Association Between Natural Hair Color, Race, and Alopecia.

Alopecia areata Androgenetic alopecia Autoinflammation Hair pigmentation Pigmentation biology Scarring alopecia United Kingdom BioBank

Journal

Dermatology and therapy
ISSN: 2193-8210
Titre abrégé: Dermatol Ther (Heidelb)
Pays: Switzerland
ID NLM: 101590450

Informations de publication

Date de publication:
02 Jul 2024
Historique:
received: 26 03 2024
accepted: 19 06 2024
medline: 2 7 2024
pubmed: 2 7 2024
entrez: 2 7 2024
Statut: aheadofprint

Résumé

Limited epidemiologic data has suggested direct associations between hair pigment, race, and incidence of alopecia areata (AA). Here, we examine the relationship between natural hair color, race, and the lifetime risk alopecia. In this case-control study, we included UK Biobank patients of all races and self-reported hair color with diagnoses of AA, androgenetic alopecia (AGA), or scarring alopecia (SA). Multivariable logistic regression was used to detect differences in lifetime risk. Findings reveal a significantly increased risk of AA among individuals with black hair compared to dark brown hair (OR 1.71 [95% CI 1.22-2.38], p < 0.001). Those with red or blonde hair showed a decreased risk of AA (0.74 [0.56-0.97]; 0.62 [0.41-0.95], p < 0.05). No racial differences in AA prevalence were observed among individuals with black hair. Darker hair colors may be associated with a higher risk of AA, lighter hair colors with a lower risk, and differences in hair color could contribute to previously noted racial variations in AA incidence, potentially influencing dermatologists' perspectives on the disease's epidemiology.

Identifiants

pubmed: 38954383
doi: 10.1007/s13555-024-01218-9
pii: 10.1007/s13555-024-01218-9
doi:

Types de publication

Journal Article

Langues

eng

Informations de copyright

© 2024. The Author(s).

Références

Ito S, Wakamatsu K. Diversity of human hair pigmentation as studied by chemical analysis of eumelanin and pheomelanin. J Eur Acad Dermatol Venereol. 2011;25(12):1369–80. https://doi.org/10.1111/j.1468-3083.2011.04278 .
doi: 10.1111/j.1468-3083.2011.04278 pubmed: 22077870
Moseley IH, George EA, Tran MM, Lee H, Qureshi AA, Cho E. Alopecia areata in underrepresented groups: preliminary analysis of the all of us research program. Arch Dermatol Res. 2023. https://doi.org/10.1007/s00403-023-02548-y .
doi: 10.1007/s00403-023-02548-y pubmed: 36763157
Benigno M, Anastassopoulos KP, Mostaghimi A, et al. A large cross-sectional survey study of the prevalence of alopecia areata in the United States. Clin Cosmet Investig Dermatol. 2020;13:259–66. https://doi.org/10.2147/CCID.S245649 .
doi: 10.2147/CCID.S245649 pubmed: 32280257 pmcid: 7131990
Ho CH, Sood T, Zito PM. Androgenetic alopecia. Treasure Island (FL): StatPearls; 2023.
Filbrandt R, Rufaut N, Jones L, Sinclair R. Primary cicatricial alopecia: diagnosis and treatment. Can Med Assoc J. 2013;185(18):1579–85. https://doi.org/10.1503/cmaj.111570 .
doi: 10.1503/cmaj.111570
Sy N, Mastacouris N, Strunk A, Garg A. Overall and racial and ethnic subgroup prevalences of alopecia areata, alopecia totalis, and alopecia universalis. JAMA Dermatol. 2023. https://doi.org/10.1001/jamadermatol.2023.0016 .
doi: 10.1001/jamadermatol.2023.0016 pubmed: 36857044 pmcid: 9979079
Lee H, Jung SJ, Patel AB, Thompson JM, Qureshi A, Cho E. Racial characteristics of alopecia areata in the United States. J Am Acad Dermatol. 2020;83(4):1064–70. https://doi.org/10.1016/j.jaad.2019.06.1300 .
doi: 10.1016/j.jaad.2019.06.1300 pubmed: 31279016
Thompson JM, Park MK, Qureshi AA, Cho E. Race and alopecia areata amongst US women. J Investig Dermatol Symp Proc. 2018;19(1):S47–50. https://doi.org/10.1016/j.jisp.2017.10.007 .
doi: 10.1016/j.jisp.2017.10.007 pubmed: 29273106
Jadeja SD, Tobin DJ. Autoantigen discovery in the hair loss disorder, alopecia areata: implication of post-translational modifications. Front Immunol. 2022;13:890027. https://doi.org/10.3389/fimmu.2022.890027 .
doi: 10.3389/fimmu.2022.890027 pubmed: 35720384 pmcid: 9205194
Sudlow C, Gallacher J, Allen N, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12(3):e1001779. https://doi.org/10.1371/journal.pmed.1001779 .
doi: 10.1371/journal.pmed.1001779 pubmed: 25826379 pmcid: 4380465
Lavian J, Li S, Lee E, et al. Validation of case identification for alopecia areata using International Classification of Diseases coding. Int J Trichol. 2020;12(5):234. https://doi.org/10.4103/ijt.ijt_67_20 .
doi: 10.4103/ijt.ijt_67_20
Herrett E, Thomas SL, Schoonen WM, Smeeth L, Hall AJ. Validation and validity of diagnoses in the general practice research database: a systematic review. Br J Clin Pharmacol. 2010;69(1):4–14. https://doi.org/10.1111/j.1365-2125.2009.03537.x .
doi: 10.1111/j.1365-2125.2009.03537.x pubmed: 20078607 pmcid: 2805870
Bell M, Lui H, Lee TK, Kalia S. Validation of medical service insurance claims as a surrogate for ascertaining vitiligo cases. Arch Dermatol Res. 2023;315(3):541–50. https://doi.org/10.1007/s00403-022-02383-7 .
doi: 10.1007/s00403-022-02383-7 pubmed: 36173455
Quan H, Li B, Saunders LD, et al. Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database. Health Serv Res. 2008;43(4):1424–41. https://doi.org/10.1111/j.1475-6773.2007.00822.x .
doi: 10.1111/j.1475-6773.2007.00822.x pubmed: 18756617 pmcid: 2517283
Jorge A, Castro VM, Barnado A, et al. Identifying lupus patients in electronic health records: development and validation of machine learning algorithms and application of rule-based algorithms. Semin Arthritis Rheum. 2019;49(1):84–90. https://doi.org/10.1016/j.semarthrit.2019.01.002 .
doi: 10.1016/j.semarthrit.2019.01.002 pubmed: 30665626 pmcid: 6609504
Ham SP, Oh JH, Park HJ, et al. Validity of diagnostic codes for identification of psoriasis patients in Korea. Ann Dermatol. 2020;32(2):115–21. https://doi.org/10.5021/ad.2020.32.2.115 .
doi: 10.5021/ad.2020.32.2.115 pubmed: 33911722 pmcid: 7992553
Lipscombe LL, Hwee J, Webster L, Shah BR, Booth GL, Tu K. Identifying diabetes cases from administrative data: a population-based validation study. BMC Health Serv Res. 2018;18(1):316. https://doi.org/10.1186/s12913-018-3148-0 .
doi: 10.1186/s12913-018-3148-0 pubmed: 29720153 pmcid: 5932874
Rezaie A, Quan H, Fedorak RN, Panaccione R, Hilsden RJ. Development and validation of an administrative case definition for inflammatory bowel diseases. Can J Gastroenterol. 2012;26(10):711–7. https://doi.org/10.1155/2012/278495 .
doi: 10.1155/2012/278495 pubmed: 23061064 pmcid: 3472911
Rees JL. Genetics of hair and skin color. Annu Rev Genet. 2003;37(1):67–90. https://doi.org/10.1146/annurev.genet.37.110801.143233 .
doi: 10.1146/annurev.genet.37.110801.143233 pubmed: 14616056
Wang EHC, Yu M, Breitkopf T, et al. Identification of autoantigen epitopes in alopecia areata. J Investig Dermatol. 2016;136(8):1617–26. https://doi.org/10.1016/j.jid.2016.04.004 .
doi: 10.1016/j.jid.2016.04.004 pubmed: 27094591
Tanaka Y, Aso T, Ono J, Hosoi R, Kaneko T. Androgenetic alopecia treatment in Asian men. J Clin Aesthet Dermatol. 2018;11(7):32–5.
pubmed: 30057663 pmcid: 6057731
Lee WS, Lee HJ. Characteristics of androgenetic alopecia in Asian. Ann Dermatol. 2012;24(3):243. https://doi.org/10.5021/ad.2012.24.3.243 .
doi: 10.5021/ad.2012.24.3.243 pubmed: 22879706 pmcid: 3412231
Tobin DJ, Fenton DA, Kendall MD. Ultrastructural observations on the hair bulb melanocytes and melanosomes in acute alopecia areata. J Investig Dermatol. 1990;94(6):803–7. https://doi.org/10.1111/1523-1747.ep12874660 .
doi: 10.1111/1523-1747.ep12874660 pubmed: 2355182
Navarini AA, Nobbe S. Marie antoinette syndrome. Arch Dermatol. 2009. https://doi.org/10.1001/archdermatol.2009.51 .
doi: 10.1001/archdermatol.2009.51 pubmed: 19528420
Messenger AG, Bleehen SS. Alopecia areata: light and electron microscopic pathology of the regrowing white hair. Br J Dermatol. 1984;110(2):155–62. https://doi.org/10.1111/j.1365-2133.1984.tb07461.x .
doi: 10.1111/j.1365-2133.1984.tb07461.x pubmed: 6696834
Petukhova L, Patel AV, Rigo RK, et al. Integrative analysis of rare copy number variants and gene expression data in alopecia areata implicates an aetiological role for autophagy. Exp Dermatol. 2020;29(3):243–53. https://doi.org/10.1111/exd.13986 .
doi: 10.1111/exd.13986 pubmed: 31169925
Hsiao JJ, Fisher DE. The roles of microphthalmia-associated transcription factor and pigmentation in melanoma. Arch Biochem Biophys. 2014;563:28–34. https://doi.org/10.1016/j.abb.2014.07.019 .
doi: 10.1016/j.abb.2014.07.019 pubmed: 25111671 pmcid: 4336945
Jabbari A, Petukhova L, Cabral RM, Clynes R, Christiano AM. Genetic basis of alopecia areata: a roadmap for translational research. Dermatol Clin. 2013;31(1):109–17. https://doi.org/10.1016/j.det.2012.08.014 .
doi: 10.1016/j.det.2012.08.014 pubmed: 23159180
Wang S, Ratnaparkhi R, Piliang M, Bergfeld WF. Role of family history in patchy alopecia areata. Dermatol Online J. 2018. https://doi.org/10.5070/D32410041734 .
doi: 10.5070/D32410041734 pubmed: 30695981
Petukhova L, Duvic M, Hordinsky M, et al. Genome-wide association study in alopecia areata implicates both innate and adaptive immunity. Nature. 2010;466(7302):113–7. https://doi.org/10.1038/nature09114 .
doi: 10.1038/nature09114 pubmed: 20596022 pmcid: 2921172
Petukhova L, Cabral RM, Mackay-Wiggan J, Clynes R, Christiano AM. The genetics of alopecia areata: what’s new and how will it help our patients? Dermatol Ther. 2011;24(3):326–36. https://doi.org/10.1111/j.1529-8019.2011.01411.x .
doi: 10.1111/j.1529-8019.2011.01411.x pubmed: 21689242
Zheng M, Ren Y. The genetic basis of pigmentation in alopecia areata. Exp Dermatol. 2017;26(6):542–3. https://doi.org/10.1111/exd.13217 .
doi: 10.1111/exd.13217 pubmed: 27673728
Colombe BW, Lou CD, Price VH. The genetic basis of alopecia areata: HLA associations with patchy alopecia areata versus alopecia totalis and alopecia universalis. J Investig Dermatol Symp Proc. 1999;4(3):216–9. https://doi.org/10.1038/sj.jidsp.5640214 .
doi: 10.1038/sj.jidsp.5640214 pubmed: 10674369
Lin B, Mbarek H, Willemsen G, et al. Heritability and genome-wide association studies for hair color in a Dutch twin family based sample. Genes (Basel). 2015;6(3):559–76. https://doi.org/10.3390/genes6030559 .
doi: 10.3390/genes6030559 pubmed: 26184321

Auteurs

Kanika Kamal (K)

Harvard Medical School, Boston, MA, USA.
Department of Dermatology, Massachusetts General Hospital, 55 Fruit Street - Bartlett 616, Boston, MA, 02114, USA.
Department of Dermatology, Brigham and Women's Hospital, Boston, MA, USA.

David Xiang (D)

Harvard Medical School, Boston, MA, USA.

Katherine Young (K)

Harvard Medical School, Boston, MA, USA.

David E Fisher (DE)

Department of Dermatology, Massachusetts General Hospital, 55 Fruit Street - Bartlett 616, Boston, MA, 02114, USA.

Arash Mostaghimi (A)

Department of Dermatology, Brigham and Women's Hospital, Boston, MA, USA.

Nicholas Theodosakis (N)

Department of Dermatology, Massachusetts General Hospital, 55 Fruit Street - Bartlett 616, Boston, MA, 02114, USA. ntheodosakis@mgh.harvard.edu.

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