A roadmap to the molecular human linking multiomics with population traits and diabetes subtypes

Anna Halama (), Shaza Zaghlool, Gaurav Thareja, Sara Kader, Wadha Al Muftah, Marjonneke Mook-Kanamori, Hina Sarwath, Yasmin Ali Mohamoud, Nisha Stephan, Sabine Ameling, Maja Pucic Baković, Jan Krumsiek, Cornelia Prehn, Jerzy Adamski, Jochen M. Schwenk, Nele Friedrich, Uwe Völker, Manfred Wuhrer, Gordan Lauc, S. Hani Najafi-Shoushtari, Joel A. Malek, Johannes Graumann, Dennis Mook-Kanamori, Frank Schmidt and Karsten Suhre ()
Additional contact information
Anna Halama: Weill Cornell Medicine-Qatar, Education City
Shaza Zaghlool: Weill Cornell Medicine-Qatar, Education City
Gaurav Thareja: Weill Cornell Medicine-Qatar, Education City
Sara Kader: Weill Cornell Medicine-Qatar, Education City
Wadha Al Muftah: Innovation Center
Marjonneke Mook-Kanamori: Weill Cornell Medicine
Hina Sarwath: Weill Cornell Medicine-Qatar, Education City
Yasmin Ali Mohamoud: Weill Cornell Medicine-Qatar, Education City
Nisha Stephan: Weill Cornell Medicine-Qatar, Education City
Sabine Ameling: University Medicine Greifswald
Maja Pucic Baković: Genos Glycoscience Research Laboratory
Jan Krumsiek: Weill Cornell Medicine
Cornelia Prehn: Helmholtz Zentrum München
Jerzy Adamski: Helmholtz Zentrum München, German Research Center for Environmental Health
Jochen M. Schwenk: KTH Royal Institute of Technology
Nele Friedrich: University Medicine Greifswald
Uwe Völker: University Medicine Greifswald
Manfred Wuhrer: Leiden University Medical Center
Gordan Lauc: Genos Glycoscience Research Laboratory
S. Hani Najafi-Shoushtari: Weill Cornell Medicine-Qatar, Education City
Joel A. Malek: Weill Cornell Medicine
Johannes Graumann: Philipps-Universität Marburg
Dennis Mook-Kanamori: Leiden University Medical Center
Frank Schmidt: Weill Cornell Medicine-Qatar, Education City
Karsten Suhre: Weill Cornell Medicine-Qatar, Education City

Nature Communications, 2024, vol. 15, issue 1, 1-23

Abstract: Abstract 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.

Date: 2024
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DOI: 10.1038/s41467-024-51134-x

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