Human Genomics最新文献

Background: Gyrate atrophy (GACR), a rare autosomal recessive chorioretinal dystrophy caused by OAT mutations, is genetically and clinically underexplored in multi-ethnic Chinese populations.

Results: Eight patients from five families all exhibited high myopia (mean - 8.28 D), early-onset vision loss, and elevated plasma ornithine. Parapapillary atrophy (PPA) was common (76.92%) and correlated with worse BCVA and longer AL. Four novel OAT mutations were identified: c.213G > A (p.Trp71Ter), c.799 A > C (p.Thr267Pro), c.897 C > A (p.Tyr299Ter) and c.-30 + 22_-30 + 43del. Minigene assays confirmed aberrant splicing for the latter.

Conclusions: This study identifies the first pathogenic 5' UTR variant in GACR, reveals ethnic-specific mutation profiles, and underscores PPA as a severity-linked feature.

Background: Recent studies have shown that unhealthy sleep behaviors are associated with chronic liver disease. However, the association of sleep patterns and genetic susceptibility with the incidence of cirrhosis remains inadequately elucidated.

Methods: This study included 364,308 participants initially free of liver cirrhosis from the UK Biobank. Sleep patterns were derived based on five self-reported sleep behaviors, including sleep duration, chronotypes, insomnia, snoring, and daytime sleepiness. Additionally, a polygenic risk score for cirrhosis was constructed for each participant. Cox regression models were utilized to estimate the hazard ratio (HR) and 95% confidence interval (CI) of cirrhosis associated with sleep patterns and polygenic risk score.

Results: During a median follow-up of 12.6 years, we recorded 1,814 cirrhosis events. Compared with healthy sleep patterns, the HRs (95% CI) for moderate and poor sleep patterns were 1.27 (95% CI: 1.14-1.42) and 1.73 (95% CI: 1.45-2.08), respectively. A joint effect of sleep and genetic factors on cirrhosis risk was observed, with HR reaching 3.50 (95% CI: 2.42-5.06) with poor sleep patterns and high genetic risk compared with those with healthy sleep patterns and low genetic risk. In addition, the high genetic risk for participants, poor sleep patterns of standardized decade liver cirrhosis were 0.49%, as opposed to 0.30% for those with healthy sleep patterns. The same trend was witnessed in individuals at low genetic risk.

Conclusions: Our results show that the healthy sleep patterns are associated with a lower risk of incident liver cirrhosis, especially in individuals with high genetic susceptibility.

The 5-lipoxygenase-activating protein (FLAP) is an integral membrane protein that is essential for 5-lipoxygenase-mediated leukotriene formation, thereby playing a key role in inflammation and serving as a potential therapeutic target. For over 30 years, researchers have been elucidating the crystal structure, identifying the inhibitor binding site, and developing several potent inhibitors, which have been investigated in preclinical and clinical studies to treat asthma, chronic kidney and cardiovascular diseases. However, despite being almost overlooked, more than 20,000 single nucleotide polymorphisms (SNPs) were detected in the ALOX5AP gene, coding for FLAP. To date, 66 SNPs have been studied in relation to a disease by different researchers, including different population groups. This review aims to synthesize current evidence on genetic variants of FLAP and delineate single SNPs that have been primarily implicated in coronary artery disease, myocardial infarction, and ischemic stroke. Associations between SNPs of ALOX5AP and these diseases have been reported, but findings remain inconsistent due to differences in study design, population diversity and methodological approaches. Although meta-analyses helped to integrate the results of different studies, they remain limited due to underlying differences and cannot provide a definitive conclusion.

Background: Idiopathic pulmonary fibrosis (IPF) is a type of progressive interstitial lung disease with an unclear cause and generally poor prognosis. Phospholipids have been implicated in IPF, motivating this investigation into phospholipid-associated biomarkers for diagnostic and prognostic use.

Materials and methods: To identify genes with differential expression, the microarray data from multiple datasets were integrated. A weighted gene co-expression network analysis (WGCNA) was conducted to highlight key modules and genes related to phospholipids in IPF. Genes related to phospholipid were sourced from the GeneCards database, and the intersection of genes with differential expression, WGCNA findings, and phospholipid-associated genes yielded the hub genes. Machine learning techniques were then utilized to construct diagnostic and prognostic models, which were subsequently tested across multiple datasets. Key genes were further confirmed through single-cell sequencing and animal model validation.

Results: Analysis of eight datasets uncovered 920 differentially expressed genes. WGCNA identified the turquoise module (1,884 genes), which overlapped with 1,031 phospholipid-related genes, leading to the identification of 50 hub genes. An 8-gene diagnostic model and an 11-gene prognostic model were developed, both exhibiting superior predictive accuracy compared to previously established models. GABARAPL1 and UNC13B, two key genes, were validated via single-cell sequencing, revealing a reduced proportion of fibroblasts expressing these genes in IPF lungs relative to controls. Additionally, both genes were found to be downregulated in IPF mouse models.

Conclusion: This research successfully identified potential biomarkers for IPF and developed a prognostic model based on liquid biopsy and a diagnostic model based on lung tissue. Further validation is required to assess their clinical applicability.

Background: Neuroblastoma, a clinically heterogeneous pediatric tumor, has varying outcomes ranging from spontaneous regression to aggressive metastasis. Recent studies have emphasized non-coding RNAs, particularly long non-coding RNAs (lncRNAs), as crucial regulators of cancer epigenetics. MALAT1 is a dual oncogenic lncRNA with some therapeutic potential but has rarely been studied in neuroblastoma.

Methods: We genotyped three MALAT1 polymorphisms (rs591291 C > T, rs619586 A > G, and rs3200401 C > T) in 402 neuroblastoma patients and 473 controls via TaqMan. Further stratification analysis was conducted to evaluate the potential associations of rs591291 and rs619586 with neuroblastoma risk. Through the GTEx database, we also investigated the impact of MALAT1 gene polymorphisms on the expression of nearby genes and splicing variants. Finally, Kaplan‒Meier analysis conducted via the R2 platform demonstrated the correlation between gene expression and the prognosis of neuroblastoma patients.

Results: We discovered that the MALAT1 gene rs619586 A > G polymorphism significantly reduced neuroblastoma risk, whereas rs3200401 C > T increased the risk of neuroblastoma. Stratification analysis revealed that these significant associations were more pronounced in specific subgroups. Moreover, MALAT1 rs619586 A > G and rs3200401 C > T are significantly associated with increased expression of another lncRNA, NEAT1. These findings indicate that reduced expression of the NEAT1 gene is linked to a greater risk and poorer prognosis for neuroblastomas.

Conclusions: MALAT1 rs619586 A > G and rs3200401 C > T significantly contribute to susceptibility to neuroblastoma, and further research is needed to investigate the underlying mechanisms involved.