Evidence map›Paper›PMID 38039081›Full record

SynthesisThe Journal of clinical endocrinology and metabolism2024

Genetic Risk Scores Identify People at High Risk of Developing Diabetic Kidney Disease: A Systematic Review.

Aleena Shujaat Ali, Cecilia Pham, Grant Morahan, Elif Ilhan Ekinci

Abstract readSystematic Review
In one paragraph

Synthesis in The Journal of clinical endocrinology and metabolism, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
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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

4 authors.

Aleena Shujaat AliDepartment of Medicine, The University of Melbourne, Melbourne 3084, Australia.ORCID 0000-0002-1485-9153
Cecilia PhamDepartment of Medicine, The University of Melbourne, Melbourne 3084, Australia.
Grant MorahanAustralian Centre for Accelerating Diabetes Innovations, The University of Melbourne, Melbourne 3000, Australia.
Elif Ilhan EkinciDepartment of Medicine, The University of Melbourne, Melbourne 3084, Australia.ORCID 0000-0003-2372-395X

Funding

Diabetes Australian Research Programme Y22G-ALIA
6 · The paper itself

Abstract

contextDiabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Measures to prevent and treat DKD require better identification of patients most at risk. In this systematic review, we summarize the existing evidence of genetic risk scores (GRSs) and their utility for predicting DKD in people with type 1 or type 2 diabetes. EVIDENCE ACQUISITION: We searched MEDLINE, Embase, Web of Science, and Cochrane Reviews in June 2022 to identify all existing and relevant literature. Main data items sought were study design, sample size, population, single nucleotide polymorphisms of interest, DKD-related outcomes, and relevant summary measures of result. The Critical Appraisal Skills Programme checklist was used to evaluate the methodological quality of studies. EVIDENCE SYNTHESIS: We identified 400 citations of which 15 are included in this review. Overall, 7 studies had positive results, 5 had mixed results, and 3 had negative results. Most studies with the strongest methodological quality (n = 9) reported statistically significant and favourable findings of a GRS's association with at least 1 measure of DKD.

conclusionThis systematic review presents evidence of the utility of GRSs to identify people with diabetes that are at high risk of developing DKD. In practice, a robust GRS could be used at the first clinical encounter with a person living with diabetes in order to stratify their risk of complications. Further prospective research is needed.

Indexed as

Diabetic NephropathiesGenetic Predisposition to DiseaseDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2Genetic Risk ScoreHumansPolymorphism, Single NucleotideRisk AssessmentRisk Factorsdiabetic kidney diseasegenetic risk scorepolygenic risk score

Identifiers

PMID38039081
PMCPMC11031242

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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.