Biomedical subjects

Shuang Liang

Publications and source records attributed to Shuang Liang.

3 recordsLinked to original sources

PubMed2026

Joint Effects of Long-Term Obesity and Genetic Susceptibility on Sex-Specific Brain Aging.

OBJECTIVE: This study aimed to examine the associations of longitudinal obesity trajectories and polygenic risk with sex-specific brain aging. METHODS: We analyzed 35,092 UK Biobank participants (16,484 males and 18,608 females). Sex-specific XGBoost models estimated multimodal brain age. We derived 16-year longitudinal obesity trajectories from repeatedly collected anthropometric measurements. Polygenic risk scores were constructed based on 55 independent genetic loci. Multivariable logistic regression examined associations of obesity trajectories and genetic risk with brain age acceleration. RESULTS: A total of 8198 (49.73%) males and 9089 (48.84%) females had accelerated brain aging. High genetic risk significantly increased brain age acceleration odds (males: OR = 1.39; females: OR = 1.34). Crucially, the high-stable obesity trajectory exerted a stronger effect in males (OR = 1.90, 95% CI: 1.64-2.21) than in females (OR = 1.25, 95% CI: 1.12-1.40), with the joint presence of high genetic risk and high-stable obesity amplifying risk to an OR of 2.78 in males and 1.57 in females. Conversely, shifting from obesity to non-obesity reduced risk by 30% in males and 18% in females. CONCLUSIONS: These findings underscore long-term obesity as a critical, sex-dimorphic driver of accelerated brain aging, and midlife weight management offers robust neuroprotection even in genetically susceptible individuals.

brain aging↗

PubMed2025

Systematic mining and quantification reveal the dominant contribution of non-HLA variations to acute graft-versus-host disease.

Human leukocyte antigen (HLA) disparity between donors and recipients is a key determinant triggering intense alloreactivity, leading to a lethal complication, namely, acute graft-versus-host disease (aGVHD), after allogeneic transplantation. Moreover, aGVHD remains a cause of mortality after HLA-matched allogeneic transplantation. Protocols for HLA-haploidentical hematopoietic cell transplantation (haploHCT) have been established successfully and widely applied, further highlighting the urgency of performing panoramic screening of non-HLA variations correlated with aGVHD. On the basis of our time-consecutive large haploHCT cohort (with a homogenous discovery set and an extended confirmatory set), we first delineated the genetic landscape of 1366 samples to quantitatively model aGVHD risk by assessing the contributions of HLA and non-HLA genes together with clinical factors. In addition to identifying multiple loss-of-function (LoF) risk variations in non-HLA coding genes, our data-driven study revealed that non-HLA genetic variations, independent of HLA disparity, contributed the most to the occurrence of aGVHD. This unexpected major effect was verified in an independent cohort that received HLA-identical sibling HCT. Subsequent functional experiments further revealed the roles of a representative non-HLA LoF gene and LoF gene pair in regulating the alloreactivity of primary human T cells. Our findings highlight the importance of non-HLA genetic risk in the new era of transplantation and propose a new direction to explore the immunogenetic mechanism of alloreactivity and to optimize donor selection strategies for allogeneic transplantation.

Humans↗

PubMed2024

metaExpertPro: A Computational Workflow for Metaproteomics Spectral Library Construction and Data-Independent Acquisition Mass Spectrometry Data Analysis.

Analysis of large-scale data-independent acquisition mass spectrometry metaproteomics data remains a computational challenge. Here, we present a computational pipeline called metaExpertPro for metaproteomics data analysis. This pipeline encompasses spectral library generation using data-dependent acquisition MS, protein identification and quantification using data-independent acquisition mass spectrometry, functional and taxonomic annotation, as well as quantitative matrix generation for both microbiota and hosts. By integrating FragPipe and DIA-NN, metaExpertPro offers compatibility with both Orbitrap and timsTOF MS instruments. To evaluate the depth and accuracy of identification and quantification, we conducted extensive assessments using human fecal samples and benchmark tests. Performance tests conducted on human fecal samples indicated that metaExpertPro quantified an average of 45,000 peptides in a 60-min diaPASEF injection. Notably, metaExpertPro outperformed three existing software tools by characterizing a higher number of peptides and proteins. Importantly, metaExpertPro maintained a low factual false discovery rate of approximately 5% for protein groups across four benchmark tests. Applying a filter of five peptides per genus, metaExpertPro achieved relatively high accuracy (F-score = 0.67-0.90) in genus diversity and showed a high correlation (rSpearman = 0.73-0.82) between the measured and true genus relative abundance in benchmark tests. Additionally, the quantitative results at the protein, taxonomy, and function levels exhibited high reproducibility and consistency across the commonly adopted public human gut microbial protein databases IGC and UHGP. In a metaproteomic analysis of dyslipidemia patients, metaExpertPro revealed characteristic alterations in microbial functions and potential interactions between the microbiota and the host.

Proteomics↗