Home   Lipidomics Research   Multiomics & CVD Research 

Multiomics in CVD Research

Research Article Genes and lipids have both been linked to cardiovascular disease, but their interrelationship had not been disclosed yet.

About the author


Henri Deda
Communications Officer

Henri Deda holds a degree in Molecular Bioengineering. He is spirited to discover what scientists are interested in and to provide concise answers.

Resources


Genetic architecture of human plasma…

Tabassum et al. | Nat Commun (2019)


An automated shotgun lipidomics platform…

Surma et al. | EJLT (2015)


Systematic screening for novel lipids by…

Papan et al. | Anal. Chem. (2014)


Lipidomics Resource Center

 

About Lipotype


Lipotype is the leading lipidomics service provider. Order your service. Send your samples. Get your data.

Lipotype Shotgun Lipidomics


Coverage of 57 lipid classes and 3100+ individual lipids

Rich variety of sample types from subcellular to organs

High-throughput analysis for data in as little as 2 weeks

GMP certified, robust, and highly reproducible

A red light LED model of the heart mounted on a black surface.

Summary

• Multiomics of 4300+ samples linked genetic variants to lipids
• Lipid metabolism is considerably influenced by genetics
• Combining lipidomic, genomic, and patient data found new risk factors for cardiovascular disease

WITH an ever-increasing pool of accessible information and new tools to mine huge data sets, biology and medicine are moving from intervention to prevention. Omics sciences such as genomics and lipidomics are strong contributors to this paradigm shift. Being major players in cardiovascular disease research, genomics and lipidomics make a great multiomics pair. It matches the capacity to identify genetic predestinations with one or multiple snapshots of the lipid metabolic status to investigate cardiovascular diseases.

An infographic showing the relationship between genes, lipids and cardiovascular diseases such as stroke, atherosclerosis or hypertension.

Where genetics zeroes in on the composition and functioning of one gene, genomics addresses the sum of all genes, the genome, and their interrelationships. The systems biology of genes delivers genome mapping and editing data, illuminates structure and function relationships and gives insights into evolutionary processes. The most important outcome is the DNA sequence.

In analogy to genomics, lipidomics is the study of lipids and lipid metabolites in biological systems. Targeting thousands of chemically distinct lipid molecules, lipidomics unveils the many different biological functions of lipids which range from storing energy, serving as hormones and signaling molecules to forming the cell membrane. Like sequencing DNA in genomics, the omics of lipids analyzes the lipid composition in cells and body fluids.

A graph showing the leading causes of death globally in 2019 including ischaemic heart disease, stroke, COPD, lower respiratory infections and more. The top two causes of death are cardiovascular diseases.

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

Since the beginning of the obesity pandemic, abnormal blood plasma lipid levels are a well-established risk factors for cardiovascular disease, such as ischaemic heart disease, stroke, or heart failure. Similarly, the risk for cardiovascular diseases is heritable and must therefore be linked to the DNA – at least to some extent. Still, the genetic architecture behind detailed blood plasma lipid profiles is unknown. Understanding their genetic regulation could help guide the development of tools for prediction and treatment of cardiovascular disease.

Thus, being major drivers in cardiovascular disease research, genomics and lipidomics make a great multiomics pair. Lipidomics eliminates the shortcoming of genomics to describe an organism’s current metabolic status, genomics waives the drawback of lipidomics to take the fixed settings of its DNA into consideration.

A graphic representation of an SNP. 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.

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.

Researchers from the Institute for Molecular Medicine at University Helsinki collaborated with scientists from Lipotype for a joint multiomics project on cardiovascular disease. They aimed to understand to which extent a lipid profile is passed from one generation to the next one and how genes, lipids, and cardiovascular diseases are related to each other. Lipid analysis was applied to more than 4300 blood plasma samples from four cohorts which contained data on cardiovascular disease events, then the same samples were genotyped in preparation for an SNP-based heritability calculation of the lipids.

In SNP-based heritability calculations, a large number of SNPs from many genomes are drawn and then correlated with corresponding traits, e.g. lipid class levels in blood plasma. If an SNP appears in many people who share a similar lipid class level, the SNP is correlated to it. Based on the calculations, a heritability estimate score is generated which ranges from 0 (not inherited) to 1 (inherited).

Scientific graphs showing heritability estimates of selected lipid classes and long, poly-unsatured fatty acids. The first graph depicts median heritability estimates in each lipid class, the second one shows heritability estimates based on selected fatty acid chains in lipid species.

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

The results of the SNP-based lipid heritability calculation highlighted considerable variations across lipid classes, for example indicating that ceramide lipids (CER) are inherited to a stronger degree than phosphatidylinositol lipids (PI). A comparison of saturation degree and chain length of fatty acids revealed additional patterns. Lipids containing polyunsaturated fatty acids – particularly chain lengths of at least 20 carbon atoms with four, five or six double bonds – had a significantly higher heritability than other lipid species.

While a person’s lipid metabolism is considerably influenced by genetics, this does not apply to all lipid species in the same way. Longer, and more saturated lipids feature a stronger genetic sharing. Still, despite dietary influences on the blood plasma lipid profile, lipid species levels are inheritable. Thus, opening up the research project to questions on how specific lipid metabolism influencing SNPs are related to an increased or decreased risk for certain cardiovascular diseases.

Linking the lipidomics and genomics data to the information on cardiovascular disease events from the more than 4300 blood plasma samples from the four cohorts brought forth new insights.

Scientific graph showing 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

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

For example, variants at GLTPD2 were linked to changes in levels of a specific sphingomyelin (SM) and a significantly decreased risk for atherosclerosis. Ceramides (CER) had been reported to influence the risk for cardiovascular events. A novel association of an SNP at SPTLC3 was associated with changes in total ceramide levels and lowered odds for intracerebral hemorrhage. Variants at COL5A1 were associated with changes in the plasma level of a specific phosphatidylcholine (PC) and simultaneously an increased risk for cerebrovascular disease.

Many more small changes in the genome were related to aberrations of the lipid profile and an increased or decreased risk for certain cardiovascular diseases. The lipidomics-genomics multiomics method shed light on lipid biology and corresponding genetic factors associated with disease risks. Such findings demonstrate how lipid analysis in a multiomics analysis can provide novel information to develop new preventive strategies – for cardiovascular disease, diabetes, and many more conditions.

Genomics and lipidomics are perfectly suited for a joint multiomics profile analysis in cardiovascular disease research. Combining data from both omics sciences delivers information for novel disease prevention strategies such as lipid metabolism altering therapies.

Lipotype Shotgun Lipidomics technology provides results in absolute values, the basis to compare data from different sample sets and/or experiments. This facilitates researchers to seamlessly integrate their lipid analysis data into results acquired from other omics technologies for true multiomics analyses.

Related articles

See all articles

together with
Institute for Molecular Medicine Finland


Logo of the FIMM, the 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

About Lipotype


Lipotype is the leading lipidomics service provider to reach your research goals. Order your lipidomics service, send in your samples and get your data in as little as two weeks.