Effect of Synbiotic L. Fermentum Strains on Body Fat Mass

Overview

In this placebo-controlled trial the effect of a synbiotic consisting of three different strains of Lactobacillus fermentum and acacia gum (gum arabic) was compared with a probiotic formulation containing identical strains on body fat mass, body weight management, traits of metabolic syndrome and gut permeability in individuals who are abdominally overweight.

The effects of probiotics on glucose and lipid metabolism, on body fat, weight, visceral fat and liver steatosis were shown by several meta-analyses for the total variety, as described above. Some probiotic species/strains, however, seem to be more efficacious (Koutnikova et al., 2019). The lactobacilli used in this trial were selected for their anti-inflammatory properties and based on induction of defensins in enterocytes. Therefore, one may expect more pronounced effects of these strains on traits of the metabolic syndrome, which is driven by low grade inflammation, than those found in the meta-analyses for the whole variety of probiotics without discriminating species and strain specificity. The combination of these Lactobacillus strains with acacia gum is expected to enable even more pronounce effects, since acacia gum was shown to increase the number of lactobacilli in the gut (Cherbut et al., 2003; Calame et al., 2008) and, hence, are supposed to promote their propagation and, hence their effects. The dosage of 10 g/day acacia gum was demonstrated to be sufficient for enhancing fecal lactobacilli and bifidobacterial (Cherbut et al., 2003; Calame et al., 2008). Acacia gum, however, seems to have own effects on traits of the metabolic syndrome. Even though the effects still need to be confirmed in more DB-RCTs, one may suggest a separate effect, e.g. by reduction of the SGLT1in the intestine (Nasir et al., 2010). This DB-RCT aims at providing first evidence for an effect of this symbiotic on traits of the metabolic syndrome. The target parameters were selected for allowing a health claim according to the Health Claim Directive of the EU (REGULATION (EC) No 1924/2006 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 20 December 2006 on Nutrition and Health Claims Made on Foods) and/or the REGULATION (EU) No 609/2013 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 12 June 2013 for Food for Special Medical Purposes after having confirmative evidence. The following health claim options are feasible according to the EFSA Guidance on the scientific requirements for health claims related to appetite ratings, weight management, and blood glucose concentrations (EFSA Journal 2012;10(3):2604) and to the EFSA Guidance on the scientific requirements for health claims related to antioxidants, oxidative damage and cardiovascular health (EFSA Journal 2011;9(12):2474): * Beneficial effect on long-term glycemia (glucose metabolism) as assessed by HbA1c, * facilitates weight management as assessed by body weight, BMI, waist circumference, or body fat mass, * reduces insulin resistance, a risk factor for type 2 diabetes, as assessed by HOMA-IR, * reduces LDL-C, a risk factor coronary heart disease, * increases HDL-C, a beneficial physiological effect. It is noteworthy that EFSA admits demonstration of effects in type 2 diabetes for health claims on these target parameters assuming that there is a continuity of these parameters from healthy to impaired metabolism (EFSA Journal 2012;10(3):2604). Alternatively, the following claims may be used as FSMPs: * For dietary management of impaired glucose metabolism and type 2 diabetes * for dietary weight management in overweight * for dietary management of insulin resistance The primary parameter has been selected by estimating the sample size for these potential targets based on the most recent meta-analysis of Koutnikova et al. 2019. Since we expect a more pronounced effect by the selected strains and the combination with acacia gum (see above) we assumed a twofold higher effect than found for the whole variety of probiotics. Taking this into account, the target parameter with the lowest estimated sample size was body fat in individuals with type 2 diabetes (N = 56 for each arm). Accordingly, this target was defined as primary parameter.

Conditions

Interventions

Eligibility

Locations (1)

Outcomes