Evidence map›Paper›PMID 38495599›Full record

ArticleKidney medicine2024

Serum Metabolomic Markers of Protein-Rich Foods and Incident CKD: Results From the Atherosclerosis Risk in Communities Study.

Lauren Bernard, Jingsha Chen, Hyunju Kim, Kari E Wong, Lyn M Steffen, Bing Yu, Eric Boerwinkle, Andrew S Levey, Morgan E Grams, Eugene P Rhee and 1 more

Open access · goldAbstract read
In one paragraph

Article in Kidney medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.7field-weighted citation impact, top 11% 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.

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

7 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. The Role of Precision Nutrition in Kidney Disease.Clinical journal of the American Society of Nephrology : CJASN · 2026
    Review
  3. Review
  4. Review
  5. Association of Dietary Micronutrient Intake and the Metabolome in Children with CKD.Clinical journal of the American Society of Nephrology : CJASN · 2025
    Article
  6. Review
  7. 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

11 authors at 6 institutions in 1 country.

Lauren BernardDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Jingsha ChenDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Hyunju KimDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Kari E WongMetabolon, Research Triangle Park, Morrisville, NC.
Lyn M SteffenDivision of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN.
Bing YuDepartment of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX.
Eric BoerwinkleDepartment of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX.
Andrew S LeveyDivision of Nephrology, Tufts Medical Center, Boston, MA.
Morgan E GramsDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Eugene P RheeNephrology Division and Endocrine Unit, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
Casey M RebholzDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Johns Hopkins University · USThe University of Texas Health Science Center at Houston · USHarvard University · USMinnesota Department of Health · USTriangle · USTufts Medical Center · US

Funding

Proteomic and epigenetic alterations associated with plant-based diets and CVDK01HL168232 · NHLBI · UNIVERSITY OF WASHINGTON · PI Hyunju Kim · 2023 to 2026
$683k
NHLBI NIH HHS K01 HL168232
6 · The paper itself

Abstract

Rationale & Objective: While urine excretion of nitrogen estimates the total protein intake, biomarkers of specific dietary protein sources have been sparsely studied. Using untargeted metabolomics, this study aimed to identify serum metabolomic markers of 6 protein-rich foods and to examine whether dietary protein-related metabolites are associated with incident chronic kidney disease (CKD). Study Design: Prospective cohort study. Setting & Participants: A total of 3,726 participants from the Atherosclerosis Risk in Communities study without CKD at baseline. Exposures: Dietary intake of 6 protein-rich foods (fish, nuts, legumes, red and processed meat, eggs, and poultry), serum metabolites. Outcomes: Incident CKD (estimated glomerular filtration rate < 60 mL/min/1.73 m Analytical Approach: Multivariable linear regression models estimated cross-sectional associations between protein-rich foods and serum metabolites. C statistics assessed the ability of the metabolites to improve the discrimination of highest versus lower 3 quartiles of intake of protein-rich foods beyond covariates (demographics, clinical factors, health behaviors, and the intake of nonprotein food groups). Cox regression models identified prospective associations between protein-related metabolites and incident CKD. Results: Thirty significant associations were identified between protein-rich foods and serum metabolites (fish, n = 8; nuts, n = 5; legumes, n = 0; red and processed meat, n = 5; eggs, n = 3; and poultry, n = 9). Metabolites collectively and significantly improved the discrimination of high intake of protein-rich foods compared with covariates alone (difference in C statistics = 0.033, 0.051, 0.003, 0.024, and 0.025 for fish, nuts, red and processed meat, eggs, and poultry-related metabolites, respectively; Limitations: Residual confounding and sample-storage duration. Conclusions: We identified candidate biomarkers of fish, nuts, red and processed meat, eggs, and poultry. A fish-related metabolite, 1-docosahexaenoylglycerophosphocholine (22:6n3), was associated with a lower risk of CKD.

Indexed as

Chronic kidney diseasedietary proteinmetabolomicsprotein sources

Identifiers

PMID38495599
PMCPMC10940775
OpenAlexW4391888797

What OpenQuestion 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 OpenQuestion graph.