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PubMed2026

Sex-specific biological aging clocks across organs and omics.

Sex differentially shapes aging, neurodevelopment and neurodegenerative diseases such as Alzheimer's disease (AD). However, most biological aging clocks (artificial intelligence-predicted age minus chronological age) were trained on sex-pooled samples and implicitly assume sex invariance.Here we developed 38 sex-specific biological aging clocks across 15 organ systems. We first demonstrate the importance of sex-stratified training for constructing sex-specific healthy normative references and then reveal marked divergence between female and male clocks. Key genetic parameters and Mendelian randomization results indicate that organ-specific aging liability and its relationships to cardiometabolic, endocrine and mental traits are configured differently in females and males. Proteomic analyses identify distinct, organ-resolved synaptic, immune, vascular and metabolic networks that differentially track female and male biological aging. In longitudinal survival analyses, sex-specific clocks predict whole-body systemic diseases and all-cause mortality in a sex-dependent and organ-dependent manner. Further analyses reveal sex-dependent associations between the brain aging clock and cognitive decline trajectory during a preclinical AD clinical trial. Sex-stratified clocks may offer distinct value by defining biological age against sex-appropriate normative references and revealing sex-dependent genetic, molecular and clinical signatures that pooled models may obscure. Meanwhile, sex-pooled and sex-interaction approaches remain valuable, as human aging and disease also share fundamental biological similarities between females and males. Together, these findings reveal sex-specific biological aging signatures in aging, AD and systemic health, highlighting the need for explicitly sex-stratified modeling approaches.

Journal Article↗

PubMed2026

Plasma proteomics and incident coronary heart disease.

BACKGROUND: Systematic profiling of plasma proteins in population studies offers a complementary approach to discovery of novel risk factors and may provide new insights into the causes of coronary heart disease. METHODS: To explore relationships between the circulating proteome and coronary heart disease (CHD), we evaluated associations of 4780 plasma proteins with incident CHD in the Cardiovascular Health Study (CHS, N=2856, 575 CHD events) and replicated significant associations in the Atherosclerosis Risk in Communities Study (ARIC, N = 10456; 1375 events). RESULTS: We find that 11 proteins significantly associate with incident CHD after adjusting for risk factors; and eight significantly replicated in ARIC. Several proteins correlate with carotid intimal medial thickness and CHD associations are attenuated in participants without subclinical atherosclerosis. Macrophage metalloelastase (MMP12) is the strongest observed association (Hazard Ratio, 1.31; 95% Confidence Interval, 1.19-1.44). Mendelian randomization (MR) identifies a causal relationship between higher MMP12 and lower CHD (Odds Ratio, OR 0.94) and ischemic stroke (OR 0.90) risk, while reverse MR found that genetic propensity to CHD increased MMP12. Taken together, multivariable MR confirms a direct protective effect of higher plasma MMP12 on CHD risk and a genetic effect of atherosclerosis and CHD on elevating MMP12. CONCLUSIONS: Proteomic analyses reveal associations with incident CHD and genomic evidence suggests that therapeutic MMP12 inhibition may confer adverse cardiovascular effects.

Journal Article↗

PubMed2002

Spatial autocorrelation and linkage of Mendelian RAPD markers in a population of Picea abies Karst.

The spatial clustering of single- and di-locus genotypes in a natural, continuous population of Norway spruce was investigated using 69 Mendelian Random Amplified Polymorphic DNA (RAPD) markers that covered about 15 of the species genome, and whose linkage relationships were known. Spatial autocorrelation techniques and randomization tests, applied to both single- and di-locus genotypes, revealed a weak, though significant, spatial structure at the scale 0-200 m (5 of single-locus and 7 of di-locus genotypes). To assess the relative importance of isolation by distance and linkage between markers on their spatial genetic structuring, we grouped joins between sampled trees into equivalence categories expected to show similar, specific patterns of spatial distribution under isolation by distance. Results from both single- and di-locus analyses were consistent with the existence of patches of like homozygotes (about 8 and 11 of loci at the single- and di-locus level, respectively) surrounded by a mix of like heterozygotes. Similar structuring has been predicted by simulation models under isolation by distance and selective neutrality. Overall, linkage between markers accounted for an increase of spatial clumping of di-locus genotypes involving tightly linked loci with recombination fractions up to 0.1, a consequence of limited, stochastic spread of single-locus genotypes in space. Our results support the hypothesis that isolation by distance and linkage have a small, though significant, effect even within continuous forest tree populations. In general, the spatial distribution of multilocus genotypes within populations should be interpreted with caution when linkage relationships among the markers used are unknown.

DNA↗

PubMed2007

Use of single-nucleotide polymorphisms in the search for genetic modifiers of the uremic phenotype.

As the modern nephrology community continues to be burdened with growing numbers of patients with end-stage renal disease (ESRD) and exceptionally high mortality rates, it is obvious that progress in the development of preventive and therapeutic strategies has not been sufficient. This urges nephrologists to focus on the underlying mechanisms for ESRD morbidity and mortality, and in particular on cardiovascular disease (CVD), which is the major contributor to premature death in this patient group. The high prevalence of inflammation, vascular ossification, and oxidative stress in ESRD predisposes these patients to CVD. Because genetic risk factors may modulate the pathophysiologic response, genotype-phenotype association studies may provide ways of predicting individual disease progression and may shed some light on key regulatory pathways. Indeed, recent genetic association studies show that polymorphisms in candidate genes related to inflammatory signaling, vascular ossification, and oxidative stress response influence the uremic phenotype. DNA polymorphisms may also be used as nonconfounded tools in observational studies conducted to test causality, as stated by the mendelian randomization approach. To date, the collection of genetic data is no longer a limitation because genetic information is easily accessible in public databases and high-throughput genotyping technologies are available. Advanced bioinformatic tools are now warranted to facilitate the integration of accumulating genetic information with clinical and biochemical end points and, finally, to implement genotype-phenotype data in the care of patients with renal failure to better identify patients at high risk and to design novel personalized therapeutic and preventive strategies.

Calcinosis↗

PubMed2026

Stage-specific ROMO1 in rheumatoid arthritis: predictive immune insights into the MIF pathway and HLA-DR/IL2RA axis via integrated GWAS, transcriptomic, single-cell, and spatial profiling.

Emerging evidence links reactive oxygen species modulator 1 (ROMO1), a key mitochondrial ROS regulator, to rheumatoid arthritis (RA) pathogenesis. However, its exact mechanism remains elusive given the conflicting evidence about its specific function. We used a four-level integrative framework combining multi-omics data and literature‑supported mechanistic inference. At the genetic level, Mendelian randomization (MR) was performed to explore potential causal relationships between ROMO1, IL2RA, HLA-DR, MIF, and RA risk, followed by differential expression analysis and machine learning-based feature selection to identify key mROS genes. The temporal expression dynamics of ROMO1 were assessed in RA progression. At the cellular and tissue levels, we integrated single-cell RNA sequencing and spatial transcriptomics to map cell-type-specific expression and synovial localization of ROMO1-related immune cells and pathways. Finally, our multi-omics findings were contextualized with literature-supported mechanistic inference. (1) MR results were consistent with a potential protective effect of ROMO1 on RA (OR = 0.52) and its potential regulation of risk factors IL2RA (OR = 0.46) and HLA-DR (OR = 0.40). Conversely, IL2RA (OR = 1.42), HLA-DR (OR = 1.88), and MIF (OR = 1.17) were positively associated with RA risk. Additionally, ROMO1 was identified as a top candidate diagnostic predictor with stage-specific dynamics: downregulated in the early but upregulated in the late/remission stages. (2) Single-cell RNA sequencing showed ROMO1's cell-specific expression in CD14+ HLA-DR+ CD74+ monocytes and CD4+ IL2RA+ T cells. Cell communication analysis further suggested that these cells may participate in MIF pathway regulation. Spatial transcriptomics subsequently identified that ROMO1-related cells localized to synovial pathological regions, with MIF pathway changes correlated with RA progression. (3) Finally, literature-supported mechanistic inference suggests that ROMO1 may modulate mROS levels to promote anti-inflammatory M2 macrophage polarization, which could theoretically contribute to reduced systemic inflammation and the alleviation of multi-organ decline in RA. This integrated multi-omics investigation, supported by literature-based mechanistic inference, suggests ROMO1 as a stage-dependent biomarker candidate and potential immune regulator in RA.

Humans↗

PubMed2026

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metabolism axis in this comorbidity remains unclear. We explored its underlying mechanisms and evaluated the therapeutic potential of gentiopicroside. METHODS: Integrated multi-omics analyses combining transcriptomics, single-cell RNA sequencing, Mendelian randomization, machine learning, molecular docking, and in vitro functional assays were performed to identify shared molecular pathways and therapeutic targets across PCOS, hypertension, NAFLD, and T2DM. RESULTS: SLC11A2 was consistently dysregulated in PCOS transcriptomic datasets, and associated with iron metabolism, inflammatory response and oxidative stress pathways. Genetic analyses validated RAS-related regulation in hypertension susceptibility and revealed shared genetic architecture between PCOS and cardiometabolic traits. Network and single-cell analyses characterized SLC11A2-associated molecular patterns in disease-relevant cell types; machine learning identified disease-classifying molecular signatures. Gentiopicroside alleviated inflammatory and oxidative stress phenotypes, including reduced IL-6 expression and reactive oxygen species accumulation. CONCLUSION: This study defines an RAS-SLC11A2 molecular framework linking iron metabolism dysregulation to PCOS-related cardiometabolic risk, elucidating the mechanisms connecting ovarian dysfunction, inflammation, oxidative stress and hypertension, and supports gentiopicroside as a promising therapeutic candidate.

Humans↗

PubMed2006

"Anti-inflammatory" drugs and their effects on type 2 diabetes.

There is a growing body of evidence for the role of inflammation in type 2 diabetes. In addition to the evidence presented elsewhere, evidence is emerging that many drugs that have apparent "anti-inflammatory" properties may reduce the incidence and/or delay the onset of type 2 diabetes. Statins have been found to lower inflammatory markers, and a post hoc analysis of the West of Scotland Coronary Prevention Study (WOSCOPS) suggested that pravastatin may reduce the risk of developing diabetes, although the Lipid Lowering Arm of the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT) found no statistically significant effect of atorvastatin on risk of developing diabetes. Fibrates have been found to lower some markers of inflammation, and a prospective trial found that bezafibrate reduces risk of developing diabetes. Angiotensin converting enzyme (ACE) inhibitors and angiotensin receptor blockers appear to reduce some markers of inflammation, and a meta-analysis concluded that ACE inhibitors and angiotensin receptor blockers reduce risk of developing type 2 diabetes. Metformin is known to reduce the risk of developing diabetes, and more recent evidence suggests it also lowers C-reactive protein, in part because of its modest weight-reducing effect. Thiazolidinediones reduce risk of developing diabetes, and consistently lower inflammatory markers independent of adiposity effects. High-dose aspirin inhibits cyclooxygenase and IkappaB kinase-beta and reduces fasting plasma glucose concentration, although there has not, as yet, been a large-scale trial to examine the effect of aspirin on the risk of developing diabetes. We conclude that although many drugs with potential anti-inflammatory properties reduce the risk of developing diabetes, it is difficult to prove that such anti-inflammatory properties contribute to their diabetes prevention since nearly all drugs have other, often more pronounced, actions. Studies with more specific inhibitors of inflammatory pathways (e.g., interleukin- 6 blockers) and mendelian randomization (genetic studies) will help determine whether targeting the inflammation axis is a fertile mechanism to treat or prevent type 2 diabetes.

Angiotensin-Converting Enzyme Inhibitors↗

PubMed2026

Integrated multi-omics strategies for identifying novel therapies in psoriasis.

MOTIVATION: Psoriasis is a chronic, immune-mediated disorder with an unmet need for effective treatments. To systematically prioritize therapeutic targets, we integrated proteome-wide Mendelian randomization (MR) with expression validation in blood/skin, genetic susceptibility analysis, differential gene expression (DGE) from bulk and single-cell RNA sequencing (scRNA-seq), colocalization, pathway enrichment, and protein-protein interaction analyses. RESULTS: Proteome-wide MR identified 29 candidate protein targets (Bonferroni-corrected), all replicated in independent datasets. Fifteen targets showed significant expression associations in blood or skin. Eleven proteins-UBLCP1, IL23A, ASF1A, RARRES2, ICAM1, PRSS53, ICAM5, GCA, IL2RA, DBI, and NFKB1-exhibited consistent directional effects with their genes. Genetic susceptibility analysis confirmed 20 target-specific polygenic scores for psoriasis and five for psoriatic arthritis. DGE analysis identified 13 targets in bulk and 13 in scRNA-seq-primarily in keratinocytes and immune cells-with IL2RA, COMP, and A2ML1 dysregulated across both. Colocalization analysis implicated shared causal variants for psoriasis in ASF1A, CD8A, CTF1, IL7R, MMP12, RARRES2, XCL2, DBI, IL23A, IL2RA, SGSH, and TIMD4. Enrichment analyses highlighted involvement in cytotoxicity, immune regulation, and JAK-STAT signaling. Eighteen targets interacted with approved anti-psoriasis drugs. Notably, drugs targeting IL2RA, IL7R, CTF1, ICAM1, MMP12, NFKB1, CD8A, DDX58, IL12A, SGSH, and FAP are approved or in trials for other diseases, suggesting repurposing potential. Our integrative multi-omics approach prioritized 29 high-confidence targets, including 13 novel candidates (RARRES2, ASF1A, CTF1, DBI, B3GNT2, CD8A, TIMD4, CRTAM, SGSH, XCL2, DAPK2, A2ML1, and FAP). Several high-priority targets-such as IL2RA, IL23, MMP12, RARRES2, IL7R, and ICAM1-were supported across analytical layers. These findings provide a robust foundation for psoriasis drug development. AVAILABILITY AND IMPLEMENTATION: The code used for the analyses in this manuscript has been archived in Zenodo at [DOI: 10.5281/zenodo.19692128].

Psoriasis↗

PubMed2026

Mapping the causal chain from genetic risk variants to lipid dysmetabolism in Parkinson's disease.

The molecular pathways linking genetic variants to Parkinson's disease (PD) onset and progression remain incompletely defined; however, risk alleles in multiple genes, including GBA1, strongly implicate lipid metabolism. To systematically identify causal biomarker signatures, we analysed comprehensive metabolome profiles from blood plasma in 149 PD patients and 150 controls, along with complementary genetic, RNA-sequencing and metabolic data from other available clinical and pathologic cohorts. Using colocalization and summary-data-based Mendelian randomization, we tested whether expression and metabolic quantitative trait loci mediate the association between implicated genetic variants and PD risk. We further integrated differential metabolomics and proteomics from blood and brain to reveal pertinent mechanisms. We show that common PD risk variants at the serine palmitoyltransferase small subunit B (SPTSSB) locus, a key regulator of de novo sphingolipid biosynthesis, are associated with increased SPTSSB brain expression and elevated plasma ceramides. Additional analyses strongly support our hypothesis that a common SPTSSB causal variant is responsible for PD risk as well as the expression and metabolic quantitative trait loci. Multiple sphingolipids and fatty acid derivatives were perturbed in PD, and we identified both unique and shared features with the Alzheimer's disease metabolome. A PD acylcarnitine signature was further replicated in human post-mortem brain tissue, when comparing those with or without preclinical Lewy body pathology. Integrated analysis of complementary brain proteomic profiles revealed dysregulation of mitochondrial processes dependent on acylcarnitines, including fatty acid beta-oxidation, the tricarboxylic acid cycle and oxidative phosphorylation. Our results identify promising biomarkers and reveal a causal chain linking genetic variation to altered gene/protein expression, lipid dysmetabolism, and the manifestation of PD.

Humans↗

PubMed2026

Sex-specific associations of the plasma-proteome with incident coronary artery disease.

AIMS: The etiology of coronary artery Disease (CAD) appears different for men and women, yet insights into underlying sex-specific biological mechanisms are limited. We integrated genomic and proteomic analyses to investigate sex-specific associations of the plasma-proteome with CAD. METHODS AND RESULTS: In 40,829 UK Biobank participants (free-of-CAD, baseline-365 days thereafter; 55% women; mean age 56.9 ± 8.1 years), we examined associations between 2,922 plasma proteins and incident CAD over a median follow-up of 13.7 years (IQR 13.1-14.4) using multivariable-adjusted Cox proportional hazards models. Sex-specific analyses identified 440 female exclusive and 32 male exclusive proteins associated with incident CAD (FDR-corrected p < 0.05), revealing distinct pathway enrichments, including innate immune response in women and angiogenesis in men. Causality was assessed through combined and sex-stratified two-sample Mendelian randomization (MR) using inverse-variance-weighted analyses with genome wide association summary statistics from 422,108 men (61,969 cases) and 521,695 women (27,128 cases) (UK Biobank, FinnGen freeze 9). Integration of direct sex-protein interaction analyses with sex-combined MR identified 59 proteins with evidence for sex-specific causal effects. Four proteins demonstrated concordant directionality in sex-stratified MR analyses (n = 943,803) and multivariable regression models, namely CDKN2D, MYH9, and SKAP2 (women), and CTSH (men). To assess translational relevance, prioritized targets were further evaluated in secondary major adverse cardiovascular events among carotid endarterectomy patients (MACE; Athero-Express) and acute myocardial infarction (AMI; MISSION!) using plasma proteomics and ELISA. After further top-target identification in the context of MACE and AMI, clinical drug candidates were identified through a machine learning framework, including CTSH (men), and TNFRSF4 (both sexes). CONCLUSIONS: We identified sex-specific associations of proteins and biological pathways with incident CAD. Whereas the majority of proteins had consistent associations in both men and women, our findings suggest a degree of sex-specific pathogenesis with evidence for potential causality, opening new alleys for tailored prevention strategies and clinical cardiovascular risk management.

Journal Article↗

PubMed2025

Whole-genome Sequence Analysis Revealed Novel Subjective Cognitive Decline-associated Genes in 10,763 Chinese.

Subjective cognitive decline (SCD) is widely regarded as a potential preclinical stage of Alzheimer's disease (AD), yet its genetic basis remains poorly understood. To address this gap, we investigated genetic biomarkers associated with SCD using whole-genome sequencing (WGS) in 10,763 Chinese participants from the Healthy Zhejiang One Million People Cohort (HOPE Cohort). The discovery stage included 9284 samples, with 1479 samples used for validation. Using a two-stage design, we systematically investigated both common and rare variants associated with SCD. In rare variant analyses, we identified and replicated an association between the upstream region of SEPHS2 and SCD. SEPHS2 is involved in selenophosphate synthesis, and a Mendelian randomization analysis reveals that its expression levels in both blood and brain cerebellum are associated with AD. Additionally, we identified CLVS2, which encodes a protein primarily expressed in neuronal cells, as a potential regulator for SCD based on missense rare variants. Multi-omics evidence suggests that both SEPHS2 and CLVS2 may play roles in neurodegenerative diseases. For common variants, we validated 8 known loci related to cognitive decline, 3 of which originated from the only existing SCD genetic study conducted under a migraine background. Overall, our WGS-based study fills the gap in SCD research by providing vital genetic evidence from an East Asian population and offers insights into the pathogenic mechanisms of SCD.

Aged↗

PubMed2026

Genetic architecture of endometriosis: risk factors, comorbidities and clinical implications.

BACKGROUND: In 1999, Dr Susan Treloar and colleagues conducted a landmark twin study in Australia and reported their estimate of 51% for the heritability of endometriosis. This important result led several groups to begin mapping genetic factors contributing to increased endometriosis risk. Despite early challenges, advances in genome-wide association studies (GWAS) have identified multiple genetic risk factors and some target genes implicated in follow-up studies on genetic regulation of transcription. Access to large publicly available genetic datasets and analysis with endometriosis GWAS results is also providing new opportunities to answer important questions about comorbid conditions associated with endometriosis and their implications for clinical practice. OBJECTIVE AND RATIONALE: The objective of the review is to summarize the last 25 years of genetic studies in endometriosis, outline contributions to our understanding of the disease, and suggest future directions to accelerate biological insights from genetic studies to improve clinical outcomes. SEARCH METHODS: A comprehensive review of scientific literature on the genetics of endometriosis was conducted through searches in PubMed and Google Scholar up to June 2026. Search terms included "endometriosis AND (genetics OR GWAS OR genetic risk factors)", For studies addressing the functional characterization of genetic risk loci, additional searches employed the terms "endometriosis AND (genotype-phenotype associations OR colocalization OR eQTL OR mQTL OR multi omics methods)". To identify studies examining shared genetic risk between endometriosis and comorbid conditions, the search strategy included "endometriosis AND (genetic correlation OR colocalization OR Mendelian randomisation)". Publications reporting discoveries related to genetic risk factors for endometriosis and studies interpreting their biological and clinical significance were critically evaluated, and 144 publications were discussed in the review. OUTCOMES: Discovery of genetic risk factors started slowly and has accelerated in recent years with developments in technology and international collaborations to combine data and increase statistical power. GWAS have mapped 80 genetic risk factors that implicate gene regulation of hormonal targets, development of the reproductive tract, regulation of cell proliferation, and regulation of epithelial cell differentiation. In common with most other complex diseases, effects of individual common genetic risk factors are small. However, several examples demonstrate that small effect sizes are not a good predictor for the impact of drugs developed against genetically validated targets. Genetic risk factors implicate five genes regulating gonadotrophin release and oestrogen action, the major target pathway of current drugs for treatment of endometriosis demonstrating proof-of-principal for biologically meaningful results. Genetic correlation and Mendelian Randomization studies highlight important causal relationships between endometriosis and comorbid conditions including a possible role for testosterone during development and shared genetic risk factors for gynaecological, gastrointestinal, pain, psychiatric, and inflammatory conditions. Understanding causal relationships between endometriosis and related conditions will aid clinical management and more personalized treatments. WIDER IMPLICATIONS: Genetic studies provide novel insights into endometriosis pathogenesis and associations with related comorbid conditions. Genetic factors modifying gene regulation and disease risk likely act in specific cell types, and access to datasets from genetically informed cell-based models, single-cell and spatial omics data are needed to accelerate progress. Future studies should address critical questions of heterogeneity and disease subtypes, expand the search for genetic risk factors to non-European populations, evaluate the role of rare and structural variants, and better integrate data from functional, genomics, genetics, and clinical studies to reduce diagnostic delay, develop novel treatment strategies, and translate discoveries into personalized management strategies for affected individuals. REGISTRATION NUMBER: N/A.

comorbid conditions↗

PubMed2006

Stillbirth and slow metabolizers of caffeine: comparison by genotypes.

BACKGROUND: Cytochrome P4501A2 (CYP1A2) and N-acetyltransferase 2 (NAT2) are key enzymes in the metabolism of caffeine. The polymorphism of these genes facilitates the detection of fast and slow metabolizers, and if caffeine is causally related to stillbirth, we expect slow metabolizers to have a higher risk of stillbirth at any given intake of caffeine. Gluthatione S-transferase alpha1 (GSTA1) may also be active in the metabolism of caffeine as it conjugates glutathione to aromatic amines. Our study, therefore, included analyses of the association between GSTA1 and stillbirth. METHODS: A nested case non-case study among women who participated in the Danish National Birth Cohort: 142 cases of singleton stillbirths and 157 controls of singleton live births. RESULTS: Slow oxidizer status (CYP1A2), slow acetylator status (NAT2), and low activity of GSTA1 were not individually associated with the risk of stillbirth [odds ratio (OR) = 1.06, 95% confidence interval (95% CI) 0.67-1.67, OR = 0.95, 95% CI 0.60-1.51, and OR = 1.42, 95% CI 0.88-2.28, respectively]. We did, however, observe that subjects with a combination of slow CYP1A2, slow NAT2, and low GSTA1 genes had almost a 2-fold risk of stillbirth compared with subjects with other combinations of genotypes. CONCLUSIONS: We found no link between any single genotype and the risk of stillbirth. An association between a combination of genotypes and stillbirth was discovered. Caffeine may be causally related to stillbirth, but larger studies using Mendelian randomization are needed to verify this.

Acetyltransferases↗

PubMed2024

Whole -genome survival analysis of 144 286 people from the UK Biobank identifies novel loci associated with blood pressure.

This study utilized UK Biobank data from 144 286 participants and employed whole-genome sequencing (WGS) data and time-to-event data over a 12-year follow-up period to identify susceptibility in genetic variants associated with hypertension. Following genotype quality control, 6 319 822 single nucleotide polymorphisms underwent analysis, revealing 31 significant variant-level associations. Among these, 29 were novel - 15 in Fibrillin-2 ( FBN2 ) and 4 in Junctophilin-2 ( JPH2 ). Mendelian randomization utilizing two identified variants (rs17677724 and rs1014754) suggested that a genetically induced decrease in heart FBN2 expression and an increase in adrenal gland JPH2 expression were causally linked to hypertension. Phenome-wide association (PheWAS) analysis using the FinnGen dataset confirmed positive associations of rs17677724 and rs1014754 with hypertension, assessed across 2727 traits in 377 277 individuals. Lastly, rs1014754 positively associated with kallistatin, whereas rs17677724 negatively associated with renin in the Fenland study, suggesting a counterregulatory response to high blood pressure. This study, employing WGS data, identified novel genetic loci and potential therapeutic targets for hypertension.

Humans↗

PubMed1979

The question of adaptive sex ratio in outcrossed vertebrates.

Of various published theories of adaptive control of progeny sex ratio only two are plausible, a physiological theory by Trivers & Willard, and a demographic theory by Verner. The first applies to species in which sons and daughters impose different costs on parents, and in which only one or very few young are produced at once. They ought to show positive correlations in the sex of successive offspring and high sex-ratio variance among progenies. Verner's theory postulates a minimization of competition for mates in neighbourhoods subject to random fluctuation in sex ratio. Optimal progenies would exactly match the population's evolutionary equilibrium sex ratio. There would be little variance among progenies. Evidence from vertebrates is unfavourable to either theory and supports, instead, a non-adaptive model, the purely random (Mendelian) determination of sex. The apparent absence of parental control of progeny sex ratio is a serious theoretical difficulty.

Adaptation, Biological↗

PubMed2025

Automated Deep Learning-Based Detection of Early Atherosclerotic Plaques in Carotid Ultrasound Imaging.

BACKGROUND: Carotid plaque presence is associated with cardiovascular risk, even among asymptomatic individuals. While deep learning has shown promise for carotid plaque phenotyping in patients with advanced atherosclerosis, its application in population-based settings of asymptomatic individuals remains unexplored. METHODS: We developed a YOLOv8-based model for plaque detection using carotid ultrasound images from 19,499 participants of the population-based UK Biobank (UKB) and fine-tuned it for external validation in the BiDirect study (N = 2,105). Cox regression was used to estimate the impact of plaque presence and count on major cardiovascular events. To explore the genetic architecture of carotid atherosclerosis, we conducted a genome-wide association study (GWAS) meta-analysis of the UKB and CHARGE cohorts. Mendelian randomization (MR) assessed the effect of genetic predisposition to vascular risk factors on carotid atherosclerosis. RESULTS: Our model demonstrated high performance with accuracy, sensitivity, and specificity exceeding 85%, enabling identification of carotid plaques in 45% of the UKB population (aged 47-83 years). In the external BiDirect cohort, a fine-tuned model achieved 86% accuracy, 78% sensitivity, and 90% specificity. Plaque presence and count were associated with risk of major adverse cardiovascular events (MACE) over a follow-up of up to seven years, improving risk reclassification beyond the Pooled Cohort Equations. A GWAS meta-analysis of carotid plaques uncovered two novel genomic loci, with downstream analyses implicating targets of investigational drugs in advanced clinical development. Observational and MR analyses showed associations between smoking, LDL cholesterol, hypertension, and odds of carotid atherosclerosis. CONCLUSIONS: Our model offers a scalable solution for early carotid plaque detection, potentially enabling automated screening in asymptomatic individuals and improving plaque phenotyping in population-based cohorts. This approach could advance large-scale atherosclerosis research.

atherosclerosis↗

PubMed2025

Comorbidity alters the genetic relationship between anxiety disorders and major depression.

BACKGROUND: Comorbid anxiety disorders (ANX) and major depression (MD) have worse clinical outcomes than either disorder alone. Analysis of genomic data based on comorbidity status may reveal more precise biological pathways and causal relationships with potential clinical implications. We investigated the genetic relationship between ANX and MD with and without mutual comorbidity. METHODS: We leveraged data from UK Biobank to perform disorder-specific genome-wide association studies (GWAS) of ANX-only (n=189,422) and MD-only (n=194,339) and generate polygenic risk scores (PRS). The Norwegian Mother, Father, and Child Cohort (MoBa, n = 130,992) served to test the associations of PRS with diagnoses. MD and ANX GWAS, including comorbidities (MD-comorbid and ANX-comorbid), were used for comparison. Genetic correlations were compared by comorbidity status, and Mendelian randomization was employed to assess causal relationships. RESULTS: The MD-only PRS showed a stronger association with MD-only compared to ANX-only cases (Z=3.74; Padjusted=0.002); however, MD-comorbid PRS did not show a significant difference (Z=2.71; Padjusted=0.08). The genetic correlation between ANX-only and MD-only was 0.53, lower than between ANX-comorbid and MD-comorbid (0.90). ANX-only showed a causal relationship with MD-only (Padjusted=0.015), but not vice versa, and contrasted the bidirectional causal relationship (Padjusted=2.9e-12, and Padjusted=9.3e-06) when comorbidity was included. Gene sets of MD-comorbid, ANX-comorbid, and MD-only, but not of ANX-only, were enriched for immune regulation pathways such as interleukin production. CONCLUSIONS: ANX and MD show more distinct genetics when comorbid cases are excluded, and ANX may be causal for MD. Disorder-specific genetic studies help uncover more relevant biological mechanisms and guide tailored clinical interventions.

Journal Article↗

PubMed2026

Integrative Analysis Uncover the Effects and Multi-Omics Features of Thigh Muscle Fat Infiltration.

The health impacts and underlying biological pathways of thigh muscle fat infiltration (TMFI) remain incompletely understood. In this study, we analyzed TMFI measured by magnetic resonance imaging in 55,120 UK Biobank participants and found that higher TMFI was significantly associated with all-cause mortality as well as with all major system-specific diseases examined (p values ranged from 2.50 × 10-88 to 9.97 × 10-04). TMFI also mediated the effects of lifestyle factors on health-related outcomes, with mediation proportions ranging from 6.7% to 71.7%. A genome-wide association study (GWAS) identified 79 lead single nucleotide polymorphisms (SNPs) linked to TMFI, and the polygenic risk score for TMFI was significantly associated with mortality and all incident diseases across examined organ systems in an independent subset of UK Biobank participants of European ancestry who were not included in the TMFI GWAS (n = 362,286, all p < 0.05). Gene-drug interactions identified multiple drugs that could potentially modulate TMFI. Analysis of single-cell transcriptomic data indicated that myogenic cells were strongly linked to TMFI (p = 7.08 × 10-08). Summary-data-based Mendelian randomization and Transcriptome-Wide Association Study analyses revealed numerous genes whose expression in specific tissues was associated with TMFI. Proteomic and metabolomic profiling uncovered a broad array of circulating biomarkers associated with TMFI, many of which mediated the effects of modifiable factors and genetic risk on TMFI. Overall, our results highlight the biological relevance of TMFI to human health and provide insights into the multi-omics mechanisms underlying TMFI, identifying potential targets for interventions.

Humans↗