Evidence map›Paper›PMID 39160153›Full record

ArticleNature communications2024

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 and 15 more

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Special Issue "Molecular Progression in Genome-Related Diseases".International journal of molecular sciences · 2026
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  10. Review
  11. Article
  12. Review
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  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

25 authors.

Anna HalamaBioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar. amh2025@qatar-med.cornell.edu.ORCID 0000-0003-4910-6255
Shaza ZaghloolBioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.ORCID 0000-0002-9132-8030
Gaurav TharejaBioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.ORCID 0000-0003-2277-6400
Sara KaderBioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.
Wadha Al MuftahQatar Genome Program, Qatar Foundation, Qatar Science and Technology Park, Innovation Center, Doha, Qatar.ORCID 0000-0003-2549-082X
Marjonneke Mook-KanamoriDepartment of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
Hina SarwathProteomics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.
Yasmin Ali MohamoudGenomics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.
Nisha StephanBioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.
Sabine AmelingGerman Centre for Cardiovascular Research, Partner Site Greifswald, University Medicine Greifswald, Greifswald, Germany.ORCID 0000-0002-3095-8362
Maja Pucic BakovićGenos Glycoscience Research Laboratory, Zagreb, Croatia.ORCID 0000-0003-0866-623X
Jan KrumsiekDepartment of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.ORCID 0000-0003-4734-3791
Cornelia PrehnMetabolomics and Proteomics Core, Helmholtz Zentrum München, Neuherberg, Germany.ORCID 0000-0002-1274-4715
Jerzy AdamskiInstitute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.ORCID 0000-0001-9259-0199
Jochen M SchwenkScience for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden.ORCID 0000-0001-8141-8449
Nele FriedrichGerman Centre for Cardiovascular Research, Partner Site Greifswald, University Medicine Greifswald, Greifswald, Germany.
Uwe VölkerGerman Centre for Cardiovascular Research, Partner Site Greifswald, University Medicine Greifswald, Greifswald, Germany.ORCID 0000-0002-5689-3448
Manfred WuhrerCenter for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands.ORCID 0000-0002-0814-4995
Gordan LaucGenos Glycoscience Research Laboratory, Zagreb, Croatia.
S Hani Najafi-ShoushtariMicroRNA Core Laboratory, Division of Research, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.
Joel A MalekDepartment of Genetic Medicine, Weill Cornell Medicine, Doha, Qatar.ORCID 0000-0002-1516-8477
Johannes GraumannInstitute of Translational Proteomics, Department of Medicine, Philipps-Universität Marburg, Marburg, Germany.ORCID 0000-0002-3015-5850
Dennis Mook-KanamoriDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
Frank SchmidtProteomics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar.
Karsten SuhreBioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar. kas2049@qatar-med.cornell.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

PhenotypeAdultCpG IslandsDiabetes MellitusDiabetes Mellitus, Type 2DNA MethylationEpigenomeFemaleGenome-Wide Association StudyHumansMaleMetabolomicsMiddle AgedMultiomicsQatarTranscriptome

Identifiers

PMID39160153
PMCPMC11333501

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.