Evidence map›Paper›PMID 35169238›Full record

ArticleScientific reports2022

Exploration of autoantibody responses in canine diabetes using protein arrays.

Allison L O'Kell, Mahasish Shome, Ji Qiu, Stacy Williams, Yunro Chung, Joshua LaBaer, Mark A Atkinson, Clive Wasserfall

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 21% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Antidiabetic effects ofFrontiers in pharmacology · 2023
    Article
  4. 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

8 authors at 2 institutions in 1 country.

Allison L O'Kell *Department of Small Animal Clinical Sciences, College of Veterinary Medicine, The University of Florida, 2015 SW 16th Ave, Box 100116, Gainesville, FL, 32608, USA. aokell@ufl.edu.ORCID 0000-0002-3412-0575
Mahasish Shome *The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
Ji QiuThe Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
Stacy WilliamsThe Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
Yunro ChungThe Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
Joshua LaBaerThe Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
Mark A AtkinsonDepartment of Pathology, Immunology, and Laboratory Medicine, The University of Florida, Gainesville, FL, USA.
Clive WasserfallDepartment of Pathology, Immunology, and Laboratory Medicine, The University of Florida, Gainesville, FL, USA.
Arizona State University · USUniversity of Florida · US

Funding

Evaluating canine diabetes as a novel means to understand the human diseaseK08DK116735 · NIDDK · UNIVERSITY OF FLORIDA · PI O'KELL, ALLISON L · 2018 to 2021
$598k
NIDDK NIH HHS K08 DK116735
6 · The paper itself

Abstract

Canine diabetes has been considered a potential model of human type 1 diabetes (T1D), however the detection of autoantibodies common in humans with T1D in affected dogs is inconsistent. The aim of this study was to compare autoantibody responses in diabetic and healthy control dogs using a novel nucleic acid programmable protein array (NAPPA) platform. We performed a cross-sectional study of autoantibody profiles of 30 diabetic and 30 healthy control dogs of various breeds. Seventeen hundred human proteins related to the pancreas or diabetes were displayed on NAPPA arrays and interrogated with canine sera. The median normalized intensity (MNI) for each protein was calculated, and results were compared between groups to identify candidate autoantibodies. At a specificity of 90%, six autoantibodies had sensitivity greater than 10% (range 13-20%) for distinguishing diabetic and control groups. A combination of three antibodies (anti-KANK2, anti-GLI1, anti-SUMO2) resulted in a sensitivity of 37% (95% confidence interval (CI) 0.17-0.67%) at 90% specificity and an area under the receiver operating characteristics curve of 0.66 (95% CI 0.52-0.80). While this study does not provide conclusive support for autoimmunity as an underlying cause of diabetes in dogs, future studies should consider the use of canine specific proteins in larger numbers of dogs of breeds at high risk for diabetes.

Indexed as

AnimalsAutoantibodiesBiomarkersBreedingCross-Sectional StudiesDiabetes Mellitus, Type 1Disease Models, AnimalDog DiseasesDogsProtein Array AnalysisRiskROC CurveSensitivity and SpecificityAutoantibodiesBiomarkers

Identifiers

PMID35169238
PMCPMC8847587
OpenAlexW4212839234

What OpenQuestion holds

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LicenceCC BY
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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.