Biomedical subjects

Pengyuan Liu

Publications and source records attributed to Pengyuan Liu.

9 recordsLinked to original sources

PubMed2025

Immune Cell Type-Specific DNA Methylation Regions Associate With 24-Hour Blood Pressure Regulation in Black People.

BACKGROUND: DNA methylation and immune cells have been linked to blood pressure (BP) regulation and the development of hypertension. However, the immune cell profiles and the cell type-specific DNA methylation associated with BPs remain unclear. METHODS: This study evaluates the 19 cell type deconvolution algorithms using reduced representation bisulfite sequencing data, comparing them to in silico mixtures derived from whole-genome bisulfite sequencing. The top-performing algorithm, Epigenetic Dissection of Intra-Sample Heterogeneity (EpiDISH)-Robust Partial Correlations, was applied to 281 Black inpatients with 24-hour BP monitoring. The immune cell profiles and cell type-specific DNA methylation regions associated with these BP phenotypes were further investigated using regression analysis. RESULTS: In patients with hypertension, B-cell and CD4 effector memory T-cell abundances were significantly elevated. Monocyte and CD8 effector memory T-cell fractions positively correlated with nighttime BP, and CD3 T cells were inversely associated with office BP. These associations remained robust after covariate adjustments and were partially validated in the Medical Information Mart for Intensive Care-IV cohort. For the first time, we identified several cell type-specific DNA methylation regions as being associated with BP phenotypes and patterns across 13 immune cells, with approximately one third predominantly found in effector CD8 T cells. CONCLUSIONS: These findings provide novel insights into the epigenetically regulated immune mechanisms underlying BP regulation and identify potential targets for hypertension management.

Humans↗

PubMed2024

Mediating effects of BMI on the association between DNA methylation regions and 24-h blood pressure in African Americans.

BACKGROUND: DNA methylation is an important epigenetic mechanism that may influence blood pressure (BP) regulation and hypertension risk. Obesity, a major lifestyle factor associated with hypertension, may interact with DNA methylation to affect BP. However, the indirect effect of DNA methylation on 24-h BP measurements mediated by obesity-related phenotypes such as BMI has not been investigated. METHODS: Causal mediation analysis was applied to examine the mediating role of BMI in the relation between DNA methylation and 24-h BP phenotypes, including SBP, DBP and mean arterial blood pressure (MAP), in 281 African American participants. RESULTS: Analysis of 38 215 DNA methylation regions, derived from 1 549 368 CpG sites across the genome, identified up to 138 methylation regions that were significantly associated with 24-h BP measurements through BMI mediation. Among them, 38 (19.2%) methylation regions were concurrently associated with SBP, DBP and MAP. Genes associated with BMI-mediated methylation regions are potentially involved in various chronic diseases such as coronary artery disease and renal disease, which are often caused or exacerbated by hypertension. Notably, three genes ( CDH4 , NOTCH1 and COLGALT1 ) showed both direct associations with 24-h BP measurements and indirect associations through BMI after adjusting for age and sex covariates. CONCLUSION: Our findings suggest that DNA methylation may contribute to the regulation of 24-h BP in African Americans both directly and indirectly through BMI mediation.

Humans↗

PubMed2006

Candidate lung tumor susceptibility genes identified through whole-genome association analyses in inbred mice.

We performed a whole-genome association analysis of lung tumor susceptibility using dense SNP maps ( approximately 1 SNP per 20 kb) in inbred mice. We reproduced the pulmonary adenoma susceptibility 1 (Pas1) locus identified in previous linkage studies and further narrowed this quantitative trait locus (QTL) to a region of less than 0.5 Mb in which at least two genes, Kras2 (Kirsten rat sarcoma oncogene 2) and Casc1 (cancer susceptibility candidate 1; also known as Las1), are strong candidates. Casc1 knockout mouse tumor bioassays showed that Casc1-deficient mice were susceptible to chemical induction of lung tumors. We also found three more genetic loci for lung adenoma development. Analysis of one of these candidate loci identified a previously uncharacterized gene Lasc1, bearing a nonsynonymous substitution (D102E). We found that the Lasc1 Glu102 allele preferentially promotes lung tumor cell growth. Our findings demonstrate the prospects for using dense SNP maps in laboratory mice to refine previous QTL regions and identify genetic determinants of complex traits.

Adenoma↗

PubMed2006

Paternal uniparental isodisomy of the entire chromosome 3 revealed in a person with no apparent phenotypic disorders.

Uniparental disomy (UPD) is a rare genetic abnormality. During a whole genome linkage study we identified a case of paternal uniparental isodisomy 3 serendipitously. This is the first ascertained human paternal UPD for chromosome 3 (UPD3pat). The finding of this paternal UPD case of the entire chromosome 3 with no apparent phenotypic disorders suggests that there are no paternal imprinted genes causing rare genetic disorders on chromosome 3.

Alleles↗

PubMed2004

A two-step strategy for detecting differential gene expression in cDNA microarray data.

A mixed-model approach is proposed for identifying differential gene expression in cDNA microarray experiments. This approach is implemented by two interconnected steps. In the first step, we choose a subset of genes that are potentially expressed differentially among treatments with a loose criterion. In the second step, these potential genes are used for further analyses and data-mining with a stringent criterion, in which differentially expressed genes (DEGs) are confirmed and some quantities of interest (such as gene x treatment interaction) are estimated. By simulating datasets with DEGs, we compare our statistical method with a widely used method, the t-statistic, for single genes. Simulation results show that our approach produces a high power and a low false discovery rate for DEG identification. We also investigate the impacts of various source variations resulting from microarray experiments on the efficiency of DEG identification. Analysis of a published experiment studying unstable transcripts in Arabidopsis illustrates the utility of our method. Our method identifies more novel and biologically interesting unstable transcripts than those reported in the original literature.

Arabidopsis↗

PubMed2004

Nonreplication in genetic studies of complex diseases--lessons learned from studies of osteoporosis and tentative remedies.

Inconsistent results have accumulated in genetic studies of complex diseases/traits over the past decade. Using osteoporosis as an example, we address major potential factors for the nonreplication results and propose some potential remedies. Over the past decade, numerous linkage and association studies have been performed to search for genes predisposing to complex human diseases. However, relatively little success has been achieved, and inconsistent results have accumulated. We argue that those nonreplication results are not unexpected, given the complicated nature of complex diseases and a number of confounding factors. In this article, based on our experience in genetic studies of osteoporosis, we discuss major potential factors for the inconsistent results and propose some potential remedies. We believe that one of the main reasons for this lack of reproducibility is overinterpretation of nominally significant results from studies with insufficient statistical power. We indicate that the power of a study is not only influenced by the sample size, but also by genetic heterogeneity, the extent and degree of linkage disequilibrium (LD) between the markers tested and the causal variants, and the allele frequency differences between them. We also discuss the effects of other confounding factors, including population stratification, phenotype difference, genotype and phenotype quality control, multiple testing, and genuine biological differences. In addition, we note that with low statistical power, even a "replicated" finding is still likely to be a false positive. We believe that with rigorous control of study design and interpretation of different outcomes, inconsistency will be largely reduced, and the chances of successfully revealing genetic components of complex diseases will be greatly improved.

Animals↗

PubMed2004

Marker-assisted selection in segregating generations of self-fertilizing crops.

Computer simulations were used to study the efficiency of MAS for breeding self-fertilizing crops, based on a general model including additive, dominance and epistasis. It was shown that MAS not only gave larger genetic responses but also dramatically increased the frequencies of superior genotypes as compared with phenotypic selection. However, the advantages of MAS over phenotypic selection were considerably reduced when conducting selection in later generations. A modified method combining MAS in early generations with phenotypic selection in later generations was thus proposed from an efficiency standpoint. We also proposed a potential index to measure the probability of an individual showing superior genotypes under selfing. It was apparent that more superior genotypes could be derived from selection by using the potential index than by using other methods. The implications of these findings for plant breeding are discussed.

Breeding↗

PubMed2003

Interaction effects between estrogen receptor alpha gene, vitamin D receptor gene, age, and sex on bone mineral density in Chinese.

We evaluated the interaction effects between the estrogen receptor alpha gene (ER-alpha), vitamin D receptor gene (VDR), age and sex on bone mineral density (BMD) in a sample of 340 unrelated males and 297 unrelated females from 401 Chinese nuclear families. Polymorphisms of PvuII and XbaI in the ER-alpha gene and ApaI in the VDR gene were detected by RFLP, and ER-alpha genotype was defined by the haplotype reconstructed according to the two loci. In the females, significant ER-VDR gene interaction ( P<0.05) was found on the lumbar spine BMD. Such interaction might account for approximately 1.0% of the BMD variation. At the femoral neck and trochanter, significant ER-age interaction effects were observed, which might explain 0.3% BMD variation for both skeletal sites. In the males, significant VDR-age interaction was found on femoral neck BMD ( P<0.05), and it accounted for 0.6% BMD variation. These interaction effects were largely dependent on gender groups, suggesting there may exist ER-VDR-sex, ER-age-sex, and VDR-age-sex complex interactions in our Chinese sample.

Age Factors↗

PubMed2003

A method for marker-assisted selection based on QTLs with epistatic effects.

A method for marker-assisted selection (MAS) based on quantitative trait loci (QTLs) with epistatic effects is proposed. The efficiency of such method is investigated by simulations under a wide range of situations. In the presence of epistasis, MAS generally yields longer persistence response than that based exclusively on additive or additive and dominance. Neglecting epistasis could result in considerable loss in response, and more pronounced at later generations. In addition to population size and trait heritability, genetic variance configurations play an important role in determining both the short- and long-term efficiencies of MAS. MAS using breeding values not only achieves higher response, but also tends to have smaller standard error than other methods in most cases. Errors in QTL detection cause distinct reductions in responses to MAS in most cases. It is thus concluded that verifications of putative QTL and its magnitude of effect and accurate map chromosome location are imperative to realize the potentials of MAS.

Epistasis, Genetic↗