Evidence map›Paper›PMID 32439301›Full record

ReviewTrends in molecular medicine2020

Multitissue Multiomics Systems Biology to Dissect Complex Diseases.

Xia Yang

Abstract readReview
In one paragraph

Review in Trends in molecular medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. PLAID: ultrafast single-sample gene set enrichment scoring.Bioinformatics (Oxford, England) · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. Non-Coding RNAs Extended Omnigenic Module of Cancers.Entropy (Basel, Switzerland) · 2024
    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

1 author.

Xia YangDepartment of Integrative Biology and Physiology, University of California, Los Angeles, CA, USA. Electronic address: xyang123@ucla.edu.

Funding

Translational Research Support CoreP30ES007048 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ROB S MCCONNELL · 1996 to 2026
$46.4M
Systems Genetics Dissection of Non-alcoholic SteatohepatitisR01DK117850 · NIDDK · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Aldons Jake Lusis · 2019 to 2026
$4.6M
Precision Medicine Approach: Using genomic information to guide TBI treatmentR01NS111378 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GOMEZ-PINILLA, FERNANDO, YANG, XIA · 2020 to 2024
$2.9M
Spatiotemporal Molecular Substrates of TBI at Single Cell ResolutionR01NS117148 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GOMEZ-PINILLA, FERNANDO, WOLLMAN, ROY · 2020 to 2024
$2.8M
DHA Reverses Gene Network Signatures of Fructose-induced Metabolic SyndromeR01DK104363 · NIDDK · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI YANG, XIA · 2015 to 2019
$2.4M
Toxicological Profiling of Engineered Nanomaterials (ENMs) in the MPS (RES)U01ES027237 · NIEHS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI NEL, ANDRE ELIAS, XIA, TIAN · 2016 to 2020
$2.2M
LncRNA Transcriptional Mechanisms of Coronary Artery Disease RiskR01HL145708 · NHLBI · STANFORD UNIVERSITY · PI QUERTERMOUS, THOMAS · 2019 to 2022
$1.6M
Cell-specific novel genomic biomarkers of TBI pathologyR21NS103088 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GOMEZ-PINILLA, FERNANDO, YANG, XIA · 2017 to 2018
$406k
NHLBI NIH HHS R01 HL145708NIDDK NIH HHS R01 DK104363NIDDK NIH HHS R01 DK117850NIEHS NIH HHS P30 ES007048NIEHS NIH HHS U01 ES027237NINDS NIH HHS R01 NS111378NINDS NIH HHS R01 NS117148NINDS NIH HHS R21 NS103088
6 · The paper itself

Abstract

Most complex diseases involve genetic and environmental risk factors, engage multiple cells and tissues, and follow a polygenic or omnigenic model depicting numerous genes contributing to pathophysiology. These multidimensional complexities pose challenges to traditional approaches that examine individual factors. In turn, multitissue multiomics systems biology has emerged to comprehensively elucidate within- and cross-tissue molecular networks underlying gene-by-environment interactions and contributing to complex diseases. The power of systems biology in retrieving novel insights and formulating new hypotheses has been well documented. However, the field faces various challenges that call for debate and action. In this opinion article, I discuss the concepts, benefits, current state, and challenges of the field and point to the next steps toward network-based systems medicine.

Indexed as

AnimalsComputational BiologyGene-Environment InteractionGenesGenomicsHumansSystems Biologycomplex diseasesgene-by-environment interactionsmultiomicsmultitissuenetworkssystems biology

Identifiers

PMID32439301
PMCPMC7395877

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.