David Alan Bennett

This paper introduces VC-TWAS, a novel variance-component TWAS method that improves power for studying complex diseases like Alzheimer's dementia by relaxing assumptions about genetic effects.

This study identifies exonic variants in ERN1, TACR3, and SPPL2C associated with Alzheimer's disease through exome-wide age-of-onset analysis, with functional insights into their regulatory roles.

This study shows neuroticism significantly affects the brain transcriptome and may mediate cognitive decline and Alzheimer's disease through TAU pathology-related gene expression.

The paper identifies pQTLs for brain proteins and finds they differ from eQTLs, suggesting distinct genetic control of mRNA and protein abundance.

This study identifies 15 genetic loci associated with muscle weakness in older adults through a large meta-analysis, revealing new pathways linked to aging and health outcomes.

The paper deconvolves 3,387 post-mortem brain samples using SPLITR to identify cell-type-specific eQTLs and genetic effects in mental disorders.

This study shows that CD2AP loss in brain endothelial cells impairs vascular function and memory in AD models, suggesting therapeutic targeting of CD2AP pathways.

The paper identifies an epigenomic factor linked to reduced activated microglia that mitigates the risk of Alzheimer's disease in APOE ε4 carriers.

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.

This paper introduces BGW-TWAS, a Bayesian method for transcriptome-wide association studies that incorporates both cis- and trans-eQTL information, improving power and identifying novel associations with Alzheimer's disease.

The paper evaluates methods for estimating cell-type proportions in brain tissue using paired transcriptomic and immunohistochemistry data, showing some algorithms provide accurate estimates.

The paper uses multiplexed proteomics to identify synaptic factors linked to cognitive resilience in Alzheimer's Disease by analyzing brain tissue from individuals with varying pathology and cognitive outcomes.

This study identifies DNA methylation loci associated with late-life depression in brain tissue, highlighting sex-specific differences.

This study identifies genetic variants and pathways associated with cognitive resilience to Alzheimer's disease, finding a novel locus linked to bile acid metabolism and methylation changes.

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.

This study identifies 114 proteins and 5 modules linked to cerebral atherosclerosis in the brain, with 23 proteins and 2 modules also associated with Alzheimer’s dementia, highlighting shared mechanisms involving synaptic signaling and myelination.

The paper identifies protein network modules in Alzheimer's disease brains and cerebrospinal fluid that are associated with energy metabolism and neuroinflammation, suggesting potential biomarkers and therapeutic targets.

The paper investigates sex and APOE ε4 genotype effects on metabolic alterations in Alzheimer’s disease using stratified analysis of serum metabolites.

The paper identifies brain microRNAs linked to late-life depressive symptoms and shows their association with cognitive decline and dementia risk.

This study identifies metabolites and pathways in serum and brain tissue associated with cognitive impairment and develops models to predict antecedent cognitive decline in older adults.

This study shows that Tau disrupts the spliceosome, leading to cryptic RNA splicing and neurodegeneration in Alzheimer’s disease.

The paper introduces a Bayesian method for transcriptomic data imputation that improves gene mapping of complex traits by enhancing imputation accuracy and TWAS power over existing tools.

This study demonstrates sex-dependent polygenic effects on Alzheimer’s disease progression by using polygenic hazard scores, showing stronger associations with clinical outcomes than traditional polygenic risk scores.

The paper examines microglial activation in elderly brains, finding strong associations with neuropathology and cognitive decline, and identifies genetic overlaps with Alzheimer's disease.

Coexpression meta-analysis of 2114 human brain RNA-seq samples across the AMP-AD consortium identifies five consensus Alzheimer's disease transcriptional clusters, including two sex-heterogeneous clusters and a previously unreported proteostasis cluster.

This study identifies tau pathology-driven chromatin organization changes in aged human brains and shows these effects can be reversed with HSP90 inhibitors.

The paper identifies genetic loci associated with cognitively-defined subgroups of late-onset Alzheimer’s disease using SNP data from multiple studies.

The paper identifies altered bile acid profiles in Alzheimer's disease, linking them to cognitive impairment and genetic variants through a large study.

This study identifies splicing variations in aging brains linked to Alzheimer’s Disease, finds genetic regulation of splicing, and highlights shared pathways with other neurodegenerative diseases.