Marie C. Sadler

Integration of genetic evidence to identify approved drug targets

The paper integrates genetic signals to improve drug target identification by comparing prioritization strategies across traits and showing that combining related disease data enhances performance.

Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications

The paper uses EHRs and biobanks to identify pharmacogenetic associations with drug response in cardiometabolic diseases, finding novel genetic predictors for personalized treatment.

Genetic association studies using disease liabilities from deep neural networks

This paper introduces two methods for GWAS using disease liabilities from deep neural networks, identifying more loci and improving prediction of newly diagnosed cases.

Linking common and rare disease genetics through gene regulatory networks

This paper links common and rare disease genetics by identifying key genes affected by common variants through gene regulatory networks, finding many key genes are outside GWAS loci.

Breaking down causes, consequences, and mediating effects of age-related telomere shortening on human health

This study investigates the relationship between telomere length and health outcomes using UK Biobank data, identifying factors that influence telomere attrition and its effects on disease risk and lifespan.

Causality-Enriched Epigenetic Age Uncouples Damage and Adaptation

The paper introduces causality-enriched epigenetic clocks, DamAge and AdaptAge, to track detrimental and adaptive methylation changes linked to aging, showing their association with adverse outcomes and beneficial adaptations.

Copy-number variants as modulators of common disease susceptibility

This study identifies 73 CNV-related disease signals in 331,522 UK Biobank participants, showing CNVs increase disease risk and earlier onset, with polygenic effects and gene dosage impacts.

Multi-layered genetic approaches to identify approved drug targets

The paper compares gene-prioritization methods for identifying drug targets across 30 traits, finding GWAS performs best with an AUC of 54.3%.

The impact of 22q11.2 copy number variants on human traits in the general population.

This study investigates the phenotypic effects of 22q11.2 copy number variants in the general population using UK Biobank data, finding associations with BMI, platelet volume, and other traits.

Exploiting the mediating role of the metabolome to unravel transcript-to-phenotype associations

The paper develops a multi-omics Mendelian randomization framework to identify transcript-metabolite-trait causal triplets and shows it outperforms classical transcriptome-wide MR by integrating multiple omics layers.

Quantifying mediation between omics layers and complex traits

The paper quantifies mediation between DNA methylation, transcriptome, and proteome layers and their impact on complex traits using multivariable Mendelian randomization.

Novel discoveries and enhanced genomic prediction from modelling genetic risk of cancer age-at-onset

This paper improves cancer genomic prediction by analyzing age-at-diagnosis instead of case-control data, finding new genomic regions and enhancing prediction accuracy using Bayesian time-to-event modeling.

The individual and global impact of copy number variants on complex human traits

This study identifies 131 CNV signals associated with 47 complex traits in the UK Biobank, revealing new gene functions and linking CNVs to decreased longevity and health outcomes.

Differentially expressed genes reflect disease-induced rather than disease-causing changes in the transcriptome

This paper introduces revTWMR, a method to determine causal relationships between gene expression and complex traits, finding that traits more strongly influence gene expression than vice versa.