medRxivGenetic & Genomic MedicinePreprint
Highly Accurate Non-Invasive Preimplantation Genetic Testing for Monogenic and Polygenic Diseases from Spent Medium
Lei HuangiD, Jin Huang, Minyue Ma, Yangyun Zou, Ruiqi Zhang, Guangjun Yin, Quangui Wang, Yingying Xia, Jialin JiaiD, Zeyu WuiD, Dandan Cao, Weiliang Song, Yaqiong Tang, Kai Liu, Xiaoran ChaiiD, Guo‐Bo CheniD, Sijia Lu, Hongmei Peng, Hao GeiD, Jie QiaoiD, Xiaoliang Sunney XieiD
Abstract
Traditional preimplantation genetic testing for in vitro fertilization (IVF) requires invasive trophectoderm biopsy, which may harm the embryo. Non-invasive preimplantation genetic testing (niPGT) utilizing cell-free DNA from spent embryo culture medium (SCM) has been attempted, but trace DNA content, maternal cell contamination, and high allele drop-out rates are barriers. Here we report an niPGT methodology achieving high diagnostic accuracy among reportable samples across diverse embryo and disease contexts. Reengineered linear whole-genome amplification with an extremely low error rate is followed by application of a Bayesian algorithm designed to determine which parental haplotypes are inherited at disease-causing sites. Among 191 SCM samples from 29 families affected by rare monogenic disorders, our method amplified all samples and enabled diagnosis of 220 out of 277 pathogenic alleles. All diagnoses (220/220) were concordant with invasive biopsy control. For select embryos, personalized genome-wide genotyping enabled exploratory polygenic risk assessment for Type II Diabetes. Our methodology requires no modification to IVF workflows and represents a key technological advance toward scalable, accurate, and safe niPGT for both monogenic and polygenic diseases.
- organism: human
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: polygenic risk
- approach: statistical model
- approach: Bayesian inference
- Citations
- 1
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