Biomedical subjects

Zihao Li

Publications and source records attributed to Zihao Li.

3 recordsLinked to original sources

PubMed2026

Integrative Genomic and Functional Investigation of the Multi-Layered Genetic Architecture Between Anorexia Nervosa and Bone Loss.

OBJECTIVE: Bone loss is a severe and often irreversible complication of anorexia nervosa (AN), yet the genetic mechanisms underlying this comorbidity remain underexplored. This study focuses on constructing a comprehensive genetic architecture between AN and estimated calcaneal bone mineral density (eBMD). METHOD: We applied an integrative framework incorporating genetic correlation, pleiotropic association, and causal inference across single-variant, multi-variant, and gene expression levels. Functional validation was conducted in vitro to investigate the biological role of the key candidate gene. RESULTS: Local genetic correlation analysis identified significant signals at 8p21.2 and 10q26.3, despite the lack of significant global correlation. Mendelian randomization analysis pointed to a suggestive negative causal effect of genetically predisposed AN on eBMD. Extensive pleiotropic signals were detected, particularly at 3p21.31 and 10q26.3, loci enriched with genes associated with both traits. Notably, we identified a novel pleiotropic signal near NCAM1 at 11q23.2, which was supported by multi-layered genetic evidence and confirmed through in vitro functional experiments. NCAM1, a well-established neural-associated gene, promoted osteoclastic differentiation and bone resorption when overexpressed in osteoclast precursor cells, indicating that NCAM1 possesses distinct functional roles in both neural and skeletal tissues. DISCUSSION: This study constructs a comprehensive genetic architecture underlying AN and eBMD and highlights NCAM1 as a key pleiotropic gene.

anorexia nervosa↗

PubMed2025

A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma.

BACKGROUND: Kidney Renal Clear Cell Carcinoma (KIRC) is a prevalent urinary malignancies worldwide. Glycosylation is a key post-translational modification that is essential in cancer progression. However, its relationship with prognosis, tumour microenvironment (TME), and treatment response in KIRC remains unclear. METHOD: Expression profiles and clinical data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering, Cox regression, and LASSO regression analyses were conducted to develop an optimal glycogene-related signature. The prognostic relevance of this molecular signature was rigorously analyzed, along with its connections to tumour microenvironment (TME), tumour mutation burden, immune checkpoint activity, cancer-immunity cycle regulation, immunomodulatory gene expression patterns, and therapeutic response profiles. Validation was performed using real-world clinical specimens, quantitative PCR (qPCR), and immunohistochemistry (IHC), supported by cohort analyses from the Human Protein Atlas (HPA) database. RESULTS: A glycogene-associated prognostic scoring system was established to categorize patients into risk-stratified subgroups. Patients in the high-risk cohort exhibited significantly poorer survival outcomes (p < 0.001). By incorporating clinicopathological variables into this framework, we established a predictive nomogram demonstrating strong calibration and a concordance index (C-index) of 0.78. The high-risk subgroup displayed elevated immune infiltration scores (p < 0.001), upregulated expression of immune checkpoint-related genes (p < 0.05), and an increased frequency of somatic mutations (p = 0.043). The risk score positively correlated with cancer-immunity cycle activation and immunotherapy-related signals. The high-risk groups also showed associations with T cell exhaustion, immune-activating genes, chemokines, and receptors. Drug sensitivity analysis revealed that low-risk patients were more sensitive to sorafenib, pazopanib, and erlotinib, whereas high-risk individuals responded better to temsirolimus (p < 0.01). qPCR and IHC analyses consistently revealed distinct expression patterns of MX2 and other key genes across the risk groups, further corroborated by the HPA findings. CONCLUSION: This glycogene-based signature provides a robust tool for predicting prognosis, TME characteristics, and therapeutic responses in KIRC, offering potential clinical utility in patient management.

Humans↗

PubMed2024

Genetic linkage disequilibrium of deleterious mutations in threatened mammals.

The impact of negative selection against deleterious mutations in endangered species remains underexplored. Recent studies have measured mutation load by comparing the accumulation of deleterious mutations, however, this method is most effective when comparing within and between populations of phylogenetically closely related species. Here, we introduced new statistics, LDcor, and its standardized form nLDcor, which allows us to detect and compare global linkage disequilibrium of deleterious mutations across species using unphased genotypes. These statistics measure averaged pairwise standardized covariance and standardize mutation differences based on the standard deviation of alleles to reflect selection intensity. We then examined selection strength in the genomes of seven mammals. Tigers exhibited an over-dispersion of deleterious mutations, while gorillas, giant pandas, and golden snub-nosed monkeys displayed negative linkage disequilibrium. Furthermore, the distribution of deleterious mutations in threatened mammals did not reveal consistent trends. Our results indicate that these newly developed statistics could help us understand the genetic burden of threatened species.

Animals↗