Intermuscular adipose tissue in Type 2 diabetes mellitus: Non-invasive quantitative imaging and clinical implications

Features, functions, and associated diseases of visceral and ectopic fat: a comprehensive review

Obesity is a complex, chronic, and recurrent disease marked by abnormal or excessive fat accumulation that poses significant health risks. The distribution of body fat, especially ectopic fat deposition, plays a crucial role in the development of chronic metabolic diseases. Under normal conditions, fatty acids are primarily stored in subcutaneous adipose tissue; however, excessive intake can lead to fat accumulation in visceral adipose tissue and ectopic sites, including the pancreas, heart, and muscle. This redistribution is associated with disruptions in energy metabolism, inflammation, and insulin resistance, impairing organ function and raising the risk of cardiovascular disease, diabetes, and fatty liver. This review explores the roles of visceral and ectopic fat in the development of insulin resistance and related diseases such as type 2 diabetes and metabolic dysfunction-associated steatotic liver disease. Specifically, we examine the structure and characteristics of different fat types, their associations with disease, and the underlying pathogenic mechanisms. Future strategies for managing obesity-related diseases may include lifestyle modifications, surgical interventions, and emerging medications that target lipid metabolism and energy regulation, aiming to improve patient outcomes.

Effect of Intravenous Contrast on CT Body Composition Measurements in Patients with Intraductal Papillary Mucinous Neoplasm

BACKGROUND

The effect of differing post-contrast phases on CT body composition measurements is not yet known.

METHODS

A fully automated AI-based body composition analysis using DAFS was performed on a retrospective cohort of 278 subjects undergoing pre-treatment triple-phase CT for pancreatic intraductal papillary mucinous neoplasm. The CT contrast phases included noncontrast (NON), arterial (ART), and venous (VEN) phases. The software selected a single axial CT image at mid-L3 on each phase for body compartment segmentation. The areas (cm2) were calculated for skeletal muscle (SM), intermuscular adipose tissue (IMAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). The mean Hounsfield units of skeletal muscle (SMHU) within the segmented regions were calculated. Bland-Altman and Chi Square analyses were performed.

RESULTS

SM-NON had a lower percentage of bias [LOA] than SM-ART, -0.7 [-7.6, 6.2], and SM-VEN, -0.3 [-7.6, 7.0]; VAT-NON had a higher percentage of bias than ART, 3.4 [-18.2, 25.0], and VEN, 5.8 [-15.0, 26.6]; and this value was lower for SAT-NON than ART, -0.4 [-14.9, 14.2], and VEN, -0.5 [-14.3, 13.4]; and higher for IMAT-NON than ART, 5.9 [-17.9, 29.7], and VEN, 9.5 [-17.0, 36.1]. The bias in SMHU NON [LOA] was lower than that in ART, -3.8 HU [-9.8, 2.1], and VEN, -7.8 HU [-14.8, -0.8].

CONCLUSIONS

IV contrast affects the voxel HU of fat and muscle, impacting CT analysis of body composition. We noted a relatively smaller bias in the SM, VAT, and SAT areas across the contrast phases. However, SMHU and IMAT experienced larger bias. During threshold risk stratification for CT-based measurements of SMHU and IMAT, the IV contrast phase should be taken into consideration.

Computed tomography-based intermuscular adipose tissue analysis and its predicting role in post-kidney transplantation diabetes mellitus

BACKGROUND

While body mass index (BMI) is the most widely used indicator as a measure of obesity factors in post-transplantation diabetes mellitus (PTDM), body composition is a more accurate measure of obesity. This study aims to investigate the effects of Computed tomography (CT)--based morphemic factors on PTDM and establish a prediction model for PTDM after kidney transplantation.

METHODS

The pre-transplant data and glycemic levels of kidney transplant recipients (June 2021 to July 2023) were retrospectively and prospectively collected. Univariate and multivariate analyses were conducted to analyze the relationship between morphemic factors and PTDM at one month, six months, and one year after hospital discharge. Subsequently, a one-year risk prediction model based on morphemic factors was developed.

RESULTS

The study consisted of 131 participants in the one-month group, where Hemoglobin A1c (HbA1c) (p = 0.02) was identified as the risk factor for PTDM. In the six-month group, 129 participants were included, and the intermuscular adipose tissue (IMAT) area (p = 0.02) was identified as the risk factor for PTDM. The one-year group had 128 participants, and the risk factors for PTDM were identified as body mass index (BMI) (p = 0.02), HbA1c (p = 0.01), and IMAT area (p = 0.007). HbA1c (%) and IMAT area were included in the risk prediction Model for PTDM in the one-year group with AUC = 0.716 (95 % CI 0.591-0.841, p = 0.001).

CONCLUSIONS

Compared to BMI and other morphemic factors, this study demonstrated that the IMAT area was the most potential predictor of PTDM.

CLINICAL TRIAL NOTATION

Chictr.org (ChiCTR2300078639).

Impaired skeletal muscle regeneration in diabetes: From cellular and molecular mechanisms to novel treatments

Diabetes represents a major public health concern with a considerable impact on human life and healthcare expenditures. It is now well established that diabetes is characterized by a severe skeletal muscle pathology that limits functional capacity and quality of life. Increasing evidence indicates that diabetes is also one of the most prevalent disorders characterized by impaired skeletal muscle regeneration, yet underlying mechanisms and therapeutic treatments remain poorly established. In this review, we describe the cellular and molecular alterations currently known to occur during skeletal muscle regeneration in people with diabetes and animal models of diabetes, including its associated comorbidities, e.g., obesity, hyperinsulinemia, and insulin resistance. We describe the role of myogenic and non-myogenic cell types on muscle regeneration in conditions with or without diabetes. Therapies for skeletal muscle regeneration and gaps in our knowledge are also discussed, while proposing future directions for the field.

Imaging of Sarcopenia in Type 2 Diabetes Mellitus

Sarcopenia is an age-related condition characterized by the loss of skeletal muscle mass, muscular strength, and muscle function. In older adults, type 2 diabetes mellitus (T2DM) constitutes a significant health burden. Skeletal muscle damage and deterioration have emerged as novel chronic complications in patients with diabetes, often linked to their increased longevity. Diabetic sarcopenia has been associated with increased rates of hospitalization, cardiovascular events, and mortality. Nevertheless, effectively managing metabolic disorders in patients with T2DM through appropriate therapeutic interventions could potentially mitigate the risk of sarcopenia. Utilizing imaging technologies holds substantial clinical significance in the early detection of skeletal muscle mass alterations associated with sarcopenia. Such detection is pivotal for arresting disease progression and preserving patients' quality of life. These imaging modalities offer reproducible and consistent patterns over time, as they all provide varying degrees of quantitative data. This review primarily delves into the application of dual-energy X-ray absorptiometry, computed tomography, magnetic resonance imaging, and ultrasound for both qualitative and quantitative assessments of muscle mass in patients with T2DM. It also juxtaposes the merits and limitations of these four techniques. By understanding the nuances of each method, clinicians can discern how best to apply them in diverse clinical scenarios.

Sarcopenia and type 2 diabetes: Pathophysiology and potential therapeutic lifestyle interventions

AIMS

Sarcopenia generally refers to the age-related reduction in muscle strength, functional ability, and muscle mass. Sarcopenia is a multifactorial condition associated with poor glucose disposal, insulin resistance, and subsequently type 2 diabetes (T2D). The pathophysiological connection between sarcopenia and T2D is complex but likely involves glycemic control, inflammation, oxidative stress, and adiposity.

METHODS AND RESULTS

Resistance exercise and aerobic training are two lifestyle interventions that may improve glycemic control in older adults with T2D and counteract sarcopenia. Further, there is evidence that dietary protein, Omega-3 fatty acids, creatine monohydrate, and Vitamin D hold potential to augment some of these benefits from exercise.

CONCLUSIONS

The purpose of this narrative review is: (1) discuss the pathophysiological link between age-related sarcopenia and T2D, and (2) discuss lifestyle interventions involving physical activity and nutrition that may counteract sarcopenia and T2D.

Association Between Handgrip Strength and Type 2 Diabetes: A Prospective Cohort Study and Systematic Review With Meta-analysis

BACKGROUND

Both absolute (kg) and relative (kg per kg of body weight) handgrip strength (HGS) have been used as indicators of HGS. Multiple studies have explored HGS associations with type 2 diabetes (T2DM); however, prognostic values were inconsistent. We aimed to examine the associations between both absolute and relative HGS and incident T2DM.

METHODS

A total of 12,957 participants aged 40 years and older (mean age 51.0 years, 58.4% men) were followed and enrolled in the Tianjin Chronic Low-grade Systemic Inflammation and Health (TCLSIH) Cohort Study. Cox proportional hazards regression models were used to examine the association of HGS with incident T2DM. Other prospective studies on HGS and risk of T2DM were identified by searching several electronic databases up to November 31, 2021. Meta-analysis was performed by combining the results from the TCLSIH study and previous prospective cohort studies.

RESULTS

From the TCLSIH Cohort study, after adjustment, relative HGS was inversely associated with T2DM (hazard ratio per 0.1 higher relative HGS 0.667, 95% confidence interval [CI] 0.616, 0.722). However, no significant association between absolute HGS and incident T2DM was found. The meta-analyses showed that per 5 kg higher HGS was associated with a 5% (95% CI 2%, 8%) lower risk of T2DM and each 0.1 higher relative HGS was associated with a 22% (95% CI 14%, 29%) lower risk of T2DM.

CONCLUSION

The results from our cohort study and meta-analysis suggest that relative HGS was better than absolute HGS in predicting incident T2DM. Adiposity was an important factor that mediates the association between HGS and T2DM.

Influences of resolvin D1 and D2 on the risk of type 2 diabetes mellitus: a Chinese community-based cohort study

Background

Although cellular and animal studies have reported that resolvin D1 (RvD1) and resolvin D2 (RvD2) are mechanisms involved in the development of type 2 diabetes mellitus (T2DM), the impact of RvD1 and RvD2 on the risk of T2DM at a population level remains unclear.

Methods

We included 2755 non-diabetic adults from a community-based cohort in China and followed them for seven years. Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of RvD1 and RvD2 with T2DM probability. Time-dependent receiver operator characteristics (ROC) curve was used to evaluate the predictive performance of RvD1 and RvD2 for the risk of T2DM based on the Chinese CDC T2DM prediction model (CDRS).

Results

A total of 172 incident T2DM cases were identified. Multivariate-adjusted HRs (95% CI) for T2DM across quartiles of RvD1 levels (Q1, Q2, Q3 and Q4) were 1.00, 1.64 (1.03-2.63), 1.80 (1.13-2.86) and 1.61 (1.01-2.57), respectively. Additionally, body mass index (BMI) showed a significant effect modification in the association of RvD1 with incident T2DM (P _interaction = 0.026). After multivariate adjustment, the HR (95% CI) for T2DM in the fourth compared with the first quartile of RvD2 was 1.94 (95% CI: 1.24-3.03). Time-dependent ROC analysis showed that the area under time-dependent ROC curves of the "CDRS+RvD1+RvD2" model for the 3-, 5- and 7-year risk of T2DM were 0.842, 0.835 and 0.828, respectively.

Conclusions

Higher RvD1 and RvD2 levels are associated with a higher risk of T2DM at the population level.

A nomogram based on radiomics intermuscular adipose analysis to indicate arteriosclerosis in patients with newly diagnosed type 2 diabetes

Objective

Early identifying arteriosclerosis in newly diagnosed type 2 diabetes (T2D) patients could contribute to choosing proper subjects for early prevention. Here, we aimed to investigate whether radiomic intermuscular adipose tissue (IMAT) analysis could be used as a novel marker to indicate arteriosclerosis in newly diagnosed T2D patients.

Methods

A total of 549 patients with newly diagnosed T2D were included in this study. The clinical information of the patients was recorded and the carotid plaque burden was used to indicate arteriosclerosis. Three models were constructed to evaluate the risk of arteriosclerosis: a clinical model, a radiomics model (a model based on IMAT analysis proceeded on chest CT images), and a clinical-radiomics combined model (a model that integrated clinical-radiological features). The performance of the three models were compared using the area under the curve (AUC) and DeLong test. Nomograms were constructed to indicate arteriosclerosis presence and severity. Calibration curves and decision curves were plotted to evaluate the clinical benefit of using the optimal model.

Results

The AUC for indicating arteriosclerosis of the clinical-radiomics combined model was higher than that of the clinical model [0.934 (0.909, 0.959) vs. 0.687 (0.634, 0.730), P < 0.001 in the training set, 0.933 (0.898, 0.969) vs. 0.721 (0.642, 0.799), P < 0.001 in the validation set]. Similar indicative efficacies were found between the clinical-radiomics combined model and radiomics model (P = 0.5694). The AUC for indicating the severity of arteriosclerosis of the combined clinical-radiomics model was higher than that of both the clinical model and radiomics model [0.824 (0.765, 0.882) vs. 0.755 (0.683, 0.826) and 0.734 (0.663, 0.805), P < 0.001 in the training set, 0.717 (0.604, 0.830) vs. 0.620 (0.490, 0.750) and 0.698 (0.582, 0.814), P < 0.001 in the validation set, respectively]. The decision curve showed that the clinical-radiomics combined model and radiomics model indicated a better performance than the clinical model in indicating arteriosclerosis. However, in indicating severe arteriosclerosis, the clinical-radiomics combined model had higher efficacy than the other two models.

Conclusion

Radiomics IMAT analysis could be a novel marker for indicating arteriosclerosis in patients with newly diagnosed T2D. The constructed nomograms provide a quantitative and intuitive way to assess the risk of arteriosclerosis, which may help clinicians comprehensively analyse radiomics characteristics and clinical risk factors more confidently.

Gender-specific data-driven adiposity subtypes using deep-learning-based abdominal CT segmentation

OBJECTIVE

The aim of this study was to quantify abdominal adiposity and generate data-driven adiposity subtypes with different diabetes risks.

METHODS

A total of 3817 participants from the Pinggu Metabolic Disease Study were recruited. A deep-learning-based recognition model on abdominal computed tomography (CT) images (A-CT model) was developed and validated in 100 randomly selected cases. The volumes and proportions of subcutaneous fat, visceral fat, liver fat, and muscle fat were automatically recognized in all cases. K-means clustering was used to identify subgroups using the proportions of the four fat components.

RESULTS

The Dice indices among the measurements assessed by the A-CT model and manual evaluation to detect liver fat, muscle fat, and subcutaneous fat areas were 0.96, 0.95, and 0.92, respectively. Three subtypes were generated separately in men and women: visceral fat dominant type (VFD); subcutaneous fat dominant type (SFD); and intermuscular fat dominant type (MFD). Compared with the SFD group, the MFD group had similar diabetes risk, and the VFD group had a 60% higher diabetes risk when age and BMI were adjusted for in men. The adjusted odds ratio for diabetes was 1.92 (95% CI: 1.32-2.78) in the MFD group and 6.14 (95% CI: 4.18-9.03) in the VFD group in women.

CONCLUSIONS

This study identified gender-specific abdominal adiposity subgroups, which may help clinicians to distinguish diabetes risk quickly and automatically.

The Important Role of Intermuscular Adipose Tissue on Metabolic Changes Interconnecting Obesity, Ageing and Exercise: A Systematic Review

As age increases, adipose tissue infiltrates muscle tissue and leads to sarcopenia. When excessive accumulation of adipose tissue accompanied progressive decrease in lean body mass especially visceral fat, termed as sarcopenic obesity (SO) and related metabolic intermuscular adipose tissue (IMAT) is an ectopic tissue found between muscle groups, and is distinct from subcutaneous adipose tissue. Until now, the association between IMAT and metabolic health was not understood. This study is the first systematic review assessing the association between IMAT and metabolic health. The PubMed, Science Direct and Cochrane databases were searched for studies reporting IMAT and metabolic risk. The descriptions of the extracted data are guided by the Preferred Reporting Items for Systematic Reviews (PRISMA) statement with a Grading of Recommendations Assessment, Development and Evaluation approach. This study is registered at PROSPERO (identifier: CRD42022337518). Six studies were pooled and reviewed using critical appraisal by the Newcastle Ottawa Scale and Centre for Evidence-Based Medicine checklist. Two clinical trials and four observational trials were included. Our results reveal that IMAT is associated with metabolic risk, especially in older adults and patients with obesity. However, in a person with abdominal obesity, VAT has a more significant role in metabolic risk than IMAT. The largest decrease in IMAT was achieved by combining aerobic with resistance training.

The emerging roles and mechanisms of exosomal non-coding RNAs in the mutual regulation between adipose tissue and other related tissues in obesity and metabolic diseases

Exosomes (EXs) are the major types of extracellular vesicles (EVs) of 30-100 nm diameter that can be secreted by most cells to the extracellular environment. EXs transport endogenous cargoes (proteins, lipids, RNAs, etc.) to target cells and thereby triggers the release of these bioactive components, which then play important roles in regulating numerous biological processes under both physiological and pathological conditions. Throughout the studies in recent years, growing evidences have shown that EXs-derived non-coding RNAs (EXs-ncRNAs) are emerging as key players in cell-to-cell communication between adipose tissue and other related tissues in obesity and metabolic diseases. In this review, we will summarize the recent findings about EXs-ncRNAs, especially focus on the following aspects: 1) the biogenesis of EXs and emerging roles of EXs-ncRNAs, 2) the role of EXs-ncRNAs (EXs-miRNAs, EXs-lncRNAs, EXs-circRNAs, etc.) that were secreted by adipose-related tissues in promoting the differentiation of preadipocytes into mature and fully functional adipocytes, and 3) the crosstalk between the adipose tissue derived EXs-ncRNAs and the development of insulin resistance, obesity and various cancers. This review aims to reveal the emerging roles and mechanisms of EXs-ncRNAs in the mutual regulation of adipose tissue and its related tissues in obesity and metabolic diseases, so as to provide references for elucidating the etiology of obesity and related metabolic diseases and screening novel therapeutic targets.