Interbatch Reliability of Blood-Based Cytokine and Chemokine Measurements in Community-Dwelling Older Adults: A Cross-Sectional Study

Abstract

Abstract Blood-based inflammatory markers hold considerable promise for diagnosis and prognostication of age-related neurodegenerative disease, though a paucity of research has empirically tested how reliably they can be measured across different experimental runs (“batches”). We quantified the interbatch reliability of 13 cytokines and chemokines in a cross-sectional study of 92 community-dwelling older adults (mean age = 74; 48% female). Plasma aliquots from the same blood draw were parallelly processed in 2 separate batches using the same analytic platform and procedures (high-performance electrochemiluminescence by Meso Scale Discovery). Interbatch correlations (Pearson’s r) ranged from small and nonsignificant (r = .13 for macrophage inflammatory protein-1 alpha [MIP-1α]) to very large (r > .90 for interferon gamma [IFNγ], interleukin-10 [IL-10], interferon gamma-induced protein 10 [IP-10], MIP-1β, thymus and activation-regulated chemokine [TARC]) with most markers falling somewhere in between (.67 ≤ r ≤ .90 for IL-6, tumor necrosis factor alpha [TNF-α], Eotaxin, Eotaxin-3, monocyte chemoattractant protein-1 [MCP-1], MCP-4, macrophage-derived chemokine [MDC]). All markers, except for IL-6 and MCP-4, showed significant differences in absolute values between batches, with discrepancies ranging in effect size (Cohen’s d) from small to moderate (0.2 ≤ |d| ≤ 0.5 for IL-10, IP-10, MDC) to large or very large (0.68 ≤ |d| ≤ 1.5 for IFNγ, TNF-α, Eotaxin, Eotaxin-3, MCP-1, MIP-1α, MIP-1β, TARC). Relatively consistent associations with external variables of interest (age, sex, systolic blood pressure, body mass index, cognition) were observed across batches. Taken together, our results suggest heterogeneity in measurement reliability of blood-based cytokines and chemokines, with some analytes outperforming others. Future work is needed to evaluate the generalizability of these findings while identifying potential sources of batch effect measurement error.