A large-scale genetic study identifies 36 genes linked to higher risk of obsessive-compulsive disorder and chronic tic disorders, proposing drug development that targets gene networks rather than single genes.

These genes influence neurotransmitter signaling and brain circuits involved in movement, decision-making, and habit formation, with activity concentrated in regions such as the cortex and striatum.

Several of the implicated genes were also associated with autism and schizophrenia, reinforcing evidence that disruptions in brain development and communication underlie multiple psychiatric conditions.

Separately, reducing EFHD1 activity could protect against fatty liver injury by limiting fat-induced cellular damage, with drug development targeting EFHD1 already underway.

Blocking EFHD1, a calcium-binding mitochondrial protein, reduced liver injury in fatty liver disease models, suggesting a potential pathway to prevent disease progression.

The work advances the field by clarifying causes and offering multiple new directions for treatments, while acknowledging the essential contributions of families who supplied samples over the past two decades.

Retroactive data collection and long-term family participation in genome sequencing are highlighted as valuable for understanding neurodevelopmental disorders and reinterpreting older samples.

The Nature Neuroscience article published on September 1, 2026 includes a full conflict-of-interest disclosure detailing authors’ funds, affiliations, and consultancies.

The study emphasizes the importance of families' DNA contributions and the potential to translate genetic insights into therapies that target core disease processes rather than just symptoms.

Two major advances emerge: a genetic network framework for OCD and tic disorders to guide new treatments, and a mitochondria-related target (EFHD1) offering a route to prevent fatty liver injury.

This is a genetic discovery, not a clinical trial, and further research is required to understand how mutations affect brain development and which biological changes are most impactful.

Findings suggest that targeting whole neural networks could enable broader therapeutic options, with substantial effect sizes noted in risk increases across cases.