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PubMed2026

Base editing for precision therapeutics.

Base editing (BE), the precise installation of single-nucleotide changes in DNA or RNA without inducing double-strand breaks, holds substantial therapeutic promise for correcting single-nucleotide variants, which constitute more than half of the known pathogenic genetic variants. Recent advances have improved base editor specificity, efficiency, and delivery, enabling clinically oriented procedures. Clinically, BE has shown early success or strong translational promise in sickle cell disease, β-thalassemia, leukemia (via CAR T and epitope engineering), hypercholesterolemia (PCSK9 and ANGPTL3), alpha-1-antitrypsin deficiency, and glycogen storage disease type Ia. Key remaining challenges include bystander editing within the activity window, residual off-target DNA and RNA editing, delivery constraints (payload size, tissue targeting, and redosing limits), immunogenicity, and the need for durable long-term safety evidence across relevant cell types and disease contexts. Continued technological refinements, careful preclinical validation, and rigorous clinical assessment will be essential to fully realize BE's transformative potential in precision medicine.

Humans↗

PubMed2025

Association of AGER genetic variants with chronic obstructive pulmonary disease susceptibility in Southern Chinese Han populations.

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) remains a leading cause of disability and mortality among elderly populations. Studies indicate that AGER plays a critical regulatory role in the pathogenesis of respiratory disorders. However, the genetic variations in AGER to COPD susceptibility remain incompletely understood. This study employs a case-control design to investigate associations between AGER genetic variants and COPD risk in the Southern Chinese Han population. METHODS: This study enrolled 270 COPD patients and 271 healthy controls. AGER single-nucleotide polymorphisms (SNPs) were analysed using the MassARRAY iPLEX platform. Logistic regression models evaluated associations between AGER polymorphisms and COPD susceptibility, with false discovery rate (FDR) correction applied to mitigate multiple testing errors. SNP-SNP interactions were investigated through multifactor dimensionality reduction (MDR) analysis. Expression quantitative trait locus (eQTL) data from the GTEx database were further analysed to assess regulatory relationships between SNPs and AGER gene expression levels. RESULTS: This study showed that rs3134941 (G allele, OR = 0.21, 95% CI = 0.10-0.41, p (FDR) = 0.001) and rs3131300 (G allele, OR = 0.32, 95% CI = 0.20-0.49, p (FDR) = 0.0001) were significantly associated with a reduced susceptibility to COPD. MDR indicated that rs3131300 was the optimal predictive model for COPD risk. Additionally, initial mechanistic investigations utilizing the GTEx database identify rs3134941 (C > G) and rs3131300 (A > G) as significant expression quantitative trait loci for AGER mRNA in cell-cultured fibroblasts and whole blood. CONCLUSION: Our study demonstrated that AGER genetic variants might play a protective role in the progression of COPD.

Aged↗

PubMed2025

Substitutions of nucleotides at the 3' ends of COL6A1/2/3 exons induce exon skipping associated with collagen VI-related muscular dystrophies and therapeutic strategies.

PURPOSE: Collagen VI-related muscular dystrophies, characterized by proximal muscle weakness and joint contractures, are caused by pathogenic variants in the genes, COL6A1 to COL6A3. A monoallelic variant at the last nucleotide of a COL6A1 exon was initially classified as a missense variant but acted as a splicing variant, resulting in exon skipping. Here, we evaluated whether single-nucleotide variants at the 3'-ends of COL6A1 to COL6A3 exons cause aberrant splicing. METHODS: Ten relevant variants were identified in patients from our repository or public databases, and their muscle COL6A1 to COL6A3 transcripts were analyzed. The effects of the variants on splicing were also analyzed by minigene assay and SpliceAI in silico prediction. RESULTS: Transcripts from muscles of individuals with suspected collagen VI-related phenotypes showed exon skipping (skipping rate >12%). Findings of minigene assay and in silico prediction experiments supported these findings. Two therapeutic approaches, splicing correction of pre-messenger RNA or gene silencing of mature messenger RNA were assessed. Among them, gene silencing using short interfering RNAs targeting the skipped transcripts proved to be effective in restoring collagen VI in cells containing the pathogenic variant. CONCLUSION: Single-nucleotide variants at the 3'-ends of exons can lead to aberrant splicing, and allele-specific gene silencing targeting such variants is a promising therapeutic strategy.

Humans↗

PubMed2025

Exome-wide association study of bleeding events in patients receiving direct oral anticoagulants.

BackgroundDirect oral anticoagulants (DOACs) are first-line medications for stroke prevention in non-valvular atrial fibrillation (AF). However, variability in drug response poses risks of hemorrhagic or thromboembolic events.ObjectivesAlthough genetic influences on DOACs safety are increasingly recognized, robust evidence directly linking specific polymorphisms to bleeding risk remains limited.DesignMulti-center observational case-control study including exome-wide association analysis of 196 non-valvular AF patients treated with rivaroxaban or apixaban, comprising 97 with bleeding complications and 99 without.MethodsDOAC plasma concentrations, urinary 6-β-hydroxycortisol and cortisol levels were measured for CYP3A4 phenotyping. Sequencing was performed on the DNBSEQ G-400 platform. Single-nucleotide variant (SNV) associations with bleeding risk were assessed using logistic regression with additive, dominant, and recessive genetic models. Polygenic risk scores (PRSs) were calculated to evaluate cumulative genetic effects.ResultsNo SNVs reached Bonferroni-corrected significance under any model. PRSs showed weak predictive ability for bleeding with apixaban. For rivaroxaban, regression indicated that ln Css min/D + 1 index increased with PRS, age, and 6-β-hydroxycortisol/cortisol ratio, but decreased with higher 6-β-hydroxycortisol and coronary heart disease presence. No statistically significant differences were found for the PharmGKB Level 3 variants rs1045642 (rivaroxaban) and rs2231142 (apixaban). Trends toward statistical significance were observed for the rs2472304-G variant in rivaroxaban users, rs6977165-C in apixaban users, and for the CYP3A4*1/*36 diplotype.ConclusionResidual equilibrium concentration of DOACs, including dose-adjusted, did not independently predict bleeding risk in non-valvular AF patients. Variants rs2472304 and rs6977165 may warrant further investigation as potential contributors to bleeding risk.

Humans↗

PubMed2025

Molecular analysis of lung adenocarcinomas from the SAFIR02-Lung cohort reveals new metastasis-associated copy-number alterations including frequent mutant-specific KRAS-allelic imbalance and identifies CDKN2A homozygous deletions as an independent biomarker of poor prognosis.

BACKGROUND: Identifying molecular alterations specific to advanced lung adenocarcinomas could provide insights into tumour progression and dissemination mechanisms. METHOD: We analysed tumour samples, either from locoregional lesions or distant metastases, from patients with advanced lung adenocarcinoma from the SAFIR02-Lung trial by targeted sequencing of 45 cancer genes and comparative genomic hybridisation array and compared them to early tumours samples from The Cancer Genome Atlas. RESULTS: Differences in copy-number alterations frequencies suggest the involvement in tumour progression of LAMB3, TNN/KIAA0040/TNR, KRAS, DAB2, MYC, EPHA3 and VIPR2, and in metastatic dissemination of AREG, ZNF503, PAX8, MMP13, JAM3, and MTURN. Conversely, no meaningful difference was found in pathogenic single-nucleotide variant frequencies, reinforcing the notion that they are early events in tumorigenesis. CDKN2A homozygous deletion was linked to poor clinical outcome in patients with early tumours (overall survival hazard ratio 2.17, 95% CI: 1.43-3.28, corrected p-value = 0.01). Furthermore, we found that KRAS mutant allele specific imbalance, i.e. focal amplification of the mutant allele, is more prevalent in locoregional or distant samples of metastatic patients than in early lesions (8.4%, 13% and 2.8% respectively). This observation was replicated in three public cohorts. Tumours with KRAS mutant allele specific imbalance show specific patterns of co-occurrence and mutual exclusion with alterations in key cancer genes like CDKN2A, TP53, STK11 and NKX2-1, often in a tumour type dependent manner. CONCLUSION: Advanced LUAD tumours exhibit higher copy-number alteration burden, with distinct alterations associated with tumour progression and metastasis. CDKN2A homozygous deletions predict poor prognosis in early disease, while KRAS mutant allele-specific imbalance is enriched in advanced tumours.

Humans↗

PubMed2025

Assessing the causal association between celiac disease and Alzheimer disease and frontotemporal dementia: A bidirectional Mendelian randomization approach.

This study aimed to investigate the bidirectional causal relationship between celiac disease (CD) and the risk of Alzheimer disease (AD) or frontotemporal dementia (FTD) using Mendelian randomization (MR), in order to clarify prior inconsistent findings. We analyzed summary-level genome-wide association study (GWAS) data for CD, AD, and FTD. Single-nucleotide polymorphisms (SNPs) strongly associated with each condition were selected as genetic instruments. MR analysis was conducted in 2 directions: from CD to AD/FTD and from AD/FTD to CD. Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) was used to detect and correct for pleiotropy, and Cochran Q assessed heterogeneity. Leave-one-out and Mendelian Randomization-Egger (MR-Egger) regression sensitivity analyses were performed to evaluate robustness. No evidence of a causal effect was found between CD and either AD or FTD in either direction (P > .05). Similarly, genetic liability to AD or FTD did not increase the risk of CD. Sensitivity analyses supported the robustness of the results, showing no pleiotropy or heterogeneity. Our findings suggest that CD is not causally linked to the development of AD or FTD. While shared genetic factors or comorbidities may exist, the association is likely noncausal, and other mechanisms of cognitive decline in CD patients warrant further study.

Humans↗

PubMed2026

Genetic Correlation Between Brain Imaging Phenotypes and Externalizing Behavior: A Large-Scale LDSC Analysis of UK Biobank IDPs.

Externalizing has been associated with differences in brain structure and function; however, it remains unclear whether these associations reflect shared common-variant genetic influences. Cross-trait linkage disequilibrium score regression was used to estimate genome-wide genetic correlations between externalizing genome-wide association study (GWAS) results and 3,935 brain imaging-derived phenotypes from the UK Biobank BIG40 resource. The imaging phenotypes covered structural magnetic resonance imaging (MRI), diffusion MRI, susceptibility-weighted imaging, resting-state functional MRI, and task-based functional MRI. Results were included in the primary analysis when the imaging phenotype had positive single-nucleotide polymorphism (SNP) heritability, a heritability Z statistic of at least 1.96, a mean GWAS chi-square statistic of at least 1.02, at least 200,000 regression SNPs, and a complete LDSC result without a fatal error. Technical imaging quality-control phenotypes were excluded from biological inference. Individual results were corrected using the Benjamini-Hochberg false discovery rate procedure. Aggregated Cauchy association tests (ACATs) were used to evaluate evidence across all imaging phenotypes and within predefined imaging categories. Statistical power, simultaneous confidence bounds, and alternative quality-control definitions were examined in sensitivity analyses. Of the 3,935 imaging phenotypes, 3,716 produced estimable genetic correlations, 2,980 met the primary LDSC quality-control criteria, and 2,967 were classified as biological imaging phenotypes. No individual phenotype survived false discovery rate correction. The smallest unadjusted P value was 0.0005, and the minimum adjusted q value was 0.486. The distribution of genetic correlations was centered near zero, with a median genetic correlation of 0.0014 and a median absolute genetic correlation of 0.0338. ACAT provided no evidence of an aggregate association across all biological imaging phenotypes (P = 0.302), and no predefined imaging category survived multiple-testing correction. The median minimum detectable genetic correlation at 80% power was 0.216. Bonferroni-adjusted simultaneous confidence intervals were fully contained within the interval [-0.30, 0.30] for 80.0% of phenotypes in the primary analysis and 88.0% under the stringent heritability quality-control definition. Broad and stringent sensitivity analyses produced the same overall conclusions. In this study, no statistically robust evidence of genome-wide genetic correlations between externalizing and individual UK Biobank brain imaging phenotypes was found. Nevertheless, small, localized, mixed-direction, or developmentally specific genetic effects remain possible.

Journal Article↗

PubMed2026

The causal relationship between multiple cardiovascular diseases and glioblastoma: A Mendelian randomization study.

Observational studies suggest an association between glioblastoma (GBM) and cardiovascular diseases (CVDs), but a causal relationship remains unestablished. This study aimed to investigate the causal link between multiple CVDs and GBM risk. The inverse variance weighted method indicated that all 18 CVDs had significant causal associations with GBM (P < .05). Genetically predicted CVDs were uniformly associated with a lower risk of GBM (odds ratio < 1), identifying them as potential protective factors. Sensitivity analyses confirmed the absence of significant heterogeneity or horizontal pleiotropy, and the MR-Steiger test validated the correct causal direction. This Mendelian randomization (MR) study provides evidence that a range of CVDs are causally associated with a decreased risk of developing GBM. These findings suggest shared biological pathways and offer new insights for understanding GBM etiology. We conducted a 2-sample MR analysis using publicly available genome-wide association study data. GBM was the outcome, and 18 cardiovascular-related traits (including coronary artery disease, myocardial infarction, and venous thromboembolism) were exposures. Instrumental variables were single-nucleotide polymorphisms significantly associated with exposures (P < 5 × 10-8). The primary analysis used the inverse variance weighted method, supplemented with MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses, including Cochran Q test, MR-Egger intercept test, leave-one-out analysis, and MR-Steiger directionality test, were performed to ensure robustness.

Causality↗

PubMed2024

Association of different milk fat content with coronary artery disease and myocardial infarction risk: A Mendelian randomization study.

BACKGROUND: Numerous observational studies have investigated on the correlation of whole, semi-skimmed, and skimmed milk with coronary artery disease (CAD) and myocardial infarction (MI) risk; However, no consensus has been reached and evidence on any causal links between these exposures and outcomes remains unclear. This study aimed to conduct univariate and multivariate Mendelian randomization (MR) analyses, using publicly released genome-wide association study summary statistics (GWAS) from the IEU GWAS database, to ascertain the causal association of milk with various fat content with CAD and MI risk. METHODS: For the exposure data, 29, 15, and 30 single-nucleotide polymorphisms for whole milk, semi-skimmed milk, and skimmed milk, respectively, obtained from 360,806 Europeans, were used as instrumental variables. CAD and MI comprised 141,217 and 395,795 samples, respectively. We used inverse variance weighted (IVW), weighted median, MR-Egger regression, and MR Pleiotropy Residual Sum and Outlier analyses to determine whether pleiotropy and heterogeneity could skew the MR results. Sensitivity tests were conducted to verify the robustness of the results. RESULTS: After adjusting for false discovery rates (FDR), we discovered proof that skimmed milk intake is a genetically predicted risk factor for CAD (odds ratio [OR] = 5.302; 95% confidence interval [CI] 2.261-12.432; P < 0.001; FDR-corrected P < 0.001) and MI (OR = 2.287; 95% CI 1.218-4.300; P = 0.010; FDR-corrected P = 0.009). Most sensitivity assessments yielded valid results. Multivariable MR for CAD and MI produced results consistent with those obtained using the IVW method. There was no causal relationship between whole or semi-skimmed milk, and CAD or MI. CONCLUSION: Our findings indicate that the consumption of skimmed milk may increase the risk of CAD and MI. This evidence may help inform dietary recommendations for preventing cardiovascular disease. Further studies are required to elucidate the underlying mechanisms.

Humans↗

PubMed2026

Robust error-minimization in the genetic code across physicochemical metrics and variant codes: A graph-theoretic analysis in GF(2)6.

The standard genetic code reduces the impact of point mutations, but the robustness of this property across physicochemical metrics, naturally occurring variant codes, and codon-reassignment mechanisms remains incompletely quantified. Embedding the 64 codons in GF(2)6 represents the hypercube Q6 as a coordinate-dependent subgraph of the encoding-independent single-nucleotide mutation graph H(3,4), and enables continuous ρ-interpolation between the two. Under a quartet-pattern shuffle null (n=10,000), the standard code is significantly low-cost across four established, code-independent physicochemical distance metrics with partially overlapping content (Grant ham p=0.0062; Miyata p<0.001; Woese polar requirement p=0.003; Kyte-Doolittle hydropathy p=0.001), and the signal strengthens monotonically as ρ moves Q6→H(3,4). A structure-aware sensitivity analysis under the alignment-derived ProtSub matrix (Jia & Jernigan 2021) yields the most extreme percentile of any measure tested (p=0.0004; all five p-values pass Bonferroni at α=0.05). Across the 27 NCBI translation tables, near-optimality is preserved: 11 of 12 informative-distance variants retain top-5% placement after BH-FDR correction. Natural codon reassignments avoid disrupting codon-family connectivity: under the encoding-independent H(3,4) adjacency, observed events are topology-breaking at relative risk 0.32 versus the candidate landscape (permutation p≤10-4). The H(3,4) result is stable by construction; the Q6 decomposition is representation-specific and fails to show depletion under 8 of 24 base-to-bit encodings, so we report H(3,4) as the primary test and Q6 as a sensitivity. Event-level conditional-logit modelling shows that topology avoidance and local physicochemical cost provide complementary, only weakly correlated signal (rs=0.15), and that topology adds explanatory value beyond physicochemistry under both Q6 and encoding-independent H(3,4) adjacency. Retrospective reanalysis of nine genome-recoding datasets is consistent with codon-family topology operating as an evolutionary-trajectory constraint distinct from acute engineering fitness. The contribution is the second axis: code evolution is jointly constrained by physicochemical smoothness and codon-family topological integrity, and these two constraints are partly independent.

Codon reassignment↗

PubMed2026

Advances in CRISPR Base Editing: From Molecular Evolution to Therapeutic Applications in Genomic Medicine.

CRISPR-Cas9 systems revolutionized gene editing, but inherent drawbacks, namely DNA double-strand breaks (DSBs) and the difficulty of achieving precise repairs (due to low HDR efficiency), led researchers to invent new, more accurate gene editing tools. Base editing represents a significant leap forward, enabling targeted single-nucleotide conversions directly on the DNA without DSBs or donor templates. The core technology involves fusing catalytically dead or nickase Cas proteins to DNA deaminase enzymes. Cytosine base editors (CBEs) convert C•G to T•A pairs, while adenine base editors (ABEs) change A•T to G•C. These editors exploit the deaminase function within the R-loop structure formed by Cas binding and co-opt endogenous DNA repair mechanisms for precision. While offering improved efficiency and editing precision, base editing faces persistent challenges, such as off-target effects, bystander edits, delivery and ethical concerns. Continuous engineering efforts have refined these tools, enhancing accuracy, expanding targetability and reducing unwanted edits. The base editing arsenal has also broadened to include C-to-G base editors (CGBEs), dual A&C editors and versions targeting organelles. Successful preclinical studies demonstrating the correction of mutations responsible for the disease have paved the way for clinical trials, which are now testing therapies for conditions like sickle cell disease, β-thalassaemia and hypercholesterolemia using various delivery systems. This review explores CRISPR base editing's origins, mechanisms of action, potential therapies and current restrictions, pointing to its broadening impact on medical genetics.

Humans↗

PubMed2026

No receptor-binding domain adaptation detected in within-host H5N1 surveillance of 4,559 US dairy outbreak sequences.

BACKGROUND: The 2024-2026 US H5N1 clade 2.3.4.4b dairy cattle outbreak has been characterised primarily through consensus-level phylogenetics. Whether mammalian-adaptation variants are emerging at sub-consensus frequencies within infected hosts, particularly at the haemagglutinin receptor-binding domain (RBD), remains unknown because no systematic within-host variant analysis of the public sequencing corpus has been performed. METHODS: We conducted a pre-registered, corpus-wide intrahost single-nucleotide variant (iSNV) analysis of all publicly available H5N1 cattle, feline-spillover, and retail-milk sequences on the NCBI Sequence Read Archive (4559 samples across 7 BioProjects). A dual-caller concordance pipeline (iVar + LoFreq) with empirically determined allele frequency (AF) threshold (3%, set via four-criterion validation including synthetic spike-in controls) was applied to an 11-site Tier 1 mammalian-adaptation panel spanning the polymerase complex, haemagglutinin RBD, and accessory proteins. Within-host nucleotide diversity was compared across host categories. RESULTS: The HA RBD sites Q226L and G228S (H3 numbering) showed zero detections across >4300 adequately sequenced samples at all AF thresholds tested (1-5%), despite the pipeline detecting other non-synonymous variants at these exact codon positions (upper 95% CI for prevalence: 0.08%). Seven of eleven adaptation sites carried statistically significant iSNV signals after Bonferroni correction (corrected α = 0.00417), though all at low prevalence (≤2.95%). Genotype stratification showed that most polymerase-site detections reflected genotype structure rather than within-host emergence: the apparent PB2 631 L→M "reversion" was largely the ancestral avian state of the D1.1 genotype (20 of 23 detections), which never acquired the 631L mammalian adaptation, with only two genuine sub-consensus events in the B3.13 background, while consensus-level PB2 701N was a fixed feature of the D1.1 genotype (10 of 14 detections) rather than independent sub-consensus emergence. Cattle exhibited significantly higher within-host nucleotide diversity than feline-spillover samples (π = 1.59 × 10-4 vs 6.11 × 10-5; Kruskal-Wallis p = 6.6 × 10-15), a finding that persisted after depth-matching (p = 4.6 × 10-5); this may reflect prolonged mammary-gland infection, though sampling differences and host biology cannot be excluded. CONCLUSIONS: We did not detect HA receptor-switching adaptation (the acquisition of human-type α2,6 receptor binding via Q226L/G228S) at any tested allele frequency in the US dairy H5N1 outbreak. Sub-consensus mammalian-adaptation signals exist at polymerase-complex sites but at low prevalence, are genotype-structured rather than independently recurrent, and require functional characterisation before informing risk assessment.

Dairy cattle↗

PubMed2026

SeqQC-former: A sequence-quality fusion framework for QC-aware review prioritization of candidate somatic SNVs in cancer genomics.

The accurate prioritization of candidate somatic single-nucleotide variants (SNVs) remains a challenge due to the substantial variability in sequencing quality across genomic loci. SeqQC-Former is a sequence-quality fusion framework that integrates the local nucleotide context with read-level quality-control (QC) covariates derived from matched tumor-normal sequencing data. This integration generates QC-aware prioritization scores for the downstream review of candidate variants. Unlike conventional variant callers, SeqQC-Former is designed not to infer biological truth but to support post-calling review and prioritization under heterogeneous sequencing conditions. The framework was trained and evaluated on a SEQC2-derived dataset comprising 89,447 candidate loci, including 1378 positive and 88,069 negative loci. In chromosome-held-out validation, which aims to reduce potential genomic-position leakage, SeqQC-Former demonstrated strong discrimination (AUROC = 0.9479; AUPRC = 0.9448), indicating good generalization to previously unseen chromosomes. Given that the SEQC2-derived labels contain QC-associated information; these results should be interpreted as an evaluation of QC-aware prioritization capability rather than an independent validation of biological variant correctness. Ablation analyses revealed that structured QC covariates provided the dominant predictive signal under the current SEQC2-derived labeling regime. SeqQC-Former achieved a significantly higher AUROC than classical machine-learning baselines, as determined by DeLong's test (p < 0.01). Application to 53,164 glioblastoma variants demonstrated that external predictions were sensitive to QC scaling and threshold selection, underscoring that model outputs should be interpreted as QC-dependent prioritization scores rather than calibrated probabilities or definitive biological classifications. Overall, SeqQC-Former offers a reproducible post-calling QC-aware prioritization framework for large-scale somatic SNV review and underscores the importance of explicitly modeling sequencing-quality information when interpreting structured cancer genomics datasets.

Humans↗