Blood inflammation relates to neuroinflammation and survival in frontotemporal lobar degeneration

Abstract

Neuroinflammation is an important pathogenic mechanism in many neurodegenerative diseases, including those caused by frontotemporal lobar degeneration. Post-mortem and in vivo imaging studies have shown brain inflammation early in these conditions, proportional to symptom severity and rate of progression. However, evidence for corresponding blood markers of inflammation and their relationships to central inflammation and clinical outcome are limited. There is a pressing need for such scalable, accessible and mechanistically relevant blood markers because these will reduce the time, risk and costs of experimental medicine trials. We therefore assessed inflammatory patterns of serum cytokines from 214 patients with clinical syndromes associated with frontotemporal lobar degeneration in comparison to healthy controls, including their correlation with brain regional microglial activation and disease progression. Serum assays used the MesoScale Discovery V-Plex-Human Cytokine 36 plex panel plus five additional cytokine assays. A subgroup of patients underwent 11C-PK11195 mitochondrial translocator protein PET imaging, as an index of microglial activation. A principal component analysis was used to reduce the dimensionality of cytokine data, excluding cytokines that were undetectable in >50% of participants. Frequentist and Bayesian analyses were performed on the principal components to compare each patient cohort with controls and test for associations with central inflammation, neurodegeneration-related plasma markers and survival. The first component identified by the principal component analysis (explaining 21.5% variance) was strongly loaded by pro-inflammatory cytokines, including TNF-α, TNF-R1, M-CSF, IL-17A, IL-12, IP-10 and IL-6. Individual scores of the component showed significant differences between each patient cohort and controls. The degree to which a patient expressed this peripheral inflammatory profile at baseline was correlated negatively with survival (higher inflammation, shorter survival), even when correcting for baseline clinical severity. Higher pro-inflammatory profile scores were associated with higher microglial activation in frontal and brainstem regions, as quantified with 11C-PK11195 mitochondrial translocator protein PET. A permutation-based canonical correlation analysis confirmed the association between the same cytokine-derived pattern and central inflammation across brain regions in a fully data-based manner. This data-driven approach identified a pro-inflammatory profile across the frontotemporal lobar degeneration clinical spectrum, which is associated with central neuroinflammation and worse clinical outcome. Blood-based markers of inflammation could increase the scalability and access to neuroinflammatory assessment of people with dementia, to facilitate clinical trials and experimental medicine studies.

Keywords: PET; blood markers; frontotemporal lobar degeneration; inflammation; survival.

Figure 1

Dissimilarity between groups across all cytokines. Darker colours and larger values indicate greater distance between groups, whereas lighter colours indicate relative similarity. bvFTD = behavioural variant of frontotemporal dementia; CBS = corticobasal syndrome; HC = healthy controls; NFPPA = non-fluent primary progressive aphasia; PSP = progressive supranuclear palsy; SVPPA = semantic variant of primary progressive aphasia.

Figure 2

Cytokine-derived principal components (PC) and group comparisons. (A) Contribution of each cytokine to Component 1 and Component 2; colours represent the strength and direction of the associations. (B) Group comparisons assessed by Kruskal–Wallis one-way ANOVA and Dunn’s post hoc tests (P-values: ***0.001, **0.01, *0.05). BF10 = Bayes factor in favour of the alternative hypothesis and against the null; bvFTD = behavioural variant of frontotemporal dementia; CBS = corticobasal syndrome; HC = healthy controls; NFPPA = non-fluent primary progressive aphasia; PSP = progressive supranuclear palsy; SVPPA = semantic variant of primary progressive aphasia.

Figure 3

Kaplan–Meir survival curve of loadings on Component 1. Patients were separated into two groups based on their loading onto Component 1, with high loadings being greater than or equal to the median (≥−0.180) and low loadings being lower than the median (<−0.180).

Figure 4

Associations between peripheral and central inflammation. (A) Correlations between cytokine-derived Component 1 individual scores and ¹¹C-PK11195 BPND in left frontal lobe and brainstem, which were identified as significantly associated with Component 1. (B) Positive correlation coefficients (Spearman’s ρ) from explorative regional analyses between cytokine-derived Component 1 individual scores and regional ¹¹C-PK11195 binding potentials across the whole brain. A = anterior; L = left; P = posterior; R = right.

Figure 5

Comfirmatory canonical correlation analysis (CCA) on cytokines and TSPO PET regional values. The bar graph shows contribution loadings for each variable to the first CCA component, which combines serum cytokines (A) and ¹¹C-PK11195 PET BPND regional values (B). Panel C shows the positive correlation (Spearman’s ρ) between cytokine-derived (y) and PET-derived (x) CCA individual scores. BS = brainstem; Cereb = cerebellum; Cing = cingulate; Ins = insula; L/R Oc = left/right occipital; L/R Pa = left/right parietal; Temp = temporal; Ventric = ventricles. See Supplementary Table 3 for a full list of loadings.