Evidence map›Paper›PMID 32462110›Full record

ArticleJournal of psoriasis and psoriatic arthritis2020

Evaluation of a Genetic Risk Score for Diagnosis of Psoriatic Arthritis.

Mary Patricia Smith, Karen Ly, Quinn Thibodeaux, Kristen Beck, Eric Yang, Isabelle Sanchez, Joanne Nititham, Tina Bhutani, Wilson Liao

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

Article in Journal of psoriasis and psoriatic arthritis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. 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

9 authors at 1 institution in 1 country.

Mary Patricia SmithDepartment of Dermatology, University of California, San Francisco, CA, USA.ORCID 0000-0002-1225-8944
Karen LyDepartment of Dermatology, University of California, San Francisco, CA, USA.
Quinn ThibodeauxDepartment of Dermatology, University of California, San Francisco, CA, USA.
Kristen BeckDepartment of Dermatology, University of California, San Francisco, CA, USA.
Eric YangDepartment of Dermatology, University of California, San Francisco, CA, USA.
Isabelle SanchezDepartment of Dermatology, University of California, San Francisco, CA, USA.
Joanne NitithamDepartment of Dermatology, University of California, San Francisco, CA, USA.
Tina BhutaniDepartment of Dermatology, University of California, San Francisco, CA, USA.
Wilson LiaoDepartment of Dermatology, University of California, San Francisco, CA, USA.ORCID 0000-0001-7883-6439
University of California, San Francisco · US

Funding

MHC and KIR Region Genomics in PsoriasisU01AI119125 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LIAO, WILSON · 2015 to 2019
$3.5M
Identification of Causal Variants in PsoriasisR01AR065174 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LIAO, WILSON · 2013 to 2016
$1.8M
National Psoriasis Foundation 2018SSRG11National Psoriasis Foundation NPF2018SSRG11NIAID NIH HHS U01 AI119125NIAMS NIH HHS R01 AR065174
6 · The paper itself

Abstract

backgroundDiagnosis of psoriatic arthritis (PsA) can be challenging, resulting in delays that contribute to irreversible joint damage, reduced quality of life, and increased mortality.

objectiveUse genetic markers to develop and evaluate a PsA genetic risk score (GRS) for its ability to discriminate between psoriasis (PsO) only and PsO with PsA among a psoriatic cohort with full genome-wide genotype data.

methodsGenome-wide single-nucleotide polymorphism genotyping was performed on 724 psoriatic patients. A set of 11 candidate risk genes previously shown to be preferentially associated with PsO or PsA were selected. To evaluate the cumulative effects of these risk loci, a PsA GRS was developed using an unweighted risk allele count (cGRS) and a weighted (wGRS) approach. Additional analyses included only human leukocyte antigen (HLA) risk alleles.

resultsThe discriminative power attributable to each GRS was evaluated by calculating the areas under the receiver operator characteristic curve (AUROC). The AUROC for the wGRS is 56.2% versus 54.1% for the cGRS, and the AUROC for the HLA-only wGRS model was 56.9% versus 55.7% for the HLA-only cGRS.

conclusionThe AUROC of 56.9% for HLA-only wGRS indicates that this approach has the greatest power in discriminating PsA from PsO among these models. Given that an AUROC of 56.9% is quite modest, this study suggests that using a small number of well-validated genetic loci provides limited predictive power for PsA, and that future approaches may benefit from using a larger number of genetic loci.

Indexed as

blood testsdiagnosispsoriasispsoriatic arthritissymptoms

Identifiers

PMID32462110
PMCPMC7252226
OpenAlexW3009639961

What OpenQuestion 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 OpenQuestion graph.