Evidence map›Paper›PMID 39530122›Full record

ArticleFrontiers in endocrinology2024

A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity.

John S House, Joseph H Breeyear, Farida S Akhtari, Violet Evans, John B Buse, James Hempe, Alessandro Doria, Josyf C Mychaleckyi, Vivian Fonseca, Mengyao Shi and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

John S HouseBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States.
Joseph H BreeyearBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States.
Farida S AkhtariBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States.
Violet EvansBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States.
John B BuseDivision of Endocrinology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, United States.
James HempeDepartment of Pediatrics, Louisiana State University School of Medicine, New Orleans, LA, United States.
Alessandro DoriaSection on Genetics and Epidemiology, Joslin Diabetes Center and Department of Medicine, Harvard Medical School, Boston, MA, United States.
Josyf C MychaleckyiCenter of Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA, United States.
Vivian FonsecaSection of Endocrinology, School of Medicine, Tulane University, New Orleans, LA, United States.
Mengyao ShiDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States.
Changwei LiDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States.
Shuqian LiuBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States.
Tanika N KellyDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States.
Daniel RotroffDepartment of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States.
Alison A Motsinger-ReifBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: We investigated the genetic determinants of variation in the hemoglobin glycation index (HGI), an emerging biomarker for the risk of diabetes complications. Methods: We conducted a genome-wide association study (GWAS) for HGI in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial ( Results: In ACCORD, we identified single nucleotide polymorphisms (SNPs) associated with HGI, including a peak with the strongest association at the intergenic SNP Discussion: Many HGI-associated SNPs were distinct from those associated with fasting plasma glucose or HbA1c, lending further support for HGI as a distinct biomarker of diabetes complications. The results of this first evaluation of the genetic etiology of HGI indicate that it is highly heritable and point to heterogeneity by sex and race.

Indexed as

Genome-Wide Association StudyGlycated HemoglobinPolymorphism, Single NucleotideAgedBiomarkersDiabetes Mellitus, Type 2EthnicityFemaleGenetic Predisposition to DiseaseGenotypeHumansMaleMiddle AgedSex FactorsBiomarkersGlycated HemoglobinACCORDARICgenome-wide association studyGWASHbA1chemoglobin glycation indexHGI

Identifiers

PMID39530122
PMCPMC11551017

What Socratic holds

Textmetadata
LicenceCC BY
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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.