We implemented a construct operationalizing distinct components of generalized inflammation using data collected in an epidemiological survey of a representative older adult population. Our construct was grounded in biology theorizing that inflammatory regulation is maintained via an up- and down-regulation feedback loop in a specific cytokine sequence. In latent factor analyses, observed interrelationships among seven serum-based inflammatory biomediators were highly consistent with the biological predictions. PCA of the biomediator values yielded an index approximating latent up-regulation, which was independently associated with worsened mobility functioning and frailty risk. Patterns of association between mobility and the individual cytokines were strongest for the biomediators involved in up-regulation. Association of mobility with the up-regulation index was stronger than, persisted independently of, and accounted for association with each individual biomediator. Two additional indices were not strongly associated with mobility; however, one approximating latent down-regulation was intriguingly associated with the number of positive frailty criteria and the individual criteria involving strength and weight loss. These findings support that systemic inflammation is a construct with internal biological validity and relevant to the process that leads to mobility disability and frailty in older persons. They also suggest that specific aspects of the inflammatory process can be measured through profiles of inflammatory biomarkers.
Previous publications have applied factor or principal components analysis to multiple inflammatory markers. Many have employed sample sizes in the tens,39–41
involved improved risk stratification together with noninflammatory factors in clinically diseased cohorts,42,43
or explored the value of expanding the metabolic syndrome.44,45
We are aware of three papers, besides ours, that have analyzed multiple cytokines toward improved measurement of inflammation per se
. An exploratory factor analysis among 580 members of the Women's Ischemia Syndrome Evaluation cohort found “proinflammation,” “pro- and antiinflammation,” and “immunosuppressive” factors remarkably similar to our “up-regulation,” “down-regulation,” and “IL-1β/TGF” components.46
Similarly, a principal components analysis of 320 consecutive acute coronary syndrome patients found “systemic inflammation,” “antiinflammation,” and “local inflammation-endothelial function” components.47
That these papers and ours should have suggested three similar dimensions of inflammatory regulation is compelling. In contrast to these investigations, ours was focused on older adults, entailed a much larger sample, and involved a population-based cohort. A very recent paper14
shares these characteristics; it analyzed a somewhat different set of cytokines. Our research has uniquely validated a biologically motivated model of inflammatory regulation, beyond implementing empirical data reduction.
Association between frailty and the inflammation indices was not stronger than with IL-6 alone. One explanation is that IL-6 plays a critical role in the development of frailty. Alternatively, as suggested by , inflammation may participate in the genesis of frailty through multiple mechanisms that cannot be represented by a single index. It should be pointed out that our study is not powered to distinguish specific inflammatory regulation effects on frailty. Fewer than 100 participants were considered frail, and the prevalence of ADL disability was low.
Our analysis has appreciable data missing. The analysis of persons with complete biomediator information preferentially loses older individuals, and complete mobility and frailty analysis, individuals with higher biomarker values. Both lose individuals who may differ from those analyzed in ways the data cannot inform. We stand behind complete-case analysis for the analysis of the inflammatory construct because its findings were not sensitive to age adjustment and most individuals excluded for missing biomediator measures did not have valid measurements on any biomediator. Our analyses of mobility and frailty are valid, assuming that outcomes are missing in ways that may depend on inflammatory or control variable status but not on mobility or frailty given these other characteristics.48
This assumption may not hold. Because inflammation tended to be elevated among those lost from the functioning subsamples, we regard it more likely that our findings have been diluted than that spurious findings have been generated.
We derived inflammation indices via PCA and handled extreme values in biomarker variables via truncation, seeking to employ strategies easily replicable by other investigators. Structural equations analyses would more effectively account for errors in measuring inflammatory dimensions than PCA, thus the simplification to PCA stands to be conservative. Factor and PC analyses were not sensitive to truncation of outlying values versus utilizing raw values. In summary, we do not believe that methodological simplification has qualitatively distorted our findings.
This initial work aimed to create biomarker indices that can capture multiple aspects of inflammation. It indicates that this line of research should be fully pursued. Our finding should be confirmed in a larger population that includes substantial numbers of frail and disabled persons. The best biomediators to be included in global indices should be selected over a larger range of markers. A huge number of proteins could be considered using microarray or multiple beads methods, but this technology still shows low sensitivity and questionable reliability. Thus, short of relevant advancements, we believe the selection of markers should continue to be biologically motivated. Study of the biomediators' utility for longitudinal prediction of frailty outcomes should also be pursued; the InCHIANTI study will provide ideal data to this end when the longitudinal frailty outcomes have been adjudicated. The line of investigation we have pursued is crucial to a better and more specific understanding of the biology that underlies the human inflammatory response and ultimately promises to help identify older persons at high risk for adverse outcomes, identify potential treatments, and, perhaps, test treatment effects.