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PubMed2026

Prioritizing Parkinson's disease risk-associated mitochondrial candidate genes via multi-omics integrative analysis.

BACKGROUND: Mitochondrial dysfunction has been implicated in Parkinson's disease (PD), but the genetically regulated mitochondrial genes associated with PD risk remain incompletely defined. METHODS: We conducted a summary-data-based genetic epidemiology study integrating summary-based Mendelian randomization (SMR), Heterogeneity in dependent instruments (HEIDI) filtering, and Bayesian colocalization to prioritize mitochondrial-related molecular features associated with PD risk. Mitochondrial-related genes were defined using MitoCarta3.0. Genetically predicted gene expression and plasma protein abundance were evaluated using expression quantitative trait loci (eQTL) data from eQTLGen and GTEx v8, and protein quantitative trait loci (pQTL) data was assessed using International Parkinson's Disease Genomics Consortium (IPDGC) as the discovery genome-wide association study (GWAS) and FinnGen as the replication dataset. Prespecified QTL analyses were interpreted using FDR correction, HEIDI filtering, and colocalization support. DNA methylation QTL analysis, mitochondrial phenotype MR, and single-nucleus RNA-seq analysis were performed as complementary analyses. RESULTS: In the primary eQTL analysis, higher genetically predicted TTC19 expression was associated with lower PD risk (OR = 0.80, 95% CI: 0.74-0.87, PPH4 = 0.80), whereas higher MALSU1 expression was associated with increased PD risk (OR = 2.21, 95% CI: 1.59-3.06, PPH4 = 0.96). Both associations survived FDR correction, passed HEIDI filtering, and showed colocalization support. GTEx whole-blood data supported the direction of the TTC19 association. No mitochondrial protein reached significance after FDR correction and colocalization filtering in the primary pQTL analysis. Complementary methylation analysis highlighted cg06270993 as an exploratory regulatory signal for MALSU1. CONCLUSIONS: This MR-colocalization study prioritizes TTC19 and MALSU1 as genetically supported mitochondrial-related candidate genes associated with PD risk. Further validation is required to define their functional roles in PD pathogenesis.

Humans↗
PubMed2026

Baseline Computed Tomography Coronary Angiography and Polygenic Risk Profiles in Adults With Type 2 Diabetes: A Cross-Sectional Analysis From the VOLTAIRE Study.

AIMS: To characterise baseline clinical, anatomical, and genetic cardiovascular risk profiles in participants enrolled in the VOLTAIRE (Evaluation of Polygenic Scores and CT Imaging in Risk Factor Modification in Patients with Type 2 Diabetes) study and examine concordance across these domains. METHODS: This analysis included adults with T2D who completed baseline computed tomography coronary angiography (CTCA) and polygenic risk score (PRS) assessment prior to randomisation in the VOLTAIRE study. Coronary atherosclerosis was evaluated using coronary artery calcium (CAC) score and CTCA-derived stenosis severity. Clinical risk was assessed using the New Zealand Society for the Study of Diabetes 5-year cardiovascular risk calculator. Polygenic risk for coronary artery disease was assessed using a genome-wide PRS and categorised into tertiles. RESULTS: Among 126 participants with T2D (mean age 57.5 ± 8.7 years; 62.7% male), coronary atherosclerotic burden was highly heterogeneous: 34.9% had CAC = 0, whereas 19.8% had CAC ≥ 400. Moderate-to-severe coronary stenosis (≥ 50%) was present in 40.5% of participants overall, including 20.4% of those classified as low clinical risk. PRS distribution was variable (low 37.3%, intermediate 35.7%, high 27.0%). Overlap between anatomical, genetic, and clinical domains was limited, with only 8.7% of participants classified as high risk across all three. CONCLUSIONS: Substantial heterogeneity and limited overlap exist between anatomical, genetic, and clinical cardiovascular risk measures in T2D. These findings support a multimodal approach to risk assessment integrating imaging and genetic profiling. TRIAL REGISTRATION: https://www. CLINICALTRIALS: gov; ID: NCT07091162.

Aged↗
PubMed2026

Polygenic risk scores in major depressive disorder: A systematic review across diagnostic, treatment, course/severity, and subtype domains.

BACKGROUND: Major depressive disorder (MDD) is heterogeneous across diagnostic, treatment-related, course/severity, and subtype domains. Polygenic risk score (PRS) studies have examined these domains, but differences in PRS sources, samples, methods, and endpoint definitions have fragmented the evidence. We synthesised findings and examined potential contributors to heterogeneity. METHODS: PubMed/MEDLINE, Embase, PsycINFO, and Web of Science were searched for studies published from January 2016 through 25 November 2025. Result records were synthesised using SWiM, and certainty was assessed with an adapted GRADE framework. RESULTS: Sixty studies contributed 493 retained records; 450 were descriptively classified as positive, null, or reverse, although records were not independent. Positive findings accounted for 44/56 diagnostic, 61/273 treatment-related, 64/100 course/severity, and 14/21 subtype records. For MDD/depression-derived PRSs and case-control MDD status, all 10 contributing studies showed higher liability in cases (exploratory exact sign test p = 0.002; FDR q = 0.004). The same PRS group showed positive findings for overall depressive symptom severity (14/18), although the study-level test was imprecise (5/5 studies; p = 0.063). Pharmacological response/remission findings for these PRSs were mostly null or directionally mixed (10 positive, 18 null, and 9 reverse). Treatment-resistant depression (TRD) findings differed by operational definition. Atypical and psychotic subtype signals arose mainly from single-study PRS and endpoint contrasts. CONCLUSIONS: PRS evidence was clearest for MDD diagnostic status and showed a tentative pattern for overall symptom burden. Treatment and subtype findings were less consistent or less replicated. Larger, ancestrally diverse studies with standardised endpoints and transparent PRS methods are needed.

Humans↗
PubMed2026

Pharmacogenomic and drug interactions risk in cardio-oncology: A precision medicine perspective for India.

Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.

Humans↗
PubMed2026

Co-location of services: an umbrella review to consider how primary care estates could be better used to support disadvantaged groups.

AIM: To examine how co-located community and health services in primary care could support disadvantaged groups. BACKGROUND: Co-locating services is thought to improve access, collaboration, and patient outcomes. There are thousands of primary care premises across the UK. At a time of stagnating or widening health inequalities, they present an ideal opportunity to support communities, especially in disadvantaged areas. METHOD: We conducted a systematic umbrella review. Articles were retrieved from Ovid MEDLINE and Ovid Embase with supplementary snowball and grey literature searches. Reviews of co-located services supporting disadvantaged groups in primary care between 2010 and February 2024 were included. Quality and risk of bias were assessed using the Joanna Briggs Institute checklist. Two reviewers assessed eligibility, extracted data and assessed quality. Outcomes relating to health, welfare, healthcare utilization, and activity and processes were assessed. Data were narratively synthesized using a convergent integrated approach. FINDINGS: 2626 studies were screened, supplemented by snowball and grey literatures searches. Thirteen reviews were included for synthesis. One review included meta-analysis. Three models of care were identified; legal advice, welfare advice, and complementary health care. Data were synthesized according to themes: access and engagement, quality of care, efficiency, improved health, and improved social factors. We found co-located services can improve access to care, engagement in treatment, and quality of care for disadvantaged groups. Improvements to social determinants of health and mental health and well-being outcomes were reported. Findings were inconsistent when considering the impact of co-location on efficiency. We conclude that co-located services in primary care have the potential to improve identification of people most in need and improve their access to high quality health care and social support. Policy makers and practitioners should maximize the use of primary care estates to support disadvantaged groups and communities.

Humans↗
PubMed2026

CNNM2 in schizophrenia: multilevel evidence of genetic susceptibility, magnesium homeostasis, neurodevelopment and cognitive dysfunction.

Schizophrenia (SCZ) is a common psychiatric disorder with a complex, genetically and environmentally influenced etiology, but the specific pathogenesis remains unclear. In recent years, the SCZ susceptibility gene CNNM2 (encoding cyclin M2) located at the 10q24.32-33 locus has received widespread attention. The well-validated SCZ risk interval 10q24.32-33 harbors two independent risk variants: rs11191580 in NT5C2 (significantly associated with CNNM2 mRNA and protein levels) and rs7914558 in CNNM2. Results from functional genomic analyses indicate that lower CNNM2 expression is significantly associated with SCZ. Imaging genetics studies have demonstrated that carriers of risk alleles of CNNM2 SNPs exhibit alterations in brain structure. Animal model studies have revealed that Cnnm2 downregulation in mice leads to impairments in sensorimotor gating and cognitive function. As an Mg2+ transporter, CNNM2 primarily maintains systemic Mg2+ homeostasis. According to clinical studies, a proportion of patients with SCZ exhibit reduced Mg2+ concentrations in plasma and cerebrospinal fluid. CNNM2 dysfunction may contribute to the pathology of SCZ by disrupting Mg2+ homeostasis, thereby affecting neurodevelopment and synaptic plasticity. A systematic consolidation of current evidence supporting the involvement of CNNM2 in SCZ pathogenesis provides a direction for further investigation of the pathological mechanisms underlying this disease, and for identification of novel targets for clinical intervention..

Schizophrenia↗
PubMed2026

Mapping the immune-genetic architecture of Epstein-Barr virus-related phenotypes and multiple sclerosis through a single-cell genetic framework for target prioritization and pharmacologic hypothesis generation.

BACKGROUND: Multiple sclerosis (MS) is a severe neuroinflammatory disease causing substantial long-term disability. Strong epidemiologic evidence links Epstein-Barr virus (EBV) exposure with MS risk, but genetic evidence for immune target prioritization in EBV-related phenotypes remains limited. METHODS: We integrated single-cell cis-eQTL data from 14 immune cell types with GWASs of an EBV-related clinical phenotype and MS using a single-cell Mendelian randomization framework with colocalization analyses. Candidate eGenes were evaluated in independent cohorts. For multi-SNP instruments, we performed heterogeneity, pleiotropy, MR-Egger, weighted median, mode-based, and MR-PRESSO sensitivity analyses. We also conducted phenome-wide association analyses and queried DrugBank to annotate candidate compounds targeting prioritized genes. RESULTS: We prioritized 43 immune-cell-specific candidate eGenes with convergent genetic support, including 6 for the EBV-related phenotype and 37 for MS. SERPINB1 in NK cells was associated with increased risk of the EBV-related phenotype, whereas HLA-G was associated with decreased risk. For MS, APOM and MSH5 showed protective associations, while AHI1 showed cell-type-dependent, bidirectional associations across immune lineages. Colocalization and independent cohort evaluation supported these findings. Among FDR-significant multi-SNP associations, MR-Egger intercept tests did not indicate directional pleiotropy, although a small subset showed heterogeneity or MR-PRESSO signals. Phenome-wide analyses identified no significant adverse phenotypic associations among evaluable genes at the prespecified threshold. DrugBank annotation nominated sodium nitroprusside, fasudil, artenimol, and choline as hypothesis-generating compounds for experimental follow-up. CONCLUSIONS: This study provides a single-cell genetic framework for prioritizing immune-cell-specific candidate targets for EBV-related phenotypes and MS, and nominates genetically supported targets and pharmacologic hypotheses for experimental investigation.

Humans↗
PubMed2026

Unravelling Ovarian Cancer: an analysis of the Influence of LRP1 and PAI1 Genetic Variations.

To assess the potential association between LRP1 (rs715948) and PAI1 (rs2227631, rs1799889) gene variation and ovarian cancer (OC) susceptibility. This study evaluated the genotypic and allelic distributions of LRP1 gene and PAI1 gene variants using Restriction Fragment Length Polymorphism (RFLP) analysis in 134&#xa0;&#xb0;C patients and 134 healthy controls. LRP1 (rs715948) showed a significant association with OC risk. The TC genotype was (OR&#x2009;=&#x2009;3.7823, 95% CI: 2.1732-6.5825, p&#x2009;<&#x2009;0.0001), and the CC genotype has (OR&#x2009;=&#x2009;2.1613, 95% CI: 1.0054-4.6459, p&#x2009;=&#x2009;0.0484). The C allele was significantly more frequent in cases (46%) than controls (32%) (OR&#x2009;=&#x2009;1.7684, 95% CI: 1.2443-2.5133, p&#x2009;=&#x2009;0.0015). For PAI1 (rs2227631), AG and GG genotypes showed no significant association (p&#x2009;=&#x2009;0.3519 and p&#x2009;=&#x2009;0.1165, respectively). PAI1 (rs1799889) AG genotype was (OR&#x2009;=&#x2009;5.855, 95% CI: 2.4663-13.9027, p&#x2009;<&#x2009;0.0001), while GG genotype showed no significance (p&#x2009;=&#x2009;0.1025). The dominant model of LRP1, (TC&#x2009;+&#x2009;CC) and C alleles, were significantly more frequent in OC cases, indicating a potential risk factor. In contrast, the dominant models (AG&#x2009;+&#x2009;GG) and G alleles of PAI1 (rs2227631, rs1799889) showed no significance with OC susceptibility. Genetic variation in LRP1 (rs715948) significantly associated with increased OC risk, particularly the TC and CC genotypes and C allele. The C allele of this gene is key markers linked to higher OC susceptibility. Whereas in PAI1 (rs2227631, rs1799889), dominant models (AG&#x2009;+&#x2009;GG) show no significance, association suggesting a less prominent role in OC susceptibility. These findings highlight LRP1 as a potential genetic biomarker for OC risk assessment, while the role of PAI1 variants warrants further investigation in larger sample size.

Humans↗
PubMed2026

Pharmacogenomics of antipsychotic-induced weight gain: A systematic review.

BACKGROUND: Antipsychotic-induced weight gain (AIWG) is a major clinical concern, affecting approximately 30% of patients. Clinical predictors explain only part of AIWG risk. Genetic and molecular variations are hypothesized to contribute to susceptibility. The purpose of this review is to summarize recent results to identify replicated and novel findings. STUDY DESIGN: Applying PRISMA guidelines, we searched MEDLINE, Embase, and PsycINFO (May 2018-May 2026) for studies on genetic and molecular associations with AIWG, extending our prior review. Reviews, editorials, and conference abstracts were excluded. We extracted study characteristics (design, diagnosis, antipsychotic exposure, sample size, ancestry, genetic variants, and AIWG outcomes) (e.g., &#x2265;7% weight gain, BMI change). RESULTS: Fifty-three studies met inclusion criteria. In candidate gene studies, the most consistently replicated genes associated with AIWG were observed for DRD2, HTR2C, and MC4R. Multiple novel associations were identified by genome-wide association studies (GWAS) (e.g., MAP2K1, ZDBF2, PEPD), polygenic risk scores (PRS) (e.g., body mass index PRS), gene expression (e.g., CYP3A4, EP300), and epigenetic analyses (e.g., cg12034943 at CRTC1). CONCLUSIONS: Polymorphisms in candidate genes related to neurotransmission and appetite regulation continue to be investigated for associations with AIWG, while novel findings have emerged from GWAS, gene expression, and epigenetic studies. Evidence remains inconsistent due to limited replication, methodological variability, sparse ancestry data, and geographical underrepresentation. No single genetic variant is ready for clinical use, and multi-omic and multi-ancestry models are needed to improve prediction and clinical utility.

Humans↗
PubMed2026

Height variation independent of known genetic variants and health in later life: a cohort study.

BACKGROUND: Adult-attained height is associated with later-life health, but it reflects both genetic and nongenetic influences. The health implications of height variation not explained by known common height-associated genetic variants remain unclear. OBJECTIVES: This study aimed to examine associations of residual height (height variation independent of known genetic variants) with multiple disease incidence and all-cause mortality in later life. METHODS: In this cohort study of 407,366 adults of European ancestry (aged 40-70 y) in the United Kingdom Biobank (2006-2010), sex- and age-specific genetically predicted height was estimated from 9863 height-associated variants, adjusted for 30 principal components of ancestry. Residual height was calculated as the difference between observed and genetically predicted height. Plasma proteomics (2054 proteins; Olink Explore) were profiled. Deaths and 49 incident diseases were ascertained through national registries. Multivariable Cox models estimated associations of residual height and related proteins with disease incidence and mortality. RESULTS: Higher residual height [mean (standard deviation, SD), 0.0 (4.8)] was associated with more favorable self-reported preadulthood exposures (e.g., later birth years, no maternal smoking around birth, being breastfed as an infant, no adoption experience, and lower childhood adversity scores) and lower hazard ratios (HRs) of 32 out of 49 diseases (median follow-up = &#x223c;12.5 y). Using participants with residual height within &#xb1;0.5 SDs from the mean as reference, those with residual height < -2 SDs had higher adjusted HRs of mortality [1.61; 95% confidence interval (CI): 1.50, 1.72], multimorbidity (1.28; 95% CI: 1.12, 1.46), cardiovascular disease (1.45; 95% CI: 1.32, 1.60), psychiatric/neurological disease (1.38; 95% CI: 1.28, 1.48), and other disease categories (e.g., diabetes, digestive, and musculoskeletal diseases). In contrast, higher genetically predicted height was associated with a higher incidence of 19 diseases, including subtypes of cancer, non-atherosclerotic cardiovascular diseases, and musculoskeletal diseases, as well as higher all-cause mortality. We identified 806 plasma proteins related to inflammation, immune response, and autophagy via tumor necrosis factor, Nuclear factor-kappa B, phosphoinositide-3 kinase/protein kinase B, and Janus kinase/signal transducer and activator of transcription signaling pathways, which were associated with residual height and multiple diseases and mortality. CONCLUSIONS: Higher residual height is associated with lower disease incidence and mortality, with associations that are distinct from those for genetically predicted height.

Humans↗
PubMed2026

Communication crossroads: Exploring generational dynamics in nursing from the bedside to the boardroom.

Nurses have up to four times more patient contact than physicians, positioning them as central drivers of communication in health care. Effective communication directly influences patient outcomes, teamwork, staff engagement, and the overall care experience. Today's nurses operate within a highly diverse environment that includes four generations in the workforce and up to eight generations of patients, each with distinct values, expectations, and communication preferences. This article examines how generational differences shape communication across three key relational domains: peer-to-peer, nurse-to-patient, and nurse-to-leader interactions, and offers insights to strengthen collaboration, engagement, and quality of care.

Humans↗
PubMed2026

Role of Polygenic Risk Scores in Predicting Cognitive Functioning after Mild Traumatic Brain Injury: A TRACK-TBI Study.

Patients with traumatic brain injury (TBI) and Glasgow Coma Scale scores of 13-15 (historically called mild TBI [mTBI]) commonly experience changes in cognitive functioning, including processing speed, memory, and executive functioning. In a prospective sample (N = 523) of individuals of European descent who had been treated in a U.S. level 1 trauma center for mTBI, we examined the prognostic value of four polygenic risk scores (PRS) for cognitive outcomes at 6-months postinjury. To estimate the impact of mTBI on cognition, primary cognitive outcomes were scaled as z-scores reflecting changes in performance relative to predicted preinjury performance. The PRS examined were previously developed and validated to predict cognition-related outcomes of educational attainment (Education-PRS), intelligence (Intelligence-PRS), and Alzheimer's disease (AD-mild traumatic brain injury (APOE)-PRS and AD + APOE-PRS). Both the Education-PRS and Intelligence-PRS displayed bivariate associations with all four cognitive outcomes (&#x3b2; = 0.19-0.32), whereas neither Alzheimer's disease PRS was significantly associated with any outcome. After controlling for other factors known to predict cognitive outcomes of TBI (e.g., sex, education, mTBI severity defined by a combination of Glasgow Coma Scale scores and the presence/absence of acute intracranial findings on clinical neuroimaging), the Education-PRS and Intelligence-PRS remained independently predictive of verbal episodic memory (&#x3b2; = 0.10-0.16), whereas their associations with processing speed and executive functioning were mostly nonsignificant and were mediated through educational attainment. Looking across primary z-score and secondary raw score outcomes, cognitive outcomes 6 months post-mTBI were good on average, and PRS made small independent contributions to outcome prediction. The mediation model findings may support theories of cognitive reserve, which propose that individuals with stronger preinjury cognitive processing abilities (often estimated by educational history) can better compensate for TBI. Moreover, findings indicate that PRS may contribute modestly to multivariable models predicting cognitive function after TBI.

Humans↗
PubMed2026

Interventions to improve school attendance: a systematic review and meta-analysis of evidence from randomised controlled trials.

BACKGROUND: Poor school attendance adversely affects youth behaviour and health trajectories. We reviewed and synthesised the evidence from randomised controlled trials (RCTs) on interventions to improve school attendance. METHODS: This systematic review and meta-analysis updates the Education Endowment Foundation (EEF) 2022 review on attendance interventions. We synthesised RCT data to inform recommendations. We searched ERIC (via EBSCOhost), PsycINFO, Web of Science and Google Scholar for publications 1 January 2020-16 October 2024 to identify attendance interventions delivered to students, parents/guardians or school staff. We also extracted and analysed RCTs identified in the EEF review. Two reviewers independently extracted data from published articles and assessed risk of bias and certainty of evidence (Grading of Recommendations Assessment, Development and Evaluation, GRADE assessment). We synthesised and meta-analysed data per our protocol (PROSPERO: CRD42024610037). RESULTS: We screened 9366 titles and abstracts and included 61 articles (2000-2024): 43 articles published 2020-2024 plus 18 articles from the previous review (2000-2020), reporting 57 trials of 54 interventions. Pooled mean difference and 95% CIs for days of school attended was 0.63 (-0.34 to 1.61), I2=64.0%, low certainty, for mentoring interventions and 0.43 (0.10 to 0.76), I2=91.9%, moderate certainty, for parental engagement interventions. Other intervention areas including targeted approaches, behavioural programmes and social-emotional interventions had smaller, heterogeneous evidence bases. Risk of bias was moderate-to-low in most trials. CONCLUSION: A large range of interventions exist to address the diverse causes of school absence. Parental engagement demonstrated a small positive effect on attendance, particularly among younger age groups. Most trials were from the USA; implementation and evaluation in other countries will inform effectiveness.

CHILD↗
PubMed2026

Association of ERBB4 and SHBG gene polymorphisms with polycystic ovarian syndrome in South Indian women: a case-control genetic analysis.

INTRODUCTION: Polycystic ovary syndrome (PCOS) is a multifactorial endocrinological disorder with a substantial genetic component. However, the role of genes involved in follicular development and androgen regulation remains incompletely understood, particularly in South Indian populations. This study aimed to evaluate how variations in the ERBB4 and SHBG genes affect PCOS risk. METHODOLOGY: A hospital-based case-control study was conducted among 400 South Indian women, comprising 200 women with PCOS and 200 age-matched healthy controls. Genomic DNA was extracted to study SNPs at ERBB4 (rs2178575 and rs1351592) and SHBG (rs1799941 and rs727428) using ARMS-PCR genotyping. The study compared genotype and allele frequencies between cases and controls while assessing their associations with allelic, homozygous, heterozygous, dominant, recessive, and over-dominant genetic models. Genotyping accuracy was confirmed by re-genotyping and Sanger sequencing of a subset of samples. RESULTS: The ERBB4 rs2178575 polymorphism demonstrated a significant association with PCOS, as the AA genotype and A allele combination increased risk across all three genetic models, including homozygous, recessive, and allelic models. The ERBB4 rs1351592 variant was associated with 3-fold higher risk of PCOS in heterozygous and GC carriers. The SHBG rs1799941 polymorphism showed a significant link to PCOS through its effects on heterozygous and allelic states, whereas rs727428 displayed no significant connection due to its monomorphic distribution. CONCLUSION: These findings suggest that polymorphisms in ERBB4 and SHBG may contribute to PCOS susceptibility in South Indian women in a locus- and model-specific manner, revealing the intricate genetic structure that defines this medical condition.

Humans↗
PubMed2025

New insights into soil amendment: Impact of humic acid on typical antibiotic resistance in agricultural soil.

Humic acid (HA) addition can improve agricultural soil, but little is known about how it affects the soil resistome. In this study, we used selective agar plate combined with quantitative PCR (qPCR) and 16S rRNA gene sequencing to investigate how HA influences antibiotic resistant bacteria (ARB) and antibiotic resistant genes (ARGs) in soil contaminated with erythromycin and kanamycin. 0.1 % HA reduced the abundance of culturable erythromycin-resistant bacteria (ERB), while promoting the growth of kanamycin-resistant bacteria (KRB). Lysinibacillus and Paenibacillus were the dominant genera in ERB and KRB, respectively, governing the changes in their abundances. At this concentration, the Lysinibacillus abundance in ERB decreased from 96.74 % to 70.57 %. Meanwhile, that of Paenibacillus in KRB increased from 33.40 % to 77.44 %. The copy number of ermF decreased after HA addition, while that of ermB increased. Furthermore, 0.1 % HA significantly reduced the copy number and relative abundance of aadA1 and aac(6')-Ib (aka aacA4)-03 in the soil. Changes in these two types of ARB and ARGs were primarily driven by shifts in the microbial community structure. Soil physicochemical properties, particularly increased organic matter (OM), altered the absolute abundance of ermB. Meanwhile, changes in intI1 abundance determined the risk associated with aadA1 and aac(6')-Ib (aka aacA4)-03. These findings emphasize the dual role of HA in the dissemination of antibiotic resistance in agricultural soils and highlight the necessity of considering dose-dependent effects when applying HA as a soil amendment.

Soil Microbiology↗
PubMed2026

Clinical and genetic features of Ph-negative myeloproliferative neoplasms with dual-driver gene positivity.

OBJECTIVES: To investigate the clinical laboratory characteristics and gene mutation features of dual-driver gene positivity in patients with Philadelphia chromosome-negative myeloproliferative neoplasm (Ph-negative MPN). METHODS: We conducted a retrospective analysis of clinical data and genetic test results from 203 newly diagnosed patients with Ph-negative MPN. Of these, 194 had single-driver gene positivity and 9 had dual-driver gene positivity. High-throughput sequencing was used to detect mutations in JAK2, CALR, and MPL. Clinical characteristics and gene mutation profiles were compared between the two patient groups. RESULTS: The incidence of dual-driver gene positivity was 4.4% (9/203), with the most common combinations being JAK2 with CALR (4 patients) and JAK2 with MPL (4 patients). Compared with the single-driver group, the dual-driver group had a significantly higher risk of bleeding [4.1% (8/194) vs. 33.3% (3/9), P&#x2009;=&#x2009;0.008] and a higher proportion of uncommon mutations [3.6% (7/194) vs. 33.3% (3/9), P&#x2009;=&#x2009;0.006]. No statistically significant differences were observed between the two groups regarding age, thrombosis incidence, splenomegaly, or routine blood test indicators. During follow-up, 1 patient in the dual-driver group died from cerebrovascular disease. No leukaemia transformation or disease-related deaths occurred among the remaining patients. DISCUSSION: The increased bleeding risk in dual-driver patients may be related to a higher proportion of CALR mutations, elevated platelet counts, and higher variant allele frequencies, though these findings require validation in larger cohorts due to the small sample size. The higher prevalence of uncommon mutations suggests a more complex mutational landscape in this subgroup. CONCLUSION: Patients with Ph-negative MPN and dual-driver gene positivity may have a higher risk of bleeding and a more complex gene mutation profile.

Humans↗
PubMed2026

Genetic determinants of gestational diabetes mellitus in thai pregnant women: role of GCKR, CDKAL1, TCF7L2, NEDD1, and CMIP variants.

BACKGROUND: Gestational diabetes mellitus (GDM) has a high global prevalence and arises from complex interactions between genetic predisposition and environmental factors. GDM is associated with metabolic disturbances and chronic low-grade inflammation, both of which contribute to its pathogenesis. This study aimed to investigate the association between GDM and 135 single-nucleotide polymorphisms (SNPs) across 20 genes related to metabolic traits. METHODS: In this case-control study, 152 pregnant women with GDM and 684 pregnant women with normal glucose tolerance (NGT) who underwent antenatal examination at Siriraj Hospital, Bangkok, were enrolled. Clinical data and blood samples were collected from all participants. Genomic DNA was isolated and subjected to whole-genome sequencing using the DNBSEQ-T7RS high-throughput sequencing platform. Genotype analyses were performed using R software, and haplotype analyses were conducted using the online SNPStats software. RESULTS: After adjusting for maternal age and pre-pregnancy body mass index, polymorphisms in TCF7L2 (rs34872471, rs7901695, rs4506565, rs7903146, rs12243326, and rs12255372), NEDD1 (rs10431408, rs11830756, rs249579, rs249585, and rs4762339), CMIP (rs2306115 and rs201681534), CDKAL1 (rs4710942), GCKR (rs2293572 and rs2293571), and GCK (rs5883890) were significantly associated with the risk of GDM. Haplotype analysis demonstrated that the TCF7L2 rs12243326-rs12255372 CA haplotype was associated with a decreased risk of GDM (OR = 0.44, 95% CI: 0.23-0.81), while the NEDD1 rs249579-rs249585-rs4762339 GGT haplotype was associated with an increased risk of GDM (OR = 1.40, 95% CI: 1.08-1.82). CONCLUSIONS: These findings suggest that genetic variations in TCF7L2, NEDD1, CMIP, CDKAL1, GCK, and GCKR contribute to GDM susceptibility in the Thai population.

Humans↗
PubMed2026

A systematic review and network meta-analysis of single nucleotide polymorphisms associated with oral submucous fibrosis risk.

BACKGROUND: Oral submucous fibrosis (OSF) is a chronic and insidious oral disease characterized by hyalinization of the subepithelial connective tissue and progressive fibrosis of the oral submucosa. It is a precancerous condition of oral squamous cell carcinoma. Studies have demonstrated that single nucleotide polymorphisms (SNPs) are closely associated with susceptibility to OSF. This study aims to comprehensively evaluate the association between SNPs and OSF risk and to rank the strength of the association between different genetic models and OSF susceptibility. METHODS: Literature related to OSF was comprehensively searched from PubMed, Web of Science, Embase, Cochrane Library, CNKI, and Wangfang databases up to July 2025. Full-text case-control studies with patients diagnosed with OSF were included. Quality assessment was performed to evaluate the risk of bias. RevMan 5.4, GeMTC 0.14.3, and STATA 17.0 were used for the pairwise and Bayesian network meta-analysis. RESULTS: A total of 24 studies with 2545 cases and 3772 controls, covering 13 SNPs in 11 genes, were included in our meta-analysis. We found that CYP1A1 rs4646903:T>C, CYP1A1 rs1048943:A>G, GSTT1 null genotype, GSTM1 null genotype, and XRCC3 rs861539:C>T were associated with an increased risk of OSF, while MMP2 rs243865:C>T and MMP3 rs3025058: 5A>6A were associated with a decreased risk of OSF. Further Bayesian network meta-analysis indicated the top 5 genetic models with the highest association with OSF risk in network group 1 were the dominant model, homozygous model, allelic model, and recessive model of CYP1A1 rs1048943:A>G (ranked 1-4), and the heterozygous/dominant model of CYP1A1 rs4646903:T>C (both ranked 5). While the allelic models of XRCC3 rs861539:C>T and MMP3 rs3025058: 5A>6A ranked first for predicting OSF in group 2 and group 3, respectively. CONCLUSION: Some specific SNPs are significantly related to the risk of OSF. Among them, the dominant model of CYP1A1 rs1048943:A>G may be the most strongly associated genetic model with OSF risk. Future large-sample, well-designed studies with detailed genotype data are needed to validate the roles of these SNPs in OSF risk.

Humans↗