Halama, A.* ; Zaghlool, S.* ; Thareja, G.* ; Kader, S.* ; Al Muftah, W.A.* ; Mook-Kanamori, M.J.* ; Sarwath, H.* ; Mohamoud, Y.A.* ; Stephan, N.* ; Ameling, S.* ; Pucic Baković, M.* ; Krumsiek, J.* ; Prehn, C. ; Adamski, J. ; Schwenk, J.M.* ; Friedrich, N.* ; Völker, U.* ; Wuhrer, M.* ; Lauc, G.* ; Najafi-Shoushtari, S.H.* ; Malek, J.A.* ; Graumann, J.* ; Mook-Kanamori, D.* ; Schmidt, F.* ; Suhre, K.*
A roadmap to the molecular human linking multiomics with population traits and diabetes subtypes.
Nat. Commun. 15:7111 (2024)
In-depth multiomic phenotyping provides molecular insights into complex physiological processes and their pathologies. Here, we report on integrating 18 diverse deep molecular phenotyping (omics-) technologies applied to urine, blood, and saliva samples from 391 participants of the multiethnic diabetes Qatar Metabolomics Study of Diabetes (QMDiab). Using 6,304 quantitative molecular traits with 1,221,345 genetic variants, methylation at 470,837 DNA CpG sites, and gene expression of 57,000 transcripts, we determine (1) within-platform partial correlations, (2) between-platform mutual best correlations, and (3) genome-, epigenome-, transcriptome-, and phenome-wide associations. Combined into a molecular network of > 34,000 statistically significant trait-trait links in biofluids, our study portrays "The Molecular Human". We describe the variances explained by each omics in the phenotypes (age, sex, BMI, and diabetes state), platform complementarity, and the inherent correlation structures of multiomics data. Further, we construct multi-molecular network of diabetes subtypes. Finally, we generated an open-access web interface to "The Molecular Human" ( http://comics.metabolomix.com ), providing interactive data exploration and hypotheses generation possibilities.
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Publication type
Article: Journal article
Document type
Scientific Article
Thesis type
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Keywords
Dna Methylation; Association; Insulin; Urine; Blood; Database; Serum; Identification; Glycosylation; Translation
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Language
english
Publication Year
2024
Prepublished in Year
0
HGF-reported in Year
2024
ISSN (print) / ISBN
2041-1723
e-ISSN
2041-1723
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Volume: 15,
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Article Number: 7111
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Nature Publishing Group
Publishing Place
London
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Peer reviewed
POF-Topic(s)
30505 - New Technologies for Biomedical Discoveries
30201 - Metabolic Health
Research field(s)
Enabling and Novel Technologies
Genetics and Epidemiology
PSP Element(s)
A-630710-001
G-500600-001
Grants
Qatar National Research Fund (QNRF)
Biomedical Research Program at Weill Cornell Medicine in Qatar - Qatar Foundation
Doha, Qatar
Copyright
Erfassungsdatum
2024-09-03