Josep Maria Mercader

The paper estimates whole-genome heritability of complex traits across diverse populations, finding rare and non-coding variants significantly contribute to heritability.

The paper examines how social determinants of health modify polygenic risk scores for cardiometabolic diseases and shows that integrating social and genetic factors improves disease prediction.

This study identifies GDF3 as an endogenous inhibitor of the ActE-ALK7 pathway in adipocytes, showing its role in metabolic diseases like MASLD/MASH and suggesting GDF3 inhibition as a therapeutic target.

This paper compares two Bayesian methods for polygenic risk scores (PRS) for hypertension across two ancestry groups, finding improved performance with updated LD panels and functional annotations, but not equitable results between groups.

This paper develops and validates multi-ancestry polygenic risk scores for type 2 diabetes prediction and complications across diverse populations.

This paper improves type 2 diabetes polygenic risk scores by including rare and population-specific variants, showing better risk prediction in diverse populations.

This study investigates causal links between T2D genetic clusters and non-cardiovascular comorbidities, identifying potential drug repurposing opportunities.

The paper identifies genetic variants near SLC2A2 that influence glycemic response to glimepiride in type 2 diabetes patients.

The paper identifies ancestry-specific T2D risk variants in South Asian populations through exome-wide association study and functional validation.

The paper conducts a large-scale rare variant GWAS meta-analysis of type 2 diabetes, identifying novel variants in monogenic diabetes genes and assessing their pathogenicity.

This study integrates multi-omics data to identify genetic variants and molecular mechanisms associated with type 2 diabetes and highlights potential drug targets.

This paper conducts a multi-ancestry time-to-event GWAS to identify genetic variants associated with incident cardiovascular disease in people with type 2 diabetes, finding three novel loci and confirming known CAD variants.

Admix-kit provides tools for genetic analysis of admixed populations, enabling simulation, association testing, and polygenic scoring.

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 demonstrates that TOPMed imputation improves the identification of rare variants associated with type 2 diabetes in Latino populations, leading to novel associations and better polygenic scores.

This paper clusters T2D genetic loci into ten groups using bNMF, identifying distinct biological mechanisms and clinical associations.

The paper identifies splicing QTLs in human pancreatic islets that contribute to type 2 diabetes susceptibility by affecting gene splicing and revealing novel molecular mechanisms.

This study identifies novel genetic loci for BMI, height, and WHRadjBMI in Hispanic/Latino populations and shows the benefits of ancestral diversity in GWAS.

This study identifies 277 T2D loci using diverse populations and improves fine-mapping to assess causal genes and mechanisms, enhancing clinical translation.

The paper creates TIGER, a resource integrating RNA-seq and genotyping data from human pancreatic islets to identify eQTLs and their associations with type 2 diabetes.

This study applies an improved GWAS strategy to age-related diseases, identifying new genetic loci by using multiple reference panels, analyzing the X chromosome, and testing non-additive models.

This paper introduces cov-LDSC, a method to estimate heritability and its enrichment in tissue-specific gene sets in admixed populations, showing high concordance across populations but population-specific differences for some traits.

The paper identifies BMI-associated metabolites using untargeted metabolomics and causal inference, finding both known and unknown metabolites with causal links to obesity.

The paper identifies a missense variant in the MARC1 gene associated with protection against cirrhosis and lower liver enzyme and cholesterol levels.

The paper identifies common polymorphic inversions associated with multiple common diseases and suggests their role in shared genetic susceptibility.

The paper links diabetes-associated enhancers with their target genes using 3D chromatin architecture in human pancreatic islets, revealing genetic variants that impact insulin secretion heritability.

PAIRUP-MS imputes and annotates unknown metabolite signals in mass spectrometry data, improving pathway analysis and meta-analysis power for metabolomics studies.

This study identifies rare genetic variants associated with type 2 diabetes using exome sequencing of 20,791 cases and 24,440 controls, and provides a Bayesian framework to improve variant prioritization.

The paper investigates the impact of rare protein truncating variants on 13 quantitative traits and 10 diseases using whole-exome sequencing data from 100,296 individuals, finding increased risk for several disorders and associations with other phenotypes.