Matthew J. Huentelman

The paper identifies reduced Golgi enzymes MAN1A1 and MAN1A2 in ALS-associated microglia and astrocytes, linking impaired glycan metabolism to neuroinflammation and disease mechanisms.

This study uses multi-omic profiling of synaptosomes to identify molecular changes in C9-FTD, revealing disrupted synaptic pathways and localized cryptic transcripts.

The paper uses pseudotime analysis on bulk RNA-seq data from Alzheimer's disease brains to identify conserved and region-specific molecular programs across nine brain regions.

This study shows that the TREM2-R47H variant causes neurodegenerative changes in forebrain organoids and impairs cell integration into the microglial niche.

This study uses bulk RNA-seq to analyze transcriptional changes in the middle temporal gyrus across Alzheimer's disease and aging, identifying distinct gene expression patterns and pathways associated with each condition.

The paper identifies molecular programs coordinated with NPTX2 that distinguish cognitive resilience in AD pathology from non-pathological cognition and AD.

This study performs a phenome-wide association analysis of APOE alleles in the All of Us Research Program, identifying significant associations with various health outcomes and highlighting sex and ancestry differences.

This study uses whole genome sequencing and AI to identify genetic variants associated with TDP43-Type-C neurodegeneration, finding novel links to FIG4, UBQLN2, INPP5A, and ANXA11.

This study uses zebrafish to examine the effects of CSNK2A1 mutations on morphology, showing a link between genetic changes and phenotypes, with partial rescue by wild-type mRNA.

The paper investigates how Celsr3 mutations affect tic-like behaviors in mice by examining striatal dopamine receptor alterations.

The paper compares transcriptomic responses in skeletal muscle and extracellular vesicles after traditional and high-intensity exercise in young adults, finding more consistent gene responses to traditional exercise and unique microRNA responses to high-intensity training.

This study identifies blood-based biomarkers associated with Alzheimer's disease genetic risk variants in a large cohort of healthy adults, showing effects from early adulthood and sex-specific patterns.

GEM, an AI-based tool, ranks causal genes highly for rare genetic diseases, improving diagnostic efficiency and reducing manual effort.

This study profiles RNA expression in MSA cerebellar tissue, identifying distinct transcriptional signatures between parkinsonian and cerebellar subtypes, with greater dysregulation observed in the cerebellar subtype.

The paper identifies genes associated with Rett syndrome-like (RTT-L) phenotype through whole exome sequencing and protein-protein interaction network analysis, revealing shared pathways with classical Rett syndrome.

Genetic correlations across 25 brain disorders (215,683 cases) reveal broad psychiatric common-variant sharing, largely distinct neurological disorders, and migraine as the only significant cross-category link.

This study identifies genetic modifiers of Alzheimer’s disease using a humanized mouse model and finds Trpc3 as a novel therapeutic target.

The paper evaluates 15 candidate SNPs associated with psychiatric disorders using 6,165 diffusion MRI scans, finding no significant associations after correction for multiple testing.