PubMed HealthSearch

Biomedical subjects

Zhen Zhao

Publications and source records attributed to Zhen Zhao.

3 recordsLinked to original sources

Shared genetic architecture between major depression and intrinsic brain functional connectome organization.

BACKGROUND: Major depression (MD) is increasingly understood as a disorder characterized by widespread abnormalities in intrinsic brain functional network organization. Although both MD and brain functional connectome architecture are highly heritable, the genetic architecture underlying their relationship remains poorly characterized. METHODS: We integrated genome-wide association studies of MD with 191 ICA-based resting-state functional connectome traits to investigate their shared genetic architecture. These traits captured intrinsic connectome organization across amplitude, functional connectivity, and global connectivity domains. Cross-trait genetic analyses were used to assess pleiotropic overlap between traits. Locus-level and gene-based analyses integrating multi-omics evidence were performed to characterize the biological relevance of shared genetic signals. RESULTS: We identified significant genetic overlap between MD and 148 of 191 brain functional connectome traits. Cross-trait analyses revealed widespread shared genetic signals organized into 627 genomic loci across amplitude, functional connectivity, and global connectivity measures. Among these, 193 loci showed evidence consistent with shared causal variants based on colocalization analyses. Gene-level integration mapped these loci to 1459 protein-coding genes (390 unique genes). Multi-layer prioritization identified 17 high-confidence genes supported by convergent genomic, transcriptomic, and proteomic evidence, with enrichment in neurodevelopmental and lipid-related metabolism pathways. CONCLUSIONS: This study provides a multi-scale characterization of the shared genetic architecture between MD and intrinsic brain functional connectome organization, revealing that shared genetic signals between MD and brain functional systems are distributed across multiple functional levels and converge at the molecular level.

Connectome

Advanced glycation end products drive blood-brain barrier lipid dysregulation via RAGE-ABCA1 signaling to promote neurovascular dysfunction in Alzheimer's disease.

Neurovascular dysfunction is an early and critical contributor to Alzheimer's disease (AD), yet the molecular mechanisms linking vascular pathology to metabolic dysregulation remain incompletely understood. Advanced glycation end products (AGEs), which accumulate during aging and metabolic stress, have been implicated in AD pathology; however, their role in cerebrovascular lipid homeostasis is unclear. Here, we demonstrate that AGE accumulation within cerebral microvessels promotes lipid droplet (LD) formation in endothelial cells through receptor for AGE (RAGE)-dependent disruption of cholesterol efflux pathways. In aged APP transgenic mice and human AD brains, we observe increased AGE deposition concomitant with elevated RAGE, DGAT1, and perilipin expression, alongside reduced ABCA1 levels. In human brain endothelial cells, AGE exposure induces lipid metabolic reprogramming characterized by enhanced LD accumulation, upregulation of lipogenic machinery, and suppression of cholesterol efflux. Mechanistically, RAGE silencing restores ABCA1 expression and attenuates LD formation, identifying RAGE as a key upstream regulator. Pharmacological activation of ABCA1 reverses AGE-induced lipid accumulation and reduces RAGE expression, highlighting a therapeutic axis. Furthermore, AGE exposure disrupts blood-brain barrier (BBB) integrity and impairs amyloid-β transport in an in vitro BBB model. In vivo, aging is associated with progressive microvascular LD accumulation, linking metabolic dysfunction to vascular pathology. Together, our findings establish an AGE-RAGE-ABCA1 signaling axis that drives endothelial lipid dysregulation and BBB impairment, providing a mechanistic framework connecting metabolic stress to neurovascular dysfunction in AD.

Journal Article

Temporal DIA-MS proteomics reveals coordinated metabolic reprogramming associated with oil accumulation in oil palm mesocarp.

Oil palm (Elaeis guineensis Jacq.) is the most productive oil-bearing crop globally, yet the molecular basis of mesocarp development and lipid accumulation remains poorly understood. Ultra-deep data-independent acquisition mass spectrometry (DIA-MS) was applied to characterize proteome dynamics in two contrasting genotypes, seedless (KS) and thin-shelled (TS), across five developmental stages (P1-P5) spanning fruit development to mature oil accumulation. Phenotypic analysis revealed higher mesocarp proportion and oil content in KS during late maturation. A total of 137,615 peptides corresponding to 12,163 protein groups were identified, providing a temporal proteomic landscape of mesocarp development. Multivariate analysis indicated that developmental progression was the primary contributor to proteomic variation, whereas genotype-associated differences increased during lipid accumulation. Differentially abundant proteins were mainly associated with carbohydrate metabolism, photosynthesis, proteolysis, antioxidant responses, and lipid biosynthesis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and KOG analyses suggested extensive remodeling of metabolic networks, including developmental changes in photosynthesis-associated proteins and increased representation of lipid-associated pathways during maturation. Weighted protein co-expression network analysis identified 17 modules associated with developmental progression and lipid accumulation, highlighting candidate proteins involved in carbon metabolism, energy production, and cellular protection. Genes encoding selected hub protein candidates were further examined by RT-qPCR. Biochemical analyses supported these proteomic patterns, showing increased acetyl-CoA availability, enhanced antioxidant enzyme activities (SOD, CAT, APX, and GR), improved GSH/GSSG balance, and reduced oxidative damage in KS. Together, these findings provide a temporal proteomic and biochemical framework for understanding genotype-associated differences in oil accumulation and identify candidate metabolic networks for functional studies.

Carbon metabolism