Publications by authors named "Xinghao Yu"

Background: Multiple Sclerosis (MS), an autoimmune disorder causing demyelination and neurological damage, has been linked to 25-hydroxyvitamin D (25OHD) levels, suggesting its role in immune response and MS onset. This study used GWAS datasets to investigate genetic associations between 25OHD and MS.

Methods: We utilized a large-scale prospective cohort to evaluate serum 25OHD levels and MS risk.

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Introduction: Previous studies have shown that inflammatory bowel disease (IBD) is associated with osteoporosis (OP) and bone mineral density (BMD), but the underlying genetic mechanisms are unclear. Our study wanted to explore the genetic and causal relationship between IBD and OP.

Materials And Methods: Based on large-scale genome-wide association summary statistics and individual-level datasets (i.

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Background: To study the shared genetic structure between autoimmune diseases and B-cell acute lymphoblastic leukemia (B-ALL) and identify the shared risk loci and genes and genetic mechanisms involved.

Methods: Based on large-scale genome-wide association study (GWAS) summary-level data sets, we observed genetic overlaps between autoimmune diseases and B-ALL, and cross-trait pleiotropic analysis was performed to detect shared pleiotropic loci and genes. A series of functional annotation and tissue-specific analysis were performed to determine the influence of pleiotropic genes.

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Introduction: Clinical observations have found that prolonged use of analgesics increases the incidence of infection. However, the direct causal relationship between prescription analgesic use (PAU) and risk of infection (ROI) remains unclear.

Methods: This study used Mendelian randomization (MR) design to estimate the causal effect of PAU on ROI, as well as their mediating factors.

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Objective: Maternal syphilis could cause serious consequences. The aim of this study was to identify risk factors for maternal syphilis in order to predict an individual's risk of developing adverse pregnancy outcomes (APOs).

Methods: A retrospective study was conducted on 768 pregnant women with syphilis.

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Purpose: To reveal relationship between air pollution exposure and osteoporosis (OP) risk.

Methods: Based on large-scale data from the UK Biobank, we evaluated the relationship between OP risk and several air pollutants. Then air pollution scores (APS) were constructed to assess the combined effects of multiple air pollutants on OP risk.

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Genomics involving tens of thousands of genes is a complex system determining phenotype. An interesting and vital issue is how to integrate highly sparse genetic genomics data with a mass of minor effects into a prediction model for improving prediction power. We find that the deep learning method can work well to extract features by transforming highly sparse dichotomous data to lower-dimensional continuous data in a non-linear way.

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Objective: This study aimed to identify novel genetic factors that contribute to body surface area (BSA) and explore its relationship with complex traits and diseases.

Methods: Based on more than 330,000 European individuals in the UK Biobank, the first large-scale genome-wide association study for BSA was performed. Comprehensive genetic analysis and enrichment analysis were then performed to explore the biological function of the identified loci.

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Recent evidence has gradually recognized that the immune and skeletal systems are two closely correlated systems, but the specific immune factors on bone mineral density (BMD) are largely unknown. Based on the summary-level data of genome-wide association studies (GWASs), we performed a series of analyses including two-sample Mendelian randomization (MR) analysis to test potential causal links between 731 immune traits [including median fluorescence intensities (MFIs), absolute cell (AC) counts, relative cell (RC) counts, and morphological parameters (MP)] and BMD. After false discovery rate (FDR) correction, 9 MFI-BMD, 16 AC-BMD, 22 RC-BMD, and 5 MP-BMD pairs reached the level of significance (FDR-adjusted < 0.

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We aimed to explore how healthy lifestyles and genetic factors influence the risk of Osteoporosis (OP). In this prospective cohort study, we first performed a genome-wide association study (GWAS) of estimated bone mineral density (eBMD) and constructed the genetic risk score (GRS) based on the effect of single nucleotide polymorphism (SNP) on eBMD. We then assessed the effect of three-level GRS and adherence to healthy lifestyles on the risk of OP and fracture, respectively.

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Purpose: Osteoporosis is associated with metabolic alterations, but the causal roles of serum metabolites on osteoporosis have not been identified.

Methods: Based on the large individual-level datasets from UK Biobank as well as GWAS summary datasets, we first constructed genetic risk scores (GRSs) for 308 of 486 human serum metabolites and evaluated the effect of each GRS on 2 major osteoporosis phenotypes, i.e.

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Background: Effective identification of high-risk rheumatoid arthritis (RA) individuals is still a challenge. Whether the combined effects of multiple previously reported genetic loci together with lifestyle factors can improve the prediction of RA risk remains unclear.

Methods: Based on previously reported results and a large-scale Biobank dataset, we constructed a polygenic risk score (PRS) for RA to evaluate the combined effects of the previously identified genetic loci in both case-control and prospective cohorts.

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Observational studies provide evidence that metabolites may be involved in the development of autoimmune diseases (ADs), but whether it is causal is still unknown. Based on the large-scale genome-wide association studies (GWAS) summary statistics, we performed two-sample Mendelian randomization (MR) to evaluate the causal associations between human blood metabolites and multiple ADs, which were inflammatory bowel disease (IBD), ulcerative colitis (UC), crohns disease (CD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), multiple sclerosis (MS), primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). After Bonferroni adjustment, we identified 6 causal features of metabolites, i.

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The correlation between autophagy defects and oral squamous cell carcinoma (OSCC) has been previously studied, but only based on a limited number of autophagy-related genes in cell lines or animal models. The aim of the present study was to analyze differentially expressed autophagy-related genes through The Cancer Genome Atlas (TCGA) database to explore enriched pathways and potential biological function. Based on TCGA database, a signature composed of four autophagy-related genes (, and ) was established by using multivariate Cox regression models and two Gene Expression Omnibus datasets were applied for external validation.

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Rheumatoid arthritis (RA) is associated with increased localized and generalized bone loss, but the complex genetic mechanism between them is still unknown. By leveraging large-scale genome-wide association studies summary statistics and individual-level datasets (i.e.

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The relationship between birth weight and osteoporosis was inconsistent in previous observational studies. Therefore, we performed a systematic evaluation to determine the inconsistent relationship and further make causal inference based on the UK Biobank datasets (~500,000 individuals) and individual/summary-level genetic datasets. Observational analyses found consistent negative associations either between birth weight and estimated bone mineral density (eBMD) or between genetic risk score (GRS) of birth weight and eBMD in total subjects, and sex-stratified subgroups.

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Observational studies have identified gout patients are often comorbid with dyslipidemia. However, the relationship between dyslipidemia and gout is still unclear. We first performed Mendelian randomization (MR) to evaluate the causal effect of four lipid traits on gout and serum urate based on publicly available GWAS summary statistics (n ~100,000 for lipid, 69,374 for gout and 110,347 for serum urate).

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Background: Previous cancer prognostic prediction models often consider only the most important transcriptomic expressions, and their power is limited. It is unknown whether prediction power can be further improved when additional transcriptomic information is incorporated.

Methods: To integrate transcriptomes, four models are compared based on 32 types of cancer in the Cancer Genome Atlas, including the general Cox model with only clinical covariates, the Cox model with a lasso penalty (coxlasso), the Cox model with an elastic net penalty (coxenet), and the mixed-effects Cox model (coxlmm).

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We employed Mendelian randomization (MR) to evaluate the causal relationship between leukocyte telomere length (LTL) and amyotrophic lateral sclerosis (ALS) with summary statistics from genome-wide association studies (n = ~ 38,000 for LTL and ~ 81,000 for ALS in the European population; n = ~ 23,000 for LTL and ~ 4,100 for ALS in the Asian population). We further evaluated mediation roles of lipids in the pathway from LTL to ALS. The odds ratio per standard deviation decrease of LTL on ALS was 1.

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Objective: Prior studies have shown that there is an inverse association between birth weight and stroke in adulthood; however, whether such association is causal remains yet known and those studies cannot distinguish between the direct fetal effect and the indirect maternal effect. The aim of the study is to untangle such relationship using novel statistical genetic approaches.

Methods: We first utilized linkage disequilibrium score regression (LDSC) and Genetic analysis incorporating Pleiotropy and Annotation (GPA) to estimate the overall genetic correlation between birth weight and stroke.

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Observational studies showed an inverse association between birth weight and chronic kidney disease (CKD) in adulthood existed. However, whether such an association is causal remains fully elusive. Moreover, none of prior studies distinguished the direct fetal effect from the indirect maternal effect.

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Observational studies have shown alcohol drinking behaviors may be associated with the risk of amyotrophic lateral sclerosis (ALS), but contradictory findings have emerged, and whether such an association is causal is unclear. We here investigate the causal relationship between alcohol consumption and ALS. By leveraging instruments from large-scale genome-wide association studies, we performed a comprehensive Mendelian randomization analysis and found alcohol consumption was causally associated with ALS, leading to ∼1.

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Background: The relationship between lipids and the risk of fracture is currently controversial and whether such association is causal remains elusive.

Methods: We performed two-sample inverse variance weighted (IVW) Mendelian randomization (MR) analyses to evaluate causal effects of four lipids (i.e.

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This systematic review was performed on the basis of Preferred Reporting Items for Systematic Reviews and Meta-analyses and Cochrane recommendations to compare sustained virological response (SVR12) and the serious adverse events in patients treated by directing-acting antivirals. We conducted a literature search in PubMed/Medline, EBSCO, Embase and the Cochrane Library until 2018. A consistency model was used to get the relative effect of odds ratio among regimens and the possibility for the efficacy and safety of 13 regimen, and we divided these regimens into DUAL or TRIO regimens to conduct integrated data analysis.

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