Novel CSF Biomarker of Metabolic Dysfunction Predicts AD‐like Associations across the Alzheimer's Spectrum

Abstract

Obesity and insulin resistance(IR) are associated with brain atrophy and cognitive decline, particularly in Alzheimer's disease (AD). IR is correlated with temporal and frontal amyloid deposition and brain atrophy in late middle‐aged participants at risk for AD, as well as less glucose metabolism in cognitively normal elders and AD participants. Because insulin‐degrading enzyme complicates the measurement of insulin levels in cerebrospinal fluid (CSF), an alternative biomarker for metabolic dysregulation in CSF should be used to draw conclusions between central hyper insulinemia and associations with brain atrophy and hypometabolism. Ecto‐nucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2), also known as autotaxin, is studied in tumor cell mobility and is produced by beige adipose tissue. ENPP2 regulates energy metabolism, and is higher in AD prefrontal cortex (PFC). Additionally, ENPP2 stimulates the formation of lysophosphatidic acid, which promotes the generation of tissue fibrosis in vivo and in vitro. We studied Alzheimer's Disease Neuroimaging Initiative(ADNI) participants who were cognitively normal (CN; n=86) or had Mild Cognitive impairment (MCI; n=135) or AD (n=66). Statistical analyses were conducted using SPSS software. Multinomial regression analyses tested if higher ENPP2 was associated with higher relative risk ratios for MCI or AD diagnosis, relative to the CN reference group. Mixed model analyses were used to regress ENPP2 against metabolic, MRI, FDG‐PET and cognitive outcomes. Then on‐parametric Spearman's statistic was used to correlate ENPP2 and CSF biomarker values. T1‐weighted MRI images were preprocessed using FreeSurfer 4.3, and cortical thickness was examined in8 bilateral regions of interest. CSF ENPP2 levels strongly corresponded with CSF insulin‐like growth factor binding protein 2, an established biomarker of glucoregulatory function, and systemic fasting glucose. ENPP2 levels were higher in MCI and AD, and each point increase in log‐based ENPP2 values corresponded to a 3.5 to 5 times increase in the odds of having some degree of clinically relevant memory impairment. Higher ENPP2 predicted thinner PFC cortical thickness in most regions of interest in AD such as medialorbitofrontal cortex, and pars orbital is in MCI. In addition, less bilateral prefrontal cortex glucose metabolism was seen in AD. ENPP2 was also positively correlated with levels of total tau, p‐Tau181, total tau/Aβ1‐42, as well as pTau‐181/Aβ1‐42 to a marginal degree. This pattern suggests that CSF ENPP2 predicts AD neuropathology in a manner similar to dysmetabolism. Future studies should examine the potential benefit of decreasing ENPP2 levels in individuals with MCI or AD.Support or Funding InformationThis study was funded by Iowa State University and NIH K99 AG047282. Neither funding source had any involvement in the report. 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.