Sub-phenotyping Metabolic Disorders Using Body Composition: An Individualized, Nonparametric Approach Utilizing Large Data Sets

Effect of tirzepatide on body fat distribution pattern in people with type 2 diabetes

AIMS

To describe the overall fat distribution patterns independent of body mass index (BMI) in participants with type 2 diabetes (T2D) in the SURPASS-3 MRI substudy by comparison with sex- and BMI-matched virtual control groups (VCGs) derived from the UK Biobank imaging study at baseline and Week 52.

METHODS

For each study participant at baseline and Week 52 (N = 296), a VCG of ≥150 participants with the same sex and similar BMI was identified from the UK Biobank imaging study (N = 40 172). Average visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (aSAT) and liver fat (LF) levels and the observed standard deviations (SDs; standardized normal z-scores: z-VAT, z-aSAT and z-LF) were calculated based on the matched VCGs. Differences in z-scores between baseline and Week 52 were calculated to describe potential shifts in fat distribution pattern independent of weight change.

RESULTS

Baseline fat distribution patterns were similar across pooled tirzepatide (5, 10 and 15 mg) and insulin degludec (IDeg) arms. Compared with matched VCGs, SURPASS-3 participants had higher baseline VAT (mean [SD] z-VAT +0.42 [1.23]; p < 0.001) and LF (z-LF +1.24 [0.92]; p < 0.001) but similar aSAT (z-aSAT -0.13 [1.11]; p = 0.083). Tirzepatide-treated participants had significant decreases in z-VAT (-0.18 [0.58]; p < 0.001) and z-LF (-0.54 [0.84]; p < 0.001) but increased z-aSAT (+0.11 [0.50]; p = 0.012). Participants treated with IDeg had a significant change in z-LF only (-0.46 [0.90]; p = 0.001), while no significant changes were observed for z-VAT (+0.13 [0.52]; p = 0.096) and z-aSAT (+0.09 [0.61]; p = 0.303).

CONCLUSION

In this exploratory analysis, treatment with tirzepatide in people with T2D resulted in a significant reduction of z-VAT and z-LF, while z-aSAT was increased from an initially negative value, suggesting a possible treatment-related shift towards a more balanced fat distribution pattern with prominent VAT and LF loss.

The association between chrononutrition behaviors and muscle health among older adults: The study of muscle, mobility and aging

Emerging studies highlight chrononutrition's impact on body composition through circadian clock entrainment, but its effect on older adults' muscle health remains largely overlooked. To determine the associations between chrononutrition behaviors and muscle health in older adults. Dietary data from 828 older adults (76 ± 5 years) recorded food/beverage amounts and their clock time over the past 24 h. Studied chrononutrition behaviors included: (1) The clock time of the first and last food/beverage intake; (2) Eating window (the time elapsed between the first and last intake); and (3) Eating frequency (Number of self-identified eating events logged with changed meal occasion and clock time). Muscle mass (D3-creatine), leg muscle volume (MRI), grip strength (hand-held dynamometer), and leg power (Keiser) were used as outcomes. We used linear regression to assess the relationships between chrononutrition and muscle health, adjusting for age, sex, race, marital status, education, study site, self-reported health, energy, protein, fiber intake, weight, height, and moderate-to-vigorous physical activity. Average eating window was 11 ± 2 h/day; first and last intake times were at 8:22 and 19:22, respectively. After multivariable adjustment, a longer eating window and a later last intake time were associated with greater muscle mass (β ± SE: 0.18 ± 0.09; 0.27 ± 0.11, respectively, p < 0.05). The longer eating window was also marginally associated with higher leg power (p = 0.058). An earlier intake time was associated with higher grip strength (-0.38 ± 0.15; p = 0.012). Chrononutrition behaviors, including longer eating window, later last intake time, and earlier first intake time were associated with better muscle mass and function in older adults.

Associations between regional adipose tissue distribution and skeletal muscle bioenergetics in older men and women

OBJECTIVE

The aim of this study was to examine associations of ectopic adipose tissue (AT) with skeletal muscle (SM) mitochondrial bioenergetics in older adults.

METHODS

Cross-sectional data from 829 adults ≥70 years of age were used. Abdominal, subcutaneous, and visceral AT and thigh muscle fat infiltration (MFI) were quantified by magnetic resonance imaging. SM mitochondrial energetics were characterized in vivo (31P-magnetic resonance spectroscopy; ATPmax) and ex vivo (high-resolution respirometry maximal oxidative phosphorylation [OXPHOS]). ActivPal was used to measure physical activity ([PA]; step count). Linear regression adjusted for covariates was applied, with sequential adjustment for BMI and PA.

RESULTS

Independent of BMI, total abdominal AT (standardized [Std.] β = -0.21; R2 = 0.09) and visceral AT (Std. β = -0.16; R2 = 0.09) were associated with ATPmax (p < 0.01; n = 770) but not following adjustment for PA (p ≥ 0.05; n = 658). Visceral AT (Std. β = -0.16; R2 = 0.25) and thigh MFI (Std. β = -0.11; R2 = 0.24) were associated with carbohydrate-supported maximal OXPHOS independent of BMI and PA (p < 0.05; n = 609). Total abdominal AT (Std. β = -0.19; R2 = 0.24) and visceral AT (Std. β = -0.17; R2 = 0.24) were associated with fatty acid-supported maximal OXPHOS independent of BMI and PA (p < 0.05; n = 447).

CONCLUSIONS

Skeletal MFI and abdominal visceral, but not subcutaneous, AT are inversely associated with SM mitochondrial bioenergetics in older adults independent of BMI. Associations between ectopic AT and in vivo mitochondrial bioenergetics are attenuated by PA.

Advances in body composition: a 100-year journey

Knowledge of human body composition at the dawn of the twentieth century was based largely on cadaver studies and chemical analyses of isolated organs and tissues. Matters soon changed by the nineteen twenties when the Czech anthropologist Jindřich Matiegka introduced an influential new anthropometric method of fractionating body mass into subcutaneous adipose tissue and other major body components. Today, one century later, investigators can not only quantify every major body component in vivo at the atomic, molecular, cellular, tissue-organ, and whole-body organizational levels, but go far beyond to organ and tissue-specific composition and metabolite estimates. These advances are leading to an improved understanding of adiposity structure-function relations, discovery of new obesity phenotypes, and a mechanistic basis of some weight-related pathophysiological processes and adverse clinical outcomes. What factors over the past one hundred years combined to generate these profound new body composition measurement capabilities in living humans? This perspective tracks the origins of these scientific innovations with the aim of providing insights on current methodology gaps and future research needs.

Body composition and body fat distribution in tissue-specific insulin resistance and in response to a 12-week isocaloric dietary macronutrient intervention

BACKGROUND

Body composition and body fat distribution are important predictors of cardiometabolic diseases. The etiology of cardiometabolic diseases is heterogenous, and partly driven by inter-individual differences in tissue-specific insulin sensitivity.

OBJECTIVES

To investigate (1) the associations between body composition and whole-body, liver and muscle insulin sensitivity, and (2) changes in body composition and insulin sensitivity and their relationship after a 12-week isocaloric diet high in mono-unsaturated fatty acids (HMUFA) or a low-fat, high-protein, high-fiber (LFHP) diet.

METHODS

This subcohort analysis of the PERSON study includes 93 individuals (53% women, BMI 25-40 kg/m2, 40-75 years) who participated in this randomized intervention study. At baseline and after 12 weeks of following the LFHP, or HMUFA diet, we performed a 7-point oral glucose tolerance test to assess whole-body, liver, and muscle insulin sensitivity, and whole-body magnetic resonance imaging to determine body composition and body fat distribution. Both diets are within the guidelines of healthy nutrition.

RESULTS

At baseline, liver fat content was associated with worse liver insulin sensitivity (β [95%CI]; 0.12 [0.01; 0.22]). Only in women, thigh muscle fat content was inversely related to muscle insulin sensitivity (-0.27 [-0.48; -0.05]). Visceral adipose tissue (VAT) was inversely associated with whole-body, liver, and muscle insulin sensitivity. Both diets decreased VAT, abdominal subcutaneous adipose tissue (aSAT), and liver fat, but not whole-body and tissue-specific insulin sensitivity with no differences between diets. Waist circumference, however, decreased more following the LFHP diet as compared to the HMUFA diet (-3.0 vs. -0.5 cm, respectively). After the LFHP but not HMUFA diet, improvements in body composition were positively associated with improvements in whole-body and liver insulin sensitivity.

CONCLUSIONS

Liver and muscle insulin sensitivity are distinctly associated with liver and muscle fat accumulation. Although both LFHP and HMUFA diets improved in body fat, VAT, aSAT, and liver fat, only LFHP-induced improvements in body composition are associated with improved insulin sensitivity.

TRIAL REGISTRATION

NCT03708419 (clinicaltrials.gov).

Skewness in Body fat Distribution Pattern Links to Specific Cardiometabolic Disease Risk Profiles

OBJECTIVE

Fat distribution pattern could help determine cardiometabolic risk profile. This study aimed to evaluate the association of balance/imbalance between visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (aSAT), and liver fat (LF) with incident type 2 diabetes (T2D) and cardiovascular disease (CVD) in the UK Biobank prospective cohort study.

METHODS

Magnetic resonance images of 40 174 participants were analyzed for VAT, aSAT, and LF using AMRA® Researcher. To assess fat distribution patterns independent of body mass index (BMI), fat z-scores (z-VAT, z-aSAT, z-LF) were calculated. Participants without prevalent T2D/CVD (N = 35 138) were partitioned based on balance between (1) z-VAT and z-LF (z-scores = 0 as cut-points for high/low), (2) z-VAT and z-aSAT, and (3) z-LF and z-aSAT. Associations with T2D/CVD were investigated using Cox regression (crude and adjusted for sex, age, BMI, lifestyle, arterial hypertension, statin treatment).

RESULTS

T2D was significantly associated with z-LF (hazard ratio, [95% CI] 1.74 [1.52-1.98], P < .001) and z-VAT (1.70 [1.49-1.95], P < .001). Both remained significant after full adjustment. For z-scores balance, strongest associations with T2D were z-VAT > 0 and z-LF > 0 (4.61 [2.98-7.12]), z-VAT > 0 and z-aSAT < 0 (4.48 [2.85-7.06]), and z-LF > 0 and z-aSAT < 0 (2.69 [1.76-4.12]), all P < .001. CVD was most strongly associated with z-VAT (1.22 [1.16-1.28], P < .001) which remained significant after adjustment for sex, age, BMI, and lifestyle. For z-scores balance, strongest associations with CVD were z-VAT > 0 and z-LF < 0 (1.53 [1.34-1.76], P < .001) and z-VAT > 0 and z-aSAT < 0 (1.54 [1.34-1.76], P < .001). When adjusted for sex, age, and BMI, only z-VAT > 0 and z-LF < 0 remained significant.

CONCLUSION

High VAT in relation to BMI (z-VAT > 0) was consistently linked to both T2D and CVD; z-LF > 0 was linked to T2D only. Skewed fat distribution patterns showed elevated risk for CVD (z-VAT > 0 and z-LF < 0 and z-VAT > 0 and z-aSAT < 0) and T2D (z-VAT > 0 and z-aSAT < 0).

Risk Stratification and Treatment of Obesity for Primary and Secondary Prevention of Cardiovascular Disease

PURPOSE OF REVIEW

In this review, we discuss contemporary and emerging approaches for risk stratification and management of excess adiposity for the primary and secondary prevention of cardiovascular disease.

RECENT FINDINGS

Obesity is simultaneously a pandemic-scale disease and major risk factor for the incidence and progression of a wide range of cardiometabolic conditions, but risk stratification and treatment remain clinically challenging. However, sex-, race-, and ethnicity-sensitive anthropometric measures, body composition-focused imaging, and health burden-centric staging systems have emerged as important facilitators of holistic risk prediction. Further, expanding therapeutic approaches, including comprehensive lifestyle programs, anti-obesity pharmacotherapies, device/endoscopy-based interventions, metabolic surgery, and novel healthcare delivery resources offer new empowerment for cardiovascular risk reduction in individuals with obesity. Personalized risk stratification and weight management are central to reducing the lifetime prevalence and impact of cardiovascular disease. Further evidence informing long-term safety, efficacy, and cost-effectiveness of novel approaches targeting obesity are critically needed.

The association between chrononutrition behaviors and muscle health among older adults: The Study of Muscle, Mobility and Aging (SOMMA)

Background

Emerging studies highlight chrononutrition's impact on body composition through circadian clock entrainment, but its effect on older adults' muscle health remains largely overlooked.

Objective

To determine the associations between chrononutrition behaviors and muscle health in older adults.

Methods

Dietary data from 828 older adults (76±5y) recorded food/beverage amounts and their clock time over the past 24 hours. Studied chrononutrition behaviors included: 1) The clock time of the first and last food/beverage intake; 2) Eating window (the time elapsed between the first and last intake); and 3) Eating frequency (Number of self-identified eating events logged with changed meal occasion and clock time). Muscle mass (D 3 -creatine), leg muscle volume (MRI), grip strength (hand-held dynamometer), and leg power (Keiser) were used as outcomes. We used linear regression to assess the relationships between chrononutrition and muscle health, adjusting for age, sex, race, marital status, education, study site, self-reported health, energy, protein, fiber intake, weight, height, and moderate-to-vigorous physical activity.

Results

Average eating window was 11±2 h/d; first and last intake times were at 8:22 and 19:22, respectively. After multivariable adjustment, a longer eating window and a later last intake time were associated with greater muscle mass (β±SE: 0.18±0.09; 0.27±0.11, respectively, P <0.05). The longer eating window was also marginally associated with higher leg power ( P =0.058). An earlier intake time was associated with higher grip strength (-0.38±0.15; P =0.012).

Conclusions

Chrononutrition behaviors, including longer eating window, later last intake time, and earlier first intake time were associated with better muscle mass and function in older adults.

GRAPHICAL ABSTRACT

Key findings

Chrononutrition behaviors, including longer eating window, later last intake time, and earlier first intake time were associated with better muscle mass and function in older adults.

Associations between regional adipose tissue distribution and skeletal muscle bioenergetics in older men and women

Objective

Examine the association of ectopic adipose tissue (AT) with skeletal muscle (SM) mitochondrial bioenergetics in older adults.

Methods

Cross-sectional data from 829 older adults ≥70 years was used. Total abdominal, subcutaneous, and visceral AT; and thigh muscle fat infiltration (MFI) was quantified by MRI. SM mitochondrial energetics were characterized using in vivo 31 P-MRS (ATP max ) and ex vivo high-resolution respirometry (maximal oxidative phosphorylation (OXPHOS)). ActivPal was used to measure PA (step count). Linear regression models adjusted for covariates were applied, with sequential adjustment for BMI and PA.

Results

Independent of BMI, total abdominal (standardized (Std.) β=-0.21; R 2 =0.09) and visceral AT (Std. β=-0.16; R 2 =0.09) were associated with ATP max ( p <0.01), but not after further adjustment for PA (p≥0.05). Visceral AT (Std. β=-0.16; R 2 =0.25) and thigh MFI (Std. β=-0.11; R 2 =0.24) were negatively associated with carbohydrate-supported maximal OXPHOS independent of BMI and PA ( p <0.05). Total abdominal AT (Std. β=-0.19; R 2 =0.24) and visceral AT (Std. β=-0.17; R 2 =0.24) were associated with fatty acid-supported maximal OXPHOS independent of BMI and PA (p<0.05).

Conclusions

Skeletal MFI and abdominal visceral, but not subcutaneous AT, are inversely associated with SM mitochondrial bioenergetics in older adults independent of BMI. Associations between ectopic AT and in vivo mitochondrial bioenergetics are attenuated by PA.

Deep learning for the prediction of type 2 diabetes mellitus from neck-to-knee Dixon MRI in the UK biobank

Rationale and objectives

We evaluate the automatic identification of type 2 diabetes from neck-to-knee, two-point Dixon MRI scans with 3D convolutional neural networks on a large, population-based dataset. To this end, we assess the best combination of MRI contrasts and stations for diabetes prediction, and the benefit of integrating risk factors.

Materials and methods

Subjects with type 2 diabetes mellitus have been identified in the prospective UK Biobank Imaging study, and a matched control sample has been created to avoid confounding bias. Five-fold cross-validation is used for the evaluation. All scans from the two-point Dixon neck-to-knee sequence have been standardized. A neural network that considers multi-channel MRI input was developed and integrates clinical information in tabular format. An ensemble strategy is used to combine multi-station MRI predictions. A subset with quantitative fat measurements is identified for comparison to prior approaches.

Results

MRI scans from 3406 subjects (mean age, 66.2 years ± 7.1 [standard deviation]; 1128 women) were analyzed with 1703 diabetics. A balanced accuracy of 78.7 %, AUC ROC of 0.872, and an average precision of 0.878 was obtained for the classification of diabetes. The ensemble over multiple Dixon MRI stations yields better performance than selecting the individually best station. Moreover, combining fat and water scans as multi-channel inputs to the networks improves upon just using single contrasts as input. Integrating clinical information about known risk factors of diabetes in the network boosts the performance across all stations and the ensemble. The neural network achieved superior results compared to the prediction based on quantitative MRI measurements.

Conclusions

The developed deep learning model accurately predicted type 2 diabetes from neck-to-knee two-point Dixon MRI scans.

Metabolic phenotyping of BMI to characterize cardiometabolic risk: evidence from large population-based cohorts

Obesity is a risk factor for type 2 diabetes and cardiovascular disease. However, a substantial proportion of patients with these conditions have a seemingly normal body mass index (BMI). Conversely, not all obese individuals present with metabolic disorders giving rise to the concept of "metabolically healthy obese". We use lipidomic-based models for BMI to calculate a metabolic BMI score (mBMI) as a measure of metabolic dysregulation associated with obesity. Using the difference between mBMI and BMI (mBMIΔ), we identify individuals with a similar BMI but differing in their metabolic health and disease risk profiles. Exercise and diet associate with mBMIΔ suggesting the ability to modify mBMI with lifestyle intervention. Our findings show that, the mBMI score captures information on metabolic dysregulation that is independent of the measured BMI and so provides an opportunity to assess metabolic health to identify "at risk" individuals for targeted intervention and monitoring.

Metabolic profiling of MRI-measured liver fat in the UK Biobank

OBJECTIVE

Liver fat associates with obesity-related metabolic disturbances and may precede incident diseases. Metabolomic profiles of liver fat in the UK Biobank were investigated.

METHODS

Regression models assessed the associations between 180 metabolites and proton density liver fat fraction (PDFF) measured 5 years later through magnetic resonance imaging, as the difference (in SD units) of each log metabolite measure with 1-SD higher PDFF among those without chronic disease and not taking statins, and by diabetes and cardiovascular diseases.

RESULTS

After accounting for confounders, multiple metabolites were associated positively with liver fat (p < 0.0001 for 152 traits), particularly extremely large and very large lipoprotein particle concentrations, very low-density lipoprotein triglycerides, small high-density lipoprotein particles, glycoprotein acetyls, monounsaturated and saturated fatty acids, and amino acids. Extremely large and large high-density lipoprotein concentrations had strong inverse associations with liver fat. Associations were broadly comparable among those with versus without vascular metabolic conditions, although negative, rather than positive, associations were observed between intermediate-density and large low-density lipoprotein particles among those with BMI ≥25 kg/m² , diabetes, or cardiovascular diseases. Metabolite principal components showed a 15% significant improvement in risk prediction for PDFF relative to BMI, which was twice as great (but nonsignificant) compared with conventional high-density lipoprotein cholesterol and triglycerides.

CONCLUSIONS

Hazardous metabolomic profiles are associated with ectopic hepatic fat and are relevant to risk of vascular-metabolic disease.

Fat infiltration in the thigh muscles is associated with symptomatic spinal stenosis and reduced physical functioning in adults with achondroplasia

BACKGROUND

Symptomatic spinal stenosis is a prevalent complication in adults with achondroplasia. Increased muscle fat infiltration (MFI) and reduced thigh muscle volumes have also been reported, but the pathophysiology is poorly understood. We explored whether the increased MFI and reduced thigh muscle volumes were associated with the presence of symptomatic spinal stenosis and physical functioning.

METHODS

MFI and thigh muscle volumes were assessed by MRI in 40 adults with achondroplasia, and compared to 80 average-statured controls, matched for BMI, gender, and age. In achondroplasia participants, the six-minute walk-test (6MWT), the 30-s sit-to-stand test (30sSTS), and a questionnaire (the IPAQ) assessed physical functioning.

RESULTS

Symptomatic spinal stenosis was present in 25 of the participants (the stenosis group), while 15 did not have stenosis (the non-stenosis group). In the stenosis group, 84% (21/25) had undergone at least one spinal decompression surgery. The stenosis group had significantly higher MFI than the non-stenosis group, with an age-, gender and BMI-adjusted difference in total MFI of 3.3 percentage points (pp) (95% confidence interval [CI] 0.04 to 6.3 pp; p = 0.03). Compared to matched controls, the mean age-adjusted difference was 3.3 pp (95% CI 1.7 to 4.9 pp; p < 0.01). The non-stenosis group had MFI similar to controls (age-adjusted difference - 0.9 pp, 95% CI - 3.4 to 1.8 pp; p = 0.51). MFI was strongly correlated with the 6MWT (r = - 0.81, - 0.83, and - 0.86; all p-values < 0.01), and moderately correlated with the 30sSTS (r = - 0.56, - 0.57, and - 0.59; all p-values < 0.01). There were no significant differences in muscle volumes or physical activity level between the stenosis group and the non-stenosis group.

CONCLUSION

Increased MFI in the thigh muscles was associated with the presence of symptomatic spinal stenosis, reduced functional walking capacity, and reduced lower limb muscle strength. The causality between spinal stenosis, accumulation of thigh MFI, and surgical outcomes need further study. We have demonstrated that MRI might serve as an objective muscle biomarker in future achondroplasia studies, in addition to functional outcome measures. The method could potentially aid in optimizing the timing of spinal decompression surgery and in planning of post-surgery rehabilitation.

BMI-adjusted adipose tissue volumes exhibit depot-specific and divergent associations with cardiometabolic diseases

For any given body mass index (BMI), individuals vary substantially in fat distribution, and this variation may have important implications for cardiometabolic risk. Here, we study disease associations with BMI-independent variation in visceral (VAT), abdominal subcutaneous (ASAT), and gluteofemoral (GFAT) fat depots in 40,032 individuals of the UK Biobank with body MRI. We apply deep learning models based on two-dimensional body MRI projections to enable near-perfect estimation of fat depot volumes (R2 in heldout dataset = 0.978-0.991 for VAT, ASAT, and GFAT). Next, we derive BMI-adjusted metrics for each fat depot (e.g. VAT adjusted for BMI, VATadjBMI) to quantify local adiposity burden. VATadjBMI is associated with increased risk of type 2 diabetes and coronary artery disease, ASATadjBMI is largely neutral, and GFATadjBMI is associated with reduced risk. These results - describing three metabolically distinct fat depots at scale - clarify the cardiometabolic impact of BMI-independent differences in body fat distribution.

The oxytocin signalling gene pathway contributes to the association between loneliness and cardiometabolic health

Increasing evidence has shown adverse effects of loneliness on cardiometabolic health. The neuromodulator and hormone oxytocin has traditionally been linked with social cognition and behaviour. However, recent implications of the oxytocin system in energy metabolism and the overrepresentation of metabolic issues in psychiatric illness suggests that oxytocin may represent a mechanism bridging mental and somatic traits. To clarify the role of the oxytocin signalling system in the link between cardiometabolic risk factors and loneliness, we calculated the contribution of single nucleotide polymorphisms (SNPs) in the oxytocin signalling pathway gene-set (154 genes) to the polygenic architecture of loneliness and body mass index (BMI). We investigated the associations of these oxytocin signalling pathway polygenic scores with body composition measured using body magnetic resonance imaging (MRI), bone mineral density (BMD), haematological markers, and blood pressure in a sample of just under half a million adults from the UK Biobank (BMD subsample n = 274,457; body MRI subsample n = 9796). Our analysis revealed significant associations of the oxytocin signalling pathway polygenic score for BMI with abdominal subcutaneous fat tissue, HDL cholesterol, lipoprotein(a), triglycerides, and BMD. We also found an association between the oxytocin signalling pathway polygenic score for loneliness and apolipoprotein A1, the major protein component of HDL. Altogether, these results provide additional evidence for the oxytocin signalling pathway's role in energy metabolism, lipid homoeostasis, and bone density, and support oxytocin's complex pleiotropic effects.

Fat Distribution Patterns and Future Type 2 Diabetes

Fat accumulation in the liver, pancreas, skeletal muscle, and visceral bed relates to type 2 diabetes (T2D). However, the distribution of fat among these compartments is heterogenous and whether specific distribution patterns indicate high T2D risk is unclear. We therefore investigated fat distribution patterns and their link to future T2D. From 2,168 individuals without diabetes who underwent computed tomography in Japan, this case-cohort study included 658 randomly selected individuals and 146 incident cases of T2D over 6 years of follow-up. Using data-driven analysis (k-means) based on fat content in the liver, pancreas, muscle, and visceral bed, we identified four fat distribution clusters: hepatic steatosis, pancreatic steatosis, trunk myosteatosis, and steatopenia. In comparisons with the steatopenia cluster, the adjusted hazard ratios for incident T2D were 4.02 (95% CI 2.27-7.12) for the hepatic steatosis cluster, 3.38 (1.65-6.91) for the pancreatic steatosis cluster, and 1.95 (1.07-3.54) for the trunk myosteatosis cluster. The clusters were replicated in 319 German individuals without diabetes who underwent MRI and metabolic phenotyping. The distribution of the glucose area under the curve across the four clusters found in Germany was similar to the distribution of T2D risk across the four clusters in Japan. Insulin sensitivity and insulin secretion differed across the four clusters. Thus, we identified patterns of fat distribution with different T2D risks presumably due to differences in insulin sensitivity and insulin secretion.

Sex- and age-specific associations between cardiometabolic risk and white matter brain age in the UK Biobank cohort

Cardiometabolic risk (CMR) factors are associated with accelerated brain aging and increased risk for sex-dimorphic illnesses such as Alzheimer's disease (AD). Yet, it is unknown how CMRs interact with sex and apolipoprotein E-ϵ4 (APOE4), a known genetic risk factor for AD, to influence brain age across different life stages. Using age prediction based on multi-shell diffusion-weighted imaging data in 21,308 UK Biobank participants, we investigated whether associations between white matter Brain Age Gap (BAG) and body mass index (BMI), waist-to-hip ratio (WHR), body fat percentage (BF%), and APOE4 status varied (i) between males and females, (ii) according to age at menopause in females, and (iii) across different age groups in males and females. We report sex differences in associations between BAG and all three CMRs, with stronger positive associations among males compared to females. Independent of APOE4 status, higher BAG (older brain age relative to chronological age) was associated with greater BMI, WHR, and BF% in males, whereas in females, higher BAG was associated with greater WHR, but not BMI and BF%. These divergent associations were most prominent within the oldest group of females (66-81 years), where greater BF% was linked to lower BAG. Earlier menopause transition was associated with higher BAG, but no interactions were found with CMRs. In conclusion, the findings point to sex- and age-specific associations between CMRs and brain age. Incorporating sex as a factor of interest in studies addressing CMR may promote sex-specific precision medicine, consequently improving health care for both males and females.

Ectopic fat is associated with cardiac remodeling—A comprehensive assessment of regional fat depots in type 2 diabetes using multi-parametric MRI

Background

Different regional depots of fat have distinct metabolic properties and may relate differently to adverse cardiac remodeling. We sought to quantify regional depots of body fat and to investigate their relationship to cardiac structure and function in Type 2 Diabetes (T2D) and controls.

Methods

From the SCAPIS cohort in Linköping, Sweden, we recruited 92 subjects (35% female, mean age 59.5 ± 4.6 years): 46 with T2D and 46 matched controls. In addition to the core SCAPIS data collection, participants underwent a comprehensive magnetic resonance imaging examination at 1.5 T for assessment of left ventricular (LV) structure and function (end-diastolic volume, mass, concentricity, ejection fraction), as well as regional body composition (liver proton density fat fraction, visceral adipose tissue, abdominal subcutaneous adipose tissue, thigh muscle fat infiltration, fat tissue-free thigh muscle volume and epicardial adipose tissue).

Results

Compared to the control group, the T2D group had increased: visceral adipose tissue volume index (P &lt; 0.001), liver fat percentage (P &lt; 0.001), thigh muscle fat infiltration percentage (P = 0.02), LV concentricity (P &lt; 0.001) and LV E/e'-ratio (P &lt; 0.001). In a multiple linear regression analysis, a negative association between liver fat percentage and LV mass (St Beta −0.23, P &lt; 0.05) as well as LV end-diastolic volume (St Beta −0.27, P &lt; 0.05) was found. Epicardial adipose tissue volume and abdominal subcutaneous adipose tissue volume index were the only parameters of fat associated with LV diastolic dysfunction (E/e'-ratio) (St Beta 0.24, P &lt; 0.05; St Beta 0.34, P &lt; 0.01, respectively). In a multivariate logistic regression analysis, only visceral adipose tissue volume index was significantly associated with T2D, with an odds ratio for T2D of 3.01 (95% CI 1.28–7.05, P &lt; 0.05) per L/m2 increase in visceral adipose tissue volume.

Conclusions

Ectopic fat is predominantly associated with cardiac remodeling, independently of type 2 diabetes. Intriguingly, liver fat appears to be related to LV structure independently of VAT, while epicardial fat is linked to impaired LV diastolic function. Visceral fat is associated with T2D independently of liver fat and abdominal subcutaneous adipose tissue.

Cardiometabolic Health Outcomes Associated With Discordant Visceral and Liver Fat Phenotypes: Insights From the Dallas Heart Study and UK Biobank

OBJECTIVE

To evaluate the cardiometabolic outcomes associated with discordant visceral adipose tissue (VAT) and liver fat (LF) phenotypes in 2 cohorts.

PATIENTS AND METHODS

Participants in the Dallas Heart Study underwent baseline imaging from January 1, 2000, through December 31, 2002, and were followed for incident cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) through 2013. Associations between VAT-LF groups (low-low, high-low, low-high, and high-high) and outcomes were assessed using multivariable-adjusted regression and were replicated in the independent UK Biobank.

RESULTS

The Dallas Heart Study included 2064 participants (mean ± SD age, 44±9 years; 54% female; 47% black). High VAT-high LF and high VAT-low LF were associated with prevalent atherosclerosis, whereas low VAT-high LF was not. Of 1731 participants without CVD/T2DM, 128 (7.4%) developed CVD and 95 (5.5%) T2DM over a median of 12 years. High VAT-high LF and high VAT-low LF were associated with increased risk of CVD (hazard ratios [HRs], 2.0 [95% CI, 1.3 to 3.2] and 2.4 [95% CI, 1.4 to 4.1], respectively) and T2DM (odds ratios [ORs], 7.8 [95% CI, 3.8 to 15.8] and 3.3 [95% CI, 1.4 to 7.8], respectively), whereas low VAT-high LF was associated with T2DM (OR, 2.7 [95% CI, 1.1 to 6.7]). In the UK Biobank (N=22,354; April 2014-May 2020), only high VAT-low LF remained associated with CVD after multivariable adjustment for age and body mass index (HR, 1.5 [95% CI, 1.2 to 1.9]).

CONCLUSION

Although VAT and LF are each associated with cardiometabolic risk, these observations demonstrate the importance of separating their cardiometabolic implications when there is presence or absence of either or both in an individual.

Adipose tissue distribution from body MRI is associated with cross-sectional and longitudinal brain age in adults

There is an intimate body-brain connection in ageing, and obesity is a key risk factor for poor cardiometabolic health and neurodegenerative conditions. Although research has demonstrated deleterious effects of obesity on brain structure and function, the majority of studies have used conventional measures such as waist-to-hip ratio, waist circumference, and body mass index. While sensitive to gross features of body composition, such global anthropometric features fail to describe regional differences in body fat distribution and composition. The sample consisted of baseline brain magnetic resonance imaging (MRI) acquired from 790 healthy participants aged 18-94 years (mean ± standard deviation (SD) at baseline: 46.8 ± 16.3), and follow-up brain MRI collected from 272 of those individuals (two time-points with 19.7 months interval, on average (min = 9.8, max = 35.6). Of the 790 included participants, cross-sectional body MRI data was available from a subgroup of 286 participants, with age range 19-86 (mean = 57.6, SD = 15.6). Adopting a mixed cross-sectional and longitudinal design, we investigated cross-sectional body magnetic resonance imaging measures of adipose tissue distribution in relation to longitudinal brain structure using MRI-based morphometry (T1) and diffusion tensor imaging (DTI). We estimated tissue-specific brain age at two time points and performed Bayesian multilevel modelling to investigate the associations between adipose measures at follow-up and brain age gap (BAG) - the difference between actual age and the prediction of the brain's biological age - at baseline and follow-up. We also tested for interactions between BAG and both time and age on each adipose measure. The results showed credible associations between T1-based BAG and liver fat, muscle fat infiltration (MFI), and weight-to-muscle ratio (WMR), indicating older-appearing brains in people with higher measures of adipose tissue. Longitudinal evidence supported interaction effects between time and MFI and WMR on T1-based BAG, indicating accelerated ageing over the course of the study period in people with higher measures of adipose tissue. The results show that specific measures of fat distribution are associated with brain ageing and that different compartments of adipose tissue may be differentially linked with increased brain ageing, with potential to identify key processes involved in age-related transdiagnostic disease processes.

PSD3 downregulation confers protection against fatty liver disease

Fatty liver disease (FLD) is a growing health issue with burdening unmet clinical needs. FLD has a genetic component but, despite the common variants already identified, there is still a missing heritability component. Using a candidate gene approach, we identify a locus (rs71519934) at the Pleckstrin and Sec7 domain-containing 3 (PSD3) gene resulting in a leucine to threonine substitution at position 186 of the protein (L186T) that reduces susceptibility to the entire spectrum of FLD in individuals at risk. PSD3 downregulation by short interfering RNA reduces intracellular lipid content in primary human hepatocytes cultured in two and three dimensions, and in human and rodent hepatoma cells. Consistent with this, Psd3 downregulation by antisense oligonucleotides in vivo protects against FLD in mice fed a non-alcoholic steatohepatitis-inducing diet. Thus, translating these results to humans, PSD3 downregulation might be a future therapeutic option for treating FLD.

MRI-Derived Radiomics Features of Hepatic Fat Predict Metabolic States in Individuals without Cardiovascular Disease

RATIONALE AND OBJECTIVES

To investigate radiomics features of hepatic fat as potential biomarkers of type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) in individuals without overt cardiovascular disease, and benchmarking against hepatic proton density fat fraction (PDFF) and the body mass index (BMI).

MATERIALS AND METHODS

This study collected liver radiomics features of 310 individuals that were part of a case-controlled imaging substudy embedded in a prospective cohort. Individuals had known T2DM (n = 39; 12.6 %) and MetS (n = 107; 34.5 %) status, and were divided into stratified training (n = 232; 75 %) and validation (n = 78; 25 %) sets. Six hundred eighty-four MRI radiomics features were extracted for each liver volume of interest (VOI) on T₁-weighted dual-echo Dixon relative fat water content (rfwc) maps. Test-retest and inter-rater variance was simulated by additionally extracting radiomics features using noise augmented rfwc maps and deformed volume of interests. One hundred and seventy-one features with test-retest reliability (ICC(1,1)) and inter-rater agreement (ICC(3,k)) of ≥0.85 on the training set were considered stable. To construct predictive random forest (RF) models, stable features were filtered using univariate RF analysis followed by sequential forward aggregation. The predictive performance was evaluated on the independent validation set with area under the curve of the receiver operating characteristic (AUROC) and balanced accuracy (Accuracy_B).

RESULTS

On the validation set, the radiomics RF models predicted T2DM with AUROC of 0.835 and Accuracy_B of 0.822 and MetS with AUROC of 0.838 and Accuracy_B of 0.787, outperforming the RF models trained on the benchmark parameters PDFF and BMI.

CONCLUSION

Hepatic radiomics features may serve as potential imaging biomarkers for T2DM and MetS.

Emerging artificial intelligence applications in liver magnetic resonance imaging

Chronic liver diseases (CLDs) are becoming increasingly more prevalent in modern society. The use of imaging techniques for early detection, such as magnetic resonance imaging (MRI), is crucial in reducing the impact of these diseases on healthcare systems. Artificial intelligence (AI) algorithms have been shown over the past decade to excel at image-based analysis tasks such as detection and segmentation. When applied to liver MRI, they have the potential to improve clinical decision making, and increase throughput by automating analyses. With Liver diseases becoming more prevalent in society, the need to implement these techniques to utilize liver MRI to its full potential, is paramount. In this review, we report on the current methods and applications of AI methods in liver MRI, with a focus on machine learning and deep learning methods. We assess four main themes of segmentation, classification, image synthesis and artefact detection, and their respective potential in liver MRI and the wider clinic. We provide a brief explanation of some of the algorithms used and explore the current challenges affecting the field. Though there are many hurdles to overcome in implementing AI methods in the clinic, we conclude that AI methods have the potential to positively aid healthcare professionals for years to come.

The PERSonalized Glucose Optimization Through Nutritional Intervention (PERSON) Study: Rationale, Design and Preliminary Screening Results

Background: It is well-established that the etiology of type 2 diabetes differs between individuals. Insulin resistance (IR) may develop in different tissues, but the severity of IR may differ in key metabolic organs such as the liver and skeletal muscle. Recent evidence suggests that these distinct tissue-specific IR phenotypes may also respond differentially to dietary macronutrient composition with respect to improvements in glucose metabolism.

Objective: The main objective of the PERSON study is to investigate the effects of an optimal vs. suboptimal dietary macronutrient intervention according to tissue-specific IR phenotype on glucose metabolism and other health outcomes.

Methods: In total, 240 overweight/obese (BMI 25 – 40 kg/m²) men and women (age 40 – 75 years) with either skeletal muscle insulin resistance (MIR) or liver insulin resistance (LIR) will participate in a two-center, randomized, double-blind, parallel, 12-week dietary intervention study. At screening, participants undergo a 7-point oral glucose tolerance test (OGTT) to determine the hepatic insulin resistance index (HIRI) and muscle insulin sensitivity index (MISI), classifying each participant as either “No MIR/LIR,” “MIR,” “LIR,” or “combined MIR/LIR.” Individuals with MIR or LIR are randomized to follow one of two isocaloric diets varying in macronutrient content and quality, that is hypothesized to be either an optimal or suboptimal diet, depending on their tissue-specific IR phenotype (MIR/LIR). Extensive measurements in a controlled laboratory setting as well as phenotyping in daily life are performed before and after the intervention. The primary study outcome is the difference in change in disposition index, which is the product of insulin sensitivity and first-phase insulin secretion, between participants who received their hypothesized optimal or suboptimal diet.

Discussion: The PERSON study is one of the first randomized clinical trials in the field of precision nutrition to test effects of a more personalized dietary intervention based on IR phenotype. The results of the PERSON study will contribute knowledge on the effectiveness of targeted nutritional strategies to the emerging field of precision nutrition, and improve our understanding of the complex pathophysiology of whole body and tissue-specific IR.

Clinical Trial Registration:https://clinicaltrials.gov/ct2/show/NCT03708419, clinicaltrials.gov as NCT03708419.

Alcohol consumption in the general population is associated with structural changes in multiple organ systems

Background:

Excessive alcohol consumption is associated with damage to various organs, but its multi-organ effects have not been characterised across the usual range of alcohol drinking in a large general population sample.

Methods:

We assessed global effect sizes of alcohol consumption on quantitative magnetic resonance imaging phenotypic measures of the brain, heart, aorta, and liver of UK Biobank participants who reported drinking alcohol.

Results:

We found a monotonic association of higher alcohol consumption with lower normalised brain volume across the range of alcohol intakes (–1.7 × 10⁻³ ± 0.76 × 10⁻³ per doubling of alcohol consumption, p=3.0 × 10⁻¹⁴). Alcohol consumption was also associated directly with measures of left ventricular mass index and left ventricular and atrial volume indices. Liver fat increased by a mean of 0.15% per doubling of alcohol consumption.

Conclusions:

Our results imply that there is not a ‘safe threshold’ below which there are no toxic effects of alcohol. Current public health guidelines concerning alcohol consumption may need to be revisited.

Funding:

See acknowledgements.

Psoriatic arthritis is associated with adverse body composition predictive of greater coronary heart disease and type 2 diabetes propensity - a cross-sectional study

OBJECTIVES

To compare body composition in PsA with metabolic disease free (MDF) controls and type 2 diabetes and assess body-composition predicted propensity for cardiometabolic disease.

METHODS

Detailed MRI body composition profiles of 26 PsA participants from the IMAPA study were compared with 130 age, sex and BMI-matched MDF controls and 454 individuals with type 2 diabetes from UK Biobank. The body-composition predicted propensity for coronary heart disease (CHD) and type 2 diabetes was compared between PsA and matched MDF controls.

RESULTS

PsA participants had a significantly greater visceral adipose tissue (VAT) volume [mean 5.89 l (s.d. 2.10 l)] compared with matched-MDF controls [mean 4.34 l (s.d. 1.83 l)] (P <0.001) and liver fat percentage [median 8.88% (interquartile range 4.42-13.18%)] compared with MDF controls [3.29% (1.98-7.25%)] (P <0.001). These differences remained significant after adjustment for age, sex and BMI. There were no statistically significant differences in VAT, liver fat or muscle fat infiltration (MFI) between PsA and type 2 diabetes. PsA participants had a lower thigh muscle volume than MDF controls and those with type 2 diabetes. Body composition-predicted propensity for CHD and type 2 diabetes was 1.27 and 1.83 times higher, respectively, for PsA compared with matched-MDF controls.

CONCLUSION

Individuals with PsA have an adverse body composition phenotype with greater visceral and ectopic liver fat and lower thigh muscle volume than matched MDF controls. Body fat distribution in PsA is more in keeping with the pattern observed in type 2 diabetes and is associated with greater propensity to cardiometabolic disease. These data support the need for greater emphasis on weight loss in PsA management to lessen CHD and type 2 diabetes risk.

Exome-Wide Association Study on Alanine Aminotransferase Identifies Sequence Variants in the GPAM and APOE Associated With Fatty Liver Disease

BACKGROUND & AIMS

Fatty liver disease (FLD) is a growing epidemic that is expected to be the leading cause of end-stage liver disease within the next decade. Both environmental and genetic factors contribute to the susceptibility of FLD. Several genetic variants contributing to FLD have been identified in exome-wide association studies. However, there is still a missing hereditability indicating that other genetic variants are yet to be discovered.

METHODS

To find genes involved in FLD, we first examined the association of missense and nonsense variants with alanine aminotransferase at an exome-wide level in 425,671 participants from the UK Biobank. We then validated genetic variants with liver fat content in 8930 participants in whom liver fat measurement was available, and replicated 2 genetic variants in 3 independent cohorts comprising 2621 individuals with available liver biopsy.

RESULTS

We identified 190 genetic variants independently associated with alanine aminotransferase after correcting for multiple testing with Bonferroni method. The majority of these variants were not previously associated with this trait. Among those associated, there was a striking enrichment of genetic variants influencing lipid metabolism. We identified the variants rs2792751 in GPAM/GPAT1, the gene encoding glycerol-3-phosphate acyltransferase, mitochondrial, and rs429358 in APOE, the gene encoding apolipoprotein E, as robustly associated with liver fat content and liver disease after adjusting for multiple testing. Both genes affect lipid metabolism in the liver.

CONCLUSIONS

We identified 2 novel genetic variants in GPAM and APOE that are robustly associated with steatosis and liver damage. These findings may help to better elucidate the genetic susceptibility to FLD onset and progression.

Use of artificial intelligence in the imaging of sarcopenia: A narrative review of current status and perspectives

Sarcopenia is a muscle disease which previously was associated only with aging, but in recent days it has been gaining more attention for its predictive value in a vast range of conditions and its potential link with overall health. Up to this point, evaluating sarcopenia with imaging methods has been time-consuming and dependent on the skills of the physician. The solution for this problem may be found in artificial intelligence, which may assist radiologists in repetitive tasks such as muscle segmentation and body-composition analysis. The major aim of this review was to find and present the current status and future perspectives of artificial intelligence in the imaging of sarcopenia. We searched the PubMed database to find articles concerning the use of artificial intelligence in diagnostic imaging and especially in body-composition analysis in the context of sarcopenia. We found that artificial-intelligence systems could potentially help with evaluating sarcopenia and better predicting outcomes in a vast range of clinical situations, which could get us closer to the true era of precision medicine.

On the Definition of Sarcopenia in the Presence of Aging and Obesity-Initial Results from UK Biobank

BACKGROUND

Current consensus is to combine a functional measure with muscle quantity to assess/confirm sarcopenia. However, the proper body size adjustment for muscle quantity is debated and sarcopenia in obesity is not well described. Further, functional measures are not muscle-specific or sensitive to etiology, and can be confounded by, for example, fitness/pain. For effective detection/treatment/follow-up, muscle-specific biomarkers linked to function are needed.

METHODS

Nine thousand six hundred and fifteen participants were included and current sarcopenia thresholds (EWGSOP2: DXA, hand grip strength) applied to investigate prevalence. Fat-tissue free muscle volume (FFMV) and muscle fat infiltration (MFI) were quantified through magnetic resonance imaging (MRI) and sex-and-body mass index (BMI)-matched virtual control groups (VCGs) were used to extract each participant's FFMV/height2 z-score (FFMVVCG). The value of combining FFMVVCG and MFI was investigated through hospital nights, hand grip strength, stair climbing, walking pace, and falls.

RESULTS

Current thresholds showed decreased sarcopenia prevalence with increased BMI (underweight 8.5%/normal weight 4.3%/overweight 1.1%/obesity 0.1%). Contrary, the prevalence of low function increased with increasing BMI. Previously proposed body size adjustments (division by height2/weight/BMI) introduced body size correlations of larger/similar magnitude than before. VCG adjustment achieved normalization and strengthened associations with hospitalization/function. Hospital nights, low hand grip strength, slow walking pace, and no stair climbing were positively associated with MFI (p < .05) and negatively associated with FFMVVCG (p < .01). Only MFI was associated with falls (p < .01). FFMVVCG and MFI combined resulted in highest diagnostic performance detecting low function.

CONCLUSIONS

VCG-adjusted FFMV enables proper sarcopenia assessment across BMI classes and strengthened the link to function. MFI and FFMV combined provides a more complete, muscle-specific description linked to function enabling objective sarcopenia detection.

Harnessing Muscle-Liver Crosstalk to Treat Nonalcoholic Steatohepatitis

Non-alcoholic fatty liver disease (NAFLD) has reached epidemic proportions, affecting an estimated one-quarter of the world's adult population. Multiple organ systems have been implicated in the pathophysiology of NAFLD; however, the role of skeletal muscle has until recently been largely overlooked. A growing body of evidence places skeletal muscle-via its impact on insulin resistance and systemic inflammation-and the muscle-liver axis at the center of the NAFLD pathogenic cascade. Population-based studies suggest that sarcopenia is an effect-modifier across the NAFLD spectrum in that it is tightly linked to an increased risk of non-alcoholic fatty liver, non-alcoholic steatohepatitis (NASH), and advanced liver fibrosis, all independent of obesity and insulin resistance. Longitudinal studies suggest that increases in skeletal muscle mass over time may both reduce the incidence of NAFLD and improve preexisting NAFLD. Adverse muscle composition, comprising both low muscle volume and high muscle fat infiltration (myosteatosis), is highly prevalent in patients with NAFLD. The risk of functional disability conferred by low muscle volume in NAFLD is further exacerbated by the presence of myosteatosis, which is twice as common in NAFLD as in other chronic liver diseases. Crosstalk between muscle and liver is influenced by several factors, including obesity, physical inactivity, ectopic fat deposition, oxidative stress, and proinflammatory mediators. In this perspective review, we discuss key pathophysiological processes driving sarcopenia in NAFLD: anabolic resistance, insulin resistance, metabolic inflexibility and systemic inflammation. Interventions that modify muscle quantity (mass), muscle quality (fat), and physical function by simultaneously engaging multiple targets and pathways implicated in muscle-liver crosstalk may be required to address the multifactorial pathogenesis of NAFLD/NASH and provide effective and durable therapies.

Cardiovascular risk factors and body composition in adults with achondroplasia

Purpose

An increased cardiovascular mortality has been reported in achondroplasia. This population-based, case–control study investigated cardiovascular risk factors and body composition in Norwegian adults with achondroplasia.

Methods

We conducted anthropometric, clinical, and laboratory assessments in 49 participants with achondroplasia, of whom 40 completed magnetic resonance imaging (MRI) for body composition analysis. Controls consisted of 98 UK Biobank participants, matched for body mass index (BMI), sex, and age.

Results

Participants were well matched for BMI (33.3 versus 32.5 kg/m²) and sex, but achondroplasia participants were younger than controls (mean age 41.1 versus 54.3 years). Individuals with achondroplasia had lower age-adjusted mean blood pressure, total and low-density lipoprotein (LDL) cholesterol, and triglycerides compared with controls, but similar fasting glucose and HbA1c values. Age-adjusted mean visceral fat store was 1.9 versus 5.3 L (difference −2.7, 95% confidence interval [CI] −3.6 to −1.9; P < 0.001), abdominal subcutaneous fat was 6.0 versus 11.2 L (−4.7, 95% CI −5.9 to −3.4; P < 0.001), and liver fat was 2.2 versus 6.9% (−2.8, 95% CI −5.2 to −0.4; P = 0.02).

Conclusion

Despite a high BMI, the cardiovascular risks appeared similar or lower in achondroplasia compared with controls, indicating that other factors might contribute to the increased mortality observed in this condition.

Fully Automated and Standardized Segmentation of Adipose Tissue Compartments via Deep Learning in 3D Whole-Body MRI of Epidemiologic Cohort Studies

PURPOSE

To enable fast and reliable assessment of subcutaneous and visceral adipose tissue compartments derived from whole-body MRI.

MATERIALS AND METHODS

Quantification and localization of different adipose tissue compartments derived from whole-body MR images is of high interest in research concerning metabolic conditions. For correct identification and phenotyping of individuals at increased risk for metabolic diseases, a reliable automated segmentation of adipose tissue into subcutaneous and visceral adipose tissue is required. In this work, a three-dimensional (3D) densely connected convolutional neural network (DCNet) is proposed to provide robust and objective segmentation. In this retrospective study, 1000 cases (average age, 66 years ± 13 [standard deviation]; 523 women) from the Tuebingen Family Study database and the German Center for Diabetes research database and 300 cases (average age, 53 years ± 11; 152 women) from the German National Cohort (NAKO) database were collected for model training, validation, and testing, with transfer learning between the cohorts. These datasets included variable imaging sequences, imaging contrasts, receiver coil arrangements, scanners, and imaging field strengths. The proposed DCNet was compared to a similar 3D U-Net segmentation in terms of sensitivity, specificity, precision, accuracy, and Dice overlap.

RESULTS

Fast (range, 5-7 seconds) and reliable adipose tissue segmentation can be performed with high Dice overlap (0.94), sensitivity (96.6%), specificity (95.1%), precision (92.1%), and accuracy (98.4%) from 3D whole-body MRI datasets (field of view coverage, 450 × 450 × 2000 mm). Segmentation masks and adipose tissue profiles are automatically reported back to the referring physician.

CONCLUSION

Automated adipose tissue segmentation is feasible in 3D whole-body MRI datasets and is generalizable to different epidemiologic cohort studies with the proposed DCNet.Supplemental material is available for this article.© RSNA, 2020.

Adverse muscle composition is linked to poor functional performance and metabolic comorbidities in NAFLD

Background & Aims

Sarcopenia and frailty are recognised as important factors in later stages of liver disease. However, their role in non-alcoholic fatty liver disease (NAFLD) is not yet fully understood. In this study we investigate the associations of MRI-measured adverse muscle composition (AMC: low muscle volume and high muscle fat) with poor function, sarcopenia, and metabolic comorbidity within NAFLD in the large UK Biobank imaging study.

Methods

A total of 9,545 participants were included. Liver fat, fat-tissue free muscle volume, and muscle fat infiltration were quantified using a rapid MRI protocol and automated image analysis (AMRA® Researcher). For each participant, a personalised muscle volume z-score (sex- and body size-specific) was calculated and combined with muscle fat infiltration for AMC detection. The following outcomes were investigated: functional performance (hand grip strength, walking pace, stair climbing, falls) and metabolic comorbidities (coronary heart disease, type 2 diabetes). Sarcopenia was detected by combining MRI thresholds for low muscle quantity and low hand grip strength according to the European working group definition.

Results

The prevalence of sarcopenia in NAFLD (1.6%) was significantly lower (p <0.05) compared with controls without fatty liver (3.4%), whereas the prevalence of poor function and metabolic comorbidity was similar or higher. Of the 1,204 participants with NAFLD, 169 (14%) had AMC and showed 1.7–2.4× higher prevalence of poor function (all p <0.05) as well as 2.1× and 3.3× higher prevalence of type 2 diabetes and coronary heart disease (p <0.001), respectively, compared with those without AMC.

Conclusions

AMC is a prevalent and highly vulnerable NAFLD phenotype displaying poor function and high prevalence of metabolic comorbidity. Sarcopenia guidelines can be strengthened by including cut-offs for muscle fat, enabling AMC detection.

Lay summary

Today, it is hard to predict whether a patient with fatty liver disease will progress to more severe liver disease. This study shows that measuring muscle health (the patient's muscle volume and how much fat they have in their muscles) could help identify the more vulnerable patients and enable early prevention of severe liver disease.

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The role of sarcopenia and frailty in NAFLD is not yet fully understood.

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Magnetic resonance imaging enables quantification of muscle composition.

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Myosteatosis in combination with low muscle volume characterises an adverse muscle composition.

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Adverse muscle composition is a novel NAFLD phenotype associated with poor function and metabolic comorbidity.

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Sarcopenia guidelines can be strengthened by including cut-offs for muscle fat.

The metabolic basis of nonalcoholic steatohepatitis

Nonalcoholic fatty liver disease (NAFLD) is a major cause of chronic liver disease and is associated with significant morbidity and mortality worldwide, with a high incidence in Western countries and non-Western countries that have adopted a Western diet. NAFLD is commonly associated with components of the metabolic syndrome, type 2 diabetes mellitus and cardiovascular disease, suggesting a common mechanistic basis. An inability to metabolically handle free fatty acid overload-metabolic inflexibility-constitutes a core node for NAFLD pathogenesis, with resulting lipotoxicity, mitochondrial dysfunction and cellular stress leading to inflammation, apoptosis and fibrogenesis. These responses can lead to the histological phenotype of nonalcoholic steatohepatitis (NASH) with varying degrees of fibrosis, which can progress to cirrhosis. This perspective review describes the key cellular and molecular mechanisms of NAFLD and NASH, namely an excessive burden of carbohydrates and fatty acids that contribute to lipotoxicity resulting in hepatocellular injury and fibrogenesis. Understanding the extrahepatic dysmetabolic contributors to NASH is crucial for the development of safe, effective and durable treatment approaches for this increasingly common disease.

Automated assessment of regional muscle volume and hypertrophy using MRI

This study aimed to validate a fully automatic method to quantify knee-extensor muscle volume and exercise-induced hypertrophy. By using a magnetic resonance imaging-based fat-water separated two-point Dixon sequence, the agreement between automated and manual segmentation of a specific ~15-cm region (partial volume) of the quadriceps muscle was assessed. We then explored the sensitivity of the automated technique to detect changes in both complete and partial quadriceps volume in response to 8 weeks of resistance training in 26 healthy men and women. There was a very strong correlation (r = 0.98, P < 0.0001) between the manual and automated method for assessing partial quadriceps volume, yet the volume was 9.6% greater with automated compared with manual analysis (P < 0.0001, 95% limits of agreement −93.3 ± 137.8 cm³). Partial muscle volume showed a 6.0 ± 5.0% (manual) and 4.8 ± 8.3% (automated) increase with training (P < 0.0001). Similarly, the complete quadriceps increased 5.1 ± 5.5% with training (P < 0.0001). The intramuscular fat proportion decreased (P < 0.001) from 4.1% to 3.9% after training. In conclusion, the automated method showed excellent correlation with manual segmentation and could detect clinically relevant magnitudes of exercise-induced muscle hypertrophy. This method could have broad application to accurately measure muscle mass in sports or to monitor clinical conditions associated with muscle wasting and fat infiltration.

Magnetic resonance imaging of obesity and metabolic disorders: Summary from the 2019 ISMRM Workshop

More than 100 attendees from Australia, Austria, Belgium, Canada, China, Germany, Hong Kong, Indonesia, Japan, Malaysia, the Netherlands, the Philippines, Republic of Korea, Singapore, Sweden, Switzerland, the United Kingdom, and the United States convened in Singapore for the 2019 ISMRM-sponsored workshop on MRI of Obesity and Metabolic Disorders. The scientific program brought together a multidisciplinary group of researchers, trainees, and clinicians and included sessions in diabetes and insulin resistance; an update on recent advances in water-fat MRI acquisition and reconstruction methods; with applications in skeletal muscle, bone marrow, and adipose tissue quantification; a summary of recent findings in brown adipose tissue; new developments in imaging fat in the fetus, placenta, and neonates; the utility of liver elastography in obesity studies; and the emerging role of radiomics in population-based "big data" studies. The workshop featured keynote presentations on nutrition, epidemiology, genetics, and exercise physiology. Forty-four proffered scientific abstracts were also presented, covering the topics of brown adipose tissue, quantitative liver analysis from multiparametric data, disease prevalence and population health, technical and methodological developments in data acquisition and reconstruction, newfound applications of machine learning and neural networks, standardization of proton density fat fraction measurements, and X-nuclei applications. The purpose of this article is to summarize the scientific highlights from the workshop and identify future directions of work.