Multimodal investigation of neuropathology and neurometabolites in mild cognitive impairment and late-life depression with 11 C-PiB beta-amyloid PET and 7T magnetic resonance spectroscopy.
Christopher W Davies-JenkinsClifford I WorkmanKathleen E HupfeldHelge J ZöllnerJeannie-Marie LeoutsakosMichael A KrautPeter B BarkerGwenn S SmithGeorg OeltzschnerPublished in: Neurobiology of aging (2024)
Positron emission tomography (PET) and magnetic resonance spectroscopy ( 1 H-MRS) are complementary techniques that can be applied to study how proteinopathy and neurometabolism relate to cognitive deficits in preclinical stages of Alzheimer's disease (AD)-mild cognitive impairment (MCI) and late-life depression (LLD). We acquired beta-amyloid (Aβ) PET and 7 T 1 H-MRS measures of GABA, glutamate, glutathione, N-acetylaspartate, N-acetylaspartylglutamate, myo-inositol, choline, and lactate in the anterior and posterior cingulate cortices (ACC, PCC) in 13 MCI and 9 LLD patients, and 13 controls. We used linear regression to examine associations between metabolites, Aβ, and cognitive scores, and whether metabolites and Aβ explained cognitive scores better than Aβ alone. In the ACC, higher Aβ was associated with lower GABA in controls but not MCI or LLD patients, but results depended upon MRS data quality control criteria. Greater variance in California Verbal Learning Test scores was better explained by a model that combined ACC glutamate and Aβ deposition than by models that only included one of these variables. These findings identify preliminary associations between Aβ, neurometabolites, and cognition.
Keyphrases
- mild cognitive impairment
- cognitive decline
- positron emission tomography
- computed tomography
- end stage renal disease
- pet imaging
- chronic kidney disease
- pet ct
- ejection fraction
- depressive symptoms
- newly diagnosed
- quality control
- stem cells
- ms ms
- peritoneal dialysis
- prognostic factors
- machine learning
- patient reported outcomes
- deep learning
- white matter
- electronic health record