Woo Young Lim1, Hyejin Lee2, Yoon Shin Cho3. 1. Department of Biomedical Science, Hallym University, Chuncheon, Gangwon-do, 24252, Republic of Korea. 2. Department of Internal Medicine, Ewha Womans University School of Medicine, Seoul, Republic of Korea. 3. Department of Biomedical Science, Hallym University, Chuncheon, Gangwon-do, 24252, Republic of Korea. yooncho33@hallym.ac.kr.
Abstract
BACKGROUND: Blood insulin level is an important risk factor for numerous disorders. Individual blood insulin level is known to be substantially influenced by genetic factors. Several genetic association studies identified a number of genetic variants for blood insulin level, but none of them was from a sex-stratified population. OBJECTIVE: This study aimed to identify male- and female-specific genetic variants related to blood insulin level and to evaluate the causal relationship between blood insulin level and polycystic ovary syndrome (PCOS) that is likely caused by high insulin in Korean women. METHODS: A genome-wide association study was conducted to identify genetic variants influencing blood insulin level in males (N = 4183) and females (N = 4659) in the Korean population. Two-sample Mendelian randomization (MR) analysis was used to investigate the causal effects of the insulin variants identified from GWAS on PCOS in Korean women. Genetic association data for PCOS were obtained from a PCOS study cohort (946 cases, 976 controls) in Ewha Womans University Hospital. RESULTS: GWAS linear regression analysis identified 13 female-specific SNPs and 13 male-specific SNPs showing suggestive associations (P < 10-5) with blood insulin level. The results from two-sample MR analysis using the GWAS variants for PCOS indicated that genetically determined insulin level was not associated with the risk of PCOS in Korean women. CONCLUSION: This study identified sex-specific genetic variants showing associations with insulin for the first time in East Asian populations. In addition, MR analysis using variants discovered from Korean women revealed that genetically determined high level of insulin is not the cause of PCOS.
BACKGROUND: Blood insulin level is an important risk factor for numerous disorders. Individual blood insulin level is known to be substantially influenced by genetic factors. Several genetic association studies identified a number of genetic variants for blood insulin level, but none of them was from a sex-stratified population. OBJECTIVE: This study aimed to identify male- and female-specific genetic variants related to blood insulin level and to evaluate the causal relationship between blood insulin level and polycystic ovary syndrome (PCOS) that is likely caused by high insulin in Korean women. METHODS: A genome-wide association study was conducted to identify genetic variants influencing blood insulin level in males (N = 4183) and females (N = 4659) in the Korean population. Two-sample Mendelian randomization (MR) analysis was used to investigate the causal effects of the insulin variants identified from GWAS on PCOS in Korean women. Genetic association data for PCOS were obtained from a PCOS study cohort (946 cases, 976 controls) in Ewha Womans University Hospital. RESULTS: GWAS linear regression analysis identified 13 female-specific SNPs and 13 male-specific SNPs showing suggestive associations (P < 10-5) with blood insulin level. The results from two-sample MR analysis using the GWAS variants for PCOS indicated that genetically determined insulin level was not associated with the risk of PCOS in Korean women. CONCLUSION: This study identified sex-specific genetic variants showing associations with insulin for the first time in East Asian populations. In addition, MR analysis using variants discovered from Korean women revealed that genetically determined high level of insulin is not the cause of PCOS.
Authors: Joselyn Rojas; Mervin Chávez; Luis Olivar; Milagros Rojas; Jessenia Morillo; José Mejías; María Calvo; Valmore Bermúdez Journal: Int J Reprod Med Date: 2014-01-28
Authors: Myungsuk Kim; Kye Won Park; Yeongseon Ahn; Eun Bi Lim; Soo Heon Kwak; Ahmad Randy; No Joon Song; Kyong Soo Park; Chu Won Nho; Yoon Shin Cho Journal: Front Genet Date: 2022-08-12 Impact factor: 4.772