Genetics

VarDrug: A Machine Learning Approach for Variant-Drug Interaction, Application to Drugs for Psychiatric Disorders

Predicting variant-drug interactions is essential for advancing precision medicine across therapeutic areas. The Pharmacogenomics Knowledge Base (PharmGKB) dataset, with ~11,000 samples, is underutilized in machine learning (ML) due to its limited size. After filtering for variant mappings and excluding metabolizer-related conditions, we obtain ~4,000 samples for a six-class prediction task (incre...

Epistatic contributions to human traits via transcription factor mechanisms

Epistasis causes an individual’s genetic background to modulate a DNA variant’s effect on trait [1–6]. Epistatic interactions among different loci in human complex traits are expected to be widespread but have not been found [7]. This could be due to small interaction effect sizes, the statistical complexity of estimating interactions that is higher than marginal variant effects, and a substantial...

aiDIVA – Diagnostics of Rare Genetic Diseases Using Large Language Models

Genome sequencing (GS) enables the accurate identification of genetic variants in most genomic regions and is rapidly transforming routine diagnostics...

Large-scale Proteomics Profiling of Peripheral Blood of DM1 patients identifies biomarkers for disease severity and functional capacity

Myotonic Dystrophy Type 1 (DM1), the most common genetic neuromuscular disorder in adults, poses significant challenges for drug development due to it...

Deep learning-based precision phenotyping of spine curvature identifies novel genetic risk loci for scoliosis in the UK Biobank

Scoliosis is the most common developmental spinal deformity, but its genetic underpinnings remain only partially understood. To enhance the identifica...

Clinical Validation of RlapsRisk BC in an international multi-cohorts setting

This study evaluated the prognostic performance of RlapsRisk BC, a multimodal deep learning tool designed to predict distant recurrence-free interval ...

The HeartMagic prospective observational study protocol – characterizing subtypes of heart failure with preserved ejection fraction

Heart failure (HF) is a life-threatening syndrome with significant morbidity and mortality. While evidence-based drug treatments have effectively redu...

Genomic Classification of Acute Lymphoblastic Leukemia Using AI: Towards Personalized Medicine

Acute lymphoblastic leukemia is a highly heterogeneous hematologic malignancy that poses significant challenges for clinicians in terms of early detec...

Enhancer-targeting CRISPR screens at coronary artery disease loci suggest shared mechanisms of disease risk

To systematically identify causal genetic mechanisms that confer risk for coronary artery disease (CAD) in GWAS loci, we mapped genome-wide variant-to...

Experimental investigation of muscle-tendon unit geometry and kinematics in lower-limb muscles during gait: Current Applications and Future Directions – A Scoping Review

Musculoskeletal (MSK) modeling and ultrasound imaging (USI) are complementary techniques that, when combined with three-dimensional gait analysis (3DG...

Development of a machine learning model to predict short duration HCV treatment response

Standard durations of direct acting antivirals (DAAs; 8–12 weeks) can be a barrier to HCV treatment initiation and completion among marginalised popul...

Identification of Key Genes Governing the Effects of Physical Activity on Ferroptosis in Alzheimer’s Disease Patients: A Machine Learning-Based Study

Disrupted brain iron metabolism and activated ferroptosis during ageing constitute significant precursors to neurodegenerative diseases. However, whet...

Using deep learning to improve genetic studies of osteoporosis

To evaluate how recent advances in deep learning can improve the construction of quantitative phenotypes for genome-wide association studies (GWAS), w...

Artificial Intelligence in Early Detection of Autism Spectrum Disorder for Preschool ages: A Systematic Literature Review

Early detection of autism spectrum disorder (ASD) improves outcomes, yet clinical assessment is time-intensive. Artificial intelligence (AI) may suppo...

Combining blood transcriptomic signatures improves the prediction of progression to tuberculosis among household contacts in Brazil

Tuberculosis remains a major health threat, infecting nearly a third of the world’s population. Of those infected, 5-10% progress from latent infectio...

ViraLite: An Ultracompact HIV Viral Load Self-Testing System with Internal Quality Control

The availability of effective antiretroviral therapy has made HIV manageable, provided patients have consistent access to routine viral load (VL) test...

Early Prediction of Gestational Diabetes Using Integrated Cell-free DNA Features and Omics-derived Genetic Scores

Gestational diabetes mellitus (GDM) affects 15.6% of pregnancies globally, with Vietnam exhibiting one of the highest prevalences at 21%. Current diag...

How do clinician and parent reported data differ? An analysis of similarity and difference in the datasets from a cross-syndrome genetics cohort study(GenROC)

Parent/patient-reported datasets provide ready access to phenotypic data for monogenic neurodevelopmental disorders yet their concordance with clinica...

Novel Epistatic Interaction Between RBMS3 and CDKN2B-AS1 in Coronary Artery Disease Risk Identified by Machine Learning Tool VariantSpark

Genome-wide association studies (GWAS) of coronary artery disease (CAD), the leading cause of mortality and morbidity globally, have identified approx...

Benchmarking non-additive genetic effects on polygenic prediction and machine learning-based approaches

Polygenic scores (PGSs) are widely used to translate genome-wide association study (GWAS) findings into tools for genetic risk prediction. Most curren...