Circulating inflammatory markers are associated with magnetic resonance imaging-visible perivascular spaces but not directly with white matter hyperintensities

Abstract

Background and purpose: White matter hyperintensities (WMH) and perivascular spaces (PVS) are features of small vessel disease, found jointly on MRI of older people. Inflammation is a prominent pathological feature of small vessel disease. We examined the association between inflammation, PVS, and WMH in the Lothian Birth Cohort 1936 (N=634).

Methods: We measured plasma fibrinogen, C-reactive protein, and interleukin-6 and rated PVS in 3 brain regions. We measured WMH volumetrically and visually using the Fazekas scale. We derived latent variables for PVS, WMH, and Inflammation from measured PVS, WMH, and inflammation markers and modelled associations using structural equation modelling.

Results: After accounting for age, sex, stroke, and vascular risk factors, PVS were significantly associated with WMH (β=0.47; P<0.0001); Inflammation was weakly but significantly associated with PVS (β=0.12; P=0.048), but not with WMH (β=0.02; P=NS).

Conclusions: Circulating inflammatory markers are weakly associated with MR-visible PVS, but not directly with WMH. Longitudinal studies should examine whether visible PVS predate WMH progression and whether inflammation modulators can prevent small vessel disease.

Keywords: aging; inflammation; leukoaraiosis; leukoencephalopathies; magnetic resonance imaging.

Figure 1

SEM of the association between measures of PVS and WMH. Model fit: Root Mean Square Error Approximation (RMSEA)=0.044, Tucker-Lewis Index (TLI)=0.952, Comparative Fit Index (CFI)=0.968 and Incremental Fit index (IFI)=0.968. A model is said to give a good fit if RMSEA < 0.06, TLI > 0.90, CFI >0.90 and IFI >0.90. Note. ‘PVS’=latent variable derived from measures of PVS, ‘WMH’=latent variable derived from measures of WMH. Models included covariates that were significantly associated with measures of WMH or PVS. BG=basal ganglia PVS, HIP=hippocampal PVS, CS=centrum semiovale PVS, high BP=hypertension, WMH v=%WMH in ICV, Faz=Fazekas, Peri=Perivascular. Shape representation: Rectangular boxes=measured observations, ellipses=latent variables, single-headed arrows=hypothesised causal pathways, and double headed arrows=correlations, dashed arrows=non-significant associations and the solid arrows=significant associations at p<0.05, and numbers adjacent to arrows are beta-weights. The numbers on the arrows pointing from the latent to the measured variables represent the strength of the association between the measured and latent variables, +/− 1 indicate the strongest association. Thick arrows pointing to the measured variables mean that that error term was accounted for in the modelling and the numbers adjacent represent the r².

Figure 2

SEM of the association between markers of Inflammation, and PVS.RMSEA=0.003, TLI=1, CFI=1 and IFI=1. Abbreviations: See Figure 1.

Figure 3

SEM of the association between inflammation and WMH load. RMSEA=0.024, TLI=0.987, CFI=0.991 and IFI=0.991. Abbreviations: See Figure 1.