Deep longitudinal multiomics profiling reveals two biological seasonal patterns in California

The influence of seasons on biological processes is poorly understood. In order to identify biological seasonal patterns based on diverse molecular data, rather than calendar dates, we performed a deep longitudinal multiomics profiling of 105 individuals over 4 years. Here, we report more than 1000 seasonal variations in omics analytes and clinical measures. The different molecules group into two major seasonal patterns which 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. Lastly, we identify molecules and microbes that demonstrate different seasonal patterns in insulin sensitive and insulin resistant individuals. The results of our study have important implications in healthcare and highlight the value of considering seasonality when assessing population wide health risk and management. Seasonal patterns of molecular markers in humans have not been extensively studied. Here, the authors combine host components (transcriptome, metabolome, proteome, immunome, clinical lab tests) and microbiome to profile 105 individuals, identifying over 1000 markers in two major seasonal patterns.