Joseph S. Reddy

This study identifies genetic risk loci for doxorubicin-induced arrhythmia through GWAS meta-analysis and validates their functional relevance in human and zebrafish models.

This study evaluates TRPC6 missense variants in cancer patients using molecular docking and patch clamp electrophysiology to predict functional impact and guide clinical decisions.

The paper identifies epigenetic changes in Alzheimer's disease brains linked to tau pathology, highlighting oligodendrocyte gene perturbations as a potential common mechanism across tauopathies.

The paper performs large-scale proteomic analysis of Alzheimer's disease brain regions across different racial and ethnic groups, identifying AD-related protein changes and APOE4 concordance with genotype.

This paper presents a multi-omics dataset from multi-ethnic Alzheimer's disease brain donors, including transcriptome, genome, and proteome data, to improve precision medicine for underrepresented populations.

This study identifies ABCA7-dependent neuropeptide Y signaling as a resilience mechanism critical for synaptic integrity and its disruption as a risk factor for Alzheimer's disease.

This study performs a genome-wide association study of brain biochemical phenotypes in Alzheimer's patients, identifying novel genetic loci and highlighting distinct genetic architectures for AD-related proteins.

The paper identifies three novel immune pathway genes with deleterious variants associated with Alzheimer's disease using polygenic risk scores in whole exome sequence data.

The paper uses single nucleus RNA sequencing to analyze brain vascular cells in Alzheimer's disease, identifying molecular changes and interactions between vascular and astrocytic cells at the blood-brain barrier.

The paper identifies four genes, including two novel ones, co-expressed with TREM2 in Alzheimer's disease using whole-exome data from ADSP.

This paper performs a large-scale eQTL meta-analysis across cerebral cortical and cerebellar brain regions, identifying distinct eQTL patterns and demonstrating improved power over existing studies.

The paper identifies cell-intrinsic differentially expressed genes in Alzheimer's disease by analyzing bulk-RNAseq data and comparing results to single nucleus RNAseq.

The paper develops a computational systems biology approach to identify novel microglial-specific targets for the phagosome in Alzheimer's disease using integrated transcriptome and genotype data.

The paper identifies dark and camouflaged gene regions in the human genome, shows how long-read sequencing reduces their prevalence, and applies an algorithm to uncover disease-relevant variants in Alzheimer's Disease Sequencing Project data.