Evaluation of Bayesian Linear Regression derived gene set test methods.

Background: Gene set tests can pinpoint genes and biological pathways that exert small to moderate effects on complex diseases like Type 2 Diabetes (T2D). By aggregating genetic markers based on biological information, these tests can enhance the statistical power needed to detect genetic associations.

Results: Our goal was to develop a gene set test utilizing Bayesian Linear Regression (BLR) models, which account for both linkage disequilibrium (LD) and the complex genetic architectures intrinsic to diseases, thereby increasing the detection power of genetic associations.

Combining SNAC and C10 in oral tablet formulations for gastric peptide delivery: A preclinical and clinical study.

Current oral formulations of macromolecules including peptides typically rely on single permeation enhancer (PE) to promote absorption and thus bioavailability. In this work, we combined two PEs, namely sodium N-[8-(2-hydroxybenzoyl) amino] caprylate (SNAC) and sodium caprate (C10), in one tablet formulation to potentially gain a synergistic effect for enhanced gastric absorption of a GLP-1 analogue and a PCSK9 inhibitor. Permeability tests on a gastric organoids-based cell model showed that the combination of SNAC and C10 can significantly improve peptide permeability compared to either SNAC or C10 alone.

Molecular diagnoses and candidate gene identification in the congenital heart disease cohorts of the 100,000 genomes project.

Congenital heart disease (CHD) describes a structural cardiac defect present from birth. A cohort of participants recruited to the 100,000 Genomes Project (100 kGP) with syndromic CHD (286 probands) and familial CHD (262 probands) were identified. "Tiering" following genome sequencing data analysis prioritised variants in gene panels linked to participant phenotype.

Salcaprozate-based ionic liquids for GLP-1 gastric delivery: A mechanistic understanding of in vivo performance.

Oral delivery of peptides requires formulations with high concentrations of permeation enhancer (PE) to promote absorption, and often necessitates fasting time between dosing and food ingestion. Improved formulations promoting a more rapid absorption would increase convenience of use but requires a faster onset of action. We have developed a salcaprozate-based ionic liquid (IL) formulation, namely choline salcaprozate (CHONAC), for oral delivery of a glucagon-like peptide-1 (GLP-1) analogue via gastric absorption.

Evaluation of Bayesian Linear Regression models for gene set prioritization in complex diseases.

Genome-wide association studies (GWAS) provide valuable insights into the genetic architecture of complex traits, yet interpreting their results remains challenging due to the polygenic nature of most traits. Gene set analysis offers a solution by aggregating genetic variants into biologically relevant pathways, enhancing the detection of coordinated effects across multiple genes. In this study, we present and evaluate a gene set prioritization approach utilizing Bayesian Linear Regression (BLR) models to uncover shared genetic components among different phenotypes and facilitate biological interpretation.

Cardiomyopathies in 100,000 genomes project: interval evaluation improves diagnostic yield and informs strategies for ongoing gene discovery.

Background: Cardiomyopathies are clinically important conditions, with a strong genetic component. National genomic initiatives such as 100,000 Genome Project (100KGP) provide opportunity to study these rare conditions at scale beyond conventional research studies.

Methods: We present the clinical and molecular characteristics of the 100KGP cohort, comparing paediatric and adult probands with diverse cardiomyopathies.

Exploring and Accounting for Genetically Driven Effect Heterogeneity in Mendelian Randomization.

Mendelian randomization (MR) is a framework to estimate the causal effect of a modifiable health exposure, drug target or pharmaceutical intervention on a downstream outcome by using genetic variants as instrumental variables. A crucial assumption allowing estimation of the average causal effect in MR, termed homogeneity, is that the causal effect does not vary across levels of any instrument used in the analysis. In contrast, the science of pharmacogenetics seeks to actively uncover and exploit genetically driven effect heterogeneity for the purposes of precision medicine.

Stem cells tightly regulate dead cell clearance to maintain tissue fitness.

Billions of cells are eliminated daily from our bodies. Although macrophages and dendritic cells are dedicated to migrating and engulfing dying cells and debris, many epithelial and mesenchymal tissue cells can digest nearby apoptotic corpses. How these non-motile, non-professional phagocytes sense and eliminate dying cells while maintaining their normal tissue functions is unclear.

A Genomics England haplotype reference panel and imputation of UK Biobank.

We built a reference panel with 342 million autosomal variants using 78,195 individuals from the Genomics England (GEL) dataset, achieving a phasing switch error rate of 0.18% for European samples and imputation quality of r = 0.75 for variants with minor allele frequencies as low as 2 × 10 in white British samples.

Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records.

Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.

Paired plasma lipidomics and proteomics analysis in the conversion from mild cognitive impairment to Alzheimer's disease.

Background: Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed.

Exome Sequencing and Statin Treatment Response in 64,000 UK Biobank Patients.

The solute carrier organic anion transporter family member 1B1 () encodes the organic anion-transporting polypeptide 1B1 (OATP1B1 protein) that transports statins to liver cells. Common genetic variants in , such as *5, cause altered systemic exposure to statins and therefore affect statin outcomes, with potential pharmacogenetic applications; yet, evidence is inconclusive. We studied common and rare variants in up to 64,000 patients from UK Biobank prescribed simvastatin or atorvastatin, combining whole-exome sequencing data with up to 25-year routine clinical records.

variants in the non-coding spliceosomal snRNA gene are a frequent cause of syndromic neurodevelopmental disorders.

Around 60% of individuals with neurodevelopmental disorders (NDD) remain undiagnosed after comprehensive genetic testing, primarily of protein-coding genes. Increasingly, large genome-sequenced cohorts are improving our ability to discover new diagnoses in the non-coding genome. Here, we identify the non-coding RNA as a novel syndromic NDD gene.

Polygenic scores for cardiovascular risk factors improve estimation of clinical outcomes in CCB treatment compared to pharmacogenetic variants alone.

Pharmacogenetic variants are associated with clinical outcomes during Calcium Channel Blocker (CCB) treatment, yet whether the effects are modified by genetically predicted clinical risk factors is unknown. We analyzed 32,000 UK Biobank participants treated with dihydropiridine CCBs (mean 5.9 years), including 23 pharmacogenetic variants, and calculated polygenic scores for systolic and diastolic blood pressures, body fat mass, and other patient characteristics.

Deep learning to decode sites of RNA translation in normal and cancerous tissues.

The biological process of RNA translation is fundamental to cellular life and has wide-ranging implications for human disease. Yet, accurately delineating the variation in RNA translation represents a significant challenge. Here, we develop RiboTIE, a transformer model-based approach to map global RNA translation.

Data-driven identification of predictive risk biomarkers for subgroups of osteoarthritis using interpretable machine learning.

Osteoarthritis (OA) is increasing in prevalence and has a severe impact on patients' lives. However, our understanding of biomarkers driving OA risk remains limited. We developed a model predicting the five-year risk of OA diagnosis, integrating retrospective clinical, lifestyle and biomarker data from the UK Biobank (19,120 patients with OA, ROC-AUC: 0.

Iron Status and Risk of Heart Disease, Stroke, and Diabetes: A Mendelian Randomization Study in European Adults.

Background: The relevance of iron status biomarkers for coronary artery disease (CAD), heart failure (HF), ischemic stroke (IS), and type 2 diabetes (T2D) is uncertain. We compared the observational and Mendelian randomization (MR) analyses of iron status biomarkers and hemoglobin with these diseases.

Methods And Results: Observational analyses of hemoglobin were compared with genetically predicted hemoglobin with cardiovascular diseases and diabetes in the UK Biobank.

Robust use of phenotypic heterogeneity at drug target genes for mechanistic insights: Application of cis-multivariable Mendelian randomization to GLP1R gene region.

Phenotypic heterogeneity at genomic loci encoding drug targets can be exploited by multivariable Mendelian randomization to provide insight into the pathways by which pharmacological interventions may affect disease risk. However, statistical inference in such investigations may be poor if overdispersion heterogeneity in measured genetic associations is unaccounted for. In this work, we first develop conditional F statistics for dimension-reduced genetic associations that enable more accurate measurement of phenotypic heterogeneity.

Cardiovascular risk burden, dementia risk and brain structural imaging markers: a study from UK Biobank.

Background: Cardiovascular risk burden is associated with dementia risk and neurodegeneration-related brain structure, while the role of genetics and incident cardiovascular disease (CVD) remains unclear.

Aims: To examine the association of overall cardiovascular risk burden with the risk of major dementia subtypes and volumes of related brain regions in a large sample, and to explore the role of genetics and CVD onset.

Methods: A prospective study among 354 654 participants free of CVD and dementia (2006-2010, mean age 56.