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Original paper

The role of CYP19A1 and ESR2 gene polymorphisms in female androgenetic alopecia in the Polish population

Adriana Łukasik
Karolina Kozicka
Aleksandra Pisarek
Anna Wojas-Pelc

Department of Dermatology, Jagiellonian University Medical College, Krakow, Poland
Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
Adv Dermatol Allergol 2022; XXXIX (4): 708-713
Online publish date: 2021/08/16
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Androgenetic alopecia is the most common type of non-cicatricial alopecia both in female and male patients. In both cases, the mechanism that leads to hair miniaturization is similar and involves a shortened anagen phase, and prolonged telogen and kenogen phases [1, 2]. The disease is chronic and progressive, leading to a gradual and diffuse hair loss in the central, parietal, and frontal scalp regions.

Amongst the numerous variables, including hormonal factors, that may impact the hair growth cycle in female androgenetic alopecia (FAGA), the role of androgens and oestrogens in the development of the disease remains unclear, especially given the fact that hormone levels are usually within normal ranges in FAGA patients [35].

Apart from the synthesis in the gonads and other organs, androgens and oestrogens are independently produced in hair follicles, where they undergo mutual interactions, impacting gene transcription and expression [6].

Presently, more and more studies focus on the role of oestrogens and oestrogen receptors located in the skin and its structures, and in particular on ER-β that is prevalent in hair follicles [7].

Both the CYP19A1 and ESR2 genes are involved in the transformation of sex hormones.

CYP19A1 is a gene located on chromosome 151, responsible for the production of aromatase, which is involved in the conversion of androgens (testosterone and androstenedione) into oestrogens [8]. Aromatase, similarly to 17β-HSD and 5α-reductase, is an enzyme that is also located in the pilosebaceous units [9]. The higher levels of aromatase in the occipital regions, described by Sawaya et al., may be indicative of the protective role of oestrogens [10]. The ESR2 gene, located on chromosome 14, encodes the β subtype (ER β) of intracellular nuclear oestrogen receptors.

To date, only a few studies have been carried out on the Chinese, Australian and European (UK, Germany) populations looking into the possible links between SNPs in the CYP19A1 and ESR2 genes and FAGA in women [1115]. Some of the studies indicated significant correlations only with respect to a few selected SNPs: rs4646, rs6493497 and rs7176005 for the CYP19A1 gene, and rs10137185, rs17101774 and rs2022748 for the ESR2 gene.

So far, no attempt has been made to carry out a similar study involving a population of Polish patients.


The aim of the study was to investigate single nucleotide polymorphisms (SNPs) in the oestrogen-related genes ESR2 and CYP19A1 in order to examine whether they might be susceptible genes for FAGA development. We tried to replicate some findings of other authors and search for new SNPs of possible importance.

Material and methods


117 FAGA patients and 128 healthy subjects, treated at the Department of Dermatology in 2017–2019, were included in the study. The diagnosis of androgenetic alopecia was confirmed by 2 dermatology specialists based on the typical history of the disease, its clinical picture, trichoscopic and histological examination.

The trichoscopic criteria of FAGA in videodermoscopy were based on the presence of 2 major criteria or 1 major and 2 minor criteria. Major criteria included an increased number of yellow dots (more than 4 yellow dots in the frontal area in 4 fields of vision at 70-fold magnification) and thin hairs, decreased average hair thickness in the frontal area and more than 10% of thin hairs (< 0.03 mm) in the frontal area. Minor criteria included an increased frontal area to occiput ratio of single-hair units (> 2 : 1), vellus hairs (> 1.5 : 1) and follicles with perifollicular discoloration (> 3 : 1) [16].

Exclusion criteria included co-existing diseases and medicines that could influence the hair loss.

The assessment of alopecia intensity was based on the 5-stage Sinclair scale. Table 1 presents the number of patients with individual stages of disease progression.

Table 1

Number of patients with particular grades of hair loss according to the Sinclair scale

Sinclair scaleNumber of FAGA patients (n = 117)

The patients’ average age was 49.2 in the FAGA group, and 47.8 in the control group. In the FAGA study arm, 35 patients started suffering from FAGA before the age of 40.

Approval for the study was obtained from the Bioethics Committee of the Jagiellonian University (decision no. 1072.6120.203.2017). All patients gave written consent for genetic studies.

SNP selection

SNP database “dbSNP” of the National Centre for Biotechnology Information was used to select the SNPs for analysis in the study [17]. The available polymorphisms, most frequently detected in the Caucasian population, with the genotype prevalence of at least 0.15, were eventually chosen for the study.

With respect to the CYP19A1 gene, 13 SNPs were selected, and with respect to the ESR2 gene, 11 SNPs were selected for analysis in the study (Table 2) [1827]. The SNPs were selected based on literature data. 4 SNPs were chosen for analysis based on their significance demonstrated in other studies carried out to date (rs4646, rs6493497, rs7176005 and rs10137185).

Table 2

Data for the SNP positions under study

SNPGeneGRCh38Allele variantsMAFRoleGene consequenceAssay ID
rs1152578ESR2chr14:64230319T/CT 0.424Not reportedIntron variantC___1436977_10
rs1256065ESR2chr14:64232214G/TG 0.431Associated with bone mineral density [18]Intron variantC___1436975_10
rs8006145ESR2chr14:64232732C/AA 0.245Prostate volume [19]Intron variantC__29383989_10
rs867443ESR2chr14:64234324G/AA 0.238Not reportedIntron variantC___1436972_20
rs17766755ESR2chr14:64249055G/AA 0.327Benign prostatic hyperplasia [20]Intron variantC__34495232_10
rs4365213ESR2chr14:64253546T/CC 0.412Alzheimer disease in women with Down syndrome [21]Intron variantC__32395442_20
rs6573549ESR2chr14:64254931T/CC 0.422Not reportedIntron variantC__32091355_10
rs61984409ESR2chr14:64263303A/CC 0.333Not reportedIntron variantC__90266873_10
rs7154455ESR2chr14:64269942G/CC 0.290Not reportedIntron variantC__29383994_10
rs960069ESR2chr14:64278284C/TC 0.443Not reportedIntron variantC___1436935_10
rs10137185ESR2chr14:64309058C/TT 0.100Associated with FPHL [22]Intron variantC__29621308_10
rs934634CYP19A1chr15:51208341C/TT 0.190Not reportedIntron variant, 3 prime UTR variantC___8794656_10
rs2255192CYP19A1chr15:51208638C/TT 0.189Not reportedIntron variant, 3 prime UTR variantC__15798398_10
rs4275794CYP19A1chr15:51208920T/CC 0.190Not reportedIntron variant, 3 prime UTR VariantC__32394041_10
rs12148604CYP19A1chr15:51209207C/TC 0.424Associated with sex hormone levels (estrone) [23]Intron variant, 3 prime UTR variantC__32071398_10
rs4646CYP19A1chr15:51210647A/CA 0.230Associated with FPHL, premature ovarian failure [12, 24]Intron variant, 3 prime UTR variantC___8234730_1_
rs10046CYP19A1chr15:51210789G/AG 0.422Associated with miscarriages [25]Intron variant, 3 prime UTR variantC___8234731_30
rs2899470CYP19A1chr15:51211480T/GT 0.348Serum oestrogen and oestrogen/testosterone ratio [26]Intron variantC___8234732_10
rs12591172CYP19A1chr15:51211530G/AG 0.420Not reportedIntron variantC___8234742_10
rs8029120CYP19A1chr15:51212737T/GT 0.410Not reportedIntron variantC___8234756_10
rs749292CYP19A1chr15:51266534G/AA 0.500Associated with ovarian cancer [27]Intron variantC___8801261_20
rs6493497CYP19A1chr15:51338638G/AA 0.092Associated with FPHL [11]Upstream variantC__29374681_10
rs7176005CYP19A1chr15:51339082C/TT 0.092Associated with FPHL [11]Upstream variantC_189237142_10
rs752760CYP19A1chr15:51339282C/TT 0.385Not reportedUpstream variantC____798312_10

[i] MAF – minor allele frequency, SNP – single nucleotide polymorphism, FAGA – female androgenetic alopecia.

Polymorphisms rs12148604 and rs2899470 in the CYP19A1 gene are linked with the levels of sex hormones. The remaining SNPs have not been examined or described in the literature yet.

Extraction of DNA

Peripheral blood for molecular tests was collected in EDTA anticoagulant tubes. A 6% solution of high-molecular weight dextran (Dextran T500, Pharmacia) was added to the whole blood for erythrocyte sedimentation. Leukocyte-rich plasma was drawn off and centrifuged for 10 min/20000 x g. DNA was isolated from white blood cells with the Chomczynski and Sacchi method (DNAzol, Gibco). 0.4 ml of the DNAzol reagent was added to the centrifuged sediment and shaken. Following the dissolution of leukocyte cellular membranes, DNA was precipitated with 0.2 ml of 95% ethyl alcohol. Afterwards, the isolated DNA was washed in 70% ethanol, and dried in an incubator at the temperature of 37°C. Later on, the DNA was solubilized in redistilled water, and in that form used for further studies.

Real-time PCR

The isolated DNA was amplified and genotyped with the use of the real-time polymerase chain reaction (real-time PCR) method.

The real-time PCR reaction was carried out on 96-well plates in the 7900 HT Real-Time PCR System (Applied Biosystems). A standard reaction mix included polymerase and substrate solutions; TaqMan Universal PCR Master Mix, starters, probes, water, and DNA based on the manufacturer’s recommendations (TaqMan Universal PCR Master Mix Protocol – Applied Biosystems). The probes and starters were purchased from Applied Biosystems in the form of ready-to-use TaqMan Gene Assays.

Statistical analysis

The study analysed 24 single nucleotide polymorphisms (SNP) located in the ESR2 and CYP19A1 genes (Table 2). Each genotype for 24 studied polymorphisms was coded in an additive way as 0, 1, or 2 considering the number of minor alleles. Genotype–phenotype association analyses were conducted using univariate binary logistic regression for FAGA defined as 1 (case) vs. 0 (control). Allelic odds ratios (ORs) with respective 95% confidence intervals (CIs) and p-values for the minor alleles classified in an additive manner were calculated (Table 3). Recessive and dominant modes of inheritance were also assessed where genotypes were coded as 0 and 1 vs. 2, and 0 vs. 1 and 2, respectively (Tables 4 and 5). Associations were tested using PS IMAGO PRO 6.0 (IBM SPSS Statistics 26).

Table 3

Results of association analysis between individual SNP positions and FAGA

SNPGeneOR (95% CI)P-value
rs1152578ESR21.092 (0.755–1.581)0.640
rs1256065ESR21.153 (0.799–1.665)0.446
rs8006145ESR20.883 (0.561–1.391)0.592
rs867443ESR20.941 (0.597–1.483)0.793
rs17766755ESR21.070 (0.713–1.607)0.743
rs4365213ESR20.992 (0.685–1.436)0.967
rs6573549ESR21.007 (0.699–1.452)0.969
rs61984409ESR20.966 (0.648–1.441)0.865
rs7154455ESR20.870 (0.563–1.346)0.533
rs960069ESR21.124 (0.776–1.628)0.535
rs10137185ESR20.892 (0.502–1.584)0.697
rs934634CYP19A11.151 (0.728–1.820)0.547
rs2255192CYP19A11.073 (0.678–1.698)0.763
rs4275794CYP19A11.032 (0.653–1.630)0.894
rs12148604CYP19A10.917 (0.636–1.323)0.645
rs4646CYP19A10.860 (0.554–1.335)0.501
rs10046CYP19A10.970 (0.671–1.401)0.870
rs2899470CYP19A10.980 (0.660–1.455)0.919
rs12591172CYP19A10.947 (0.654–1.371)0.771
rs8029120CYP19A10.893 (0.607–1.314)0.566
rs749292CYP19A11.171 (0.824–1.663)0.378
rs6493497CYP19A11.396 (0.762–2.558)0.280
rs7176005CYP19A11.404 (0.766–2.574)0.272
rs752760CYP19A10.987 (0.678–1.438)0.947

[i] CI – confidence interval, OR – odds ratio, SNP – single nucleotide polymorphism.

Table 4

Results of association analysis between individual SNP positions and FAGA for a recessive model of allele classification

SNPGeneOR (95% CI)P-value
rs1152578ESR20.833 (0.424–1.638)0.597
rs1256065ESR20.948 (0.490–1.836)0.875
rs8006145ESR20.439 (0.083–2.311)0.331
rs867443ESR20.444 (0.084–2.340)0.338
rs17766755ESR21.013 (0.395–2.600)0.978
rs4365213ESR21.090 (0.544–2.184)0.808
rs6573549ESR21.048 (0.535–2.053)0.890
rs61984409ESR20.826 (0.334–2.047)0.680
rs7154455ESR20.411 (0.105–1.605)0.201
rs960069ESR20.904 (0.469–1.742)0.762
rs10137185ESR20.350 (0.036–3.417)0.366
rs934634CYP19A11.844 (0.430–7.909)0.410
rs2255192CYP19A11.860 (0.434–7.981)0.404
rs4275794CYP19A11.844 (0.430–7.909)0.410
rs12148604CYP19A10.797 (0.408–1.560)0.509
rs4646CYP19A10.734 (0.202–2.673)0.640
rs10046CYP19A10.939 (0.479–1.840)0.854
rs2899470CYP19A10.960 (0.410–2.248)0.924
rs12591172CYP19A10.887 (0.449–1.754)0.730
rs8029120CYP19A10.648 (0.308–1.366)0.254
rs749292CYP19A11.082 (0.610–1.921)0.787
rs6493497CYP19A12.390 (0.212–26.988)0.481
rs7176005CYP19A12.390 (0.212–26.988)0.481
rs752760CYP19A11.621 (0.771–3.410)0.203

[i] CI – confidence interval, OR – odds ratio, SNP – single nucleotide polymorphism.

Table 5

Results of association analysis between individual SNP positions and FAGA for a dominant model of allele classification

SNPGeneOR (95% CI)P-value
rs1152578ESR21.361 (0.790–2.346)0.267
rs1256065ESR21.421 (0.822–2.456)0.208
rs8006145ESR20.935 (0.565–1.547)0.793
rs867443ESR21.010 (0.609–1.674)0.971
rs17766755ESR21.108 (0.666–1.843)0.692
rs4365213ESR20.935 (0.549–1.594)0.806
rs6573549ESR20.985 (0.576–1.685)0.957
rs61984409ESR21.005 (0.604–1.671)0.986
rs7154455ESR20.954 (0.576–1.579)0.855
rs960069ESR21.399 (0.801–2.442)0.238
rs10137185ESR20.957 (0.500–1.831)0.894
rs934634CYP19A11.109 (0.654–1.878)0.702
rs2255192CYP19A11.008 (0.594–1.712)0.975
rs4275794CYP19A10.958 (0.566–1.624)0.874
rs12148604CYP19A10.961 (0.561–1.646)0.885
rs4646CYP19A10.856 (0.513–1.428)0.552
rs10046CYP19A10.975 (0.570–1.668)0.926
rs2899470CYP19A10.980 (0.587–1.639)0.940
rs12591172CYP19A10.960 (0.561–1.644)0.881
rs8029120CYP19A11.012 (0.590–1.735)0.965
rs749292CYP19A11.416 (0.792–2.529)0.240
rs6493497CYP19A11.401 (0.719–2.733)0.322
rs7176005CYP19A11.410 (0.723–2.750)0.313
rs752760CYP19A10.765 (0.454–1.292)0.317

[i] CI – confidence interval, OR – odds ratio, SNP – single nucleotide polymorphism.


Univariate association analyses did not show statistical significance for any of the DNA variants of the ESR2 and CYP19A1 genes in the studied sample population (Table 3). No significant effects were also noted for a recessive and dominant manner of minor allele classification (Tables 4 and 5).


Many hormones, including the thyroid, adrenal, pineal and pituitary gland hormones, impact the hair growth cycle [28]. Oestrogens are usually believed to have protective qualities [3, 29, 30], even though some studies indicate that hair growth is slowed under their influence due to the initiation of an earlier catagen phase, and prolongation of telogen phase [31].

With respect to the CYP19A1 gene, Yip et al. demonstrated a statistically significant incidence of the CC genotype for polymorphism rs4646 in their study carried out in Australia [12]. Johansson et al. described higher oestrogen levels in patients with that genotype, what could substantiate the hypothesis that the hair growth cycle is inhibited under the influence of oestrogens [32].

Redler et al. failed to confirm the findings of Yip et al. in a study involving the German and British populations [13]. In a study of Rui et al. involving the Chinese population, a statistically significant difference was observed with respect to the distribution of alleles in polymorphisms rs6493497 and rs7176005, but no correlation was found for rs4646 either [11].

As regards the ESR2 gene, Yip et al. indicated the significance of rs10137185, rs17101774, and rs2022748 polymorphisms in the Australian population [14].

Even though initially Redler et al. did not observe any significant correlations in the German and British populations, they did confirm the significance of rs10137185 in a later study involving the German population only. The authors pointed to potentially important variables such as the number of patients included in the study and a later stage of alopecia progression [22].

That proposition is confirmed by the results obtained in a study conducted by Yip et al., which involved the largest group of subjects (484 FAGA patients and 471 control subjects) [12].

In our study, we searched for correlations that would be true for the entire group of patients, taking into account the severity grade of alopecia, however the small number of patients with advanced grade of hair loss might have impacted the final results, leading to a lack of agreement with Redler’s study results.

The number of patients included in our study was sufficient to assess allele frequency in the Polish population, but it might be too small to reach the threshold of statistical significance.


Numerous studies carried out so far on FAGA etiopathogenesis have not been successful at explicating the role of genes or sex hormones in the development of the disease.

Our study showed no association of CYP19A1 and ESR2 genes with FAGA in the Polish population, although some of the SNPs included in our research showed a statistically significant incidence in Australian, Chinese and German populations.

As the small size of the studied group could be the reason for no findings regarding the selected SNPs, it prompts us to conclude that further research is needed that would include more patients.

It is also possible that another variant in the CYP19A1 and ESR2 gene is associated with FAGA in the Polish population.

Due to the suspected possibility of communication and co-dependence of receptor pathways for steroid hormones like oestrogens and androgens, it is also necessary to look into the functioning of hormones, and a potential impact of genes on hormonal activity [33, 34].

Undoubtedly, the high costs incurred in the course of studies remain one of the limitations involved.

Conflict of interest

The authors declare no conflict of interest.



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