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PubMed2026

Robust human genetic evidence supporting causal effects of FGF21 on reducing alcohol consuming behaviours.

BACKGROUND: Alcohol use disorder (AUD) represents a tremendous societal burden, yet few efficacious therapies are available and widely used. Pre-clinical and human observational data support fibroblast growth factor 21 (FGF21) as a promising therapeutic target for the treatment of AUD. The objective of this study is to identify a robust genetic instrument for FGF21 agonism and leverage it to explore the effects of FGF21 agonism on AUD and related traits, as well as metabolic outcomes more widely. METHODS: We first compared associations with the positive control outcomes of liver fat and liver cirrhosis risk for the FGF21 cis-protein quantitative trait locus (cis-pQTL) (rs838131) to those for the common allele FGF21 L174P missense variant (rs739320). Having identified the L174P missense variant as a plausible genetic instrument, we subsequently performed association analyses investigating effects on AUD, related traits, and metabolic outcomes more widely. Finally, we performed colocalisation analyses to test whether observed association results reflect a causal mechanism that overlaps with the clinical effects of FGF21 on liver fat and liver cirrhosis. RESULTS: Consistent association and colocalisation evidence support a protective association between genetically predicted FGF21 agonism and alcohol consumption (association p = 1 × 10-18, colocalisation posterior probability = 0.90), problematic alcohol use (association p = 0.02, posterior probability = 0.64), and AUD (association p = 9 × 10-8, posterior probability = 0.97). Similar evidence was also observed for favourable effects of FGF21 on improving kidney function, lowering triglyceride levels, lowering proportional energy intake from carbohydrates, increasing proportional energy intake from protein and fat, increasing body weight and lowering waist-to-hip ratio. CONCLUSIONS: This study identifies a genetic instrument for FGF21 effects to provide causal human evidence supporting favourable effects of FGF21 analogues for the treatment of AUD and related traits, as well as on metabolic outcomes more broadly. Further clinical study is duly warranted.

Humans↗

PubMed2026

Genome-wide interactions with cadmium exposure in dysglycemia: Populational effects and molecular insights.

Dysglycemia is a complex metabolic disorder governed by the interplay between environmental exposures and genetic factors, yet the precise molecular mechanisms driving these gene-environment (G×E) interactions remains poorly understood. Here, we characterized the population-level landscape and molecular causality underlying the interactions between cadmium (Cd), a widespread environmental toxicant, and genetic susceptibility loci in dysglycemia. By conducting a Genome-wide Environmental Interaction (GWEI) study within a sub-cohort of the China National Human Biomonitoring (CNHBM) cohort (N = 1298), we identified 29 genetic risk loci that significantly interact with Cd burden to exacerbate elevated fasting plasma glucose levels. Functional enrichment integrated with metabolomic profiling unmasked a profound multi-omics convergence, positioning epigenetic modifications (e.g. H3K27me3) and zinc-finger transcription factors (e.g. OVOL2, KLFs) as central regulatory hubs that disrupt metabolic homeostasis. To establish causality, we demonstrated that the rs11743277 A>T variant at the lead G×E locus functions as a Cd-responsive enhancer element, facilitating recruitment of TEAD3 and upregulating TICAM2 expression in CRISPR/Cas9-edited HepG2 cells, especially upon Cd exposure. This initiates a TICAM2-mediated inflammatory response, with elevated pro-inflammatory cytokines (IFN-β, TNF-α, IL-6) impairing downstream insulin signaling and glucose utilization. Collectively, these findings establish a robust paradigm for G×E interactions in complex metabolic disorders, revealing how environmental stressors reprogram genetic susceptibilities through molecular checkpoints and paving the way for tailored, precision-prevention strategies in environmental health.

CRISPR/Cas9 editing↗

PubMed2001

The power to detect linkage disequilibrium with quantitative traits in selected samples.

Results from power studies for linkage detection have led to many ongoing and planned collections of phenotypically extreme nuclear families. Given the great expense of collecting these families and the imminent availability of a dense diallelic marker map, the families are likely to be used in allelic-association as well as linkage studies. However, optimal selection strategies for linkage may not be equally powerful for association. We examine the power to detect linkage disequilibrium for quantitative traits after phenotypic selection. The results encompass six selection strategies that are in widespread use, including single selection (two designs), affected sib pairs, concordant and discordant pairs, and the extreme-concordant and -discordant design. Selection of sibships on the basis of one extreme proband with high or low trait scores provides as much power as discordant sib pairs but requires the screening and phenotyping of substantially fewer initial families from which to select. Analysis of the role of allele frequencies within each selection design indicates that common trait alleles generally offer the most power, but similarities between the marker- and trait-allele frequencies are much more important than the trait-locus frequency alone. Some of the most widespread selection designs, such as single selection, yield power gains only when both the marker and quantitative trait loci (QTL) are relatively rare in the population. In contrast, discordant pairs and the extreme-proband design provide power for the broadest range of QTL-marker-allele frequency differences. Overall, proband selection from either tail provides the best balance of power, robustness, and simplicity of ascertainment for family-based association analysis.

Alleles↗

PubMed2026

Reference-Free Microsatellite Instability Detection from Tumor Sequencing Using Intrasample Variability Modeling.

Microsatellite instability (MSI) is a predictive biomarker in several tumor types. However, many next-generation sequencing-based callers require matched normal samples, reference panels, or pretrained models, limiting their portability across assays and sequencing centers. We developed PROMIS (PROfiling of Microsatellite InStability), a tumor-only, reference-free pipeline that uses a discrete mixture model to characterize intrasample repeat-length distributions at predefined microsatellite loci. Locus-level classifications are then aggregated into a continuous MSI score. We benchmarked PROMIS in colorectal (CRC), endometrial (UCEC), and gastric (STAD) cancers from The Cancer Genome Atlas. PROMIS achieved an overall area under the receiver operating characteristic curve (AUC) of 0.995 and cohort-specific AUCs of 1.00 in CRC and stomach adenocarcinoma and 0.999 in uterine corpus endometrial carcinoma, comparable to established tools despite not using matched normals or pretrained models. Subsampling demonstrated robust performance with substantially fewer loci. In silico dilution showed progressively reduced MSI-microsatellite-stable discrimination, with the pooled AUC declining from 0.83 at 10% tumor fraction to 0.53 at 1%. At low tumor fractions, tumor-type-specific baseline microsatellite variability increasingly influenced PROMIS scores. Finally, in prostate and CRC cell-free DNA cohorts, including Illumina TSO500 data and an 18-gene panel, PROMIS yielded MSI scores concordant with orthogonal tissue- and panel-based classifications across the evaluated Illumina-based sequencing contexts. Accordingly, the present validation should be considered limited to Illumina-based sequencing platforms. PROMIS is intended to complement existing genomic profiling workflows by enabling MSI assessment from sequencing data already generated for broader molecular analyses. Prospective clinical validation remains necessary before clinical implementation.

Journal Article↗

PubMed2025

Genome-Wide Association Analyses of HPV16 and HPV18 Seropositivity Identify Susceptibility Loci for Cervical Cancer.

Infection by high-risk human papillomavirus is known to exacerbate cervical cancer development. The host immune response is crucial in disease regression. Large-scale genetic association studies for cervical cancer have identified few susceptibility variants, mainly at the human leukocyte antigen locus on chromosome 6. We hypothesized that the host immune response modifies cervical cancer risk and performed three genome-wide association analyses for HPV16, HPV18 and HPV16/18 seropositivity in 7814, 7924, and 7924 samples from the UK Biobank, followed by validation genotyping in the German Cervigen case-control series of cervical cancer and dysplasia. In GWAS analyses, we identified two loci associated with HPV16 seropositivity (6p21.32 and 15q26.2), two loci associated with HPV18 seropositivity (5q31.2 and 14q24.3), and one locus for HPV16 and/or HPV18 seropositivity (at 6p21.32). MAGMA gene-based analysis identified HLA-DQA1 and HLA-DQB1 as genome-wide significant (GWS) genes. In validation genotyping, the genome-wide significant lead variant at 6p21.32, rs9272293 associated with overall cervical disease (OR = 0.86, p = 0.004, 95% CI = 0.78-0.95, n = 3710) and HPV16 positive invasive cancer (OR = 0.73, p = 0.005, 95% CI = 0.59-0.91, n = 1431). This variant was found to be a robust eQTL for HLA-DRB1, HLA-DQB1-AS1, C4B, HLA-DRB5, HLA-DRB6, HLA-DQB1, and HLA-DPB1 in a series of cervical epithelial tissue samples. We additionally genotyped twenty-four HPV seropositivity variants below the GWS threshold out of which eleven variants were found to be associated with cervical disease in our cohort, suggesting that further seropositivity variants may determine cervical disease outcome. Our study identifies novel genomic risk loci that associate with HPV type-specific cervical cancer and dysplasia risk and provides evidence for candidate genes at one of the risk loci.

Humans↗

PubMed2026

DAZL-targeted inducible kill switches enable efficient ablation of chicken primordial germ cells.

Competition from endogenous primordial germ cells (PGCs) in recipient embryos limits the generation of fully donor-derived offspring in avian surrogate-host systems. An inducible and germline-restricted ablation strategy is therefore needed to create sterile recipients without compromising somatic development. Using CRISPR/Cas9-mediated homology-directed repair, we inserted three inducible suicide-gene cassettes (iCaspase9, RapaCasp9, and CD) into the endogenous DAZL locus of chicken PGCs. All knock-in lines showed stable reporter expression and retained typical PGC morphology. Comparative functional analyses identified iCaspase9 activated by AP20187 as the most sensitive and specific ablation system, achieving near-complete killing at nanomolar concentrations without detectable toxicity in control cells. RapaCasp9 induced with rapamycin also ablated engineered PGCs efficiently, but rapamycin caused marked non-specific growth inhibition in control cells. Replacing rapamycin with the synthetic A/C heterodimerizer AP21967 largely eliminated this off-target toxicity while preserving rapid and robust killing. By contrast, yeast-derived CD variants did not substantially improve 5-fluorocytosine sensitivity in chicken PGCs. DAZL-restricted iCaspase9/AP20187 and the optimized RapaCasp9/AP21967 system provide efficient inducible kill switches for chicken PGCs in vitro. These platforms establish a practical genetic toolkit for generating sterile surrogate hosts to support avian genome editing, germline replacement, and Sire Dam Surrogate breeding.

CRISPR/Cas9↗

PubMed2026

Integration of Genome-Wide Association Studies With Single-Cell and Bulk Expression Quantitative Trait Locus to Identify Stroke Susceptibility Genes.

BACKGROUND: Previous studies have integrated genome-wide association studies with expression quantitative trait locus (eQTL) data from bulk tissues to identify stroke susceptibility genes. However, eQTL data exhibit high cell-type specificity, and genetic variants may have distinct effects across stroke subtypes. METHODS: We applied the summary-data-based Mendelian randomization (MR) method to integrate eQTL data from 7 brain cell types with genome-wide association studies data for 5 stroke phenotypes (stroke, ischemic stroke, cardioembolic stroke, large artery stroke, and small vessel stroke). Results were compared with summary-data-based MR using eQTL data from 49 tissues in the Genotype-Tissue Expression project. Robustness of significant single-cell summary-data-based MR associations was assessed via MR and colocalization analyses. Further evaluations included single-cell RNA-seq differential expression, protein-protein interaction, druggability, and phenome-wide association studies. RESULTS: Single-cell summary-data-based MR identified many novel significant genes not detected using bulk tissue eQTL data. Validated associations revealed 2 stroke risk genes (LRCH1, ICA1L), 3 stroke protective genes (AHI1, LYRM9, CENPQ), 2 large artery stroke risk genes (LIPA, ELL), and 1 ischemic stroke protective gene (CENPQ). Single-cell RNA-seq showed significantly increased LIPA expression in mouse stroke samples compared with controls. Protein-protein interaction and druggability analyses, along with phenome-wide association studies, prioritized LIPA and LRCH1 as potential therapeutic targets for stroke while indicating possible adverse effects. CONCLUSIONS: Integrating single-cell eQTL with stroke-subtype genome-wide association studies uncovers novel cell-type-specific causal genes and highlights promising therapeutic targets, advancing understanding of stroke pathogenesis.

Genome-Wide Association Study↗

PubMed2025

A comprehensive evaluation of candidate genetic polymorphisms in a large histologically characterized MASLD cohort using a novel framework.

BACKGROUND: There is a substantial heritable component to metabolic dysfunction-associated steatotic liver disease (MASLD), and several genetic variants that promote MASLD development or associate with its severity have been reported. These associations vary in terms of their effect size and degree of replication. METHODS: We developed a framework to classify previously identified MASLD genetic polymorphisms into 4 tiers based on effect size and extent of replication in the literature. We tested the association between "tier 1" single-nucleotide polymorphisms (OR ≥1.5, replicated in >2 independent studies) and biopsy measures of MASLD severity in a large, well-characterized histologic cohort of MASLD patients (n=3094). RESULTS: Across 19 "tier 1" variants reflecting 11 genetic loci, only those in the PNPLA3-SAMM50-PARVB locus showed significant associations with biopsy-proven fibrosis severity and NAFLD activity score; the highest risk was for the rs738409 p.I148M variant in PNPLA3. A genetic risk score based on "tier 1" variants, as well as a previously developed genetic risk score based on variants in PNPLA3, TM6SF2, and HSD17B13, were both associated with fibrosis and NAFLD activity score, but these results were driven entirely by PNPLA3 rs738409. CONCLUSIONS: Our study provides a framework to prioritize evaluation of genetic polymorphisms for future replication efforts and demonstrates that in a large case-only cohort, histologic severity of MASLD is only robustly associated with the presence of variation in PNPLA3 among known candidate genes. These findings may have implications for patient risk stratification based on the presence of PNPLA3 rs738409.

Humans↗

PubMed2026

Genetic and epigenetic underpinnings of biological aging: a multi-omics study integrating Mendelian randomization, spatial transcriptomics, and drug target discovery.

Inflammaging represents a hallmark of biological aging, yet the causal inflammatory mediators driving multi-dimensional epigenetic aging and their effector genes remain poorly characterized at the genetic level. We developed a four-tier analytical framework integrating causal screening, multi-omics effector gene mapping, spatial transcriptomics, and drug target evaluation. Two-sample Mendelian randomization (MR) of 91 circulating inflammatory proteins against six aging phenotypes identified IL-12B, IFNG, and IL-2 as the most robust pro-aging mediators with consistent effects across independent outcomes. Using multi-omics summary-based MR (SMR) as the core analytical engine, we integrated four-layer whole-blood molecular QTL resources eQTL (eQTLGen, n = 31,684), sQTL (GTEx, n = 755), pQTL (INTERVAL + SCALLOP, n = 34,232), and mQTL (McRae et al., n = 1,980) - with GWAS summary statistics for four epigenetic age acceleration measures. At a stringent threshold (P_SMR < 1×10⁻¹²), seven high-confidence effector genes were identified: NHLRC1, TPMT, SELP, and RIPPLY3 for IEAA; ZNF373A and PLDN for HannumAA; and EDARADD for PhenoAA. The chromosome 6p21 NHLRC1-TPMT locus, overwhelmingly driven by methylation QTL signals (-log₁₀P = 26.06), emerged as the dominant genetic node of epigenetic aging. Spatial projection via gsMap onto a mouse E16.5 embryo atlas (121,767 cells) revealed preferential enrichment in smooth muscle and lung, with EDARADD showing marked specificity in mucosal epithelium. Cross-database drug target mining classified TPMT and SELP as repurposable known targets and NHLRC1 as a high-priority novel druggable candidate. This study provides multi-omics convergent causal evidence for inflammation-driven epigenetic aging and delivers genetically anchored targets for precision anti-aging intervention.

Aging↗

PubMed2026

Tandem duplication-driven expansion and UV-B stress adaptation of the LHC gene family in Artemisia annua L.

BACKGROUND: Artemisia annua L., is the primary natural source of the antimalarial drug artemisinin. In nature, fluctuating light is a major environmental stress that affects plant growth and artemisinin biosynthesis. Although the light-harvesting chlorophyll a/b-binding (LHC) superfamily plays a key role in mediating plant responses to fluctuating light, systematic research of this gene family in A. annua has not yet been conducted, limiting our understanding of light adaptation in this medicinally important species. RESULTS: This study investigated the evolutionary dynamics and functional adaptation of the light-harvesting chlorophyll a/b-binding (LHC) superfamily in A. annua, with a focus on the early light‑induced protein (ELIP) subfamily. Comparative genomics of 24 plant species showed that the LHC superfamily recently expanded in the examined Asteraceae lineages through duplication events. In A. annua, 229 LHC genes identified from four haplotype genomes comprised 205 allelic and 24 haplotype-specific loci, with the ELIP subfamily expanding significantly via tandem duplication. Notably, compared to non-Asteraceae plants, ELIPs exhibited a uniform single-exon architecture, indicating it is a genomic feature unique to Asteraceae plants. Population genomics of 41 individuals showed dynamic copy number variations ranging from 1 to 4 copies per locus. Interestingly, a structurally disrupted ELIP allele remained transcriptionally active and produced long aberrant transcripts, showing that this subfamily is still actively evolving. Under UV-B stress, AaELIP loci showed synchronized induction trend but differed in expression levels, suggesting a division into major and auxiliary roles within the expanded tandem cluster. Overall, while the response of ELIPs to light stress is evolutionarily conserved, this dramatic expansion and structural streamlining of AaELIPs may represent a key evolutionary adaptation that enhances the plant's ability to cope with intense light and radiation stress. CONCLUSIONS: Collectively, this study demonstrates a significant expansion of the LHC superfamily in A. annua, especially within the ELIP subfamily, as well as its robust response to UV-B treatment, underscoring the essential role of ELIPs in mediating light stress responses. These findings provide a valuable foundation for future research to uncover the molecular mechanisms underlying A. annua's adaptation to complex light environments.

Artemisia annua↗

PubMed2026

Disruption of major Ptchd1 isoforms causes autistic traits in social behavior and communication.

PTCHD1 is an X-linked three-exon gene associated with autism spectrum disorder (ASD) and/or intellectual disability (ID). Mice lacking Ptchd1 exon 2 (Ptchd1Δexon2) exhibit hyperactivity and learning impairments, but do not recapitulate ASD-like traits. Through mapping of clinically reported loss-of-function mutations in human patients, we determined that PTCHD1 exon 3 is a high-risk locus. We therefore generated an alternative Ptchd1 knockout mouse model by targeting Ptchd1 exon 3 (Ptchd1Δexon3) using CRISPR/Cas9. Our analyses revealed that two major PTCHD1/Ptchd1 transcripts-a (full-length) and c (shorter)-were expressed in the brain. In Ptchd1Δexon2 mice, Ptchd1_a was lost, but Ptchd1_c was compensatorily upregulated, and these mice showed no ASD-like social deficits. In Ptchd1Δexon3 mutants, both Ptchd1_a and Ptchd1_c were lost, along with dysregulation of social and communication behaviors, increased repetitive behavior, and motor and learning impairments. Our side-by-side analyses of Ptchd1Δexon2 and Ptchd1Δexon3 mice suggest a functional link between PTCHD1/Ptchd1 and ASD, demonstrating that loss-of-function mutations disrupting C-terminal Ptchd1 lead to robust ASD-relevant phenotypes in mice, more faithfully recapitulating clinically observed traits.

Animals↗

PubMed2026

Identification of compounds that repress DUX4 expression in facioscapulohumeral muscular dystrophy.

Facioscapulohumeral muscular dystrophy (FSHD) is caused by epigenetic dysregulation of the disease locus, leading to pathogenic misexpression of DUX4 in skeletal muscle. Thus, most FSHD therapeutic approaches target DUX4. Our previous study identified the chromatin remodeling factor BAZ1A (bromodomain adjacent to zinc finger domain protein 1A) as a promising target for therapeutic development. Here we used an artificial intelligence-based screening pipeline to identify molecules predicted to bind the BAZ1A bromodomain, and validated hit compounds using FSHD-specific assays in FSHD myocytes. One compound, termed C06, emerged as a potent repressor of DUX4 and DUX4 target gene expression. Interestingly, while C06 exhibited binding to BAZ1A in vitro, it can also inhibit multiple kinases, including p38α, an upstream activator of DUX4. Despite this, at low doses C06 was an equally effective and more specific repressor of DUX4 than losmapimod, which is a robust and specific p38 inhibitor. At low concentrations, C06 returns the DUX4 gene expression signature to a healthier profile without major effects on the muscle transcriptome. Thus, C06 is a useful tool for potent and specific DUX4 suppression, and a viable candidate for further development. Our results highlight both the utility and limitations of AI for targeted drug discovery, and the importance of using an FSHD-specific functional screening strategy for selecting relevant candidates.

Muscular Dystrophy, Facioscapulohumeral↗

PubMed2026

Genomic basis of developmental defects of enamel and sex-specific effects.

We conducted a multi-ancestry genome-wide association study (GWAS) of developmental defects of enamel (DDE) in the primary dentition among 6,061 U.S. preschool-aged children (3-5 years). We investigated four DDE phenotypes (demarcated opacities, diffuse opacities, hypoplastic defects, and a combined DDE trait) leveraging main-effect models, joint gene-sex interaction testing (2df), and sex-stratified analyses. SNP-based heritability for the combined DDE trait was estimated at 20%, with concordance analyses robustly supporting a genetic etiology. We identified 39 unique genome-wide significant loci (P<5×10 ), with five surpassing a study-wide Bonferroni-corrected statistical significance criterion (P<1.25×10 9), including Y RNA and ALDH1A1. The main-effect GWAS identified 20 loci, including HBS1L and MYB, genes regulating hematopoiesis with plausible roles in amelogenesis. Joint test and sex-stratified analyses revealed 19 additional loci, including ALDH1A1, TENM2, and DLGAP2, demonstrating sex-specific heterogeneity. Nineteen loci exhibited sex-specific differences after Bonferroni correction (P<2x10-3), including genes involved in retinoic acid signaling (ALDH1A1), odontogenesis (TENM2), and neurodevelopment (DLGAP2, CDH10). Pathway enrichment highlighted ectodermal and synapse organization networks, suggesting shared etiological mechanisms between DDE and systemic conditions like neurofibromatosis and autism spectrum disorder. Notably, no locus generalized in an external GWAS of permanent dentition DDE, underscoring fundamental biological differences in the genetic architectures governing primary versus permanent enamel formation. Crucially, a comprehensive cross-trait pleiotropy lookup against early childhood caries (ECC) revealed no shared genetic architecture, supporting the notion that the established clinical and epidemiological association between DDE and ECC is likely driven by structural defects increasing caries lesion susceptibility rather than genetic pleiotropy. By integrating gene-sex interaction testing, this study offers novel insights into the complex, sexually dimorphic genetic etiology of DDE and augments the biological evidence base that can support the development of precision pediatric dentistry.

developmental defects of enamel↗

PubMed2025

Integrative omics of the genetic basis for wheat WUE and drought resilience reveal the function of TaMYB7-A1.

Improving wheat drought resilience and water use efficiency (WUE) is critical for sustaining productivity under increasing water scarcity. Here, we integrate genome-wide association study (GWAS), expression quantitative trait locus (eQTL) mapping, population-transcriptome analysis, and summary-data-based mendelian randomization (SMR), followed by functional validation using indexed EMS mutants and transgenic lines, to systematically identify key WUE regulators. GWAS across water conditions in 228 accessions identifies 73 quantitative trait loci (QTLs) for WUE-traits. Transcriptome profiling of 110 diverse accessions reveals 28 drought-responsive modules. eQTL mapping uncovers 146,966 regulatory variants, including condition-specific hotspots associated with key drought-related pathways. Integrative analysis underscores 85 high-confidence candidate genes, notably TaMYB7-A1. Overexpression of TaMYB7-A1 enhances photosynthesis, WUE, root development, and grain yield under drought condition by activating TaPIP2;2-B1 (water transport), TaRD20-D1 (stomatal regulation), and TaABCB4-B1 (root growth), reflecting reduced water loss and improved physiological resilience. Our study presents a comprehensive regulatory map and robust targets for wheat drought adaptation and resilient cultivar breeding.

Triticum↗

PubMed2026

Trimeric autotransporter adhesins driving chain-like adhesion diversify surface colonization strategies in Shiga toxin-producing Escherichia coli.

Bacteria frequently colonize host and environmental surfaces under fluid flow. Chain-like adherence pattern (CLAP) is an EibG-mediated surface colonization phenotype of certain Shiga toxin-producing Escherichia coli (STEC) that lack the locus of enterocyte effacement (LEE). EibG, an immunoglobulin-binding trimeric autotransporter adhesin, drives CLAP, but the temporal dynamics and genetic diversity underlying chain formation remain unclear. Here, we use live-cell time-lapse imaging to show that chains arise from single cells that elongate and divide without separation. Under flow, chains resist detachment and undergo shear-dependent fragmentation at cell-cell junctions, releasing viable clonal units that disperse downstream. Comparative genomics reveals diversity among EibG-related adhesins and identifies distinct lineages, including chain-like adhesins (Cla) that mediate CLAP while lacking IgG binding. Screening of 1,354 genomes from England shows that claB is present in 95.6% of strains from major LEE-negative STEC serotypes, highlighting its epidemiological prevalence. Targeted mutagenesis demonstrates that chain formation and IgG binding are mediated by distinct structural domains, revealing the modular functional architecture of these adhesins. Furthermore, we show that EibG, ClaA, and ClaB confer robust resistance to complement-mediated killing. Collectively, these findings establish CLAP as a dynamic, surface-associated strategy of LEE-negative STEC and reveal diversification among adhesins that drive this behavior.

Bacterial Adhesion↗

PubMed2026

Quantitative trait locus qLDC5 regulates primary root branching in an auxin-dependent manner.

L-type lateral root (LLR) density determines root system architecture, affecting nutrient acquisition in rice (Oryza sativa L.), particularly under low-phosphorus conditions. Previous studies identified genotypic differences in LLR density and a quantitative trait locus (QTL) enhancing LLR density on crown roots (qLDC5). We showed that LLR densities on crown and primary roots were closely correlated and confirmed higher LLR density on primary roots in qLDC5 donor DJ123 compared with the African variety NERICA4 using X-ray micro-computed tomography. We confirmed the qLDC5 effect in a field experiment for LLR density on primary roots. LLR densities on primary and crown roots, therefore, appear under similar genetic control. Developmental analyses revealed that DJ123 and NDJ188-a derivative line harboring qLDC5-initiate more lateral root primordia than NERICA4, with a higher proportion progressing to elongation, but that exogenous auxin application reversed this ranking. Within qLDC5, auxin biosynthesis gene OsYUCCA2 and auxin response factor OsARF15 were up-regulated in DJ123. Transcriptome analysis revealed an indirect auxin-mediated regulatory network underlying LLR variation. Differentially expressed genes in DJ123 and NDJ188 were enriched for ent-kaurene and gibberellin metabolism, including the robust induction of OsGA2ox5. These findings suggest qLDC5 increases lateral root density by coordinating gibberellin, auxin, and terpene pathways.

Oryza↗

PubMed2026

Genome-wide association meta-analysis of eating behavior traits revealed one susceptibility locus for emotional eating.

In order to identify new and genome-wide significant loci for eating behavior traits (cognitive restraint, uncontrolled eating and emotional eating), we conducted a meta-GWAS with seven studies of European ancestry (n = 11,250). Eating behavior was assessed using the Three-Factor Eating Questionnaire. Genotype effects of single studies were estimated using additive models adjusting for age, sex, BMI, and principal components and single study results were combined by fixed-effect meta-analysis.For cognitive restraint and uncontrolled eating, no genome-wide significant association could be detected. For emotional eating, one genomic region on chromosome 5 comprising two polymorphisms attained genome-wide significance (P = 4.0×10-8 for rs6877636 and P = 3.2×10-8 for rs6897090). The minor alleles were associated with higher emotional eating scores (β=0.093 ± 0.017), with a similar direction of effect in each study. Both SNPs, in near perfect linkage disequilibrium, mapped to RP11-24P24.1, a processed pseudogene of ornithine decarboxylase 1 (ODC1). Enrichment analysis revealed a significant overlap between genome-wide BMI-associated variants and nominal emotional eating variants, supporting the hypothesis that shared genetic factors may influence both eating behavior traits and obesity risk. Finally, we observed a number of interesting associations reaching suggestive significance (P < 10-6) involving BMI candidate genes, including a suggestive association between FTO variants and cognitive restraint (rs9922708, β = 0.069, P = 5.9×10-7).In conclusion, our meta-GWAS identified for the first time a robust chromosomal region associated with emotional eating in seven studies. Given that emotional eating strongly influences body weight but is often stigmatized, recognizing genetic susceptibility to certain eating behaviors may help reduce stigma and alleviate guilt.

Journal Article↗

PubMed2025

Genetic pleiotropy underlying obesity and autoimmune disorders: a large-scale cross-trait gwas analysis in European ancestry populations.

BACKGROUND: Obesity and autoimmune disorders represent a significant comorbidity burden, yet their shared genetic architecture is not fully understood. Elucidating the pleiotropic genetic basis underlying both conditions is crucial for unraveling the mechanisms driving their co-occurrence and advancing therapeutic strategies. METHODS: We conducted a large-scale cross-trait analysis integrating genome-wide association study (GWAS) summary data for obesity and 17 autoimmune diseases. Genetic correlations were assessed using LD score regression and high-definition likelihood. Cross-trait pleiotropic analysis was performed using Stratified Pleiotropic Locus Mapping (PLACO) to identify shared loci, followed by Bayesian colocalization to confirm shared causal variants. Gene-level and tissue-specific heritability analyses were conducted, and drug targets were prioritized via summary-based Mendelian randomization (SMR). Finally, immune co-localization and bidirectional Mendelian randomization were employed to elucidate immunological mechanisms and causal relationships. RESULTS: Our analysis identified eight autoimmune diseases with significant genetic correlations to obesity. We discovered 10,324 pleiotropic SNPs, which mapped to 52 independent risk loci, with nine loci confirmed as shared causal variants by colocalization. Gene-level analysis revealed 133 unique pleiotropic genes, including CLN3, SH2B1, and MMEL1, enriched in pathways of hematopoietic cell differentiation and immune homeostasis. Tissue-specific heritability was most prominent in the spleen, whole blood, and EBV-transformed lymphocytes. Immuno-co-localization implicated six IgD+ CD38- %B cell-related traits as key pathological conduits. Bidirectional Mendelian randomization established a causal role of obesity in hypothyroidism, psoriasis, and multiple sclerosis, while revealing an inverse causal association of type 1 diabetes with obesity risk. CONCLUSIONS: This study demonstrates a robust shared genetic foundation between obesity and multiple autoimmune diseases, pinpointing specific pleiotropic loci, genes, and immune cell subsets. Our findings provide a mechanistic framework for their comorbidity and highlight potential targets for therapeutic intervention.

Humans↗