We See Four Seasons, But Our Body Only “Sees” Two
- The relationship between biological processes and the seasons is not well-understood.
- Usually, seasonal patterns are identified using calendar dates.
- Researchers used deep longitudinal multiomics profiling to identify biological seasonal patterns on diverse molecular data.
- The study includes 105 individuals over the course of 4 years.
- Multiomics is a biological analysis approach that uses different data which include the genome, proteome, transcriptome, epigenome, metabolome, and microbiome.
- With multiomics, scientists can analyze complex biological data to find novel associations between biological entities, pinpoint relevant biomarkers and build elaborate markers of disease and physiology.
- Researchers report more than 1000 seasonal variations in omics analytes and clinical measures.
- Analyte is a chemical substance that is the subject of chemical analysis.
- The different molecules group into two major seasonal patterns.
- The two seasonal patterns correlate with peaks in late spring and late fall/early winter in California.
- The two patterns are enriched for molecules involved in human biological processes such as inflammation, immunity, cardiovascular health, as well as neurological and psychiatric conditions.
- Researchers also identify molecules and microbes that demonstrate different seasonal patterns in insulin sensitive and insulin resistant individuals.
- The results suggest important implications in healthcare.
- This study highlights the value of considering seasonality when assessing population wide health risk and management.
Sources:
Sailani, M.R., Metwally, A.A., Zhou, W. et al. Deep longitudinal multiomics profiling reveals two biological seasonal patterns in California. Nat Commun 11, 4933 (2020). https://doi.org/10.1038/s41467-020-18758-1
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0857-9
https://doi.org/10.1016%2Fj.tibtech.2016.04.004
https://doi.org/10.1038%2Fnmicrobiol.2016.101
