bioRxiv ScienceSearch

bioRxiv · 10.1101/371815

Identification of salivary and plasma biomarkers for obesity in children by non-targeted metabolomic analysis

Abstract

Chemical compounds in the saliva most likely to be associated with obesity are identified in a metabolomic analysis of paired whole saliva and plasma samples from 68 children (10-year old) who have also been evaluated for their gingival redness.\n\nResultsThrough metabolomic analysis119 compounds were found only in saliva, 210 only in plasma and 126 in both. The most common plasma metabolites were lipids. The most common saliva metabolites were peptides. Amino acids and their metabolites were common in both samples.\n\nSurrogate indicators were identified by computing correlations between saliva and plasma. 29 of the 126 found in both saliva and plasma had significant positive correlation and only 4 of those (urate, creatinine, pipecolate and hydroxyproline) were associated with obesity as potential surrogate biomarkers. The uremic toxin N1-Methyl-2-pyridone-5-carboxamide (2PY) was also elevated in the saliva of obese children. 21 biochemicals were elevated in both obesity and gingivitis suggesting that some biochemical pathways for gingivitis and obesity are shared.\n\nOf the metabolites found only in saliva, 35 were associated with obesity (p<0.01). The most significant was phosphate. Saliva had 53 dipeptides, seven of which were associated with obesity. Two volatile amines (putrescine and cadaverine) and their amino acid precursors (ornithine and lysine) were also associated with obesity.\n\nOf the metabolites found only in plasma, 64 were associated with obesity (p<0.01). Significant increases in branched-chain and aromatic amino acids, significant reductions in serotonin, serine, and glycine and increased androgen metabolism are changes observed in 10-year old obese children that have also been reported with adult patients having type II diabetes.\n\nConclusionsSalivary urate may be a valuable measure of metabolic disease particularly in association with fructose consumption. Elevated salivary creatinine levels and presence of 2PY suggests a possible association of obesity with developing kidney disease in obese children. Though not a surrogate variable, salivary phosphate, (AUROC= 0.8) could also be an important indicator of obesity. Cadaverine, putrescine and dipeptides are also likely oral bacterial products that could help define the metabolic pathways responsible for obesity. The results of this study indicate that salivary metabolites can be important indicators of developing metabolic disease in children and provide a biochemical signature in the pathways that lead to obesity.

Explore related subjects

Keep this discovery

BibTeXRIS

Goodson, J. M., Hardt, M., Hartman, M.-L., Schulte, F., Tavares, M., Al-Mutawa, S., Ariga, J., Soparkar, P., Behbehani, J., Behbehani, K., Razzaque, M.. 2018-07-18. Identification of salivary and plasma biomarkers for obesity in children by non-targeted metabolomic analysis. https://doi.org/10.1101/371815

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Translating surveillance data into incidence estimates

Monitoring a population for a disease requires the hosts to be sampled and tested for the pathogen. This results in sampling series from which to estimate the disease incidence, i.e. the proportion of hosts infected. Existing estimation methods assume that disease incidence is not changing between monitoring rounds, resulting in underestimation of the disease incidence. In this paper we develop an incidence estimation model accounting for epidemic growth with monitoring rounds sampling varying incidence. We also show how to accommodate the asymptomatic period characteristic to most diseases. For practical use, we produce an approximation of the model, which is subsequently shown accurate for relevant epidemic and sampling parameters. Both the approximation and the full model are applied to stochastic spatial simulations of epidemics. The results prove their consistency for a very wide range of situations.

epidemiology

The Swiss Primary Ciliary Dyskinesia registry: objectives, methods and first results

Primary Ciliary Dyskinesia (PCD) is a rare hereditary, multi-organ disease caused by defects in ciliary structure and function. It results in a wide range of clinical manifestations, most commonly in the upper and lower airways. Central data collection in national and international registries is essential to studying the epidemiology of rare diseases and filling in gaps in knowledge of diseases such as PCD. For this reason, the Swiss Primary Ciliary Dyskinesia Registry (CH-PCD) was founded in 2013 as a collaborative project between epidemiologists and adult and paediatric pulmonologists.\n\nThe registry records patients of any age, suffering from PCD, who are treated and resident in Switzerland. It collects information from patients identified through physicians, diagnostic facilities, and patient organisations. The registry dataset contains data on diagnostic evaluations, lung function, microbiology and imaging, symptoms, treatments, and hospitalizations.\n\nBy May 2018, CH-PCD has contacted 566 physicians of different specialties and identified 134 patients with PCD. At present this number represents an overall 1 in 63,000 prevalence of people diagnosed with PCD in Switzerland. Prevalence differs by age and region; it is highest in children and adults younger than 30 years, and in Espace Mittelland. The median age of patients in the registry is 25 years (range 5-73), and 49 patients have a definite PCD diagnosis based on recent international guidelines. Data from CH-PCD are contributed to international collaborative studies and the registry facilitates patient identification for nested studies.\n\nCH-PCD has proven to be a valuable research tool that already has highlighted weaknesses in PCD clinical practice in Switzerland. Development of centralised diagnostic and management centres and adherence to international guidelines are needed to improve diagnosis and management--particularly for adult PCD patients.

epidemiology

Perfect Counterfactuals for Epidemic Simulations

Simulation studies are often used to predict the expected impact of control measures in infectious disease outbreaks. Typically, two independent sets of simulations are conducted, one with the intervetnion, and one without, and epidemic sizes (or some related metric) are compared to estimate the effect of the intervention. Since it is possible that controlled epidemics are larger than uncontrolled ones if there is substantial stochastic variation between epidemics, uncertainty intervals from this approach can include a negative effect even for an effective intervention. To more precisely estimate the number of cases an intervention will prevent within a single epidemic, here we develop a single world approach to matching simulations of controlled epidemics to their exact uncontrolled counterfac-tual. Our method borrows concepts from percolation approaches prune out possible epidemic histories and create potential epidemic graph that can be realized to create perfectly matched controlled and uncontrolled epidemics. We present an implementation of this method for a common class of compartmental models, and its application in a simple SIR model. Results illustrate how, at the cost of some computation time, this method substantially narrows confidence intervals and avoids non-sensical inferences.

epidemiology