Assessing the impact of bariatric surgery on cardiovascular risk in type 2 diabetes: a systematic review and meta-analysis using OMICs data

Figures

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  Fig. 1. Conceptual illustration of multi-OMICs integrating genomics, epigenomics, transcriptomics, microbiome, metabolomics, and proteomics to study disease. Genomics mainly studies DNA sequence and associated heritable biochemical modifications through rapid elucidation of an entire genome. Epigenomics studies factors affecting gene expression. Transcriptomics studies the detection and quantification of RNA molecules. Metabolomics captures comprehensive profiling of metabolite concentration in biological systems to investigate the chemical processes involved in metabolism. Proteomics analyze all expressed proteins in biological systems and their function. These disciplines’ interaction leads to a phenotype change defined as any observable characteristic

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  Fig. 2. PRISMA flowchart and upset plot of included studies.(a) PRISMA Flowchart illustrating the selection process. (* Note: Six studies included multiple approaches).(b) Upset plot summarizing shared OMICs approaches within the included studies. Overlapping OMICs approaches are indicated by intersections in the dot-and-line chart. The upper bar chart illustrates the number of studies per set intersection and the lower left bar chart shows the number of studies addressing each approach

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  Fig. 3. Forest plots of mean differences and confidence intervals for inflammation biomarkers pre- and post-surgery. Analysis was performed at several postoperative time points using Random effects model of mean differences to assess the continuous data and statistical heterogeneity