Miscarriage risk predictable, study finds

A woman’s risk of suffering one of the most common types of miscarriages can be predicted based on a specialized analysis of her genome, according to a Rutgers study. Scientists said this insight could allow patients and clinicians to make better-informed decisions regarding reproductive choices and fertility treatment plans.

Reporting in the science journal Human Genetics, Rutgers researchers describe a technique combining genomic sequencing with machine-learning methods to predict the possibility a woman will undergo a miscarriage because of egg aneuploidy — a term describing a human egg with an abnormal number of chromosomes. Aneuploidy in human eggs accounts for a significant proportion of infertility, causing early miscarriage and in vitro fertilization (IVF) failure.

Recent studies have shown that genes predispose certain women to aneuploidy, but the exact genetic causes of aneuploid egg production have remained unclear. The Rutgers study is the first to evaluate how well individual genetic variants in the mother’s genome can predict a woman’s risk of infertility.

“The goal of our project was to understand the genetic cause of female infertility and develop a method to improve clinical prognosis of patients’ aneuploidy risk,” said Jinchuan Xing, an author of the study and an associate professor in the genetics department at the Rutgers School of Arts and Sciences. “Based on our work, we showed that the risk of embryonic aneuploidy in female IVF patients can be predicted with high accuracy with the patients’ genomic data. We also have identified several potential aneuploidy risk genes.”

“I like to think of the coming era of genetic medicine when a woman can enter a doctor’s office or, in this case, perhaps, a fertility clinic with her genomic information, and have a better sense of how to approach treatment,” Xing said. “Our work will enable such a future.”

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