Tim B. Bigdeli

This study performs a single-nucleus transcriptome-wide association study to identify gene-trait associations in brain disorders, revealing cell-type-specific genetic regulation and ancestry-specific patterns.

This study analyzes 173 multiplex Portuguese families to identify rare genetic variants associated with schizophrenia, mood disorders, and autism, finding a CHD2 mutation linked to diverse mental illness phenotypes.

This study identifies a genetic link between externalizing traits and suicide risk using genomic data and electronic health records from over 500,000 veterans.

The paper identifies novel CNV loci and dose-dependent gene effects across six psychiatric disorders using genome-wide analysis.

The paper identifies shared and divergent genetic mechanisms across psychiatric disorders using gene-set burden analysis of copy number variants.

This study identifies genetic risk loci and factors underlying clinical subtypes of bipolar disorder using GWAS and meta-analysis.

This study identifies ten genetic loci associated with dry eye disease and finds significant genetic correlations with several comorbidities.

This study conducts trans-ancestry GWAS on UK Biobank data to identify novel MDD risk loci, finding 61 loci with increased sample size and ancestry inclusivity.

This study identifies prevalence and disease risks for male and female sex chromosome trisomies using registry data from 1.5 million participants, finding shared phenotypic associations across trisomy subtypes.

This study evaluates imputation performance of reference panels in a Pakistani population, finding that ex1KG outperforms TOPMed despite its smaller size.

This study identifies 63 AMD risk loci across multiple ancestries, highlighting ancestry-dependent genetic heterogeneity and potential therapeutic targets.

This study identifies population-specific eQTLs in brain tissues from European, African American, and Asian ancestry individuals, revealing new schizophrenia risk genes and variants missed in European-only datasets.

The paper introduces BGE, a sequencing method that combines low-pass whole genome and deep whole exome data, showing high accuracy and cost-effectiveness for genetic variant discovery.

The paper identifies genetically distinct patient subgroups across diseases by analyzing polygenic risk and pathway convergence.

This study identifies 240 novel genetic loci associated with mosaic loss of chromosome Y through a multi-ancestry GWAS of the Million Veteran Program and UK Biobank.

This study identifies correlates of risk for disinhibited behaviors in veterans using polygenic scores and electronic health records, finding strong associations with substance use disorders and related health outcomes.

This study identifies somatic copy number variants (sCNVs) in schizophrenia cases, revealing their contribution to risk and specific NRXN1 disruptions.

The paper uses brain cell-type-specific protein interactomes to interpret genetic data in schizophrenia and identifies enriched networks and genes associated with the disease.

This paper introduces PheMED, a tool to quantify effect size dilution in GWAS due to phenotypic misclassification, and demonstrates its applications in improving meta-analysis.

A genome-wide association study of 69,369 schizophrenia cases and 236,642 controls identifies 270 risk loci, prioritizes 130 genes, and links common and rare risk variants to neuronal synaptic biology.

Exomes of 24,248 schizophrenia cases and 97,322 controls implicate ultra-rare damaging variants in 10 genes, including GRIN2A and GRIA3, with odds ratios of 3 to 50.

The paper validates polygenic risk scores for schizophrenia, bipolar disorder, and depression using VA EHR data and shows their association with disease risk and hospitalization.

This study analyzes ancestry diversity changes in the Million Veteran Program over time and shows that refined ancestry modeling reduces population stratification in GWAS of height.

This study identifies sex-dependent genetic risk loci shared and specific to mood and psychotic disorders using genome-wide interaction analysis.

This study identifies genetic loci associated with suicide attempts and shows shared genetic architecture with psychiatric disorders and non-psychiatric risk factors.

This study evaluates the prognostic value of polygenic risk scores for schizophrenia and finds they do not improve outcome prediction beyond clinical features.

This study identifies genetic variants shared between schizophrenia and alcohol use disorder, finding both convergent and divergent effects and evidence of brain tissue expression.

Meta-analysis of 41,917 European-ancestry bipolar disorder cases versus 371,549 controls yields 64 risk loci (33 novel), neuronal and synaptic gene enrichment, and 15 eQTL-prioritized genes.

The paper compares ten polygenic score methods for psychiatric disorders across multiple cohorts, finding that some methods significantly improve prediction statistics over the baseline PC+T method.

This study identifies 308 genetic loci associated with mood disorder and schizophrenia across East Asian and European populations, revealing shared and distinct genetic mechanisms.