Neurometabolic timecourse of healthy aging

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2022-12, Vol.264, p.119740-119740, Article 119740
• Main Authors: Gong, Tao, Hui, Steve C.N., Zöllner, Helge J., Britton, Mark, Song, Yulu, Chen, Yufan, Gudmundson, Aaron T., Hupfeld, Kathleen E., Davies-Jenkins, Christopher W., Murali-Manohar, Saipavitra, Porges, Eric C., Oeltzschner, Georg, Chen, Weibo, Wang, Guangbin, Edden, Richard A.E.
• Format: Article
• Language: English
• Subjects: Adult; Age; Aging; Algorithms; Alzheimer's disease; Aspartic Acid; Choline - metabolism; Cortex (cingulate); Cross-Sectional Studies; Female; Gyrus Cinguli - metabolism; healthy aging; Homeostasis; Humans; Localization; Macromolecules; Magnetic Resonance Imaging; Magnetic resonance spectroscopy; Magnetic Resonance Spectroscopy - methods; Male; Metabolism; Metabolites; N-Acetylaspartylglutamic acid; neurometabolite; Neurosciences; PRESS; Regression analysis; Sex; Spectrum analysis; Statistical analysis
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2022.119740

•A large structured cross-sectional cohort of neurometabolic aging dataset is presented;•Significant age correlations were observed for tCho, tCr, mI, and sI in CSO and for NAAG, tCho, tCr, and Gln in PCC;•No age correlations were found for tNAA, NAA, Glx, Glu, GSH, PE, Lac, or Asp in either region. The neurometabolic timecourse of healthy aging is not well-established, in part due to diversity of quantification methodology. In this study, a large structured cross-sectional cohort of male and female subjects throughout adulthood was recruited to investigate neurometabolic changes as a function of age, using consensus-recommended magnetic resonance spectroscopy quantification methods. 102 healthy volunteers, with approximately equal numbers of male and female participants in each decade of age from the 20s, 30s, 40s, 50s, and 60s, were recruited with IRB approval. MR spectroscopic data were acquired on a 3T MRI scanner. Metabolite spectra were acquired using PRESS localization (TE=30 ms; 96 transients) in the centrum semiovale (CSO) and posterior cingulate cortex (PCC). Water-suppressed spectra were modeled using the Osprey algorithm, employing a basis set of 18 simulated metabolite basis functions and a cohort-mean measured macromolecular spectrum. Pearson correlations were conducted to assess relationships between metabolite concentrations and age for each voxel; Spearman correlations were conducted where metabolite distributions were non-normal. Paired t-tests were run to determine whether metabolite concentrations differed between the PCC and CSO. Finally, robust linear regressions were conducted to assess both age and sex as predictors of metabolite concentrations in the PCC and CSO and separately, to assess age, signal-noise ratio, and full width half maximum (FWHM) linewidth as predictors of metabolite concentrations. Data from four voxels were excluded (2 ethanol; 2 unacceptably large lipid signal). Statistically-significant age*metabolite Pearson correlations were observed for tCho (r(98)=0.33, p