Global Metabolic Shifts in Age and Alzheimer’s Disease Mouse Brains Pivot at NAD+/NADH Redox Sites

Abstract

Age and Alzheimer's disease (AD) share some common features such as cognitive impairments, memory loss, metabolic disturbances, bioenergetic deficits, and inflammation. Yet little is known on how systematic shifts in metabolic networks depend on age and AD. In this work, we investigated the global metabolomic alterations in non-transgenic (NTg) and triple-transgenic (3xTg-AD) mouse brain hippocampus as a function of age by using untargeted Ultrahigh Performance Liquid Chromatography-tandem Mass Spectroscopy (UPLC-MS/MS). We observed common metabolic patterns with aging in both NTg and 3xTg-AD brains involved in energy-generating pathways, fatty acids oxidation, glutamate, and sphingolipid metabolism. We found age-related downregulation of metabolites from reactions in glycolysis that consumed ATP and in the TCA cycle, especially at NAD + /NADH-dependent redox sites, where age-and AD-associated limitations in the free NADH may alter reactions. Conversely, metabolites increased in glycolytic reactions in which ATP is produced. With age, inputs to the TCA cycle were increased including fatty acid ␤-oxidation and glutamine. Overall age-and AD-related changes were > 2-fold when comparing the declines of upstream metabolites of NAD + /NADH-dependent reactions to the increases of downstream metabolites (p = 10 −5 , n = 8 redox reactions). Inflammatory metabolites such as ceramides and sphingosine-1phosphate also increased with age. Age-related decreases in glutamate, GABA, and sphingolipid were seen which worsened with AD genetic load in 3xTg-AD brains, possibly contributing to synaptic, learning-and memory-related deficits. The data support the novel hypothesis that age-and AD-associated metabolic shifts respond to NAD(P) + /NAD(P)H redox-dependent reactions, which may contribute to decreased energetic capacity.

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

“…We detected increased Ins (β=0.363), Glc (β=0.324), Lac (β=0.355), and NAAG (β=0.329) with age, as well as decreased GSH (β=-0.335). Age-related increases in Ins and decreased GSH are generally in good agreement with previous studies (Harris et al 2014;Zhang et al 2009;Gruber et al 2008;Paban, Fauvelle, and Alescio-Lautier 2010;Emir et al 2011), while reports of changes in Glc, Lac, and NAAG concentrations have been significantly more mixed (Duarte, Do, and Gruetter 2014;Dong and Brewer 2019;Harris et al 2014;Paban, Fauvelle, and Alescio-Lautier 2010;Miccheli et al 2003;Małgorzata Marjańska et al 2017). Despite differences between studies, the neurochemical changes that we report are consistent with the known occurrence of Glc hypometabolism and mitochondrial dysfunction with age, resulting in a shift towards anaerobic energy metabolism, decreased antioxidant capacity, and an increased inflammatory response (Camandola and Mattson 2017;Yin et al 2016;Miccheli et al 2003;Godbout and Johnson 2009).…”

“…All of these metabolites feed into or are downstream products of the TCA cycle; a transaminase reaction in neuronal mitochondria converts Glu and oxaloacetate into Asp and alpha-ketoglutarate, a TCA-cycle intermediate, while aspartate is used for NAA synthesis. As such, changes in these metabolites are typically interpreted as altered TCA cycle activity and therefore impaired mitochondrial bioenergetics (Dong and Brewer 2019;Yin et al 2016;Benarroch 2008). Our findings of unaltered tCr, NAA, Glu, and Gln with age requires further investigation, though an alternative explanation that we will discuss in the following section is the frequent study of single sex-cohorts whereas our study examined both males and females.…”

“…Deficits in cognitive function with age are associated with impaired cerebral glucose metabolism and energy balance, with further exacerbation seen in neurodegenerative disorders (Yin et al 2016;Ravera et al 2019;Miccheli et al 2003). Specifically, aging induces a shift from aerobic to anaerobic energy metabolism, due in part to decreased neuronal glucose uptake and mitochondrial energy-transducing capacity, and resulting in increased oxidant production, decreased tricarboxylic acid cycle (TCA) activity, and compromised electron transport and oxidative phosphorylation activity (Yin et al 2016;Dong and Brewer 2019;Miccheli et al 2003). These altered metabolic pathways are observable using MRS, as many of the compounds that comprise the NMRvisible neurochemical profile are heavily implicated in energy metabolism.…”

“…The glycolytic pathway produces two pyruvate molecules, which then participate in either a) aerobic metabolism via oxidation of pyruvate to acetyl-CoA for entry into the TCA cycle and oxidative phosphorylation within the mitochondria, or b) anaerobic metabolism via reduction of pyruvate to Lac. With age, the pool of nicotinamide adenine dinucleotide (NAD and NAD+) available for oxidative reactions decreases and Glc metabolism shifts from aerobic to anaerobic (Yin et al 2016;Camandola and Mattson 2017;Dong and Brewer 2019). This shift results in less pyruvate being routed towards the TCA cycle, and more towards reduction into Lac via lactate dehydrogenase (LDH), particularly because LDH activity also increases with age as a result of oxidative stress (Ravera et al 2019;Dong and Brewer 2019).…”

“…With age, the pool of nicotinamide adenine dinucleotide (NAD and NAD+) available for oxidative reactions decreases and Glc metabolism shifts from aerobic to anaerobic (Yin et al 2016;Camandola and Mattson 2017;Dong and Brewer 2019). This shift results in less pyruvate being routed towards the TCA cycle, and more towards reduction into Lac via lactate dehydrogenase (LDH), particularly because LDH activity also increases with age as a result of oxidative stress (Ravera et al 2019;Dong and Brewer 2019). Increased pyruvate reduction to Lac ensures the cytoplasmic pool of NAD+ is being regenerated, which is necessary for maintaining a high glycolytic rate to produce ATP (Camandola and Mattson 2017;McKenna et al 2012).…”