Skeletal muscle proteomes reveal downregulation of mitochondrial proteins in transition from prediabetes into type 2 diabetes

Öhman, Tiina; Teppo, Jaakko; Datta, Neeta; Mäkinen, Selina; Varjosalo, Markku; Koistinen, Heikki A.

doi:10.1016/j.isci.2021.102712

Cited by 23 publications

(17 citation statements)

References 62 publications

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“…Overall, the proteome coverage of tissues was larger than earlier studies, while it overlapped with more than 72% of the proteomes of other studies ( Figure 1 B; Table S1 D). 18 , 19 , 20 , 21 , 22 , 23 One sample and more than 41% of the proteins were excluded from further analysis after a thorough quality-control process ( Figures S1 A–S1E; Table S1 E). Next, we selected as confounding factors clinical and technical variables with median explained variance of proteomics data larger than 1% ( Table S1 F).…”

Section: Resultsmentioning

confidence: 99%

Organ-specific metabolic pathways distinguish prediabetes, type 2 diabetes, and normal tissues

Diamanti

Cavalli²,

Pereira³

et al. 2022

Cell Reports Medicine

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Section: Resultsmentioning

confidence: 99%

Organ-specific metabolic pathways distinguish prediabetes, type 2 diabetes, and normal tissues

Diamanti

Cavalli²,

Pereira³

et al. 2022

Cell Reports Medicine

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“…Muscle samples were obtained from the vastus lateralis muscle for mass spectrometry analysis. Under multi-linear regression, the proteome analysis designated 200 proteins for glucose tolerance status ( Öhman et al, 2021 ), including mitochondrial energy metabolism proteins of isocitrate dehydrogenase [NAD] subunit beta, mitochondrial (IDH3B), NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 10, mitochondrial (NDUFA10), and ATP synthase subunit an (MT-ATP6), which were decreased by worsening of the glucose tolerance status and independent of the subjects’ age. Of these decreased proteins, the study also found NADH dehydrogenase [ubiquinone] 1 beta subcomplex subunit 3 (NDUFB3) and NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 2 (NDUFA2) to be increased with physical activity, whose implication highlights the importance of early intervention.…”

Section: Early Detection Of Mets: From “Omics” To Clinical “Big Data”...mentioning

confidence: 99%

“Big Data” Approaches for Prevention of the Metabolic Syndrome

et al. 2022

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Metabolic syndrome (MetS) is characterized by the concurrence of multiple metabolic disorders resulting in the increased risk of a variety of diseases related to disrupted metabolism homeostasis. The prevalence of MetS has reached a pandemic level worldwide. In recent years, extensive amount of data have been generated throughout the research targeted or related to the condition with techniques including high-throughput screening and artificial intelligence, and with these “big data”, the prevention of MetS could be pushed to an earlier stage with different data source, data mining tools and analytic tools at different levels. In this review we briefly summarize the recent advances in the study of “big data” applications in the three-level disease prevention for MetS, and illustrate how these technologies could contribute tobetter preventive strategies.

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“…In diabetes, mitochondria displayed a downregulation of OXPHOS genes [16] as well as a reduction in OXPHOS proteins in skeletal muscle [65]. Here, the focus was to examine the expression of enzymes involved in the TCA cycle.…”

Section: Plos Onementioning

confidence: 99%

High glucose-induced inhibition of osteoblast like MC3T3-E1 differentiation promotes mitochondrial perturbations

Medeiros

Wallace

2022

PLoS ONE

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Diabetes mellitus is a metabolic disorder that causes health concerns worldwide. Patients with diabetes exhibit multisystemic symptoms, including loss of bone quality over time. The progressive deterioration of bone promotes failure to withstand damage and increases the risk of fractures. Much of the molecular and metabolic mechanism(s) in diabetic bone remains unclear. In vitro studies suggest that hyperglycemia inhibits mineralization, affecting bone formation and function. In this study, inhibition of osteoblast differentiation was induced using hyperglycemia to assess whether high glucose promotes mitochondrial impairment along with altered bone matrix formation. It was hypothesized that bone energy metabolism would be altered in these cells as calcium deposition, a key phase for bone function, is suppressed. Early passages of osteoblast like MC3T3-E1 cells were differentiated under normal and high glucose conditions. To investigate osteoblast differentiation, we quantified calcium accumulation by alizarin red staining and analyzed immunoblots of key proteins. To assess mitochondrial function, we quantified mitochondrial DNA (mtDNA), detected expression and function of key proteins from the Tricarboxylic (TCA) cycle, measured mitochondrial respiration, and fuel oxidation of alternative nutrients. Results confirmed previous work showing that mineralization was inhibited and AKT expression was reduced in high glucose-treated bone cells. Unexpectedly, high glucose-treated osteoblast cells utilize both mitochondrial respiration and glycolysis to maintain energy demands with partial help of fatty acid for reliance of baseline bioenergetics. These metabolic shifts suggest that hyperglycemia maintain bone metabolic needs in an early differentiated state concurrent to the inhibition in bone matrix formation.

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Skeletal muscle proteomes reveal downregulation of mitochondrial proteins in transition from prediabetes into type 2 diabetes

Cited by 23 publications

References 62 publications

Organ-specific metabolic pathways distinguish prediabetes, type 2 diabetes, and normal tissues

Organ-specific metabolic pathways distinguish prediabetes, type 2 diabetes, and normal tissues

“Big Data” Approaches for Prevention of the Metabolic Syndrome

High glucose-induced inhibition of osteoblast like MC3T3-E1 differentiation promotes mitochondrial perturbations

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