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Glucose metabolism mainly reflects local atrophy and tau pathology at symptomatic stages of Alzheimer’s disease
Author(s) -
Strom Amelia,
Iaccarino Leonardo,
Edwards Lauren,
LesmanSegev Orit H.,
SoleimaniMeigooni David N.,
Jagust William J.,
Miller Bruce L.,
Rabinovici Gil D.,
Joie Renaud La
Publication year - 2020
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.043968
Subject(s) - white matter , posterior cingulate , atrophy , temporal lobe , dementia , psychology , pittsburgh compound b , pathology , standardized uptake value , precuneus , nuclear medicine , medicine , neuroscience , cortex (anatomy) , magnetic resonance imaging , positron emission tomography , disease , radiology , cognition , epilepsy
Background We assessed the relative contributions of four potential mechanisms associated with [18F]‐Fluorodeoxyglucose (FDG)‐PET hypometabolism in the posterior cingulate cortex (PCC) and inferior parietal (IP) lobe, two primary regions of hypometabolism in AD: 1) local (amyloid and tau) pathology and atrophy, 2) pathology in functionally connected regions, 3) deafferentation from the degenerating medial temporal lobe (MTL), and 4) vascular injury in the white matter (Figure 1). Method Eighty‐five patients with MCI or AD dementia underwent MRI and PET with FDG for glucose metabolism, [11C]‐Pittsburgh Compound B (PIB) for amyloid, and [18F]‐Flortaucipir (FTP) for tau within one year (Table 1). SUVR were calculated using tracer‐specific reference regions: pons for FDG, cerebellar cortex for PIB, and inferior cerebellar cortex for FTP. ROIs and volume of white matter hyperintensities (WMH) were defined in native space using FreeSurfer. Regions with high or low connectivity to PCC/IP were defined based on task‐free fMRI data from cognitively normal participants from neurosynth.org (Figure 2). Imaging variables were transformed into age‐adjusted z‐scores using demographic‐matched modality‐specific control groups (Table 1). Multiple regression analyses were run to identify variables associated with FDG‐SUVR, using a composite disease severity score combining Mini‐Mental State Examination and Clinical Dementia Rating scores as a covariate. Result Local gray matter volume (GMV) and FTP‐SUVR, but not PIB‐SUVR, were independently associated with FDG‐SUVR in PCC (R 2 =.603, β GMV =0.353, β FTP =‐0.374) and IP (R 2 =.702, β GMV =0.419, β FTP =‐0.361) in a model that included disease severity (Table 2). Models including PIB/FTP in connected regions did not outperform models with disease severity and local GMV/FTP alone. Results were similar when including measures of pathology in non‐connected regions. Similarly, models including MTL volume did not outperform models with disease severity and local GMV/FTP alone. Volume of WMH was weakly associated with FDG‐SUVR in PCC but not IP. Conclusion Hypometabolism reflected local atrophy and tau pathology. A weak association between WMH volume and PCC hypometabolism was seen, suggesting that white matter damage may also be a driver of hypometabolism. Our data did not support hypotheses of a detrimental effect of pathology in connected regions or MTL volume in the symptomatic stage of AD.