Shahram Bahrami

University of Oslo, Norway

Title: Unveiling the genetic landscape of basal ganglia: implications for common brain disorders

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Biography

Shahram Bahrami is a researcher in statistical genetics and neuroinformatics at the University of Oslo and NSG. His work focuses on integrating genomic and brain imaging data to understand the biological basis of neuropsychiatric and neurodegenerative diseases. He has extensive experience in multivariate GWAS, polygenic risk scoring, and cross-phenotype genetic correlation analyses. His recent research explores the genetic architecture of brain structures as potential biomarkers of aging and disease. He leads projects funded by the Research Council of Norway, focusing on precision medicine and brain health in aging populations.

Abstract

Age-related changes in brain structure are central to understanding cognitive decline and neurodegenerative risk. The basal ganglia, a key subcortical network implicated in motor and cognitive functions, undergo significant structural changes across the lifespan and are affected in both psychiatric and neurological disorders. In this study, we conducted a multivariate genome-wide association study (GWAS) of basal ganglia volumes using imaging and genetic data from 34,794 Europeans, with replication in 4,808 white and generalization in 5,220 non-white Europeans. Our multivariate GWAS identified 72 genetic loci associated with basal ganglia volumes, with a replication rate of 55.6% (P < 0.05) and 87.5% showing the same direction, revealing a distributed genetic architecture across basal ganglia structures.

To assess relevance for brain aging and pathology, we evaluated genetic correlations and pleiotropy between basal ganglia volume and eight brain-related disorders, including four neuropsychiatric (ADHD, ASD, BIP, SCZ) and four neurological conditions (MDD,MIG, ALZ, PD). We identified 3 loci significantly overlapping with ADHD, 2 with ASD, 20 with BIP, 83 with SCZ, 15 with MDD, 33 with MIG, 21 with ALZ, and 28 with PD. These findings highlight a substantial shared genetic architecture between basal ganglia structure and disorders that span neurodevelopmental to neurodegenerative pathways. These results underscore the utility of multivariate approaches for detecting brain-based biomarkers of aging and support basal ganglia morphology as a target for early identification of at-risk individuals. Our findings provide novel insights into the biological mechanisms linking subcortical brain aging and disease vulnerability.