OPEDGP · Omics Phenotyping of Endocrine Disease in the General Population
„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“
- Период
- 2015-08-01 → 2017-07-31
- Финансиране от ЕС
- 200 195 €
- Участници
- 1
- Схема
- MSCA-IF-EF-ST
Линиите свързват координатора с партньорите.
Накратко на български
Метаболитите в урината, като глюкозата и някои аминокиселини, се анализират за откриване на маркери за ендокринни заболявания като хипотиреоидизъм. Това помага за създаването на по-добри инструменти за диагностика и оценка на риска от развитие на тези заболявания.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Omics Phenotyping of Endocrine Disease in the General Population
Background and objectives: Endocrine diseases, such as diabetes and thyroid diseases, are common in the general population and poses a significant burden to individual and society. During the last decade metabolomics, as one of the ‘omics’ techniques including genomics, transcriptomics or proteomics, gains more and more popularity in the field of biomarker discovery and represents a promising tool to identify new diagnostic tool and disease-related pathways and biomarkers of disease risk and prognosis. Metabolomics deals with the investigation of the metabolome comprising the entirety of all small-molecule, so-called metabolites, in any biological sample. Metabolomics is mostly used as hypothesis-free approach because it gives an overview over the metabolic state of an organism (sample) at a given time point. In the present project we used nuclear magnetic resonance spectroscopy (NMR) based metabolomics approach to reveal new markers of endocrine diseases in large population-based studies with longitudinal follow-up. We focused on the urinary metabolome due to the non-invasive nature of the biofluid and the promising implementation in screening tools. Results: The key thyroid hormones, triiodothyronine (T3) and thyroxine (T4), are central components of the hypothalamic-pituitary-thyroid axis and are under control of the pituitary gland released thyroid-stimulating hormone (TSH). TSH and free T4 (FT4) are accepted biomarkers for the diagnosis and follow-up of disorders in thyroid function. We found that significant associations of different amino acids, glucose and trigonelline with changes in thyroid function. Trigonelline was, beside the relation with continuous changes in thyroid function, also associated with an increased risk of hypothyroidism. Trigonelline is known as a metabolite in the niacin metabolism and a bioactive compound in coffee suggesting coffee playing a role in thyroid function. We also investigated the association of baseline urine metabolites with 5-year changes in continuous markers of glucose homoeostasis including fasting glucose, glycated haemoglobin (HbA1c) and homoeostasis model assessment of insulin resistance (HOMA-IR). Several urinary metabolites like alanine, betaine, 1-methylnicotinamide, trimethylamine and trigonelline, were associated with detrimental longitudinal changes in biomarkers of glucose homoeostasis (see figure 1 attached as image). These findings support the hypothesis that the betaine metabolism is involved in the mechanisms of diabetes. The increased betaine excretion might be an early marker of tubular impairment. Beside betaine, the detected metabolites revealed links to the coffee metabolism and the possible influence of the gut microbiome. Urine seems to be a promising tool to screen for individuals who are likely to be affected by longitudinal alterations in glucose homoeostasis. Conclusions: We found evidence that urinary metabolites can be used as biomarkers of endocrine diseases (thyroid disease and diabetes) and changes in biomarkers of endocrine function even in a general population setting. These findings may improve our understanding of disease mechanisms and lead to better prediction of disease.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
Metabolomics is a relatively new technology that provides information about levels of human metabolites, the low molecule products at the end (downstream) of the metabolic pathways of human physiology. In theory, metabolite profiles may more closely reflect the clinical phenotype and thus potentially improve risk prediction. Another advantage is that that they can be performed on non-invasive biofluids like urine. Several metabolomics studies have suggested that the metabolite profile of an individual can be used as a predictor of type 2 diabetes. However, evidence from large-scale population-based studies with comprehensive phenotypes of diabetes and thyroid disease is limited. The aim of the project is to identify urine metabolite profiles associated with risk of diabetes and thyroid disease and to investigate pathogenetic pathways by identifying genetic determinants of these metabolites. The project takes advantage of the long tradition of population-based and registry-based epidemiological research in Denmark. The experienced researcher will complete a training program supervised by two recognised Danish research institutions with complementary expertise in the fields of epidemiology and genetics, respectively. Hereby the experienced researcher will achieve competences in the field of statistical modelling of epidemiological data with repeated measures and use of the unique Danish registries for research. Furthermore, during the secondment at the partner institution the experienced researcher will receive training in genetic epidemiology. In return, knowledge of metabolomics will be translated to the beneficiary and partner organizations. It is expected that the results will provide novel insights into the pathophysiology of diabetes and thyroid disease and identify novel biomarkers to improve risk prediction in individuals.
Оригинален текст от CORDIS (на английски).
Участници
- REGION HOVEDSTADEN · HillerodКоординаторДания
Връзки
- Виж в CORDIS
- DOI: 10.3030/657595
- https://www.regionh.dk/fcfs/befolkningsbaseret-epidemiologi/samarbejder/Sider/Metabolomics.aspx
Данни: CORDIS, © Европейски съюз
