PubMed HealthSearch

Biomedical subjects

Xinrui Li

Publications and source records attributed to Xinrui Li.

2 recordsLinked to original sources

Distinct spatial immune microenvironment features of different EGFR mutation subtypes in early-stage lung adenocarcinoma.

Epidermal growth factor receptor (EGFR) mutations are common in lung adenocarcinoma (LUAD), yet their influence on the spatial tumor immune microenvironment (TIME) in early-stage disease remains unclear. We characterized the spatial TIME in 144 treatment-naïve, early-stage LUADs using integrated genomic sequencing and multiplex immunohistochemistry (mIHC). Although EGFR-mutant tumors overall displayed reduced CD8 + T-cell infiltration compared with EGFR-wild-type tumors, substantial heterogeneity was observed among EGFR subtypes. Specifically, L858R and rare-variant subtypes exhibited higher tumor mutational burden, greater CD8 + T-cell density, and enrichment of T-cell-dominant cellular neighborhoods relative to 19del subtype, consistent with a comparatively immune-infiltrated phenotype. In contrast, 19del tumors showed lower T-cell infiltration. TP53 co-mutation was also associated with enhanced CD8 + T-cell infiltration. These cross-sectional findings identify hypothesis-generating spatial immune phenotypes across EGFR-mutant LUAD subtypes; their potential relevance to perioperative treatment selection requires prospective validation in outcome-annotated treatment cohorts.

Humans

Genetic insights into the relationship between age at menarche and mental health-related phenotypes.

BACKGROUND: Multiple observational studies have reported associations between age at menarche (AAM) and mental health problems, yet their shared genetic architecture remains poorly characterized. METHODS: We leveraged genome-wide association study summary statistics for AAM and 15 mental health-related phenotypes. We conducted a multi-method integrative analysis encompassing linkage disequilibrium score regression, pleiotropic analysis under the composite null hypothesis, functional mapping and annotation, multi-marker analysis of genomic annotation, pathway enrichment, and bidirectional two-sample Mendelian randomization (MR) to explore shared genetic architecture and potential causal relationships. RESULTS: Our study identified significant genetic correlations between AAM and eight mental health-related phenotypes (miserableness, fed-up feelings, nervous feelings, ever thought that life is not worth living, ever self-harmed, depression, ever smoker, and age started smoking in former smokers). A total of 155 pleiotropic loci, 18 colocalized loci (e.g., 6q16.3), and 203 pleiotropic genes (e.g., LIN28B) were identified. These genes are expressed in multiple regions, including the cerebral cortex and hypothalamus, and are involved in various biological processes and signaling pathways. Additionally, MR analysis revealed causal associations between AAM and 5 mental health-related phenotypes (mood swings, miserableness, fed-up feelings, and age at which smokers started smoking in former/current smokers). CONCLUSIONS: Our study revealed extensive genetic associations between AAM and mental health-related phenotypes, and further explored the potential causal relationships between them. These findings enhance our understanding of the relationship from a genetic perspective and establish a foundation for future research to explore the biological pathways and environmental interactions contributing to these associations.

Genome-Wide Association Study