Human Genomics最新文献

Background: Hearing loss (HL) is a prevalent disease in children, and conventional neonatal hearing screening has a limited effect. The objective of this study was to analyze the frequency of frequent deafness-associated variants [GJB2, GJB3, SLC26A4, and MTRNR1 (12 S rRNA)] in neonates from South China and determine the risk of hereditary HL through combined genetic and hearing screening.

Methods: A cohort of 38,589 neonates was enrolled between November 2019 and June 2022 in South China. All participants underwent genetic and hearing screenings. High-risk neonates were followed up, and data were analyzed to evaluate the correlation between genetic results and hearing outcomes.

Results: The high-risk rate was 1.80% (694/38589), and the carrier rate was 24.20% (9338/38589). The most frequent allele was GJB2 c.109G > A (10.43%, 8049/77178), followed by GJB2 c.235delC (0.77%, 594/77178) and SLC26A4 c.919-2 A > C (0.50%, 385/77178). Of the 694 high-risk neonates, 403 participated in follow-up. The failure or recommended reexamination rate at the first hearing screening (48-72 h) was 50.38% (203/403), and the HL diagnosis rate at three months was 30.48% (42/140).

Conclusions: The carrier rates of deafness-related gene mutations in South China were determined. Additionally, certain high-risk neonates developed HL and benefited from follow-up and intervention. Genetic screening can improve early diagnosis and facilitate identification of late-onset cases, resulting in timely clinical recommendations.

Cerebral Cavernous Malformations (CCMs) are brain vascular lesions that occur in sporadic or inherited (autosomal dominant) forms. The malformations are driven by mutations in KRIT1, CCM2, PDCD10 or MAP3K3. Known oncogenic variants in PIK3CA accompany CCM-specific variants in lesions. While the primary genetic etiology of CCM lesions is relatively well understood, a subset of lesions does not yet have an identified molecular genetic etiology. Moreover, whether large genomic alterations occur somatically in CCM lesion tissue has been largely unexplored. In PIK3CA + cancers, large somatic copy number alterations ('CNAs') are frequent, with whole genome doubling and aneuploidy identified in most tumors. Such CNA events are known to be associated with course of disease and therapeutic response. In this study, using whole genome SNP-genotyping and Mosaic Chromosome Alteration (MoChA) analysis, we identify the presence of large (> 1 MB) somatic CNAs in CCMs, with specific enrichment of events in chromosome arms 16p,19p,17q, 20q. We also identify additional chromosome arm level events encompassing known CCM genes in a subset of lesions. Thus, we characterize a pattern of large genomic events that had remained hidden by the insensitivity of the molecular and analytical methods previously used. Finally, we propose that similar events may be found in other vascular malformations or PIK3CA overgrowth syndromes that have yet to be analyzed in this manner.

Background: Early-stage (stage I-II) cutaneous melanoma accounts for the majority of melanoma diagnoses. However, more than 40% of patients who die due to melanoma were initially diagnosed with an early-stage melanoma. This highlights the current limitations of the Tumor Node Metastasis (TNM) staging and shows that additional biomarkers, prognostic for distant metastasis, need to be identified.

Methods: The aim of this study was to identify prognostic genome-wide methylation markers of metastasized primary early-stage melanomas and retrieving biological insights from its matched distant metastasis. We selected 45 samples from the Dutch Early-Stage Melanoma (D-ESMEL) study, representing case-control sets where the primary melanoma of each metastatic case (n = 15) is matched to a primary melanoma of a control (n = 15) based on known clinical risk factors. Matched distant metastasis (n = 15) were also retrieved. Laser capture microdissection was performed to isolate the tumor tissue, where after a genome-wide methylated DNA sequencing (MeD-seq) was conducted. After quality control, a total of 30 samples were retained for analysis, including 11 controls, 9 cases, and 10 metastatic samples. Differentially methylated regions (DMR) between primary tumors of the cases-control sets and the tumor of the primary case and its metastasis were tested using Chi-squared test with a genome-wide sliding window analysis, as well as a paired t-test in predefined promotor, gene body, and CpG-island regions.

Results: MeD-seq analyses did not reveal prognostic methylation markers in primary melanomas, which have additional prognostic value on top of known clinical risk factors after correction for multiple testing. However, exploratory analysis before correction revealed eight protein coding genes with the largest methylation difference between primary melanomas of patients with and without metastasis and between primary melanomas and matched distant metastasis: CYP2E1, PTPRN2, CHCHD2, NDRG2, EDN2, GC, USP17L1, and SERPINB8.

Conclusion: This study found 8 genes that have been implicated in primary tumors or metastasis of other cancers which require further investigation into their involvement of metastasis in melanoma.

Purpose: Identification of targets of intervention to promote lifespan is crucial given lifespan is an important measure of public health. Telomere length and epigenetic clocks are key biological markers of aging, whether they are targets of intervention in men or women is unclear. We examined their associations with sex-specific lifespan in a Mendelian randomization study.

Methods: We used genetic summary statistics of telomere length and lifespan (parental attained age and survival to recruitment) from the UK Biobank (n = ~ 0.5 million, mean age = ~ 57 years) and of epigenetic clocks (GrimAge, PhenoAge, HannumAge and Intrinsic epigenetic age acceleration) from a meta-analysis of 28 cohorts (n = 34,710). Using this data, we employed two-sample MR to estimate the causal effect of each aging biomarker on lifespan in men and women. Estimates were obtained using inverse variance weighting with sensitivity analysis.

Results: There was no evidence that telomere length was associated with lifespan in men (0.17 years per standard deviation of log telomere length, 95% confidence interval (CI) -0.54 to 0.88, survival - 0.17 years, 95% CI -0.39 to 0.05) or in women (0.04, 95% CI -0.88 to 0.96), although telomere length was associated with poorer survival to recruitment in women (survival - 0.24 years, 95% CI -0.44 to -0.03). Associations of epigenetic clocks with lifespan and survival were null in both men and women. Sensitivity analysis gave similar estimates.

Conclusions: Telomere length and commonly used epigenetic clocks may not be an appropriate target for promoting lifespan. Instead, efforts to develop interventions for aging should target causal drivers of lifespan.

Ambient air pollution is a major environmental carcinogen consisting of a complex mixture of particulate matter, gases, and adsorbed toxicants. Fine (PM_2.5) and ultrafine (PM_0.1) particles are of particular concern due to their capacity to penetrate deep into the lungs and translocate systemically, carrying carcinogens such as heavy metals, volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs). Exposure arises from traffic emissions, industrial activity, biomass combustion, and indoor sources, with inhalation as the primary route. Epidemiologic studies have firmly established associations between air pollution, particularly PM_2.5 and increased risks of lung, bladder, breast, and hematologic cancers, even at concentrations below regulatory thresholds. Mechanistically, pollutant-induced carcinogenesis is driven by oxidative stress, DNA damage, epigenetic reprogramming, immune dysregulation, and impaired cell cycle control. Air pollution generates reactive oxygen species (ROS), disrupts mitochondrial function, alters DNA repair pathways, and modulates the expression of tumor suppressor genes through methylation and histone modifications. Prolonged inflammation and immune suppression in polluted tissue microenvironments further promote malignant transformation. Recent studies have shown increased interest in microplastics (MPs) as potential environmental carcinogens, given their unique physical properties and poorly characterized toxicological profiles. Preliminary findings indicate that microplastics are detectable in multiple cancer types and may correlate with distinct molecular alterations, suggesting a link to carcinogenesis and highlighting a critical future direction for environmental cancer research.

As genomic research scales globally, legal constraints such as data localization provisions in data privacy and other laws and ethical imperatives around privacy and sovereignty increasingly challenge traditional models of data sharing. Data visiting, where analysis occurs within the provider's computing environment without moving the data, offers a promising alternative, yet its governance remains underdeveloped. This article introduces the Seven-Dimensional Data Visiting Framework (7D-DVF), a structured tool for designing, assessing, and regulating data visiting systems in genomics. Building on the Global Alliance for Genomics and Health (GA4GH) data sharing lexicon, the framework disaggregates data visiting into seven adjustable dimensions: researcher autonomy, data location, data visibility, nature of the shared data, output governance, trust and control model, and auditability and traceability. Each dimension operates as a governance lever, enabling proportional, context-sensitive configurations that balance privacy, utility, and legal compliance. The article illustrates how the 7D-DVF can guide practical implementation through checklists and real-world scenarios, including institutional data control, Indigenous data sovereignty, and federated AI model training. By shifting genomic governance from reactive compliance to design-based stewardship, the 7D-DVF equips stakeholders to operationalize secure, lawful, and future-ready data sharing practices.