What drives insulin resistance? Proteomics reveals key pathways in human skeletal muscle

What drives insulin resistance? Proteomics reveals key pathways in human skeletal muscle

By understanding how fasting muscle proteins signal insulin resistance, this study paves the way for personalized type 2 diabetes treatments based on individual molecular profiles.

​​​​​​​​​​​​​​Study:Personalized molecular signatures of insulin resistance and type 2 diabetes. Photo credit: Mikrogen/Shutterstock.com

A study recently published in the journalcellused state-of-the-art proteomic technology to map the molecular signatures of insulin resistance in patients with diabetes.

Understanding heterogeneity in type 2 diabetes

Type 2 diabetes (T2D) is a rapidly growing metabolic disease characterized worldwide by elevated blood glucose levels during fasting or after food consumption.

T2D is also associated with peripheral insulin resistance, affecting skeletal muscle, liver and adipose tissue. A recent study documented that over 500 million people worldwide are living with T2D.

Genetic and environmental factors influence the heterogeneous pathogenesis of T2D. Subgroup stratification and deep phenotyping enabled the identification of distinct T2D clusters associated with different clinical outcomes.

This finding highlights the need to consider continuous variation in metabolic function when diagnosing and treating patients, as traditional diagnostic categories (such as T2D or normal glucose tolerance) may not fully capture the underlying biology.

Previous studies have shown that skeletal muscle is the primary tissue associated with insulin-stimulated glucose uptake and the major site of insulin resistance in T2D.

Improper insulin-stimulated glucose uptake could be due to a post-receptor defect, such as: It reduces the abundance of signaling molecules or glucose transporters under normal conditions.

A comprehensive system-wide assessment is needed to develop personalized treatments to identify individual insulin signaling differences that contribute to T2D heterogeneity.

Although mass spectrometry-based proteomics has been significantly utilized in cancer research, few proteomic studies in relevant tissues related to insulin resistance have employed this strategy.

Identifying the differences in phenotypic traits, proteome and phosphoprotome signatures, and differential responses to environmental stimuli could help determine changes in causative proteins and pathways. This information could enable the development of personalized medicine for T2D.

About the study

The current study used proteomics technology and deepIn vivoPhenotyping to map diabetogenic traits based on the protein landscape of normal and diabetic individuals.

Both men and women with normal glucose tolerance (NGT) or T2D were recruited. All participants were matched based on age, gender, body mass index (BMI), and smoking status.

Any participant presenting with hypertension (above 160/100 mm Hg), actively using nicotine, diagnosed with cardiovascular disease (CVD), or being treated with warfarin, insulin, corticosteroids, or lithium.

Biopsy samples were obtained from theVastus lateralisMusculature of eligible participants before and during the hyperinsulinemic-uglycemic clamp.

This approach enabled the identification of proteomic and phosphoproteomic molecular signatures within individuals in the fast state and the dynamics of acute insulin signaling.

It is noteworthy that most women in the study were post- or peri-menopausal, which may influence the metabolic comparisons.

The validation cohort was obtained from a previously published study to confirm the reproducibility of the results.

Study design

The discovery cohort included 77 participants and was used to determine the molecular landscape of insulin resistance and type 2 diabetes (T2D). Of these, 34 participants were diagnosed with T2D and 43 individuals had NGT.

A validation cohort was developed to validate the results, consisting of 34 individuals with T2D and 12 matched participants who performed NGT.

All participants in each cohort underwent in vivo glycemic phenotypes that demonstrated elevated fasting glucose, HOMA-IR, and fasting insulin levels in individuals with T2D. Decreased hyperinsulinemic-euglycemic clamp-derived M values ​​demonstrated decreased whole-body insulin sensitivity.

Study results

A significant heterogeneity in insulin sensitivity m-value was observed. Interestingly, some participants with T2D showed higher insulin sensitivity than those with normal glucose tolerance, defying conventional diagnostic methods and supporting a precision medicine approach.

Experimental findings demonstrated the importance of skeletal muscle, particularly phospho-signaling, in whole-body insulin sensitivity.

Variation in the proteomic landscape was observed within diagnostic groups. Stratified proteome-phenotype associations showed that mitochondrial protein content was highly correlated with whole-body insulin sensitivity. However, mitochondrial abundance was not a unique feature of T2D diagnosis, suggesting that it reflects insulin sensitivity rather than disease status.

In addition, the study implicates novel protein degradation and turnover pathways, including the proteasome and ubiquitin-mediated proteolysis, as well as Wnt and adrenergic signaling, which are negatively correlated with insulin sensitivity. This suggests that altered protein turnover may contribute to insulin resistance.

In contrast, higher abundance of glycolytic enzymes was negatively correlated with insulin sensitivity.

The study also highlighted that the ratio of lactate dehydrogenase isoforms (LDHA/LDHB) and the overall stoichiometric relationships between glycolytic and oxidative phosphorylation proteins provided additional insight into metabolic variation via individual protein abundance.

A total of 118 phosphosites were associated with insulin resistance in the fasted state, compared to 66 phosphosites in the insulin-stimulated state alone. Unexpectedly, the study found that phosphoproteome signatures of the fasting state predicted insulin sensitivity even more strongly than those in the insulin-stimulated state.

Enrichment analysis revealed that activation of C-Jun N-terminal kinase (JNK) and P38 family kinases was associated with insulin resistance. Therefore, the JNK-P38 pathway may be a predominant driver of aberrant human skeletal muscle signaling in insulin resistance.

Cellular assays also determined the role of MAP kinase-activated protein kinase 2 (MAPKAPK2) as an upstream regulator of AMPKγ. 3 S65, which is crucial for regulating skeletal muscle insulin sensitivity.

The AMPKγ3-S65 site was found to be unique in humans and highly correlated with insulin resistance, suggesting that it may serve as a human-specific marker or therapeutic target.

The current study demonstrated the complex nature of dysregulated signaling pathways in insulin resistance. Importantly, the researchers found that although there was impairment in certain signaling pathways, other components such as Akt and some of its downstream substrates remained functional even in highly insulin-resistant individuals, demonstrating that insulin resistance does not affect all signaling nodes equally.

The study observed distinct gender differences in the proteome and phosphoprotome. However, the molecular signatures of insulin resistance remained largely similar between men and women.

While men showed higher expression of proteins related to glucose metabolism, women showed higher expression of proteins related to lipid metabolism. However, differences in kinase activity also emerged, such as: B. CAMK2 and mTOR signaling. This highlights the relevance of sex as a biological variable.

Despite these differences, signaling signatures associated with insulin resistance were largely conserved across sexes.

restrictions

The authors note that the study's clinical research design identified associations rather than causal mechanisms. The heterogeneity of type 2 diabetes adds complexity, and the sample may not, however, be complete of all T2D phenotypes or demographic diversity.

The majority of women were post- or peri-menopausal, and potential confounding factors such as diet and medications were not extensively controlled. Further studies, particularly regarding the functional role of the AMPKγ3 -S65 site, are required.

Conclusions

The current study identified the key molecular pathways associated with insulin resistance. The skeletal muscle molecular signature was strongly associated with clinical markers of insulin sensitivity than with fasting glucose control.

The proteome and phosphoprotome signatures of fasting skeletal muscle were identified as significant determinants of whole-body insulin sensitivity.

Selective components of insulin signaling such as Akt substrates remained present even in insulin-resistant patients. This suggests that insulin resistance does not affect all signaling pathways equally.

The study supports the need to move beyond categorical diagnostic groupings and instead focus on individualized, mechanistically informed strategies for T2D care.

Future research needs to consider the heterogeneity in T2D among patients and focus on developing tailored strategies for T2D treatment.

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