Beyond GWAS: Identification and characterization of causal genes and novel biomarkers for coronary heart disease
There is a large need for revitalization of the cardiovascular field with: a) improved risk stratification on the individual level through personalized medicine for more adequate individually-tailored treatments; and b) new targets for drug development based on pathways previously unknown to be involved in CHD pathophysiology.
The overall aims of this research program are to improve treatment and risk prediction of CHD by discovery of new potential drug targets through improved understanding of biology; and identification of new biomarkers for improved risk stratification and individualized treatment by use of –omics methods in large population-based samples. The specific aims include: a) Identification of causal genes and functional variants through re-sequencing and other fine-mapping methods in known CHD regions, combined with expression profiling in liver, arteries, myocardium and skeletal muscle; b) Functional characterization of genes and pathways implicated in CHD pathophysiology via global metabolomic profiling, targeted proteomic profiling, and human system biology; c) Clinical biomarker identification and validation in the primary prevention setting.
In this proposal, we will integrate genomic, transcriptomic, metabolomic and proteomic data from six longitudinal, population-based cohort studies (STHLM2, Karma, TWINGENE, PIVUS, ULSAM and GOSH) and one study with tissue collections for expression studies (ASAP, N=600). The cohort studies include >200,000 individuals; there are 2,368 incident CHD cases at time of submission; and the estimated number of cases by 2015 is 9,086.
Our work is anticipated to lead to new important insights of the pathophysiology of coronary heart disease, opening up new avenues for drug development, and leading to new biomarkers that will improve risk prediction and prognostication.
Persons involved: Whole group
Genetics of insulin sensitivity: An integrated approach to discovery
In this research project, we propose to map novel genetic loci associated with insulin resistance by whole-exome sequencing in the tails of the insulin sensitivity distribution (248 individuals from each tail) of 71-year-old men examined with euglycemic hyperinsulinemic clamps from the ULSAM cohort (yr 1-2). We will combine exome sequencing with genotyping using Illumina Omni2.5 to also be able to interrogate the noncoding parts of the genome (yr 1-2).
Potential susceptibility loci will be replicated by examining independent samples assessed with the intravenous methods for measurement insulin sensitivity (N=4,856 individuals; yr 2-4), and we will address the potential role of these loci for fasting glucose and insulin, 2-h glucose and HbA1C (MAGIC); fat%, BMI and waist-hip ratio (GIANT); type 2 diabetes (DIAGRAM); lipid levels (Global Lipid Genetics Consortium) and coronary heart disease.
To characterize the pathophysiological role of novel genetic loci for insulin resistance, we will perform expression studies in a variety of relevant tissues, including skeletal muscle (n=206 from ULSAM and n=40 from elsewhere), adipose tissue (n=896), lymphoblastoid cells (n=826), liver (n=270), and aortic root (n=420; yr 2-4). Further, we will conduct downstream analyses of proteins and metabolites assessed with state-of-the-art targeted proteomics and global metabolomic profiling in ULSAM (yr 1-5).
This research proposal aims to identify novel genetic loci associated with insulin resistance and to characterize their mechanisms of action. We hope that our access to unique study materials, selection of state-of-the art methods, and strong track-record of successful collaborations in this field will generate substantial benefit to the scientific community, lead to new important insights around insulin resistance and its associated disorders, and produce new biomarkers of disease and improved risk prediction and prognostication, as well as new treatments against type 2 diabetes and cardiovascular disease.
Persons involved: Whole group
GIANT extremes: Differences between the extremes and overall distribution of anthropometric traits
Anthropometric traits have a strong genetic component with heritability estimates between 40-70% for body mass index (BMI) and ~80% for height; however, established loci only account for a small fraction (1-10%) of the phenotypic variance of these complex traits. It has been hypothesized that the extremes of the distributions of these traits are enriched for genetic loci and may have a distinct genetic architecture compared to the general population.
To explore the genetic contribution of the extremes (defined as the upper and lower 5th percentile) of BMI, height, and waist-hip ratio [WHR] adjusted for BMI and clinical classes of obesity (including overweight and obesity classes I, II, and III), we have conducted meta-analyses of ~2.8 million SNPs from 49 genome-wide association studies of European ancestry totaling from 4,774 cases and 5,481 controls (extreme WHR) to 93,015 cases and 65,840 controls (overweight) for these traits. The most promising loci from each meta-analysis (P<5 x 10-6) have been taken forward for replication into up to 65,332 cases and 39,294 controls.
We are currently finalizing a manuscript describing these findings.
Persons involved: Erik, Stefan, Andrea
Metabochip projects within several consortia
The Metabochip is a custom Illumina iSelect genotyping array designed to analyze, in a cost-effective manner, ~200,000 single nucleotide polymorphisms (SNPs) identified through GWAS meta-analyses of cardiovascular and metabolic traits. It was designed using data from the following GWAS meta-analysis consortia: CARDIoGRAM (coronary artery disease), DIAGRAM (type 2 diabetes), GIANT (anthropometrical traits), MAGIC (glycemic traits), Global Lipids Genetics Consortium (lipids), ICBP-GWAS (blood pressure), and QT-IGC (QT interval). The SNPs were selected for their associations with the following 25 traits: type 2 diabetes (T2D), fasting glucose, myocardial infarction, coronary artery disease, LDL cholesterol, HDL cholesterol, triglycerides, body mass index, waist-to-hip ratio adjusted for body mass index, systolic blood pressure, diastolic blood pressure, QT interval (primary traits); fasting insulin, 2-hr glucose, HbA1c, age of diagnosis of T2D, early onset T2D (cases < 45 years vs controls), waist circumference adjusted for BMI, height, percent fat mass, total cholesterol, platelet counts, mean platelet volume, and white blood cell counts (secondary traits). After merging and pruning the lists (to remove redundant SNPs), a total of 217,697 SNPs representing 245,243 bead types was submitted to Illumina for manufacturing.
Our group has submitted data to all seven consortia listed above, and we are active in the writing and analysis groups of the metabochip papers coming out of GIANT, GLGC, MAGIC and CARDIoGRAM.
Persons involved: Whole group
ENGAGE Mendelian randomization project
The European Network of Genomic and Genetic Epidemiology (ENGAGE) is a research project funded with 12 million euros by the European Commission under the 7th Framework Programme-Health Theme. The project duration is five years, starting from January 1st, 2008. The ENGAGE Consortium has brought together 24 leading research organizations and two biotechnology and pharmaceutical companies across Europe and in Canada and Australia.
We have, together with a group from Oxford University, been leading one of the flagship projects within ENGAGE. This flagship project has performed genotyping of a few SNPs in a large number of individuals across the ENGAGE cohorts aiming to address causality, pleiotropy and gene-environment interactions. Currently, we are analyzing data from the first part of this project where we investigate the FTO locus in a series of large-scale Mendelian randomization experiments in order to assess whether BMI has a mediation effect on the associations observed at this locus with a number of traits. Common variation in the FTO gene is associated with BMI and type 2 diabetes. Increased BMI is associated with various diabetes risk factors, including raised insulin, glucose, and triglycerides, other quantitative traits and related binary phenotypes.
Persons involved: Erik, Sara, Tove
The ongoing global obesity epidemic is a huge public health problem, as obesity is a strong risk factor for cardiovascular disease (CVD). Adipokines, cytokines that are mainly produced by adipose tissue, provide a link between obesity, insulin resistance, and inflammation, and have been proposed to be involved in the development of CVD.
In this project, we have examined associations of different adipokines (adiponectin, leptin, visfatin, ghrelin, retinol-binding protein 4, apelin, adipose-specific fatty acid binding protein, fetuin-A) with: a) genetic and early life factors; b) cardiovascular risk factors and subclinical CVD; and c) clinical CVD. We have used several population-based, longitudinal cohort studies (Swedish Twin Registry; Uppsala Longitudinal Study of Adult Men; and Prospective Investigation of the Vasculature in Uppsala Seniors). By utilizing the unique strengths of each study, we have examined the relations of adipokines and the development of cardiovascular disease throughout the cardiovascular continuum, from genetic and early life factors, through cardiometabolic factors and subsequent subclinical disease, to overt CVD. Increased knowledge of links between obesity and CVD may provide novel insights of disease mechanisms, biomarkers of disease, and treatments against CVD.
Persons involved: Erik, Stefan