Back

Functional consequences of genetic risk for neuropsychiatric conditions at chr22q

Nadig, A.; Tegtmeyer, M.; Patil, A.; Zhang, Y.; Ling, E.; Weiner, D.; Liyanage, D.; Erdin, S.; Yadav, R.; Bybjerg-Grauholm, J.; Collins, R.; iPSYCH Consortium, ; Psychiatric Genomics Consortium Autism Working Group, ; Grove, J.; Borglum, A.; Talkowski, M.; O'Connor, L.; Kadoch, C.; McCarroll, S. A.; Nehme, R.; Robinson, E.

2025-07-07 genetic and genomic medicine
10.1101/2025.07.01.25330642 medRxiv
Show abstract

Understanding how common and rare genetic variation raises risk for neuropsychiatric disease remains a major challenge. We identify the long arm of chromosome 22 (chr22q) as a region where common polygenic risk for schizophrenia, autism, ADHD, and lower IQ is associated with coordinated downregulation of gene expression in postmortem human brain tissue. The effects are strikingly consistent between neuropsychiatric diagnoses and across brain cell types, and appear to be specific to brain-related traits. We observe that common variant risk for neuropsychiatric diseases has remarkably diffuse expression associations across chr22q, including long-range aggregate associations between genetic variants and genes over 10 Mb away. Polygenic risk for psychiatric disease at chr22q is more strongly associated with lower cognitive ability than elsewhere in the genome, suggesting phenotypic convergence with the 22q11.2 deletion, a rare genetic disorder that causes intellectual disability, schizophrenia, autism, and ADHD. Using human iPSC data, we show that the 22q11.2del induces similarly broad expression downregulation across chr22q in multiple neural cell types and experimental settings. Altogether, our results nominate chr22q as a regulatory hub in neuropsychiatric disease, where common and rare genetic risk factors converge both functionally and phenotypically.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.