Risk for miscarriage can now be predicted
Researchers have came up with a new way of predicting and treating one of the most common types of miscarriages.
What you need to know:
- Recent studies have shown that genes predispose certain women to aneuploidy ( a term describing a human egg with an abnormal number of chromosomes) 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.
Women can now breathe a sigh of relief after researchers came up with a new way of predicting and treating one of the most common types of miscarriages.
A woman’s risk of suffering the miscarriage can now be predicted based on a specialised analysis of her genome as reported by Human Genetics, a global scientific journal.
The researchers at Rutgers School of Arts and Sciences, who worked with Reproduction Medicine Associates of New Jersey, an IVF clinic in Basking Ridge in the US, disclosed a technique that involves 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.
“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,” said Jinchuan Xing, author of the study and an associate professor in the genetics department at the institution.
He explained that the goal of the project was to understand the genetic cause of female infertility and develop a method to improve clinical prognosis of patients’ aneuploidy risk.
The experts highlighted that miscarriages can be predicted based on a specialised analysis of a woman’s genome and the insight could allow patients and clinicians to make better-informed decisions regarding reproductive choices and fertility treatment plans.
“… we created a software using machine learning, an aspect of artificial intelligence in which programmes can learn and make predictions without following specific instructions.
“To do so, we developed algorithms and statistical models that analysed and drew inferences from patterns in the genetic data,” the author highlighted. Xing believes patients and doctors around the world will now have a better sense on how to approach treatment. “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,” he said.
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.
