Metabolic Communication and Healthy Aging: Where Should We Focus Our Energy?

Smith, Hannah J.; Sharma, Aradhana; Mair, William

doi:10.1016/j.devcel.2020.06.011

Cited by 56 publications

(46 citation statements)

References 177 publications

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“…Notably, the use of alternative fuel sources such as fatty acids and ketones has been linked to the pro-longevity intervention calorie restriction (46). Cana suppressed hepatic TORC1 signaling, while increasing AMPK activity in this tissue; both effects are associated with life span extension in mice and other organisms (47). Cana treatment also increased serum levels of FGF21, a peptide hormone that induces a shift from carbohydrate to lipid metabolism; FGF21 extends life span in mice when overexpressed (48).…”

Section: Discussionmentioning

confidence: 99%

Canagliflozin extends life span in genetically heterogeneous male but not female mice

et al. 2020

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Section: Discussionmentioning

confidence: 99%

Canagliflozin extends life span in genetically heterogeneous male but not female mice

et al. 2020

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“…Specifically, some anti‐aging interventions may need to be tissue‐specific to safely promote health span extension. Indeed, work in animal models has shown that anti‐aging interventions can mediate significantly disparate effects when applied in different tissues (Smith et al, 2020). However, it is also possible that a small number of global interventions may be capable of safely increasing human health span.…”

Section: Discussionmentioning

confidence: 99%

Modeling the human aging transcriptome across tissues, health status, and sex

Shokhirev

Johnson²

2020

Aging Cell

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Aging in humans is an incredibly complex biological process that leads to increased susceptibility to various diseases. Understanding which genes are associated with healthy aging can provide valuable insights into aging mechanisms and possible avenues for therapeutics to prolong healthy life. However, modeling this complex biological process requires an enormous collection of high‐quality data along with cutting‐edge computational methods. Here, we have compiled a large meta‐analysis of gene expression data from RNA‐Seq experiments available from the Sequence Read Archive. We began by reprocessing more than 6000 raw samples—including mapping, filtering, normalization, and batch correction—to generate 3060 high‐quality samples spanning a large age range and multiple different tissues. We then used standard differential expression analyses and machine learning approaches to model and predict aging across the dataset, achieving an R2 value of 0.96 and a root‐mean‐square error of 3.22 years. These models allow us to explore aging across health status, sex, and tissue and provide novel insights into possible aging processes. We also explore how preprocessing parameters affect predictions and highlight the reproducibility limits of these machine learning models. Finally, we develop an online tool for predicting the ages of human transcriptomic samples given raw gene expression counts. Together, this study provides valuable resources and insights into the transcriptomics of human aging.

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“…Another relevant gene to consider is MTOR, which encodes Mechanistic Target of Rapomycin, a protein belonging to a family of phosphatidylinositol kinase-related kinases which mediate cellular responses to stresses such as DNA damage and nutrient deprivation. This gene is a central regulator of metabolic homeostasis and is associated with lifespan in many species [43,44]. MTOR is a component of two distinct complexes of which mTORC1 controls protein synthesis, cell growth and proliferation.…”

Section: Stress and Dna Damagementioning

confidence: 99%

Age Related Changes in the Circulating Leukocyte Transcriptome in Dairy Cows

Buggiotti

Cheng

Salavati

et al. 2020

Preprint

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Background: Previous studies of ageing have identified many pathways which are consistently altered in humans and model organisms. Dairy cows are often culled at quite young ages due to an inability to cope adequately with metabolic and infectious diseases, resulting in reduced milk production and infertility. Improved longevity is therefore a desirable trait which would benefit both farmers and their cows. This study analysed the transcriptome derived from RNA-seq data of leukocytes obtained from Holstein cows in early lactation with respect to lactation number. Results: Samples were divided into three age groups for analysis: i) primiparous (PP, n = 53), ii) multiparous in lactations 2-3 (MP 2-3, n = 121), and iii) MP in lactations 4-7 (MP>3, n = 55). Leukocyte expression was compared between PP vs MP>3 cows with MP 2-3 as background using DESeq2 followed by weighted gene co-expression network analysis (WGCNA). Seven modules were significantly correlated (r ≥ 0.25) to the trait age. Genes from the modules which were more highly expressed in either the PP or MP>3 cows were pooled, and the gene lists subjected to David functional annotation cluster analysis. The top three clusters from modules more highly expressed in the PP cows all involved regulation of gene transcription, particularly zinc fingers. Another cluster included genes encoding enzymes in the mitochondrial beta-oxidation pathway. Top clusters up-regulated in MP>3 cows included the terms Glycolysis/Gluconeogenesis, C-type lectin, and Immunity. Differentially expressed candidate genes for ageing previously identified in the human blood transcriptome up-regulated in PP cows were mainly associated with T-cell function (CCR7, CD27, IL7R, CAMK4, CD28), mitochondrial ribosomal proteins (MRPS27, MRPS9, MRPS31), and DNA replication and repair (WRN). Those up-regulated in MP>3 cows encoded immune defence proteins (LYZ, CTSZ, SREBF1, GRN, ANXA5, ADARB1). Conclusions: Genes and pathways associated with age in cows were identified for the first time to date, and we found that many were comparable to those known to be associated with ageing in humans and model organisms. We also detected changes in energy utilization and immune responses in leukocytes with age.

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Metabolic Communication and Healthy Aging: Where Should We Focus Our Energy?

Cited by 56 publications

References 177 publications

Canagliflozin extends life span in genetically heterogeneous male but not female mice

Canagliflozin extends life span in genetically heterogeneous male but not female mice

Modeling the human aging transcriptome across tissues, health status, and sex

Age Related Changes in the Circulating Leukocyte Transcriptome in Dairy Cows

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