Evidence map›Paper›PMID 30944665›Full record

SynthesisDisease markers2019

Systematic Meta-analysis Revealed an Association of PGC-1

Wanning Xia, Nanxing Chen, Wenjia Peng, Xianjie Jia, Ying Yu, Xuesen Wu, Huaiquan Gao

Open access · hybridAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Disease markers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 22% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Role of theGenes · 2024
    Review
  4. Heliyon · 2024
    Article
  5. Review
  6. Article
  7. Neurobiological Opportunities in Diabetic Polyneuropathy.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2021
    Review
  8. 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

7 authors at 1 institution in 1 country.

Wanning XiaSchool of Public Health, Bengbu Medical University, Bengbu, Anhui 233030, China.ORCID 0000-0001-5783-459X
Nanxing ChenSchool of Public Health, Bengbu Medical University, Bengbu, Anhui 233030, China.
Wenjia PengSchool of Public Health, Bengbu Medical University, Bengbu, Anhui 233030, China.
Xianjie JiaSchool of Public Health, Bengbu Medical University, Bengbu, Anhui 233030, China.ORCID 0000-0002-2707-1170
Ying YuDepartment of Physiology, Bengbu Medical University, Bengbu, Anhui 233030, China.ORCID 0000-0003-0925-0148
Xuesen WuSchool of Public Health, Bengbu Medical University, Bengbu, Anhui 233030, China.ORCID 0000-0001-8438-9380
Huaiquan GaoSchool of Public Health, Bengbu Medical University, Bengbu, Anhui 233030, China.ORCID 0000-0001-9318-4475
Bengbu Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenome-wide association study (GWAS) provides an unprecedented opportunity to reveal substantial genetic contribution to type 2 diabetes mellitus (T2DM) and glycemic identification of allelic heterogeneity and population-specific genetic variants, yet it also faces difficulty due to the vast amount of potential confounding factors and limited availability of clinical data. To identify responsible susceptibility loci and genomic polymorphism for T2DM and glycemic traits, we have systematically investigated a genome-wide association study related to T2DM. Although GWAS has captured many common genetic variations, which are related to T2DM, each risk allele (RA) of single-nucleotide polymorphisms (SNPs) at these loci is not conclusive. Therefore, it is common to present a combination of several SNPs to infer T2DM risk, yet it is still insufficient to be deterministic. To streamline the identification of a deterministic genetic variation in T2DM, we developed this meta-analysis as a showcase to comprehensively identify the association between cumulative RAs and T2DM risk by combining different studies in reported literature and databases. After all, we identified that PGC-1

methodsWe performed comprehensive information retrieval and knowledge discovery meta-analysis by searching extensively published literature and different electronic databases to acquire eligible studies for the above association study. We developed a method to use pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) in five genetic models (allelic, dominant, recessive, homozygous, and heterozygous genetic models) to identify the relationship among ethnicity subgroup analyses comprehensively.

resultsWe identified 20 eligible studies consisting of 16,182 subjects (8,038 cases and 8,144 controls) in our meta-analysis. PGC-1

conclusionOur development of meta-analysis revealed that the minor allele (A) carriers, especially AA genotype carriers, can lead to risk of T2DM in the Caucasian and Indian populations. This is the first report that such risk has been confirmed. Our finding shed new light into the genetic alteration in T2DM.

Indexed as

Polymorphism, Single NucleotideDiabetes Mellitus, Type 2HumansPeroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alphaPeroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alphaPPARGC1A protein, human

Identifiers

PMID30944665
PMCPMC6421808
OpenAlexW2920124160

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.