–1467. doi: 10.1038/ng.3951 - DOI - PubMed
    1. Locke AE, Kahali B, Berndt SI, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518(7538):197–206. - PMC - PubMed
    1. Wen W, Cho YS, Zheng W, et al. Meta-analysis identifies common variants associated with body mass index in east Asians. Nat Genet. 2012;44(3):307–311. - PMC - PubMed