Evidence map›Paper›PMID 35812273›Full record

ArticleKidney international reports2022

ACLY and CKD: A Mendelian Randomization Analysis.

Pedrum Mohammadi-Shemirani, Michael Chong, Nicolas Perrot, Marie Pigeyre, Gregory R Steinberg, Guillaume Paré, Joan C Krepinsky, Matthew B Lanktree

Open access · goldAbstract read
In one paragraph

Article in Kidney international reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

6 citing papers in PubMed, 6 citations in OpenAlex.

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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

8 authors at 4 institutions in 1 country.

Pedrum Mohammadi-ShemiraniDepartment of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada.
Michael ChongDepartment of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada.
Nicolas PerrotDepartment of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada.
Marie PigeyreDepartment of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada.
Gregory R SteinbergDivision of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
Guillaume ParéDepartment of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada.
Joan C KrepinskyCentre for Metabolism, Obesity, and Diabetes Research, McMaster University, Hamilton, Ontario, Canada.
Matthew B LanktreeDepartment of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada.
McMaster University · CAPopulation Health Research Institute · CASt. Joseph’s Healthcare Hamilton · CAThrombosis and Atherosclerosis Research Institute · CA

Funding

Medical Research Council MC_PC_17228Medical Research Council MC_QA137853
6 · The paper itself

Abstract

Introduction: Adenosine triphosphate-citrate lyase (ACLY) inhibition is a therapeutic strategy under investigation for atherosclerotic cardiovascular disease, nonalcoholic steatohepatitis, and metabolic syndrome. Mouse models suggest that ACLY inhibition could reduce inflammation and kidney fibrosis. Genetic analysis of ACLY in chronic kidney disease (CKD) has not been performed. Methods: We constructed a genetic instrument by selecting variants associated with Results: Conclusion: Mendelian randomization analyses revealed that genetically reduced ACLY expression was associated with reduced risk of CKD but had no effect on either eGFR or ACR. Further evaluation of ACLY in kidney disease is warranted.

Indexed as

chronic kidney diseasecitratefibrosisgenomicsMendelian randomization

Identifiers

PMID35812273
PMCPMC9263230
OpenAlexW4224239632

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.