Inflammatory Proteins are Highly Variable During a Natural Stressor: A Call for Intensive Longitudinal Blood Microsampling

Abstract

Much research investigates how inflammation might play a role in stress-mediated diseases such as heart disease and depression. However, standard longitudinal designs often have measurement lags of months or years between assessments. This status quo is at odds with evidence that inflammatory biology and stress are both highly dynamic and would require much shorter time lags to quantify change as it naturally occurs, with minimal risk of confounding or effects diluting over time. Inspired by the use of intensive longitudinal data collection in psychological research, this study collected high frequency (every 3 days) blood microsamples over 22 days as 86 incoming college students transitioned onto campus (total observations = 622 blood samples). Samples were analyzed for CRP, TNF-, IFN-{gamma}, IL-1{beta}, IL-2, IL-4, IL-6, IL-10, IL-12p70, and IL-17A. Results using both bivariate correlation and intra-class correlation coefficients (which can be used for future power analyses for longitudinal research with these proteins) demonstrate low reliability. Notably, hierarchical linear models demonstrated that, even at this frequency of assessment, most proteins were characterized by less than 6% stable between-person differences. These results provide compelling evidence that investment in intensive longitudinal data collection of immune proteins is critical for understanding how inflammatory biology might function in psychosocial models of risk and resilience.