Diabetes research and clinical practice · 2025
Preimplantation genetic testing for type 2 diabetes based on family-specific polygenic risk score: A proof-of-concept study.
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Xu Chenming, Chen Songchang, Zou Yangyun, Chen Yulin, Wu Yanting, Xu Congjian, Xia Yingying, Chen Guobo, Jin Li, Lu Sijia, Huang Hefeng
Аннотация
AIMS: This study aims to evaluate the feasibility of family-specific polygenic risk prediction in reducing the risk of type 2 diabetes (T2D) in the offspring from an infertile couple with a family history of early-onset T2D.
METHODS: We innovatively established a family-specific polygenic risk prediction model for this T2D family and the embryo with the lowest risk of T2D were selected for implantation.
RESULTS: Initially, whole exome sequencing analysis in the family failed to identify monogenic-level pathogenic or likely pathogenic variants responsible for T2D. Thus, preimplantation genetic testing for monogenic disease (PGT-M) may be not applicable. Subsequently, we innovatively developed a family-specific polygenic-level T2D risk prediction model including 114 T2D risk SNPs and weighted by the genotype-phenotype correlation of asymptomatic individuals and T2D patients in the pedigree. Using this model, the euploid embryo P_5977_1C exhibited the lowest T2D risk and was selected for implantation. The newborn displayed the same lowest T2D polygenic risk and normal growth and development after a 16-month follow-up.
CONCLUSION: Our study provided preliminary evidence for the feasibility of developing a more accurate polygenic risk prediction model using pedigree information and its application in embryo selection.
METHODS: We innovatively established a family-specific polygenic risk prediction model for this T2D family and the embryo with the lowest risk of T2D were selected for implantation.
RESULTS: Initially, whole exome sequencing analysis in the family failed to identify monogenic-level pathogenic or likely pathogenic variants responsible for T2D. Thus, preimplantation genetic testing for monogenic disease (PGT-M) may be not applicable. Subsequently, we innovatively developed a family-specific polygenic-level T2D risk prediction model including 114 T2D risk SNPs and weighted by the genotype-phenotype correlation of asymptomatic individuals and T2D patients in the pedigree. Using this model, the euploid embryo P_5977_1C exhibited the lowest T2D risk and was selected for implantation. The newborn displayed the same lowest T2D polygenic risk and normal growth and development after a 16-month follow-up.
CONCLUSION: Our study provided preliminary evidence for the feasibility of developing a more accurate polygenic risk prediction model using pedigree information and its application in embryo selection.