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Deciphering the decline of metabolic elasticity in aging and obesity.

ABSTRACT: Organisms must adapt to fluctuating nutrient availability to maintain energy homeostasis. Here, we term the capacity for such adaptation and restoration "metabolic elasticity" and model it through ad libitum-fasting-refeeding cycles. Metabolic elasticity is achieved by coordinate versatility in gene expression, which we call "gene elasticity." We have developed the gene elasticity score as a systematic method to quantify the elasticity of the transcriptome across metabolically active tissues in mice and non-human primates. Genes involved in lipid and carbohydrate metabolism show high gene elasticity, and their elasticity declines with age, particularly with PPARγ dysregulation in adipose tissue. Synchronizing PPARγ activity with nutrient conditions through feeding-timed agonism optimizes their metabolic benefits and safety. We further broaden the conceptual scope of metabolic and gene elasticity to dietary challenges, revealing declines in diet-induced obesity similar to those in aging. Altogether, our findings provide a dynamic perspective on the dysmetabolic consequences of aging and obesity.

SUBMITTER: Zhou Q

PROVIDER: S-EPMC10528724 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Deciphering the decline of metabolic elasticity in aging and obesity.

Zhou Qiuzhong Q Yu Lexiang L Cook Joshua R JR Qiang Li L Sun Lei L

Cell metabolism 20230824 9

Organisms must adapt to fluctuating nutrient availability to maintain energy homeostasis. Here, we term the capacity for such adaptation and restoration "metabolic elasticity" and model it through ad libitum-fasting-refeeding cycles. Metabolic elasticity is achieved by coordinate versatility in gene expression, which we call "gene elasticity." We have developed the gene elasticity score as a systematic method to quantify the elasticity of the transcriptome across metabolically active tissues in ...[more]

PMID: 37625407

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Project description:Background/objectivesTo investigate potential mechanisms underlying the well-established relationship of diabetes and obesity with cognitive decline, among older adults participating in a population-based study.Design/settingTen-year population-based cohort study.ParticipantsA total of 478 individuals aged 65 years and older.MeasurementsWe assayed fasting blood for markers of glycemia (glucose and hemoglobin A1c [HbA1c]), insulin resistance (IR) (insulin and homeostatic model assessment of IR), obesity (resistin, adiponectin, and glucagon-like peptide-1), and inflammation (C-reactive protein). We modeled these indices as predictors of the slope of decline in global cognition, adjusting for age, sex, education, APOE*4 genotype, depressive symptoms, waist-hip ratio (WHR), and systolic blood pressure, in multivariable regression analyses of the entire sample and stratified by sex-specific median WHR. We then conducted WHR-stratified machine-learning (Classification and Regression Tree [CART]) analyses of the same variables.ResultsIn multivariable regression analyses, in the entire sample, HbA1c was significantly associated with cognitive decline. After stratifying by median WHR, HbA1c remained associated with cognitive decline in those with higher WHR. No metabolic indices were associated with cognitive decline in those with lower WHR. Cross-validated WHR-stratified CART analyses selected no predictors in participants older than 87 to 88 years. Faster cognitive decline was associated, in lower WHR participants younger than 87 years, with adiponectin of 11 or greater; and in higher WHR participants younger than 88 years, with HbA1c of 6.2% or greater.ConclusionsOur population-based data suggest that, in individuals younger than 88 years with central obesity, even modest degrees of hyperglycemia might independently predispose to faster cognitive decline. In contrast, among those younger than 87 years without central obesity, adiponectin may be a novel independent risk factor for cognitive decline. J Am Geriatr Soc 68:991-998, 2020.

Project description:Alzheimer's disease (AD) is the most common form of dementia. Obesity in middle age increases AD risk and severity, which is alarming given that obesity prevalence peaks at middle age and obesity rates are accelerating worldwide. Midlife, but not late-life obesity increases AD risk, suggesting that this interaction is specific to preclinical AD. AD pathology begins in middle age, with accumulation of amyloid beta (Aβ), hyperphosphorylated tau, metabolic decline, and neuroinflammation occurring decades before cognitive symptoms appear. We used a transcriptomic discovery approach in young adult (6.5 months old) male and female TgF344-AD rats that overexpress mutant human amyloid precursor protein and presenilin-1 and wild-type (WT) controls to determine whether inducing obesity with a high-fat/high-sugar “Western” diet during preclinical AD increases brain metabolic dysfunction in dorsal hippocampus (dHC), a brain region vulnerable to the effects of obesity and early AD. Analyses of dHC gene expression data showed dysregulated mitochondrial and neurotransmission pathways, and up-regulated genes involved in cholesterol synthesis. Western diet amplified the number of genes that were different between AD and WT rats and added pathways involved in noradrenergic signaling, dysregulated inhibition of cholesterol synthesis, and decreased intracellular lipid transporters. Importantly, the Western diet impaired dHC-dependent spatial working memory in AD but not WT rats, confirming that the dietary intervention accelerated cognitive decline. To examine later consequences of early transcriptional dysregulation, we measured dHC monoamine levels in older (13 months old) AD and WT rats of both sexes after long-term chow or Western diet consumption. Norepinephrine (NE) abundance was significantly decreased in AD rats, NE turnover was increased, and the Western diet attenuated the AD-induced increases in turnover. Collectively, these findings indicate obesity during prodromal AD impairs memory, potentiates AD-induced metabolic decline likely leading to an overproduction of cholesterol, and interferes with compensatory increases in NE transmission.

Project description:This study aims to identify the clinical and genetic markers related to the two uncommon nutritional statuses-metabolically unhealthy normal-weight (MUNW) and metabolically healthy overweight/obese (MHOW) individuals in the physically active individuals. Physically active male volunteers (n = 120) were recruited, and plasma samples were analyzed for the clinical parameters. Triglycerides, HDL-Cholesterol, LDL-cholesterol, total cholesterol, C-reactive protein, and insulin resistance were considered as markers of metabolic syndrome. The subjects were classified as 'healthy' (0 metabolic abnormalities) or 'unhealthy' (≥1 metabolic abnormalities) in their respective BMI group with a cut-off at 24.9 kg/m2. Analysis of biochemical variables was done using enzyme linked immunosorbent assay (ELISA) kits with further confirmation using western blot analysis. The microarray was conducted, followed by quantitative real-time PCR to identify and analyze differentially expressed genes (DEGs). The MHOW group constituted 12.6%, while the MUNW group constituted 32.4% of the total study population. Pro-inflammatory markers like interleukin-6, tumor necrosis factor (TNF)-α, and ferritin were increased in metabolically unhealthy groups in comparison to metabolically healthy groups. Gene expression profiling of MUNW and MHOW individuals resulted in differential expression of 7470 and 5864 genes, respectively. The gene ontology (GO) biological pathway analysis showed significant enrichment of the 'JAK/STAT signaling pathway' in MUNW and 'The information-processing pathway at the IFN-β enhancer' pathway in MHOW. The G6PC3 gene has genetically emerged as a new distinct gene showing its involvement in insulin resistance. Biochemical, as well as genetic analysis, revealed that MUNW and MHOW are the transition state between healthy and obese individuals with simply having fewer metabolic abnormalities. Moreover, it is possible that the state of obesity is a biological adaptation to cope up with the unhealthy parameters.

Dataset Information

Deciphering the decline of metabolic elasticity in aging and obesity.

Publications

Deciphering the decline of metabolic elasticity in aging and obesity.

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