By revealing 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. Image credit: Microgen/Shutterstock.com
A recent study, published in the journal Cell, utilized cutting-edge 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 condition worldwide characterized by increased blood glucose levels during fasting or after food consumption.
T2D is also associated with peripheral insulin resistance, which affects the skeletal muscle, liver, and adipose tissue. A recent study documented that over 500 million people live with T2D worldwide.
Genetic and environmental factors influence the heterogeneous pathogenesis of T2D. Subgroup stratification and deep phenotyping enabled the identification of distinct T2D clusters associated with various clinical outcomes.
This finding highlights the need to consider continuous variation in metabolic function when diagnosing and treating patients, as conventional 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 insufficient recruitment of the glucose transporter 4 (GLUT4) to the plasma membrane and post-translational modifications. It reduces the abundance of signaling molecules or glucose transporters in normal conditions.
A comprehensive system-wide evaluation is required to develop personalized treatments to identify individual insulin signaling variations contributing to T2D heterogeneity.
Although mass spectrometry-based proteomics has been significantly exploited in cancer research, few proteomics-related studies in relevant tissues related to insulin resistance have utilized this strategy.
Identifying the differences in phenotypic traits, proteome and phosphoproteome signatures, and varied 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 deep in vivo phenotyping to map diabetogenic traits based on the skeletal muscle protein landscape of normal and diabetic individuals.
Both men and women with normal glucose tolerance (NGT) or T2D were recruited. All participants were paired based on age, sex, body mass index (BMI), and smoking status.
Any participant showing high blood pressure (above 160/100 mm Hg), actively using nicotine, diagnosed with cardiovascular diseases (CVD), or being treated with warfarin, insulin, corticosteroids, or lithium was excluded.
Biopsy samples were obtained from the vastus lateralis muscle of the eligible participants before and during the hyperinsulinemic-euglycemic clamp.
This approach enabled the identification of proteomic and phosphoproteomic molecular signatures within individuals in the fasted state and the dynamics of acute insulin signaling.
It is notable that most women in the study were post- or peri-menopausal, which may affect metabolic comparisons.
The validation cohort was sourced from a previously published study to confirm the reproducibility of results.
Study design
The discovery cohort comprised 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 designed to validate the findings, which consisted of 34 individuals with T2D and 12 matched participants exhibiting NGT.
All participants in each cohort underwent in vivo glycemic phenotyping, which revealed elevated fasting glucose, HOMA-IR, and fasting insulin levels in individuals with T2D. Decreased hyperinsulinemic-euglycemic clamp-derived M-values indicated reduced whole-body insulin sensitivity.
Study findings
A significant heterogeneity in the insulin sensitivity M-value was observed. Interestingly, some participants with T2D exhibited a higher insulin sensitivity than those with normal glucose tolerance, opposing conventional diagnostic methods and supporting a precision medicine approach.
Experimental findings indicated the importance of skeletal muscle, particularly phospho-signaling, in whole-body insulin sensitivity.
A variation in the proteomic landscape within the diagnosis groups was observed. Stratified proteome-phenotype associations revealed mitochondrial protein content strongly correlated with whole-body insulin sensitivity. However, mitochondrial abundance was not a distinct feature of T2D diagnosis, suggesting it reflects insulin sensitivity, not disease status.
Additionally, the study newly implicated protein degradation and turnover pathways, including the proteasome and ubiquitin-mediated proteolysis, as well as Wnt and adrenergic signaling, as being negatively correlated with insulin sensitivity. This suggests altered protein turnover may contribute to insulin resistance.
In contrast, a higher abundance of glycolytic enzymes was negatively correlated with insulin sensitivity.
The study also emphasized that the ratio of lactate dehydrogenase isoforms (LDHA/LDHB) and the overall stoichiometric relationships between glycolytic and oxidative phosphorylation proteins provided added insight into metabolic variation beyond individual protein abundance.
A total of 118 phosphosites were found to be linked with insulin resistance in the fasted state, compared with 66 phosphosites exclusively in the insulin-stimulated state. Unexpectedly, the study found that fasting-state phosphoproteome signatures were even more predictive of insulin sensitivity than those in the insulin-stimulated state.
The enrichment analysis indicated that the activation of c-Jun N-terminal kinase (JNK) and p38 family kinases was linked to insulin resistance. Therefore, the JNK-p38 pathway could 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 AMPKγ3 S65, crucial in regulating skeletal muscle insulin sensitivity.
The AMPKγ3 S65 site was uniquely found in humans and strongly correlated with insulin resistance, suggesting it could 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 severely insulin-resistant individuals, showing that insulin resistance does not uniformly affect all signaling nodes.
The study observed distinct sex-specific differences in the proteome and phosphoproteome. However, molecular signatures of insulin resistance remained broadly similar between men and women.
While males showed higher expression of glucose metabolism-related proteins, females showed higher expression of lipid metabolism-related proteins. However, differences in kinase activity, such as CAMK2 and mTOR signaling, also emerged. This highlights the relevance of sex as a biological variable.
Despite these differences, insulin resistance-related signaling signatures were largely conserved across sexes.
Limitations
The authors note that the study's clinical research design identifies associations rather than causative mechanisms. The heterogeneity of type 2 diabetes adds complexity, and the sample, while larger than most, may not fully represent all T2D phenotypes or demographic diversity.
The majority of women were post- or peri-menopausal, and potential confounders such as diet and medication were not exhaustively controlled. Further research, especially regarding the functional role of the AMPKγ3 S65 site, is required.
Conclusions
The current study identified the crucial molecular pathways associated with insulin resistance. The molecular signature of skeletal muscle was strongly linked with clinical markers of insulin sensitivity rather than fasting glucose control.
The proteome and phosphoproteome signatures of skeletal muscle in the fasting state were identified as significant determinants of whole-body insulin sensitivity.
Selective components of insulin signaling, such as AKT substrates, remained active even in insulin-resistant participants. This suggests that insulin resistance does not affect all signaling pathways equally.
The study supports the need to move beyond categorical diagnostic groupings and to instead focus on individualized, mechanistically informed strategies for T2D care.
Future research must consider the heterogeneity in T2D within patients and focus on developing tailored strategies for T2D treatment.
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