Evidence map›Paper›PMID 28659805›Full record

ArticleFrontiers in pharmacology2017

Statins and New-Onset Diabetes Mellitus: LDL Receptor May Provide a Key Link.

Qi Yu, Ying Chen, Cang-Bao Xu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

17 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
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  4. Therapeutic Gene Editing in Dyslipidemias.Reviews in cardiovascular medicine · 2024
    Review
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  14. Serum aromatic and branched-chain amino acids associated with NASH demonstrate divergent associations with serum lipids.Liver international : official journal of the International Association for the Study of the Liver · 2021
    Article
  15. Article
  16. Article
  17. 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

3 authors at 1 institution in 1 country.

Qi YuInstitute of Basic and Translational Medicine, Xi'an Medical UniversityXi'an, China.
Ying ChenInstitute of Basic and Translational Medicine, Xi'an Medical UniversityXi'an, China.
Cang-Bao XuInstitute of Basic and Translational Medicine, Xi'an Medical UniversityXi'an, China.
Xi'an Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous studies have noted that populations treated with statins have increased risk for new-onset diabetes mellitus; however, the underlying molecular mechanisms are not fully understood. Interestingly, familial hypercholesterolemia (FH) patients with mutations in the low-density lipoprotein receptor (LDLR) gene are protected against diabetes mellitus (DM), despite these patients being subjected to long-term statin therapy. Since the common pathway between FH and statin therapy is LDLR-mediated cellular cholesterol uptake, the arising question is whether the LDLR plays an important role in the diabetogenic effect of statins. Indeed, given that statins can regulate the LDLR expression in liver and peripheral tissue, there is a possible mechanism that the increased LDLR causes cellular cholesterol accumulation and dysfunction in pancreatic islets, explaining why statins fail to increase the risk of DM in FH patients. In this paper, with regarded to recent literatures, we highlight the role of LDLR in the pathophysiology of cholesterol-induced pancreatic islets dysfunction, which may provide the key link between statins treatment and the increased risk of new-onset diabetes mellitus.

Indexed as

familial hypercholesterolemiaisletlow-density lipoprotein receptorstatintype 2 diabetes mellitus

Identifiers

PMID28659805
PMCPMC5468445
OpenAlexW2626787342

What OpenQuestion holds

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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.