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Baron C, Cherkaoui S, Therrien-Laperriere S, Ilboudo Y, Poujol R, Mehanna P, Garrett ME, Telen MJ, Ashley-Koch AE, Bartolucci P, Rioux JD, Lettre G, Des Rosiers C, Ruiz M, Hussin JG. Gene-metabolite annotation with shortest reactional distance enhances metabolite genome-wide association studies results. bioRxiv 2023:2023.03.22.533869. [PMID: 36993181 PMCID: PMC10055409 DOI: 10.1101/2023.03.22.533869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Studies combining metabolomics and genetics, known as metabolite genome-wide association studies (mGWAS), have provided valuable insights into our understanding of the genetic control of metabolite levels. However, the biological interpretation of these associations remains challenging due to a lack of existing tools to annotate mGWAS gene-metabolite pairs beyond the use of conservative statistical significance threshold. Here, we computed the shortest reactional distance (SRD) based on the curated knowledge of the KEGG database to explore its utility in enhancing the biological interpretation of results from three independent mGWAS, including a case study on sickle cell disease patients. Results show that, in reported mGWAS pairs, there is an excess of small SRD values and that SRD values and p-values significantly correlate, even beyond the standard conservative thresholds. The added-value of SRD annotation is shown for identification of potential false negative hits, exemplified by the finding of gene-metabolite associations with SRD ≤1 that did not reach standard genome-wide significance cut-off. The wider use of this statistic as an mGWAS annotation would prevent the exclusion of biologically relevant associations and can also identify errors or gaps in current metabolic pathway databases. Our findings highlight the SRD metric as an objective, quantitative and easy-to-compute annotation for gene-metabolite pairs that can be used to integrate statistical evidence to biological networks.
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Affiliation(s)
- Cantin Baron
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Québec, Canada
- Montreal Heart Institute, Québec, Canada
| | - Sarah Cherkaoui
- Montreal Heart Institute, Québec, Canada
- Division of Oncology and Children’s Research Center, University Children’s Hospital Zurich, University of Zurich, Switzerland
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Center, Université Paris-Saclay, Villejuif, France
| | | | - Yann Ilboudo
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Québec, Canada
- Montreal Heart Institute, Québec, Canada
| | | | | | - Melanie E. Garrett
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Marilyn J. Telen
- Division of Hematology, Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | | | - Pablo Bartolucci
- Université Paris Est Créteil, Hôpitaux Universitaires Henri Mondor, APHP, Sickle cell referral center – UMGGR, Créteil, France
- Université Paris Est Créteil, IMRB, Laboratory of excellence LABEX, Créteil, France
| | - John D. Rioux
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Québec, Canada
- Montreal Heart Institute, Québec, Canada
- Département de Médecine, Université de Montréal, Québec, Canada
| | - Guillaume Lettre
- Montreal Heart Institute, Québec, Canada
- Département de Médecine, Université de Montréal, Québec, Canada
| | - Christine Des Rosiers
- Département de Biochimie et de Médecine Moléculaire, Université de Montréal, Québec, Canada
- Montreal Heart Institute, Québec, Canada
- Département de Nutrition, Université de Montréal, Québec, Canada
| | - Matthieu Ruiz
- Montreal Heart Institute, Québec, Canada
- Département de Nutrition, Université de Montréal, Québec, Canada
| | - Julie G. Hussin
- Montreal Heart Institute, Québec, Canada
- Département de Médecine, Université de Montréal, Québec, Canada
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