Multiomics approaches harness synergies and eliminate shortcomings to effectively deliver what one omics science alone cannot achieve. Lipotype’s new white paper “Unlocking the Power of Multiomics” highlights why combining genomics with lipidomics makes for a great omics pair.
Genomics for genes, lipidomics for lipids
Being major players in cardiovascular disease research, genomics and lipidomics are perfectly suited for a joint multiomics approach. It matches the capacity to identify genetic predestinations with one or multiple snapshots of the lipid metabolic status.
Linking genotype with phenotype will be critical when it comes to clinical diagnostics and to the goal of identifying the onsets of a disease.
From genotype to phenotype: interconnected disease risk factors
In this study, a large number of SNPs (single-nucleotide polymorphisms) from genomes was drawn. They were then correlated with corresponding lipid species levels from human blood plasma. The blood plasma has been analyzed with Lipotype Shotgun Lipidomics technology. The most important findings are the following.
First, the heritability of lipid species levels was quantified from the SNP correlations. Second, genetic predispositions influencing lipid species levels provide useful information for cardiovascular disease risk predictions. And third, lipidomics yields greater statistical power to identify SNPs with direct roles in lipid metabolism. Lipidomics outperforms traditional lipid panel measures used in clinical routine.
Lipotype White Paper: Unlocking the Power of Multiomics
Press release: Unlocking the Power of Multiomics – Lipotype releases new Multiomics White Paper
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Lipidomics is the large-scale investigation of lipids in biological systems. Venturing into the analysis of large dataset, with potential thousands of lipidomes, by advanced multiparametric statistical approaches is a challenging endeavour. We established algorithms and a full set of methods tailored to quantitative lipid data. This allows to perform statistical analysis and enrichment analysis in order to identify lipid biomarkers. In our recently published white paper a cohort of healthy subjects is compared with a cohort of diseased subjects. The result is a lipid signature that discriminates healthy from disease. Those could then potentially be of use for disease stratification or diagnosis by means of predictive modelling (machine learning). In this white paper, we will guide you through the data analysis process for lipid biomarkers. Read more
Learn more about Big Data Lipidomics and get the White Paper.
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In the latest issue of the Journal of the American Heart Association, Lipotype and Lund University published a paper in which high-throughput lipidomic screening was successfully applied to reveal molecular lipid profiles in blood serum specific for Diabetes mellitus and myocardial infarction.
Read the whole publication here:
Identification of Shared and Unique Serum Lipid Profiles in Diabetes Mellitus and Myocardial Infarction, , 2016
Lipotype performed with the Lund University, Sweden a study to analyze 2000 blood samples in order to identify disease related lipid biomarkers.
Read more in our case study :about the study here!