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Supplementary Information for
Genome-wide association study identifies variants at CLU and PICALM associated with
Alzheimer's disease, and shows evidence for additional susceptibility genes
Denise Harold, Richard Abraham, Paul Hollingworth, Rebecca Sims, Amy Gerrish,
Marian Hamshere, Jaspreet Singh Pahwa, Valentina Moskvina, Kimberley Dowzell, Amy
Williams, Nicola Jones, Charlene Thomas, Alexandra Stretton, Angharad Morgan, Simon
Lovestone, John Powell, Petroula Proitsi, Michelle K Lupton, Carol Brayne, David C.
Rubinsztein, Michael Gill, Brian Lawlor, Aoibhinn Lynch, Kevin Morgan, Kristelle Brown,
Peter Passmore, David Craig, Bernadette McGuinness, Stephen Todd, Clive Holmes, David
Mann, A. David Smith, Seth Love, Patrick G. Kehoe, John Hardy, Simon Mead, Nick Fox,
Martin Rossor, John Collinge, Wolfgang Maier, Frank Jessen, Britta Schürmann, Hendrik
van den Bussche, Isabella Heuser, Johannes Kornhuber, Jens Wiltfang, Martin Dichgans,
Lutz Frölich, Harald Hampel, Michael Hüll, Alison Goate, John S.K. Kauwe, Carlos
Cruchaga, Petra Nowotny, John C. Morris, Kevin Mayo, Kristel Sleegers, Karolien Bettens,
Sebastiaan Engelborghs, Peter De Deyn, Christine van Broeckhoven, Gill Livingston,
Nicholas J. Bass, Hugh Gurling, Andrew McQuillin, Rhian Gwilliam, Panagiotis Deloukas,
Ammar Al-Chalabi, Christopher E. Shaw, Magda Tsolaki, Andrew Singleton, Rita
Guerreiro, Thomas W. Mühleisen, Markus M. Nöthen, Susanne Moebus, Karl-Heinz
Jöckel, Norman Klopp, H-Erich Wichmann, Minerva M. Carrasquillo, V. Shane Pankratz,
Steven G. Younkin, Peter Holmans, Michael O’Donovan, Michael J.Owen, Julie Williams.
MAYO ¶
1958BC
CORIELL
UK
610
USA
610
Germany
610
USA
300
UK
550
USA
550
Germany
550
Germany
550
UK/USA
300
4957
3941
62.7
6.6
73.2
78.6
80.4
1221
1009
70.4
0.0
75.7
80.9
N/A
1223
960
60.4
8.3
‡
72.1
78.4
82.9
503
424
56.1
0.0
73.1
80.5
84.1
278
211
58.8
0.0
‡
63.2
N/A
N/A
53
47
74.5
0.0
N/A
80.6
N/A
155
127
63.0
0.0
72.1
81.3
N/A
680
555
63.9
0.0
70.5
72.9
N/A
844
608
57.4
29.6
‡
74.1
N/A
†
73.9
-
-
-
-
-
Mean Age at onset
Age at assessment, mean
Age at death, mean *
Elderly Screened Controls
n, total
n, passed QC
% Female
% Neuropathological Confirmed
Age at assessment, mean
Age at death, mean *
Population Controls
n, total
n, passed QC
% Female
% Neuropathological Confirmed
Age at assessment, mean
Age at death, mean *
2857
2078
58.0
8.3
75.2
80.4
1044
873
62.0
0.0
75.9
N/A
121
82
59.8
23.2
76.7
81.6
300
233
66.1
0.0
77.7
N/A
-
-
-
137
37
64.9
0.0
79.5
N/A
1255
853
51.2
17.9
73.6
71.5
-
-
-
-
-
6825
5770
51.8
0.0
48.6
N/A
-
-
-
-
-
-
-
-
4032
3751
50.8
0.0
44.0
N/A
808
697
59.1
0.0
58.1
N/A
481
434
49.1
0.0
56.0
N/A
380
353
53.0
0.0
54.6
N/A
1124
535
50.3
0.0
57.2
N/A
ALS
NIMH
UK
610
HNR
UCL: LASER
USA
610
KORA F4
UCL: PRION
UK
610
BONN
WASHU ||
Geographical Region
Illumina Chip
AD Cases
n, total
n, passed QC
% Female
% Neuropathological Confirmed
MRC §
UK/Ire
610
TOTAL
ART
Supplementary Table 1. Sample size and descriptive statistics for the discovery sample.
* Only available for neuropathological samples
† Mean age at death for autopsy confirmed samples only (n=246). Age at onset data is not available for these participants.
‡ Age at onset only available for a proportion of the sample
§ 883 cases and 886 controls from the MRC sample described above were also included in the Abraham et al. study1. 877 cases and 862 controls were
included in the Grupe et al. study2. 374 cases and 181 controls were included in the Li et al. study3 (as part of a replication sample).
|| 150 cases and 158 controls from the WASHU sample described above were also included in the Grupe et al. study2.
¶ All MAYO cases and controls formed the Stage 1 sample of the Carrasquillo et al. study 4.
Geographical Region
AD Cases
n
% Female
% Neuropathological Confirmed
Mean Age at onset
Age at assessment, mean
Age at death, mean †
Elderly Screened Controls
n
% Female
% Neuropathological Confirmed
Age at assessment, mean
Age at death, mean †
GREEK
BONN
ART
MRC
BELGIUM *
TOTAL
Supplementary Table 3. Sample size and descriptive statistics for the follow-up sample.
Belgium
UK/Ire
UK
Germany
Greece
2023
66.2
0.0
73.2
78.2
N/A
1091
66.2
7.5
74.4
78.6
N/A
198
64.6
0.0
76.2
81.7
N/A
82
79.3
0.0
73.7 §
78.0
N/A
248
65.2
0.0
69.4 §
75.7
N/A
404
64.6
0.0
69.0 §
76.7
N/A
2340
59.1%
0.0%
69.8
N/A
662
58.4%
0.0%
63.0
N/A
372
64.2%
0.0%
76.6
N/A
305
67.7%
0.0%
74.0
N/A
618
65.5%
0.0%
79.6
N/A
383 ‡
37.7%
0.0%
54.9
N/A
* The Belgian sample was also included in the replication sample of Amouyel et al., this
issue of Nature Genetics
† Only available for neuropathological samples
‡ 171 aged-matched screened controls, 212 population controls
§ Age at onset only available for a proportion of the sample
Supplementary Table 4. SNPs selected for follow-up genotyping. P-values in the GWAS, the extension sample, a previous AD
GWAS (TGEN), and the combined sample (Meta) are also shown. All p-values are two-tailed.
LD with GWS SNP
SNP
rs7982
rs3087554
rs9331888
rs7012010
rs561655
rs592297
rs636848
rs532470
rs7941541
rs541458
rs543293
rs677909
Gene
CLU
CLU
CLU
CLU
PICALM
PICALM
PICALM
PICALM
PICALM
PICALM
PICALM
PICALM
Reason For Follow Up
Synonymous
3’UTR
5’UTR (transcript 2)
GWAS P<1x10-3
Within a Putative TFBS
Synonymous
Within a Putative TFBS
Putative eSNP
GWAS P<1x 10-4
GWAS P<1x 10-4
GWAS P<1x 10-4
GWAS P<1x 10-4
D’
r
1.000
1.000
1.000
0.682
0.960
0.923
0.312
0.468
0.957
0.954
0.875
0.910
1.000
0.091
0.199
0.100
0.720
0.283
0.023
0.126
0.708
0.590
0.577
0.558
2
GWAS
P-value
(N≤11789)
1x10-9 *
N/A
N/A
8x10-4
9x10-6 *
6x10-5 *
3x10-1 *
7x10-2 *
2x10-7
2x10-6
7x10-7
2x10-5
Extension
P-value
(N≤4233)
0.032
0.146
0.304
0.309
0.016
0.019
0.017
0.498
0.189
0.027
0.109
0.050
TGEN
P-value
(N≤1411)
N/A
N/A
N/A
0.033 *
N/A
0.136 *
N/A
N/A
0.005 *
0.038
0.023
0.012
Li et al.
P-value †
(N≤1489)
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
0.049
0.114
0.097
Meta
P-value
(N≤18922)
8x10-10 ‡
0.146
0.304
1x10-4 ‡
1x10-7 ‡
2x10-7 ‡
2x10-2 ‡
3x10-2 ‡
3x10-9 ‡
8x10-10 §
3x10-9 §
8x10-9 §
P-value is based on imputed genotypes. † P-value for Cochran-Armitage trend test rather than logistic regression, as only
genotype counts (from their discovery sample) were available. ‡ Meta P-value is based on partially imputed genotypes. § Meta
P-value for Mantel-Haenszel 2 test rather than logistic regression as only genotype counts were available for the Li et al. study.
GWS= genome-wide significant; OR = odds ratio for the minor allele.
*
Meta
OR
0.86
1.09
1.05
1.10
0.87
0.86
1.07
1.06
0.86
0.86
0.87
0.87
Supplementary Note
Stage 1 Discovery Sample: The discovery sample included 4,113 cases and 1,602 elderly
screened controls genotyped at the Sanger Institute on the Illumina 610-quad chip, referred
to collectively hereafter as the 610 group. These samples were recruited by the Medical
Research Council (MRC) Genetic Resource for AD (Cardiff University; Institute of
Psychiatry, London; Cambridge University; Trinity College Dublin), the Alzheimer’s
Research Trust (ART) Collaboration (University of Nottingham; University of Manchester;
University of Southampton; University of Bristol; Queen’s University Belfast; the Oxford
Project to Investigate Memory and Ageing (OPTIMA), Oxford University); Washington
University, St Louis, United States; MRC PRION Unit, University College London;
London and the South East Region AD project (LASER-AD), University College London;
Competence Network of Dementia (CND) and Department of Psychiatry, University of
Bonn, Germany and the National Institute of Mental Health (NIMH)AD Genetics Initiative.
These data were combined with data from 844 AD cases and 1,255 elderly screened
controls ascertained by the Mayo Clinic, Jacksonville, Florida; Mayo Clinic, Rochester,
Minnesota; and the Mayo Brain Bank, which were genotyped using the Illumina
HumanHap300 BeadChip. These samples were used in a previous GWAS of AD4. All AD
cases met criteria for either probable (NINCDS-ADRDA5, DSM-IV) or definite (CERAD)6
AD. A total of 6,825 population controls were included in stage 1. These were drawn from
large existing cohorts with available GWAS data, including the 1958 British Birth Cohort
(1958BC) (http://www.b58cgene.sgul.ac.uk), NINDS funded neurogenetics collection at
Coriell Cell Repositories (Coriell) (see http://ccr.coriell.org/), the KORA F4 Study7, Heinz
Nixdorf Recall Study8,9 and ALS Controls. The ALS Controls were genotyped using the
Illumina HumanHap300 BeadChip. All other population controls were genotyped using the
Illumina HumanHap550 Beadchip. Clinical characteristics of the discovery sample can be
found in Supplementary Table 1. We have obtained approval to perform a genome wide
association study including 19,000 participants (MREC 04/09/030; Amendment 2 and 4;
approved 27 July 2007). All individuals included in these analyses have provided informed
consent to take part in genetic association studies.
Stage 2 Follow-up Sample: The follow-up sample comprised 2,023 AD cases and 2,340
controls. Samples were drawn from the MRC genetic resource for AD; the ART
Collaboration; Competence Network of Dementia and Department of Psychiatry,
University of Bonn; Aristotle University of Thessaloniki; a Belgian sample derived from a
prospective clinical study at the Memory Clinic and Department of Neurology, ZNA
Middelheim, Antwerpen10; and the University of Munich. Clinical characteristics of the
follow-up sample can be found in Supplementary Table 3. Note that the Belgian sample
was also included in the replication sample of Amouyel et al. (this issue of Nature
Genetics).
Analysis of SNPs highlighted by previous GWA studies
Several GWA studies of AD have been performed to date and all identify the APOE locus
as being most significantly associated with AD. In an attempt to validate other risk loci
identified by these studies, we have tested ~100 SNPs in our sample that were highlighted
by previous GWAS publications1-4,11-14 (we have only considered GWAS based on over
100 individuals). For each SNP, we have aimed to perform a similar analysis to that
conducted in the original study, e.g. choice of genetic model, outcome variable, etc. Where
there is an overlap in individuals between a study and our own (see Supplementary Table
1), we have excluded those individuals prior to analysis. Thus, for each SNP, the sample
tested here is completely independent of that employed in the original study. Where a SNP
has not been directly genotyped in our study, we have aimed to identify a proxy SNP (r2
>0.7). For some regions, the same proxy SNP was identified to represent several different
markers. For example, some of the SNPs in the GAB2 gene that show association with AD
in the Reiman et al.14 study are in perfect LD in the HapMap CEU population. In such
situations, proxy SNP data is presented only once. The results of our analysis are shown in
Supplementary Table 5. We observe a number of SNPs showing association with AD with
p<0.05. This includes 2 SNPs previously identified by us in our smaller, GWAS pooling
study1. The first SNP (rs13115107, p=0.011) is in an intron of the ODZ3 gene, and shows
the same direction of effect in this independent subset of our sample as in the original
study. In our full sample this SNP has a p= 8x10-4, OR= 1.12. The second SNP is in an
intron of the PDE9A gene (rs3819902; p= 0.032); again we observe the same direction of
effect as in the original study. In our full sample, the SNP has a p= 6.2x10-4, OR= 0.85.
We also observe association with rs5984894, an intronic SNP of the PCDH11X gene
previously reported to be significantly associated with AD by Carrasquillo et al.4 in their
stage 1 sample of 844 cases and 1255 controls (included in this GWAS) and replicated in
their stage 2 sample of 1547 cases and 1209 controls. As in the original study, we have
analyzed the SNP by multivariable logistic regression, specifically modeling each carrier
group i.e. males hemizygous, females heterozygous and females homozygous for the minor
(A) allele; gender was included as a covariate and as with all SNPs analyzed in this study,
we have also included geographical region of origin and the first 4 principal components
from the EIGENSRTAT analysis as covariates. As a result, we obtain a 3 degrees of
freedom global p-value of 0.015 for the SNP in the independent subset of our sample.
However, it should be noted that when females homozygous for the A allele are compared
to females homozygous for the G allele, the direction of effect is in the opposite direction to
that observed in the original study (OR= 0.88, 95% CI =0.75-1.02, p=0.095 in this study).
We observe several nominally significant associations with SNPs highlighted by the
Beecham et al. study11. Amongst these is rs3807031 (p=9.7x10-3, OR= 1.09), a SNP in the
~2kb intergenic region between the ZNRD1 and PPP1R11 genes. An OR for this SNP was
not included in the Beecham publication so it is unknown if the effect is in the same
direction. We also observe association with rs3781835 (p= 9.7x10-3, OR= 0.63) an intronic
SNP in the SORL1 gene. SORL1 has shown association with AD in a number of studies15-21,
and although replication has been inconsistent19,22,23, the gene is ranked 9th in the AlzGene
database24 (which provides a comprehensive catalog of genetic association studies in AD
and details of meta-analyses for polymorphisms with available genotype counts in four or
more independent samples). Beecham et al.11 present a joint analysis of their own data with
that of Reiman et al.14, resulting in p=6.2x10-3, OR=0.54 for rs3781835. Our association,
showing the same direction of effect in an independent sample, thus provides additional
support for SORL1 as an AD susceptibility gene.
That a number of SNPs in Supplementary Table 5 do not show association in our sample
does not invalidate the original findings. There are some caveats to our analysis; for
example, not all SNPs were directly genotyped in our GWAS. An attempt was made to
identify proxy SNPs, but for some the LD between the proxy and original SNP had r2<1.
Moreover, seemingly perfect proxies may show lower levels of LD when examined in a
sample larger than the 60 HapMap CEU founders employed here. For a small number of
variants, proxy SNPs were not available at all. Another caveat is that it was not always
possible to perform the same analysis as in the original study. For example, in the study by
Bertram et al.24, the authors test for association with AD status and age at onset jointly in
their family-based sample. Our analysis of their most significant SNPs tested for
association with AD alone. To truly examine the evidence for AD candidate risk loci
identified to date, it is important that meta-analyses of existing datasets be performed. To
promote such efforts, our GWAS data will be made available to other researchers within 6
months.
Supplementary References
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disease using DNA pooling. BMC Med Genomics 1, 44 (2008).
2.
Grupe, A. et al. Evidence for novel susceptibility genes for late-onset Alzheimer's
disease from a genome-wide association study of putative functional variants. Hum
Mol Genet 16, 865-73 (2007).
3.
Li, H. et al. Candidate single-nucleotide polymorphisms from a genomewide
association study of Alzheimer disease. Arch Neurol 65, 45-53 (2008).
4.
Carrasquillo, M.M. et al. Genetic variation in PCDH11X is associated with
susceptibility to late-onset Alzheimer's disease. Nat Genet 41, 192-8 (2009).
5.
McKhann, G. et al. Clinical diagnosis of Alzheimer's disease: report of the
NINCDS-ADRDA Work Group under the auspices of Department of Health and
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Mirra, S.S. et al. The Consortium to Establish a Registry for Alzheimer's Disease
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Birnbaum, S. et al. Key susceptibility locus for nonsyndromic cleft lip with or
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Hillmer, A.M. et al. Susceptibility variants for male-pattern baldness on
chromosome 20p11. Nat Genet 40, 1279-81 (2008).
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Brouwers, N. et al. Genetic variability in progranulin contributes to risk for
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risk locus for late-onset Alzheimer disease. Am J Hum Genet 84, 35-43 (2009).
12.
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disease susceptibility loci in addition to APOE. Am J Hum Genet 83, 623-32 (2008).
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Coon, K.D. et al. A high-density whole-genome association study reveals that
APOE is the major susceptibility gene for sporadic late-onset Alzheimer's disease. J
Clin Psychiatry 68, 613-8 (2007).
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Reiman, E.M. et al. GAB2 alleles modify Alzheimer's risk in APOE epsilon4
carriers. Neuron 54, 713-20 (2007).
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Bettens, K. et al. SORL1 is genetically associated with increased risk for late-onset
Alzheimer disease in the Belgian population. Hum Mutat 29, 769-70 (2008).
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Feulner, T.M. et al. Examination of the current top candidate genes for AD in a
genome-wide association study. Mol Psychiatry (2009).
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Kolsch, H. et al. Association of SORL1 gene variants with Alzheimer's disease.
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Lee, J.H. et al. The association between genetic variants in SORL1 and Alzheimer
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(2007).
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Li, Y. et al. SORL1 variants and risk of late-onset Alzheimer's disease. Neurobiol
Dis 29, 293-6 (2008).
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Rogaeva, E. et al. The neuronal sortilin-related receptor SORL1 is genetically
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