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 journal Human Genetics, Rutgers researchers describe a technique combining genomic sequencing with machine-learning methods to predict the possibility that a woman will undergo a miscarriage because of egg aneuploidy – a term describing a human egg with an abnormal number of chromosomes. Infertility is a major reproductive health issue that affects about 12 percent of women of reproductive age in the U.S. Aneuploidy in human eggs accounts for a significant proportion of infertility, causing early miscarriage and in vitro fertilization (IVF) failure. To read the full story.