TY - JOUR
T1 - Novel Genetic Risk and Metabolic Signatures of Insulin Signaling and Androgenesis in the Anovulation of Polycystic Ovary Syndrome
AU - Wu, Xiaoke
AU - Wang, Chi Chiu
AU - Cao, Yijuan
AU - Li, Jian
AU - Li, Zhiqiang
AU - Ma, Hongli
AU - Gao, Jingshu
AU - Chang, Hui
AU - Zhang, Duojia
AU - Cong, Jing
AU - Wang, Yu
AU - Wu, Qi
AU - Han, Xiaoxiao
AU - Chung, Pui Wah Jacqueline
AU - Li, Yiran
AU - Zheng, Xu
AU - Chen, Lingxi
AU - Zeng, Lin
AU - Borchert, Astrid
AU - Kuhn, Hartmut
AU - Chen, Zi Jiang
AU - Ng, Ernest Hung Yu
AU - Stener-Victorin, Elisabet
AU - Zhang, Heping
AU - Legro, Richard S.
AU - Mol, Ben Willem J.
AU - Shi, Yongyong
N1 - Funding Information:
The authors are grateful to all staff in the PCOSAct group for their effort in the collection of blood samples and clinical dataset which used in current study. Special thanks to Prof. Attila Toth from Institute of Physiological Chemistry, Dresden, Germany for the REC114 antibody. This study was supported by the National key Research and Development Program of China (2019YFC1709500); the National Collaboration Project of Critical Illness by Integrating Chinese Medicine and Western Medicine; the Project of Heilongjiang Province Innovation Team “TouYan;” the Yi-Xun Liu and Xiao-Ke Wu Academician Workstation; the Innovation Team of Reproductive Technique with Integrative Chinese Medicine and Western Medicine in Xuzhou City, China; Heilongjiang University of Chinese Medicine from the National Clinical Trial Base; Heilongjiang Provincial Clinical Research Center for Ovary Diseases; the Research Grant Council (T13-602/21-N, C5045-20EF, and 14122021); and Food and Health Bureau in Hong Kong, China (06171026). Ben Willem J. Mol is supported by a National Health and Medical Research Council (NHMRC) Investigator grant (GNT1176437). Ben Willem J. Mol reports consultancy for ObsEva and Merck and travel support from Merck. Xiaoke Wu, Yongyong Shi, and Chi Chiu Wang developed the research question and designed the study. Xiaoke Wu, Yongyong Shi, Yijuan Cao, and Chi Chiu Wang designed the analysis. Yongyong Shi and Zhiqiang Li contributed to the design of the experiment of whole-exome plus targeted SNP sequencing and the analysis, and interpreted the results. Jingshu Gao, Hui Chang, Duojia Zhang, Jing Cong, Yu Wang, Qi Wu, Xiaoxiao Han, Pui Wah Jacqueline Chung, Yiran Li, and Lin Zeng contributed to the experiment of metabolic profile and immunofluorescent staining and the analysis, and interpreted the results. Astrid Borchert and Hartmut Kuhn provided antibody support and advice. Xu Zheng and Lingxi Chen contributed to create the predictive model with deep machine learning. Jian Li, Qi Wu, Hongli Ma, Xu Zheng, and Lingxi Chen contributed to the analysis of the clinical characteristics and interpreted the results. Jian Li, Hongli Ma, Hui Chang, Jing Cong, and Chi Chiu Wang drafted the manuscript. All authors reviewed and revised the manuscript. Xiaoke Wu is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Xiaoke Wu, Chi Chiu Wang, Yijuan Cao, Jian Li, Zhiqiang Li, Hongli Ma, Jingshu Gao, Hui Chang, Duojia Zhang, Jing Cong, Yu Wang, Qi Wu, Xiaoxiao Han, Pui Wah Jacqueline Chung, Yiran Li, Xu Zheng, Lingxi Chen, Lin Zeng, Astrid Borchert, Hartmut Kuhn, Zijiang Chen, Ernest Hung Yu Ng, Elisabet Stener-Victorin, Heping Zhang, Richard S. Legro, Ben Willem J. Mol, and Yongyong Shi declare that they have no conflict of interest or financial conflicts to disclose.
Funding Information:
This study was supported by the National key Research and Development Program of China ( 2019YFC1709500 ); the National Collaboration Project of Critical Illness by Integrating Chinese Medicine and Western Medicine ; the Project of Heilongjiang Province Innovation Team “TouYan;” the Yi-Xun Liu and Xiao-Ke Wu Academician Workstation; the Innovation Team of Reproductive Technique with Integrative Chinese Medicine and Western Medicine in Xuzhou City , China; Heilongjiang University of Chinese Medicine from the National Clinical Trial Base ; Heilongjiang Provincial Clinical Research Center for Ovary Diseases ; the Research Grant Council ( T13-602/21-N , C5045-20EF , and 14122021 ); and Food and Health Bureau in Hong Kong, China ( 06171026 ).
Publisher Copyright:
© 2023
PY - 2023/4
Y1 - 2023/4
N2 - Ovulation induction is a first-line medical treatment for infertility in polycystic ovary syndrome (PCOS). Poor ovulation responses are assumed to be due to insulin resistance and hyperandrogenism. In a prospective cohort (PCOSAct) of 1000 infertile patients with PCOS, whole-exome plus targeted single-nucleotide polymorphism (SNP) sequencing and comprehensive metabolomic profiling were conducted. Significant genome-wide common variants and rare mutations associated with anovulation were identified, and a prediction model was built using machine learning. Common variants in zinc-finger protein 438 gene (ZNF438) indexed by rs2994652 (p = 2.47 × 10–8) and a rare functional mutation in REC114 (rs182542888, p = 5.79 × 10–6) were significantly associated with failure of ovulation induction. Women carrying the A allele of rs2994652 and REC114 p.Val101Leu (rs182542888) had lower ovulation (odds ratio (OR) = 1.96, 95% confidence interval (95%CI) = 1.55–2.49; OR = 11.52, 95%CI = 3.08–43.05, respectively) and prolonged time to ovulation (mean = 56.7 versus (vs) 49.0 days, p < 0.001; 78.1 vs 68.6 days, p = 0.014, respectively). L-phenylalanine was found to be increased and correlated with the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) index (r = 0.22, p = 0.050) and fasting glucose (r = 0.33, p = 0.003) for rs2994652, while arachidonic acid metabolism was found to be decreased and associated with increased anti-Müllerian hormone (AMH; r = –0.51, p = 0.01) and total testosterone (TT; r = –0.71, p = 0.02) for rs182542888. A combined model of genetic variants, metabolites, and clinical features increased the prediction of ovulation (area under the curve (AUC) = 76.7%). Common variants in ZNF438 and rare functional mutations in REC114, associated with phenylalanine and arachidonic acid metabolites, contributed to the failure of infertility treatment in women with PCOS.
AB - Ovulation induction is a first-line medical treatment for infertility in polycystic ovary syndrome (PCOS). Poor ovulation responses are assumed to be due to insulin resistance and hyperandrogenism. In a prospective cohort (PCOSAct) of 1000 infertile patients with PCOS, whole-exome plus targeted single-nucleotide polymorphism (SNP) sequencing and comprehensive metabolomic profiling were conducted. Significant genome-wide common variants and rare mutations associated with anovulation were identified, and a prediction model was built using machine learning. Common variants in zinc-finger protein 438 gene (ZNF438) indexed by rs2994652 (p = 2.47 × 10–8) and a rare functional mutation in REC114 (rs182542888, p = 5.79 × 10–6) were significantly associated with failure of ovulation induction. Women carrying the A allele of rs2994652 and REC114 p.Val101Leu (rs182542888) had lower ovulation (odds ratio (OR) = 1.96, 95% confidence interval (95%CI) = 1.55–2.49; OR = 11.52, 95%CI = 3.08–43.05, respectively) and prolonged time to ovulation (mean = 56.7 versus (vs) 49.0 days, p < 0.001; 78.1 vs 68.6 days, p = 0.014, respectively). L-phenylalanine was found to be increased and correlated with the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) index (r = 0.22, p = 0.050) and fasting glucose (r = 0.33, p = 0.003) for rs2994652, while arachidonic acid metabolism was found to be decreased and associated with increased anti-Müllerian hormone (AMH; r = –0.51, p = 0.01) and total testosterone (TT; r = –0.71, p = 0.02) for rs182542888. A combined model of genetic variants, metabolites, and clinical features increased the prediction of ovulation (area under the curve (AUC) = 76.7%). Common variants in ZNF438 and rare functional mutations in REC114, associated with phenylalanine and arachidonic acid metabolites, contributed to the failure of infertility treatment in women with PCOS.
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U2 - 10.1016/j.eng.2022.08.013
DO - 10.1016/j.eng.2022.08.013
M3 - Article
AN - SCOPUS:85141319191
SN - 2095-8099
VL - 23
SP - 103
EP - 111
JO - Engineering
JF - Engineering
ER -