Alejo J. Nevado‐Holgado

This study uses brain-genotype scores to identify genetic associations with plasma proteins, finding 116 significant associations after FDR correction that conventional SNP models miss.

The paper uses plasma proteomics to identify differentially abundant proteins and co-expression modules across Alzheimer's disease stages, highlighting potential biomarkers for early detection.

The paper uses longitudinal proteomic data to identify molecular subtypes of Parkinson's disease, revealing conserved modules and their associations with clinical phenotypes.

This study uses deep learning to profile neuronal morphology changes caused by Aβ1-42, achieving higher accuracy than traditional feature-based methods.

This study shows iPSC-derived astrocytes from AD patients reflect key pathophysiological features, offering a new model for AD research and therapeutic screening.

This study identifies 262 STRs significantly associated with MRI-derived grey matter volumes in UK Biobank participants, with 12 associations replicated and no nearby SNPs in linkage disequilibrium.

The paper identifies DNA methylation and proteomic markers associated with brain health through integrated methylome and phenome analyses.

The paper identifies genetic and epigenetic factors influencing plasma protein levels linked to Alzheimer's disease, finding novel associations with TREM2 and TBCA.

The paper links indoxyl sulfate, a gut microbiome-derived metabolite, to anxiety symptoms and specific brain connectivity patterns in patients with depression.

This study identifies shared transcriptomic changes between Alzheimer's disease and Major Depression in mice, suggesting Major Depression may be an early manifestation of Alzheimer's.

The paper uses targeted metabolomics to analyze changes in acylcarnitines, amines, and lipids in response to citalopram/escitalopram treatment in MDD patients, identifying metabolic correlates of treatment response.

The paper combines GWAS, clinical data, and experimental models to identify JAK-STAT pathway dysregulation as a potential therapeutic target for Alzheimer’s disease.

This study shows that serum from MCI patients predicts AD conversion up to 3.5 years before diagnosis by altering hippocampal progenitor cell behavior.