Am. J. Hum. Genet. 77:140–148, 2005

ReportGenetic Variation in the Human Androgen Receptor Gene Is the Major
Determinant of Common Early-Onset Androgenetic Alopecia
Axel M. Hillmer,1,2 Sandra Hanneken,4 Sibylle Ritzmann,4 Tim Becker,3 Jan Freudenberg,2Felix F. Brockschmidt,2 Antonia Flaquer,3 Yun Freudenberg-Hua,2 Rami Abou Jamra,2Christine Metzen,4 Uwe Heyn,2 Nadine Schweiger,4 Regina C. Betz,2,5 Bettina Blaumeiser,5
Jochen Hampe,6 Stefan Schreiber,6 Thomas G. Schulze,7 Hans Christian Hennies,8Johannes Schumacher,2 Peter Propping,2 Thomas Ruzicka,4 Sven Cichon,1,5Thomas F. Wienker,3 Roland Kruse,4 and Markus M. Nöthen1,5
1

Department of Genomics, Life & Brain Center, and 2Institute of Human Genetics, and 3Institute for Medical Biometry, Informatics andEpidemiology, University of Bonn, Bonn; 4Department of Dermatology, University of Düsseldorf, Düsseldorf; 5Department of Medical
Genetics, University of Antwerp, Antwerp; 6Institute for Clinical Molecular Biology, Christian-Albrechts-Universität zu Kiel, Kiel, Germany;
7
Division of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Mannheim; and 8Department of Molecular Genetics andGene Mapping Center, Max Delbrück Center for Molecular Medicine, Berlin

Androgenetic alopecia (AGA), or male-pattern baldness, is the most common form of hair loss. Its pathogenesis isandrogen dependent, and genetic predisposition is the major requirement for the phenotype. We demonstrate thatgenetic variability in the androgen receptor gene (AR) is the cardinal prerequisite for the development of earlyonset AGA, with an etiological fraction of 0.46. The investigation of a large number of genetic variants covering
the AR locus suggests that a polyglycine-encoding GGN repeat in exon 1 is a plausible candidate for conferring
the functional effect. The X-chromosomal location of AR stresses the importance of the maternal line in theinheritance of AGA.

Androgenetic alopecia (AGA [MIM 109200]), or malepattern baldness, is characterized by a defined patternof hair loss from the scalp (Hamilton 1951). In whites,
the proportion of affected males increases steadily withage, so that a male in his 50s has a 50% chance of havingsome degree of AGA (Hamilton 1951). Association of
AGA with a variety of clinical phenotypes has been suggested, including coronary heart disease (Lotufo et al.
2000), benign prostatic hyperplasia (Hawk et al. 2000),
prostate cancer (Oh et al. 1998), and disorders associated with insulin resistance (Matilainen et al. 2000). Androgen dependence is an important characteristic of
AGA, and genetic disposition, which is assumed to bepolygenic, plays the most substantial role in the develReceived March 21, 2005; accepted for publication April 27, 2005;
electronically published May 18, 2005.
Address for correspondence and reprints: Dr. Markus M. Nöthen,Department of Genomics, Life & Brain Center, University of Bonn,
Sigmund-Freud-Straße 25, 53127 Bonn, Germany. E-mail: markus.noethen@uni-bonn.de䉷 2005 by The American Society of Human Genetics. All rights reserved.
0002-9297/2005/7701-0015$15.00

140

opment of AGA (Küster and Happle 1984; Ellis et al.
1998; Nyholt et al. 2003). Although the only factor
known to influence onset age in patients with AGA isgenetic predisposition, no systematic approach has hitherto been undertaken, to our knowledge, to identify thecontributing genes.
As part of a genomewide linkage study of AGA, weinvestigated linkage to markers covering the X chromosome. The sample consisted of 95 families in which
at least two brothers had early-onset AGA (391 genotyped individuals, including 201 affected men). We obtained evidence of linkage in chromosomal region Xq1222 (nonparametric linkage [NPL] score of 2.70 [fig. 1])(for X-chromosomal marker information, see table 1).
This region contains the AR gene (MIM 313700), which
is an obvious candidate for explaining the developmentof AGA, and an association with this region has beensuggested elsewhere (Ellis et al. 2001), on the basis ofresults from the investigation of three polymorphic sites.
In the present study, we have systematically explored thecontribution of the AR gene to the development of earlyonset AGA.

Figure 1
Multipoint NPL analysis of chromosome X, calculated by the Allegro v1.2 software (Gudbjartsson et al. 2000). The X-axis is the chromosome location (top, cM; bottom,
STR marker), and the Y-axis is the LOD score.

142

Am. J. Hum. Genet. 77:140–148, 2005

Table 1
STR Markers Used for Linkage Analysis
of Chromosome X
The table is available in its entirety in the online
edition of The American Journal of Human Genetics.

We tested 39 SNPs, two STRs (a polyglutamine-encoding CAG repeat and a polyglycine-encoding GGN
repeat in exon 1 of AR), and one biallelic insertion polymorphism (XARx8insA), in a range of 4.4 Mb at the
AR locus, for association with AGA (fig. 2). Our analysis
included the three previously studied variants (Ellis etal. 2001): the CAG and GGN repeats and StuI RFLP
(rs6152). TaqMan assays for genotyping of SNPs, listed
in table 2, were designed by Applied Biosystems. PCRs
were performed using 2.5 ng genomic DNA, AmpliTaq
Gold DNA polymerase (Applied Biosystems), and an
annealing temperature of 60⬚C for 45 cycles on Biometra
T1 (Biometra) or Perkin Elmer GeneAmp 9700 (Applied
Biosystems) thermocyclers. Fluorescence was measured
with an ABI Prism 7900HT sequence detection system(Applied Biosystems). The fragment lengths of the CAG
repeat, the GGN repeat, and XARx8insA were determined using the following fluorescence-labeled primers
for PCR: CAG-F 5-TCCAGAATCTGTTCCAGAGCGTGC-3 and CAG-R 5-GCTGTGAAGGTTGCTGTTCCTCAT-3 (La Spada et al. 1991), GGN-F 5-CCTGGCACACTCTCTTCACA-3 and GGN-R 5-GGATAGGGCACTCTGCTCAC-3, and XARx8insA-F 5-CACGGGAAGTTTAGAGAGCT-3 and XARx8insA-R 5-TCACCTTCTCGTCACTATTG-3. Forty nanograms of genomic DNA was used in PCRs with AmpliTaq DNA
polymerase (Applied Biosystems) in 38 cycles on a PTC200 (MJ Research). The annealing temperatures were
62⬚C–60⬚C (touchdown PCR) for the CAG repeat, 58⬚C
for the GGN repeat, and 63⬚C–55⬚C (touchdown PCR)
for XARx8insA. MasterAmp PCR PreMix G (Epicentre)
was used to amplify GGN fragments. Fragment lengthsof the amplified products were analyzed on an ABI Prism
377 DNA sequencer (Applied Biosystems). Double-strand
sequencing of genomic regions was performed with the
ABI Prism BigDye Terminator Cycle Sequencing kit, version 2.0 (Applied Biosystems), and the ABI Prism 3730
DNA analyzer (Applied Biosystems).
For case-control analysis, we compared allele frequencies in 198 males with early-onset AGA (including 95
unrelated and randomly chosen affected individuals fromthe linkage-analysis families), 188 control individuals, and
157 unaffected individuals. For family-based association
analysis, we studied 179 families containing at least one
affected male in the youngest generation. The familybased association sample included the 95 families fromthe linkage analysis and overlapped with the case sample,
for 179 individuals. All affected males were aged !40

years (mean [Ⳳ SD] 32.0 Ⳳ 5.2) and had AGA that wasrepresentative of the most severely affected 10% of the
distribution for the respective age class, on the basis of
the classification of Hamilton (1951) (modified by Norwood [1975]). AGA classification, age, and ethnicity werethe exclusive criteria used to select individuals for inclusion in the case sample. Unaffected males were aged 160
years (mean 67.9 Ⳳ 6.2) and without AGA, representing
the least-affected 20% of the distribution for this age class.
Families and unrelated individuals both with and without
AGA were recruited through various sources, includingpress reports and advertisements in magazines, newspapers, and placards. Control individuals were male blood
donors from the blood transfusion center of the University
Hospital Bonn, from whom information was available
only on sex, age in years (mean 29.4 Ⳳ 8.6), and ethnicity.
EDTA anticoagulated venous blood samples were collected from all individuals, and lymphocyte DNA was
isolated by salting out with saturated NaCl solution (Miller et al. 1988). All participants were of German descent.
The study was approved by the ethics committee of the
University of Bonn, and informed consent was obtained
from all participants.
Association analysis was conducted using a modification of the FAMHAP software (Becker and Knapp
2004a, 2004b) for X-chromosomal data. Case-control
SNP single-marker analysis was performed using the x2
distribution of the 2 # 2 contingency table, and multiallelic markers were evaluated with the permutationalversion of the x2 test. For case-control haplotype analysis, P values were calculated from the x2 distribution
with n⫺1 df of the respective likelihood-ratio test (n pnumber of different haplotypes). The family data wereanalyzed with the permutation-based association test for
nuclear families (Zhao et al. 2000; Knapp and Becker
2003). For each marker (single-locus analysis) and eachmarker combination (haplotype analysis), we used 1010
permutation replicates.
Pairwise distances between haplotypes were calculated
as allele mismatches. By resampling markers randomly
with replacement, 100 bootstrapped data sets were generated as input for the program neighbor contained in
the PHYLIP package.
A region of 1 Mb showed strong association with thelowest P value of 2.1 # 10⫺12 for rs10521339 in thecase-control analysis of affected and unaffected individuals (table 3). As expected, the association is stronger
for comparisons between individuals with AGA and individuals without AGA than between individuals with
AGA and an unselected control sample (table 3). We
also performed a separate analysis of the 103 cases thatwere not included in the linkage analysis and found thatthe association was also present in this sample (data notshown). The association is further supported by familybased analysis, for which SNP rs938059 shows the low-

143

Reports

est P value (4.03 # 10⫺6) (table 3). AR is the only known
gene in the strongly associated 1-Mb–spanning region(fig. 2 and table 3). The X-linked ectodysplasin-A2 receptor (XEDAR), which is located 900 kb 5 of AR, isoutside this region (fig. 2 and table 3). The significanceof the association decreases within the 3 part of the 180kb–spanning AR gene, and oligophrenin 1 (OPHN1),
which is located 320 kb 3 of AR, is not within the blockof strongest association (fig. 2 and table 3). rs6152(P p 6.66 # 10⫺10 [table 3]) in exon 1 of AR corresponds to the StuI RFLP, for which an association has
been described by Ellis et al. (2001).
The long range of the associated SNPs implies thepresence of a large haplotype block, visible in fig. 2B.
In principle, this is not unexpected in a location close
to the centromere, where recombination events occur at
a relatively low frequency (Nagaraja et al. 1997). To test
whether the size of the haplotype block stands out evenin comparison with X-chromosomal loci with similar
low recombination frequencies, we analyzed average
pairwise linkage disequilibrium (LD) (measured by FDF)
between SNPs retrieved from the HapMap Project database in 1-cM–sized windows. Average pairwise LD
was found to be inversely correlated with recombination
rate (Spearman’s r p ⫺0.598; P ! .001). An average LD
higher than that at the AR locus was displayed by only
the six windows covering the centromere; these windows
showed distinctively smaller recombination rates (fig.
3A). This result might suggest that the predominant AR

Table 2
Oligonucleotides for TaqMan Assays
The table is available in its entirety in the online
edition of The American Journal of Human Genetics.

haplotypes are evolutionarily more recent, perhaps indicating positive selective pressure acting at this locus(Bamshad and Wooding 2003). Since androgens mediatea wide range of developmental and physiological responses through the androgen receptor (AR) and areespecially important in the male reproductive system(Lee and Chang 2003), it is conceivable that variability
in AR can have an impact on selection. In accordancewith this hypothesis, the haplotype with the highest frequency (0.45 [fig. 3B]) (which also confers risk of AGA)
in the German population seems to be evolutionarily
recent, as indicated by the low sequence identity withthe ancestral haplotype (fig. 3B).
Sequencing of the transcribed region and of 3.4 kb
of conserved sequences in the 5 region and intron 1of AR in 12 individuals revealed only two additionalvariants of the associated haplotype (XARx7_01 andXARx8insA [table 3]). The additional variants were
noncoding and did not show a stronger association thanother tested markers. Of the two repeat polymorphisms
in the coding region, the CAG repeat was not associatedwith AGA (affected/unaffected global P value of .1),
whereas the GGN repeat was highly associated (affected/

Figure 2
Gene and LD structure of the AR locus. A, Distribution of known genes (left) and typed SNPs and STRs (right) at the AR locus.
The shown genomic region spans 4.4 Mb. Gene content information is based on Ensembl. B, LD in 198 individuals with AGA (upper rightdiagonal) and in 157 individuals without AGA (lower left diagonal) was measured with x2 and was visualized using the GOLD program (Abecasis
and Cookson 2000).

Table 3
Association of AGA with Markers at the AR Locus
SNP ANDALLELE
rs12560201:
GA
rs1332720:
CT
rs1044165:
AG
rs708969:
AT
rs1379146:
TA
rs1158928:
AG
rs1485682:
CT
rs1385699:
AG
rs1385695:
AG
rs775362:GA
rs1041668:
GA
rs5964577:
AT
rs532649:
AG
rs989345:
AG
rs938059:
CA
rs925391:
GA
rs5919287:
CT
rs2221799:
AG
rs10521339:
AT
rs2223841:
AG
rs2207081:
AG
rs2497935:
AG
rs962458:
G
A
CAGe:
18
19
20

TDTa

FREQUENCY
AffectedControl

UnaffectedTransmitted

AFFECTED/CONTROL ANALYSIS
c

Nontransmitted

P

P
⫺1

.112
.888

.108
.892

.115
.885

23

27

.995
.005

1.000
.000

1.000
.000

0

1

.124
.876

.122
.878

.178
.822

22

23

.875
.125

.776
.224

.755
.245

36

29

.872
.128

.723
.277

.724
.276

39

29

.883
.117

.700
.300

.701
.299

42

27

.883
.117

.707
.293

.705
.295

42

27

.887
.113

.708
.292

.722
.278

44

28

.949
.051

.799
.201

.739
.261

38

13

.949
.051

.809
.191

.744
.256

37

13

.036
.964

.194
.806

.258
.742

9

39

.954
.046

.806
.194

.747
.253

36

12

.960
.036

.807
.193

.735
.265

37

7

.964
.036

.811
.189

.737
.263

36

6

.036
.964

.195
.805

.263
.737

7

40

.969
.031

.811
.189

.737
.263

38

6

.964
.036

.802
.198

.734
.266

39

7

.964
.036

.804
.196

.744
.256

39

7

.954
.046

.778
.212

.677
.323

11

41

.954
.046

.789
.211

.688
.312

44

11

.959
.041

.792
.208

.688
.312

44

10

.949
.041

.790
.208

.684
.316

45

12

.015
.985

.102
.898

.146
.854

2

17

.042
.110
.194

.085
.106
.112

.110
.110
.103

13
30
50

12
39
19

d

OR
⫺1

AFFECTED/UNAFFECTED ANALYSIS
ORd

CI

POSITIONb

9.38 # 10.97.5–1.87

63,335,397

1.00

ND

ND

64,598,557

CI

P
⫺1

6.68 # 10

8.99 # 10

1.04.55–1.82

1.00

1.00

ND

ND

1.00

9.50 # 10⫺1

.98

.55–1.89

1.58 # 10⫺1

1.53

.85–2.76

65,024,747

5.35 # 10⫺1

1.21 # 10⫺2

2.02

1.16–3.53

3.90 # 10⫺3

2.27

1.29–465,252,916

3.25 # 10⫺12.68 # 10⫺4

2.61

1.55–4.45

4.72 # 10⫺4

2.60

1.51–4.5

65,389,382

1.30 # 10⫺11.04 # 10⫺5

3.23

1.89–5.56

2.08 # 10⫺5

3.22

1.85–5.61

65,532,217

1.30 # 10⫺1

1.97 # 10⫺5

3.13

1.82–5.35

3.08 # 10⫺5

3.16

1.81–5.48

65,598,612

1.22 # 10⫺11.60 # 10⫺5

3.23

1.86–5.59

9.41 # 10⫺5

3.00

1.71–5.32

65,608,007

2.97 # 10⫺3

1.03 # 10⫺5

4.68

2.24–9.78

2.40 # 10⫺8

6.57

3.17–13.63

65,687,533

4.10 # 10⫺3

2.09 # 10⫺5

4.39

2.13–9.21

3.73 # 10⫺8

6.40

3.11–13.39

65,762,194

1.49 # 10⫺41.80 # 10⫺6

6.42

2.74–15.03

1.58 # 10⫺99.29

4.03–21.44

65,868,977

2.50 # 10⫺3

4.24 # 10⫺6

4.99

2.32–10.68

1.20 # 10⫺8

7.02

3.29–15.08

65,954,512

5.96 # 10⫺65.42 # 10⫺7

6.38

2.75–14.71

2.33 # 10⫺10

9.62

4.17–22.13

66,050,269

4.65 # 10⫺6

1.60 # 10⫺6

6.24

2.74–14.66

6.13 # 10⫺10

9.56

4.2–22.29

66,084,055

4.03 # 10⫺6

1.10 # 10⫺6

6.55

2.82–15.25

9.20 # 10⫺10

9.63

4.18–22.17

66,119,748

4.76 # 10⫺65.97 # 10⫺7

7.28

3.03–18.03

1.98 # 10⫺10

11.15

4.65–27.42

66,123,458

4.62 # 10⫺6

2.57 # 10⫺7

6.61

2.87–12.82

1.76 # 10⫺10

9.70

4.22–22.45

66,143,635

4.62 # 10⫺6

3.37 # 10⫺7

6.53

2.84–15.18

1.39 # 10⫺9

9.21

4.04–21.47

66,159,637

4.00 # 10⫺4

1.95 # 10⫺7

5.65

2.65–12.04

2.10 # 10⫺12

9.89

4.62–20.7

66,291,407

9.40 # 10⫺6

1.20 # 10⫺6

5.59

2.62–11.94

1.72 # 10⫺11

9.48

4.48–20.05

66,353,192

4.33 # 10⫺67.00 # 10⫺7

6.21

2.8–13.78

5.04 # 10⫺12

10.72

4.89–23.75

66,356,719

1.79 # 10⫺5

3.10 # 10⫺6

5.00

2.41–10.36

3.17 # 10⫺11

8.69

4.23–17.87

66,447,287

2.89 # 10⫺32.87 # 10⫺4

7.32

2.12–25.3

2.56 # 10⫺6

11.10

3.27–37.74

66,528,985

NSNS
2.66 # 10⫺2

ND
ND
1.91

ND
ND
1.07–3.41

NSNS
2.20 # 10⫺2

ND
ND
2.10

ND
ND
1.10–3.99

2.71 # 10⫺1 f

66,548,181(continued)

144

Table 3 (continued)
SNP ANDALLELE
21
22
23
24
25
rs6152:
T
C
GGNe:
23
24
rs1204038:
AG
rs5919393:
CT
rs1337080:
A
G
XARx7_001g:
AG
XARx8insAh:
delA
A
rs2781516:
AG
rs2885913:
GA
rs2363785:
GT
rs1936313:
TC
rs492933:
CT
rs1410127:
CT
rs1157321:
GT
rs7887862:
CT
rs1927232:
CT
rs5965536:
CG
rs792952:
C
G

TDTa

FREQUENCY
AffectedControl

UnaffectedTransmitted

Nontransmitted

.147
.136
.126
.084
.047

.191
.122
.090
.080
.064

.205
.096
.068
.096
.075

32
32
26
19
12

31
28
30
36
14

.046
.954

.201
.799

.282
.718

11

40

.651
.182

.495
.367

.421
.461

76
21

43
68

.046
.954

.208
.792

.271
.729

11

39

.046
.954

.218
.782

.274
.726

11

38

.985
.015

.907
.093

.859
.141

15

2

.010
.990

.039
.961

.032
.968

3

3

.944
.056

.804
.196

.739
.261

34

13

.128
.872

.228
.772

.282
.718

21

38

.255
.745

.441
.559

.465
.535

40

64

.745
.255

.562
.438

.555
.445

65

37

.744
.256

.551
.449

.575
.425

65

39

.736
.264

.614
.386

.623
.377

67

40

.735
.265

.608
.392

.619
.381

66

40

.848
.152

.659
.341

.656
.344

64

27

.152
.848

.118
.882

.098
.902

36

21

.719
.281

.653
.347

.708
.292

49

44

.154
.846

.121
.879

.151
.849

35

24

.249
.751

.240
.760

.240
.760

53

36

AFFECTED/CONTROL ANALYSISAFFECTED/UNAFFECTED ANALYSIS

Pc

P

ORd

CI

P

ORd

CI

POSITIONb

5.88 # 10⫺5

NS
NS
NS
NS
NS
3.80 # 10⫺6

ND
ND
ND
ND
ND
5.26

ND
ND
ND
ND
ND
2.45–11.3

NS
NS
NS
NS
NS
6.66 # 10⫺10

ND
ND
ND
ND
ND
8.21

ND
ND
ND
ND
ND
3.86–17.45

66,548,648

9.79 # 10⫺52.06 # 10⫺3
5.39 # 10⫺51.90 # 10⫺6

1.91
.38
5.45

1.26–.2.88.24–.62
2.55–11.67

2.07 # 10⫺52.62 # 10⫺8
2.83 # 10⫺9

2.57
.26
7.72

1.656–3.98.161–.42
3.62–16.46

66,571,246

1.58 # 10⫺56.00 # 10⫺7

5.82

2.73–12.41

1.69 # 10⫺8

7.88

3.7–16.77

66,608,378

5.73 # 10⫺3

6.71 # 10⫺4

6.73

1.92–23.14

4.75 # 10⫺6

10.78

3.12–36.19

66,661,940

1.00

6.79 # 10⫺2

3.95

.81–19.25

1.45 # 10⫺1

3.21

.61–16.76

66,725,646

3.29 # 10⫺3

5.09 # 10⫺5

4.11

1.99–8.47

6.62 # 10⫺8

5.94

2.94–12.02

66,727,141

3.28 # 10⫺2

1.00 # 10⫺2

2.02

1.18–3.48

2.86 # 10⫺4

2.69

1.56–4.64

66,885,052

4.46 # 10⫺2

1.49 # 10⫺4

2.31

1.49–3.57

4.29 # 10⫺5

2.53

1.62–3.97

66,898,824

1.73 # 10⫺2

1.82 # 10⫺4

2.28

1.47–3.53

2.04 # 10⫺4

2.34

1.49–3.68

66,954,319

2.48 # 10⫺2

7.91 # 10⫺5

2.37

1.54–3.64

9.15 # 10⫺4

2.15

1.36–3.37

66,983,669

2.44 # 10⫺2

1.15 # 10⫺2

1.76

1.13–2.72

2.39 # 10⫺2

1.69

1.07–2.65

67,046,865

2.83 # 10⫺2

8.02 # 10⫺3

1.79

1.16–2.76

2.13 # 10⫺2

1.71

1.08–2.67

67,063,402

7.83 # 10⫺4

1.59 # 10⫺5

2.89

1.75–4.7

2.73 # 10⫺5

2.93

1.75–4.87

67,104,762

1.09 # 10⫺1

3.31 # 10⫺1

1.34

.74–2.41

1.28 # 10⫺1

1.65

.86–3.2

67,148,136

6.77 # 10⫺11.77 # 10⫺1

1.36

.87–2.11

8.23 # 10⫺1

1.06

.66–1.69

67,165,912

1.56 # 10⫺1

3.57 # 10⫺1

1.33

.73–2.41

9.50 # 10⫺1

1.02

.57–1.84

67,300,796

1.39 # 10⫺1

8.45 # 10⫺1

1.05

.65–1.69

8.56 # 10⫺1

1.05

.64–1.71

67,766,144

7.79 # 10⫺5 f

NOTE.—ND p not determined; NS p not significant.
a
Family transmission/disequilibrium test (Knapp and Becker 2003).
b
UCSC Genome Bioinformatics Plus Strand Build 35.
c
Permutation-based value for association.
dOdds ratio.
e
Only alleles with frequencies ⭓0.05 in controls.
f
Global P value.
g
GCTTTGTCTAATGCTCCTTC[G/A]TGGGCATGCTTCCCCTCCCC(intron 6 of AR).
h
ACAAGCAAACAAAAAAAAAA[A/delA]GCAAAAACAAAACAAAAAAT (exon 8 of AR).

145

66,549,360

146

Am. J. Hum. Genet. 77:140–148, 2005

Figure 3

The AR locus: LD relative to the X-chromosome and haplotype structure. A, Average pairwise LD (measured by FDF) between
SNPs retrieved from the HapMap Project database, plotted over X-chromosomal recombination rates in 1-cM–sized windows. An average LD
higher than that at the AR locus was displayed by only the six windows covering the centromere and showed distinctively smaller recombination
rates. B, Neighbor-joining tree of frequent haplotype sequences (15% in the samples from the individuals with AGA, controls, and individuals
without AGA) within the most strongly associated haplotype block (genetic markers rs1385695–XARx8insA). The CAG repeat, XARx7_01,
and XARx8insA were omitted from tree construction, because the corresponding Pan troglodytes allele could not be retrieved from the chimpanzee
genomic sequence. The AGA haplotype is shown in red, and the chimpanzee haplotype is shown in orange. The AGA haplotype shows low
sequence identity to the ancestral (chimpanzee) haplotype. Haplotype frequencies of the respective samples are indicated in parentheses (affected/
control/unaffected [in %]). GGN-23 is indicated as “23”; GGN-24 is indicated as “24.”unaffected global P value of .0001). The study by Elliset al. (2001) also showed a larger effect for the GGN
repeat than the CAG repeat. However, the pooling ofalleles in their study renders an exact comparison of
results difficult. The GGN allele of 23 repeats showeda difference of affected versus unaffected allele frequencies of 0.23, which was in the range of the strongestassociated SNPs (rs1385695–XARx8insA [table 3]) but
with a lower frequency in controls. This suggests that
GGN-23 either is closer to the AGA mutation or is itself
the AGA-susceptibility allele. Previously obtained functional data, in which shorter repeat alleles of the GGN
repeat were associated with higher protein levels andthereby higher AR activity (Ding et al. 2005), support
the possibility of a causal role for the repeat, and thiswould be compatible with current understanding of theinvolvement of androgens in AGA. Several studies havealso suggested an effect of CAG repeat lengths on AR
transactivating activity (Mhatre et al. 1993; Chamberlain et al. 1994; Kazemi-Esfarjani et al. 1995; Choong
et al. 1996; Nakajima et al. 1996; Beilin et al. 2000;
Ding et al. 2004). Since both repeats modulate AR activity and since we observe an association only between
the GGN repeat and AGA, it may be that cells of thehair follicle lack cofactors that interact with the CAGencoded domain.
Interestingly, shorter alleles for the GGN repeat havealso been associated with prostate cancer (Hsing et al.
2000; Chang et al. 2002), whereas longer alleles havebeen associated with endometrial cancer (Sasaki et al.

2005), which would be in accordance with the differing
effects of androgens on the endometrium and the prostate (androgens exert an inhibitory effect on endometrial
cell proliferation, whereas they have a mitogenic effectin the prostate). However, the association findings withprostate cancer remain controversial, and no effect was
shown in a large meta-analysis (Zeegers et al. 2004).
The association with endometrial cancer has yet to be
confirmed.
It remains possible that an as-yet-undetected variant
in either a regulatory region affecting the expression levelor an intronic variant affecting the splicing pattern ofAR might be responsible for AGA susceptibility. The
latter seems unlikely since we did not detect alternatively
spliced transcripts of AR in human hair follicles of sevenindividuals representing different haplotypes. Previous
studies have identified AR regulatory elements up to position ⫺737 of the AR transcription start site (Faber etal. 1991, 1993; Supakar et al. 1993), as well as exonic
enhancers in exon 1 (Faber et al. 1993) and exons 4 and
5 (Grad et al. 2001). Our sequencing analysis of 12
individuals with the associated haplotype revealed novariability in these regulatory elements of AR. However,there may be additional regions with regulatory effectthat have not yet been fully characterized (Lower et al.
2004). Haplotypes carrying the GGN-24 allele show
clearly higher frequencies in individuals without AGA
than in those with AGA (fig. 3B). Since this effect isstrikingly weaker in the ACAAAAAGCATTTAAG-24ATA haplotype than in the other GGN-24–carrying hap-147

Reports

lotypes (fig. 3B), it is likely that further functionally relevant variability exists that modifies the protective effectof GGN-24–bearing haplotypes.
It is interesting to note that genetic variation in AR,
which is located on the X chromosome, cannot explain
the resemblance of fathers and sons with respect to thedevelopment of AGA (Küster and Happle 1984; Ellis etal. 1998), since sons always inherit the X chromosome
from their mothers. The fact that family studies of AGA
have typically stressed the resemblance of fathers andsons is understandable, given the differences in patternsof hair loss between males and females. Our genetic data,
however, stress the relative importance of the maternalline in the inheritance of AGA, since we estimate an
etiological fraction of 0.46 that can be attributed to having ⭐23 GGN repeats within AR. This suggests that the
average phenotypic resemblance should be greater between affected males and their maternal grandfathers
than between affected males and their fathers. It is likelythat the remaining etiological fraction is due to genetic
variation at autosomal loci, which could explain the similarity of the AGA pattern of fathers and sons. Some
autosomal candidate genes have been investigated in thepast, including the insulin gene (Ellis et al. 1999), the5a-reductase genes (Ellis et al. 1998), and the hairlessgene (Hillmer et al. 2001, 2002), but none of these has
been associated with AGA. A systematic linkage-based
approach should enable the identification of additionalloci.

Acknowledgments
We thank all participants for consenting to the study and forproviding blood samples. This study was supported by grants
from the Deutsche Forschungsgemeinschaft (DFG) (Forschergruppen “Keratinozyten—Proliferation und differenzierte Leistung in der Epidermis” and “Genetische Epidemiologie und
Medizinische Genetik komplexer Erkrankungen”), the Bundesministerium für Bildung und Forschung (German Human Genome Project, “Pharmacogenomics”), and the Alfried Krupp
von Bohlen und Halbach-Stiftung. R.C.B. is a recipient of a DFG
Emmy Noether fellowship. We thank Faten Dahdouh and Carola Müller, for assistance in STR genotyping, and Dr. Christine
Schmäl, for help in preparing the manuscript.

Web Resources
The URLs for data presented herein are as follows:
Ensembl, http://www.ensembl.org/ (for AR locus information)
HapMap, http://www.hapmap.org/ (for pairwise LD on the X
chromosome [genotypes queried in November 2004])
Online Mendelian Inheritance in Man (OMIM), http://www.ncbi.nlm.nih.gov/Omim/ (for AGA and AR)
University of California–Santa Cruz (UCSC) Genome Bioinformatics, http://genome.ucsc.edu/ (for X-chromosomal re-

combination rates and definition of the reference strand for
SNP allele calling)

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