Altered macromolecular pattern and content in the aging human brain

Abstract

The resonances originating from proteins underlie those of metabolites in brain H nuclear magnetic resonance (NMR) spectra. These resonances have different physical properties from those of metabolites, such as shorter T and T relaxation time constants. The age dependence of the macromolecular pattern and content in the human brain was investigated with a focus on adults over 66 years of age using ultrahigh-field in vivo magnetic resonance spectroscopy. Eighteen young and 23 cognitively normal older adults were studied at 7 T. Metabolite spectra were acquired in the occipital cortex and the posterior cingulate cortex with single-voxel stimulated echo acquisition mode (STEAM) spectroscopy in 14 young and 20 older adults. Macromolecular spectra were acquired in the occipital cortex using an inversion recovery STEAM sequence in four young and three older adults. The macromolecular pattern was apparent over the 0.5-4.5-ppm range in the inversion recovery spectra and the 0.5-2-ppm range in the metabolite spectra. Macromolecular content was quantified from metabolite spectra using LCModel and from inversion recovery spectra using integration. Age-associated differences in the macromolecular pattern were apparent via both types of spectra, with the largest difference observed for the 1.7- and 2-ppm macromolecular resonances. A higher macromolecular content was observed in the older adults for both brain regions. Age-specific macromolecular spectra are needed when comparing metabolite spectra from subjects of differing ages because of age-associated differences in macromolecular pattern. Age-associated pattern and content differences may provide information about the aging process.

Longitudinal Quantification of Metabolites and Macromolecules Reveals Age- and Sex-Related Changes in the Healthy Fischer 344 Rat Brain

“…We report increased MM signal in five of the nine MMs that we quantified. Increased MM signal with age in humans has previously been described (Hofmann et al 2001;Małgorzata Marjańska et al 2018), wherein the greatest MM differences associated with age occurred for the 1.7 and 2.0 ppm MM resonances, and a notable increase was observed at 3.9 ppm. This is in agreement with our results, wherein the largest increase occurred in MM2.02 (β=0.423), followed by MM1.20 (β=0.380), MM1.66 (β=0.357), MM0.89 (β=0.331),and MM3.84 (β=0.290).…”

“…While we noted increases in MM0.89 and MM2.02, we did not see a similar increase at MM2.97 alongside the increase at MM1.66. Marjanksa et al also noted a lack of apparent connectivity for the 1.66 and 2.97 ppm peaks suggesting that perhaps additional macromolecules other than those proposed by Behar et al (Behar et al 1994) are contributing to the increase at 1.66 ppm (Małgorzata Marjańska et al 2018).…”

“…In 1993 and 1994, Behar et al characterized the "broad background" signal of MRS spectra as high molecular weight cytosolic macromolecules between 0.9 and 4.4 ppm and assigned each resonance to protons on specific amino acids (Behar and Ogino 1993;Behar et al 1994). However, due to the fact that the broad peaks are likely representative of overlapping multiplets from various amino acids within different proteins, the exact composition of each MM resonance is not known (Behar and Ogino 1993;Behar et al 1994;Považan et al 2018;Małgorzata Marjańska et al 2018).…”

“…Alternatively, parameterization of the IR-derived MM signal into components has emerged as a viable option for determining the concentration of individual MMs; this process has been successfully applied to MRS and MRSI data obtained in humans from 1.5T and 7T (Seeger et al 2003;Považan et al 2018;Otazo et al 2006), and in rats at 9.4T and 17.2T (Lee and Kim 2017;Lopez-Kolkovsky, Mériaux, and Boumezbeur 2016). Age-related change in MM concentration has been investigated in humans, but either the MM signal was quantified as a single entity (Małgorzata Marjańska et al 2018), or individual MMs were quantified, but not longitudinally (Hofmann et al 2001). To our knowledge, no preclinical studies have characterized longitudinal changes in individual MMs with age.…”

Adaptive Baseline Fitting for1H MR Spectroscopy Analysis

“…More recently, this parameter has been adjusted to encourage flatter baselines [14,15,16], suggesting the default LCModel baseline flexibility may not be optimal in some cases.…”