Long-read DNA sequencing technologies have been rapidly evolving in recent years, and their ability to assess large and complex regions of the genome makes them ideal for clinical applications in molecular diagnosis and therapy selection, thereby providing a valuable tool for precision medicine. In the third-generation sequencing duopoly, Oxford Nanopore Technologies and Pacific Biosciences work towards increasing the accuracy, throughput, and portability of long-read sequencing methods while trying to keep costs low. These trades have made long-read sequencing an attractive tool for use in research and clinical settings. This article provides an overview of current clinical applications and limitations of long-read sequencing and explores its potential for point-of-care testing and health care in remote settings.

BACKGROUND: Our study aims to investigate an intrinsic link underlying sex hormone-binding globulin (SHBG) and rheumatoid arthritis (RA), which remains inconclusive in observational settings. METHODS: Summary statistics were collected from the largest GWAS(s) on SHBG adjusted for BMI (SHBGadjBMI; Noverall = 368,929; Nmen = 180,094; Nwomen = 188,908), crude SHBG (Noverall = 370,125; Nmen = 180,726; Nwomen = 189,473), and RA (Ncase = 22,350; Ncontrol = 74,823). A genome-wide cross-trait design was performed to quantify global and local genetic correlation, identify pleiotropic loci, and infer a causal relationship. RESULTS: Among the overall population, a significant global genetic correlation was observed for SHBGadjBMI and RA ([Formula: see text] = 0.11, P = 1.0 × 10-4) which was further supported by local signal (1q25.2). A total of 18 independent pleiotropic SNPs were identified, of which three were highly likely causal variants and four were found to have effects on both traits through gene expression mediation. A putative causal association of SHBGadjBMI on RA was demonstrated (OR = 1.20, 95% CI = 1.01-1.43) without evidence of reverse causality (OR = 0.999, 95% CI = 0.997-1.000). Sex-specific analyses revealed distinct shared genetic regions (men: 1q32.1-q32.2 and 5p13.1; women: 1q25.2 and 22q11.21-q11.22) and diverse pleiotropic SNPs (16 in men and 18 in women, nearly half were sex-specific) underlying SHBGadjBMI and RA, demonstrating biological disparities between sexes. Replacing SHBGadjBMI with crude SHBG, a largely similar yet less significant pattern of results was observed. CONCLUSION: Our cross-trait analysis suggests an intrinsic, as well as a sex-specific, link underlying SHBG and RA, providing novel insights into disease etiology.

BACKGROUND: The RNA m6A modification has been implicated in multiple neurological diseases as well as macrophage activation. However, whether it regulates microglial activation during hypoxic-ischemic brain damage (HIBD) in neonates remains unknown. Here, we aim to examine whether the m6A modification is involved in modulating microglial activation during HIBD. We employed an oxygen and glucose deprivation microglial model for in vitro studies and a neonatal mouse model of HIBD. The brain tissue was subjected to RNA-seq to screen for significant changes in the mRNA m6A regulator. Thereafter, we performed validation and bioinformatics analysis of the major m6A regulators. RESULTS: RNA-seq analysis revealed that, among 141 m6A regulators, 31 exhibited significant differential expression (FC (abs) ≥ 2) in HIBD mice. We then subjected the major m6A regulators Mettl3, Mettl14, Fto, Alkbh5, Ythdf1, and Ythdf2 to further validation, and the results showed that all were significantly downregulated in vitro and in vivo. GO analysis reveals that regulators are mainly involved in the regulation of cellular and metabolic processes. The KEGG results indicate the involvement of the signal transduction pathway. CONCLUSIONS: Our findings demonstrate that m6A modification of mRNA plays a crucial role in the regulation of microglial activation in HIBD, with m6A-associated regulators acting as key modulators of microglial activation.

BACKGROUND: Thalassemia is an extremely prevalent monogenic inherited blood disorder in southern China. It is important to comprehensively understand the molecular spectrum of thalassemia in an area with such a high prevalence of thalassemia before taking appropriate actions for the prevention and treatment of this disorder. Herein, we explored the clinical feasibility of using next-generation sequencing (NGS) for large-scale population screening to illustrate the prevalence and spectrum of thalassemia in Southern Jiangxi. METHODS: Blood samples collected from 136,312 residents of reproductive age in Southern Jiangxi were characterized for thalassemia by NGS. A retrospective analysis was then conducted on blood samples determined to be positive for thalassemia. RESULTS: In total, 19,827 (14.545%) subjects were diagnosed as thalassemia carriers, and the thalassemia prevalence rate significantly varied by geographical region (p < 0.001). A total of 40 α-thalassemia genotypes including 21 rare genotypes were identified, with -@-SEA/αα being the most prevalent genotype. 42 β-thalassemia genotypes including 27 rare genotypes were identified, with the most common mutation IVS II-654 C > T accounting for 35.257% of these β-thalassemia genotypes. Furthermore, 74 genotypes were identified among 608 individuals with combined α- and β-thalassemia. Notably, most individuals with rare thalassemia mutations had mildly abnormal hematologic parameters including microcytic hypochromia. CONCLUSIONS: Our findings demonstrate the great heterogeneity and diverse spectrum of thalassemia in Southern Jiangxi, emphasizing the importance and necessity of persistent prevention and control of thalassemia in this region. Additionally, our findings further suggest that NGS can effectively identify rare mutations and reduce the misdiagnosis rate of thalassemia.

BACKGROUND: As one of the most common intestinal inflammatory diseases, celiac disease (CD) is typically characterized by an autoimmune disorder resulting from ingesting gluten proteins. Although the incidence and prevalence of CD have increased over time, the diagnostic methods and treatment options are still limited. Therefore, it is urgent to investigate the potential biomarkers and targeted drugs for CD. METHODS: Gene expression data was downloaded from GEO datasets. Differential gene expression analysis was performed to identify the dysregulated immune-related genes. Multiple machine algorithms, including randomForest, SVM-RFE, and LASSO, were used to select the hub immune-related genes (HIGs). The immune-related genes score (IG score) and artificial neural network (ANN) were constructed based on HIGs. Potential drugs targeting HIGs were identified by using the Enrichr platform and molecular docking method. RESULTS: We identified the dysregulated immune-related genes at a genome-wide level and demonstrated their roles in CD-related immune pathways. The hub genes (MR1, CCL25, and TNFSF13B) were further screened by integrating several machine algorithms. Meanwhile, the CD patients were divided into distinct subtypes with either high- or low-immunoactivity using single-sample gene set enrichment analysis (ssGSEA) and consensus clustering. By constructing IG score based on HIGs, we found that patients with high IG score were mainly attributed to high-immunoactivity subgroups, which suggested a strong link between HIGs and immunoactivity of CD patients. In addition, the novel constructed ANN model showed the sound diagnostic ability of HIGs. Mechanistically, we validated that the HIGs play pivotal roles in regulating CD's immune and inflammatory state. Through targeting the HIGs, we also found potential drugs for anti-CD treatment by using the Enrichr platform and molecular docking method. CONCLUSIONS: This study unveils the HIGs and elucidates the networks regulated by these genes in the context of CD. It underscores the pivotal significance of HIGs in accurately predicting the presence or absence of CD in patients. Consequently, this research offers promising prospects for the development of diagnostic biomarkers and therapeutic targets for CD.

BACKGROUND: Diagnostic efficacy is now well established for diagnostic genomic testing in rare disease. Assessment of overall utility is emerging as a key next step, however ambiguity in the conceptualisation and measurement of utility has impeded its assessment in a comprehensive manner. We propose a conceptual framework to approach determining the broader utility of diagnostic genomics encompassing patients, families, clinicians, health services and health systems to assist future evidence generation and funding decisions. BODY: Building upon previous work, our framework posits that utility of diagnostic genomics consists of three dimensions: the domain or type and extent of utility (what), the relationship and perspective of utility (who), and the time horizon of utility (when). Across the description, assessment, and summation of these three proposed dimensions of utility, one could potentially triangulate a singular point of utility axes of type, relationship, and time. Collectively, the multiple different points of individual utility might be inferred to relate to a concept of aggregate utility. CONCLUSION: This ontological framework requires retrospective and prospective application to enable refinement and validation. Moving forward our framework, and others which have preceded it, promote a better characterisation and description of genomic utility to inform decision-making and optimise the benefits of genomic diagnostic testing.