Evidence map›Paper›PMID 33186361›Full record

ArticlePloS one2020

Sensitive detection of multiple islet autoantibodies in type 1 diabetes using small sample volumes by agglutination-PCR.

Felipe de Jesus Cortez, David Gebhart, Peter V Robinson, David Seftel, Narges Pourmandi, Jordan Owyoung, Carolyn R Bertozzi, Darrell M Wilson, David M Maahs, Bruce A Buckingham and 10 more

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Role of mitochondrial DNA in diabetes Mellitus Type I and Type II.Saudi journal of biological sciences · 2022
    Review
  17. Article
  18. Article
  19. Review
  20. 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

20 authors.

Felipe de Jesus CortezEnable Biosciences Inc., South San Francisco, CA, United States of America.
David GebhartEnable Biosciences Inc., South San Francisco, CA, United States of America.
Peter V RobinsonEnable Biosciences Inc., South San Francisco, CA, United States of America.
David SeftelEnable Biosciences Inc., South San Francisco, CA, United States of America.
Narges PourmandiEnable Biosciences Inc., South San Francisco, CA, United States of America.
Jordan OwyoungEnable Biosciences Inc., South San Francisco, CA, United States of America.
Carolyn R BertozziDepartment of Chemistry, Stanford University, Stanford, CA, United States of America.
Darrell M WilsonStanford Diabetes Research Center, Stanford, CA, United States of America.
David M MaahsStanford Diabetes Research Center, Stanford, CA, United States of America.
Bruce A BuckinghamStanford Diabetes Research Center, Stanford, CA, United States of America.
John R MillsDepartment of Laboratory Medicine/Pathology, Mayo Clinic, College of Medicine, Rochester, MN, United States of America.
Matthew M RoforthDepartment of Laboratory Medicine/Pathology, Mayo Clinic, College of Medicine, Rochester, MN, United States of America.
Sean J PittockDepartment of Laboratory Medicine/Pathology, Mayo Clinic, College of Medicine, Rochester, MN, United States of America.
Andrew McKeonDepartment of Laboratory Medicine/Pathology, Mayo Clinic, College of Medicine, Rochester, MN, United States of America.
Kara PageT1D Exchange, Boston, MA, United States of America.
Wendy A WolfT1D Exchange, Boston, MA, United States of America.
Srinath SandaDiabetes Center, University of California, San Francisco, San Francisco, CA, United States of America.
Cate SpeakeDiabetes Clinical Research Program, Benaroya Research Institute, Seattle, WA, United States of America.
Carla J GreenbaumDiabetes Clinical Research Program, Benaroya Research Institute, Seattle, WA, United States of America.
Cheng-Ting TsaiEnable Biosciences Inc., South San Francisco, CA, United States of America.ORCID 0000-0002-8718-8821

Funding

Stanford Center for Clinical & Translational Education and Research (Spectrum)UL1TR003142 · NCATS · STANFORD UNIVERSITY · PI O'HARA, RUTH M · 2019 to 2023
$45.0M
Spectrum Stanford Center for clinical and Translational Research and EducationUL1TR001085 · NCATS · STANFORD UNIVERSITY · PI CULLEN, MARK RICHARD, GREENBERG, HARRY BERNARD · 2013 to 2017
$37.1M
Type I Diabetes Trialnet at StsnfordU01DK061042 · NIDDK · STANFORD UNIVERSITY · PI WILSON, DARRELL M · 2001 to 2018
$8.5M
An Ultrasensitive, High-Throughput, and Low-Cost Autoimmunity Panel for the Early Diagnosis and Improved Treatment of Type 1 DiabetesR44DK111005 · NIDDK · ENABLE BIOSCIENCES, INC. · PI SEFTEL, DAVID · 2018 to 2025
$4.4M
Development of An Automated High-Throughput Dried Blood Spot Assay to Facilitate Large Scale Screening for Type 1 Diabetes RiskR44DK124009 · NIDDK · ENABLE BIOSCIENCES, INC. · PI SEFTEL, DAVID · 2019 to 2020
$1.5M
Antibody-Detection-by-Agglutination-PCR (ADAP): An Ultra-Sensitive, High-Throughput, Multiplexable Tool for T1D Diagnosis and MonitoringR43DK111005 · NIDDK · ENABLE BIOSCIENCES, INC. · PI SEFTEL, DAVID · 2016 to 2016
$224k
NCATS NIH HHS UL1 TR001085NCATS NIH HHS UL1 TR003142NIDDK NIH HHS R43 DK111005NIDDK NIH HHS R44 DK111005NIDDK NIH HHS R44 DK124009NIDDK NIH HHS U01 DK061042
6 · The paper itself

Abstract

Islet autoantibodies are predominantly measured by radioassay to facilitate risk assessment and diagnosis of type 1 diabetes. However, the reliance on radioactive components, large sample volumes and limited throughput renders radioassay testing costly and challenging. We developed a multiplex analysis platform based on antibody detection by agglutination-PCR (ADAP) for the sample-sparing measurement of GAD, IA-2 and insulin autoantibodies/antibodies in 1 μL serum. The assay was developed and validated in 7 distinct cohorts (n = 858) with the majority of the cohorts blinded prior to analysis. Measurements from the ADAP assay were compared to radioassay to determine correlation, concordance, agreement, clinical sensitivity and specificity. The average overall agreement between ADAP and radioassay was above 91%. The average clinical sensitivity and specificity were 96% and 97%. In the IASP 2018 workshop, ADAP achieved the highest sensitivity of all assays tested at 95% specificity (AS95) rating for GAD and IA-2 autoantibodies and top-tier performance for insulin autoantibodies. Furthermore, ADAP correctly identified 95% high-risk individuals with two or more autoantibodies by radioassay amongst 39 relatives of T1D patients tested. In conclusion, the new ADAP assay can reliably detect the three cardinal islet autoantibodies/antibodies in 1μL serum with high sensitivity. This novel assay may improve pediatric testing compliance and facilitate easier community-wide screening for islet autoantibodies.

Indexed as

AdolescentAdultAgglutinationAutoantibodiesDiabetes Mellitus, Type 1FemaleGlutamate DecarboxylaseHumansInsulin AntibodiesIslets of LangerhansMaleMass ScreeningPolymerase Chain ReactionSensitivity and SpecificityYoung AdultAutoantibodiesGlutamate DecarboxylaseICA512 autoantibodyInsulin Antibodies

Identifiers

PMID33186361
PMCPMC7665791

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.