Genome-wide association study of sexual maturation in males and females highlights a role for body mass
and menarche loci in male puberty
Supplementary Material
Figure S1. Forest plot for rs246185 in the male genome-wide association meta-analysis. This plot depicts the
effect size (beta, black squares) and SD (gray bar) for each contributing cohort, for all discovery cohorts
combined, and for discovery plus follow-up studies combined. Cochran’s test (Q) for heterogeneity between
the discovery and follow-up effect sizes was 0.23, corresponding to a P of 0.99.
1
Figure S2. a) QQ plots from the primary meta-analyses. P-values have been automatically double corrected for
genomic inflation by the meta-analysis program GWAMA (1, 2) as described in the Materials and Methods.
b) Manhattan plots
2
Figure S3. a) Regional plot of the chromosome 16p13.12 locus before follow-up analysis showing the P-value
for each marker from the discovery male analysis along the chromosome (genome build 36). rs246185 is
highlighted as a yellow triangle and lies within two recombination hotspots between MKL2 and PARN.
3
b) Regional association plot of the same locus imputed against the 1000 Genomes reference set (genome build
37). rs246185 is presented as a yellow triangle, and rs193536 is shown as a red triangle.
4
Figure S4. Position weight matrices (PWMs) representing preferred binding motif sequences for predicted
binding sites affected by two SNPs in LD with rs246185 from the RegulomeDB output (3). The red boxes
surround rs74755650 in panels a and b, and rs193536 in panels c and d. R2 between rs246185 and rs7475560
is 0.75, and between rs246185 and rs193536 is 0.85.
5
Figure S5. Scatter plots showing the relationship between the effect size for all 31 known BMI-increasing alleles (4) and the effect size for Tanner
staging in males, females, and both sexes combined. See Table S6 for the specific alleles that are represented here.
6
Table S1. Cohort summary information (separate excel sheet).
Table S2. Genes nearby the chr 16p13.12 locus, their function, and the phenotypic effect of mutants in human and mouse.
Approximate
distance to
rs246185a
32 kb
Functionb
Mutations in
humansc
Phenotype in moused
blood vessel morphogenesis, cardiac muscle
tissue development, cell differentiation,
embryonic organ development, heart
morphogenesis
none
cellular, growth/size,
mortality/aging, nervous system
poly(A)-specific ribonuclease
(deadenylation nuclease)
bifunctional apoptosis inhibitor
131 kb
3'-exoribonuclease
none
none
329 kb
anti-apoptosis
none
none
ERCC4
excision repair crosscomplementing rodent repair
deficiency, complementation
group 4
347 kb
nucleotide excision repair
cellular, growth/size, liver/biliary,
mortality/aging
PLA2G10
phospholipase A2, group X
369 kb
catalyzes the release of fatty acids from
phospholipids and play a role in a wide range of
physiologic functions. GnRH pathway, MAPK
pathway
xeroderma
pigmentosum
complementation
group F (XP-F), or
xeroderma
pigmentosum VI
(XP6)
none
Gene
Full name
MKL2
myocardin-like 2
PARN
BFAR
a
Estimated from Ensembl (http://www.ensembl.org).
Function summarized from AceView (http://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/index.html?human).
c
Human mutations queried from Online Mendelian Inheritance in Man (http://www.ncbi.nlm.nih.gov/omim).
d
Mouse mutations queried from Mouse Phenome Database (http://phenome.jax.org/).
b
7
hematopoietic, homeostasis,
immune; endocrine/exocrine,
homeostasis; cardiovascular,
cellular, hematopoietic,
homeostasis, immune, muscle,
reproductive
Table S3. RegulomeDB (1, 2) (http://regulome.stanford.edu/) functional analysis of SNPs in high LD (r2>0.6) with index SNP rs246185 from the
1000 Genomes Pilot I data set. Queried on April 25, 2013. See the website for detailed annotation of analysis, data output, and scoring.
SNP
Distancea
R2
D´
Positionb
Regulome DB scorec
Evidence
rs246185
0
1.000
1.000
14302933
4, Minimal binding evidence
rs74755650
356
0.750
0.948
14302577
2b, Likely to affect binding
rs181766
554
0.958
1.000
14302379
4, Minimal binding evidence
rs193536
588
0.846
1.000
14302345
2b, Likely to affect binding
rs246180
3509
0.958
1.000
14299424
No data
Chromatin_Structure|FAIRE, Chromatin_Structure|DNase-seq,
Protein_Binding|ChIP-seq|EGR1, Protein_Binding|ChIP-seq|SMARCB1,
Protein_Binding|ChIP-seq|NR3C1
Motifs|PWM|WT1, Motifs|PWM|MAZR, Motifs|Footprinting|WT1,
Motifs|Footprinting|MAZR, Chromatin_Structure|FAIRE,
Chromatin_Structure|DNase-seq, Protein_Binding|ChIP-seq|POLR2A
Chromatin_Structure|FAIRE, Chromatin_Structure|DNase-seq,
Protein_Binding|ChIP-seq|SIN3A, Protein_Binding|ChIP-seq|MXI1,
Protein_Binding|ChIP-seq|EP300, Protein_Binding|ChIP-seq|MYC,
Protein_Binding|ChIP-seq|MAX, Protein_Binding|ChIP-seq|NFKB1,
Protein_Binding|ChIP-seq|RAD21, Protein_Binding|ChIP-seq|USF1,
Protein_Binding|ChIP-seq|SMC3, Protein_Binding|ChIP-seq|BHLHE40,
Protein_Binding|ChIP-seq|JUND, Protein_Binding|ChIP-seq|RFX5,
Protein_Binding|ChIP-seq|PAX5, Protein_Binding|ChIP-seq|GTF2F1,
Protein_Binding|ChIP-seq|YY1, Protein_Binding|ChIP-seq|ZNF143,
Protein_Binding|ChIP-seq|NR3C1, Protein_Binding|ChIP-seq|POLR2A,
Protein_Binding|ChIP-seq|FOSL2, Protein_Binding|ChIP-seq|ZBTB7A,
Protein_Binding|ChIP-seq|CTCF, Protein_Binding|ChIP-seq|IRF4,
Protein_Binding|ChIP-seq|CDX2, Protein_Binding|ChIP-seq|HDAC2
Motifs|PWM|ER, Motifs|Footprinting|Pax-3, Motifs|Footprinting|ER,
Motifs|PWM|Pax-3, Chromatin_Structure|FAIRE, Chromatin_Structure|DNase-seq,
Protein_Binding|ChIP-seq|SIN3A, Protein_Binding|ChIP-seq|MXI1,
Protein_Binding|ChIP-seq|EP300, Protein_Binding|ChIP-seq|MYC,
Protein_Binding|ChIP-seq|MAX, Protein_Binding|ChIP-seq|NFKB1,
Protein_Binding|ChIP-seq|RAD21, Protein_Binding|ChIP-seq|USF1,
Protein_Binding|ChIP-seq|SMC3, Protein_Binding|ChIP-seq|BHLHE40,
Protein_Binding|ChIP-seq|JUND, Protein_Binding|ChIP-seq|RFX5,
Protein_Binding|ChIP-seq|PAX5, Protein_Binding|ChIP-seq|GTF2F1,
Protein_Binding|ChIP-seq|YY1, Protein_Binding|ChIP-seq|ZNF143,
Protein_Binding|ChIP-seq|NR3C1, Protein_Binding|ChIP-seq|POLR2A,
Protein_Binding|ChIP-seq|FOSL2, Protein_Binding|ChIP-seq|ZBTB7A,
Protein_Binding|ChIP-seq|CTCF, Protein_Binding|ChIP-seq|IRF4,
Protein_Binding|ChIP-seq|CDX2, Protein_Binding|ChIP-seq|HDAC2
No data
rs1704528
6682
0.881
1.000
14296251
6, Minimal binding evidence
8
Motifs|PWM|c-Ets-1, Motifs|PWM|Elk-1, Motifs|PWM|c-Ets-1(p54),
Motifs|PWM|Tel-2, Motifs|PWM|NERF1a, Motifs|PWM|c-Ets-2, Motifs|PWM|Ets,
Motifs|PWM|FLI1, Motifs|PWM|Etv1
rs1659127
7127
0.837
0.955
14295806
6, Minimal binding evidence
rs30153
10955
0.831
0.912
14291978
6, Minimal binding evidence
Motifs|PWM|CAC-bindingprotein, Motifs|PWM|MAZR, Motifs|PWM|Klf7,
Motifs|PWM|SP1, Motifs|Footprinting|Klf4, Motifs|PWM|Klf4, Motifs|PWM|SP4,
Motifs|PWM|Sp1
Motifs|PWM|Zbtb3
rs30152
12785
0.793
0.910
14290148
No data
No data
rs246177
14664
0.647
1.000
14288269
4, Minimal binding evidence
rs246176
14717
0.647
1.000
14288216
4, Minimal binding evidence
Chromatin_Structure|DNase-seq, Protein_Binding|ChIP-seq|POLR2A,
Protein_Binding|ChIP-seq|CTCF
Chromatin_Structure|DNase-seq, Protein_Binding|ChIP-seq|POLR2A
rs246175
15284
0.647
1.000
14287649
3a, Less likely to affect
binding
rs246173
15596
0.602
1.000
14287337
4, Minimal binding evidence
a
Distance in bp from index SNP rs246185.
Position on human genome build 18.
c
See http://regulome.stanford.edu/about for a detailed explanation of scoring.
9
b
Motifs|PWM|Tcfap2c, Motifs|PWM|Tcfap2a, Chromatin_Structure|FAIRE,
Chromatin_Structure|DNase-seq, Protein_Binding|ChIP-seq|GATA1,
Protein_Binding|ChIP-seq|TFAP2C, Protein_Binding|ChIP-seq|TFAP2A,
Protein_Binding|ChIP-seq|SMARCA4, Protein_Binding|ChIP-seq|IKZF1,
Protein_Binding|ChIP-seq|EBF1, Protein_Binding|ChIP-seq|TAL1
Motifs|Footprinting|T, Motifs|Footprinting|AP-4, Chromatin_Structure|FAIRE,
Chromatin_Structure|DNase-seq, Protein_Binding|ChIP-seq|GATA1,
Protein_Binding|ChIP-seq|HNF4A, Protein_Binding|ChIP-seq|MEF2C,
Protein_Binding|ChIP-seq|MYC, Protein_Binding|ChIP-seq|TRIM28,
Protein_Binding|ChIP-seq|NANOG, Protein_Binding|ChIP-seq|CEBPB,
Protein_Binding|ChIP-seq|ELF1, Protein_Binding|ChIP-seq|SMARCB1,
Protein_Binding|ChIP-seq|POLR3A, Protein_Binding|ChIP-seq|HSF1,
Protein_Binding|ChIP-seq|SMARCA4, Protein_Binding|ChIP-seq|RFX5,
Protein_Binding|ChIP-seq|ETS1, Protein_Binding|ChIP-seq|IKZF1,
Protein_Binding|ChIP-seq|TBP, Protein_Binding|ChIP-seq|NR3C1,
Protein_Binding|ChIP-seq|FOSL2, Protein_Binding|ChIP-seq|WRNIP1,
Protein_Binding|ChIP-seq|ZEB1, Protein_Binding|ChIP-seq|GTF3C2,
Protein_Binding|ChIP-seq|GATA3, Protein_Binding|ChIP-seq|RXRA,
Protein_Binding|ChIP-seq|HDAC2, Protein_Binding|ChIP-seq|THAP1,
Protein_Binding|ChIP-seq|SIN3A, Protein_Binding|ChIP-seq|NRF1,
Protein_Binding|ChIP-seq|EP300, Protein_Binding|ChIP-seq|NFKB1,
Protein_Binding|ChIP-seq|IRF1, Protein_Binding|ChIP-seq|USF1,
Protein_Binding|ChIP-seq|BRCA1, Protein_Binding|ChIP-seq|CCNT2,
Protein_Binding|ChIP-seq|PAX5, Protein_Binding|ChIP-seq|GTF2F1,
Protein_Binding|ChIP-seq|YY1, Protein_Binding|ChIP-seq|GATA2,
Protein_Binding|ChIP-seq|IRF4, Protein_Binding|ChIP-seq|CDX2,
Protein_Binding|ChIP-seq|POLR3G, Protein_Binding|ChIP-seq|SRF,
Protein_Binding|ChIP-seq|BRF1
Table S4. Power calculations for various allele frequency scenarios. These calculations were performed in R (v 2.15.1).
n=10000
Allele freq (allele 1/allele 2)
Beta
1x10-5
P 1x10-6
5x10-8
n=6000
Allele freq (allele 1/allele 2)
Beta
1x10-5
P 1x10-6
5x10-8
n=4000
Allele freq (allele 1/allele 2)
Beta
1x10-5
P 1x10-6
5x10-8
10
0.2/0.8
0.05
0.02
0.01
0
0.2/0.8
0.075
0.26
0.14
0.11
0.2/0.8
0.1
0.77
0.63
0.58
0.5/0.5
0.05
0.08
0.04
0.03
0.2/0.8
0.05
0
0
0
0.2/0.8
0.075
0.05
0.02
0.01
0.2/0.8
0.1
0.31
0.18
0.15
0.5/0.5
0.05
0.02
0.01
0
0.5/0.5
0.075
0.21
0.11
0.09
0.5/0.5
0.1
0.73
0.56
0.52
0.2/0.8
0.05
6.00E-04
0
0
0.2/0.8
0.075
0.01
0.005
0.003
0.2/0.8
0.1
0.1
0.04
0.03
0.5/0.5
0.05
0.5/0.5
0.075
0.06
0.02
0.02
0.5/0.5
0.1
0.33
0.19
0.16
0.004
0.0007
0.0005
0.5/0.5
0.075
0.65
0.49
0.44
0.5/0.5
0.1
0.98
0.96
0.95
Table S5. Association of age at menarche SNPs with Tanner sexual maturation. We extracted known
menarche-associated variants from the male, female, and combined Tanner analysis, and report their
associations here for the menarche-advancing allele. A higher beta for the Tanner association corresponds to
earlier puberty. All SNPs from Elks et al (5) unless otherwise noted. The Bonferroni-corrected significance
threshold is 0.001 (corrected for assessing 44 loci).
SNP
Chr
Position
Gene
β
P
Male
β
Male P
Female
β
Female P
RXRG
Menarcheadvancing
allele
T
rs466639
1
163661506
0.011
0.59
0.052
0.15
-0.009
0.72
rs633715
1
176119203
SEC16B
C
0.026
0.11
0.024
0.39
0.027
0.17
rs2947411
rs1172294b,c
2
604168
TMEM18
G
0.036
0.04
-0.014
0.64
0.060
0.005
2
25022704
G
0.006
0.67
-0.021
0.36
0.019
0.25
rs17268785
2
56445587
ADCY3,
POMC, RBJ
CCDC85A
A
0.018
0.31
0.005
0.86
0.025
0.26
rs12472911a
2
141944979
LRP1B
T
0.017
0.29
0.013
0.64
0.020
0.33
rs17188434
2
156805022
NR4A2
C
0.028
0.30
0.027
0.58
0.029
0.39
rs12617311
2
199340810
PLCL1
A
0.026
0.07
-0.015
0.55
0.046
0.01
rs7617480
3
49185736
KLHDC8B
C
-0.001
0.94
-0.007
0.80
0.002
0.94
rs6762477
3
50068213
RBM6
A
-0.026
0.06
-0.054
0.02
-0.012
0.46
rs7642134
3
86999572
VGLL3
A
0.020
0.15
0.018
0.43
0.020
0.22
rs6438424
3
119057512
3q13.32
A
0.001
0.97
-0.014
0.56
0.007
0.65
rs2687729
3
129377916
EEFSEC
A
-0.009
0.57
0.037
0.15
-0.031
0.09
rs6439371
3
134093442
A
-0.005
0.72
-0.019
0.43
0.002
0.90
rs3914188a
3
185492742
TMEM108,
NPHP3
ECE2
G
0.008
0.59
-0.020
0.45
0.022
0.24
rs2002675
3
187112262
A
0.000
0.99
-0.001
0.97
0.001
0.97
rs13187289
C
0.028
0.11
0.010
0.75
0.038
0.08
a
5
133877076
TRA2B,
ETV5
PHF15
a
5
137735214
KDM3B
A
0.033
0.05
0.035
0.20
0.031
0.12
rs4840086
6
100315159
G
0.012
0.39
-0.031
0.19
0.033
0.05
rs7759938
6
105485647
PRDM13,
MCHR2
LIN28B
T
0.080
3.42E-08
0.063
0.012
0.088
5.57E-07
rs1361108
6
126809293
T
0.026
0.05
-0.001
0.95
0.040
0.02
rs1079866
7
41436618
C6orf173,
TRMT11
INHBA
C
0.054
0.0049
0.048
0.15
0.058
0.01
rs7821178
8
78256392
PXMP3
A
0.009
0.52
0.049
0.04
-0.011
0.53
rs2090409
9
108006909
TMEM38B
A
0.061
1.84E-05
0.075
0.002
0.054
0.002
rs10980926
9
113333455
ZNF483
G
-0.008
0.55
-0.015
0.51
-0.005
0.79
rs4929923
11
8595776
TRIM66
T
0.018
0.21
0.014
0.55
0.019
0.26
rs900145
11
13250481
ARNTL
T
0.046
0.0016
0.049
0.05
0.045
0.01
11
46009151
PHF21A
T
0.009
0.69
0.025
0.53
0.002
0.96
rs10899489
11
77773021
GAB2
C
-0.006
0.76
0.051
0.11
-0.036
0.12
rs6589964
11
122375893
BSX
A
0.015
0.29
0.028
0.26
0.009
0.60
rs9555810a
13
110979438
C
0.034
0.02
0.026
0.31
0.039
0.03
rs6575793
14
100101970
C13orf16,
ARHGEF7
BEGAIN
T
-0.008
0.57
-0.013
0.60
-0.006
0.74
rs3743266a,d
15
58568805
RORA
C
0.048
0.0008
0.033
0.18
0.055
0.002
15
65489961
IQCH
C
-0.004
0.75
-0.033
0.15
0.011
0.52
rs757647
rs16938437
a
rs7359257
11
a
rs1659127
rs4788196
b
16
14295806
MKL2
G
0.050
0.0008
0.117
4.35E-06
0.016
0.37
16
29874935
MAPK3
G
0.016
0.24
0.016
0.49
0.016
0.33
rs9939609
16
52378028
FTO
A
0.028
0.04
0.003
0.91
0.040
0.01
rs1364063
16
68146073
NFAT5
T
0.014
0.30
0.022
0.35
0.010
0.54
rs9635759
17
46968784
CA10
G
0.017
0.25
-0.039
0.13
0.046
0.01
rs2243803
18
41210670
SLC14A2
T
0.023
0.09
0.017
0.48
0.026
0.12
rs1398217
18
43006236
FUSSEL18
G
0.001
0.93
-0.011
0.65
0.007
0.67
rs1862471
19
9861322
OLFM2
G
0.023
0.10
0.030
0.22
0.020
0.25
rs10423674
19
18678903
CRTC1
C
0.031
0.03
0.002
0.95
0.045
0.01
rs852069
20
17070593
PCSK2
A
0.006
0.66
-0.011
0.63
0.015
0.37
a
a
a
Defined as a possible menarche locus (5).
Associated with menarche in a study of the pubertal growth spurt (6).
c
Associated with menarche in a study of the overlap between body mass loci and menarche (7).
d
Associated with menarche in African Americans (8).
b
12
Table S6. Association of body mass index-increasing alleles to Tanner sexual maturation. We extracted known
BMI-associated variants from the Tanner male, female, and combined analyses, and report their associations
here for the BMI-increasing allele. A higher Tanner beta corresponds to earlier pubertal timing. All SNPs are
from (4) unless otherwise noted. The Bonferroni-corrected significance threshold is 0.0016 (corrected for
assessing 31 loci).
SNP
Chr
Position
Gene
BMIincreasing
allele
β
P
Male β
Male P
Female β
Female
P
BMI loci previously associated with age at menarchea
rs2815752
1
72585028
NEGR1
A
-0.001
0.93
-0.026
0.27
0.011
0.52
1
74764232
TNNI3K
A
0.024
0.07
0.055
0.02
0.009
0.60
1
176180142
SEC16B
T
-0.025
0.12
-0.030
0.29
-0.023
0.25
b
2
612827
TMEM18
C
0.037
0.04
-0.016
0.6
0.062
0.004
b,c
2
25011512
C
0.006
0.67
-0.023
0.31
0.020
0.22
rs887912
2
59156381
ADCY3/
POMC/RBJ
FANCL
T
-0.004
0.78
-0.070
0.005
0.031
0.09
rs9816226
3
187317193
ETV5
T
0.012
0.51
-0.028
0.36
0.032
0.15
rs10938397
4
44877284
GNPDA2
G
0.017
0.2
0.005
0.82
0.023
0.16
rs987237
6
50911009
TFAP2B
G
-0.005
0.77
0.004
0.88
-0.010
0.64
rs4929949
11
8561169
RPL27A/STK33
C
0.033
0.02
0.039
0.09
0.029
0.07
rs10767664
11
27682562
BDNF
A
0.023
0.17
0.039
0.17
0.015
0.47
rs7138803
12
48533735
FAIM2
A
0.028
0.04
0.037
0.11
0.023
0.16
rs12444979
16
19841101
GPRC5B
C
0.058
0.003
0.085
0.01
0.044
0.06
b
16
52361075
FTO
A
0.024
0.08
-0.011
0.62
0.041
0.01
19
39001372
KCTD15
G
0.004
0.75
0.032
0.19
-0.009
0.6
rs1514175
b
rs10913469b
rs2867125
rs713586
a
rs1558902
rs29941
BMI loci not associated with age at menarche
rs1555543
1
96717385
PTBP2
C
-0.011
0.43
-0.016
0.5
-0.008
0.62
rs2890652
2
142676401
LRP1B
C
0.027
0.12
0.010
0.72
0.035
0.1
rs13078807
3
85966840
CADM2
G
0.001
0.97
-0.026
0.36
0.014
0.49
rs2112347
5
75050998
FLJ35779
T
0.015
0.29
0.040
0.09
0.002
0.92
rs206936
6
34410847
NUDT3
G
0.016
0.33
0.010
0.73
0.019
0.34
9
28404339
LRRN6C
G
0.002
0.91
0.023
0.36
-0.009
0.61
rs3817334
11
47607569
MTCH2
T
0.042
0.002
0.015
0.51
0.055
0.0008
rs4771122
13
26918180
MTIF3
G
0.005
0.74
0.025
0.37
-0.004
0.84
rs9568856d
13
52962982
OLFM2
A
0.016
0.44
0.005
0.89
0.021
0.4
rs11847697
14
29584863
PRKD1
T
0.035
0.30
0.041
0.5
0.032
0.43
rs10150332
14
79006717
NRXN3
C
-0.004
0.79
0.040
0.15
-0.026
0.18
rs2241423
15
65873892
MAP2K5
G
0.006
0.72
0.029
0.28
-0.006
0.75
rs7359397
16
28793160
SH2B1
T
0.011
0.41
0.014
0.54
0.01
0.55
b
18
55990749
MC4R
A
-0.042
0.008
-0.090
0.0009
-0.018
0.36
rs2287019
19
50894012
QPCTL
C
-0.03
0.09
-0.006
0.84
-0.042
0.05
rs3810291
19
52260843
TMEM160
A
0.011
0.48
-0.010
0.71
0.022
0.26
rs10968576
c
rs571312
a
Associated with age at menarche in (5) and/or (7).
Also associated with or in LD (r2>0.9) with a SNP associated with childhood BMI (9).
c
Also associated with decreased pubertal growth across puberty (relative pubertal height change from 8 to adult) (6).
d
Childhood BMI locus (9).
b
13
Table S7. MAGENTA gene set enrichment analyses. See Materials and Methods and Segrè et al (10) for a detailed description of the method.
95th percentile males and females combined
Database
Gene set
Centromere DNA-binding protein
10
Nominal
GSEA Pvalue
9.00 E-04
ligand-dependent nuclear receptor
activity
KEGG ACUTE MYELOID LEUKEMIA
positive regulation of transcription
from RNA polymerase II promoter
27
1.00E-04
0.23
1
7
NR4A2, RORA
52
265
6.00E-04
7.00E-04
0.12
0.83
3
13
9
26
MAPK3
ARNTL, INHBA, NR4A2,
PROP1, RORA, RXRG, VEGFA,
CRTC1, MKL2, BSX
embryonic pattern specification
post-Golgi vesicle-mediated
transport
steroid hormone receptor activity
nuclear hormone receptor
9
38
8.00E-04
2.80E-03
0.18
0.97
0
2
4
7
44
44
4.90E-03
5.60E-03
0.97
0.28
2
2
7
7
phosphoprotein phosphatase activity
Signal transduction
33
248
5.70E-03
5.80E-03
0.96
1.00
2
12
6
22
Transmission across chemical
synapses
Panther
Oxytocin receptor mediated signaling
pathway
REACTOME
Nuclear receptor transcription
pathway
GOTERM
dephosphorylation
GOTERM
3',5'-cyclic-AMP phosphodiesterase
activity
th
75 percentile males and females combined
Database
Gene set
121
6.00E-03
0.46
6
13
NR4A2, RORA, RXRG,
PLA2G10, TRIB1
ADCY3
16
7.40E-03
0.34
1
4
PLCL1, PLCG1
47
8.30E-03
0.71
2
7
NR4A2, RORA, RXRG
17
9
8.40E-03
8.70E-03
1.00
1.00
1
0
4
3
Gene set
size
Nominal
GSEA Pvalue
FDR
Expected
# genes
Observed
# genes
GOTERM
aminopeptidase activity
25
4.00E-06
0.004
6
17
REACTOME
Hormone sensitive lipase HSL
mediated triacylglycerol hydrolysis
KEGG APOPTOSIS
12
4.20E-05
0.004
3
10
74
1.00E-04
0.01
19
34
PANTHER MOLECULAR
FUNCTION
GOTERM
KEGG
GOTERM
GOTERM
GOTERM
GOTERM
PANTHER MOLECULAR
FUNCTION
GOTERM
PANTHER BIOLOGICAL
PROCESS
REACTOME
KEGG
14
Gene set
size
FDR
Expected
# genes
Observed
# genes
0.02
1
4
Flagged gene names
NR4A2, RORA, RXRG
NR4A2, RORA, RXRG
Flagged gene names
GOTERM
manganese ion binding
25
1.00E-04
0.11
6
15
REACTOME
INTRINSIC PATHWAY FOR APOPTOSIS
28
1.30E-03
0.13
7
15
BIOCARTA
AGPCR PATHWAY
13
1.40E-03
0.10
3
9
BIOCARTA
CSK PATHWAY
19
1.90E-03
0.12
5
11
REACTOME
APOPTOSIS
113
2.20E-03
0.24
28
42
GOTERM
steroid hormone receptor activity
44
2.40E-03
0.84
11
20
NR4A2, RORA, RXRG
REACTOME
47
2.70E-03
0.25
12
21
NR4A2, RORA, RXRG
53
2.90E-03
0.17
13
23
CETP
GOTERM
NUCLEAR RECEPTOR TRANSCRIPTION
PATHWAY
LPS IL-1 Mediated Inhibition of RXR
Function
apoptosis
419
3.00E-03
0.73
105
129
ARHGEF7, LY86, NISCH,
FAIM2, BFAR
GOTERM
cation binding
28
3.10E-03
0.65
7
14
GOTERM
transcription factor activity
786
3.30E-03
0.64
197
228
GOTERM
autophagic vacuole
10
3.30E-03
0.76
3
7
GOTERM
actin binding
250
3.50E-03
0.60
63
81
GOTERM
internal side of plasma membrane
13
4.00E-03
0.74
3
8
BIOCARTA
P53 HYPOXIA PATHWAY
20
4.00E-03
0.16
5
11
PANTHER_MOLECULA
R_FUNCTION
GOTERM
Epimerase/racemase
35
4.60E-03
0.77
9
16
13
5.60E-03
0.63
3
8
BIOCARTA
positive regulation of cytokine
secretion
MYOSIN PATHWAY
29
5.90E-03
0.21
7
14
ARHGEF7
KEGG
KEGG PROSTATE CANCER
84
6.10E-03
0.41
21
32
FGFR1, MAPK3
REACTOME
REGULATION OF INSULIN SECRETION
BY GLUCAGON LIKE PEPTIDE 1
cell development
59
6.50E-03
0.40
15
24
ITPR2
16
7.60E-03
0.59
4
9
ligand-dependent nuclear receptor
activity
Detoxification
27
7.80E-03
0.64
7
13
57
7.80E-03
1.00
14
23
TELOMERE MAINTENANCE
45
8.80E-03
0.42
11
19
microtubule bundle formation
9
9.00E-03
0.75
2
6
Ingenuity
GOTERM
GOTERM
PANTHER BIOLOGICAL
PROCESS
REACTOME
GOTERM
15
ARNTL, KLF9, ETV5, HOXC13,
MAF, NR4A2, PAX5, PROP1,
RORA, RXRG, TBX15, TFAP2B,
LHX3, HESX1, NFE2L3, NFAT5,
ZNF483, BSX
KCNMA1, MKL2
NR4A2, RORA
GOTERM
peroxisomal membrane
39
9.10E-03
0.67
10
17
GOTERM
telomere maintenance via
telomerase
Insulin/IGF pathway- mitogen
activated protein kinase kinase/MAP
kinase cascade
9
9.60E-03
0.66
2
6
19
9.70E-03
0.60
5
10
Gene set
size
FDR
Expected
# genes
Observed
# genes
0.05
1
4
Panther
95th percentile females
Database
Gene set
Thyrotropin-releasing hormone
receptor signaling pathway
regulation of transcription, DNAdependent
11
Nominal
GSEA Pvalue
1.40E-03
816
1.00E-04
0.43
41
64
9
5.00E-04
0.14
0
4
GOTERM
histone methyltransferase activity
(H3-K4 specific)
protein kinase cascade
85
6.00E-04
0.42
4
13
GOTERM
zinc ion binding
1488
1.30E-03
0.55
74
96
GOTERM
dendrite development
19
1.70E-03
0.62
1
5
KLF9, NR4A2, RORA, RXRG,
SF1, LHX3, BRAP, ZNF259,
RBM6, PHF15, BFAR, PHF21A,
FANCL, ADAMTS9, ZNF608,
PRDM13, ZNF483, LIN28B
BDNF
GOTERM
inhibition of adenylate cyclase
activity by G-protein signaling
pathway
Transcription_cofactor
29
2.10E-03
0.41
1
6
ADCY3
136
3.00E-03
0.43
7
15
SF1
associative learning
13
3.00E-03
0.37
1
4
REACTOME
G_ALPHA_Z_SIGNALLING_EVENTS
14
3.10E-03
0.43
1
4
GOTERM
microtubule associated complex
24
4.90E-03
0.48
1
5
GOTERM
transcription factor activity
789
5.20E-03
0.59
39
55
Panther
GOTERM
GOTERM
PANTHER_MOLECULA
R_FUNCTION
GOTERM
16
Flagged gene names
ARNTL, ETV5, HOXC13, MAF,
NR4A2, PAX5, PROP1, RORA,
RXRG, TBX15, TFAP2B, LHX3,
HESX1, NFE2L3, NFAT5,
ZNF483, LIN28B, BSX
ADCY3
ARNTL, KLF9, ETV5, HOXC13,
MAF, NR4A2, PAX5, PROP1,
RORA, RXRG, TBX15, TFAP2B,
LHX3, HESX1, NFE2L3, NFAT5,
ZNF483, BSX
GOTERM
phosphoprotein phosphatase activity
33
5.30E-03
0.43
2
6
GOTERM
histone H3-K4 methylation
8
5.40E-03
0.41
0
3
PANTHER_BIOLOGICAL
_PROCESS
GOTERM
Extracellular_transport_and_import
66
5.80E-03
0.90
3
9
4 iron, 4 sulfur cluster binding
25
6.50E-03
0.47
1
5
CDKAL1
REACTOME
PKA_ACTIVATION
17
8.00E-03
0.70
1
4
ADCY3
Panther
Circadian_clock_system
9
8.50E-03
0.12
0
3
ARNTL
GOTERM
activation of protein kinase A activity
17
9.20E-03
0.49
1
4
ADCY3
GOTERM
cognition
9
9.40E-03
0.44
0
3
CHD7
Gene set
size
FDR
Expected
# genes
Observed
# genes
Flagged gene names
ADCY3
th
75 percentile females
Database
Gene set
KEGG
KEGG_DILATED_CARDIOMYOPATHY
81
Nominal
GSEA Pvalue
1.00E-04
0.01
20
36
KEGG
KEGG_APOPTOSIS
75
1.00E-04
0.02
19
33
KEGG
KEGG_LONG_TERM_POTENTIATION
64
1.00E-04
0.01
16
29
Panther
PI3_kinase_pathway
13
2.00E-04
0.00
3
10
KEGG
KEGG_ACUTE_MYELOID_LEUKEMIA
52
8.00E-04
0.02
13
24
MAPK3
KEGG
191
9.00E-04
0.03
48
67
KEGG
KEGG_REGULATION_OF_ACTIN_CYT
OSKELETON
KEGG_ENDOMETRIAL_CANCER
50
9.00E-04
0.02
13
23
FGF8, FGFR1, MAPK3,
ARHGEF7
MAPK3
KEGG
KEGG_PROSTATE_CANCER
84
2.40E-03
0.05
21
33
FGFR1, MAPK3
GOTERM
ligand-dependent nuclear receptor
activity
TEL_PATHWAY
27
6.00E-04
0.60
7
15
NR4A2, RORA
18
7.00E-04
0.07
5
11
90
9.00E-04
0.23
23
37
GRB14, PLCG1
59
1.10E-03
0.16
15
26
ITPR2
BIOCARTA
CELL_SURFACE_INTERACTIONS_AT_T
HE_VASCULAR_WALL
REGULATION_OF_INSULIN_SECRETIO
N_BY_GLUCAGON_LIKE_PEPTIDE_1
BAD_PATHWAY
25
1.20E-03
0.12
6
14
MAPK3
GOTERM
phosphoprotein phosphatase activity
33
1.30E-03
0.54
8
17
BIOCARTA
CSK_PATHWAY
19
1.80E-03
0.08
5
11
GOTERM
histone H2A acetylation
12
1.90E-03
0.52
3
8
REACTOME
TELOMERE_MAINTENANCE
47
2.50E-03
0.27
12
21
BIOCARTA
CK1_PATHWAY
17
3.10E-03
0.08
4
10
BIOCARTA
REACTOME
REACTOME
17
ITPR2, MAPK3
GOTERM
autophagic vacuole
10
3.10E-03
0.52
3
7
KEGG
73
3.20E-03
0.06
18
29
MAPK3, NFAT5
GOTERM
KEGG_B_CELL_RECEPTOR_SIGNALIN
G_PATHWAY
central nervous system development
92
3.20E-03
0.41
23
35
PROP1, FAIM2, CHD7
GOTERM
hormone biosynthetic process
10
3.70E-03
0.45
3
7
REACTOME
INHIBITION_OF_INSULIN_SECRETION
_BY_ADRENALINE_NORADRENALINE
autophagic vacuole membrane
28
3.70E-03
0.26
7
14
12
3.80E-03
0.40
3
8
KEGG_CHEMOKINE_SIGNALING_PAT
HWAY
response to UV
157
3.90E-03
0.09
39
54
ADCY3, MAPK3
28
3.90E-03
0.54
7
14
ERCC4
Neurotransmitter_release
87
4.00E-03
0.77
22
33
ITPR2, KCNMA1
61
4.10E-03
0.39
15
25
ARHGEF7
121
4.50E-03
0.26
30
43
ADCY3
REACTOME
Rho guanyl-nucleotide exchange
factor activity
TRANSMISSION_ACROSS_CHEMICAL
_SYNAPSES
DARPP32_EVENTS
26
4.60E-03
0.17
7
13
GOTERM
cation binding
29
4.60E-03
0.52
7
14
GOTERM
visual learning
23
4.90E-03
0.56
6
12
REACTOME
TIE2_SIGNALING
18
5.20E-03
0.24
5
10
GRB14
KEGG
KEGG_CALCIUM_SIGNALING_PATHW
AY
Signal_transduction
158
5.40E-03
0.09
40
54
ADCY3, ITPR2, PLCG1, TACR3
247
5.40E-03
0.47
62
79
NR4A2, RORA, RXRG,
PLA2G10, TRIB1
76
5.70E-03
0.10
19
29
18
5.70E-03
0.48
5
10
REACTOME
KEGG_HYPERTROPHIC_CARDIOMYO
PATHY_HCM
hydrogen ion transmembrane
transporter activity
EXTENSION_OF_TELOMERES
26
6.20E-03
0.19
7
13
BIOCARTA
CARM1_PATHWAY
13
6.20E-03
0.11
3
8
GOTERM
nuclear body
16
6.40E-03
0.35
4
9
GOTERM
microtubule associated complex
24
6.50E-03
0.38
6
12
GOTERM
cell migration
54
6.50E-03
0.45
14
22
GOTERM
hyaluronic acid binding
16
6.60E-03
0.43
4
9
STAB1
REACTOME
DOWNSTREAM_EVENTS_IN_GPCR_SI
GNALING
391
6.60E-03
0.22
98
119
ADCY3, GIPR, GNRHR, ITPR2,
KISS1, MC4R, POMC, TAC3,
TACR3, ARHGEF7, PROK2,
GOTERM
KEGG
GOTERM
PANTHER_BIOLOGICAL
_PROCESS
GOTERM
REACTOME
PANTHER_BIOLOGICAL
_PROCESS
KEGG
GOTERM
18
PROKR2
GOTERM
79
6.80E-03
0.37
20
30
ARHGEF7
KEGG
induction of apoptosis by
extracellular signals
KEGG_RENAL_CELL_CARCINOMA
67
6.90E-03
0.10
17
26
MAPK3, VEGFA
GOTERM
growth cone
51
7.30E-03
0.47
13
21
ARHGEF7
GOTERM
ER-Golgi intermediate compartment
36
7.80E-03
0.44
9
16
REACTOME
DEPOLARIZATION_OF_THE_PRESYNA
PTIC_TERMINAL_TRIGGERS_THE_OP
ENING_OF_CALCIUM_CHANNELS
arachidonic acid secretion
11
7.80E-03
0.21
3
7
11
8.20E-03
0.52
3
7
PANTHER_BIOLOGICAL
_PROCESS
GOTERM
Cell_structure_and_motility
169
8.30E-03
0.38
42
56
ER overload response
9
9.00E-03
0.49
2
6
PANTHER_BIOLOGICAL
_PROCESS
REACTOME
Amino_acid_activation
33
9.20E-03
0.53
8
15
WARS2
45
9.40E-03
0.27
11
19
SLC6A14
GOTERM
AMINO_ACID_AND_OLIGOPEPTIDE_
SLC_TRANSPORTERS
embryonic pattern specification
9
9.50E-03
0.37
2
6
KEGG
KEGG_MELANOMA
65
9.50E-03
0.13
16
25
GOTERM
clathrin coated vesicle membrane
11
9.70E-03
0.46
3
7
GOTERM
NuA4 histone acetyltransferase
complex
14
9.90E-03
0.41
4
8
Gene set
Gene set
size
FDR
Expected
# genes
Observed
# genes
PANTHER_MOLECULA
R_FUNCTION
GOTERM
Protease_inhibitor
10
Nominal
GSEA Pvalue
1.10E-03
0.02
1
4
cytosol
1118
1.00E-04
0.70
56
78
PANTHER_BIOLOGICAL
_PROCESS
KEGG
Apoptosis
173
1.00E-04
0.17
9
20
51
3.00E-04
0.10
3
9
GOTERM
KEGG_AMYOTROPHIC_LATERAL_SCL
EROSIS_ALS
cysteine-type endopeptidase activity
48
1.40E-03
0.80
2
8
REACTOME
ERK_MAPK_TARGETS
19
1.60E-03
0.29
1
5
GOTERM
95th percentile males
Database
19
FGF8, FGFR1, MAPK3
Flagged gene names
GAD2, PLCG1, PRKD1, MAPK3,
RPL27A, ARHGEF7, SPRY2,
NISCH
PRKD1
MAPK3
KEGG
KEGG_STEROID_HORMONE_BIOSYN
THESIS
Other_phosphatase
36
2.10E-03
0.08
2
7
68
2.20E-03
0.19
3
10
28
2.50E-03
0.09
1
6
72
2.50E-03
0.33
4
10
21
2.70E-03
0.28
1
5
REACTOME
Amyotrophic.Lateral.Sclerosis.Signali
ng
P75_NTR_RECEPTOR_MEDIATED_SIG
NALLING
ABORTIVE_ELONGATION_OF_HIV1_T
RANSCRIPT_IN_THE_ABSENCE_OF_T
AT
SIGNALLING_BY_NGF
202
2.80E-03
0.41
10
20
BIOCARTA
CASPASE_PATHWAY
21
3.50E-03
0.39
1
5
GOTERM
T cell differentiation in the thymus
13
3.70E-03
1.00
1
4
GOTERM
bone resorption
13
3.80E-03
0.81
1
4
REACTOME
APOPTOSIS
116
4.30E-03
0.25
6
13
REACTOME
NUCLEAR_EVENTS_KINASE_AND_TR
ANSCRIPTION_FACTOR_ACTIVATION
spliceosomal snRNP assembly
22
4.60E-03
0.26
1
5
24
5.60E-03
0.78
1
5
25
6.00E-03
0.17
1
5
GOTERM
Alzheimer_diseaseamyloid_secretase_pathway
ubiquitin-specific protease activity
24
6.10E-03
0.86
1
5
GOTERM
early endosome membrane
35
7.50E-03
0.76
2
6
BIOCARTA
P53_PATHWAY
16
7.60E-03
0.30
1
4
GOTERM
cytoskeleton
612
7.70E-03
0.71
31
44
MAPK3, DNM3
GOTERM
microtubule
210
7.70E-03
0.72
11
19
SPRY2, DNM3
GOTERM
9
8.00E-03
0.87
0
3
GOTERM
regulation of mitochondrial
membrane permeability
cell-cell adherens junction
25
8.10E-03
0.77
1
5
GOTERM
microtubule bundle formation
9
8.80E-03
0.89
0
3
75 percentile males
Database
Gene set
Gene set
size
FDR
Expected
# genes
Observed
# genes
GOTERM
coreceptor activity
15
Nominal
GSEA Pvalue
6.00E-04
0.53
4
10
REACTOME
NUCLEOTIDE_LIKE_PURINERGIC_REC
EPTORS
11
1.30E-03
0.10
3
8
PANTHER_MOLECULA
R_FUNCTION
Ingenuity
REACTOME
REACTOME
GOTERM
Panther
NUDT3
ARHGEF7
ADCY3, IRS1, ITPR2, PLCG1,
MAPK3, MAP2K5, ARHGEF7
MAPK3
th
20
Flagged gene names
REACTOME
P2Y_RECEPTORS
7
1.90E-03
0.15
2
6
Ingenuity
T.Cell.Receptor.Signaling
33
2.80E-03
0.14
8
16
Ingenuity
28
3.80E-03
0.09
7
14
GOTERM
Amyotrophic.Lateral.Sclerosis.Signali
ng
positive regulation of transcription
123
4.20E-03
1.00
31
44
MKL2
GOTERM
cytosol
1118
4.50E-03
1.00
280
311
GAD2, PLCG1, PRKD1, MAPK3,
RPL27A, ARHGEF7, SPRY2,
NISCH
BIOCARTA
AGPCR_PATHWAY
13
4.50E-03
0.58
3
8
REACTOME
HIV_INFECTION
167
4.60E-03
0.39
42
57
KEGG
KEGG_ARRHYTHMOGENIC_RIGHT_V
ENTRICULAR_CARDIOMYOPATHY_AR
VC
RHO_GTPASE_CYCLE
68
5.10E-03
0.72
17
27
108
5.70E-03
0.38
27
39
ARHGEF7
PANTHER_BIOLOGICAL
_PROCESS
BIOCARTA
Signal_transduction
244
5.80E-03
0.72
61
78
NR4A2, RORA, RXRG,
PLA2G10, TRIB1
MCM_PATHWAY
18
6.00E-03
0.32
5
10
GOTERM
filopodium assembly
13
6.10E-03
1.00
3
8
REACTOME
CD28_DEPENDENT_VAV1_PATHWAY
11
6.20E-03
0.39
3
7
PANTHER_MOLECULA
R_FUNCTION
GOTERM
Annexin
63
6.80E-03
1.00
16
25
nucleotide binding
1614
7.00E-03
1.00
404
434
REACTOME
187
7.20E-03
0.34
47
62
GOTERM
REGULATION_OF_INSULIN_SECRETIO
N
cysteine-type endopeptidase activity
48
7.30E-03
1.00
12
20
BIOCARTA
ACH_PATHWAY
16
7.40E-03
0.29
4
9
PANTHER_BIOLOGICAL
_PROCESS
Other_metabolism
379
9.20E-03
0.70
95
114
REACTOME
21
PLCG1
DNM3
ADCY3, FGFR1, PARN, PRKD1,
MAPK3, MAP2K5, SFRS10,
WARS2, DNM3, TNNI3K,
CHD7, PTBP2, EEFSEC, CPEB4
ITPR2
MAP2K5, MRPS22
Cohort study descriptions
Avon Longitudinal Study of Parents and Children (ALSPAC)
ALSPAC is a prospective birth cohort which recruited pregnant women with expected delivery dates between
April 1991 and December 1992 from Bristol, United Kingdom. 14,541 pregnant women were initially enrolled
with 14,062 children born. Detailed information on health and development of children and their parents
were collected from regular clinic visits and completion of questionnaires. A detailed description of the cohort
has been published previously (11). Ethical approval was obtained from the ALSPAC Law and Ethics
Committee and the Local Ethics Committees. Please note that the study website contains details of all the
data that is available through a fully searchable data dictionary (http://www.bris.ac.uk/alspac/researchers/dataaccess/data-dictionary/).
A total of 9,912 subjects were genotyped using the Illumina HumanHap550 quad genome-wide SNP
genotyping platform by 23andMe subcontracting the Wellcome Trust Sanger Institute, Cambridge, UK and the
Laboratory Corporation of America, Burlington, NC, USA.
An important facet in the study of children as they go through late childhood into adolescence concerns the
timing of the onset of puberty. One of the measures used to assess the stage of puberty in the ALSPAC study is
concerned with a self-rating of puberty. The questionnaire was developed in association with Dr Carol Rubin of
the Centers for Disease Control (CDC), Atlanta, USA. CDC funded the printing and coding of these
questionnaires. The questions asked were obviously different for boys and girls. Each questionnaire included a
set of pictures, based on those developed by Tanner adapted from those used in studies in the USA.
Individuals were excluded from further analysis on the basis of having incorrect gender assignments; extreme
heterozygosity (<0.320 and >0.345 for the Sanger data and <0.310 and >0.330 for the LabCorp data); high
levels of individual missingness (>3%); evidence of cryptic relatedness (>10% IBD) and being of non-European
ancestry (as detected by a multidimensional scaling analysis seeded with HapMap 2 individuals). EIGENSTRAT
analysis revealed no additional obvious population stratification and genome-wide analyses with other
phenotypes indicate a low lambda. The resulting data set consisted of 8,365 individuals. SNPs with a minor
allele frequency of <1% and call rate of <95% were removed. Only SNPs which passed an exact test of Hardy–
Weinberg equilibrium (P >5 × 10-7) were considered for analysis. After cleaning, 500,527 SNPs were available
for analysis. Known autosomal variants were imputed with MACH 1.0.16 Markov Chain Haplotyping software
(12), using CEPH individuals from phase 2 of the HapMap project (HG18) as a reference set (release 22). For
the X chromosomal variants, imputation was performed using MiniMac (v4.43) (13) and CEPH individuals from
phase 3 of the HapMap project (HG18) were used as the reference set.
1958 British Birth Cohort or NCDS (B58C-WTCCC) and 1958 British Birth Cohort or NCDS (B58C-T1DGC): The
population-based 1958BC included initially all children born in England, Scotland or Wales during one week in
March 1958 (N=17,415). Medical examination was carried out at age 11 years (1969), and this included an
assessment of pubertal development based on breast rating in participating girls. DNA was collected as part of
a biomedical examination carried out at 45 years. Genome-wide data for the 1958BC was obtained through
two sub-studies in which participants of the 1958BC members (restricted to white European ancestry) were
used as a control population. First, 3,000 cohort members were randomly selected as controls for the
22
Wellcome Trust Case Control Consortium (WTCCC (14) including 1,083 girls with Tanner staging) and
genotyped on the Affymetrix SNP 6.0 platform. Secondly, 2,592 participants (1083 girls with staging) were
used as controls for a type 1 diabetes case-control study (T1DGC (15)), with samples genotyped through the
JDRF/WT Diabetes and Inflammation Laboratory (DIL) using the Illumina Infinium 550K chip. Ethical approval
for the biomedical survey was obtained from the South East Multi-centre Research Ethics Committee (ref.
01/1/44) and the Joint UCL/UCLH Committees on the Ethnics of Human Research (Committee A) (ref.
08/H0714/40).
Cardiovascular Risk in Young Finns Study (YFS): The Cardiovascular Risk in Young Finns (YFS) is a populationbased 30 year follow up-study (http://youngfinnsstudy.utu.fi/). The first cross-sectional survey was conducted
in 1980, when 3,596 Caucasian subjects aged 3-18 years participated. The follow-up studies for the same
subjects were performed in 1983, 1986, and 2007. In adulthood, the latest 30-year follow-up study was
conducted in 2011 (ages 33-48 years) with ca. 2,100 participants. The study cohort for the present analysis
comprised of subjects who had data on Tanner pubertal stage classification at 9 to 18 years old (measured in
1980, 1983 and 1986) available with genotype and other risk factor data (16). The study was approved by the
local Ethical Committees and was performed according to the Helsinki Declaration.
Netherlands Twin Register (NTR): The Netherlands Twin Register (NTR) is a large population-based study that
has collected data on the health and behaviour of twin families since 1986 (17). Data on Tanner stages have
been collected in a number of subprojects. In some, Tanner stage was assessed by a clinician or trained
researcher; in others, Tanner stage was based on self-reports using pictures or schematic drawings (18, 19).
Blood and/or buccal samples were collected in several projects and genotyped on the Affymetrix Human SNP
Array 6.0 at the Avera Institute, Sioux Falls, South Dakota (USA) (20). Genotypes were called using the
BIRDSEED V2 algorithm and SNPs were imputed at the MD Anderson Cancer Center, Houston, Texas (USA)
using the BEAGLE software. If an individual had multiple samples available, the sample with the highest quality
was selected. In monozygotic twin pairs, one individual was selected at random. Siblings and dizygotic twin
pairs were kept in the dataset; in total, genotypic and phenotypic data were available for 265 children. To
correct the analyses for the dependencies in the data, the --within option in Plink was used with family
number as a cluster variable. Study protocols were approved by the medical ethics board of the VU Medical
Center Amsterdam, the Netherlands (IRB number IRB00002991).
Netherlands Study of Depression and Anxiety (NESDA) and NTR eQTL dataset: NESDA and NTR studies were
approved by the Central Ethics Committee on Research Involving Human Subjects of the VU University
Medical Center, Amsterdam (IRB number IRB-2991 under Federalwide Assurance 3703; IRB/institute codes,
NESDA 03-183; NTR 03-180), and all subjects provided written informed consent. The sample used for eQTL
analysis consisted of 5,071 subjects, 3,109 NTR (from 1,571 families: 614 dizygotic twin pairs, 1 monozygotic
triplet, 668 monozygotic twin pairs, 394 siblings and 148 unrelated subjects) and 1,962 NESDA participants.
The age of the participants ranged from 17 to 88 years (mean 38, SD 13) and 65% of the sample was female.
Western Australia Pregnancy Study (RAINE): Recruitment of the Western Australian Pregnancy (RAINE)
cohort has previously been described in detail (21–23). In brief, between 1989 and 1991, 2,900 pregnant
women were recruited prior to 18-weeks gestation into a randomised controlled trial to evaluate the effects
23
of repeated ultrasound in pregnancy. Children have been comprehensively phenotyped from birth to 21 years
of age (average ages of one, two, three, six, eight, ten, fourteen, seventeen and twenty-one) by trained
members of the Raine research team. Most of the children are of Caucasian ethnicity. Data collection included
questionnaires completed by the child’s primary carer and by the adolescent from age 14, physical
assessments by trained assessors at all follow up years, and DNA collection from year 14 follow-up. The study
was conducted with appropriate institutional ethics approval, and written informed consent was obtained
from all mothers. Study individual genotype data was extracted from the genome-wide Illumina 660 Quad
Array.
TEENS of Attica: Genes and Environment Study (TEENAGE): The TEENAGE study is a cross-sectional study. The
study target population comprised 857 adolescent students aged 13–15 years attending the first three classes
of public secondary schools located in the wider Athens area of Attica. Prior to recruitment all study
participants gave their verbal assent along with their parents’/guardians’ written consent forms. The study
protocol was approved by the Institutional Review Board of Harokopio University and the Greek Ministry of
Education, Lifelong Learning and Religious Affairs (24). Sexual maturity status was assessed by self-evaluation
of the individual (25, 26) in the presence of the team’s paediatrician according to Tanner’s criteria (27) for
breast, pubic hair and genital development. DNA samples of 707 study participants were genotyped using
Illumina HumanOmniExpress BeadChips (Illumina, San Diego, CA, USA) at the Wellcome Trust Sanger Institute,
Hinxton, UK. Genotyping and data quality control have been described previously (28). Genotypes were called
using Illuminus algorithm (29) and SNPs were imputed using the program IMPUTE (30).
Infancia y Medio Ambiente (Environment and childhood) Project (INMA): Population-based birth cohorts
were established as part of the INMA – INfancia y Medio Ambiente [Environment and Childhood] Project in
several regions of Spain following a common protocol. This analysis uses the INMA cohort of Menorca
(Balearic Islands) established between 1997 and 1998. This project aims to study the associations between
pre- and postnatal environmental exposures and growth, health, and development from early fetal life until
adolescence and has been described previously in detail (31). Pregnant women were enrolled during the
pregnancy at public primary health care centers or public hospitals. Detailed measurements were performed
using physical examinations and biological samples were collected. Informed consent was obtained from all
participants and the study was approved by the Hospital Ethics Committee. Whole blood or saliva DNA
collected at age 4y was available for 432/482 (89%) children from Menorca. Samples from white European
children were selected for the genome-wide genotyping using the HumanOmni1-Quad Beadchip
(Illumina). This analysis uses data from 119 females from the cohort.
Leipzig Childhood Cohort (LEIPZIG): A representative sample of children and adolescents from Central
Germany was collected in a cross-sectional study from schools. Schools were selected to cover representative
local areas within the city of Leipzig and its suburbs (hence social distribution) and covering different school
types, hence levels of education. Physical examinations were performed by pediatricians. Height was
measured using a standardized mobile digital stadiometer and weight by digital scale with an accuracy of 0.1
kg. The study was approved by the local ethics committee #054-2006. All guardians and children gave
informed consent to the study and analyses.
24
Special Turku Coronary Risk Factor Intervention Project (STRIP): The STRIP trial is a prospective, randomized
study that aims to prevent atherosclerosis beginning in infancy. The main objectives of STRIP have been to
study the safety and effects of a low saturated fat diet in childhood. In brief, between February 1990 and June
1992, families of 6-month-old infants were recruited at well-baby clinics in Turku, Finland. At 7 months of age,
1,062 infants were randomly allocated to a dietary intervention (n=540) or control (n=522) group. The
intervention group received individualized dietary and subsequently antismoking counseling at least
biannually until 20 years of age.
The STRIP study has several dimensions. First, the follow-up period of the intervention and control children
and families is long, i.e. from 7 months of age through childhood and adolescence till early adulthood. The
coronary risk factor profile exploration has been wide ranging (serum lipids and lipoprotein and
apolipoproteins, glucose and insulin values, blood pressure, recurrent infections, oral health, etc.) and
included also many measurable aspects of daily life (diet, physical activity, smoking, socioeconomic status,
psychosocial well-being, etc.) have been explored. Vascular ultrasonic measurements were introduced at the
age of 11 and repeated every two years thereafter. The core laboratory examinations have covered the key
atherosclerosis risk factors and these values and aspects have been monitored in all STRIP children regularly
and frequently, most of them annually.
Pubertal status of the child was recorded from the age of 9 years onward. The physicians who examined the
children were trained by an experienced pediatric endocrinologist to correctly stage pubertal development.
The signs of puberty were recorded according to Tanner staging. Breast tissue diameter and testicular length
were measured with a ruler, and pubic hair development was estimated visually. The respective pubertal
stages (M1 through M5 and P1 through P5 in girls; G1 through G5 and P1 through P5 in boys) were recorded
according to well established criteria. M2 stood for breast budding; G2 indicated testicular length of 20 mm
(corresponding volume 3 mL).
The study was approved by the Joint Commission on Ethics of the Turku University and the Turku University
Central Hospital. Written informed consent was obtained from the parents in the beginning of the study and
from the adolescents at 15 years of age. The Joint Commission on Ethics of the Turku University and the Turku
University Central Hospital approved the STRIP study. Informed consent was obtained from the parents of the
children at the beginning of the trial.
References
1. Magi, R., Lindgren, C.M. and Morris, A.P. (2010) Meta-analysis of sex-specific genome-wide association
studies. Genet. Epidemiol., 34, 846–853.
2. Mägi, R. and Morris, A.P. (2010) GWAMA: software for genome-wide association meta-analysis. BMC
Bioinformatics, 11, 288.
3. Boyle, A.P., Hong, E.L., Hariharan, M., Cheng, Y., Schaub, M.A., Kasowski, M., Karczewski, K.J., Park, J., Hitz,
B.C., Weng, S., et al. (2012) Annotation of functional variation in personal genomes using RegulomeDB.
Genome Res., 22, 1790–1797.
25
4. Speliotes, E.K., Willer, C.J., Berndt, S.I., Monda, K.L., Thorleifsson, G., Jackson, A.U., Lango Allen, H.,
Lindgren, C.M., Luan, J., Mägi, R., et al. (2010) Association analyses of 249,796 individuals reveal 18
new loci associated with body mass index. Nat. Genet., 42, 937–948.
5. Elks, C.E., Perry, J.R.B., Sulem, P., Chasman, D.I., Franceschini, N., He, C., Lunetta, K.L., Visser, J.A., Byrne,
E.M., Cousminer, D.L., et al. (2010) Thirty new loci for age at menarche identified by a meta-analysis of
genome-wide association studies. Nat. Genet., 42, 1077–1085.
6. Cousminer, D.L., Berry, D.J., Timpson, N.J., Ang, W., Thiering, E., Byrne, E.M., Taal, H.R., Huikari, V.,
Bradfield, J.P., Kerkhof, M., et al. (2013) Genome-wide association and longitudinal analyses reveal
genetic loci linking pubertal height growth, pubertal timing and childhood adiposity. Hum. Mol. Genet.,
10.1093/hmg/ddt104.
7. Fernández-Rhodes, L., Demerath, E.W., Cousminer, D.L., Tao, R., Dreyfus, J.G., Esko, T., Smith, A.V.,
Gudnason, V., Harris, T.B., Launer, L., et al. (2013) Association of Adiposity Genetic Variants With
Menarche Timing in 92,105 Women of European Descent. Am. J. Epidemiol., 10.1093/aje/kws473.
8. Demerath, E.W., Liu, C.-T., Franceschini, N., Chen, G., Palmer, J.R., Smith, E.N., Chen, C.T.L., Ambrosone,
C.B., Arnold, A.M., Bandera, E.V., et al. (2013) Genome-wide association study of age at menarche in
African-American women. Hum. Mol. Genet., 10.1093/hmg/ddt181.
9. Bradfield, J.P., Taal, H.R., Timpson, N.J., Scherag, A., Lecoeur, C., Warrington, N.M., Hypponen, E., Holst, C.,
Valcarcel, B., Thiering, E., et al. (2012) A genome-wide association meta-analysis identifies new
childhood obesity loci. Nat. Genet., 44, 526–531.
10. Segrè, A.V., DIAGRAM Consortium, MAGIC investigators, Groop, L., Mootha, V.K., Daly, M.J. and Altshuler,
D. (2010) Common inherited variation in mitochondrial genes is not enriched for associations with type
2 diabetes or related glycemic traits. PLoS Genet., 6.
11. Boyd, A., Golding, J., Macleod, J., Lawlor, D.A., Fraser, A., Henderson, J., Molloy, L., Ness, A., Ring, S. and
Smith, G.D. (2012) Cohort Profile: The ‘Children of the 90s’—the index offspring of the Avon
Longitudinal Study of Parents and Children. Int. J. Epidemiol., 10.1093/ije/dys064.
12. Li, Y., Willer, C.J., Ding, J., Scheet, P. and Abecasis, G.R. (2010) MaCH: using sequence and genotype data to
estimate haplotypes and unobserved genotypes. Genet. Epidemiol., 34, 816–834.
13. Howie, B., Fuchsberger, C., Stephens, M., Marchini, J. and Abecasis, G.R. (2012) Fast and accurate
genotype imputation in genome-wide association studies through pre-phasing. Nat. Genet., 44, 955–
959.
14. International Multiple Sclerosis Genetics Consortium, Wellcome Trust Case Control Consortium 2, Sawcer,
S., Hellenthal, G., Pirinen, M., Spencer, C.C.A., Patsopoulos, N.A., Moutsianas, L., Dilthey, A., Su, Z., et
al. (2011) Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.
Nature, 476, 214–219.
15. Barrett, J.C., Clayton, D.G., Concannon, P., Akolkar, B., Cooper, J.D., Erlich, H.A., Julier, C., Morahan, G.,
Nerup, J., Nierras, C., et al. (2009) Genome-wide association study and meta-analysis find that over 40
loci affect risk of type 1 diabetes. Nat. Genet., 41, 703–707.
26
16. Heinonen, I., Helajarvi, H., Pahkala, K., Heinonen, O.J., Hirvensalo, M., Palve, K., Tammelin, T., Yang, X.,
Juonala, M., Mikkila, V., et al. (2013) Sedentary behaviours and obesity in adults: the Cardiovascular
Risk in Young Finns Study. BMJ Open, 3.
17. Van Beijsterveldt, C.E.M., Groen-Blokhuis, M., Hottenga, J.J., Franić, S., Hudziak, J.J., Lamb, D., Huppertz, C.,
de Zeeuw, E., Nivard, M., Schutte, N., et al. (2013) The Young Netherlands Twin Register (YNTR):
longitudinal twin and family studies in over 70,000 children. Twin Res. Hum. Genet. Off. J. Int. Soc. Twin
Stud., 16, 252–267.
18. Van Soelen, I.L.C., Brouwer, R.M., van Baal, G.C.M., Schnack, H.G., Peper, J.S., Chen, L., Kahn, R.S.,
Boomsma, D.I. and Hulshoff Pol, H.E. (2013) Heritability of volumetric brain changes and height in
children entering puberty. Hum. Brain Mapp., 34, 713–725.
19. Hoekstra, R.A., Bartels, M. and Boomsma, D.I. (2006) Heritability of testosterone levels in 12-year-old twins
and its relation to pubertal development. Twin Res. Hum. Genet. Off. J. Int. Soc. Twin Stud., 9, 558–565.
20. Scheet, P., Ehli, E.A., Xiao, X., van Beijsterveldt, C.E.M., Abdellaoui, A., Althoff, R.R., Hottenga, J.J.,
Willemsen, G., Nelson, K.A., Huizenga, P.E., et al. (2012) Twins, tissue, and time: an assessment of SNPs
and CNVs. Twin Res. Hum. Genet. Off. J. Int. Soc. Twin Stud., 15, 737–745.
21. Newnham, J.P., Sharon, S.F., Michael, C.A., Stanley, F.J. and Landau, L.I. (1994) [Effects of frequent
ultrasound during pregnancy: a randomised controlled trial]. Jordemodern, 107, 83–86.
22. Williams, L.A., Evans, S.F. and Newnham, J.P. (1997) Prospective cohort study of factors influencing the
relative weights of the placenta and the newborn infant. BMJ, 314, 1864–1868.
23. Evans, S., Newnham, J., MacDonald, W. and Hall, C. (1996) Characterisation of the possible effect on
birthweight following frequent prenatal ultrasound examinations. Early Hum. Dev., 45, 203–214.
24. Ntalla, I., Giannakopoulou, M., Vlachou, P., Giannitsopoulou, K., Gkesou, V., Makridi, C., Marougka, M.,
Mikou, G., Ntaoutidou, K., Prountzou, E., et al. (2013) Body composition and eating behaviours in
relation to dieting involvement in a sample of urban Greek adolescents from the TEENAGE (TEENs of
Attica: Genes & Environment) study. Public Health Nutr., 10.1017/S1368980013000074.
25. Duke, P.M., Litt, I.F. and Gross, R.T. (1980) Adolescents’ self-assessment of sexual maturation. Pediatrics,
66, 918–920.
26. Bonat, S., Pathomvanich, A., Keil, M.F., Field, A.E. and Yanovski, J.A. (2002) Self-assessment of pubertal
stage in overweight children. Pediatrics, 110, 743–747.
27. Garn, S.M. (1956) Growth at adolescence. By J. M. Tanner. Pp. vii + 212. Blackwell Scientific Publications,
Oxford. Publisher simultaneously by Charles C Thomas and the Ryerson Press. 1955. Am. J. Phys.
Anthropol., 14, 120–122.
28. Ntalla, I., Panoutsopoulou, K., Vlachou, P., Southam, L., William Rayner, N., Zeggini, E. and Dedoussis, G.V.
(2013) Replication of established common genetic variants for adult BMI and childhood obesity in
Greek adolescents: the TEENAGE study. Ann. Hum. Genet., 77, 268–274.
27
29. Teo, Y.Y., Inouye, M., Small, K.S., Gwilliam, R., Deloukas, P., Kwiatkowski, D.P. and Clark, T.G. (2007) A
genotype calling algorithm for the Illumina BeadArray platform. Bioinforma. Oxf. Engl., 23, 2741–2746.
30. Marchini, J., Howie, B., Myers, S., McVean, G. and Donnelly, P. (2007) A new multipoint method for
genome-wide association studies by imputation of genotypes. Nat. Genet., 39, 906–913.
31. Guxens, M., Ballester, F., Espada, M., Fernández, M.F., Grimalt, J.O., Ibarluzea, J., Olea, N., Rebagliato, M.,
Tardón, A., Torrent, M., et al. (2012) Cohort Profile: the INMA--INfancia y Medio Ambiente-(Environment and Childhood) Project. Int. J. Epidemiol., 41, 930–940.
Consortia
1. The Early Growth Genetics (EGG) Consortium
Linda S Adair, Wei Ang, Mustafa Atalay, Toos van Beijsterveldt, Nienke Bergen, Kelly Benke, Diane J Berry, Dorret
I Boomsma, Jonathan P Bradfield, Pimphen Charoen, Lachlan Coin, Cyrus Cooper, Diana L Cousminer, Shikta Das,
Oliver S P Davis, George V Dedoussis, Paul Elliott, Xavier Estivill, David M Evans, Bjarke Feenstra, Claudia
Flexeder, Tim Frayling, Rachel M Freathy, Romy Gaillard, Frank Geller, Matthew Gillman, Struan F A Grant, Maria
Groen-Blokhuis, Liang-Kee Goh, Mònica Guxens, Hakon Hakonarson, Andrew T Hattersley, Claire M A Haworth,
Dexter Hadley, Johannes Hedebrand, Joachim Heinrich, Anke Hinney, Joel N Hirschhorn, Berthold Hocher, John
W Holloway, Claus Holst, Jouke Jan Hottenga, Momoko Horikoshi, Ville Huikari, Elina Hypponen, Carmen Iñiguez,
Vincent WV Jaddoe, Marjo-Riitta Jarvelin, Marika Kaakinen, Tuomas O Kilpeläinen, Mirna Kirin, Matthew
Kowgier, Hanna-Maaria Lakka, Timo A Lakka, Leslie A Lange, Debbie A Lawlor, Terho Lehtimäki, Alex Lewin,
Cecilia Lindgren, Virpi Lindi, Reedik Maggi, Julie Marsh, Mark I McCarthy, Mads Melbye, Christel Middeldorp,
Iona Millwood, Karen L Mohlke, Dennis O Mook-Kanamori, Jeffrey C Murray, Michel Nivard, Ellen Aagaard Nohr,
Ioanna Ntalla, Emily Oken, Ken K Ong, Paul F O’Reilly, Lyle J Palmer, Kalliope Panoutsopoulou, Jennifer
Pararajasingham, Ewan R Pearson, Craig E Pennell, Chris Power, Thomas S Price, Inga Prokopenko, Olli T
Raitakari, Alina Rodriguez, Rany M Salem, Seang-Mei Saw, Andre Scherag, Sylvain Sebert, Niina Siitonen, Olli
Simell, Thorkild I A Sørensen, Ulla Sovio, Beate St Pourcain, David P Strachan, Jordi Sunyer, H Rob Taal, Yik-Ying
Teo, Elisabeth Thiering, Carla Tiesler, Nicholas J Timpson, Andre G Uitterlinden, Beatriz Valcárcel, Nicole M
Warrington, Scott White, Elisabeth Widén, Gonneke Willemsen, James F Wilson, Hanieh Yaghootkar & Eleftheria
Zeggini.
2. The ReproGen Consortium
Cathy E Elks, John R B Perry, Patrick Sulem, Daniel I Chasman, Nora Franceschini, Chunyan He, Kathryn L Lunetta,
Jenny A Visser, Enda M Byrne, Diana L Cousminer, Daniel F Gudbjartsson, Tõnu Esko, Bjarke Feenstra, Jouke-Jan
Hottenga, Daniel L Koller, Zoltán Kutalik, Peng Lin, Massimo Mangino, Mara Marongiu, Patrick F McArdle, Albert
V Smith, Lisette Stolk, Sophie H van Wingerden, Jing Hua Zhao, Eva Albrecht, Tanguy Corre, Erik Ingelsson,
Caroline Hayward, Patrik K E Magnusson, Erin N Smith, Shelia Ulivi, Nicole M Warrington, Lina Zgaga, Helen
Alavere, Najaf Amin, Thor Aspelund, Stefania Bandinelli, Inês Barroso, Gerald S Berenson, Sven Bergmann,
Hannah Blackburn, Eric Boerwinkle, Julie E Buring, Fabio Busonero, Harry Campbell, Stephen J Chanock, Wei
Chen, Marilyn C Cornelis, David Couper, Andrea D Coviello, Pio d'Adamo, Ulf de Faire, Eco J C de Geus, Panos
Deloukas, Angela Döring, George Davey Smith, Douglas F Easton, Gudny Eiriksdottir, Valur Emilsson, Johan
Eriksson, Luigi Ferrucci, Aaron R Folsom, Tatiana Foroud, Melissa Garcia, Paolo Gasparini, Frank Geller, Christian
Gieger, The GIANT Consortium, Vilmundur Gudnason, Per Hall, Susan E Hankinson, Liana Ferreli, Andrew C
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Heath, Dena G Hernandez, Albert Hofman, Frank B Hu, Thomas Illig, Marjo-Riitta Järvelin, Andrew D Johnson,
David Karasik, Kay-Tee Khaw, Douglas P Kiel, Tuomas O Kilpeläinen, Ivana Kolcic, Peter Kraft, Lenore J Launer,
Joop S E Laven, Shengxu Li, Jianjun Liu, Daniel Levy, Nicholas G Martin, Wendy L McArdle, Mads Melbye, Vincent
Mooser, Jeffrey C Murray, Sarah S Murray, Michael A Nalls, Pau Navarro, Mari Nelis, Andrew R Ness, Kate
Northstone, Ben A Oostra, Munro Peacock, Lyle J Palmer, Aarno Palotie, Guillaume Paré, Alex N Parker, Nancy L
Pedersen, Leena Peltonen, Craig E Pennell, Paul Pharoah, Ozren Polasek, Andrew S Plump, Anneli Pouta,
Eleonora Porcu, Thorunn Rafnar, John P Rice, Susan M Ring, Fernando Rivadeneira, Igor Rudan, Cinzia Sala,
Veikko Salomaa, Serena Sanna, David Schlessinger, Nicholas J Schork, Angelo Scuteri, Ayellet V Segrè, Alan R
Shuldiner, Nicole Soranzo, Ulla Sovio, Sathanur R Srinivasan, David P Strachan, Mar-Liis Tammesoo, Emmi
Tikkanen, Daniela Toniolo, Kim Tsui, Laufey Tryggvadottir, Jonathon Tyrer, Manuela Uda, Rob M van Dam, Joyce
B J van Meurs, Peter Vollenweider, Gerard Waeber, Nicholas J Wareham, Dawn M Waterworth, Michael N
Weedon, H Erich Wichmann, Gonneke Willemsen, James F Wilson, Alan F Wright, Lauren Young, Guangju Zhai,
Wei Vivian Zhuang, Laura J Bierut, Dorret I Boomsma, Heather A Boyd, Laura Crisponi, Ellen W Demerath,
Cornelia M van Duijn, Michael J Econs, Tamara B Harris, David J Hunter, Ruth J F Loos, Andres Metspalu, Grant W
Montgomery, Paul M Ridker, Tim D Spector, Elizabeth A Streeten, Kari Stefansson, Unnur Thorsteinsdottir,
André G Uitterlinden, Elisabeth Widen, Joanne M Murabito, Ken K Ong & Anna Murray.
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