Mathematical modeling of adipocyte size distributions: Identifiability and parameter estimation from rat data

Fat cells, called adipocytes, are designed to regulate energy homeostasis by storing energy in the form of lipids. Adipocyte size distribution is assumed to play a role in the development of obesity-related diseases. These cells that do not have a characteristic size, indeed a bimodal size distribution is observed in adipose tissue. We propose a model based on a partial differential equation to describe adipocyte size distribution. The model includes a description of the lipid fluxes and the cell size fluctuations and using a formulation of a stationary solution fast computation of bimodal distribution is achieved. We investigate the parameter identifiability and estimate parameter values with CMA-ES algorithm. We first validate the procedure on synthetic data, then we estimate parameter values with experimental data of 32 rats. We discuss the estimated parameter values and their variability within the population, as well as the relation between estimated values and their biological significance. Finally, a sensitivity analysis is performed to specify the influence of parameters on cell size distribution and explain the differences between the model and the measurements. The proposed framework enables the characterization of adipocyte size distribution with four parameters and can be easily adapted to measurements of cell size distribution in different health conditions.

Tissue pleiotropic effect of biotin and prebiotic supplementation in established obesity

Combination therapies targeting multiple organs and metabolic pathways are promising therapeutic options to combat obesity progression and/or its comorbidities. The alterations in the composition of the gut microbiota initially observed in obesity have been extended recently to functional alterations. Bacterial functions involve metabolites synthesis that may contribute to both the gut microbiota and the host physiology. Among them are B vitamins, whose metabolism at the systemic, tissue or microbial level are dysfunctional in obesity. We previously reported that the combination of oral supplementation of a prebiotic (fructo-oligosaccharides, FOS) and vitamin B7/B8 (biotin) impedes fat mass accumulation and hyperglycemia in mice with established obesity. This was associated with an attenuation of dysbiosis with improved microbial vitamin metabolism. We now extend this study by characterizing whole-body energy metabolism along with adipose tissue transcriptome and histology in this mouse model. We observed that FOS resulted in increased caloric excretion in parallel with down-regulation of genes and proteins involved in jejunal lipid transport. The combined treatments also strongly inhibited the accumulation of subcutaneous fat mass, with a reduced adipocyte size and expression of lipid metabolism genes. Down-regulation of inflammatory and fibrotic genes and proteins was also observed in both visceral and brown adipose tissues and liver by combined FOS and biotin supplementation. In conclusion, oral administration of a prebiotic and biotin has a beneficial impact on the metabolism of key organs involved in the pathophysiology of obesity, which could have promising translational applications.

Latent dirichlet allocation for double clustering (LDA-DC): discovering patients phenotypes and cell populations within a single Bayesian framework

BACKGROUND

Current clinical routines rely more and more on "omics" data such as flow cytometry data from host and microbiota. Cohorts variability in addition to patients' heterogeneity and huge dimensions make it difficult to understand underlying structure of the data and decipher pathologies. Patients stratification and diagnostics from such complex data are extremely challenging. There is an acute need to develop novel statistical machine learning methods that are robust with respect to the data heterogeneity, efficient from the computational viewpoint, and can be understood by human experts.

RESULTS

We propose a novel approach to stratify cell-based observations within a single probabilistic framework, i.e., to extract meaningful phenotypes from both patients and cells data simultaneously. We define this problem as a double clustering problem that we tackle with the proposed approach. Our method is a practical extension of the Latent Dirichlet Allocation and is used for the Double Clustering task (LDA-DC). We first validate the method on artificial datasets, then we apply our method to two real problems of patients stratification based on cytometry and microbiota data. We observe that the LDA-DC returns clusters of patients and also clusters of cells related to patients' conditions. We also construct a graphical representation of the results that can be easily understood by humans and are, therefore, of a big help for experts involved in pre-clinical research.

Beta-hydroxybutyrate dampens adipose progenitors' profibrotic activation through canonical Tgfβ signaling and non-canonical ZFP36-dependent mechanisms

BACKGROUND/PURPOSE

Adipose tissue contains progenitor cells that contribute to beneficial tissue expansion when needed by de novo adipocyte formation (classical white or beige fat cells with thermogenic potential). However, in chronic obesity, they can exhibit an activated pro-fibrotic, extracellular matrix (ECM)-depositing phenotype that highly aggravates obesity-related adipose tissue dysfunction.

METHODS

Given that progenitors' fibrotic activation and fat cell browning appear to be antagonistic cell fates, we have examined the anti-fibrotic potential of pro-browning agents in an obesogenic condition.

RESULTS

In obese mice fed a high fat diet, thermoneutral housing, which induces brown fat cell dormancy, increases the expression of ECM gene programs compared to conventionally raised animals, indicating aggravation of obesity-related tissue fibrosis at thermoneutrality. In a model of primary cultured murine adipose progenitors, we found that exposure to β-hydroxybutyrate selectively reduced Tgfβ-dependent profibrotic responses of ECM genes like Ctgf, Loxl2 and Fn1. This effect is observed in both subcutaneous and visceral-derived adipose progenitors, as well as in 3T3-L1 fibroblasts. In 30 patients with obesity eligible for bariatric surgery, those with higher circulating β-hydroxybutyrate levels have lower subcutaneous adipose tissue fibrotic scores. Mechanistically, β-hydroxybutyrate limits Tgfβ-dependent collagen accumulation and reduces Smad2-3 protein expression and phosphorylation in visceral progenitors. Moreover, β-hydroxybutyrate induces the expression of the ZFP36 gene, encoding a post-transcriptional regulator that promotes the degradation of mRNA by binding to AU-rich sites within 3'UTRs. Importantly, complete ZFP36 deficiency in a mouse embryonic fibroblast line from null mice, or siRNA knock-down in primary progenitors, indicate that ZFP36 is required for β-hydroxybutyrate anti-fibrotic effects.

CONCLUSION

These data unravel the potential of β-hydroxybutyrate to limit adipose tissue matrix deposition, a finding that might exploited in an obesogenic context.

Long-Term Weight Outcome After Bariatric Surgery in Patients with Melanocortin-4 Receptor Gene Variants: a Case-Control Study of 105 Patients

INTRODUCTION

Pathogenic heterozygous MC4R variants are associated with hyperphagia and variable degrees of obesity. Several research groups have reported short-term weight loss outcomes after bariatric surgery in a few patients with MC4R variants, but lack of longer-term data prevents evidence-based clinical decision-making.

MATERIALS AND METHODS

Bariatric surgery patients with heterozygous (likely) pathogenic MC4R variants, from three collaborating centers in the Netherlands, France, and the UK, were compared to matched controls (matched 2:1 for age, sex, preoperative BMI, surgical procedure, and diabetes mellitus, but without MC4R mutations). Weight loss and regain outcomes up to 6 years of follow-up were compared.

RESULTS

At 60 months of follow-up after RYGB, cases with MC4R variants showed weight regain with a mean of 12.8% (± 10.4 SD) total weight loss (TWL) from nadir, compared to 7.9% (± 10.5 SD) in the controls (p = 0.062). Among patients receiving SG, the cases with MC4R variants experienced inferior weight loss (22.6% TWL) during the first year of follow-up compared to the controls (29.9% TWL) (p = 0.010).

CONCLUSIONS

This multicenter study reveals inferior mid-term weight outcomes of cases with MC4R variants after SG, compared to RYGB. Since adequate weight loss outcomes were observed after RYGB, this procedure would appear to be an appropriate surgical approach for this group. However, the pattern of weight regain seen in cases with MC4R variants after both RYGB and SG highlights the need for pro-active lifelong management to prevent relapse, as well as careful expectation management.