Genetic polymorphisms in folate pathway enzymes, DRD4 and GSTM1 are related to temporomandibular disorder

BACKGROUND Temporomandibular disorder (TMD) is a multifactorial syndrome related to a critical period of human life. TMD has been associated with psychological dysfunctions, oxidative state and sexual dimorphism with coincidental occurrence along the pubertal development. In this work we study the association between TMD and genetic polymorphisms of folate metabolism, neurotransmission, oxidative and hormonal metabolism. Folate metabolism, which depends on genes variations and diet, is directly involved in genetic and epigenetic variations that can influence the changes of last growing period of development in human and the appearance of the TMD. METHODS A case-control study was designed to evaluate the impact of genetic polymorphisms above described on TMD. A total of 229 individuals (69% women) were included at the study; 86 were patients with TMD and 143 were healthy control subjects. Subjects underwent to a clinical examination following the guidelines by the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD). Genotyping of 20 Single Nucleotide Polymorphisms (SNPs), divided in two groups, was performed by multiplex minisequencing preceded by multiplex PCR. Other seven genetic polymorphisms different from SNPs (deletions, insertions, tandem repeat, null genotype) were achieved by a multiplex-PCR. A chi-square test was performed to determine the differences in genotype and allelic frequencies between TMD patients and healthy subjects. To estimate TMD risk, in those polymorphisms that shown significant differences, odds ratio (OR) with a 95% of confidence interval were calculated. RESULTS Six of the polymorphisms showed statistical associations with TMD. Four of them are related to enzymes of folates metabolism: Allele G of Serine Hydoxymethyltransferase 1 (SHMT1) rs1979277 (OR = 3.99; 95%CI 1.72, 9.25; p = 0.002), allele G of SHMT1 rs638416 (OR = 2.80; 95%CI 1.51, 5.21; p = 0.013), allele T of Methylentetrahydrofolate Dehydrogenase (MTHFD) rs2236225 (OR = 3.09; 95%CI 1.27, 7.50; p = 0.016) and allele A of Methionine Synthase Reductase (MTRR) rs1801394 (OR = 2.35; 95CI 1.10, 5.00; p = 0.037). An inflammatory oxidative stress enzyme, Gluthatione S-Tranferase Mu-1(GSTM1), null allele (OR = 2.21; 95%CI 1.24, 4.36; p = 0.030) and a neurotransmission receptor, Dopamine Receptor D4 (DRD4), long allele of 48 bp-repeat (OR = 3.62; 95%CI 0.76, 17.26; p = 0.161). CONCLUSIONS Some genetic polymorphisms related to folates metabolism, inflammatory oxidative stress, and neurotransmission responses to pain, has been significantly associated to TMD syndrome.

Gut microbiota in children with type 1 diabetes differs from that in healthy children: a case-control study.

BACKGROUND A recent study using a rat model found significant differences at the time of diabetes onset in the bacterial communities responsible for type 1 diabetes modulation. We hypothesized that type 1 diabetes in humans could also be linked to a specific gut microbiota. Our aim was to quantify and evaluate the difference in the composition of gut microbiota between children with type 1 diabetes and healthy children and to determine the possible relationship of the gut microbiota of children with type 1 diabetes with the glycemic level. METHODS A case-control study was carried out with 16 children with type 1 diabetes and 16 healthy children. The fecal bacteria composition was investigated by polymerase chain reaction-denaturing gradient gel electrophoresis and real-time quantitative polymerase chain reaction. RESULTS The mean similarity index was 47.39% for the healthy children and 37.56% for the children with diabetes, whereas the intergroup similarity index was 26.69%. In the children with diabetes, the bacterial number of Actinobacteria and Firmicutes, and the Firmicutes to Bacteroidetes ratio were all significantly decreased, with the quantity of Bacteroidetes significantly increased with respect to healthy children. At the genus level, we found a significant increase in the number of Clostridium, Bacteroides and Veillonella and a significant decrease in the number of Lactobacillus, Bifidobacterium, Blautia coccoides/Eubacterium rectale group and Prevotella in the children with diabetes. We also found that the number of Bifidobacterium and Lactobacillus, and the Firmicutes to Bacteroidetes ratio correlated negatively and significantly with the plasma glucose level while the quantity of Clostridium correlated positively and significantly with the plasma glucose level in the diabetes group. CONCLUSIONS This is the first study showing that type 1 diabetes is associated with compositional changes in gut microbiota. The significant differences in the number of Bifidobacterium, Lactobacillus and Clostridium and in the Firmicutes to Bacteroidetes ratio observed between the two groups could be related to the glycemic level in the group with diabetes. Moreover, the quantity of bacteria essential to maintain gut integrity was significantly lower in the children with diabetes than the healthy children. These findings could be useful for developing strategies to control the development of type 1 diabetes by modifying the gut microbiota.

Gut Microbiota Composition in Male Rat Models under Different Nutritional Status and Physical Activity and Its Association with Serum Leptin and Ghrelin Levels.

BACKGROUND Several evidences indicate that gut microbiota is involved in the control of host energy metabolism. OBJECTIVE To evaluate the differences in the composition of gut microbiota in rat models under different nutritional status and physical activity and to identify their associations with serum leptin and ghrelin levels. METHODS IN A CASE CONTROL STUDY, FORTY MALE RATS WERE RANDOMLY ASSIGNED TO ONE OF THESE FOUR EXPERIMENTAL GROUPS: ABA group with food restriction and free access to exercise; control ABA group with food restriction and no access to exercise; exercise group with free access to exercise and feed ad libitum and ad libitum group without access to exercise and feed ad libitum. The fecal bacteria composition was investigated by PCR-denaturing gradient gel electrophoresis and real-time qPCR. RESULTS In restricted eaters, we have found a significant increase in the number of Proteobacteria, Bacteroides, Clostridium, Enterococcus, Prevotella and M. smithii and a significant decrease in the quantities of Actinobacteria, Firmicutes, Bacteroidetes, B. coccoides-E. rectale group, Lactobacillus and Bifidobacterium with respect to unrestricted eaters. Moreover, a significant increase in the number of Lactobacillus, Bifidobacterium and B. coccoides-E. rectale group was observed in exercise group with respect to the rest of groups. We also found a significant positive correlation between the quantity of Bifidobacterium and Lactobacillus and serum leptin levels, and a significant and negative correlation among the number of Clostridium, Bacteroides and Prevotella and serum leptin levels in all experimental groups. Furthermore, serum ghrelin levels were negatively correlated with the quantity of Bifidobacterium, Lactobacillus and B. coccoides-Eubacterium rectale group and positively correlated with the number of Bacteroides and Prevotella. CONCLUSIONS Nutritional status and physical activity alter gut microbiota composition affecting the diversity and similarity. This study highlights the associations between gut microbiota and appetite-regulating hormones that may be important in terms of satiety and host metabolism.

Impact of the gut microbiota on the development of obesity and type 2 diabetes mellitus.

Obesity and its associated disorders are a major public health concern. Although obesity has been mainly related with perturbations of the balance between food intake and energy expenditure, other factors must nevertheless be considered. Recent insight suggests that an altered composition and diversity of gut microbiota could play an important role in the development of metabolic disorders. This review discusses research aimed at understanding the role of gut microbiota in the pathogenesis of obesity and type 2 diabetes mellitus (TDM2). The establishment of gut microbiota is dependent on the type of birth. With effect from this point, gut microbiota remain quite stable, although changes take place between birth and adulthood due to external influences, such as diet, disease and environment. Understand these changes is important to predict diseases and develop therapies. A new theory suggests that gut microbiota contribute to the regulation of energy homeostasis, provoking the development of an impairment in energy homeostasis and causing metabolic diseases, such as insulin resistance or TDM2. The metabolic endotoxemia, modifications in the secretion of incretins and butyrate production might explain the influence of the microbiota in these diseases.

Localization of the cannabinoid CB1 receptor and the 2-AG synthesizing (DAGLα) and degrading (MAGL, FAAH) enzymes in cells expressing the Ca(2+)-binding proteins calbindin, calretinin, and parvalbumin in the adult rat hippocampus.

The retrograde suppression of the synaptic transmission by the endocannabinoid sn-2-arachidonoylglycerol (2-AG) is mediated by the cannabinoid CB1 receptors and requires the elevation of intracellular Ca(2+) and the activation of specific 2-AG synthesizing (i.e., DAGLα) enzymes. However, the anatomical organization of the neuronal substrates that express 2-AG/CB1 signaling system-related molecules associated with selective Ca(2+)-binding proteins (CaBPs) is still unknown. For this purpose, we used double-label immunofluorescence and confocal laser scanning microscopy for the characterization of the expression of the 2-AG/CB1 signaling system (CB1 receptor, DAGLα, MAGL, and FAAH) and the CaBPs calbindin D28k, calretinin, and parvalbumin in the rat hippocampus. CB1, DAGLα, and MAGL labeling was mainly localized in fibers and neuropil, which were differentially organized depending on the hippocampal CaBPs-expressing cells. CB(+) 1 fiber terminals localized in all hippocampal principal cell layers were tightly attached to calbindin(+) cells (granular and pyramidal neurons), and calretinin(+) and parvalbumin(+) interneurons. DAGLα neuropil labeling was selectively found surrounding calbindin(+) principal cells in the dentate gyrus and CA1, and in the calretinin(+) and parvalbumin(+) interneurons in the pyramidal cell layers of the CA1/3 fields. MAGL(+) terminals were only observed around CA1 calbindin(+) pyramidal cells, CA1/3 calretinin(+) interneurons and CA3 parvalbumin(+) interneurons localized in the pyramidal cell layers. Interestingly, calbindin(+) pyramidal cells expressed FAAH specifically in the CA1 field. The identification of anatomically related-neuronal substrates that expressed 2-AG/CB1 signaling system and selective CaBPs should be considered when analyzing the cannabinoid signaling associated with hippocampal functions.

Metabolomic insights into the intricate gut microbial-host interaction in the development of obesity and type 2 diabetes.

Gut microbiota has recently been proposed as a crucial environmental factor in the development of metabolic diseases such as obesity and type 2 diabetes, mainly due to its contribution in the modulation of several processes including host energy metabolism, gut epithelial permeability, gut peptide hormone secretion, and host inflammatory state. Since the symbiotic interaction between the gut microbiota and the host is essentially reflected in specific metabolic signatures, much expectation is placed on the application of metabolomic approaches to unveil the key mechanisms linking the gut microbiota composition and activity with disease development. The present review aims to summarize the gut microbial-host co-metabolites identified so far by targeted and untargeted metabolomic studies in humans, in association with impaired glucose homeostasis and/or obesity. An alteration of the co-metabolism of bile acids, branched fatty acids, choline, vitamins (i.e., niacin), purines, and phenolic compounds has been associated so far with the obese or diabese phenotype, in respect to healthy controls. Furthermore, anti-diabetic treatments such as metformin and sulfonylurea have been observed to modulate the gut microbiota or at least their metabolic profiles, thereby potentially affecting insulin resistance through indirect mechanisms still unknown. Despite the scarcity of the metabolomic studies currently available on the microbial-host crosstalk, the data-driven results largely confirmed findings independently obtained from in vitro and animal model studies, putting forward the mechanisms underlying the implication of a dysfunctional gut microbiota in the development of metabolic disorders.