Holistic Integration of Omics Tools for Precision Nutrition in Health and Disease.
Omar Ramos-LópezJosé Alfredo Martínez HernándezFermin Ignacio MilagroPublished in: Nutrients (2022)
The combination of multiple omics approaches has emerged as an innovative holistic scope to provide a more comprehensive view of the molecular and physiological events underlying human diseases (including obesity, dyslipidemias, fatty liver, insulin resistance, and inflammation), as well as for elucidating unique and specific metabolic phenotypes. These omics technologies include genomics (polymorphisms and other structural genetic variants), epigenomics (DNA methylation, histone modifications, long non-coding RNA, telomere length), metagenomics (gut microbiota composition, enterotypes), transcriptomics (RNA expression patterns), proteomics (protein quantities), and metabolomics (metabolite profiles), as well as interactions with dietary/nutritional factors. Although more evidence is still necessary, it is expected that the incorporation of integrative omics could be useful not only for risk prediction and early diagnosis but also for guiding tailored dietary treatments and prognosis schemes. Some challenges include ethical and regulatory issues, the lack of robust and reproducible results due to methodological aspects, the high cost of omics methodologies, and high-dimensional data analyses and interpretation. In this review, we provide examples of system biology studies using multi-omics methodologies to unravel novel insights into the mechanisms and pathways connecting the genotype to clinically relevant traits and therapy outcomes for precision nutrition applications in health and disease.
Keyphrases
- single cell
- long non coding rna
- insulin resistance
- poor prognosis
- dna methylation
- healthcare
- public health
- metabolic syndrome
- type diabetes
- mass spectrometry
- endothelial cells
- mental health
- gene expression
- health information
- oxidative stress
- transcription factor
- binding protein
- stem cells
- skeletal muscle
- small molecule
- body mass index
- risk assessment
- social media
- human health
- deep learning
- polycystic ovary syndrome
- fatty acid
- health promotion
- weight gain
- decision making
- glycemic control
- pluripotent stem cells