Research


 * Research **

In a research experiment done in 2008, the goal was to understand Celiac Disease and its mechanism from a holistic point of view. This study gave a comprehensive metabonomic picture of a complex and multifactorial pathology. In this study they highlighted new molecular mechanisms to help treat and relieve Celiac Disease symptoms that are not currently explained.

Thirty-four adult Celiac Disease patients who were all diagnosed at the same time participated in the study. Thirty-four healthy adults from the Gastrointestinal Unit served as the control group for the study. Blood and urine samples were taken from both the experimental and control groups at the start of the study. From the Celiac Disease group, blood and urine samples were also taken from a select subgroup at 3, 6, and 12 months while on a strict gluten-free diet. Each subject would fast overnight and samples were taken in the morning. Both groups were also asked to record their dietary habits and medication usage throughout the study (Bertini, 2009).

There were many tests performed throughout this study, one of which being Antibody testing. Anti-tissue transglutaminase antibodies were measured. Genomic DNA was also extracted from the sampled blood and both groups were genotyped from HLA-DRB1, HLA-DQA1, and HLA-DQB1 genes by PCR-SSP (polymerase chain reaction-sequence specific primers). Frozen serum samples and urine samples were used to perform NMR analysis. To assess the prediction ability of the model, the original data set was split, removing 20% of the samples prior to any statistical analysis. Parameter selection was carried out by a 6-fold cross validation on the remaining 80% of data. The whole procedure was done 250 times and each time the same data set was used for the four statistical methods. To assess which resonance peaks were significantly different between control and experimental groups, a one-way analysis of variance was used. The statistical significance of the means over the two groups was assessed using ANOVA. A p-value less than or equal to 0.05 was considered statistically significant (Bertini, 2009).

Four different statistical analyses have been used on the experimental data set. **Table 1** shows a detailed comparison of the methods carried out on the CMPG spectra data set.



The best discrimination comes from the CPMG spectra. In this spectra, signals arising from large macromolecules have been repressed. This has shown that although Celiac patients often appear to be hypocholesterolemic, lipids do not contribute significantly to the metabonomic signature of Celiac Disease. All but one CPMG serum sample of the follow-up after 12 months were classified as belonging to the healthy subject group, while after 3-6 months several samples were still classified as Celiac Disease patients (shown in **Figure 3**) (Bertini, 2009).



While comparing serum samples of untreated Celiac Disease patients against healthy subjects, it was found that Celiac patients have lower levels of asparagine, isoleucine, methionine, proline, valine, methylamine, pyruvate, creatine, choline, methylglutarate, lactate, lipids, and glycoproteins. Decreased levels of pyruvate and lactate have never been associated with Celiac Disease. Celiac patients had higher levels of glucose and 3-hydroxybutyric acid. When it came to urine samples, Celiac patients had lower levels of mannitol, glutamate, glutamine and pyrimidines. They also had higher levels of indoxyl sulfate, choline, glycine, acetoacetate, uracil, metapropionic acid and phenylacetylglycine (Bertini, 2009). **Table 4** shows all of this data.



Analysis of serum after 12 months of treatment on a gluten-free diet showed decreased levels of glucose and in increase in lipoproteins. There was also a decrease of 3-hydroxybutyric acid and an increase of amino acids, lactate and creatinine levels (Bertini, 2009). The distributions of all metabolite levels that were significantly different between Celiac patients and healthy subjects, as well as their changes in the 12 month follow-up are summarized in **Table 5**.



The decreased levels of pyruvate are something that we should take note of and pay attention to. Pyruvate is the product of Glycolysis, the anaerobic metabolism of glucose. A decrease of pyruvate levels in Celiac patients is consistent with the fact that in untreated Celiac patients, Glycolysis is somehow impaired. Impairment of Glycolysis explains both a lowering of pyruvate levels as well as lactate and in increase of glucose levels in the blood. If Glycolysis is reduced, then lipid beta-oxidation should be increased. But, under conditions of malabsorption as in Celiac patients, intake of lipids is reduced. Enhanced lipids beta-oxidation and malabsorption explains lower levels of lipids in Celiac patients. Lipid catabolism is reduced and the use of ketonic bodies becomes a more important mechanism of energy in Celiac patients, explaining higher levels of 3-hydroxybutyric acid in blood and acetoacetate in urine. Energy conversion from lipids and ketonic bodies catabolism is far less efficient than from glucose and can explain the chronic fatigue symptom in Celiac patients. Patients on a gluten-free diet tend to regain their strength and energy, forming the assumption that this is gluten-related. There was also found to be a strong correlation between glucose and 3-hydroxybutyric acid levels over a 12 month period (Bertini, 2009).

Aside from gluten consumption, the composition and function of hastrointestinal mircoflora have been indicated as a probable environmental factor is Celiac Disease. Microbiota contribute to several processes in the body, such as defense against pathogens, immunity, development of intestinal microvilli, and metabolic energy recovery. This study has also found that the metabonome of Celiac patients is characterized by higher levels of m-HPPA, IS and PAG. m-HPPA mostly originates from gut microflora. IS is a harmful uremic toxin produced in the liver from indole through indoxyl. Indole is one of the subproducts of tryptophan metabolism by intestinal bacteria. PAG excretion in urine has recently been attributed to gut microflora. These finding are consistent with the hypothesis that in Celiac patients gut microflora of the small bowel is altered. The presence of these metabolites in urine can also be caused my altered intestinal permeability. It has been proposed that increased permeability is a precondition for Celiac Disease (Bertini, 2009).

In conclusion, this study has shown that this metabonome has three components. One directly related to malabsorption, one related to energy metabolism, and the third related to alterations of gut microflora and intestinal permeability (Bertini, 2009).

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