Multi-Omics Investigation into Acute Myocardial Infarction: An Integrative Method Revealing Interconnections amongst the Metabolome, Lipidome, Glycome, and Metallome

Abstract

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. This work aims to investigate the translational potential of a multi-omics study (comprising metabolomics, lipidomics, glycomics, and metallomics) in revealing biomechanistic insights into AMI. Following the N-glycomics and metallomics studies performed by our group previously, untargeted metabolomic and lipidomic profiles were generated and analysed in this work via the use of a simultaneous metabolite/lipid extraction and liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis workflow. The workflow was applied to blood plasma samples from AMI cases (n = 101) and age-matched healthy controls (n = 66). The annotated metabolomic (number of features, n = 27) and lipidomic (n = 48) profiles, along with the glycomic (n = 37) and metallomic (n = 30) profiles of the same set of AMI and healthy samples were integrated and analysed. The integration method used here works by identifying a linear combination of maximally correlated features across the four omics datasets, via utilising both block-partial least squares-discriminant analysis (block-PLS-DA) based on sparse generalised canonical correlation analysis. Based on the multi-omics mapping of biomolecular interconnections, several postulations were derived. These include the potential roles of glycerophospholipids in N-glycan-modulated immunoregulatory effects, as well as the augmentation of the importance of Ca–ATPases in cardiovascular conditions, while also suggesting contributions of phosphatidylethanolamine in their functions. Moreover, it was shown that combining the four omics datasets synergistically enhanced the classifier performance in discriminating between AMI and healthy subjects. Fresh and intriguing insights into AMI, otherwise undetected via single-omics analysis, were revealed in this multi-omics study. Taken together, we provide evidence that a multi-omics strategy may synergistically reinforce and enhance our understanding of diseases.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

“…Due to the elevated risk of mortality with these diseases, there is a need for strategies in its identification, prevention, and treatment within healthcare. In 2022, as evidenced in Figure 5, the bulk of research articles focussed on related diseases: CVD, 232–255 diabetes, 166,233,249,250,256–278 liver disease, 51,279–293 MetS 277,294,295 and obesity 277,295–305 …”

“… 227 , 228 , 229 , 230 , 231 Due to the elevated risk of mortality with these diseases, there is a need for strategies in its identification, prevention, and treatment within healthcare. In 2022, as evidenced in Figure 5 , the bulk of research articles focussed on related diseases: CVD, 232 , 233 , 234 , 235 , 236 , 237 , 238 , 239 , 240 , 241 , 242 , 243 , 244 , 245 , 246 , 247 , 248 , 249 , 250 , 251 , 252 , 253 , 254 , 255 diabetes, 166 , 233 , 249 , 250 , 256 , 257 , 258 , 259 , 260 , 261 , 262 , 263 , 264 , 265 , 266 , 267 , 268 ,…”

“…Bibliometric analyses of clinical lipidomics publications in 2022 using Scopus search terms “lipidomics” AND “clinic*” on 15 th December 2022 …”

“…Bibliometric analyses of clinical lipidomics publications in 2022 according to separation techniques, detectors, and RPLC columns used …”

From multi-omics approaches to personalized medicine in myocardial infarction

“…Furthermore, multi-omics data integration analysis enables the development of biomarkers for early diagnosis and personalized medicine of MI. Lim et al (341)…”