1.Identification and Potential Clinical Utility of Common Genetic Variants in Gestational Diabetes among Chinese Pregnant Women
Claudia Ha-ting TAM ; Ying WANG ; Chi Chiu WANG ; Lai Yuk YUEN ; Cadmon King-poo LIM ; Junhong LENG ; Ling WU ; Alex Chi-wai NG ; Yong HOU ; Kit Ying TSOI ; Hui WANG ; Risa OZAKI ; Albert Martin LI ; Qingqing WANG ; Juliana Chung-ngor CHAN ; Yan Chou YE ; Wing Hung TAM ; Xilin YANG ; Ronald Ching-wan MA
Diabetes & Metabolism Journal 2025;49(1):128-143
Background:
The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications.
Methods:
We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants.
Results:
Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals.
Conclusion
Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.
2.Identification and Potential Clinical Utility of Common Genetic Variants in Gestational Diabetes among Chinese Pregnant Women
Claudia Ha-ting TAM ; Ying WANG ; Chi Chiu WANG ; Lai Yuk YUEN ; Cadmon King-poo LIM ; Junhong LENG ; Ling WU ; Alex Chi-wai NG ; Yong HOU ; Kit Ying TSOI ; Hui WANG ; Risa OZAKI ; Albert Martin LI ; Qingqing WANG ; Juliana Chung-ngor CHAN ; Yan Chou YE ; Wing Hung TAM ; Xilin YANG ; Ronald Ching-wan MA
Diabetes & Metabolism Journal 2025;49(1):128-143
Background:
The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications.
Methods:
We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants.
Results:
Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals.
Conclusion
Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.
3.Identification and Potential Clinical Utility of Common Genetic Variants in Gestational Diabetes among Chinese Pregnant Women
Claudia Ha-ting TAM ; Ying WANG ; Chi Chiu WANG ; Lai Yuk YUEN ; Cadmon King-poo LIM ; Junhong LENG ; Ling WU ; Alex Chi-wai NG ; Yong HOU ; Kit Ying TSOI ; Hui WANG ; Risa OZAKI ; Albert Martin LI ; Qingqing WANG ; Juliana Chung-ngor CHAN ; Yan Chou YE ; Wing Hung TAM ; Xilin YANG ; Ronald Ching-wan MA
Diabetes & Metabolism Journal 2025;49(1):128-143
Background:
The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications.
Methods:
We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants.
Results:
Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals.
Conclusion
Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.
4.Identification and Potential Clinical Utility of Common Genetic Variants in Gestational Diabetes among Chinese Pregnant Women
Claudia Ha-ting TAM ; Ying WANG ; Chi Chiu WANG ; Lai Yuk YUEN ; Cadmon King-poo LIM ; Junhong LENG ; Ling WU ; Alex Chi-wai NG ; Yong HOU ; Kit Ying TSOI ; Hui WANG ; Risa OZAKI ; Albert Martin LI ; Qingqing WANG ; Juliana Chung-ngor CHAN ; Yan Chou YE ; Wing Hung TAM ; Xilin YANG ; Ronald Ching-wan MA
Diabetes & Metabolism Journal 2025;49(1):128-143
Background:
The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications.
Methods:
We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants.
Results:
Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals.
Conclusion
Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.
5.Multiparametric magnetic resonance imaging/transrectal ultrasound fusion prostate biopsy with semi-robotic navigation in the Chinese population: initial results.
Wai Kit MA ; Brian Sh HO ; Andrew Sh LAI ; Ka Cheong LAM ; Yun Sang CHAN ; Lawrance Kc YIP ; Ada Tl NG ; James Hl TSU ; Ming Kwong YIU
Asian Journal of Andrology 2018;20(1):93-94
6.Prostate health index can stratify patients with Prostate Imaging Reporting and Data System score 3 lesions on magnetic resonance imaging to reduce prostate biopsies.
John Shung-Lai LEUNG ; Wai-Kit MA ; Brian Sze-Ho HO ; Stacia Tsun-Tsun CHUN ; Rong NA ; Yongle ZHAN ; Chi-Yuen NG ; Chi-Ho IP ; Ada Tsui-Lin NG ; Yiu-Chung LAM
Asian Journal of Andrology 2023;26(1):20-24
We aim to evaluate prostate health index as an additional risk-stratification tool in patients with Prostate Imaging Reporting and Data System score 3 lesions on multiparametric magnetic resonance imaging. Men with biochemical or clinical suspicion of having prostate cancer who underwent multiparametric magnetic resonance imaging in two tertiary centers (Queen Mary Hospital and Princess Margaret Hospital, Hong Kong, China) between January 2017 and June 2022 were included. Ultrasound-magnetic resonance imaging fusion biopsies were performed after prostate health index testing. Those who only had Prostate Imaging Reporting and Data System score 3 lesions were further stratified into four prostate health index risk groups and the cancer detection rates were analyzed. Out of the 747 patients, 47.3% had Prostate Imaging Reporting and Data System score 3 lesions only. The detection rate of clinically significant prostate cancer in this group was 15.0%. The cancer detection rates of clinically significant prostate cancer had statistically significant differences: 5.3% in prostate health index <25.0, 7.4% in prostate health index 25.0-34.9, 17.9% in prostate health index 35.0-54.9, and 52.6% in prostate health index ≥55.0 (P < 0.01). Among the patients, 26.9% could have avoided a biopsy with a prostate health index <25.0, at the expense of a 5.3% risk of missing clinically significant prostate cancer. Prostate health index could be used as an additional risk stratification tool for patients with Prostate Imaging Reporting and Data System score 3 lesions. Biopsies could be avoided in patients with low prostate health index, with a small risk of missing clinically significant prostate cancer.