Juan I. Young

This study identifies DNA methylation changes in aging and Alzheimer's disease using brain and blood data, finding concordant CpG sites associated with AD progression.

This paper investigates the impact of an ancestry-specific ABCA7 deletion on lipid homeostasis in Alzheimer's disease, showing disrupted lipid regulation in neurons.

This study uses eHiCA to identify regulatory interactions at the PICALM-EED locus, showing distinct chromatin interactions for SNPs within a segregating haplotype.

The paper identifies ancestry-specific chromatin architecture differences in Alzheimer's Disease using Hi-C and ATAC-seq data from African and European ancestry individuals.

This study performs a sex-stratified transcriptomic meta-analysis of Alzheimer's disease to identify sex-specific and sex-dependent gene expression differences and potential drug targets.

This study identifies age-associated DNA methylation changes in blood and their overlap with Alzheimer's disease by analyzing two cohorts and finding shared genetic variants and CpGs associated with both aging and AD.

The paper identifies an African-origin haplotype that reduces AD risk in APOEε4 carriers by 75% and explores its molecular mechanisms through sequencing and methylation analysis.

This study generates a Sord knockout rat model to study SORD deficiency, revealing motor-predominant neuropathy with elevated sorbitol and neurofilament light chain levels.

The paper shows that ELA-associated increased chromatin accessibility and expression of APOE4 in astrocytes contribute to higher AD risk in APOE4/4 carriers.

MethReg identifies CpG sites with high regulatory potential by integrating DNA methylation, gene expression, and TF binding data to uncover TF-target gene associations in specific methylation contexts.

The paper identifies differential regulatory control of APOEε4 on African versus European haplotypes through enhancer activity and promoter interactions analyses.

The paper finds that APOEϵ4 expression is higher in European ancestry carriers and linked to A1 reactive astrocytes, potentially explaining higher AD risk in this group.

coMethDMR identifies differentially methylated regions by first selecting co-methylated sub-regions and then testing their association with phenotypes using a mixed effects model.