This investigation found significant sociodemographic differences in the molecular precursors for chronic disease in young adults, providing a molecular framework by which health disparities in chronic disease can be effectively tackled earlier in life.
Public health research has shown that there are significant sociodemographic disparities in chronic disease prevalence and outcomes which become increasingly prevalent over the course of our lives, but particularly in mid to late adulthood (Crook and Peters 2008; Cole et al. 2020). The result of these disparities is increased prevalence of disease and worse outcomes for people of color, lower socioeconomic status individuals, as well as various geographical disparities (Crook and Peters 2008). However, chronic diseases develop over the course of many years in part due to the activity of molecular pathways involved in inflammation, metabolism, and immune function. Due to this long developmental period the biological basis of these health disparities may emerge in adolescence or early adulthood. However, there is little known about the sociodemographic disparities in the molecular precursors of chronic disease because population health studies have rarely studied the molecular characteristics of adolescents and young adults. The goal of this research was to determine if there are sociodemographic disparities in the molecular pathways that develop in young adulthood which result in chronic disease. Answering this question could provide an additional framework through which to tackle health disparities in early life by mitigating molecular risk before they develop into chronic disease.
In order to answer this question, the researchers analyzed genome-wide transcriptional profiles from a representative sample of 1,126 young adults. They assessed the profile variation as a function of individual demographic characteristics, sociodemographic conditions, and biobehavioral factors which could be confounded with demographic characteristics in genes involved in inflammation and type I interferon responses. The analysis quantified sociodemographic variation using three analytic approaches which correspond to three levels of biological influence on gene expression. The first level used pre-specified sets of inflammatory and type I interferon genes to identify broad variations in innate immune activity. The second level analyzed empirical differences in the genome-wide transcriptional profiles in terms of the regulation by transcription factors involved in inflammation and type I interferon responses. Finally, the third level of analysis looked at empirical differences in genome-wide transcriptional profiles in terms of their cellular origins, specifically immune cells involved in inflammatory and type I interferon responses.
The first level of analysis identified significant sociodemographic variation in gene expression across the entire set of analyzed transcription profiles. In this level of analysis, the results for each individual gene set separately indicated significant sociodemographic variation. The results for the inflammatory gene set showed up-regulation of expression in females relative to males, and in blacks relative to non-Hispanic whites. The results for the type I interferon gene set showed up-regulation of expression in females relative to males and in blacks relative to non-Hispanic whites that was even more significant than the results for inflammatory gene expression. The major difference they found at this level of analysis was that the type I interferon gene set varied most strongly due to individual demographic characteristics, whereas inflammatory gene expression varied more due to biobehavioral factors. At this level of analysis, the results showed no difference due to sociodemographic factors such as family poverty level or residential region
For the second and third level of analysis the results again showed significant demographic disparities in every category of analysis. For the second level of analysis this meant that there was significant variation in the binding of each transcription factor involved in inflammation, type I interferon, and neuroendocrine activity. These results were particularly strong for immunoregulatory transcription factors, as well as, cAMP response element-binding proteins. In terms of the level three analysis there was significant variation in the activity of each cell type that was analyzed, particularly in the myeloid lineage immune cells involved in inflammatory and type I interferon immune responses. In addition to this both level two and three analyses revealed significant regional disparities, as well as substantial family poverty-related differences in transcription factor response and cell activity.
This study reveals that there are significant sociodemographic disparities in the expression of inflammatory and type I interferon genes that emerge in young adulthood, and therefore were precursors for the numerous disparities we see in chronic diseases. While the expression of inflammatory and type I interferon genes varied significantly as a result of all of the sociodemographic factors examined, the magnitude of these effects varied greatly across factors. Racial and Ethnic identity and BMI are more associated with differentially expressed genes and statistically significant transcript associations than the other sociodemographic factors analyzed, which is important when addressing racial disparities in chronic disease risk. The results found in this study provide a framework by which health disparities can be reduced by mitigating molecular risk gradients before they develop into diagnosable chronic diseases. This study highlights the importance of initiating social, behavioral, and policy interventions early in life in order to effectively reduce disparities in Chronic Disease risk and outcomes. The next steps based on this research should be to do an analysis of the transcription profiles of younger age groups in order to identify the developmental periods where the sociodemographic differences in gene expression first appear in order to implement policy and social change which can most effectively address this problem.
Cole, S. W., M.J. Shanahan, L. Gaydosh, K.M. Harris, 2020. Population-based RNA profiling in Add Health finds social disparities in inflammatory and antiviral gene regulation to emerge by young adulthood. PNAS 117(9): 4601-4608. https://www.pnas.org/content/117/9/4601
Crook, E.D., Peters M, 2008. Health disparities in chronic disease: where the money is. Am J Med Sci 335(4): 266-270. https://www.amjmedsci.org/article/S0002-9629(15)32323-5/fulltext