Hydroxyurea (HU) has been widely used as a first-line therapy for sickle cell disease (SCD), an autosomal recessive monogenic disorder characterized by abnormal haemoglobin and chronic haemolysis. However, its multiple mechanisms of action, particularly those related to SCD pathogenesis, remain incompletely understood. We characterized the transcriptional profiles of erythroid cells differentiated from peripheral blood mononuclear cells collected from patients with SCD, either treated with HU or untreated, and compared them with healthy controls (HC) using bulk RNA sequencing. We identified 1398 differentially expressed genes (DEGs) in erythroid cells derived from untreated patients with SCD and 495 DEGs in cells derived from HU-treated patients, both compared with HC. Functional enrichment analysis using gene ontology and Kyoto encyclopedia of genes and genomes revealed significant enrichment of biological processes and pathways, including oxidative phosphorylation, proteasome function, autophagy, natural killer cell cytotoxicity, adaptive immune response, and inflammatory response. Additionally, 12 of the top DEGs identified in patients with SCD were validated by quantitative RT-PCR in comparison with HC. The identified genes and pathways could play a role in SCD pathogenesis and may serve as potential targets for the development of novel therapeutic strategies.
Exercise-induced heart rate response (ΔHR) reflects autonomic regulation and cardiovascular fitness. While coronary heart disease (CHD)-associated genetic variants are known to influence vascular and metabolic pathways, their role in modulating heart rate dynamics remains underexplored. This study aimed to evaluate and functionally characterize CHD-related genetic variants associated with ΔHR using integrated statistical, network-based, and regulatory approaches. Sixteen CHD-linked single-nucleotide polymorphisms (SNPs) were analyzed in a Hungarian population-based cohort (n = 665) using adjusted linear regression models. YMCA 3 min step test was carried out, with HR measured at rest, immediately post-exercise, and during recovery at 5 and 10 min. An optimized genetic risk score (oGRS) was constructed through stepwise inclusion based on model performance. Functional clustering was performed using STRING network analysis, and regulatory potential was assessed via RegulomeDB. Four SNPs—rs6725887 (WDR12), rs964184 (ZPR1), rs9349379 (PHACTR1), and rs1746048 (CXCL12)—showed individually significant positive associations with ΔHR (p < 0.05). An additional four variants—rs646776 (CELSR2), rs46522 (UBE2Z), rs10455872 (LPA), and rs12190287 (TCF21)—were retained in the final oGRS based on incremental model improvement, yielding a cumulative p-value of 6.97 × 10⁻9. The oGRS was significantly associated with multiple heart rate parameters, including HRexerc, ΔHR5min, and ΔHR10min (Bonferroni-corrected p < 0.00625). STRING analysis identified a functional cluster comprising five genes (CELSR2, PHACTR1, UBE2Z, WDR12, and ZPR1), while CXCL12, LPA, and TCF21 remained unclustered, suggesting functional heterogeneity. All oGRS variants exhibited high regulatory potential (RegulomeDB ranks 1b–1f), with rs9349379 (PHACTR1) showing the highest transcriptional relevance (score 0.99). These findings demonstrate that CHD-associated genetic variants significantly influence exercise-induced heart rate dynamics. The oGRS framework provides a reproducible approach for dissecting polygenic contributions to autonomic cardiovascular traits in a general population, with implications for functional genomics and personalized cardiovascular risk stratification.
Hearing loss is a common disorder involving over 200 genes, some of which harbor rare variants. The distribution of these variants in the diverse ethnic populations of southwestern China remains unclear. In this study, we analyzed rare variants across the 3′,5′‑UTR, splicing and exonic regions of 20 common hearing-impaired genes in 477 patients from Southwestern China, representing four language families (Sinitic, Tibeto-Burman, Kra-Dai and Hmong-Mien) and 15 ethnic groups. A substantial number of rare variants were identified, more than half of which resided in exonic regions. These exonic variants were most prevalent in the Sinitic and Tibeto-Burman groups, with significant distribution differences between them. These variants were highly enriched in genes including USH2A, TRIOBP, MYO15A and MYO7A. Over 20
Personalized pharmacotherapy requires systematic consideration of genetic factors influencing drug efficacy and safety. The accumulation of large-scale whole-exome sequencing (WES) resources provides an opportunity to assess population frequencies of clinically significant pharmacogenetic variants; however, the applicability of exome-based pharmacogenomics across populations, particularly those underrepresented in existing reference datasets, requires further evaluation. A retrospective analysis of 6102 anonymized sequencing datasets obtained between 2020 and 2025 was performed using the DNBSEQ-G400 (MGI) platform and Agilent SureSelect Human All Exon v6/v7/v8 enrichment kits. SNV and indel detection, CNV analysis, high-resolution HLA typing, and diplotype assignment for key pharmacogenes were conducted. Pharmacogenomic annotations were derived from ClinPGx (formerly PharmGKB) (levels of evidence 1 A–2B), CPIC, and PharmVar. Haplotype phasing (SHAPEIT5), genotype imputation (IMPUTE5), and phased linkage disequilibrium analysis were performed using a reference panel of 814 Russian whole-genome sequences generated with the same bioinformatic workflow to assess the feasibility of reconstructing clinically relevant non-coding pharmacogenetic variants not captured by WES. WES reliably detected 33 of 34 Very Important Pharmacogenes (VIPs), allowing determination of allele frequencies, metabolizer statuses for 13 VIPs, and HLA diversity. The highest allelic and phenotypic variability was observed in CYP2D6, CYP2C19, and CYP2B6. A total of 663 ClinPGx annotations were identified, predominantly related to drug metabolism (50.38
Polygenic risk score (PRS) is a valuable tool for predicting the risk of breast cancer (BC). However, limited studies have been conducted in Chinese women. This study aimed to develop and validate a PRS which could be used to identify individuals with high risk of breast cancer. The associations between the PRS and patients’ clinicopathological characteristics or survival outcomes were also evaluated. We developed a PRS based on genome-wide association studies (GWAS)-identified risk variants with a three-stage design across four cohorts. In total, 7,056 patients and 6,659 controls were enrolled from Fujian Medical University Union Hospital (FJMUUH) and Shanghai Breast Cancer Genetics Study (SBCGS). Five approaches were utilized to calculate the PRS, including repeated logistic regression (RLR), logistic ridge regression (LRR), artificial neural network (ANN), random forest (RF) and support vector machine (SVM). Logistic regression analyses were performed to assess the association between established PRS and clinicopathological characteristics. The correlation between PRS and patients’ survival outcomes was evaluated by Cox regression models. Overall, 7 SNPs were selected for PRS development. PRSLRR achieved robust and stable performance across cohorts, yielding an area under the receiver operating characteristic curve (AUC) of 0.633 and an OR of 1.64 per 1 SD increase. Women in the top5
Traditional molecular diagnosis of rare genetic diseases often struggles with complex genotype–phenotype relationships, such as pleiotropy and locus heterogeneity. Despite advances in next-generation sequencing, variant interpretation remains a major bottleneck, frequently requiring labor-intensive expert review to establish phenotypic specificity. To address this challenge, we developed GenPhenia, a deep learning–based framework designed to assist phenotype-driven gene prioritization using clinical features encoded with the Human Phenotype Ontology (HPO). GenPhenia leverages large-scale synthetic clinical history datasets and a graph neural network architecture with message-passing strategies combined with BERT-based phenotype embeddings to learn phenotype–gene associations. The model was validated using both ClinVar-derived datasets and real-world clinical cohorts. On the challenging MCRD benchmark dataset, GenPhenia achieved 60
Urban environments expose residents to multiple simultaneous stressors that often act synergistically (e.g., air pollution and extreme heat amplifying cardiovascular and respiratory risks), contributing to a substantial public health burden. Environmental factors account for an estimated 13
Ocular disorders represent a significant public health concern with diverse manifestations that can lead to visual impairment and blindness. Understanding the genetic basis of ocular disorders in specific populations is essential for targeted therapeutic and preventive strategies. Studies on the epidemiology or mutation spectrum of eye disorders in the United Arab Emirates (UAE) are limited. To delineate the molecular spectrum of ocular disorders in the UAE, a retrospective chart review of patients with ocular disorders evaluated between January 2010 and January 2023 at Tawam Hospital, Al Ain was performed. Genetic testing was performed based on the patient's clinical phenotypes and family history. A total of 232 patients with eye disorders were evaluated, 119 (51
Y chromosome microdeletions (YCMs) are the second most prevalent genetic determinant of male infertility, but validated predictive models are limited. We retrospectively enrolled 4096 male infertility patients (October 2013–October 2023) for model development and randomly divided them into training (80
The genetic component of ulcerative colitis (UC) remains largely unexplained in non-European populations. This study aimed to investigate the polygenic architecture of UC in an Indian population. Whole-exome sequencing was performed in 160 UC patients and 379 ethnically matched controls. Gene-based rare variant burden tests (SKAT-O, CMC) and exome-wide association testing of coding and noncoding common variants using allelic chi-square testing were performed. Burden analysis identified 85 previously unreported genes significantly enriched for rare variants in UC, of which 22 showed suggestive associations (P ≤ 5 × 10⁻³; odds ratio 2.6–10.9). These genes were primarily involved in epithelial integrity, immune signalling, DNA repair, and vesicle trafficking pathways. Exome-wide association analysis identified 55 common variants surpassing the Bonferroni-corrected significance threshold (P ≤ 5.57 × 10⁻⁷), mapping to 44 unreported and two known susceptibility genes, with most belonging to functional categories similar to those observed in the rare variant analysis. Logistic regression analysis showed that variants significant in the allelic test remained significant after adjustment for covariates. STRING network analysis revealed functional interactions between eight genes identified in this study and known inflammatory bowel disease–related genes. Sub-phenotype analysis further indicated genetic heterogeneity among clinically defined UC subgroups. This first exome-based study of Indian UC patients expands the genetic landscape of the disease and identifies population-specific associations that appear distinct from those reported in Western cohorts, suggesting potential differences in underlying disease mechanisms. Most identified genes map to disease-relevant pathways. However, given the modest sample size and limited statistical power, these findings should be considered exploratory and require further validation to clarify their contribution to UC pathogenesis. The study also underscores the importance of conducting genetic investigations in genetically diverse and understudied populations to improve the broader applicability of genetic findings.
Emanuel syndrome is a rare chromosomal disorder arising from an unbalanced translocation between chromosomes 11 and 22, leading to severe developmental delays, and multisystem impairments. Physiotherapy supports motor function in affected children. An 8-year-old boy with Emanuel syndrome, received five physiotherapy sessions targeting strengthening, trunk control, and balance, with exercises also engaging lower-limb flexibility as part of functional movement practice. Improvements were observed in dynamic sitting balance, calf flexibility, and hand function, before therapy was discontinued. Individualized physiotherapy can provide meaningful gains, though limited adherence restricts long-term assessment. Greater awareness and timely multidisciplinary care remain important for optimising functional outcomes.
Type 2 diabetes mellitus (T2D) is no longer viewed solely as a metabolic disorder but rather as a chronic, low-grade inflammatory disease shaped by the interplay of immune signaling and metabolic stress across key organs. This study explored inflammatory molecular signatures in pancreatic islets, adipose tissue (AT), and liver associated with T2D. Publicly available human genomic and transcriptomic datasets were identified through a PubMed search. Differentially expressed genes and all identified non-coding RNAs (ncRNAs) from the three tissues were subjected to bioinformatic and enrichment analyses to identify tissue-specific and common inflammatory mediators. Through integrative multi-omics and functional analyses, we delineated both shared and tissue-specific inflammatory circuits in pancreatic islets, liver, and AT, highlighting the convergence of cytokine networks, particularly TNF-α, IL-6 and IL-17, as potential mediators of inter-organ dysfunction. These cytokines can contribute to a pathological feedback loop whereby inflammatory cues originating in AT propagate to pancreatic and hepatic compartments, compounding insulin resistance and β-cell failure. AKT1, MAPK3, and CCL2 may represent key cross-tissue effectors linking inflammatory signaling and metabolic control, whose activity is also sensitive to age-related molecular drift and stress response imbalances. Additionally, ncRNAs such as miR-3064 and miR-21 emerged as potential key post-transcriptional regulators of NF-κB, IL-6 and IL-17 signaling pathways, supporting the notion that epigenetic and transcriptomic reprogramming is involved in metabolic inflammation. Overall, our findings suggest a multi-layered inflammatory architecture underlying T2D, highlighting inflammatory mediators and regulatory RNAs as potential targets for precision therapeutic strategies.
To evaluate the diagnostic yield and clinical value of a phenotype-driven genomic testing strategy in fetuses with central nervous system (CNS) abnormalities. In this retrospective single-center study, 966 fetuses with CNS abnormalities detected by prenatal ultrasound and/or fetal magnetic resonance imaging were included. All cases underwent copy number variation sequencing (CNV-seq), while karyotyping and trio exome sequencing (trio-ES) were performed based on clinical indications and parental preference. Fetuses were stratified into isolated-single, isolated-complex, and non-isolated subgroups according to CNS involvement and extracranial abnormalities. Diagnostic yields were compared across phenotypic subgroups and common CNS phenotypes. Among 966 fetuses with prenatal CNS abnormalities, pathogenic or likely pathogenic (P/LP) variants were identified in 12.63
Retinitis pigmentosa (RP) is an inherited disease of the retina. It is characterized by progressive degeneration of the retinal photoreceptor cells. This pathology is due to mutations in CRB1 gene that is encoded by the crumbs homolog 1 (CRB1) protein. The aim of this study is to identify the mutations in Algerian patients with Retinitis Pigmentosa and to assess their structural, and functional implications as well as their correlation with clinico-pathology features. This study was performed in collaboration with the ophthalmological department of Farhat Hached Hospital, Sousse, Tunisia. Whole-exome sequencing was performed on an Algerian female patient (IV.3) presenting RP. Polymerase chain reaction (PCR) followed by Direct Sanger sequencing were performed in all family’s members (III3, III4, IV.3, IV4 and IV5,) to validate the mode of inheritance and confirm the disease segregation. Bioinformatics tools, including PolyPhen, were used to predict the pathogenicity through a scoring system, while SWISS-MODEL, PyMOL, InterProt and AlphaFold Server were performed for CRB1 structural modeling and to assess the impact of the mutations on its three-dimensional structure stability and flexibility. Based on the ophthalmological investigation, including fundus examination, Fluorescein Angiography (FA), and Optical Coherence Tomography (OCT), the two affected sisters (IV.3 and IV.4) exhibited a mottled fundus appearance with widespread areas of Retinal Pigment Epithelium (RPE) atrophy. FA demonstrated multiple hyperfluorescent areas consistent with window defects due to RPE loss, interspersed with relatively hypofluorescent regions corresponding to advanced chorioretinal atrophy. A relatively preserved central hyperfluorescent island was observed. OCT revealed marked degeneration of the outer retinal layers, with thinning of the photoreceptor layer, particularly in the peripheral retina. These findings initially suggested a choroideremia-like phenotype. Whole-exome sequencing identified a homozygous pathogenic variant in CRB1 gene (p.Glu710Val) in two affected sisters (IV.3 and IV4) by the autosomal recessive Retinitis Pigmentosa form, while no pathogenic variants were detected in CHM gene. The structural analysis revealed that the residue 710 is located in a domain Laminin G-like (LG) of the crumbs homolog 1 (CRB1) protein rather than in a calcium-binding EGF-like domain. The p.Glu710Val substitution abolishes a stabilizing hydrogen bond with Gln853, thereby disrupting the local interaction network within the Laminin G–like domain. The loss of this polar interaction may reduce local structural stability and alter the microenvironment of this domain. This is the first ophthalmological and molecular report of autosomal recessive Retinitis Pigmentosa in Algerian patients. Although ophthalmological investigation initially suggested a choroideremia-like phenotype, whole-exome sequencing identified a pathogenic CRB1variant, while only benign variants were detected in CHM gene. This case highlights the phenotypic overlap between inherited retinal dystrophies and underscores the importance of combining comprehensive ophthalmic assessment with molecular genetic testing for accurate diagnosis.
Lipid metabolism involves multiple genes that contribute to various diseases including metabolic disorders. Although extensive research has focused on identifying large-effect variants in coding regions, few studies have examined the effects of variations in regulatory and non-coding regions. Apolipoprotein C2 (APOC2) gene plays a central role in activating lipoprotein lipase; however, the effect of upstream variants on its transcriptional regulation remains unclear. We aimed to (1) identify genetic variants in a targeted APOC2 upstream region of, (2) annotate and characterize predicted cis-regulatory elements (CREs) in-silico, (3) map identified variants to transcription factor binding sites (TFBS), and (4) evaluate the association of selected variants with dyslipidemia and body mass index (BMI). Twelve variants were identified by sequencing of the APOC2 targeted region in a Kuwaiti cohort (n = 600). In-silico annotation using multiple tools identified 626 putative CRE within the targeted region which were prioritized into 48 predicted TFBS of functional relevance. Four variants (rs10425530, rs111782345, rs112698600, and rs2288912) met the criteria for association testing. A significant independent association, employing multivariate analysis, was observed between rs10425530 and BMI under a dominant model (β = 2.26; p = 0.022) among the Kuwaiti Arabs that requires further investigation in a large cohort. Motif-based analyses predicted that the rs10425530 A allele may alter the binding affinity of NR2C2, NR2C1, and GCM2 motifs by 21.10
The past decade has witnessed an unprecedented convergence of exposomic technologies, population-scale genomics, and AI-enabled data science, creating the conditions for a new integrative discipline. Here we introduce ExposoGenomics, defined as the integrative study of how the genome and exposome, treated as jointly dynamic systems, interact across the life course to shape health and disease. ExposoGenomics moves beyond classical gene-environment interaction models by embedding high-dimensional, temporally resolved exposure data within a multi-omic and AI-enabled analytical architecture oriented toward causal discovery, mechanistic understanding, and translational application. We describe the conceptual foundations of this framework, its mechanistic architecture linking external exposures to genomic responses through physiologically based kinetic models and adverse outcome networks, and the analytical approaches, including causal machine learning, graph-based integration, and foundation models, required to realize its potential. We emphasize that computational prediction must be accompanied by rigorous empirical validation, and that findings must be grounded in biologically plausible, causally supported mechanisms. In conjunction with this Perspective, Human Genomics formally launches ExposoGenomics as a dedicated article category and invites submissions that advance this integrative agenda.
Dry eye disease (DED), a prevalent ocular condition, has seen rising incidence rates. Aberrant inflammation and immune dysregulation are key pathogenic factors in DED. However, the underlying mechanisms linking autoimmunity to DED therapy remain incompletely understood. Herbal medicine's potential in treating DED warrants further exploration due to rendering monotherapy insufficient for clinical needs. DED-related datasets and genes were initially identified from the GEO database and other public repositories. After retrieving the data, differential gene expression analysis and functional enrichment analysis were performed. Subsequently, a protein–protein interaction network was constructed to identify core modules and hub genes. To enhance the reliability and diagnostic value of these findings, the hub genes were further validated using independent external datasets and refined through machine learning algorithms (LASSO and SVM-RFE) to extract characteristic genes. These characteristic genes were then used for reverse prediction of potential Traditional Chinese Medicine natural products, leading to the construction of a gene-natural products network. Following this, molecular docking was employed to screen for promising natural products based on binding affinity. In parallel, immune cell infiltration was estimated using CIBERSORTx, and single-cell RNA sequencing data were analyzed to elucidate cell-type-specific expression patterns of the characteristic genes. Finally, the therapeutic potential of the top-predicted natural product was validated using an in vitro cellular model of DED. GSE44101 was selected as the base dataset. Differential gene analysis identified 1089 differential genes and 3504 DED-related genes from five databases, with 235 overlapping genes. Enrichment analysis linked DED to Cytokine-Cytokine receptor interaction, PI3K-Akt, IL-17, and JAK-STAT signaling pathways. The PPI network yielded 20 hub genes, validated and refined using other GEO datasets and machine learning, resulting in 10 characteristic genes: CDK1, CCNA2, CXCL13, CCR1, FEN1, CCR7, SELL, RAD51, CXCL1, and KIF11. Genistein was identified as the key TCM natural product. Molecular docking revealed stable interactions between Genistein and CDK1, IL-1β, CDC20, and CCNA2, with CDC20 showing the highest stability. CIBERSORT analysis demonstrated associations between characteristic genes and specific immune cell infiltration in DED. Single-cell RNA sequencing localized their expression to key corneal cell types, with IL-1β predominantly expressed in macrophages. Cell experiments confirmed that Genistein at a concentration of 12.5 μmol/L could protect human corneal epithelial cells from NaCl-induced hyperosmotic damage and TNF-α-induced immune injury, reducing the cell detachment rate and decreasing the area of cell death loss. Genistein downregulated the expression of CDK1, IL-1β, and CCNA2 at the RNA and protein levels, while upregulating the expression of CDC20. Genistein demonstrates therapeutic potential for DED, likely through regulating CDK1, IL-1β, CDC20, and CCNA2 to exert anti-inflammatory, anti-oxidative stress, and anti-apoptotic effects.
The solute carrier family 26 (SLC26) encodes multifunctional anion transporters that mediate the transmembrane exchange of monovalent and divalent anions. While pathogenic variants in several SLC26 genes cause inherited disorders, only SLC26A4 and SLC26A5 have been linked to hereditary hearing loss (HHL). Exome sequencing performed in probands from nine unrelated Moroccan families with sensorineural hearing loss identified eight SLC26A4 variants, including previously reported and novel variants, as well as a homozygous canonical splice-site variant in SLC26A5 (c.1311 + 1G > T). Sanger sequencing confirmed co-segregation of all identified variants, and in silico prediction tools consistently supported their pathogenicity. Molecular dynamics simulations performed on three SLC26A4 missense variants (p. Ser353Ala, p. Phe555Cys, and p. Leu582Pro) indicated significant, state-dependent alteration in pendrin's structural stability, suggesting impaired conformational transitions required for efficient Cl⁻/HCO₃⁻ exchange. This study provides a comprehensive molecular characterization of SLC26A4- and SLC26A5-related hearing loss in Moroccan families and significantly expands the mutational landscape of hereditary hearing loss in North Africa.
Mitochondrial diseases, often stemming from recessive nuclear gene mutations, represent a heterogeneous group of disorders with significant morbidity and mortality. Carrier screening for these conditions is population-specific, yet data on the pathogenic variant burden in the Iranian population remain limited. This study aimed to analyze whole-exome sequencing (WES) data from 9989 Iranian individuals to identify the spectrum and frequency of recessive mitochondrial disease variants and to develop a population-specific carrier screening panel. We analyzed WES data from 9989 unrelated Iranian individuals. Variants in 1,564 nuclear genes associated with mitochondrial function were filtered for rarity (minor allele frequency < 0.01 in public databases), predicted pathogenicity, and recessive inheritance patterns (homozygous or compound heterozygous). Clinically relevant variants were manually curated, and carrier frequencies for significant recessive mitochondrial conditions were calculated. Our analysis identified variants across 15 groups of mitochondrial-related nuclear genes in 345 individuals recognized as carriers. Of these, 123 variants (35.6
National genome projects (NGPs) are increasingly shaping precision medicine by improving representation of population-specific genetic diversity. This review compiles findings from NGPs across Asia and Africa, regions that remain underrepresented in global genomic databases despite their extensive demographic and genetic diversity. A total of 53 studies from 24 countries were identified to understand (1) the genomic approach utilized, (2) novel findings that have emerged, and (3) strategies for improving research in these regions. The NGPs implement population-based variome databases (20 NGPs), linear reference genome assemblies (8 NGPs), and graph-based pangenome assemblies (1 NGP). Novel variants ranged between 0.28
