Human Genomics最新文献

Background/aims: The advent of genetic biobanking has powered gene-environment interaction (GxE) studies in various disease contexts. Therefore, we aimed to discover novel GxE effects that address hot spring residency as a risk to inconspicuous disease association.

Methods: A complete genetic and demographic registry comprising 129,451 individuals was obtained from Taiwan Biobank (TWB). After geographical disease prevalence was analyzed to identify putative disease association with hot-spring residency, multivariable regression and logistic regression were rechecked to exclude socioeconomic confounders in geographical-disease association. Genome-wide association study (GWAS), gene ontology (GO), and protein-protein interaction (PPI) analysis identified predisposing genetic factors among hotspring-associated diseases. Lastly, a polygenic risk score (PRS) model was formulated to stratify environmental susceptibility in accord with their genetic predisposition.

Results: After socioeconomic covariate adjustment, prevalence of dry eye disease (DED) was significantly associated with hot spring distribution. Through single nucleotide polymorphisms (SNPs) discovery and subsequent PPI pathway aggregation, CDKL2 kinase pathways were significantly enriched in hot-spring specific DED functional SNPs. Notably, PRS predicted disease well in hot spring regions (AUC = 0.9168). Hot spring and discovered SNPs contributed to crossover GxE effect on DED (relative risk (RR)_G+E-= 0.99; RR_G-E+ = 0.35; RR_G+E+ = 2.04).

Conclusion: We identified hot-spring exposure as a modifiable risk in the PRS-predicted GxE context of DED.

Introduction: Dabigatran is a direct oral anticoagulant associated with a high incidence of gastrointestinal bleeding, which presents a significant clinical concern. Genetic polymorphisms in the enzymes responsible for drug absorption (ABCB1) and activation (CES1) may influence dabigatran's pharmacokinetics, potentially altering drug concentration and therapeutic response. The current systematic review and meta-analysis aim to identify genetic variants correlated with dabigatran exposure and evaluate their importance.

Methods: We systematically searched PubMed, Web of Science, Scopus, Cochrane Library, and Embase to identify studies on dabigatran pharmacogenomics. The review included observational and clinical studies that met eligibility criteria. RevMan 5.4 was used to conduct the meta-analysis. Quality assessment was done using ROB 2.0 and NOS tools.

Results: Out of 1336 records retrieved, 1008 were screened, resulting in 16 studies included in the systematic review and 9 in the meta-analysis. Data from 3834 participants (61.8% males) were reviewed. For the ABCB1 polymorphism rs4148738, both CT and TT genotypes decreased C _trough compared to CC genotype (MD = - 9.82, 95% CI [- 17.65, - 1.99], P = 0.01) and (MD= - 7.69, 95% CI [- 15.54, 0.16], P = 0.05), respectively. While CES1 rs8192935 GG increased C _max compared to AA (MD = 22.66, 95% CI [5.04, 40.27], P = 0.01). For CES1 rs2244613 AA, both C _max and C _trough exhibited higher levels compared to GG (MD = 13.58, 95% CI [- 0.08,27.25], P = 0.05) and (MD = 13.41, 95% CI [8.05,18.77], P < 0.01), respectively. Also, compared to GG the heterozygote type GA increased the C _max (MD = 32.02, 95%CI [16.54,47.5], P < 0.01). Bleeding risk did not significantly differ across ABCB1 rs1045642, ABCB1 rs4148738 and CES1 rs8192935 polymorphisms. Only CES1 rs2244613 T allele showed significant effect on bleeding (OR = 2.43, P = 0.002). Stroke incidence did not differ across ABCB1 rs4148738, CES1 rs2244613, and CES1 rs8192935 genotypes.

Conclusion: ABCB1 rs4148738 T allele reduced dabigatran trough levels, while CES1 rs8192935 GG increased peak levels. CES1 rs2244613 TT raised both peak and trough levels, and its T allele was linked to higher bleeding risk. No consistent associations were found for other variants. These findings highlight CES1 rs2244613 as a key contributor to variability in dabigatran response, warranting further large-scale studies to confirm its role in personalized anticoagulation therapy.

Background: The weak splice acceptor site (AS) of exon 9 underlies almost all pathogenic variants of Cullin3 (CUL3) causing exon 9 skipping in Gordon syndrome, emphasizing the need for splicing-targeted therapeutic strategies. This study explored universal therapeutic targets to modulate AS and investigated their potential and mechanisms for restoring normal splicing.

Results: Through bioinformatic prediction, minigene assays, EMSA, CRISPR/Cas9-mediated construction of mutant cell lines and RIP, three rescue sites in the polypyrimidine (Py) tract of intron 8 were identified, including A(-9)T, A(-10)T and AA(-9, -10)TT, with AA(-9, -10)TT most effectively promoting exon inclusion by extending the Py-tract to increase U2AF2 binding. Additionally, previous candidate target A18G was confirmed to rescue exon 9 skipping by weakening hnRNP A1 splicing inhibition in endogenous cell models.

Conclusions: Our findings highlight the therapeutic potential of AA(-9, -10)TT and A18G in CUL3-related Gordon syndrome, suggesting the targeted modification of cis-elements could be an ideal and universal strategy to develop treatments for splicing-related diseases.

Objective: Ulcerative colitis (UC), a chronic inflammatory bowel disease, continues to pose substantial challenges in both diagnosis and treatment. The aryl hydrocarbon receptor (AhR) plays a pivotal role in intestinal immune regulation; however, its core regulatory network in the progression of UC remains largely undefined. This study aims to identify core UC-related genes associated with AhR and to validate their expression in dextran sulfate sodium (DSS)-induced murine models, thereby elucidating potential mechanisms underlying UC progression.

Methods: Using the GSE75214 and GSE87466 datasets from the Gene Expression Omnibus (GEO) database, immune cell infiltration was quantified via the CIBERSORT algorithm. Candidate genes were identified through differential expression analysis, weighted gene co-expression network analysis (WGCNA) module selection, and construction of an AhR co-expression network. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were performed, followed by construction of a protein-protein interaction (PPI) network using STRING and application of two machine learning algorithms to identify AhR-associated hub genes. Finally, the expression of key genes was validated in DSS-induced UC mouse models using real-time quantitative real-time quantitative polymerase chain reaction (RT-qPCR).

Results: A total of nine AHR-related shared genes were identified, which were significantly enriched in immune response, amino acid metabolism, and oxidative stress pathways. Through integration of the PPI network and machine learning approaches, three central hub genes (PPARG, IL1B, and IDO1) were identified. Immune infiltration analysis revealed pronounced immune dysregulation during the progression of UC, which may contribute to disease development. Animal experiments confirmed the expression of these three key genes in colonic tissues, and hematoxylin-eosin (H&E) staining revealed extensive infiltration of inflammatory cells, consistent with the bioinformatics findings.

Conclusion: PPARG, IL1B, and IDO1 were identified as potential key genes closely associated with AHR, suggesting their possible involvement in modulating AhR signaling in UC, thereby offering a theoretical basis for disease diagnosis and therapeutic strategies.

Aging, a complex biological process, entails sequential changes in organisms that elevate the risk of frailty, disease, and mortality, affecting individuals at the level of cellular, organ, and organism. This process is influenced by genetic diversity, socioeconomic status, healthcare infrastructure, lifestyle choices, and cultural practices. Gerontology delves into the factors shaping longevity, aging processes, and aging from both evolutionary and individual perspectives. Centenarians and supercentenarians serve as models for studying exceptional longevity, offering insights into the aging process and resistance to age-related diseases. This research investigates common genetic variations (SNPs) shared among 3 centenarians and 18 supercentenarians, individuals aged 110 years or older. 754,520 SNPs were found to be common among all the 21 samples. Utilizing SNPnexus, a genetic variant annotation tool, we annotated coding variants and assessed potential disease susceptibilities associated with these variants. Ensembl was used as an annotation system, we annotated 1,607,122 variants, and found 11,348 coding variants. Among them, 4980 had non-synonymous variants, and 110 variants were observed to have deleterious effects. These deleterious SNPs were linked with 79 genes among them 16 novel variants were identified in 9 genes. The population frequency comparison using the 1000 Genomes Project and gnomAD revealed that a subset of these common, non-synonymous SNPs and deleterious SNPs had minor allele frequencies (MAF) below 1% or were absent entirely, suggesting potential rare variants specific to this cohort. In addition, we also found statistically significant (p < 0.05) 148 enriched pathways, among them the top enriched pathways such as extracellular matrix (ECM) remodeling, signal transduction, disease-associated pathways, sensory processing and metabolism of proteins and RNA. These preliminary findings may help prioritize candidate variants and genes for future studies on larger cohorts with appropriate controls can help in understanding the genetic basis of exceptional longevity.

Background: Gitelman syndrome (GS) is a rare tubulopathy with clinical and genetic heterogeneity. This study aimed to investigate the characteristics of Chinese GS patients.

Methods: The diagnosis of GS was established by combining clinical phenotypes with genetic testing, after which the clinical, biochemical, and genetic data were statistically analyzed.

Results: We reported 95 Chinese GS patients aged 2-52 years. The younger group (≤ 16 years) had more frequent febrile episodes (20.4% vs. 4.3%, P = 0.028) and nausea/vomiting (12.2% vs. 0.0%, P = 0.027) but fewer paresthesia/numbness (20.4% vs. 43.5%, P = 0.026) and palpitations (8.2% vs. 37.0%, P = 0.001), along with higher serum potassium and magnesium levels (2.86 ± 0.45 mmol/L vs. 2.67 ± 0.38 mmol/L, P = 0.034; 0.65 ± 0.14 mmol/L vs. 0.58 ± 0.16 mmol/L, P = 0.031) than the older group (> 16 years). Moreover, serum potassium and magnesium levels were positively correlated and both were negatively correlated with age. Additionally, Among 170 detected SLC12A3 variants, 73 distinct variants were identified, including six novel ones. The compound heterozygous group exhibited higher serum magnesium levels compared to the heterozygous and homozygous groups (0.65 ± 0.17 mmol/L vs. 0.56 ± 0.09 mmol/L, P = 0.015; 0.65 ± 0.17 mmol/L vs. 0.51 ± 0.07 mmol/L, P < 0.001). Age at diagnosis was associated with variant types.

Conclusion: The study characterized the phenotypic and genotypic features of Chinese GS patients, highlighting age and mutation genotype as key factors influencing phenotype, underscoring the importance of standardized potassium and magnesium supplementation, and expanding the known mutation spectrum with novel variants.

Background: Recurrent acute liver failure (RALF) is a rare and life-threatening disorder often triggered by infections or febrile episodes. Variants in genes regulating vesicular transport, including RINT1, NBAS have been implicated in RALF and are classified as infantile liver failure syndromes type 2 and 3 (ILFS2 and ILFS3), often associated with multisystemic manifestations.

Methods: We conducted comprehensive clinical, laboratory and genetic evaluations of a proband presenting with RALF and neutropenia. Whole-exome sequencing (WES), whole-genome sequencing (WGS), Sanger analysis, autozygosity mapping and 3D protein structural modeling were conducted to identify and characterize the pathogenic variant.

Results: A novel homozygous variant in the RINT1 gene (NM_021930.6:c.1435G > C, p.Ala479Pro) was identified in a proband from Chuvashia presenting with RALF and neutropenia, with both parents confirmed as heterozygous carriers. Structural modeling suggested a destabilizing effect on the RINT1/TIP20 domain. Two siblings with identical symptoms further supported the pathogenicity of this variant and its autosomal recessive inheritance. Runs of homozygosity (ROH) analysis indicated a possible founder effect in the Chuvash population. Our study expands the phenotypic spectrum of RINT1-related ILFS3, which in this case lacked the skeletal or neurological features previously described but included neutropenia.

Conclusion: We report a novel RINT1 variant cause ILFS3 and neutropenia, supporting its classification as a potential population-specific disorder. These findings highlight the importance of early genetic screening and clinical monitoring in affected populations.

Background: Limited drug treatment data are available for osteomyelitis (OM), an inflammatory bone condition secondary to infection. Given its genetic characteristics, it is necessary to integrate genetics into drug development for osteomyelitis. This study applied pharmacogenomics to identify new drug targets for osteomyelitis using Mendelian randomization (MR).

Methods: Following the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization guidelines, expression and protein quantitative trait loci (QTL) analysis was applied to simulate drug exposure. Single nucleotide polymorphisms were selected as instrumental variables for MR analysis using blood QTL data and independent osteomyelitis genome-wide association study datasets from UK Biobank and FinnGen R10. A random-effects model meta-analysis combining the results from two datasets was performed. Bayesian co-localization analysis was conducted to validate the targets. Sensitivity analyses were performed using various MR methods, with MR-Egger regression and Cochran's Q test being conducted to assess the horizontal pleiotropy and heterogeneity of the instrumental variables.

Results: At α = 1 × 10^-5, the meta-analysis identified 12 drug target mechanisms. Gene expression of QDPR, TGM1, NTSR1, CBR3, and NEK6 was positively correlated with osteomyelitis risk, whereas HLA-DRB1, LAMC1, LTB4R, MAPK3, FPR1, ABAT, and LTA4H were negatively correlated with this risk. Five potential drug repurposing opportunities and three drugs that may increase osteomyelitis risk were identified. Sensitivity analyses highlighted LTA4H, LAMC1, QDPR, and NEK6 as having the strongest genetic evidence based on MR-Egger regression and protein QTL tests.

Conclusions: This study identified 12 new genetically supported drug targets for osteomyelitis, thereby providing a genetic foundation for new drug development, repurposing existing drugs, and personalized treatment.

Background: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide. Despite advancements in treatment, drug resistance and limited therapeutic efficacy persist, underscoring the urgent need for novel and mechanistically informed therapeutic strategies. Identifying genetically supported drug targets may accelerate the development of precision therapies in NSCLC.

Methods: We implemented an integrative multi-omics framework combining single-cell RNA sequencing (scRNA-seq), genome-wide association studies (GWAS), and molecular quantitative trait locus (QTL) datasets including expression (eQTL), protein (pQTL), and DNA methylation (mQTL) QTLs. Druggable candidates were systematically evaluated using a suite of Mendelian randomization (MR) approaches-including summary data-based MR (SMR), generalized SMR (GSMR), and genetic risk score (GRS) analysis. Epigenetic regulation and downstream signaling were further explored through mediation MR analysis.

Results: C4BPA, a complement-regulatory macromolecule, emerged as a risk factor for NSCLC across multiple MR models, with consistent findings validated at both transcriptomic and proteomic levels. Epigenetic activation of C4BPA via DNA methylation was observed, and C4BPA expression was shown to promote NSCLC progression through the inflammatory chemokine CCL8 signaling axis. Sensitivity analyses confirmed the robustness of association inference.

Conclusions: Our findings identify C4BPA as a genetically validated and biologically plausible therapeutic target for NSCLC. This study demonstrates the power of integrating single-cell transcriptomics with population-scale omics and association inference to uncover actionable targets, offering a scalable framework for advancing precision oncology in lung cancer.