Neuronal Pentraxin 2 Predicts Medial Temporal Atrophy and Memory Decline across the Alzheimer's Disease Spectrum

PURPOSE Chronic neuro‐inflammation is an important mechanism underlying normal aging and Alzheimer's disease (AD) that is thought to potentiate medial temporal lobe (MTL) atrophy and memory decline. Currently, there are not enough prognostic biomarkers that can track the development and progression of normal aging versus AD, as well as differing effects on the brain. Our study examined which pro‐ or anti‐inflammatory cerebrospinal fluid (CSF) biomarkers best predicted AD neuropathology over 24 months. METHODS Baseline mass spectrometry data from two hundred and eighty‐five adults was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Our focus was on examining biomarkers directly associated with inflammatory processes. For our study, we utilized T1‐weighted medial temporal gray matter volumes at baseline and months 6, 12, and 24 after baseline. Statistical analyses were conducted using SPSS 23.0 software. We used linear mixed models as well as least significant differences (LSD) post‐hoc tests to analyze how variables differed by baseline diagnosis (normal aging, pre‐AD, AD) or pre‐AD patients that did or did not convert to AD. We used stepwise regression analyses to analyze which inflammatory biomarkers best predicted atrophy and memory decline over 24 months. We specifically focused on CSF levels of Neuronal Pentraxin 2 (NPTX2) and Chitinase‐3‐like‐protein‐1 (C3LP1), as they are the inflammatory biomarkers that significantly predicted MTL atrophy and memory decline. NPTX2 is a biomarker of synaptic plasticity. C3LP1 is a biomarker of microglial activation and chronic neuro‐inflammation. We also analyzed relative risk ratios for diagnosis with NPTX2 and C3LP1 with multinomial logistic regression analyses. Preliminary results for memory indicate that, regardless of baseline diagnosis, higher NPTX2 levels strongly predict higher memory scores by month 24 (Figure 1). RESULTS NPTX2 and C3LP1, respectively beneficial and adverse biomarkers of synaptic plasticity and microglial activation, loaded significantly. By month 24, higher baseline NPTX2 corresponded to less MTL atrophy [R 2 = .287] and less memory decline [R 2 = .560]. Conversely, higher C3LP1 modestly predicted more MTL atrophy [R 2 =.083]. CONCLUSIONS Our study suggests that NPTX2 is a promising biomarker for predicting longitudinal changes in medial temporal volume, especially memory performance across the AD spectrum. Baseline NPTX2 performs better than C3LP1 in predicting MTL atrophy and memory decline over time. C3LP1 was a comparatively modest predictor of medial temporal atrophy and memory decline. For future directions, studies should investigate if clinical trials using anti‐inflammatory drugs/nutritional therapy increase or inhibit NPTX2 and/or C3LP1. Support or Funding Information This study was funded by Iowa State University and NIH K99 AG047282. Data collection and sharing for this project were funded by the ADNI (National Institutes of Health Grant U01‐AG‐024904) and Department of Defense ADNI (award number W81XWH‐12‐2‐0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the Alzheimer's Association and the Alzheimer's Drug Discovery Foundation. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private‐sector contributions are facilitated by the Foundation for the National Institutes of Health ( www.fnih.org ). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. The data used in the preparation of this article were obtained from the ADNI database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.

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