Autotaxin is Related to Metabolic Dysfunction and Predicts Alzheimer’s Disease Outcomes

Article type: Research Article

Authors: McLimans, Kelsey E.^{a; 1; 3} | Willette, Auriel A.^{a; b; c; d; 1; 3; *} | for the Alzheimer’s Disease Neuroimaging Initiative²

Affiliations: [a] Department of Food Science and Human Nutrition, Iowa State University, Ames, IA, USA | [b] Department of Psychology, Iowa State University, Ames, IA, USA | [c] Department of Neurology, University of Iowa, Iowa City, IA, USA | [d] Aging Mind and Brain Initiative, University of Iowa, Iowa City, IA, USA

Correspondence: [*] Correspondence to: Auriel A. Willette, 224A MacKay Hall, Ames, IA 50011, USA. Tel.: +1 515 294 3110; Fax: +1 515 294 6193; E-mail: awillett@iastate.edu.

Note: [1] These authors contributed equally to this work.

Note: [2] Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://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. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

Note: [3] Statistical analysis conducted by Kelsey McLimans and Dr. Auriel Willette, Iowa State University.

Abstract: Background: Obesity and insulin resistance are associated with neuropathology and cognitive decline in Alzheimer’s disease (AD). Objective: Ecto-nucleotide pyrophosphatase/phosphodiesterase 2, also called autotaxin, is produced by beige adipose tissue, regulates metabolism, and is higher in AD prefrontal cortex (PFC). Autotaxin may be a novel biomarker of dysmetabolism and AD. Methods: We studied Alzheimer’s Disease Neuroimaging Initiative 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 autotaxin was associated with higher relative risk for MCI or AD diagnosis, compared to the CN group. Linear mixed model analyses were used to regress autotaxin against MRI, FDG-PET, and cognitive outcomes. Spearman correlations were used to associate autotaxin and CSF biomarkers due to non-normality. FreeSurfer 4.3 derived mean cortical thickness in medial temporal lobe and prefrontal regions of interest. Results: Autotaxin levels were significantly higher in MCI and AD. Each point increase in log-based autotaxin corresponded to a 3.5 to 5 times higher likelihood of having MCI and AD, respectively. Higher autotaxin in AD predicted hypometabolism in the medial temporal lobe [R2 = 0.343, p < 0.001] and PFC [R2 = 0.294, p < 0.001], and worse performance on executive function and memory factors. Autotaxin was associated with less cortical thickness in PFC areas like orbitofrontal cortex [R2 = 0.272, p < 0.001], as well as levels of total tau, p-tau181, and total tau/Aβ1–42. Conclusions: These results are comparable to previous reports using insulin resistance. CSF autotaxin may be a useful dysmetabolism biomarker for examining AD outcomes and risk.

Keywords: Diabetes mellitus, fluorodeoxyglucose F18, insulin resistance, mild cognitive impairment, MRI, positron emission tomography

DOI: 10.3233/JAD-160891

Journal: Journal of Alzheimer's Disease, vol. 56, no. 1, pp. 403-413, 2017