Evidence map›Paper›PMID 26005397›Full record

ArticleProceedings. American Statistical Association. Annual Meeting

A novel method for testing association of multiple genetic markers with a multinomial trait.

Soonil Kwon, Mark O Goodarzi, Kent D Taylor, Jinrui Cui, Y-D Ida Chen, Jerome I Rotter, Willa Hsueh, Xiuqing Guo

Open access · greenAbstract read
PubMed Full text at PMC
In one paragraph

Article in Proceedings. American Statistical Association. Annual Meeting. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 72% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 institutions in 1 country.

Soonil KwonMedical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA.
Mark O GoodarziMedical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA.
Kent D TaylorMedical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA.
Jinrui CuiMedical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA.
Y-D Ida ChenMedical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA.
Jerome I RotterMedical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA.
Willa HsuehThe Methodist Hospital Research Institute, Houston, TX.
Xiuqing GuoMedical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA.
Cedars-Sinai Medical Center · USMethodist Hospital · US

Funding

Mapping Genes for Atherosclerosis and Insulin ResistanceR01HL088457 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI ROTTER, JEROME I · 2007 to 2010
$3.0M
NHLBI NIH HHS R01 HL088457
6 · The paper itself

Abstract

We developed a multinomial probit model with singular value decomposition for testing a large number of single nucleotide polymorphisms (SNPs) simultaneously, using maximum likelihood estimation and permutation. The method was validated by simulation. We simulated 1000 SNPs, including 9 associated with disease states, and 8 of the 9 were successfully identified. Applying the method to study 32 genes in our Mexican-American samples for association with prediabetes through either impaired glucose tolerance (IGT) or impaired fasting glucose (IFG), we found 3 genes (SORCS1, AMPD1, PPAR) associated with both IGT and IFG, while 5 genes (AMPD2, PRKAA2, C5, TCF7L2, ITR) with the IGT mechanism only and 6 genes (CAPN10, IL4,NOS3, CD14, GCG, SORT1) with the IFG mechanism only. These data suggest that IGT and IFG may indicate different physiological mechanism to prediabetes, via different genetic determinants.

Identifiers

PMID26005397
PMCPMC4439253
OpenAlexW2421597135

What OpenQuestion holds

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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.