Douglas M. Ruderfer

This paper validates EHR-based BD phenotyping algorithms by showing their genetic correlation with traditional BD cases, suggesting they identify genetically similar cases.

This paper uses transcriptomic imputation to identify gene-tissue associations linked to Anorexia Nervosa risk, finding significant links in both brain and metabolic tissues.

The paper identifies concordant transcriptional signatures of schizophrenia in hiPSC-derived neurons and post mortem brains, suggesting neurons better model genetic risk and recommends increasing cohort size in hiPSC studies.

The paper uses Bayesian modeling to analyze rare exonic variants in schizophrenia and neurodevelopmental disorders, identifying 1,551 risk genes for schizophrenia and 98 new risk genes for developmental disorders.

The paper uses transcriptomic imputation to identify schizophrenia risk genes across multiple brain regions, finding 71 associated genes and 36 enriched pathways.

This study uses transcriptomic imputation to identify 29 novel genes associated with bipolar disorder and its subtypes, revealing biological pathways related to oxidative stress and circadian rhythms.

The paper identifies a common collagen disease in Puerto Ricans using identity-by-descent mapping and genomic data from a health system.

The paper integrates GWAS and conditional eQTL data to identify schizophrenia risk loci with co-localization, finding 40 loci and six with conditional eQTL co-localization.