• Cardiovascular diseases are the leading cause of death
• Omic-based studies can produce novel insight into diseases
• Multiomics analyses of 2200 plasma samples found links between genotypes, lipids, and cardiovascular diseases
CARDIOVASCULAR diseases are the leading cause of death worldwide. This group of conditions – which includes arrhythmia and heart failure – are indicated by a reduced ability of the heart and blood vessels to move blood throughout the body. Risk factors for cardiovascular disease include genetics, diet, and physical inactivity; symptoms include stroke and heart attack.
Leading causes of death globally: In 2019, the 10 leading causes of death accounted for 55% of all deaths worldwide. Cardiovascular diseases are highlighted in green. WHO Global Health Estimates, World Health Organization (2019), www.who.int
Plasma lipids such as cholesterols, triglycerides, and lipoproteins are often used to estimate an individual’s risk of developing cardiovascular diseases. Often, certain cardiovascular and inflammatory diseases are reflected in plasma lipidome. While informative, a more comprehensive picture of the plasma lipidome – especially if combined with other omic endpoints – may improve prediction of and inform therapies for cardiovascular diseases.
The study cohort consisted of 2181 samples from the EUFAM and FINRISK biobanks. Individual samples were analyzed via genotyping and plasma lipidomics followed by association analyses. This approach identified ~9.3 million genetic markers; 141 lipid species distributed among 13 classes; and numerous associations between genotypes and lipid species.
Initial analyses showed that single nucleotide polymorphisms – or SNPs, which are common heritable genetic variations – associate with the presence of certain lipid species in the plasma. Specifically, ceramides and lipids containing polyunsaturated fatty acids were highly heritable; phosphatidylinositols were the least heritable.
Single Nucleotide Polymorphisms (SNPs): SNPs are genetic variations in just one base pair. For example, most people may have the genetic code GCAACGTTAGA at a specific position but some might feature the genetic sequence GCAGCGTTAGA instead.
Subsequent genome-wide association analyses identified 2817 associations between 518 genetic variants and 42 lipid species. These associations both corroborated previous research and identified new associations. For example, the analysis demonstrated a strong association between genetic variants and lipid species containing polyunsaturated fatty acids; it also identified a new relationship between the ROCK1 loci – involved in glucose metabolism – and short acyl-chain lyso-phosphatidylcholine.
Heritability of lipidomic profiles and genetic correlations among the lipid species:A Median heritability estimates in each lipid class. B Heritability estimates based on selected fatty acid chains in lipid species. Rubina Tabassum et al., Nature Communications (2019), doi: 10.1038/s41467-019-11954-8
To explore how these associations relate to cardiovascular disease, 25 phenotypes linked to cardiovascular disease were cataloged from data available in the FinnGEN and UK Biobank cohorts. Then, these phenotypes were compared to genetic variants associated with lipid species. This analysis showed that 10 genetic variants associated with lipids also correlate with cardiovascular disease phenotypes.
For example, variants at GLTPD2 were linked to sphingomyelin concentration and thus risk for atherosclerosis; variants at SPTLC3 were shown to regulate total ceramide levels and thus odds for intracerebral hemorrhage; and variants at COL5A1 were associated with phosphatidylcholine level and thus probability of cerebrovascular disease. Further, these lipidomic-based associations were statistically stronger than those for traditional plasma lipid metrics.
Relationship between lipid-associated variants and cardiovascular diseases: Shown are selected associations of the identified genetic variants (SNPs) with the strongest associated lipid (species), and the relationship between the identified variants with cardiovascular disease phenotypes as odds ratios. Highlighted in red color are associations significant at FDR <0.05. Rubina Tabassum et al., Nature Communications (2019), doi: 10.1038/s41467-019-11954-8
Overall, this report established the heritability of plasma lipid levels and linked these metrics to risk for cardiovascular disease phenotypes. The study’s multiomics database – comprised of population genotypic, lipidomic, and phenotypic data – may also serve as a resource for future studies of population health.
Omic-based studies that include lipidomics can be very informative. In this report, such data were used to establish new associations between genetic variants, plasma lipid species, and risk for cardiovascular diseases. In previous studies, a combination of lipidomic and other omic data have produced new insights regarding the molecular basis of diseases like type 1 diabetes, Alzheimer’s disease, and cancer.
Lipotype Lipidomics technology can characterize the lipidome in plasma samples. The resulting data can predict risk for conditions like cardiovascular disease and obesity; can monitor changes in lipid metabolism during insulin sensitivity and anorexia; and may be used to study other biological conditions.
Related articles
Lipidomics of keratinocyte differentiation
Lipid analysis helps to discover lipid species affecting the differentiation of human skin stem cells.
together with Institute for Molecular Medicine Finland
FIMM is a translational institute with a driving mission to perform innovative research on patients and populations targeted towards understanding drivers of health and disease and delivering improvements to the safety, efficacy and efficiency of healthcare.
Share this story
You are currently viewing a placeholder content from OpenStreetMap. To access the actual content, click the button below. Please note that doing so will share data with third-party providers.
