Evidence map›Paper›PMID 31365490›Full record

ReviewShock (Augusta, Ga.)2020

Quality Control Measures and Validation in Gene Association Studies: Lessons for Acute Illness.

Maria Cohen, Ashley J Lamparello, Lukas Schimunek, Fayten El-Dehaibi, Rami A Namas, Yan Xu, A Murat Kaynar, Timothy R Billiar, Yoram Vodovotz

Open access · greenAbstract readReview
In one paragraph

Review in Shock (Augusta, Ga.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 37% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Integrating multi-omics data for next-generation cancer research and precision medicine.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
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

9 authors at 2 institutions in 1 country.

Maria CohenDepartment of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
Ashley J LamparelloDepartment of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania.
Lukas SchimunekDepartment of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania.
Fayten El-DehaibiDepartment of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania.
Rami A NamasDepartment of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania.
Yan XuDepartment of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
A Murat KaynarDepartment of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
Timothy R BilliarDepartment of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania.
Yoram VodovotzDepartment of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania.
University of Pittsburgh · USMcGowan Institute for Regenerative Medicine · US

Funding

Research Training in Anesthesiology and Pain MedicineT32GM075770 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI YAN XU · 2007 to 2026
$4.8M
NIGMS NIH HHS T32 GM075770
6 · The paper itself

Abstract

Acute illness is a complex constellation of responses involving dysregulated inflammatory and immune responses, which are ultimately associated with multiple organ dysfunction. Gene association studies have associated single-nucleotide polymorphisms (SNPs) with clinical and pharmacological outcomes in a variety of disease states, including acute illness. With approximately 4 to 5 million SNPs in the human genome and recent studies suggesting that a large portion of SNP studies are not reproducible, we suggest that the ultimate clinical utility of SNPs in acute illness depends on validation and quality control measures. To investigate this issue, in December 2018 and January 2019 we searched the literature for peer-reviewed studies reporting data on associations between SNPs and clinical outcomes and between SNPs and pharmaceuticals (i.e., pharmacogenomics) published between January 2011 to February 2019. We review key methodologies and results from a variety of clinical and pharmacological gene association studies, including trauma and sepsis studies, as illustrative examples on current SNP association studies. In this review article, we have found three key points which strengthen the potential accuracy of SNP association studies in acute illness and other diseases: providing evidence of following a protocol quality control method such as the one in Nature Protocols or the OncoArray QC Guidelines; enrolling enough patients to have large cohort groups; and validating the SNPs using an independent technique such as a second study using the same SNPs with new patient cohorts. Our survey suggests the need to standardize validation methods and SNP quality control measures in medicine in general, and specifically in the context of complex disease states such as acute illness.

Indexed as

Acute DiseaseGenetic Association StudiesQuality ControlHumansPolymorphism, Single NucleotideReproducibility of Results

Identifiers

PMID31365490
PMCPMC6989353
OpenAlexW2966158690

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.