Shahram Bahrami

This study analyzes GWAS data from nearly 1 million cases to show widespread genetic overlap between neurological and psychiatric disorders, with shared biological processes and divergent effect sizes.

This study identifies 118 new genetic loci associated with Alzheimer's disease across diverse ancestries and discovers 48 novel risk loci, including those enriched in neuronal cell types.

This study identifies shared genetic loci between common epilepsies and general cognitive ability using LDSC, MiXeR, and conjFDR analyses.

This study identifies 114 novel genomic loci for anxiety and finds extensive genetic overlap with schizophrenia, bipolar disorder, major depression, and ADHD.

This study identifies 72 genetic loci associated with basal ganglia volumes and finds significant genetic overlaps with Parkinson's disease, schizophrenia, and migraine.

This study identifies 14 novel opioid use disorder loci and 7 shared loci with schizophrenia, bipolar disorder, and major depression using genome-wide association summary statistics.

The paper introduces Meta-MOSTest, an extension of MOSTest for meta-analysis of multivariate GWAS, showing it maintains statistical power and type I error control across multiple cohorts.

The paper identifies 173 genetic loci associated with hippocampal formation volume and finds genetic overlap with eight brain disorders.

This study uses a multivariate genetic approach to analyze personality and cognitive traits, identifying pleiotropy and improving polygenic prediction.

This study identifies 42 genetic loci associated with thalamus and its nuclei volumes and finds genetic overlaps with cortical regions and ten brain disorders.

This study identifies seven novel genetic loci for Alzheimer's disease using a large GWAS and highlights microglia and immune pathways as key contributors to disease pathology.

The paper identifies genetic loci associated with brainstem volumes and finds genetic overlaps with psychiatric and neurological disorders.

The paper introduces AI-MiXeR, a method to estimate variant counts and effect sizes across functional annotations using GWAS summary statistics, revealing phenotype-specific polygenicity and effect size differences.

This study identifies shared genetic loci between multiple system atrophy and inflammatory bowel disease using conjFDR, highlighting immune and gut-related molecular mechanisms.