Evidence map›Paper›PMID 20714348›Full record

SynthesisPLoS genetics2010

Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits.

Ayellet V Segrè, DIAGRAM Consortium, MAGIC investigators, Leif Groop, Vamsi K Mootha, Mark J Daly, David Altshuler

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PLoS genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 305 papers, 31 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
305citing papers in PubMed, 31 pooled it
12.3field-weighted citation impact, top 1% 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

305 citing papers in PubMed, 31 syntheses or guidelines pooled it, 481 citations in OpenAlex.

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245 more citing papers are in PubMed but not listed here.

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 2 institutions in 2 countries.

Ayellet V SegrèBroad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
DIAGRAM Consortium
MAGIC investigators
Leif Groop
Vamsi K Mootha
Mark J Daly
David Altshuler
Broad Institute · USLund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mitochondrial dysfunction has been observed in skeletal muscle of people with diabetes and insulin-resistant individuals. Furthermore, inherited mutations in mitochondrial DNA can cause a rare form of diabetes. However, it is unclear whether mitochondrial dysfunction is a primary cause of the common form of diabetes. To date, common genetic variants robustly associated with type 2 diabetes (T2D) are not known to affect mitochondrial function. One possibility is that multiple mitochondrial genes contain modest genetic effects that collectively influence T2D risk. To test this hypothesis we developed a method named Meta-Analysis Gene-set Enrichment of variaNT Associations (MAGENTA; http://www.broadinstitute.org/mpg/magenta). MAGENTA, in analogy to Gene Set Enrichment Analysis, tests whether sets of functionally related genes are enriched for associations with a polygenic disease or trait. MAGENTA was specifically designed to exploit the statistical power of large genome-wide association (GWA) study meta-analyses whose individual genotypes are not available. This is achieved by combining variant association p-values into gene scores and then correcting for confounders, such as gene size, variant number, and linkage disequilibrium properties. Using simulations, we determined the range of parameters for which MAGENTA can detect associations likely missed by single-marker analysis. We verified MAGENTA's performance on empirical data by identifying known relevant pathways in lipid and lipoprotein GWA meta-analyses. We then tested our mitochondrial hypothesis by applying MAGENTA to three gene sets: nuclear regulators of mitochondrial genes, oxidative phosphorylation genes, and approximately 1,000 nuclear-encoded mitochondrial genes. The analysis was performed using the most recent T2D GWA meta-analysis of 47,117 people and meta-analyses of seven diabetes-related glycemic traits (up to 46,186 non-diabetic individuals). This well-powered analysis found no significant enrichment of associations to T2D or any of the glycemic traits in any of the gene sets tested. These results suggest that common variants affecting nuclear-encoded mitochondrial genes have at most a small genetic contribution to T2D susceptibility.

Indexed as

Genetic VariationQuantitative Trait, HeritableCase-Control StudiesCohort StudiesDiabetes Mellitus, Type 2Genome-Wide Association StudyGlucoseMitochondrial ProteinsPolymorphism, Single NucleotideGlucoseMitochondrial Proteins

Identifiers

PMID20714348
PMCPMC2920848
OpenAlexW2167806431

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.