Dataset Information

[Design of a genomic, environmental, microbial and metabolomic study on celiac disease: an approach to the future of personalized prevention of celiac disease].

ABSTRACT: Over recent years we have seen rising many clinical and scientific innovations about celiac disease (CE), however the most important innovation that will contribute to change the future of the research and clinic in this field is the natural history of the disease. For many years it has been though that a genetic predisposition and the exposure to gluten were necessary and sufficient to develop CE. Recent studies, however, suggest that the loss of tolerance to gluten may occur in any moment of life upon certain conditions. Furthermore, several environmental factors known to play a role in shaping the intestinal microflora have also been considered related to the development of CE. Delivery mode, the infant diet and the use of antibiotics are included among these factors. To this day no large scale studies have determined if and how the microbiome composition and its metabolomic profile may influence the loss of tolerance to gluten and the consequent development of CE. In this paper we describe a prospective, multi-centric and longitudinal study on infants at risk for CE that will use different techniques to better understand the role of the microbome during the first steps in the development of the autoimmune disease.

SUBMITTER: Serena G

PROVIDER: S-EPMC5479768 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Publications

[Design of a genomic, environmental, microbial and metabolomic study on celiac disease: an approach to the future of personalized prevention of celiac disease].

Serena Gloria G Leonard Maureen M MM Camhi Stephanie S Huedo-Medina Tania B TB Fasano Alessio A

Recenti progressi in medicina 20160601 6

Over recent years we have seen rising many clinical and scientific innovations about celiac disease (CE), however the most important innovation that will contribute to change the future of the research and clinic in this field is the natural history of the disease. For many years it has been though that a genetic predisposition and the exposure to gluten were necessary and sufficient to develop CE. Recent studies, however, suggest that the loss of tolerance to gluten may occur in any moment of l ...[more]

PMID: 27362724

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Project description:BackgroundGenomic prediction aims to leverage genome-wide genetic data towards better disease diagnostics and risk scores. We have previously published a genomic risk score (GRS) for celiac disease (CD), a common and highly heritable autoimmune disease, which differentiates between CD cases and population-based controls at a clinically-relevant predictive level, improving upon other gene-based approaches. HLA risk haplotypes, particularly HLA-DQ2.5, are necessary but not sufficient for CD, with at least one HLA risk haplotype present in up to half of most Caucasian populations. Here, we assess a genomic prediction strategy that specifically targets this common genetic susceptibility subtype, utilizing a supervised learning procedure for CD that leverages known HLA-DQ2.5 risk.MethodsUsing L1/L2-regularized support-vector machines trained on large European case-control datasets, we constructed novel CD GRSs specific to individuals with HLA-DQ2.5 risk haplotypes (GRS-DQ2.5) and compared them with the predictive power of the existing CD GRS (GRS14) as well as two haplotype-based approaches, externally validating the results in a North American case-control study.ResultsConsistent with previous observations, both the existing GRS14 and the GRS-DQ2.5 had better predictive performance than the HLA haplotype approaches. GRS-DQ2.5 models, based on directly genotyped or imputed markers, achieved similar levels of predictive performance (AUC = 0.718-0.73), which were substantially higher than those obtained from the DQ2.5 zygosity alone (AUC = 0.558), the HLA risk haplotype method (AUC = 0.634), or the generic GRS14 (AUC = 0.679). In a screening model of at-risk individuals, the GRS-DQ2.5 lowered the number of unnecessary follow-up tests for CD across most sensitivity levels. Relative to a baseline implicating all DQ2.5-positive individuals for follow-up, the GRS-DQ2.5 resulted in a net saving of 2.2 unnecessary follow-up tests for each justified test while still capturing 90 % of DQ2.5-positive CD cases.ConclusionsGenomic risk scores for CD that target genetically at-risk sub-groups improve predictive performance beyond traditional approaches and may represent a useful strategy for prioritizing individuals at increased risk of disease, thus potentially reducing unnecessary follow-up diagnostic tests.

Dataset Information

[Design of a genomic, environmental, microbial and metabolomic study on celiac disease: an approach to the future of personalized prevention of celiac disease].

Publications

[Design of a genomic, environmental, microbial and metabolomic study on celiac disease: an approach to the future of personalized prevention of celiac disease].

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