Joint projects

ULSAM is involved in several large international collaborations. Most of them are focused on the identification of susceptibility genes for complex diseases.

Meta-Analysis of Glucose and Insulin Consortium (MAGIC)

The aim of the MAGIC consortium is to use large-scale genome-wide discovery to uncover genetic variants with robust associations to continuous metabolic traits of direct-relevance to type 2 diabetes: fasting glucose and fasting insulin levels together with HOMA-derived indices of beta-cell function and insulin action.

GENEtics of Insulin Sensitivity (GENESIS)

Insulin sensitivity is largely determined at the genetic level, with a heritability estimated at ~50%. However, GWAS in individuals with diabetes have exclusively identified genes that appear to be associated with pancreatic beta cell development and insulin production rather than peripheral tissue sensitivity to insulin action, which is the key component of insulin resistance. This is likely due to the study of imprecise surrogate measures of insulin resistance, a limitation which we aim to overcome in the GENESIS consortium consisting only of cohorts in whom insulin action is rigorously measured as a primary phenotype by gold standard euglycemic clamp or insulin suppression methods.

Genetic Investigation of ANthropometric Traits (GIANT)

The overall goal of the GIANT consortium is to combine data from large-scale genetic studies to identify variants that are associated with anthropometric traits, including height and obesity-related measures.

European Network of Genomic and Genetic Epidemiology (ENGAGE)

ENGAGE is a transnational collaborative research project funded by the European Commission. ENGAGE aims at translating the wealth of data emerging from large-scale research efforts in genetic and genomic epidemiology conducted in well-characterized European (and other) population cohorts into information relevant to future clinical applications.

Emerging Risk Factor Collaboration (ERFC)

The aim of ERFC is to study associations of circulating lipid and inflammatory markers with cardiovascular disease with reliable estimates under different circumstances and with the possibity to correct for within-person variability. ERFC has established a central database on over 1.2 million participants from 110 prospective population-based studies, in which subsets have information on lipid and inflammatory markers, other established risk factors and characteristics, as well as major cardiovascular morbidity and cause-specific mortality.