Evidence map›Paper›PMID 39496618›Full record

ArticleScientific reports2024

Metabolite and protein associations with general health in the population-based CHRIS study.

Essi Hantikainen, Christian X Weichenberger, Nikola Dordevic, Vinicius Verri Hernandes, Luisa Foco, Martin Gögele, Roberto Melotti, Cristian Pattaro, Markus Ralser, Fatma Amari and 5 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

15 authors.

Essi HantikainenInstitute for Biomedicine, Eurac Research, Bolzano, Italy. essimarjatta.hantikainen@eurac.edu.
Christian X WeichenbergerInstitute for Biomedicine, Eurac Research, Bolzano, Italy.
Nikola DordevicInstitute for Biomedicine, Eurac Research, Bolzano, Italy.
Vinicius Verri HernandesDepartment of Food Chemistry and Toxicology, University of Vienna, Vienna, Austria.
Luisa FocoInstitute for Biomedicine, Eurac Research, Bolzano, Italy.
Martin GögeleInstitute for Biomedicine, Eurac Research, Bolzano, Italy.
Roberto MelottiInstitute for Biomedicine, Eurac Research, Bolzano, Italy.
Cristian PattaroInstitute for Biomedicine, Eurac Research, Bolzano, Italy.
Markus RalserDepartment of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Fatma AmariDepartment of Biochemistry, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Vadim FarztdinovCore Facility, High-Throughput Mass Spectrometry, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Michael MüllederCore Facility, High-Throughput Mass Spectrometry, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Peter P PramstallerInstitute for Biomedicine, Eurac Research, Bolzano, Italy.
Johannes RainerInstitute for Biomedicine, Eurac Research, Bolzano, Italy.
Francisco S DominguesInstitute for Biomedicine, Eurac Research, Bolzano, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying biomarkers able to discriminate individuals on different health trajectories is crucial to understand the molecular basis of age-related morbidity. We investigated multi-omics signatures of general health and organ-specific morbidity, as well as their interconnectivity. We examined cross-sectional metabolome and proteome data from 3,142 adults of the Cooperative Health Research in South Tyrol (CHRIS) study, an Alpine population study designed to investigate how human biology, environment, and lifestyle factors contribute to people's health over time. We had 174 metabolites and 148 proteins quantified from fasting serum and plasma samples. We used the Cumulative Illness Rating Scale (CIRS) Comorbidity Index (CMI), which considers morbidity in 14 organ systems, to assess health status (any morbidity vs. healthy). Omics-signatures for health status were identified using random forest (RF) classifiers. Linear regression models were fitted to assess directionality of omics markers and health status associations, as well as to identify omics markers related to organ-specific morbidity. Next to age, we identified 21 metabolites and 10 proteins as relevant predictors of health status and results confirmed associations for serotonin and glutamate to be age-independent. Considering organ-specific morbidity, several metabolites and proteins were jointly related to endocrine, cardiovascular, and renal morbidity. To conclude, circulating serotonin was identified as a potential novel predictor for overall morbidity.

Indexed as

BiomarkersHealth StatusAdultAgedAged, 80 and overCross-Sectional StudiesFemaleHumansMaleMetabolomeMiddle AgedProteomeBiomarkersProteomeAgingCHRIS studyComorbidityHealth statusMetabolomicsProteomics

Identifiers

PMID39496618
PMCPMC11535378

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.