Estimation of blood-based biomarkers of glial activation related to neuroinflammation

Fumihiko Yasuno; Atsushi Watanabe; Yasuyuki Kimura; Yumeka Yamauchi; Aya Ogata; Hiroshi Ikenuma; Junichiro Abe; Hiroyuki Minami; Takashi Nihashi; Kastunori Yokoi; Saori Hattori; Nobuyoshi Shimoda; Kensaku Kasuga; Takeshi Ikeuchi; Akinori Takeda; Takashi Sakurai; Kengo Ito; Takashi Kato

doi:10.1016/j.bbih.2022.100549

Estimation of blood-based biomarkers of glial activation related to neuroinflammation

Brain Behav Immun Health. 2022 Nov 5:26:100549. doi: 10.1016/j.bbih.2022.100549. eCollection 2022 Dec.

Authors

Fumihiko Yasuno^{1

2}, Atsushi Watanabe³, Yasuyuki Kimura^{1

2}, Yumeka Yamauchi³, Aya Ogata^{2

4}, Hiroshi Ikenuma², Junichiro Abe², Hiroyuki Minami¹, Takashi Nihashi¹, Kastunori Yokoi¹, Saori Hattori², Nobuyoshi Shimoda⁵, Kensaku Kasuga⁶, Takeshi Ikeuchi⁶, Akinori Takeda¹, Takashi Sakurai¹, Kengo Ito^{1

2}, Takashi Kato^{1

2}

Affiliations

¹ National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, Japan.
² Department of Clinical and Experimental Neuroimaging, Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Japan.
³ Equipment Management Division, Center for Core Facility Administration, National Center for Geriatrics and Gerontology, Obu, Japan.
⁴ Department of Pharmacy, Faculty of Pharmacy, Gifu University of Medical Science, Kani, Japan.
⁵ Molecular Analysis Division, Center for Core Facility Administration, National Center for Geriatrics and Gerontology, Obu, Japan.
⁶ Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan.

Abstract

Background: Neuroinflammation is a well-known feature of Alzheimer's disease (AD), and a blood-based test for estimating the levels of neuroinflammation would be expected. In this study, we examined and validated a model using blood-based biomarkers to predict the level of glial activation due to neuroinflammation, as estimated by ¹¹C-DPA-713 positron emission tomography (PET) imaging.

Methods: We included 15 patients with AD and 10 cognitively normal (CN) subjects. Stepwise backward deletion multiple regression analysis was used to determine the predictors of the TSPO-binding potential (BP_ND) estimated by PET imaging. The independent variables were age, sex, diagnosis, apolipoprotein E4 positivity, body mass index and the serum concentration of blood-based biomarkers, including monocyte chemotactic protein 1 (MCP-1), fractalkine, chitinase 3-like protein-1 (CHI3L1), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), and clusterin.

Results: Sex, diagnosis, and serum concentrations of MCP1 and sTREM2 were determined as predictors of TSPO-BP_ND in the Braak1-3 area. The serum concentrations of MCP1 and sTREM2 correlated positively with TSPO-BP_ND. In a leave one out (LOO) cross-validation (CV) analysis, the model gave a LOO CV R² of 0.424, which indicated that this model can account for approximately 42.4% of the variance of brain TSPO-BP_ND.

Conclusions: We found that the model including serum MCP-1 and sTREM2 concentration and covariates of sex and diagnosis was the best for predicting brain TSPO-BP_ND. The detection of neuroinflammation in AD patients by blood-based biomarkers should be a sensitive and useful tool for making an early diagnosis and monitoring disease progression and treatment effectiveness.

Keywords: Alzheimer’s disease (AD); Blood-based biomarkers; Monocyte chemotactic protein 1 (MCP-1); Neuroinflammation; Positron emission tomography (PET); Soluble triggering receptor expressed on myeloid cells 2 (sTREM2).