Mengze Li

The paper identifies metabolomic signatures associated with extreme old age using data from the New England Centenarian Study and links them to biological age and mortality risk.

This study identifies age and survival-related transcriptomic signatures in longevity-enriched cohorts using RNAseq data from blood samples.

This study identifies genetic variants associated with cognitive domains like memory and attention using GWAS in the Long Life Family Study, finding domain-specific genetic architecture.

The paper validates and expands a serum protein signature associated with APOE genotypes, identifying new protein associations and potential targets for Alzheimer's disease prevention.

The paper validates and expands a serum protein signature of extreme old age using LC-MS/MS, identifying 80 conserved proteins across platforms associated with aging pathways.

The paper introduces yQTL Pipeline, a tool for QTL discovery and visualization, applied to metabolomics data from NECS, identifying 14,983 mQTLs with improved efficiency.