Researchers identify a significant expansion in the genetic landscape of obsessive-compulsive disorder and tic disorders, revealing potential common roots with autism and schizophrenia, and emphasizing the need for inclusive medical testing.
Researchers have identified 36 genes that appear to carry a strong risk for obsessive-compulsive disorder and chronic tic disorders, a jump from the four genes that had previously been established. According to a study published in Nature Neuroscience, the team analysed whole-exome sequencing data from 3,964 patients, including 2,418 parent-child trios and 1,734 control trios, nearly doubling the size of earlier case collections. The variants were rare, but the effect sizes were striking: the study reported an average odds ratio of 57, although damaging mutations were seen in only about 3% to 8% of affected patients.
Several of the newly identified genes overlap with those already associated with autism, schizophrenia and developmental delay, suggesting that the conditions may share underlying biological pathways. Belinda Wang, the study’s lead author, said the findings point to networks of interacting genes rather than isolated single-gene causes. Jay Tischfield, an emeritus distinguished professor of genetics at Rutgers and a senior co-author, said in a statement that this network approach could make it easier to design future treatments.
The work on OCD and tic disorders comes alongside other recent research highlighting how neurodevelopmental conditions can be missed or measured unevenly in clinical practice. A separate retrospective cohort study published in JAMA Network Open found that autism diagnoses among females in a Midwestern health system rose by 19% a year after 2020, while male rates were flat or declined. The study of 171,134 patients found that girls and women were diagnosed, on average, 3.4 years later than boys and men, and the authors said the pattern likely reflects better recognition of historically underdiagnosed presentations rather than a sudden change in prevalence. Another review, published in European Radiology, found that only 14% of validation studies for commercial radiology artificial intelligence systems reported performance by sex, age or race and ethnicity, underscoring wider concerns about whether new medical tools are being tested evenly across patient groups.
Disclaimer: This content is for informational purposes only and is not intended to be a substitute for professional medical judgment, advice, diagnosis, or treatment.
