Nat Commun. 2024 Aug 19. 15(1): 7111
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,
Karsten Suhre.
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.