Biomedical subjects

Jinying Zhao

Publications and source records attributed to Jinying Zhao.

5 recordsLinked to original sources

PubMed2026

DNA methylation signatures in skeletal muscle associated with physical function in healthy older adults.

Despite the substantial variability in physical function among older adults, the molecular mechanisms remain poorly characterized, particularly within skeletal muscle. This study aimed to determine the patterns of DNA methylation in skeletal muscle associated with physical function in healthy older adults. We analyzed DNA methylation (EPIC v2 array; 875,554 CpG sites) in skeletal muscle from 92 healthy older adults (median age 74; 62% female). Associations were examined across five phenotypes: Short Physical Performance Battery (SPPB), 6-min walk test (6MWT), handgrip strength, perceived disability (PAT-D), and lifestyle health (modified Life's Essential 8). Linear regression models adjusted for age, sex, race, BMI, and muscle fiber composition. Genomic inflation corrected via the BACON method (FDR < 0.05). Gene set enrichment analysis was performed on suggestive hits (FDR < 0.1). We identified significant differentially methylated probes (DMPs) and regions (DMRs) across all phenotypes: SPPB (70 DMPs, 22 DMRs), 6MWT (16 DMPs, 566 DMRs), handgrip strength (2 DMRs), PAT-D (19 DMPs, 1 DMR), and lifestyle health (2 DMPs). DMRs largely overlapped promoters. Identified genes overlapped known musculoskeletal and neurological GWAS hits, including RUNX2 and FOXL1 (bone mineral density), IGFBP3 (muscle mass), and NEK1 and SHANK1 (neurological function). Enrichment analysis revealed that 6MWT-associated genes relate to nervous and skeletal system development, while handgrip-associated genes involve cytoskeletal dynamics and protein assembly. Epigenetic variation in aging skeletal muscle is associated with physical function. The enrichment of pathways related to nervous and musculoskeletal development suggests specific epigenetic mechanisms underlying functional decline, offering potential targets for intervention in older adults.

DNA methylation↗

PubMed2005

An entropy-based statistic for genomewide association studies.

Efficient genotyping methods and the availability of a large collection of single-nucleotide polymorphisms provide valuable tools for genetic studies of human disease. The standard chi2 statistic for case-control studies, which uses a linear function of allele frequencies, has limited power when the number of marker loci is large. We introduce a novel test statistic for genetic association studies that uses Shannon entropy and a nonlinear function of allele frequencies to amplify the differences in allele and haplotype frequencies to maintain statistical power with large numbers of marker loci. We investigate the relationship between the entropy-based test statistic and the standard chi2 statistic and show that, in most cases, the power of the entropy-based statistic is greater than that of the standard chi2 statistic. The distribution of the entropy-based statistic and the type I error rates are validated using simulation studies. Finally, we apply the new entropy-based test statistic to two real data sets, one for the COMT gene and schizophrenia and one for the MMP-2 gene and esophageal carcinoma, to evaluate the performance of the new method for genetic association studies. The results show that the entropy-based statistic obtained smaller P values than did the standard chi2 statistic.

Entropy↗

PubMed2004

Network-based regulatory pathways analysis.

MOTIVATION: A useful approach to unraveling and understanding complex biological networks is to decompose networks into basic functional and structural units. Recent application of convex analysis to metabolic networks leads to the development of network-based metabolic pathway analysis and the decomposition of metabolic networks into metabolic extreme pathways that are true functional units of metabolic systems. Metabolic extreme pathways are derived from limited knowledge of the metabolic networks, but provide an integrated predictive description of metabolic networks. It is important to extend the concept of network-based metabolic pathways to genetic networks and develop mathematical procedures for network-based regulatory pathway analysis. RESULTS: We have established Kirchhoff's first law in genetic networks and introduced a concept of gene flows using matrix decomposition method. The Kirchhoff's first law provides the theoretical foundations for mathematical framework for development defining network-based regulatory pathways, and applying convex analysis in decomposing the genetic networks into regulatory extreme pathways. We presented a new approach to characterize the extreme pathway and developed a new algorithm for identifying a set of extreme pathways. Convex analysis and extreme pathway structure provide a unified framework for functional and structural analysis of metabolic and genetic networks, which will increase our ability to analyze, interpret and predict the function of metabolic and genetic networks. The proposed models for network-based regulatory pathway analysis have been applied to apoptosis regulatory network.

Algorithms↗

PubMed2003

Haplotype block linkage disequilibrium mapping.

Linkage disequilibrium (LD) mapping is emerging as a powerful alternative approach to identifying genes for complex disease. However, the feasibility and success of LD mapping depend largely on the extent and pattern of LD. Erratic pattern of pair-wise LD seriously compromises LD mapping. Recently discovered haplotype block structure dramatically alleviates the irregular pattern of LD and holds the promise for mapping complex disease genes. To facilitate applications of the haplotype block LD mapping, in this report we conduct theoretical analysis for haplotype block LD mapping. We present an overall LD measure of the haplotype to quantify the LD level of the haplotype block, between the haplotype blocks, and between the haplotype block and the marker locus. Most theoretical and empirical studies of the extent of LD and evaluation of the power of LD mapping have focused on pair-wise LD and single marker LD mapping. There is a lack of systematic and integrative analysis for the haplotype block LD mapping. In this report, we develop population genetic models of the haplotype blocks and analytic tools for calculation of noncentrality parameter of the statistic for the haplotype block LD mapping. We evaluate the impact of the population parameters and disease models on the power of the haplotype block LD mapping in the hope to improve its study design. We compare the powers of the single marker LD and haplotype block LD mapping. Haplotype block structure is an important discovery. Our preliminary results of theoretic analysis further demonstrate that the haplotype block LD analysis is a breakthrough in LD mapping and is a promising tool for genome-wide association studies.

Chromosome Mapping↗

PubMed2002

Generalized T2 test for genome association studies.

Recent progress in the development of single-nucleotide polymorphism (SNP) maps within genes and across the genome provides a valuable tool for fine-mapping and has led to the suggestion of genomewide association studies to search for susceptibility loci for complex traits. Test statistics for genome association studies that consider a single marker at a time, ignoring the linkage disequilibrium between markers, are inefficient. In this study, we present a generalized T2 statistic for association studies of complex traits, which can utilize multiple SNP markers simultaneously and considers the effects of multiple disease-susceptibility loci. This generalized T2 statistic is a corollary to that originally developed for multivariate analysis and has a close relationship to discriminant analysis and common measure of genetic distance. We evaluate the power of the generalized T2 statistic and show that power to be greater than or equal to those of the traditional chi2 test of association and a similar haplotype-test statistic. Finally, examples are given to evaluate the performance of the proposed T2 statistic for association studies using simulated and real data.

Algorithms↗