Evidence map›Paper›PMID 37119971›Full record

ReviewMolecular & cellular proteomics : MCP2023

Multi-Omics Profiling for Health.

Mohan Babu, Michael Snyder

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Molecular & cellular proteomics : MCP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 215 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
215citing papers in PubMed, 5 pooled it
–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

215 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  12. Emerging technologies in the spatial proteomics landscape.Analytical and bioanalytical chemistry · 2026
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155 more citing papers are in PubMed but not listed here.

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

2 authors.

Mohan BabuDepartment of Genetics, Stanford University School of Medicine, Stanford, California, USA.
Michael SnyderDepartment of Genetics, Stanford University School of Medicine, Stanford, California, USA. Electronic address: mpsnyder@stanford.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The world has witnessed a steady rise in both non-infectious and infectious chronic diseases, prompting a cross-disciplinary approach to understand and treating disease. Current medical care focuses on treating people after they become patients rather than preventing illness, leading to high costs in treating chronic and late-stage diseases. Additionally, a "one-size-fits all" approach to health care does not take into account individual differences in genetics, environment, or lifestyle factors, decreasing the number of people benefiting from interventions. Rapid advances in omics technologies and progress in computational capabilities have led to the development of multi-omics deep phenotyping, which profiles the interaction of multiple levels of biology over time and empowers precision health approaches. This review highlights current and emerging multi-omics modalities for precision health and discusses applications in the following areas: genetic variation, cardio-metabolic diseases, cancer, infectious diseases, organ transplantation, pregnancy, and longevity/aging. We will briefly discuss the potential of multi-omics approaches in disentangling host-microbe and host-environmental interactions. We will touch on emerging areas of electronic health record and clinical imaging integration with muti-omics for precision health. Finally, we will briefly discuss the challenges in the clinical implementation of multi-omics and its future prospects.

Indexed as

GenomicsNeoplasmsHumansMetabolomicsMultiomicsProteomicsCOVID-19data integrationdietelectronic health recordexposomegenomicsgut microbiomelipidomicslongitudinalmetabolomicsomicsprecision healthproteomicstranscriptomicswearables

Identifiers

PMID37119971
PMCPMC10220275

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.