Association of peripheral inflammatory markers with connectivity in large-scale functional brain networks of non-demented older adults

Abstract

Background: Systemic inflammation has emerged as a risk factor for cognitive decline and Alzheimer's disease, but inflammation's effect on distributed brain networks is unclear. We examined the relationship between peripheral inflammatory markers and subsequent functional connectivity within five large-scale cognitive networks and evaluated the modifying role of cortical amyloid and APOE ε4 status.

Methods: Blood levels of soluble tumor necrosis factor-alpha receptor-1 and interleukin 6 were assessed in 176 participants (at baseline mean age: 65 (SD 9) years; 63% women; 85% cognitively normal, 15% mild cognitive impairment (MCI)) and were combined to derive an Inflammatory Index. Approximately six years later, participants underwent resting-state functional magnetic resonance imaging to quantify functional connectivity; a subset of 137 participants also underwent ¹¹C Pittsburgh compound-B (PiB) PET imaging to assess cortical amyloid burden.

Results: Using linear regression models adjusted for demographic characteristics and cardiovascular risk factors, a higher Inflammatory Index was associated with lower connectivity within the Default Mode (β = -0.013; 95% CI: -0.023, -0.003) and the Dorsal Attention Networks (β = -0.017; 95% CI: -0.028, -0.006). The strength of these associations did not vary by amyloid status (positive/negative). However, there was a significant interaction between Inflammatory Index and APOE ε4 status, whereby ε4-positive participants with a higher Inflammatory Index demonstrated lower connectivity. Inflammatory Index was unrelated to connectivity within other large-scale cognitive networks (Control, Limbic, and Salience/Ventral Attention networks).

Conclusion: Peripheral pro-inflammatory signaling in older adults without dementia, especially among APOE ε4-positive individuals, is associated with altered connectivity within two large-scale cognitive networks.

Keywords: Alzheimer’s disease; Default mode network; Dorsal attention network; Functional connectivity; Inflammation; Interleukin 6; Resting-state functional magnetic resonance imaging; Tumor necrosis factor.

Figure 1.. BIOCARD study design and timeline

^a Inflammatory biomarkers were measured primarily (83%) from blood collected in 2009 or 2010; 15% of inflammatory markers were measured from blood collected in 2011; 2% of inflammatory markers were measured at a later date. Abbreviations: rs-fMRI, resting state functional magnetic resonance imaging; PET, positron emission tomography; PiB, ¹¹C Pittsburgh compound-B

Figure 2.. Neuroanatomical representation of cognitive and sensory-motor resting state networks.

Using resting state functional magnetic resonance imaging (fMRI), we derived seven resting state networks from 114 parcellated brain regions based on methods published by Yeo et al., 2011.

Figure 3.. The association between Inflammatory Index quartiles and estimated intrinsic network connectivity

Using participants with the lowest level (1^st quartile) of the Inflammatory Index as the reference group, intrinsic connectivity within each cognitive network was estimated for each Inflammatory Index quartile using fully adjusted linear regression models (N=176). Intrinsic connectivity estimates and standard errors are displayed for each functional network. Intrinsic connectivity values were standardized to facilitate comparability and interpretability. P-trend values for Inflammation Index quartiles are P=0.013 and P=0.006 for Default Mode Network and Dorsal Attention Network, respectively. *P<.05