Melina Claussnitzer

The paper introduces CASTIE, a method for context-dependent eQTL mapping in single-cell data, identifying regulatory variants missed by static models and linking them to disease traits.

sc-pcQTL identifies multi-gene QTLs in single-cell RNA-seq data by combining hurdle modeling and principal-component analysis, revealing cell-type-specific regulatory effects.

This study identifies peripheral immune and metabolic tissues as key contributors to Alzheimer's disease genetic risk, independent of brain-specific factors.

The paper maps context-dependent genetic regulation of cardiometabolic loci in human adipocytes using a multi-donor cell village system and single-nucleus multiome sequencing under various metabolic stress conditions.

TEscape uses long-read sequencing to comprehensively annotate the human transposable element transcriptome, identifying over 83,000 previously unannotated isoforms.

This study identifies 282 genetic loci associated with insulin resistance through multi-trait GWAS, highlighting adipose-specific and systemic regulators and potential therapeutic targets.

The paper introduces TGlow, a high-content imaging platform for single-cell phenotyping of human lymphocytes, revealing distinct morphological states and drug responses.

This study identifies 12 enhancers in the 9p21.3 CAD risk locus that regulate MTAP, modulating vascular cell-state transitions and CAD risk through stress-responsive mechanisms.

This study identifies genetic subtypes of obesity that uncouple adiposity from cardiometabolic risks, revealing distinct biological pathways and protein associations.

The paper identifies genes associated with obesity and fat distribution using genetic and functional data, then validates their roles through CRISPR knockdown in cell lines.

This study identifies IRX3 as a regulator of sumoylation that controls adipogenesis and osteogenesis through epigenetic mechanisms, linking the FTO locus to obesity.

The paper identifies rare missense variants in LAR that destabilize the extracellular domain, disrupt LAR:NGL-3 interactions, and impair synaptic adhesion and synaptogenesis.

The paper presents a genome-wide perturbation atlas using CRISPR-Cas9 knockouts to link genes to cellular phenotypes, identifying TMEM251/LYSET as a Golgi-resident protein involved in lysosomal enzyme trafficking.

This study shows that reducing RREB1 in mice and humans decreases adipogenesis and improves insulin sensitivity, linking RREB1 to type 2 diabetes risk.

This study identifies genetic subtypes of type 2 diabetes across diverse ancestries, revealing ancestry-specific risk profiles and BMI thresholds.

The paper introduces LipocyteProfiler, a high-throughput microscopy assay to profile lipid-storing cells and identifies cellular programs linked to metabolic traits like insulin resistance and lipodystrophy.

The paper identifies a causal eQTL at MTIF3 associated with weight loss and shows MTIF3 deficiency affects adipocyte mitochondrial function and lipid metabolism.

The paper develops a deep learning method for adipocyte phenotyping and finds adipocyte area correlates with BMI but no genome-wide significant genetic associations.

The paper introduces HiDRA, a method for high-resolution functional analysis of regulatory regions, identifying 13,000 driver elements and linking them to disease-associated variants.

CONVERGE identifies co-localization of GWAS variants with transcription factor binding sites in regulatory regions to find novel trait regulators, outperforming existing methods in validating type 2 diabetes regulators.