Li Zhang

This study engineers AAV9 variants guided by LRP6 to enhance BBB penetration and reduce liver tropism in non-human primates.

This study identifies PIKfyve as a targetable vulnerability in pancreatic cancer by showing its role in lipid metabolism and synthetic lethality with KRAS-MAPK inhibitors.

This study uses clustering to identify prediabetes phenotypes and their association with treatment outcomes in the DPP trial, finding that more comprehensive models better differentiate metabolically healthy overweight individuals.

This study identifies a metabolic link between methionine metabolism, DNA repair, and radiation resistance in glioblastoma, showing that inhibiting SAM synthesis enhances radiation efficacy.

This study examines longitudinal associations between circulating microRNAs and weight changes over two years in the Diabetes Prevention Program.

This study identifies molecular changes in bladder mucosa that initiate cancer, revealing inflammation's role and mutation patterns linked to early carcinogenesis.

This study shows that purine metabolism affects DNA repair and therapy resistance in glioblastoma, suggesting that targeting purine synthesis could improve treatment outcomes.

This study shows that activating PKM2 with ML-265 protects photoreceptors from stress-induced apoptosis in vitro and in vivo.

The paper derives a simple approximation to bias in gene-environment interaction estimates when clinically diagnosed cases may include a nuisance pathologic state, and demonstrates its validity through simulations and an Alzheimer's disease study.

This study investigates the effects of KMT2D loss in brain cell development, finding precocious neuronal differentiation and disrupted oxygen responses in Kabuki syndrome models.

This study identifies distinct genomic and molecular features of sarcomatoid bladder cancer, linking EMT dysregulation to aggressive behavior and immune infiltration.

The paper derives a simple approximation to correct genetic effect estimates in case-control GWAS when multiple disease states share a clinical diagnosis and applies it to Alzheimer's disease.

The paper derives a theoretical approximation for bias in gene-environment interaction estimates in case-control studies with silent disease and validates it through simulations and a prostate cancer study.