Human Genomics

Although the Y chromosome represents roughly 2% of the male genome, it is often ignored in genome-wide association studies (GWAS). Subsequently, the potential health impacts of Y-chromosomal genetic variation remain incompletely understood. To fill this gap, we performed a phenome-wide association study (PheWAS) in FinnGen across 1,426 binary and quantitative traits using Y-chromosomal variation (frequency [&ge;] 1%) in 104,334 genotyped men. As Y chromosome variation is prone to population stratification, we performed carefully adjusted association analyses and further examined these through kin-based validation in 19,275 female and 24,712 male 1st degree relatives. We found 121 suggestive (p < 5.6x10-3) phenotypic associations in the Y chromosome, yet none of these were strong enough to reach phenome-wide significance (p < 3.9x10-6). While only 38 associations were supported in the kin-based validation, intriguingly we found support for a previously suggested link between haplogroup I1 and coronary heart disease (CHD; OR=1.06, 95%CI=1.02-1.11, p=3.7x10-3; male validation OR=1.05; female validation OR=0.97). The I1-CHD association was detected across distinct geographical areas within Finland and was independent from Loss of Y (LOY) and the autosomal risk to CHD, proposing a link between germline Y-chromosomal variation and heart disease risk. Overall, this study presents a comprehensive phenome-wide analysis of Y-chromosomal associations, highlighting the potential relevance of Y-chromosomal variation beyond sex determination. Our findings further emphasize the need for improved capture of Y-chromosomal variants and further analyses in biobank-scale data to allow for deeper exploration of male-specific genetic architecture of complex diseases.

Background: Alpha-1 antitrypsin deficiency (AATD) caused by the PI*ZZ mutation (Glu342Lys) results in hepatic accumulation of misfolded AAT-Z protein and reduced circulating AAT levels, leading to progressive liver disease and emphysema. Gene correction therapy represents a potentially curative approach by directly correcting the underlying genetic defect. We report the first case of successful hepatic gene correction with early histological and functional assessment. Methods/Case presentation: We report the case of a 66-year-old male patient with PI*ZZ AATD who underwent gene correction therapy within the YOLT-202 phase I/Ia clinical trial (clinical trial.gov ID NCT07193615). Ten weeks post treatment a liver biopsy was performed to re-evaluate pre-existing F2 liver fibrosis as measured by elastography before entering the study. Serum samples allowed functional assessment of the AAT-mediated elastase inhibition. Results: Liver biopsy did not show signs of hepatic inflammation and demonstrated 54% (Sanger) and 57% (Illumina) gene correction rate of the PI*ZZ variant on the DNA level with no bystander edits or off-target effects. Following a transient elevation of transaminases during the early post-treatment period, liver enzymes normalized. Monthly serum AAT measurements demonstrated biologically active and stable therapeutic levels throughout follow-up. Conclusions: This case demonstrates efficient and precise hepatic gene correction without concerning histological alterations and with substantial improvement of functional parameters, supporting the feasibility and safety of gene editing approaches for AATD.

Background: Aortic stenosis (AS) is a progressive valvular disease associated with poor prognosis once symptoms develop, yet routine echocardiographic screening is impractical. While artificial intelligence (AI)-based electrocardiogram (ECG) models have shown promise for AS detection, it remains unclear whether they primarily reflect conventional left ventricular hypertrophy (LVH) voltage criteria or capture additional ECG features. Methods and Results: We developed a deep learning model using 244,816 ECGs from 51,713 patients across six academic institutions in Japan (CLIDAS database). AS labels were derived from inpatient Diagnosis Procedure Combination (DPC) codes. The model achieved an area under the receiver operating characteristic curve (AUC) of 0.849 (95% confidence interval 0.832-0.865) in the independent test cohort, with consistent performance across institutions, sex, and age. At a threshold of 0.1, sensitivity was 79.1%, specificity was 73.9%, and negative predictive value (NPV) was 98.0%. Conventional LVH voltage criteria (Sokolow-Lyon AUC 0.706; Cornell AUC 0.692) showed lower performance, and adding them to the AI model conferred no incremental benefit (AUC 0.849 vs. 0.847). Gradient-weighted class activation mapping (Grad-CAM) revealed predominant attention around QRS complexes in limb leads, beyond regions typically assessed in LVH evaluation. Conclusions: This multicenter AI-ECG model demonstrated strong discrimination for AS and captured ECG features beyond conventional LVH voltage criteria. The high NPV supports its use as a rule-out pre-screening tool.

Background: A growing burden of cardiovascular risk factors has raised cardiovascular disease-related mortality in Sub-Saharan Africa (SSA), driving higher prevalence of heart failure with reduced ejection fraction (HFrEF) and its complication with atrial fibrillation (AF). No prospective study has examined AF's clinical impact on HFrEF in SSA. Aim: To determine AF prevalence in HFrEF, describe HFrEF-AF clinical characteristics, and determine AF's impact on mortality. Methods: In this prospective observational study at a tertiary hospital in Johannesburg, 136 HFrEF patients were enrolled and categorised as HFrEF- SR (sinus rhythm) or HFrEF-AF. Baseline clinical characteristics and biochemistry were recorded. Comprehensive echocardiography including left atrial strain by 2D speckle-tracking was performed. Median follow-up was 30.6 months. Results: AF was present in 28 patients (21%). The mean age was 58.7 {+/-} 14.9 years (52.9% male) and differed between groups (p < 0.001). Hypertensive heart disease was the leading cause of HFrEF (36%). Compared with SR, HFrEF-AF patients had poorer health status (KCCQ 27 [16-43] vs 45 [32-60], p < 0.001) and lower left atrial strain (26.2 {+/-} 11.3%, p < 0.001). Guideline-directed medical therapy was suboptimal in the AF group: anticoagulation use was higher than SR (60% vs 9.5%, p < 0.001) but overall inadequate; HFrEF-AF patients received lower median doses of carvedilol (15.6 mg vs 25 mg, p = 0.002) and enalapril (10 mg vs 20 mg, p = 0.004), and fewer received spironolactone (50% vs 75.3%, p = 0.013). Survival was significantly lower in HFrEF-AF (0.41 [0.22-0.61]) versus SR (0.73 [0.61-0.82], p < 0.001). Independent predictors of mortality included prior stroke, lower TAPSE and KCCQ, and higher E/e' and heart rate. Conclusion: AF is common among HFrEF patients in this SSA cohort (though lower than in high-income countries) and associates with worse clinical status, suboptimal therapy, and higher mortality.

NAT2 is an important pharmacogene which encodes the N-acetyltransferase 2 enzyme that is involved in the metabolism of multiple medications, and variants in this gene can affect patient response to these medications. CPIC has published a clinical guideline for prescribing hydralazine using NAT2 genotypes. Just prior to the guideline, updated NAT2 star allele numbering and definitions were released, differing somewhat from the historical nomenclature. Clinical pharmacogenomic testing panels often test for the most common star alleles, so knowledge of the most common updated NAT2 star alleles is critical for the implementation of the CPIC NAT2/hydralazine guideline. We first determine NAT2 diplotype frequencies from UK Biobank (UKBB) 200k phased genomes, then analyzed allele, diplotype, and phenotype population frequencies from the All of Us Research program, PennMedicine BioBank (PMBB) and UKBB 500k datasets. We found that analyzing NAT2 diplotypes from phased data provides critical information for algorithms designed to predict diplotypes from unphased data. We observed that NAT2*5, *6, and *4 were the most common star alleles in that order, and the top 11 most frequent NAT2 star alleles were the same across all biobanks. However, differences in star allele frequencies across biogeographical populations were observed. The largest difference led to a higher frequency of NAT2 poor metabolizer phenotypes as compared to rapid and intermediate metabolizer phenotypes in all global populations except in the EAS population, where NAT2 poor metabolizers were in the minority.

Diabetic peripheral neuropathy (DPN) is a common and disabling condition for which no disease-modifying therapies are available. Glycemic and metabolic drivers do not fully explain why only a subset of individuals with diabetes develop DPN, and genetic contributors remain poorly defined. We aimed to perform a multi-population genome-wide association study (GWAS) of DPN to highlight potential new etiological pathways and therapeutic targets. Methods We performed a multi-population GWAS of neuropathy in people with and without diabetes using the VA Million Veteran Program and UK Biobank, followed by replication in the All of Us Research Program (AoU), and gene-based and gene-set analyses to identify implicated pathways. Causal relationships between circulating serine levels and DPN were further tested using two sample Mendelian randomization. To further evaluate pathogenic potential, we analyzed rare, high impact variants in GWAS implicated genes among individuals with unresolved inherited neuropathies using the GENESIS platform. Findings Among individuals with type 2 diabetes, we identified seven genome wide significant loci (p<5x10-): PHGDH and PSPH (key serine synthesis genes), TEAD1, CYP4F11, LARGE1, FTO, and COBLL1. No loci were significant in individuals without diabetes or with type 1 diabetes. Four loci (PHGDH, TEAD1, FTO and CYP4F11) replicated in AoU (p <0.05). Mendelian randomization demonstrated that higher genetically predicted serine levels were associated with lower DPN risk, consistent with a causal role of serine metabolism in disease pathogenesis. Rare-variant burden analyses revealed associations of predicted deleterious variants with inherited neuropathy case status in PHGDH (odds ratio [OR] 12.7 [95% CI 7.9, 20.4]), PSPH (OR 8.5 [7.2, 10.2]), PHKG1 (OR 4.8 [3.7, 6.3]), and LARGE1 (OR 0.007 [0.0004, 0.1]). Interpretation Convergent genetic evidence across common and rare variation implicates serine synthesis as a key pathway in DPN. These findings link diabetic and inherited neuropathies through a shared metabolic mechanism, identifying serine metabolism as a potential therapeutic target.

Abstract Background: Heart Failure is a complex clinical syndrome of growing public health concern in sub-Saharan Africa, yet the data from Sierra Leone are absent. The aim of the study is to characterise the clinical profile, etiological and temporal trends of hospitalised HF patients at Choithrams Memorial Hospital (CMH), Freetown, Sierra Leone, to confirm specific management strategies. Methods: This single-center, retrospective observational cohort study analysed data on HF patients (>18years) admitted at the CMH between January 2021 to 31 December 2025. The clinical definition of HF was based on the Framingham criteria and the European Society of Cardiology (ESC) guidelines , including standard echocardiographic parameters. All variables, including patients demographics, HF. phenotype, aetiology, medical history and hospital outcomes were extracted from the digital record. Non-parameteric tests, multivariable logistic regression to identify variables associated with etiology, Wilcoxon rank-sum test to compare groups and Kruskal-Wallis test to analyse trends over time were utilised. Result: A total of 765 patients were included in the study, with a median age of 53 years (IQR 42-61) and male predominance of 55.3%. Patients with recurrent HF (60.9%) were more common than those with de novo HF (39.1%), were older (54 years vs 53 years), had a higher comorbidity burden (34% vs 4%, p < 0.001), and presented with a cold-wet hemodynamic profile (18.4% vs 8.4%, p < 0.001). HFrEF (61.3%) was the most predominant phenotype, though HFpEF increased with age. Dilated Cardiomyopathy (37.0%), Hypertensive Heart Disease (31.2%) and Valvular Heart Failure (17.1%) were the leading etiologies, while ischemic heart disease (6.3%) was relatively uncommon. A majority of the patients were referred (77.9%), and 50.8% presented with NYHA IV. The strongest independent predictor for HF was hypertensive heart disease [AOR = 17.81; C.I 95%: (3.13-48.76), p <0.001]. An analysis of the trends in etiologies and demographics over the five-year period demonstrated no significant changes (all p-values > 0.05 for age, sex, aetiology, and most comorbidities). Conclusion: HF affects the younger adult population in Sierra Leone and is mainly caused by DCM and HHD. The late case presentations, the high prevalence of recurrent HF, and the associated high burden of comorbidities emphasize an urgent need to develop and implement improved strategies for the prevention, early detection, and long-term management of HF within Sierra Leone's healthcare system.

Cardiovascular diseases (CVDs) remain the primary global health burden, motivating the search for robust, non-invasive risk biomarkers. We harness a foundation model pretrained on over 10 million recordings, to evaluate ECG-derived age deviation as a cross-cohort biomarker of CVD burden. A predictive model, trained exclusively on healthy subjects, achieved accurate age prediction. Diseased subjects exhibited significant positive age acceleration across multiple categories, with structural and ischemic heart diseases showing the largest effects. External validation in a hospital-based cohort (n=160,493) confirmed that age acceleration independently predicts all-cause mortality, with the strongest prognostic value in patients under 65 years. Furthermore, we demonstrated that disease discrimination and mortality prediction are preserved across 6-lead and single-lead configurations, supporting potential deployment in wearable or mobile devices. Our analysis also revealed a striking morphological confound from the complete left bundle branch block, leading us to propose absolute age deviation as a more robust, universal risk marker. These findings establish ECG-derived biological age deviation as a highly generalizable and clinically actionable biomarker for assessing cardiovascular risk. We have also developed a web application at https://bioinformatics.mdc-berlin.de/ECGage that allows users to easily test our framework.

Rare diseases (RDs) remain a major diagnostic challenge. Genetic and phenotypic heterogeneity, incomplete knowledge of disease mechanisms, and limitations in variant clinical interpretation leave many patients without a molecular diagnosis. Meanwhile, the growing volume of genomic data generated in clinical practice offers an opportunity to develop data-driven methodologies for exploring disease mechanisms and improving the reanalysis of unsolved cases. We aggregated real-world genomic data from 11,084 unrelated patients with suspected RD. Patients were clinically classified into 122 diseases. We built a multi-disease genomic variant frequency database (FJD-DB), which enabled the development of variant and gene-disease association scores by means of case-control subcohort comparisons across 32 disease groups. Functional enrichment analyses were then used to highlight disease-associated protein domains, pathways, biological processes, and phenotypes. Finally, the resulting knowledge was integrated into a data-driven framework for the guided reanalysis of unsolved RD patients applied to Inherited Retinal Dystrophies (IRD) patients as first use case. FJD-DB contained more than 45 million unique variants, including ~185,000 potentially pathogenic variants. Disease-specific analyses identified disease-associated pathogenic variants and highlighted both established and candidate disease genes. We detected 179 significantly enriched protein domains across 23 diseases, 124 Human Phenotype Ontology terms across 13 diseases, 79 Reactome pathways across 10 diseases, and 72 Gene Ontology biological processes across 8 diseases, revealing highly disease-specific functional signatures. Integration of disease-specific variant, gene, and functional association signals enabled the development of a data-driven framework for guided reanalysis of unsolved RD cases. Applied to more than 1,100 unsolved IRD cases, the framework generated clinically relevant findings in 26 patients, including four molecular diagnoses, seven candidate diagnoses, and 15 cases upgraded from non-informative findings to variants of uncertain significance. Aggregated real-world genomic data can be leveraged to identify disease-associated molecular signals generating novel biological hypotheses. A unified analytical framework provides a scalable strategy for knowledge discovery and guided reanalysis, facilitating the identification of overlooked and potentially novel genetic causes of RDs.

Objectives: Incisional hernia (IH) affects 13-30% of people after abdominal surgery, resulting in substantial morbidity and costs. While clinical risk factors have been studied extensively, genomic risk for IH is incompletely understood. We aimed to evaluate the impact of polygenic risk scores (PRS) on IH risk prediction. Methods] We created and evaluated three PRS for abdominal hernia, ventral hernia and latent hernia susceptibility for prediction of IH in an institutional biobank. The primary outcome was defined as the diagnosis or repair of an IH based on ICD-9/10-CM/PCS and CPT codes. Clinical covariates included age, sex, body mass index (BMI), smoking status, index procedure type, and perioperative surgical site infection. A phenome-wide association study (PheWAS) was performed to assess clinical associations with increased PRS. We then tested the ability of the PRS to improve prediction for IH by modeling clinical covariates with and without PRS in patients who underwent abdominal surgery. Model performance was assessed using 10 iterations of 5-fold cross-validation to estimate Brier scores and area under the receiver operating characteristic curve (AUROC), which were compared using cross-model Bayesian analysis of variance. Results: In 55,809 subjects, assessed PRS was significantly associated with incisional, umbilical, and ventral hernia on PheWAS, with 1.19 greater odds of developing IH per 1-SD increase in PRS (95% CI: 1.13-1.25, P \< 0.001). Of 9,909 subjects who underwent qualifying abdominal surgery, 706 developed IH. In this cohort, the latent hernia susceptibility PRS was associated with a 16% increased hazard of developing IH per 1-SD increase (HR 1.16; 95% CI: 1.07-1.26; P \< 0.001). Compared to a predictive model using clinical covariates (Brier score = 0.047, 95% CI: 0.046-0.048; AUROC = 0.660, 95% CI: 0.653-0.666), addition of the PRS showed similar Brier score and AUROC estimates (Brier score = 0.047, 95% CI: 0.046-0.048; AUROC: 0.667, 95% CI: 0.661-0.673) at five years. Cross-model Bayesian analysis demonstrated \>99% probability of practical equivalence when trying to detect a difference of [&ge;] 0.02. Conclusion: All three PRS for hernia were independently associated with IH, suggesting that genomic factors contribute significantly to IH development. However, none of the three PRS meaningfully improved clinical IH risk prediction in patients who underwent abdominal surgery. This suggests that clinical comorbidities and surgical techniques may be equally as important as genomic architecture.

Whole-exome and whole-genome sequencing technology has enabled the discovery of rare genetic variants associated with human health and diseases. However, existing statistical methods used for rare variant association testing are not well-suited for building genetic risk prediction models that jointly incorporate rare and common variants. We propose STELLAR, a flexible ensemble learning-based approach to compute rare variant polygenic risk scores (PRS) using association summary statistics to enhance conventional common variant PRS. Our method combines burden-based and penalty-based rare variant analysis and leverages functional annotation information to prioritize potentially causal variants within the prediction models. In simulation studies, PRS using STELLAR consistently showed the highest prediction accuracy compared to models using common variants alone or rare variant burdens. Applied to UK Biobank whole-exome sequencing data (n=310,831) across eight continuous and five binary traits, STELLAR significantly improved prediction accuracy, refined stratification of individuals at the highest genetic risk beyond common variants, and prioritized biologically relevant genes. STELLAR provides a scalable strategy to incorporate rare variants into PRS in addition to common variants, advancing precision risk prediction and enabling more comprehensive assessment of genetic contributions to complex diseases.

Background Thalassemia is one of the most common monogenic disorders worldwide, current screening strategies combining hematological testing with molecular assays still carry a risk of missed diagnoses and undesirable efficiency, particularly for complex structural variants and rare mutations. Methods In this prospective double-blind, multicenter cohort study of 3,842 participants (3,362 pregnant women and 480 male partners), we conducted a head-to-head comparison to systematically evaluate the incremental clinical value and detection performance of single-molecule nanopore sequencing in thalassemia (SMITH) against conventional hematological testing and next-generation sequencing (NGS). Findings The overall concordance rate between NGS and SMITH was 98.6% (3789/3842). The discrepant cases (n=53) were directly attributed to the superior detection capabilities of SMITH, which successfully identified complex structural rearrangements-including 45 -globin gene triplications and four HK alleles-that were missed by NGS. Furthermore, SMITH accurately detected four rare variants (c.134_135insT/, c.-22(C>T)/, {beta}N/{beta}c.316-290delinsAGGGCAATAATTT and {beta}3.5 kb deletion/{beta}N ) and resolved ten trans and three cis configurations within the globin gene allele. Clinically, these technical advantages translated to a 9.3% (5/54) increase in the detection rate of high-risk prenatal couples, effectively preventing one birth affected by moderate-to-severe thalassemia. Additionally, SMITH corrected a diagnostic discrepancy in one case (HK vs. -3.7), sparing the couple from an unnecessary invasive procedure. Interpretation Our findings demonstrate that SMITH provides a powerful platform for resolving globin gene rearrangements, detecting rare variants, and enabling direct haplotype phasing. By effectively eliminating diagnostic blind spots, SMITH is expected to become an optimal method for thalassemia prevention programs. Funding This study was supported by Chinese National Natural Science Foundation Projects 81760037 and 82271894.

Background: Aberrant DNA methylation can mediate the functional effects of rare genetic variation and contribute to imprinting disorders, repeat expansion diseases, and other pathogenic regulatory mechanisms. Long-read sequencing technologies now enable genome-wide detection of CpG methylation alongside genetic variation from a single assay. However, methods for systematic identification and interpretation of methylation outliers from long-read sequencing data remain limited. Methods: We developed METAFORA, a computational workflow for detecting methylation outlier regions from PacBio and Oxford Nanopore long-read sequencing data. METAFORA constructs population-level methylation references, segments the genome into correlated CpG blocks, infers technical and biological sources of variation through hidden factor estimation, models uncertainty due to variable depth sequencing, and computes covariate-adjusted methylation outlier scores for individual samples. We applied METAFORA across large long-read sequencing cohorts and integrated methylation outliers with multi-omic data. METAFORA is implemented as a snakemake workflow available at https://github.com/tjense25/METAFORA. Results: METAFORA identified methylation outlier regions associated with rare structural variants, tandem repeat expansions, and imprinting abnormalities. We found outlier regions were enriched for molecular outliers across transcriptomic and chromatin accessibility datasets, supporting their functional relevance in gene regulation. In a representative case, METAFORA identified an imprinting defect affecting the GNAS locus associated with an STX16 deletion. Conclusions: METAFORA enables scalable detection and interpretation of methylation outliers from long-read sequencing data and provides a framework for integrating epigenetic outliers with genomic and multi-omic analyses. These approaches may improve interpretation of rare regulatory variation and support discovery of clinically relevant epigenetic abnormalities in genomic medicine.

Background: Neurological, neuropsychiatric, and neurodevelopmental disorders cluster in ALS families, sharing a common genetic architecture with ALS. Pathogenic variants in genes associated with other neurological, neurodevelopmental, or neuropsychiatric disorders may also co-occur in ALS and modify phenotype. We have sought to determine the prevalence and clinical pattern of likely-pathogenic/pathogenic (LP/P) non-ALS neurological, neurodevelopmental, and neuropsychiatric variants, alone and in combination with ALS-gene variants, in two large ALS cohorts. Methods: Whole-genome sequencing (WGS) of 469 Irish and 774 Answer ALS people with ALS (pwALS) was analysed for ClinVar LP/P variants associated with other neurological (n = 15541), neurodevelopmental (n = 9761), and neuropsychiatric (n = 321) phenotypes. Inheritance patterns for associated genes (autosomal recessive/autosomal dominant) along with the associated phenotype were validated using OMIM. Standardised clinical data included family history, site and age of onset, El Escorial category, survival, motor decline, and cognitive and behavioural assessments. Known ALS-gene variants and C9orf72 repeat expansion status were included for each cohort. Results: Non-ALS neurological variants were identified in 47/469 (10.0%) Irish and 69/774 (8.9%) Answer ALS participants, most frequently in hereditary spastic paraplegia-associated genes (3.2% Irish; 2.8% Answer ALS). Irish neurological variant carriers showed higher frequency of respiratory onset (10.6% vs 1.2%, Fisher's exact p = 0.002, {Phi} = 0.20) and fewer premorbid behavioural symptoms (0.92 +/- 0.56 vs 3.08 +/- 0.97, Cohen's d = -0.40). Neurodevelopmental variants occurred in 12/469 (2.6%) Irish and 20/774 (2.6%) Answer ALS participants. In the Irish cohort, neurodevelopmental variant carriers had significantly shorter survival in Cox proportional hazards model (log-rank p = 0.005), corresponding to a more than two-fold increased hazard of death (HR = 2.25, 95% CI 1.26-4.00), and had significantly increased familial burden of neuropsychiatric disorders among first- and second-degree relatives (negative binomial IRR for carriers = 2.41, 95% CI: 1.12-5.18, p = 0.025). Across combined cohorts, 18 individuals (Irish n = 8; Answer ALS n = 10) carried [&ge;]2 LP/P variants spanning ALS and non-ALS genes. Conclusion: Rare LP/P variants in genes associated with other neurological and neurodevelopmental disorders occur in up to 12% of pwALS across two independent cohorts. Carriers show distinct phenotypes, shorter survival, and characteristic family history patterns. These findings suggest that extended pleiotropic and oligogenic architectures may contribute to ALS heterogeneity.

Background: Artemisinin-based combination therapies remain the mainstay of malaria control strategies; nevertheless, the advent of genetic markers linked to partial artemisinin resistance in Plasmodium falciparum has elicited substantial concern across African settings. To assess the prevalence, geographic distribution, and clinical associations of these molecular markers, we undertook a systematic review and meta-analysis of observational cohort studies.Methods: We conducted a search of cohort studies published between January 2015 and June 2025, following PRISMA 2020 guidelines. We queried databases including PubMed/MEDLINE, Scopus, Web of Science, and CINAHL. Eligibility required prospective enrollment of patients, longitudinal monitoring (therapeutic efficacy studies), and pfkelch13 propeller domain genotyping.Results: A meta-analytical synthesis of 888 isolates from six core prospective cohorts revealed a pooled prevalence of 6% (95% CI: 2.1%-11.8%) for validated pfkelch13 mutations. A profound geographic dichotomy was identified: while West and Central African cohorts maintained a 0% prevalence, East African hotspots showed significant expansion, with prevalence reaching 12.8% in Rwanda and up to 25.5% in Northern Uganda; high statistical heterogeneity (, ) reflects this biological divergence. Conclusions: These findings highlight the established and expanding presence of artemisinin partial resistance in East Africa. Standardized surveillance is essential to adapt malaria control policies across the continent. Keywords: Africa; artemisinin resistance; clinical indicators; pfkelch13 gene; molecular markers; partial resistance; Plasmodium falciparum.

Cardiovascular diseases (CVDs) are highly heritable, but pathogenesis at the organ and physiological level is still poorly defined. Polygenic risk scores (PRSs), which estimate individual genetic susceptibility to a disease, may allow for the identification of associated abnormal organ structures. Ultimately, identifying where cardiovascular polygenic risk manifests can guide early interventions, shape mechanistic hypotheses, and motivate prevention trials for cardiac remodelling. This study investigated the association between PRSs for five common CVDs [heart failure (HF), coronary artery disease (CAD), atrial fibrillation (AF), abdominal aortic aneurysm (AAA) and ischaemic stroke (IS)] and 28 imaging-derived phenotypes (IDPs) from cardiac magnetic resonance imaging of ~62,000 participants in UK Biobank. To investigate the cardiac features associated with elevated polygenic risk of CVDs, we tested CVD PRSs against cardiac IDPs and identified 97 significant associations (FDR [&le;] 0.05). We further identified 32 significant putative mediators between CVD PRSs and incident disease events, revealing that across CVDs, polygenic risk manifested as distinct patterns in cardiac structures. HF implicated all cardiac chambers, including left ventricular and left atrial dysfunction alongside enlarged aorta. AF was characterised by biatrial enlargement and reduced ejection fractions, most prominently in the left atrium but also involving left ventricular wall thickness. IS exhibited left ventricular hypertrophy and left atrial dysfunction, while CAD predominantly involved left ventricular hypertrophy. AAA was primarily characterised by enlarged descending aorta. Overall, cardiac IDPs mediated a substantial proportion of polygenic risk for CVDs, in particular for HF. Taken together, our results show that cardiac structure and function lie on the pathway between polygenic risk and cardiovascular events.

**Abstract** **Background:** Transcatheter edge-to-edge repair (TEER) is an established treatment for mitral regurgitation but remains highly dependent on operator experience and complex transesophageal echocardiography (TEE)-guided intraprocedural imaging. Artificial intelligence (AI)-based semantic segmentation may improve procedural reproducibility and intraprocedural guidance; however, no TEER-specific segmentation framework has been reported. **Objectives:** To develop and evaluate AutoClip, a clinician-driven AI-guided TEE semantic segmentation model designed for simultaneous delineation of mitral valve anatomy and in-vivo TEER device components. **Methods:** A retrospective proof-of-concept study was conducted using 987 intraprocedural TEE frames derived from 10 video clips in 3 patients undergoing MitraClip G4 implantation. Seven semantic labels, including mitral leaflets and device components, were manually annotated using ITK-SNAP. Following standardized preprocessing and region-of-interest extraction, an Attention U-Net architecture was trained frame-wise on bicommissural and corresponding X-plane TEE views. Model performance was assessed using mean intersection-over-union (IoU) and Dice coefficient on an independent test set. **Results:** The Attention U-Net demonstrated improved sensitivity to small device structures compared with conventional U-Net architectures. Preliminary training performance achieved a mean IoU of approximately 0.93, while independent test performance reached a mean IoU of 0.46 across foreground classes. Qualitative assessment demonstrated feasible simultaneous segmentation of mitral leaflets, clip arms, grippers, and delivery shaft during TEER procedures. **Conclusions:** AutoClip represents a proof-of-concept TEER-specific TEE semantic segmentation framework initiated through a clinician-oriented workflow without formal computer science expertise. Although preliminary accuracy remains modest due to limited sample size, this study establishes a reproducible pathway for future AI-assisted intraprocedural guidance systems and larger multicenter development efforts in structural heart interventions.

Background: The manifestations of cardiovascular disease (CVD) among people with HIV (PWH) differ by region globally. While HIV disease is associated with increased atherosclerotic CVD risk in the global North, non-ischemic heart failure (HF) is more common in sub-Saharan Africa, the global HIV epicenter. We estimated the effect of treated HIV on the frequency and phenotype of HF and its cardiac precursors in South Africa (SA). Methods: In an observational study, we recruited PWH on antiretroviral therapy (ART), age [&ge;]40 years and people without HIV (PWoH) with similar distributions of age, sex, ethnicity, and hypertension, from a community clinic in Khayelitsha (Cape Town, SA). Procedures included a clinical assessment, echocardiography (Echo), and b-type natriuretic peptide (BNP) measure. Echo parameters defined structural abnormalities, left ventricle (LV) filling pressure, and LV systolic and diastolic dysfunction (DD). HF was defined by symptoms and/or BNP [&ge;]35pg/mL and LV dysfunction, subcategorized as reduced, mildly reduced, or preserved ejection fraction (HFrEF, HFmrEF, and HFpEF). Comparisons by HIV status were adjusted for age, sex, hypertension, smoking, obesity, diabetes, elevated LDL-cholesterol, and hazardous alcohol use. Results: Between September 2022 and August 2025, we enrolled 1008 PWH and 500 controls [median (Q1-Q3) age 48 years (43-53), 77% female]. Among PWH and controls respectively, 37% and 39% had hypertension, 21% and 25% were current smokers, 40% and 45% were obese, and 9% and 17% had diabetes. LV systolic dysfunction (1%) and HFrEF (1%) were rare, and undiagnosed HFpEF (8%) was the predominant HF phenotype. Compared to controls, PWH had higher odds of elevated LV mass index (LVMI) (OR 2.1; 95%CI 1.5-3.0) and DD (OR 1.4; 95%CI 1.0-2.0). Risk for elevated LVMI and DD was greatest among women with HIV, who also had an increased risk for undiagnosed HFpEF (OR 1.9; 95%CI 1.2-3.2), compared to women without HIV; effects which were not seen among men (p=0.051 for HIV*Sex interaction). Conclusions: In a peri-urban SA community with a high burden of cardiometabolic risk factors, the frequency of abnormal structural and functional cardiac precursors of HFpEF was greater amongst ART-treated PWH. This was most pronounced amongst women with HIV, who also had increased risk of undiagnosed HFpEF.

Background: Primary aldosteronism (PA) is increasingly recognized as a common cause of hypertension. The 2025 Endocrine Society guideline introduced a simplified diagnostic framework, but its real-world clinical implications remain unclear. Methods: We conducted a multicenter retrospective cohort study of hypertensive patients undergoing PA testing in Taiwan. PA was defined biochemically according to the 2025 Endocrine Society criteria. Multivariable logistic regression identified factors associated with PA diagnosis and aldosterone-targeted therapy. Among patients with suppressed renin (?1 ng/mL/h), restricted cubic splines evaluated the adjusted association between renin and PA probability. Results: Among 18,766 patients undergoing PA testing, 6,760 (36.0%) met diagnostic criteria for PA. PA was associated with older age, female sex, lower potassium, resistant hypertension, and a higher antihypertensive medication burden. Among patients with suppressed renin, lower renin remained significantly associated with higher adjusted PA probability. However, only 39.0% of patients with PA received aldosterone-targeted therapy, including 28.2% who received mineralocorticoid receptor antagonist therapy within 6 months and 9.4% who underwent adrenalectomy during follow-up. Lower renin, higher aldosterone, lower potassium, and resistant hypertension were associated with aldosterone-targeted therapy, while younger patients with fewer comorbidities were more likely to undergo adrenalectomy. Conclusions: Using the updated diagnostic framework, PA was highly prevalent among hypertensive patients undergoing PA testing. Nevertheless, many patients who met these biochemical criteria did not receive aldosterone-targeted therapy in routine care. These findings highlight the potential treatment implications of broader PA recognition and support the development of practical pathways to guide MRA therapy, adrenalectomy referral, and individualized management.

Despite its high prevalence and the discovery of hundreds of genetic associations, the genetic determinants and heterogeneous manifestations of asthma remain incompletely understood. Incorporating polygenic risk scores (PRS) into asthma research offers a powerful approach to quantify inherited susceptibility, refine risk profiles, and advance mechanistic understanding of disease development. For this study, we leveraged whole-genome sequencing (WGS) data from two family-based cohorts of childhood asthma - the Genetics of Asthma in Costa Rica Study (GACRS) and the Childhood Asthma Management Program (CAMP) - to examine the transmission profiles of externally derived asthma PRS and their associations with clinical phenotypes in children with asthma. To further elucidate molecular mechanisms, we integrated large-scale external genome-wide association study (GWAS) summary statistics and genetic prediction models of protein abundance in a two-step proteome-wide association study (PWAS) of asthma. Our findings provide robust evidence supporting the validity of externally derived asthma PRS (asthma PRS association p-value p={10}^{-24} [GACRS and CAMP trios combined] for the Global Biobank Meta-analysis Initiative [GBMI]) and reveal consistent associations with spirometry measures and atopy markers across both studies, as 13 of 21 traits (62%) were significantly associated with the GBMI-PRS in the meta-analysis after multiple-testing correction. Moreover, the results of the integrative proteomic analysis implicate IL-1 signaling in the etiology of asthma, reinforcing the candidacy of IL1R1 antagonists for drug repurposing.