Evidence map›Paper›PMID 38014829›Full record

ArticleActa dermato-venereologica2023

Hailey-Hailey Disease is Associated with Diabetes: A Population-based Cohort Study, Clinical Cohort Study, and Pedigree Analysis.

Philip Curman, William Jebril, Carmella Evans-Molina, Etty Bachar-Wikstrom, Henrik Larsson, Martin Cederlöf, Jakob D Wikström

Open access · goldAbstract read
In one paragraph

Article in Acta dermato-venereologica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 75% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

7 authors at 4 institutions in 3 countries.

Philip CurmanDermatology and Venereology Division, Department of Medicine (Solna), Karolinska Institutet, Stockholm, Sweden; Dermato-Venereology Clinic, Karolinska University Hospital, Stockholm, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. philip.curman@ki.se.
William JebrilDermatology and Venereology Division, Department of Medicine (Solna), Karolinska Institutet, Stockholm, Sweden; Dermato-Venereology Clinic, Karolinska University Hospital, Stockholm, Sweden.
Carmella Evans-MolinaDepartments of Anatomy, Cell Biology, and Physiology; Biochemistry and Molecular Biology; Medicine; Pediatrics, Indiana University School of Medicine, Indianapolis, IN 46202; The Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN 46202; Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; Roudebush VA Medical Center, Indianapolis, IN 46202, USA.
Etty Bachar-WikstromDermatology and Venereology Division, Department of Medicine (Solna), Karolinska Institutet, Stockholm, Sweden; Dermato-Venereology Clinic, Karolinska University Hospital, Stockholm, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Henrik LarssonDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Martin CederlöfDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
Jakob D WikströmDermatology and Venereology Division, Department of Medicine (Solna), Karolinska Institutet, Stockholm, Sweden; Dermato-Venereology Clinic, Karolinska University Hospital, Stockholm, Sweden.
Karolinska Institutet · SEKarolinska University Hospital · SEÖrebro University · SERichard L. Roudebush VA Medical Center · US

Funding

Control of beta cell function and survival by RYR2-mediated calcium signalsR01DK127236 · NIDDK · INDIANA UNIVERSITY INDIANAPOLIS · PI EVANS-MOLINA, CARMELLA · 2021 to 2025
$2.2M
BLRD VA I01 BX001733NIDDK NIH HHS R01 DK127236
6 · The paper itself

Abstract

Hailey-Hailey disease is a rare hereditary skin disease caused by mutations in the ATP2C1 gene encoding the secretory pathway Ca2+/Mn2+-ATPase 1 (SPCA1) protein. Extracutaneous manifestations of Hailey-Hailey disease are plausible but still largely unknown. The aim of this study was to explore the association between Hailey-Hailey disease and diabetes. A population-based cohort study of 347 individuals with Hailey-Hailey  disease was performed to assess the risks of type 1  diabetes and type 2 diabetes, using Swedish nationwide registries. Pedigrees from 2 Swedish families with Hailey-Hailey disease were also investigated: 1 with concurrent type 1 diabetes and HLA-DQ3, the other with type 2 diabetes. Lastly, a clinical cohort with 23 individuals with Hailey-Hailey disease and matched healthy controls was evaluated regarding diabetes. In the register data males with Hailey-Hailey disease had a 70% elevated risk of type 2 diabetes, whereas no  excess risk among women could be confirmed. In both pedigrees an unusually high inheritance for diabetes was observed. In the clinical cohort, individuals with Hailey-Hailey disease displayed a metabolic phenotype indicative of type 2 diabetes. Hailey-Hailey disease seems to act as a synergistic risk factor for diabetes. This study indicates, for the first time, an association between Hailey-Hailey disease and diabetes and represents human evidence that SPCA1 and the Golgi apparatus may be implicated in diabetes pathophysiology.

Indexed as

Diabetes Mellitus, Type 2Pemphigus, Benign FamilialCalcium-Transporting ATPasesCohort StudiesFemaleHumansMaleMutationPedigreeATP2C1 protein, humanCalcium-Transporting ATPases

Identifiers

PMID38014829
PMCPMC10695124
OpenAlexW4389086606

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.