Evidence map›Paper›PMID 36658343›Full record

ArticleNature biomedical engineering2024

Multi-omics microsampling for the profiling of lifestyle-associated changes in health.

Xiaotao Shen, Ryan Kellogg, Daniel J Panyard, Nasim Bararpour, Kevin Erazo Castillo, Brittany Lee-McMullen, Alireza Delfarah, Jessalyn Ubellacker, Sara Ahadi, Yael Rosenberg-Hasson and 7 more

2 registry-linked trialsOpen access · hybridAbstract read
In one paragraph

Article in Nature biomedical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 60 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 1 pooled it
14.9field-weighted citation impact, top 1% of its field
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.

NCT06359197 early_phase1unknown statusnot on this map

Feasibility Study for Investigating the Effect of Caffeine Consumption on Protein Biomarkers Related to Cardiovascular Disease

TypeinterventionalSponsorHamilton Health Sciences CorporationRan2024 to 2025Enrolled36ConditionsHealthyArmsCaffeine Pill, Placebo, TASSO+ Device, Finger prick and collection on Whatman Protein 903 Saver Cards, Intravenous Sampling
NCT07617649 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Laboratory Based Identification of Heat Stress Biomarkers and Effective Cooling Interventions

TypeinterventionalSponsorStanford UniversityRan2026 to 2028Enrolled30ConditionsHyperthermiaArmsHand cooling table, Cooling bandana
3 · Its place in the literature

Who cites it

60 citing papers in PubMed, 1 synthesis or guideline pooled it, 97 citations in OpenAlex.

  1. Pooled it
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  6. Article
  7. Article
  8. Review
  9. Article
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  11. Single-Injection Multi-Omics Analysis by Direct Infusion Mass Spectrometry.Angewandte Chemie (International ed. in English) · 2026
    Article
  12. Article
  13. Article
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  15. Review
  16. Monocytes are biological sensors of aging and frailty in humans.bioRxiv : the preprint server for biology · 2026
    Article
  17. Article
  18. Review
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  20. Review
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

17 authors at 3 institutions in 1 country.

Xiaotao Shen *Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0002-9608-9964
Ryan Kellogg *Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Daniel J Panyard *Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0001-5480-4803
Nasim Bararpour *Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Kevin Erazo CastilloDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Brittany Lee-McMullenDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Alireza DelfarahDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Jessalyn UbellackerDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Sara AhadiDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Yael Rosenberg-HassonHuman Immune Monitoring Center, Microbiology and Immunology, Stanford University Medical Center, Stanford, CA, USA.
Ariel GanzDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0002-7173-2239
Kévin ContrepoisDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Basil MichaelDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Ian SimmsDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Chuchu WangHoward Hughes Medical Institute, Stanford University, Stanford, CA, USA.ORCID 0000-0003-2015-7331
Daniel HornburgDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Michael P SnyderDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA. mpsnyder@stanford.edu.ORCID 0000-0003-0784-7987
Stanford Medicine · USHoward Hughes Medical Institute · USStanford University · US

Funding

Longitudinal Multi-Omic Profiles to Reveal Mechanisms of Obesity-Mediated Insulin ResistanceR01DK110186 · NIDDK · STANFORD UNIVERSITY · PI MCLAUGHLIN, TRACEY, SNYDER, MICHAEL P. · 2017 to 2021
$3.2M
6 · The paper itself

Abstract

Current healthcare practices are reactive and use limited physiological and clinical information, often collected months or years apart. Moreover, the discovery and profiling of blood biomarkers in clinical and research settings are constrained by geographical barriers, the cost and inconvenience of in-clinic venepuncture, low sampling frequency and the low depth of molecular measurements. Here we describe a strategy for the frequent capture and analysis of thousands of metabolites, lipids, cytokines and proteins in 10 μl of blood alongside physiological information from wearable sensors. We show the advantages of such frequent and dense multi-omics microsampling in two applications: the assessment of the reactions to a complex mixture of dietary interventions, to discover individualized inflammatory and metabolic responses; and deep individualized profiling, to reveal large-scale molecular fluctuations as well as thousands of molecular relationships associated with intra-day physiological variations (in heart rate, for example) and with the levels of clinical biomarkers (specifically, glucose and cortisol) and of physical activity. Combining wearables and multi-omics microsampling for frequent and scalable omics may facilitate dynamic health profiling and biomarker discovery.

Indexed as

MultiomicsBiomarkersBiomarkers

Identifiers

PMID36658343
PMCPMC10805653
OpenAlexW4317498917

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.