Evidence map›Paper›PMID 36184273›Full record

ArticleThe Journal of hand surgery2022

Familial Clustering and Genetic Analysis of Severe Thumb Carpometacarpal Joint Osteoarthritis in a Large Statewide Cohort.

Catherine M Gavile, Nikolas H Kazmers, Kendra A Novak, Huong D Meeks, Zhe Yu, Joy L Thomas, Channing Hansen, Tyler Barker, Michael J Jurynec

Open access · greenAbstract read
In one paragraph

Article in The Journal of hand surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

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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 3 institutions in 1 country.

Catherine M GavileDepartment of Orthopaedics, University of Utah, Salt Lake City, UT.
Nikolas H KazmersDepartment of Orthopaedics, University of Utah, Salt Lake City, UT.
Kendra A NovakDepartment of Orthopaedics, University of Utah, Salt Lake City, UT.
Huong D MeeksHuntsman Cancer Institute, Utah Population Database, University of Utah, Salt Lake City, UT.
Zhe YuHuntsman Cancer Institute, Utah Population Database, University of Utah, Salt Lake City, UT.
Joy L ThomasIntermountain Healthcare, Precision Genomics, St. George, UT.
Channing HansenIntermountain Healthcare, Biorepository, South Salt Lake City, UT.
Tyler BarkerDepartment of Orthopaedics, University of Utah, Salt Lake City, UT; Intermountain Healthcare, Precision Genomics, Murray, UT; Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT.
Michael J JurynecDepartment of Orthopaedics, University of Utah, Salt Lake City, UT; Department of Human Genetics, University of Utah, Salt Lake City, UT. Electronic address: mjurynec@genetics.utah.edu.
University of Utah · USIntermountain Healthcare · USHuntsman Cancer Institute · US

Funding

Utah Center for Clinical and Translational ScienceUL1TR002538 · NCATS · UNIVERSITY OF UTAH · PI HESS, RACHEL, MAJERSIK, JENNIFER JUHL · 2018 to 2022
$26.0M
Establishing a new genetic mouse model of osteoarthritisR21AG063534 · NIA · UNIVERSITY OF UTAH · PI GRUNWALD, DAVID J., JURYNEC, MICHAEL J · 2020 to 2021
$419k
NCATS NIH HHS UL1 TR002538NIA NIH HHS R21 AG063534
6 · The paper itself

Abstract

purposeOur goals were to identify individuals who required surgery for thumb carpometacarpal (CMC) joint osteoarthritis (OA), determine if CMC joint OA clusters in families, define the magnitude of familial risk of CMC joint OA, identify risk factors associated with CMC joint OA, and identify rare genetic variants that segregate with familial CMC joint OA.

methodsWe searched the Utah Population Database to identify a cohort of CMC joint OA patients who required surgery. Affected individuals were mapped to pedigrees to identify high-risk families with excess clustering of CMC joint OA. Cox regression models were used to calculate familial risk of CMC joint OA in related individuals. Risk factors were evaluated using logistic regression models. Whole exome sequencing was used to identify rare coding variants associated with familial CMC joint OA.

resultsWe identified 550 pedigrees with excess clustering of severe CMC joint OA. The relative risk of CMC joint OA requiring surgical treatment was elevated significantly in first- and third-degree relatives of affected individuals, and significant associations with advanced age, female sex, obesity, and tobacco use were observed. We discovered candidate genes that dominantly segregate with severe CMC joint OA in 4 independent families, including a rare variant in Chondroitin Sulfate Synthase 3 (CHSY3).

conclusionsFamilial clustering of severe CMC joint OA was observed in a statewide population. Our data indicate that genetic and environmental factors contribute to the disease process, further highlighting the multifactorial nature of the disease. Genomic analyses suggest distinct biological processes are involved in CMC joint OA pathogenesis. CLINICAL RELEVANCE: Awareness of associated comorbidities may guide the diagnosis of CMC joint OA in at-risk populations and help identify individuals who may not do well with nonoperative treatment. Further pursuit of the genes associated with severe CMC joint OA may lead to assays for detection of early stages of disease and have therapeutic potential.

Indexed as

Carpometacarpal JointsOsteoarthritisChondroitin SulfatesCluster AnalysisFemaleGenetic Predisposition to DiseaseHumansThumbChondroitin SulfatesCarpometacarpal hand osteoarthritisCMC joint osteoarthritishand osteoarthritisosteoarthritis geneosteoarthritis risk factorsthumb base osteoarthritis

Identifiers

PMID36184273
PMCPMC9547951
OpenAlexW4298007987

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.