ARTICLE
Auteur(s) : Raghunandan Dudda-Subramanya1,
Andrew F Alexis2, Kimberly Siu3, Animesh A Sinha4
1Drexel University, Philadelphia, PA
2Department of Dermatology, St. Luke’s-Roosevelt
Hospital, New York, NY
3Department of Dermatology, New York University School
of Medicine, New York
4Division of Dermatology and Cutaneous Sciences, Center
for Investigative Dermatology, College of Human Medicine, Michigan
State University, East Lansing, MI 48824
accepté le 9 Mars 2007
Alopecia areata (AA) is a clinically heterogeneous disease
characterized by nonscarring hair loss on the scalp or any
hair-bearing surface. There is no male or female predilection and
persons of any age can be affected [1]. AA varies considerably with
respect to age of onset, extent of involvement, and disease
duration. Particularly in severe or chronic cases, AA may cause
considerable psychological and emotional distress for affected
individuals [2]. The estimated lifetime risk of developing AA is
1.7% [3]. Despite its high prevalence, the treatment of AA is
essentially palliative and nonspecific. A better understanding of
genetic and environmental factors that determine disease
heterogeneity is required to advance disease diagnosis, prognosis
and treatment.
Clinical presentation and caveats
The clinical presentation and course of alopecia areata is variable
and unpredictable. While a circumscribed patch of non-scarring
alopecia on the scalp is the most common initial presentation, bald
patches may first be noted on other hair-bearing sites, including
the eyebrows, eyelashes, or beard area. Scalp alopecia may also
present with either a diffuse or reticular pattern of thinning, as
opposed to discrete bald patches. A patient can present with
complete loss of hair on the scalp – alopecia totalis and/or body –
alopecia universalis. Initial areas of alopecia may regrow, expand,
or persist, while new patches variably develop. Hair loss can be
limited to the periphery of the scalp in a band-like distribution
-ophiasis pattern, or conversely, it can spare the periphery of the
scalp-sisapho (ophiasis inversus) [4]. Pitting of the nails is seen
in 10 to 66% of cases [5]. (See figure 1 for representative
photos of various AA phenotypes). Given the variability in pattern,
extent of involvement and clinical progression, AA is best
considered a disease spectrum that ranges from transient, limited
hair loss on one pole, to prolonged complete loss of body and scalp
hair on the opposite pole. However, a universally accepted and
comprehensive classification scheme to define all patients along
this spectrum is currently lacking. In 1999, Olsen et al. [6]
published a set of baseline clinical staging guidelines to help
stratify patients into three groups according to extent of scalp
hair loss, and the presence of body hair loss or nail involvement:
alopecia totalis (AT), which signifies 100% loss of terminal hair
on the scalp; alopecia universalis (AU), defined as 100% scalp
terminal hair and 100% body hair loss; and AT/AU, which describes
100% scalp terminal hair loss with a variable extent of body hair
loss. While this classification system is useful to broadly group
patients, it does not account for all clinical subsets of disease,
for example, those with loss of body or facial hair alone are not
defined in this scheme. In a 1999 study, Olsen and colleagues [7]
stratified patients according to extent and duration of disease.
Patients with AA – with any extent of involvement – for 6 months or
less were defined as Group I. Patients with greater than 25% hair
loss on the scalp for 18 months or longer, but never with 100% hair
loss (AT/AU) were defined as Group II (patchy AA). Patients with
100% scalp hair loss with or without body hair loss for greater
than 2 years at any time were defined as Group III (AT/AU). Again,
this classification does not define the entire clinical spectrum of
AA. Most notably, patients who have AA of any extent for a duration
of greater than 6 months, but less than 18 months, are not
classified. In 2004, Part II of the Alopecia Areata Investigational
Assessment Guidelines categorized scalp hair loss into further
subclasses from S0-S5, and introduced the
“Severity of Alopecia Tool” or SALT score. These tools were
designed to allow both the extent and density of hair loss to be
graded visually in one score [7].
In any case, by definition, AA is a dynamic and unpredictable
condition. A patient who presents with a single patch of AA on the
scalp may later progress to have widespread loss of hair on the
scalp and body. As such, it would only be possible to properly
classify this patient’s disease after sufficient time has elapsed
to observe its full progression. The ‘sufficient’ amount of time
will vary individually. An ideal clinical classification of AA
should allow stratification of patients by extent of involvement
(percentage of hair loss), pattern of hair loss (e.g. patchy,
diffuse, ophiasis, etc.), anatomic location (scalp, face, or body),
and duration of disease (figure 2). Patients could
be further grouped according to known or proposed prognostic
factors as these may correlate with the clinical severity and
course of disease. Such risk factors could include, early onset of
AA, family history, HLA type, and atopy [8] to assist in
determining the probable clinical disease course and direct
treatment options. Given the variable course of disease,
effectively combining and weighting these disparate variables into
one classification scheme remains a daunting challenge.
Our understanding of the prognosis, treatment, and etiology of
AA has in large measure been hampered by our inability to
effectively stratify patients across the wide spectrum of disease.
For example, if the underlying pathophysiology of transient patchy
AA of the scalp differs from that of the diffuse, chronic form, it
would be essential to study such patients separately to draw
accurate conclusions on disease outcome, etiology, and treatment
options. In the absence of a universally accepted classification
system, pooling of data from patients with similar disease
presentation and outcome is not possible. Therefore, the ability to
assess the potential genetic and environmental factors that
underlie disease is currently limited; this, in turn, restricts our
ability to identify accurate prognostic factors and effective
therapeutic targets. As a corollary, a more complete understanding
of the genetic markers and pathomechanisms of disease can be
expected to clarify the observed clinical heterogeneity in AA; this
in turn, will allow the clinician or investigator to better
stratify individual patients into pathophysiologically distinct
sub-categories of disease.
Genetics of alopecia
There is strong evidence for a genetic basis in the pathogenesis of
AA. There is no direct correlation, however, between phenotype and
genotype as is seen in ‘simple’ Mendelian inheritance. Hence, hair
loss in AA can be termed a “complex trait” – in other words, it is
multifactorial and polygenic in origin.
Genetic complexity undoubtedly underlies the clinical
heterogeneity observed in AA. Variations in the clinical expression
of disease confound genetic research and add to the difficulty in
interpreting results from different studies. Emerging strategies
for genetic analysis incorporating genome-wide approaches should
facilitate better elucidation of the genetic avocation in AA
(discussed in further detail below).
Family and twin studies
Support for a genetic etiology in AA is largely based on increased
frequencies of disease among family members of patients. Ten to 42%
of AA patients report a positive family history of at least one
first-degree relative [9-12]. A family history of disease is higher
in those patients who have early-onset disease – 37% in patients
who had their first patch before 30 years of age, 7.1% if disease
initiation occurred after 30 years of age [13]. Further, the
estimated lifetime risk of AA in children of patients with AA is
6%, considerably higher compared to the risk in the general
population [14].
In a study of AA in twins [14], the concordance rate among
monozygotic twins was found to be 55%, a rate similar to many other
autoimmune disorders [15-19]. The higher concordance in monozygotic
twins vs. dizygotic twins [14] clearly indicates that genotypic
similarity among identical twins is responsible, at least in part,
for the condition. Precisely which genetic elements control
susceptibility to disease, however, is largely unknown.
HLA Genes
Several HLA associations have been reported with AA (summarized in
figure 3),
suggesting that susceptibility is at least in part a genetic trait
mapping to the Major Histocompatibility Complex (MHC) region
located on chromosome 6 in humans, and consistent with the
assertion that AA is autoimmune in nature. Early studies
highlighted HLA class I associations, but these have not proven to
be consistent. Reports on HLA class II associations in AA have been
more reproducible, perhaps concomitant with the development of
better typing methods. Moreover, direct linkage analysis advocates
the link between the HLA class II region and AA; a LOD (logarithm
of odds) score of 2.42 for HLA-DQB at 5% recombination and 2.34 for
HLA-DR at 0% recombination was reported in one study [20]. In
humans, several studies report increases in DR4, DR5 (DR11), [13,
21-27], DR6 [20], and HLA-DQ3 (including both subtypes DQB1*0301
(DQ7) and DQB1*0302 (DQ8)) [13, 20-22]. Perhaps most interesting
are the differential HLA associations in clinical sub-types of AA
[28]. HLA-DRB1*1104 and DQB1*0301 (DQ7) are significantly increased
in long-standing AT/AU patients, (DR11: relative risk (RR) = 30.2
and DQ7: RR = 3.1 in AT/AU) [13]. Colombe et al. report a
bimodal pattern: an early-onset form of AA associated with HLA-DR11
with greater severity and with higher incidence of family history,
and a late-onset form being of milder severity and nonheritable
[28]. A study of Turkish AA patients (88 patients) [29], however,
did not reveal associations with DR4 and DR11 (DR5), but did show
significantly higher DQ3 and DQ1 in AA. Thus, ethnic variations and
differences in study designs that exist among these investigations
likely account to some extent for the variable results.
Negative HLA associations have been reported as well in AA. The
frequency of HLA-DR52a [27] and DR16 [29] have been reported to be
decreased. Similarly, a decrease in DR1 was observed among male AA
patients [26], possibly suggesting a protective role for the
same.
Collectively, studies of human HLA associations in AA have
revealed multiple associations with disease. Whether the
association of more than one HLA arises due to disease
heterogeneity or occurs due to strong linkage disequilibrium,
wherein an allele from one genetic locus is found in association
with a particular allele from another locus from the same haplotype
more frequently than expected [30], is not yet clear. In
Caucasians, most DR5 (DR11) haplotypes also carry the DQB1*0301
(DQ7 subtype of DQ3); nearly half of those with DR4 also carry the
DQB1*0301 (DQ7), with the remaining half carrying DQB1*0302 (DQ8
subtype of DQ3). Different global populations have characteristic
frequencies for single alleles and allele combinations in linkage
disequilibrium [30]. AA patients in Turkey have a higher frequency
of HLA-A1, HLA-B62, HLA-DQ1, and HLA-DQ3 [29], as well as DQB1*03
[31], while in Denmark, individuals with DQA1*0501, DQB1*0301, and
DPA1*0103 alleles carry a greater risk of developing AA [22]. More
recently, Han Chinese AA individuals were found to have a higher
frequency of HLA-DQA1*0104, DQB1*0604, and DQA1*0606 [32].
Interestingly, a study of a Belgian-German population found that
DRB1*03 (most suggestive of DRB1*0301) was a protective factor
against AA vs. controls [33]. However, the results also
demonstrated that the protective effect was frequently present in
individuals with a familial history of AA and less commonly among
those with sporadic cases. The study also demonstrated a
predisposing effect of DRB1*04 (most prevalent was DRB1*0401) in
the European population. Overall, the phenomenon of linkage
disequilibrium has made it difficult to conclude with certainty
which HLA allele(s) truly confer disease risk. The general
consensus at present is that the DQ relation seems primary, and DR
secondary [30]. Quite possibly, more than one MHC locus could
confer susceptibility to disease, particularly between distinct
clinical or ethnic sub-populations.
Because of their functional role in activation of immune (and
presumably autoimmune) responses, HLA molecules themselves are
likely to be important in disease. The association of AA with
HLA-DR and HLA-DQ supports the notion that CD4+ T cells are
involved in the disease process. HLA DR and DQ molecules are
responsible for presenting antigen to CD4+ T cells [34]. In
addition, tissue histology of affected AA areas demonstrates the
presence of perifollicular CD4+ lymphocytic infiltrate as well as a
CD8+ intrafollicular infiltrate [35]. AIDS patients devoid of CD4+
T cells have developed AA, further supporting a role for CD8+ T
cells in AA [36]. Kalish et al. suggest that normal hair epithelium
is an immune privilege site due to its lack of HLA-A, B, C
expression [34]. T cell recognition of follicular autoantigens may
then be induced by the increased expression of HLA-A,B,C as well as
HLA-DR during inflammatory conditions, resulting in a loss of
immune privilege [34]. It has been suggested that the production of
interferon-gamma from CD8+ T cells may be the mechanism in which
HLA-DR is induced [37].
There are several other non-HLA genes that map within the MHC
region that may be primary or additional susceptibility loci, with
HLA being in linkage association due to proximity. One plausible
candidate AA-susceptibility gene [38], Notch4, maps to the
centromeric end of the HLA class-III region (335 kb telomeric to
DRB1). In mammals, Notch 1-4 genes are known to be involved in
angiogenesis, hair growth, and T-cell maturation [39-43]. Several
associations between Notch4 gene polymorphisms and AA have been
reported [38, 44]. Whether the Notch4 association reflects a
distinct susceptibility locus within the MHC region, or occurs as a
result of linkage disequilibrium needs to be further examined.
Non-MHC genes
Most individuals who carry putative disease susceptibility MHC
alleles do not develop disease. Thus, MHC loci appear to be
necessary, but not sufficient for disease development. Accordingly,
disease concordance in monozygotic twins (55%) is much higher than
dizygotic twins [27]. Hence, it can be deduced that non-MHC genes
(as well as environmental factors, discussed below) are also
elemental in the pathogenesis of autoimmunity. For example, it is
known that the frequency of AA is greatly increased in patients
with trisomy-21 (Down’s syndrome), with an overall prevalence of
6-9%, 17% in females [45, 46], suggesting susceptibility loci may
be located on chromosome 21.
Furthermore, genes related to specific biological pathways that
are altered in disease comprise a pool of potential susceptibility
elements. Immune dysregulation has now almost irrefutably been
implicated in AA pathogenesis. The frequency of autoimmune
disorders among AA patients, efficacy of immunomodulatory
medications, presence of CD4+ and CD8+ T lymphocytes peri- and
intra-follicularly, ability of lesional skin grafted onto athymic
nude (nu/nu) mice to regrow hair, and induction of AA among SCID
mice from autologous lesional skin all serve as evidence for
immunologic causality in AA. Two case reports of AA developing
post-bone marrow transplantation indicate that susceptibility to AA
may be transferred [47], lending further support to the autoimmune
hypothesis of AA [48].
The immune system and the genes that are responsible for
regulating its activities are inextricably linked, foreshadowing
the putative importance of candidate immune related genes in the
induction, maintenance, and course of AA. The MX1 gene, encoding
the interferon-induced p78 protein MxA and located at 21q22.3 may
be one candidate. MxA is highly expressed in lesional anagen-hair
bulbs from AA patients compared to controls [49]. Out of the 4
known polymorphisms of MX1 gene, a significantly high association
of a +9959 polymorphism in intron 6 is seen with AA (OR = 1.79
(1.21-2.66)) [50]. Furthermore, AA frequency is increased in the
recessive condition APECED (autoimmune polyendocrinopathy
candidiasis ectodermal dystrophy syndrome), also known as PGA- type
I (autoimmune polyglandular syndrome), wherein the gene responsible
is autoimmune regulator (AIRE) – again mapping to chromosome
21q22.3 [51]. A rare polymorphic allele of this gene, AIRE916G is
increased in AA overall, and more so in AU [52].
Cytokines have often been implicated in AA pathology. On
chromosome 2, the gene cluster encoding the cytokine IL-1 and
related molecules has been reported on several occasions to be of
potential disease relevance. Interleukin-1 (IL-1) recruits
inflammatory cells such as macrophages, neutrophils, and
T-lymphocytes in tissues. IL-1α has also been shown to inhibit
human hair follicle growth and hair fiber production in whole-organ
cultures [53]. The gene IL1RN encodes IL-ra (IL-1 receptor
antagonist) and associations of the allele IL1RN*2 (IL1RN+2018)
with AU have been reported in 2 UK based studies, [54-56], although
this was not confirmed in a US population [57]. Polymorphisms at
position +4737 of IL-1L1, a homologue of IL-1r, have also been
reported in AA [54] and composite genotypes including at least
three copies of either of the alleles of IL1RN and IL1L1 loci
conferred more than a mere additive increase in risk for AA,
indicating a synergy between the two genes [54]. Further studies
with analysis of well-defined clinical subgroups will be needed to
elucidate whether IL1RN and IL1L1 themselves, or a gene in linkage
disequilibrium with both, predispose individuals to disease [54].
TNF-α also has an inhibitory effect on hair growth in vitro and is
speculated to induce hair loss in vivo. TNF-α gene polymorphisms
(TNF-308 genotype) distinguish AA patients with patchy vs.
extensive disease [58]. Recently, Migration Inhibitory Factor
(MIF), a lymphokine involved in the regulation of the
proinflammatory cytokines such as IL-1 and TNFα, was shown to be
increased in the sera of patients with severe AA [59]. Shimizu et
al. have proposed an MIF gene promoter polymorphism (MIF-173*C) as
a risk factor for early onset of disease (onset < 20 years)
[59].
TH-1 cytokines have been implicated in AA [34, 37], INF-γ
injected into human scalp transplanted on nude mice causes the
expression of ICAM-1 and HLA-DR33. ICAM-1 is an important adhesion
molecule that allows for the migration of lymphocytes to
inflammatory sites. In addition to INF-γ, IL-2 and TNF-α have been
shown to be expressed in situ in lesional skin of AA patients [34].
It remains to be determined if TH-1 dysregulation is genetically
encoded in AA.
Emerging strategies
Although there is no consensus strategy to study diseases with an
underlying complex genetic basis, newer tools are emerging as we
have advanced our knowledge of the complete human genome.
To date, no clear susceptibility loci (MHC or non-MHC) have been
identified for AA. Linkage analysis and positional cloning using
restriction-fragment length polymorphisms and polygenetic
microsatellite markers have been the mainstay approaches that have
helped to uncover nearly 1,200 disease causing genes, primarily in
single-gene Mendelian diseases [60]. To connect phenotype with
genotype in complex diseases such as AA, emergent strategies must
confront low allele frequencies and low relative risks of multiple
disease associated genes. Today, with wider sequencing of the human
genome, single nucleotide polymorphisms (SNPs) can be used in
large-scale linkage and association studies of non-Mendelian
diseases [61-64] (figure
4). Nevertheless, such studies in AA face considerable
challenges posed by clinical heterogeneity and genetic variability
between ethnically distinct populations.
In many instances, studies involving animal models with
spontaneous or induced AA have helped provide greater insights into
the pathogenesis, clinical behavior, and treatment modalities of
AA. In murine models, linkages have been reported to genes HOXC13
[65] and ZNT4 [66]. Using 211 microsatellite probes, Sundberg et
al. suggest a major susceptibility locus on mouse chromosome 17,
homologous to the human HLA class II region, and a minor locus on
chromosome 9 are linked to AA in the C3H/HeJ mice [67]. Further
exploration into the chromosomal linkages responsible for AA-like
conditions in animal models and correlation with putative
susceptibility loci in humans will be helpful to better define the
genetic basis of disease.
Working from the other end, high-throughput transcriptional
analysis of RNA expression has emerged as a useful strategy to the
study of complex disease. DNA microarrays have entered the
frontline of investigational medicine as we enter the post-genomic
era. “Gene-chips” represent a bio-informatics based intersection
between biology and technology that enables analysis on a
genome-wide scale. The transcriptional level of molecular
communication in a cell could be interpreted as a final outcome of
gene-gene and gene-environment interactions. As disease specific
molecular signatures are revealed [68, 69], they will facilitate
the identification of specific diagnostic and prognostic markers,
as well as novel therapeutic targets. Microarray studies in C3H/HeJ
mouse models and in humans affected with AA performed by Carroll
and colleagues demonstrated the importance of cell-mediated
mechanisms in the pathogenesis of AA [70]. Alternations in the
expression of immune related genes, particularly those involved in
T-cell response, were also observed by Subnramanya, et al. [71].
This study found evidence for immune response, cell cycle control,
and apoptosis related genes in disease pathogenesis. Further
analyses involving expression profiling will undoubtedly enable
redefining and refining the currently recognized and unrecognized
clinical sub-classes in AA class prediction and class discovery
respectively, and help to unravel functional pathways
mechanistically involved in AA pathology.
In summary, there is strong evidence for a genetic basis of AA.
The role of genes seems to be more prominent in the early
onset-poor prognosis type of AA than the late-onset type, as
evidenced by the higher family history among early-onset patients
and stronger associations with several MHC and non-MHC genes in
later category. Future work in gene mapping and gene expression
analysis can be expected to more clearly delineate disease
susceptibility loci and reveal genetic and molecular markers of
disease progression.
Environmental factors
Although very little is known regarding the non-genetic elements
relevant in AA, several environmental factors have been the subject
of speculation in this regard. While numerous reports exist
relating AA to infections, stress factors, toxins, and diet
content, none have been confirmed.
There has been one report demonstrating cytomegalovirus (CMV)
DNA in scalp lesions of AA [72]. This finding, however, failed to
be confirmed in another study [73], and PCR analysis of peripheral
blood mononuclear cells of patients showed no relation between AA
and latent or active CMV infection [14]. Similarly, Helicobacter
pylori was shown to have increased prevalence in patients with AA
in one report [74], but not another [75]. Thus, microbial
associations with AA remain non-conclusive.
Several studies suggest behavioral or psychological stress as
precipitating factors in AA. Epidemic AA has been reported in
industrial settings [76] and an increased frequency of disease has
been observed among prisoners [77]. Higher numbers of stressors in
the 6 months preceding hair loss [78] and higher prevalence of
diagnosed psychiatric disorders among AA patients [79] implicate a
yet unknown role for emotional stress in disease pathology. Several
reports also refute the role of stressors as factors in disease
pathology [80, 81]. Nevertheless, a role for neuropeptides
mediating psycho-neuro-endocrinimmunological connections has been
suggested in AA, as well as for several other dermatoses [82].
Type-2β receptors for the stress related corticotropin-releasing
hormone (CRH) are overexpressed in lesional alopecia skin [83],
however, specific mechanistic links between stress and disease
remain to be established.
Higher frequencies of AA have also been reported in patients
with celiac disease by several investigators, especially within the
pediatric population [84-88]. Evaluation of gluten-free-diets,
however, shows that the two conditions have an independent course
and this diet does not affect hair growth [85]. More recently, a
soy-derived genistein diet has been associated with resistance to
AA in murine models, suggesting an effect on estrogen dependent
mechanisms and/or immune-modulations imparting modifications in AA
susceptibility [87]. Finally, there has been one report linking
exposure to an acrylamide-like substance to AA [89].
Although there have been associations of external agents linked
to disease, much work remains to establish the contribution of
individual factors to AA pathogenesis. The likelihood that
environmental contacts are inconsistent within a population – not
every patient will have had equal exposure to all potential agents
– underscores mechanisms for disease variability and limits
experimental scrutiny. Most plausibly, environmental elements exert
impact through an interplay with genetic elements to modify the
development and expression of disease, and thus help to drive the
clinical heterogeneity in AA.
Final pathways of disease
The final pathways that lead to the development of AA remain to be
fully defined. Clearly, genes and environment are heavily
intertwined in the disease process. Although no clear susceptible
loci have been identified, genes regulating inflammatory mediators
of the immune system have been associated with more extensive
disease. In addition, several infectious and drug triggers are
implicated in modulating disease expression. The next frontier for
investigators will be to more directly link gene, gene-gene, and
gene-environmental effects with specific immunologic and/or
follicular cycle defects. A formidable challenge will lie in
assigning overlapping, but distinct sets of disease susceptibility
loci and precipitating/exacerbating infectious or other
environmental triggers to clinical subsets stratified by phenotype,
prognosis, and treatment response. The capacity of high-throughput
microarray studies to survey the sum effects of genetic and
environmental mediators across large patient populations may be the
technological vehicle best suited for these purposes.
While the genetics are complicated, studies to identify
disease-causing genes are not likely to be fruitless, particularly
with the emergence of newer genetic mapping technologies.
Initially, straightforward association studies simply involving
affected (any subtype) vs. unaffected individuals may offer the
best method to begin to untangle the genetics of AA. Later studies
with phenotypic subgroups may then distinguish the genes that
underlie the observed clinical complexity.
In any case, the wide-ranging genetic and environmental factors
associated with AA both reflect and reinforce the basis for the
substantial clinical heterogeneity that characterizes this complex
disease. Defining multiplex etiologic factors should help to
illuminate prognostic indicators for this largely unpredictable
condition. Moreover, unraveling the gene-environmental interactions
that underpin disturbances in biological pathways leading to the
variable expression of disease will undoubtedly set the stage for
new, disease-specific treatment modalities that move beyond the
largely nonspecific and variably efficacious options currently
available. A more clear delineation of specific genetic markers and
environmental triggers of AA can be expected to lead towards the
next generation of therapeutic medicine – where individualized
treatment options are tailored to a patient’s specific subcategory
of disease.
Acknowledgements
Financial support: none. Conflict of interest: none.
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