no evidence that extended tracts of homozygosity are associated with alzheimer's disease
TRANSCRIPT
RESEARCH ARTICLE
No Evidence that Extended Tracts of Homozygosityare Associated with Alzheimer’s DiseaseRebecca Sims,1* Sarah Dwyer,1 Denise Harold,1 Amy Gerrish,1 Paul Hollingworth,1 Jade Chapman,1
Nicola Jones,1 Richard Abraham,1 Dobril Ivanov,1 Jaspreet Singh Pahwa,1 Valentina Moskvina,1
Kimberley Dowzell,1 Charlene Thomas,1 Alexandra Stretton,1 Simon Lovestone,2 John Powell,2
Petroula Proitsi,2Michelle K. Lupton,2 Carol Brayne,3 David C. Rubinsztein,4Michael Gill,5 Brian Lawlor,5
Aoibhinn Lynch,5 Kevin Morgan,6 Kristelle S. Brown,6 Peter A. Passmore,7 David Craig,7
Bernadette McGuiness,7 Stephen Todd,7 Janet A. Johnston,7 Clive Holmes,8 David Mann,9
A. David Smith,10 Seth Love,11 Patrick G. Kehoe,11 John Hardy,12 Simon Mead,13 Nick Fox,13
Martin Rossor,13 John Collinge,13 Gill Livingston,14 Nicholas J. Bass,14 Hugh Gurling,14
Andrew McQuillin,14 Lesley Jones,1 Peter A. Holmans,1 Michael O’Donovan,1 Michael J. Owen,1
and Julie Williams1
1MRC Centre for Neuropyschiatric Genetics and Genomics, Department of Psychological Medicine and Neurology, Cardiff University,
Heath Park, Cardiff, CF14 4XN2Department of Neuroscience, Institute of Psychiatry, Box P055, De Crespigny Park, London, SE5 8AF3Department of Public Health & Primary Care, Institute of Public Health,University of Cambridge, Forvie Site, Robinson Way, Cambridge, CB2 0SR4Cambridge Institute for Medical Research, Wellcome Trust/MRC Building, University of Cambridge, Addenbrooke’s Hospital, Hills Road,
Cambridge, CB2 0XY5Mercer’s Institute for Research on Ageing, St James Hospital and Trinity College, Hospital 4 Top Floor, St. James’s Hospital, James’s Street,
Dublin 86Institute of Genetics, School of Molecular Medical Sciences (MOL), Division of Clinical Chemistry, Queen’s Medical Centre,
University of Nottingham, NG7 2UH7Centre for Public Health, Queen’s University, Whitla Medical Building, 97 Lisburn Road, Belfast, BT9 7BL8University of Southampton, Division of Clinical Neurosciences, LD74, South Academic Block, Mailpoint 806, Southampton General Hospital,
Southampton, SO16 6YD9Greater Manchester Neuroscience Centre, University of Manchester, Salford Royal NHS Foundation Trust, Salford, M6 8HD10OPTIMA. University of Oxford, Room 4403, Level 4, John Radcliffe Hospital, Headington, Oxford, OX3 9DU11Institute of Clinical Neurosciences, University of Bristol, Department of Neuropathology, Frenchay Hospital, Bristol, BS16 1LE12Department of Molecular Neuroscience and Reta Lilla Weston Laboratories, Institute of Neurology, Queen Square, London, WC1N 3BG13Department of Neurodegenerative Disease, Institute of Neurology, Queen Square, London, WC1N 3BG14University College London, Department of Mental Health Sciences, 67-73 Riding House Street, 2nd Floor, Charles Bell House, London W1W 7EJ
Received 6 January 2011; Accepted 9 June 2011
We sought to investigate the contribution of extended runs
of homozygosity in a genome-wide association dataset of
1,955 Alzheimer’s disease cases and 955 elderly screened
controls genotyped for 529,205 autosomal single nucleotide
polymorphisms. Tracts of homozygosity may mark regions
inherited from a common ancestor and could reflect disease
loci if observed more frequently in cases than controls. We
found no excess of homozygous tracts in Alzheimer’s disease
cases compared to controls and no individual run of homozy-
gosity showed association to Alzheimer’s disease.
� 2011 Wiley-Liss, Inc.
Key words: alzheimer’s disease; runs of homozygosity;
genome-wide association study
Additional Supporting Information may be found in the online version of
this article.
*Correspondence to:
Rebecca Sims, HenryWellcome Building, Heath Park, Cardiff, CF14 4XN.
E-mail: [email protected]
Published online 2 August 2011 in Wiley Online Library
(wileyonlinelibrary.com).
DOI 10.1002/ajmg.b.31216
� 2011 Wiley-Liss, Inc. 764
Neuropsychiatric Genetics
INTRODUCTION
Alzheimer’s disease (AD) is themost common form of dementia; it
is genetically complex and shows heritability up to 79% [Gatz et al.,
2006]. Until recently the Apolipoprotein E (APOE) gene, was the
only unequivocal susceptibility gene for late-onset Alzheimer’s
disease [Saunders et al., 1993]. We recently published a genome-
wide association study (GWAS) of Alzheimer’s disease which
identified two new genome-wide significant susceptibility loci:
clusterin (CLU: P¼ 8.5� 10�10) and phosphatidylinositol-binding
clathrin assembly protein gene (PICALM: P¼ 1.3� 10�9) [Harold
et al., 2009]. Subsequent publications have supported these find-
ings, and have produced further evidence for additional loci such as
complement receptor 1 (CR1) [Lambert et al., 2009], bridging
integrator 1 (BIN1) [Seshadri et al., 2010], ATP-binding cassette,
sub-family A, member 7 (ABCA7) [Hollingworth et al., 2011], the
membrane-spanning 4-domains, subfamily A (MS4A) gene cluster
onchromosome11 [Hollingworth et al., 2011;Naj et al., 2011],CD2
associated protein (CD2AP) [Hollingworth et al., 2011; Naj et al.,
2011], ephrin receptor precursor (EPHA1) [Seshadri et al., 2010;
Hollingworth et al., 2011; Naj et al., 2011], and CD33 antigen
precursor (CD33) [Hollingworth et al., 2011; Naj et al., 2011].
However, to date the loci identified to associate with AD at the
genome-wide level only explain roughly 32% of the genetic risk for
AD. Extended runs of homozygosity (ROHs) have been shown to
occur at a high frequency in the human genome [Gibson et al., 2006;
Lencz et al., 2007;McQuillan et al., 2008] andmay account for some
of the unexplained heritability. These runs most likely denote
extended homozygosity inherited from a common ancestor [Li
et al., 2006],with the longest tracts expected tooccur inmore closely
related individuals where little recombination has occurred
[Gibson et al., 2006]. Although initially thought of as a marker
of consanguinity, ROHshave recently been shown tobe common in
outbred populations [Gibson et al., 2006; McQuillan et al., 2008;
Simon-Sanchez et al., 2007]. Homozygosity mapping assumes that
affected individuals co-inherit two copies of the disease allele froma
common ancestor, and that such regions can be identified by
stretches of genetic markers that are homozygous by descent.
Unrelated affected individuals will harbour many different homo-
zygous regions across their genomes, but will share the same
homozygous region that harbours the disease loci. The role of
these ROHs has historically been overlooked in complex disease.
However, the advent of whole genome single nucleotide polymor-
phism (SNP) assay technology has provided a powerful tool to
investigate the presence of homozygous segments in case-control
samples [Lencz et al., 2007]. To date, ROHs have been shown to
associate with neurological conditions such as schizophrenia
[Lencz et al., 2007], Parkinson’s disease [Wang et al., 2009] and
AD [Farrer et al., 2003; Nalls et al., 2009a; Liu et al., 2009]. For
example, Lencz and colleagues successfully identified an excess
burden of ROHs in schizophrenic cases compared with controls
(P¼ 0.009), and identified nine individual regions that contained
ROHs at a significantly greater frequency in cases [Lencz et al.,
2007]. Interestingly, three of these regions contained genes previ-
ously found to associate with schizophrenia. Four previous studies
have reportedROHs inAD[Clarim�onet al., 2009; Farrer et al., 2003;Nalls et al., 2009a; Liu et al., 2009]. The first study was conducted in
an isolated, highly inbred population with a high incidence of
disease assuming a dominant mode of inheritance [Farrer et al.,
2003]. One study catalogued the homozygous genomic regions of
an inbred pedigree where two siblings suffered from early onset AD
[Clarim�on et al., 2009]. While, another study identified ROHs that
spanned less than 1Mb [Liu et al., 2009]. A potential issue with
analysing GWAS data for ROHs is that a stretch of homozygosity
could be a hemizygous deletion and not a true homozygous tract. It
has been suggested that the effect of copy number variations
(CNVs) on a homozygosity mapping study can be greatly reduced
by setting a large minimum length of a homozygous genomic
region, typically a minimum run of homozygosity (ROH) length
of 1Mb is used [Farrer et al., 2003;Nalls et al., 2009a; Liu et al., 2009;
Nalls et al., 2009b].Nalls and colleagues [Nalls et al., 2009a]used the
publically available translational genomics research institute
(TGen) GWAS dataset [Reiman et al., 2007] to investigate
ROHs greater than 1Mb in a population of 837 late-onset AD
cases and 550 controls genotyped for 311,970 SNPs using the
Affymetrix 500 k GeneChip array. The study failed to identify an
overall excess burden of ROHs in cases, but did identify one ROH
on chromosome 8 (37,835,460-38,143,780) (NCBI36/hg18) which
was significantly overrepresented in cases when compared to con-
trols after correction for multiple testing (P¼ 0.017, OR¼ 3.02)
[Nalls et al., 2009a].
Using data generated from our AD GWAS we describe here a
statistical comparison of ROHs greater than 1Mb in a UK and
Ireland series of 1,955 AD patients and 955 elderly screened con-
trols, genotypedon the Illumina610-quadarray.Wealso attempt to
replicate the finding of Nalls and colleagues [Nalls et al., 2009a] by
analysing the ROHs on chromosome 8 in this dataset.
METHODS
Sample Ascertainment and Diagnostic CriteriaThe GERAD1 sample has been extensively described elsewhere
[Harold et al., 2009]. Analyses were restricted to those samples
How to Cite this Article:Sims R, Dwyer S, Harold D, Gerrish A,
Hollingworth P, Chapman J, Jones N,
AbrahamR, IvanovD,Pahwa JS,MoskvinaV,
Dowzell K, Thomas C, Stretton A, Lovestone
S, Powell J, Proitsi P, Lupton MK, Brayne C,
Rubinsztein DC, Gill M, Lawlor B, Lynch A,
Morgan K, Brown KS, Passmore PA, Craig D,
McGuiness B, Todd S, Johnston JA, Holmes
C, Mann D, Smith AD, Love S, Kehoe PG,
Hardy J,Mead S, FoxN, RossorM, Collinge J,
Livingston G, Bass NJ, Gurling H, McQuillin
A, Jones L, Holmans PA, O’Donovan M,
OwenMJ,Williams J. 2011. No Evidence that
Extended Tracts of Homozygosity are
Associated with Alzheimer’s Disease.
Am J Med Genet Part B 156:764–771.
SIMS ET AL. 765
with UK/Irish ancestry who were genotyped on the 610 chip. AD
cases with age-at-onset less than 60 years were excluded from the
analyses. There were 1,955 AD cases and 955 elderly screened
controls of UK or Irish origin which passed our stringent quality
control measures. Demographics of the sample can be seen in
Table 1. 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 UK (ARUK) Collabo-
ration (University of Nottingham; University of Manchester; Uni-
versity of Southampton; University of Bristol; Queen’s University
Belfast; the Oxford Project to Investigate Memory and Ageing
(OPTIMA), Oxford University); London and the South East
Region AD project (LASER-AD), University College London.
AD cases met criteria for either probable (NINCDS-ADRDA
[McKhann et al., 1984], DSM-IV) or definite (CERAD [Mirra
et al., 1991]) AD. Controls were screened for dementia using
the MMSE or ADAS-cog, and were determined to be free from
dementia at neuropathological examination or had a Braak score of
2.5 or lower.
Genotyping and Quality ControlAll samples were genotyped at the Sanger Institute on the Illumina
610-quad chip and passed the quality control measures applied
[Harold et al., 2009]. Stringent quality controls (QC) filters were
applied to remove poorly performing samples and SNPs using tools
implemented in PLINK v1.05 (http://pngu.mgh.harvard.edu/
�purcell/plink) [Purcell et al., 2007] as previously described
[Harold et al., 2009]. Briefly, we excluded individuals with missing
genotype rates >0.01; with inconsistencies between reported gen-
der and genotype-determined gender or ambiguous genotype-
determined gender, or who appeared to have non-European
ancestry. We also examined genetic relatedness and only retained
one of each pair of individuals with an identity-by-descent estimate
�0.125 (the level expected forfirst cousins).Markerswere excluded
if they had a minor allele frequency (MAF)< 0.01 or a Hardy-
Weinberg Equilibrium P� 1� 10�5, in either cases or controls.
SNPs with a MAF� 0.05 were excluded if they had a genotype
missing rate of >0.03 in either cases or controls; for SNPs with a
MAFbetween 0.01 and 0.05, amore stringent genotypemissing rate
threshold of 0.01 was employed. After quality control 1,955 cases,
955 elderly screened controls and 529,205 autosomal markers
remained. Additional data generated/utilised by our AD GWAS
were not included in this study due to inter-chip and population
stratification differences that could not be accounted for in our
analyses.
Identification of Runs of HomozygosityROHs analysis was performed using PLINK v1.07 [Purcell et al.,
2007]. In linewith previousROHs studies usingGWASdata, ROHs
that spanned a minimum of 1Mb [Lencz et al., 2007; Nalls et al.,
2009a; Vine et al., 2009; Curtis et al., 2008] and having at least 100
consecutive SNPs [Lencz et al., 2007; Vine et al., 2009] receiving a
homozygous call were identified, allowing amaximumof 2missing
data points per 50 SNP window [Nalls et al., 2009a].
Burden AnalysisThe burden of ROHs in cases and controls was defined as the
number of ROHs per person using PLINK v1.07 [Purcell et al.,
2007]. The burden analysis was also stratified by size and the case-
control ratio was determined by dividing the rate in the cases by the
rate in the controls. The overall burden of ROHs in the sample was
assessed by a 1-tailed test based upon 10,000 permutations under
TABLE 1. Summary Descriptive of the Case and Control Sample Used in This Study
Geographical region TOTALMRC ART UCL LASER
UK/Ireland UK UKAD cases
n, total 2342 1219 1070 53n, passed QC 1955 1007 901 47% female 66.6 70.4 61.9 74.5% neuropathological confirmed 3.1 0 6.8 0Mean age at onset 75.1 75.7 73.9b n/aMean age at assessment 80.2 80.9 79.1 80.6Mean age at deatha 83.4 n/a 83.4 n/a
Eldery screened controlsn, total 1165 1044 121 n/an, passed QC 955 873 82 n/a% female 62.0 62.0 59.8 n/a% neuropathological confirmed 2.0 0 23.2 n/aMean age at assessment 75.5 75.9 76.7 n/aMean age at deatha 81.6 n/a 81.6 n/a
aOnly available for neuropathological samples.bAge at Onset only available for a proportion of the sample.
766 AMERICAN JOURNAL OF MEDICAL GENETICS PART B
the prior hypothesis that ROHs of interest would bemore frequent
in cases compared to controls.
Given our sample size we have 80% power to detect an associa-
tion at P¼ 1� 10�6 provided a mean increase of at least one ROH
per case.
Homozygosity MappingConsensus regions of overlapping ROHs were defined where
homozygous loci in at least two individuals overlapped by a
minimum of 100 kb and included at least 3 SNPs. These consensus
regions were then split into those where more than 1% of all
individuals harboured a ROH (common) and those where less
than 1% of all individuals harboured a ROH (rare). Individual loci
were then tested for association using PLINK v1.07 [Purcell et al.,
2007] using empirical P-values generated for single point analysis
and genome-wide analyses (1-tailed).We investigated whether any
ROHs overlapped the known AD susceptibility genes. ROHs were
defined as overlapping a known AD susceptibility gene if they
spanned either the gene region� 20 kb, or where the extent of
linkage disequilibrium extended beyond 20 kb the gene region plus
the block of linkage disequilibrium. For theMS4A gene cluster the
chromosome 11 region; 59,570,863-59,861,775 (UCSC NCBI36/
hg18 freeze) was investigated. The number of ROHs in cases and
controls at the chromosome 8 locus, previously found to be
associated with AD [Nalls et al., 2009a], was also evaluated in
the full dataset by generating empirical P-values (1-tailed). ROHs
were defined if they spanned at least 50% of the consensus region
identified by Nalls and colleagues [Nalls et al., 2009a], in line with
previous regional analyses of CNV studies [Chapman et al., 2011;
Kirov, 2010].
RESULTS
ROHs Burden AnalysisA total of 63,204 ROHs were identified. There was no significant
difference in the proportion of individuals with at least 1 ROH, in
the amount of the genome covered by ROHs, nor in the average
ROH size between cases and controls (Table 2). Burden analysis
revealed no significant difference in the number of ROHs per
person between cases and controls for ROHs greater than 1Mb
or when the data was stratified by size (Table 3).
Homozygosity MappingA total of 252 consensus regions harbouring common ROHs were
identified. No region was significantly associated with disease after
correction for multiple testing (Table 4). A total of 11 regions were
nominally associated with AD (P< 0.05).
A total of 818 consensus regions harbouring rare ROHs were
identified, similarly to the common consensus analysis, none
were significantly associated with disease after correction for
multiple testing (Table 5). A total of 11 regions were nominally
associated with AD (P< 0.05).
Known AD Susceptibility GenesROHs at the known AD susceptibility genes APP, PSEN1, PSEN2,
MAPT, APOE, CLU, PICALM,CR1, BIN1, ABCA7, theMS4A gene
cluster, EPHA1,CD33 andCD2AP, did not show any association to
AD in this dataset (Table 6).
Associated ROHs RegionThe chromosome 8 region found to be associated with AD in a
previous study [Nalls et al., 2009a] did not show any association in
TABLE 2. Summary of all Identified ROHs Characteristics
(minimum ROHs size 1 Mb)
Cases Controls P valueTotal number ROHs 42417 20787 –Proportion of sample� 1 ROH 21.7 21.77 0.66Rate of ROHs per individual 1 1 1Total size of ROHs (kb) 32070 32020 0.45Average size of ROH (kb) 1476 1469 0.14
TABLE 3. ROHs Burden Analysis Stratified by Size. P values Given as 1-sided Empirical P values after 10,000 Permutations
Size of ROH Test Cases Controls Case/Control ratio P value�l Mb ROH(n) 42417 20787 – –
ROH burden per person 21.7 21.77 1.00 0.66�2Mb ROH(n) 4670 2272 – –
ROH burden per person 2.39 2.38 1.00 0.44�3Mb ROH(n) 1163 568 – –
ROH burden per person 0.59 0.59 1.00 0.51�4Mb ROH(n) 420 198 – –
ROH burden per person 0.21 0.21 1.04 0.37�5Mb ROH(n) 199 91 – –
ROH burden per person 0.10 0.10 1.07 0.35
SIMS ET AL. 767
this dataset (Table 7). The frequency of ROHs in the original study
was 4% in the overall sample (5% in cases and 2% in controls).
However in this studyROHsat this locus areonly seen in0.2%of the
overall sample (0.3% cases and 0.1% controls), with ROHs identi-
fied in five cases and one control.
DISCUSSION
Extended ROHs greater than 1Mb in length have been shown to be
commonwithin outbred populations [Gibson et al., 2006;McQuil-
lan et al., 2008; Simon-Sanchez et al., 2007]. Analysis of ROHsusing
GWASdata has previouslyproved fruitful in identifying evidence of
associationwithneurodevelopmental disease such as schizophrenia
[Lencz et al., 2007], and neurodegenerative disease including AD
[Nalls et al., 2009a]. The advantage of thismethodology is its ability
to identify rare recessive variants through the identification of
haplotypes which carry deleterious mutations. Here we attempted
to use ROHs mapping to identify possible candidate loci for late-
onset AD. Using SNP data from 1,955 AD cases and 955 elderly
screened controls, genotyped as part of our GERAD1 GWAS, we
identified an average of 21.74 homozygous runs per individual
larger than 1Mb containing more than 100 consecutive SNPs. We
foundno evidence for an increased rate ofROHs in individualswith
AD compared with controls, nor an increase in the number of
individuals harbouring at least one ROH (Table 2). There was also
no significant difference in the proportion of the genome that is
homozygous, with the total and average size of each ROH not
differing between cases and controls (Table 2). These findings were
confirmed by the burden analysis which revealed no significant
difference in the number of ROHs per person between cases and
controls (Table 3). Overall, the results suggest that our AD popu-
lation is no more consanguineous than age-matched screened
controls.
Specific loci that harbour excess ROHs in cases may reveal
haplotypes that contain recessive deleteriousmutations. Therefore,
we aimed to identify consensus regions harbouring both common
and rare ROHs. No common or rare ROHs were significantly
associated with disease after correction for multiple testing
(Tables 4 and 5). Whether ROHs in cases encompass more genes
than those in controls was not investigated in this study, however as
the minimum size of ROHs was set at 1Mb, the vast majority of all
ROHs would intersect genes. ROHs at the knownAD susceptibility
genes did not show any association with AD (Table 6).
The chromosome 8 locus where ROHs have previously been
found to associate with AD [Nalls et al., 2009a] was investigated in
this dataset. This analysiswasperformedusing allROHsdata,with a
minimum 50% overlap of any identified ROHs and the associated
region. We failed to replicate the original finding; moreover in this
study ROHs in this region are only seen in 0.2% of the overall
sample comparedwith 4% in the original study [Nalls et al., 2009a].
There are a number of possible explanations for our failure to
replicate. The initial study used a publically available dataset from a
Caucasian population of Northern European ancestry from the
USA and the Netherlands, whereas, our sample consists of a
Caucasian population from the UK and Ireland. A recent study
has shown that genomic regions where ROHs occur can differ
TABLE 4. Table of Consensus Regions Harbouring Common ROHs Over-Represented in Cases
Region ID Chr SNP1 SNP2 BP1 BP2 Size (kb) nSNP
ROH counts Frequency
Emp1 Emp2Cases Controls Cases Controls
ROH_6090 9 rs10491806 rs10992463 94324033 94581596 257.56 16 86 26 0.044 0.027 0.017 0.87
ROH_3126 21 rs2243503 rs2832194 29234932 29416121 181.19 21 126 44 0.064 0.046 0.025 0.985
ROH_22142 4 rs924234 rs13105102 144847402 144959649 112.25 11 27 5 0.014 0.005 0.026 0.955
ROH_10342 7 rs10487300 rs10487306 110466164 110612703 146.54 30 38 9 0.019 0.009 0.028 0.98
ROH_24153 5 rs4916875 rs825395 91123834 91284916 161.08 20 9 0 0.005 0 0.028 0.945
ROH_19344 3 rs16831996 rs13324292 122154702 122498514 343.81 25 19 3 0.010 0.003 0.036 0.991
ROH_19343 3 rs17678695 rs555890 122623786 122754748 130.96 16 19 3 0.010 0.003 0.036 0.991
ROH_2 4 rs16989258 rs10017188 33574446 33733979 159.53 9 676 298 0.346 0.312 0.036 0.998
ROH_1 4 rs13143386 rs7660253 33786427 33948197 161.77 18 676 298 0.346 0.312 0.037 0.998
ROH_13096 9 rs10971712 rs307682 33810938 33963324 152.39 17 35 9 0.018 0.009 0.049 0.999
ROH_2218 17 rs17222691 rs3809724 54126095 54416020 289.93 19 165 63 0.084 0.066 0.049 0.999
ROH_21531 13 rs17281193 rs985035 83040366 83160898 120.53 26 11 1 0.006 0.001 0.056 0.998
ROH_18017 18 rs2127958 rs11660313 16907608 18059212 1151.60 99 23 5 0.012 0.005 0.064 1
ROH_1673 19 rs4802066 rs241951 42801141 42962003 160.86 11 197 79 0.101 0.083 0.07 1
ROH_14238 2 rs16845742 rs6738264 161835280 161948500 113.22 18 37 11 0.019 0.012 0.087 1
ROH_25477 5 rs7703201 rs7710769 91637248 91857453 220.21 15 6 0 0.003 0 0.09 1
ROH_5815 1 rs1556562 rs1337107 92806611 92991364 184.75 13 78 28 0.040 0.029 0.093 1
ROH_20384 1 rs2152318 rs17278862 177560134 177936708 376.57 83 6 0 0.003 0 0.094 1
ROH_20042 1 rs1148821 rs12121845 178062128 178334611 272.48 34 6 0 0.003 0 0.094 1
Listed are all regions associated with Alzheimer’s disease P< 0.1 (uncorrected for multiple testing). The size of the consensus region is shown in Size (kb) columnwith the number of SNPs included in theregion shown as nSNP. Emp1 is the empirical single point P value whilst Emp2 is the global P value. Positions are according to UCSC NCBI36/hg18 freeze.
768 AMERICAN JOURNAL OF MEDICAL GENETICS PART B
TABLE 5. Table of Consensus Regions Harbouring Rare ROHs Over-Represented in Cases
Region ID Chr SNP1 SNP2 BP1 BP2 Size (kb) nSNP
ROH counts Frequency
Emp1 Emp2Cases Controls Cases Controls
ROH_33184 16 rs251633 rs9923303 15387380 15795631 408.25 58 18 1 0.009 0.001 0.006 0.29
ROH_29826 11 rs10890985 rs1347910 108733615 108862269 128.65 13 21 2 0.011 0.002 0.008 0.41
ROH_31694 16 rs7179 rs4985124 14897345 15032942 135.60 3 19 2 0.010 0.002 0.013 0.74
ROH_32511 13 rs976100 rs11619622 41193142 41468201 275.06 39 18 2 0.009 0.002 0.022 0.90
ROH_41599 12 rs8192593 rs3741659 52187372 52395926 208.55 36 9 0 0.005 0 0.027 0.97
ROH_33641 4 rs1397470 rs713435 67142556 67276720 134.16 11 13 1 0.007 0.001 0.03 0.98
ROH_33817 1 rs2998164 rs6678578 168505039 168815179 310.14 49 16 2 0.008 0.002 0.036 1
ROH_34738 14 rs9743995 rs11622835 102792001 103037257 245.26 39 12 1 0.006 0.001 0.04 1
ROH_41434 18 rs269985 rs2612578 41039995 41223475 183.48 34 8 0 0.004 0 0.041 1
ROH_43285 2 rs16859684 rs748615 13108727 13250777 142.05 20 8 0 0.004 0 0.043 1
ROH_34896 9 rs10817168 rs1556027 113114526 113375366 260.84 28 15 2 0.008 0.002 0.048 1
ROH_39533 1 rs3851932 rs12749684 83418941 83580250 161.31 15 11 1 0.006 0.001 0.06 1
ROH_41844 7 rs6467230 rs2735842 128533241 128633705 100.46 14 7 0 0.004 0 0.063 1
ROH_43506 15 rs2415029 rs11853067 66949549 67709250 759.70 115 7 0 0.004 0 0.064 1
ROH_38550 2 rs2579612 rs11673874 119988253 120787281 799.03 68 10 1 0.005 0.001 0.078 1
ROH_38551 2 rs1545360 rs6711847 119743369 119891525 148.16 28 10 1 0.005 0.001 0.078 1
ROH_35184 4 rs1436 rs2942543 66724850 66920041 195.19 28 10 1 0.005 0.001 0.081 1
ROH_35743 8 rs12680797 rs17826587 24515385 24690133 174.75 38 13 2 0.007 0.002 0.087 1
ROH_44898 9 rs1932165 rs13284305 104013447 104174876 161.43 57 6 0 0.003 0 0.09 1
ROH_44073 5 rs9293744 rs344656 77672779 77927783 255.00 36 6 0 0.003 0 0.09 1
ROH_37877 18 rs4643412 rs4513176 25810800 26073661 262.86 43 6 0 0.003 0 0.092 1
ROH_41880 7 rs10262259 rs7793296 51922768 52213803 291.04 65 6 0 0.003 0 0.092 1
ROH_45287 3 rs1869998 rs6771516 149286040 149426293 140.25 15 6 0 0.003 0 0.093 1
ROH_31843 11 rs2186643 rs12798333 63634650 63769360 134.71 22 6 0 0.003 0 0.093 1
ROH_41998 5 rs1559085 rs2549779 96104458 96242143 137.69 59 6 0 0.003 0 0.095 1
ROH_44593 15 rs1435395 rs12899101 86169088 86628576 459.49 119 6 0 0.003 0 0.096 1
Listed are all regions associated with Alzheimer’s disease P< 0.1 (uncorrected for multiple testing). The size of the consensus region is shown in Size (kb) columnwith the number of SNPs included in theregion shown as nSNP. Emp1 is the empirical single point P value whilst Emp2 is the global P value. Positions are according to UCSC NCBI36/hg18 freeze.
TABLE 6. Results of ROHs Analysis for the Known AD Susceptibility Genes
Gene Chr BP1 BP2
ROH counts Frequency
P valueCases Controls Cases ControlsCLU 8 27490368 27548244 3 0 0.002 0 0.31CD2AP 6 47500502 47817026 10 3 0.005 0.003 0.34PSEN1 14 72652932 72776862 16 6 0.008 0.006 0.39PSEN2 1 225104896 225170427 33 14 0.017 0.015 0.40EPHA1 7 142778328 142836107 13 6 0.007 0.006 0.57CD33 19 56400147 56455086 1 0 0.001 0 0.68CR1 1 205716096 205901733 16 8 0.008 0.008 1BIN1 2 127490350 127631085 8 5 0.004 0.005 1MS4A 11 59570863 59861775 14 7 0.007 0.007 1PICALM 11 85302286 85547592 48 26 0.025 0.027 1ABCA7 19 971102 1036570 0 0 0 0 1APOE 19 50080879 50124490 1 2 0.001 0.002 1APP 21 26154732 26485003 0 5 0.005 0.005 1MAPT 17 41307544 41481546 74 41 0.038 0.043 1
Positions are according to UCSC NCBI36/hg18 freeze.
SIMS ET AL. 769
significantly between different Caucasian populations with the
ROHs from 249 outbred Scottish individuals overlapping only
43% of all common ROHs indentified in a Caucasion population
of 322 from Long Island, New York [McQuillan et al., 2008]. Other
possible explanations for the difference in the findings include: 1)
the genotyping platform used. The original study’s genotyping was
performed on the Affymetrix 5.0 GeneChip array, while our dataset
was genotyped on the Illumina 610-quad chip. Only 62,939 SNPs
overlap between the TGen dataset [Reiman et al., 2007] used by
Nalls and colleagues [Nalls et al., 2009a] and our own dataset.
Nalls and colleagues have a maximum of eight SNPs within
the chromosome 8 consensus region while we have fourteen. 2)
the methodology used to identify ROHs. In the original study the
minimumnumber of SNPsper homozygous runwas set at 50,while
in this studywe defined a region to contain a homozygous run if the
locus contained a minimum of 100 SNPs.
A caveat of this study is that CNVs may be included in the
analysis, despite the analysis of only those ROHs greater than
1 Mb. One ROHs study has sought to investigate the effect of
CNVs on their findings [McQuillan et al., 2008]. The removal
of any CNVs overlapping with ROHs revealed no significant
difference compared to the results prior to the removal of
deletions, reducing the total mean length of ROHs in their
sample by less than 0.3% [McQuillan et al., 2008]. Also, analysis
of our GWAS data, including the 1,955 AD cases and 955
controls used in this study, identified a total of 23 rare deletions
greater than 1 Mb [Chapman et al., 2011]. This compares to
63,204 ROHs detected in this study meaning that the effect of
CNVs on the results of this study should beminimal. Other caveats
of this study include not LD pruning the GWAS data to obtain an
independent set of SNPs, and setting a low SNP minor allele
frequency (MAF) of 1%. By setting a higher MAF and LD pruning
the dataset we would have minimised the probability of ROHs
being homozygous by chance, however, this may have introduced
type II errors.
In summary, we find that while ROHs are common in our
outbred population, statistically theseROHs are not a risk factor for
late-onset AD in our dataset. However, it is possible that future
sequencing may identify deletorious variations significantly asso-
ciated with AD which are missed by genome-wide genotyping
platforms.
Author ContributionsJ.W. directed this study, assisted byM.J.O.,M.O.D., R.S.,D.H., and
J. Chapman. R.S. took primary responsibility for drafting the
manuscript assisted by S.D., J.Chapman, D.H., A.G., J.W., L.J.,
P.A.H., M.O.D., and M.J.O. All authors contributed to the sample
collection, sample preparation, genotyping and/or conduct of the
GWASuponwhich this study is based. J.W.,R.A., P.H., R.S.,A.G., J.
Chapman, K.D., N.J., A.S., C.T., S. Lovestone, J.P., P.P., M.K.L.,
C.B.,D.C.R.,M.G., B.L., A.L., K.M., K.S.B., P.A.P., D.C., B.M., S.T.,
C.H., D.M., A.D.S., S. Love, P.G.K., J.H., S.M., N.C.F., M.R.,
J. Collinge, G.L., N.J.B., H.G., and A.M., contributed towards
clinical sample collection, ascertainment, diagnosis and prepara-
tion of samples. D.H. completed statistical quality control. R.S.
produced association statistics, under the supervision ofD.H., S.D.,
J.W., and P.A.H. All authors discussed the results and approved the
manuscript.
ACKNOWLEDGMENTS
We thank the individuals and families who took part in this
research. Cardiff University was supported by theWellcome Trust,
Medical Research Council (MRC, UK), Alzheimer’s Research UK
(ARUK) and the Welsh Assembly Government. ARUK supported
sample collections at the Institute of Psychiatry, the South West
Dementia Bank and the Universities of Cambridge, Nottingham,
Manchester and Belfast. The Belfast group acknowledges support
from the Alzheimer’s Society, Ulster Garden Villages, Northern
Ireland Research and Development Office and the Royal College of
Physicians–Dunhill Medical Trust. The MRC and Mercer’s Insti-
tute for Research on Ageing supported the Trinity College group.
The SouthWest Dementia Brain Bank acknowledges support from
BristolResearch intoAlzheimer’s andCareof theElderly.D.C.R. is a
Wellcome Trust Senior Clinical Research Fellow. London and the
South East Region (LASER)-AD was funded by Lundbeck.
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