Evidence map›Paper›PMID 39927731›Full record

ArticleHuman molecular genetics2025

Genetic analysis of elevated levels of creatinine and cystatin C biomarkers reveals novel genetic loci associated with kidney function.

Matteo D'Antonio, Timothy D Arthur, Wilfredo G Gonzalez Rivera, Ximei Wu, Jennifer P Nguyen, Melissa Gymrek, Park Woo-Yeong, Kelly A Frazer

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Human molecular genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Admixture mapping identifies complex trait associations with local ancestry in themedRxiv : the preprint server for health sciences · 2025
    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

8 authors.

Matteo D'AntonioDivision of Biomedical Informatics, Department of Medicine, University of California San Diego, 9500 Gilman Dr., La Jolla, CA 92093, United States.ORCID 0000-0001-5844-6433
Timothy D ArthurDivision of Biomedical Informatics, Department of Medicine, University of California San Diego, 9500 Gilman Dr., La Jolla, CA 92093, United States.
Wilfredo G Gonzalez RiveraDivision of Biomedical Informatics, Department of Medicine, University of California San Diego, 9500 Gilman Dr., La Jolla, CA 92093, United States.
Ximei WuDivision of Biomedical Informatics, Department of Medicine, University of California San Diego, 9500 Gilman Dr., La Jolla, CA 92093, United States.
Jennifer P NguyenDivision of Biomedical Informatics, Department of Medicine, University of California San Diego, 9500 Gilman Dr., La Jolla, CA 92093, United States.
Melissa GymrekDivision of Biomedical Informatics, Department of Medicine, University of California San Diego, 9500 Gilman Dr., La Jolla, CA 92093, United States.
Park Woo-YeongDivision of Nephrology, Department of Internal Medicine, Keimyung University School of Medicine, Keimyung University Dongsan Hospital, 1035 Dalgubeol-daero, Daegu, Republic of Korea.
Kelly A FrazerDepartment of Pediatrics, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, United States.

Funding

Genetic & Social Determinants of Health: Center for Admixture Science and TechnologyRM1HG011558 · NHGRI · YALE UNIVERSITY · PI FRAZER, KELLY A, GYMREK, MELISSA · 2021 to 2025
$11.2M
San Diego Biomedical Informatics Education & Research (SABER)T15LM011271 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SHAMIM NEMATI · 2012 to 2026
$9.7M
Pancreas cell type-specific regulatory variants and T2D disease risk associationF31DK131867 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI NGUYEN, JENNIFER PHUONG · 2022 to 2023
$80k
Cardiac stage-specific regulatory variants and their disease risk associationF31HL158198 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ARTHUR, TIMOTHY DONALD · 2021 to 2022
$79k
Alfred P. Sloan Foundation's Minority G-2022-10127National Research Foundation of Korea 2021R1F1A1061572NHGRI NIH HHS RM1 HG011558NHLBI NIH HHS F31 HL158198NIDDK NIH HHS F31 DK131867NIH HHS F31DK131867NIH HHS RM1HG011558NLM NIH HHS T15 LM011271
6 · The paper itself

Abstract

The rising prevalence of chronic kidney disease (CKD), affecting an estimated 37 million adults in the United States, presents a significant global health challenge. CKD is typically assessed using estimated Glomerular Filtration Rate (eGFR), which incorporates serum levels of biomarkers such as creatinine and cystatin C. However, these biomarkers do not directly measure kidney function; their elevation in CKD results from diminished glomerular filtration. Genome-wide association studies (GWAS) based on eGFR formulas using creatinine (eGFRcre) or cystatin C (eGFRcys) have identified distinct non-overlapping loci, raising questions about whether these loci govern kidney function or biomarker metabolism. In this study, we show that GWAS on creatinine and cystatin C levels in healthy individuals reveal both nonoverlapping genetic loci impacting their metabolism as well as overlapping genetic loci associated with kidney function; whereas GWAS on elevated levels of these biomarkers uncover novel loci primarily associated with kidney function in CKD patients.

Indexed as

CreatinineCystatin CGenetic LociKidneyRenal Insufficiency, ChronicAdultAgedBiomarkersFemaleGenome-Wide Association StudyGlomerular Filtration RateHumansMaleMiddle AgedPolymorphism, Single NucleotideBiomarkersCreatinineCystatin Ccreatininecystatin Cgenome-wide association studieskidney function, chronic kidney disease

Identifiers

PMID39927731
PMCPMC12010162

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Registered trials

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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.