ARTICLE
Auteur(s) : Asem Alkhateeb1,
Nour Al-Dain Marzouka1, Firas
Qarqaz2
1Biotechnology and Genetics Department, Jordan
University of Science and Technology, P.O. Box 3030 Irbid
22110, Jordan
2Dermatology Department, Jordan University
of Science and Technology, Irbid, Jordan
accepté le 27 Ao�t 2010
Vitiligo is an acquired disease characterized by dynamic loss of
pigmentation of the skin which is caused by the death of
melanocytes from the involved areas by an autoimmune based
mechanism [1]. Vitiligo is a non-contagious and common disorder
with a prevalence of 0.38% in Caucasians [2]. No study has been
conducted on the prevalence of vitiligo among Arabs but it is
thought to have a similar prevalence.
Vitiligo is a genetic disorder with complex etiologies involving
multiple genes and with environmental triggers playing a role in
producing the phenotype [1, 3]. Epidemiologic studies support a
genetic and autoimmune basis of vitiligo. Vitiligo clusters in
families, results in increased risk in first-degree relatives, and
shows a high concordance rate in monozygotic twins [3, 4].
A quarter of vitiligo patients have other autoimmune diseases
and their close relatives are at a higher risk for autoimmune
disease than the general population. These associated autoimmune
diseases include autoimmune thyroid disease, adult-onset autoimmune
diabetes mellitus, systemic lupus erythematosus, rheumatoid
arthritis, Addison's disease, pernicious anemia, and psoriasis [4,
5].
Linkage and association studies have implicated many genes in
vitiligo. The genes that had strong support include CTLA, [6, 7]
human leukoctye antigen (HLA) loci, [8, 9] NALP1 (NLRP1), [10, 11]
and PTPN22 [12-15]. All these genes are associated with autoimmune
susceptibility [16] and thus support the autoimmune basis of
vitiligo. Recently, a variant in the SMOC2 gene, rs13208776, was
found to be associated with vitiligo, in an isolated European
founder population [17]. SMOC2 gene is located very close to IDDM8,
which is linked and associated with autoimmunity [18-22].
Before this paper, SMOC2 was reported to be associated with only
the European founder population found in Romania. Whether SMOC2 is
specific to that population, or a risk factor in other populations,
is yet to be determined. In this study we examined the contribution
of the SMOC2 variant, rs13208776, to the risk of vitiligo in a set
of Jordanian Arab patients. We also worked out the allele
frequency of the variant in our Jordanian population. For that
purpose we genotyped SMOC2 variant in 44 generalized vitiligo
patients and 151 matched controls. Our results do
not support association of the variant with the disease.
Materials and methods
Study subjects
Study cases were recruited from one large hospital serving the
north part of Jordan (King Abdullah Hospital) during 2008. Vitiligo
diagnosis was established by a dermatologist (F.Q) using standard
diagnostic criteria [24]. All 44 generalized patients
completed a detailed questionnaire that included information about
age, age of onset, sex, other autoimmune diseases, family history,
and other relevant information. All 151 controls reported no
history of vitiligo or apparent autoimmune disease; they were
matched to patients with regard to age, sex, and geographical
distribution. Informed consent was obtained from all
195 participants in the study. This study was approved by the
ethics Institutional Review Board of the Jordan University of
Science and Technology.
Genotyping
Genomic DNA from patients and controls was extracted from
peripheral blood using a genomic purification kit (Qiagen).
Genotyping of the rs13208776 SNP was done using a PCR-based
restriction fragment length polymorphism (RFLP) assay. An amplicon
of 485bp containing the SNP was generated using the forward primer
5′- CTCAGAAATTGGCACCCTCT-3′ and reverse primer 5′-
GTCTCCGGTTTAAGGGAGGA-3′ (GenBank accession number NM_001166412.1).
Primers were designed using Primer3 software [25]. DNA
amplification was done in a 25 μL PCR reaction volume with
12.5 μL GoTaq® Green Master Mix, 2x (dNTPs, MgCl2,
PCR buffer and Taq polymerase) (Promega Corp., Madison, WI, USA),
2.5 μL of each primer (1 μmol/L final concentration)
(Alpha DNA, Montreal QC, Canada), 4.5 μL nuclease free water,
and 3.0 μL (~50 ng) of DNA template. A touch down
PCR program was performed; 95 °C for 10 minutes, followed
by 18 cycles of denaturation at 94 °C for
30 seconds, annealing at 65 °C for 30 seconds (with
a 0.5 °C decrease in each subsequent cycle) and an extension
at 72 °C for 30 seconds. Following this were twenty-five
cycles of denaturation at 94 °C for 30 seconds, annealing
at 56 °C for 30 seconds and extension at 72 °C for
30 seconds. PCR products were run on 2% agarose gel and
visualized by UV light after ethidium bromide staining to assess
the correct sizing of the amplified product. Following PCR,
products were digested by BsaHI (New England Biolabs, Ipswich, MA,
USA) for 2 hours at 37 °C. Variant allele (G) resulted in
the digestion of the 485 bp amplicon into 223 bp,
165 bp and 97 bp fragments. Variant allele (A) resulted
in 388 bp and 97 bp fragments. The restriction fragments
of PCR products were separated by electrophoresis on a 3% agarose
gel containing 10 μg/mL ethidium bromide and visualized by UV
light, and genotypes were recorded. Positive and negative controls
were included in each run.
Statistical analysis
Data were entered in Excel (Microsoft Corporation) for the
calculation of allele and genotype frequencies. Hardy-Weinberg
equilibrium (HWE) was tested to determine if the population was
fulfilling the HWE at the variant locus. It was assessed in the
observed genotype distribution with a chi-squared test. Allelic
association p-values were determined using a Chi square test
between cases and controls. Genotypic association p-values were
determined by the Freeman-Halton extension of Fisher's exact test
for a 2 × 3 contingency table which evaluates the occurrence of all
three genotypes as an array between the cases and controls [26].
A web-based calculator was used to compute p-values (Vassar
Stats). A p-value < 0.05 was considered to be statistically
significant for both tests. Odds ratio and 95% confidence interval
were calculated to assess the risk associated with alleles and
genotypes.
Results
In this study we included 44 Jordanian patients with vitiligo, all
of whom had the generalized type of vitiligo (table 1). The sex ratio was almost equal
(52.3% female, 23 of 44 overall). The average age of
patients was 28.8 years and the average age of onset was 21.1
years, similar to that found in a larger cohort of Caucasian
patients in the US and UK [4]. Most patients (77.3%, 34 of 44)
reported changing patches of depigmentation. The majority of
patients (93.2%, 41 of 44) had less than 25% coverage of
depigmented patches. A few patients reported a different eye
color (8.1%, 3 of 37; not all patients responded to all
questions), none had deafness, and 5.3% (2 of 38) reported exposure
to chemicals. Just 2.3% (1 of 42) patient reported other
autoimmunity (diabetes) and 15.4% (4 of 26) reported a family
history of vitiligo. One hundred and fifty-one Jordanian control
subjects who had no history of vitiligo or any apparent autoimmune
disease were recruited. Patients and controls were attendees of the
same hospital, which serves the north part of Jordan, where the
population is known to be relatively genetically homogeneous. No
significant differences (p < 0.05) were found between subjects
and controls with regard to age and sex.
All 44 patients with vitiligo were genotyped for the
rs13208776 using restriction fragment length polymorphism (RFLP).
A representative gel for the data generated for the different
genotypes is shown in figure 1. Genotypical
frequencies of the SMOC2 variant in the control population met HWE
expectations. In the control group, the frequency of heterozygous
genotype (GA) was 33.1% (50 of 151) and for the homozygote minor
genotype (AA), 7.9% (12 of 151). This corresponded to a minor
(mutant) allele frequency of 24.5% (table 2). In vitiligo patients, the frequency
of the heterozygous genotype (GA) was 50.0% (22 of 44) and for the
homozygote minor genotype (AA), it was 4.5% (2 of 44), this
corresponded to a minor (mutant) allele frequency of 29.5%.
Statistical analysis showed no significant allelic (p = 0.21) or
genotypic (p = 0.12) difference between vitiligo patients and
controls (table 2).
Table 1 Clinical and demographic characteristics
of vitiligo patients
|
Characteristic
|
Value
|
|
Gender
|
52.3% female (23 of 44)
|
|
47.7% male (21 of 44)
|
|
Age (y)
|
28.8 ± 15.9
|
|
Age of onset (y)
|
21.1 ± 16.0
|
|
Patients with changing patches
|
77.3% (34 of 44)
|
|
Depigmented areas
|
93.2% (1-25% coverage)
|
|
2.3% (26-50% coverage)
|
|
0% (51-75% coverage)
|
|
4.5% (76-100% coverage)
|
|
Patients with different eye color
|
8.1% (3 of 37)
|
|
Deaf vitiligo patients
|
0%
|
|
Exposed to chemicals
|
5.3% (2 of 38)
|
|
Other autoimmunity
|
2.4% (1 of 42)
|
|
Reported family history of vitiligo
|
15.4% (4 of 26)
|
Table 2 Allele and genotype distributions
of the SMOC2 intronic variant G>A single nucleotide
polymorphism in Jordanian vitiligo patients and controls
|
Genotype or allele
|
Vitiligo (n = 44) [no. (%)]
|
Controls (n = 151) [no. (%)]
|
p-valuea
|
Odds ratio (95% CI)
|
|
GG
|
20 (45.5)
|
89 (58.9)
|
0.12
|
|
|
GA
|
22 (50.0)
|
50 (33.1)
|
|
|
|
AA
|
2 (4.5)
|
12 (7.9)
|
|
|
|
G
|
62 (70.5)
|
228 (75.5)
|
0.21
|
1.29 (0.76-2.19)
|
|
A
|
26 (29.5)
|
74 (24.5)
|
|
|
Discussion
In this study we tried to investigate a newly discovered candidate
risk gene for vitiligo to confirm or negate its association with
vitiligo in our Jordanian Arab vitiligo patients. This is the first
work intending to replicate the Birlea et al. findings
regarding SMOC2 and vitiligo [17]. We recruited 44 patients
with generalized vitiligo from the same hospital, which serves the
north part of Jordan. Each patient filled in a questionnaire
regarding clinical and demographic characteristics. We had
151 matched autoimmune-free control individuals.
Our patients had an equal sex ratio which is consistent with the
majority of previous reports. Age of onset was comparable to that
found in Saudi [27], Turkish [28], and Caucasian patients from the
US and UK [4]. Extent of depigmentation was scored by self-report
of fractional skin surface involvement in quartiles: < 25%,
25-50%, 50-75%, 75-100%. The majority of patients (93.2%) reported
involvement of < 25% of their skin surface. Most patients
(77.3%) reported changing sizes of the depigmented patches.
Familial aggregation of vitiligo is common and supports the genetic
basis of vitiligo. In our patient cohort, 15.4% of vitiligo
patients reported a family history of the disease, consistent with
previous reports [4]. However, very few patients reported the
occurrence of other autoimmunity (2.3%); this may be due to a lack
of awareness or to the relatively young age of our patients
(average age 28.8 years).
The SMOC2 (secreted modular calcium binding gene) is located on
the long arm of chromosome 6. It encodes a broadly expressed, SPARC
(secreted protein acidic and rich in cyteine)-related glycoprotein
that harbors two EF-hand calcium binding domains, two thyrogobulin
type-I domains, a follistatin-like domain and a putative signal
peptide [29, 30]. The exact function of the SMOC2 protein is not
determined, although it has been suggested to play a role in
metastasis [31], cell cycle regulation [32], and angiogenesis [33].
The SMOC2 protein has a role in calcium binding, one link to
vitiligo is the previous demonstration of defective calcium
transport in melanocytes and keratinocytes of vitiligo patients
[34]. Additionally, the SMOC2 protein is expressed in the basal
levels of the epidermis and it stimulates primary keratinocytes to
attach in culture. This could link SMOC2 to vitiligo since one of
the etiological theories of vitiligo hinges on the fact that
defective cell adhesion could cause chronic cell detachment and
thus melanocyte loss in vitiligo patients. The SMOC2 gene might not
be in linkage disequilibrium with IDDM8 which is very close in
location to SMOC2. And IDDM8 has been connected to type I diabetes
[18-21], and rheumatoid arthritis [22]. Type I diabetes and
rheumatoid arthritis are epidemiologically associated with
generalized vitiligo in the general Caucasian population [4] and in
the Romanian population [35] where the SMOC2 variant was associated
with vitiligo [17]. However, no paper till now has suggested a
direct association of IDDM8 with vitiligo.
In our sample of generalized vitiligo patients we could
not support the association of the SMOC2 variant with
vitiligo. Our population frequency of the variant was found to be
24.5%, indicating a polymorphic marker. This population allele
frequency is the first to be reported. It may differ across
different populations. Our patients’ allele frequency was 29.5%,
which was not significantly different from the controls’ frequency.
Different genotypes were also not statistically different in
patients compared to controls. Our results suggest that SMOC2 does
not play a major role as a risk factor for vitiligo in our
patients. The postulated role of SMOC2 might be population
specific, as genetic purification in the small isolated Romanian
population resulted in a higher population specific risk for the
SMOC2 susceptibility allele. This attributable risk might be much
smaller in out-bred Caucasian populations or other world
populations. On the other hand our small patient cohort might hide
the contribution of this candidate variant. A larger cohort
could give a higher statistical assurance to our results.
Conclusion
In summary, we investigated the association of the SMOC2 rs13208776
intronic variant with vitiligo in our patients and our results
showed a lack of such an association. This may be due to
differences in the genetic make-up between Caucasian and
Mediterranean patients, an isolated population-specific
attributable risk for a rare variant, or could be due to the
limited number of vitiligo patients in our cohort. A larger
independent cohort could confirm or negate this lack of association
of SMOC2.
Disclosure
Acknowledgments: We thank all participating patients and controls.
We thank Dr Ziad Al-Baghdadi for his help in collecting
patient samples. This work was supported by grant #43/2008 from the
Deanship of Research in Jordan University of Science and
Technology. Conflict of interest : none.
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