Copy Number Variation in Familial Parkinson Disease
Nathan Pankratz1*, Alexandra Dumitriu2, Kurt N. Hetrick3, Mei Sun4,5, Jeanne C. Latourelle2, Jemma B.
Wilk2, Cheryl Halter1, Kimberly F. Doheny3, James F. Gusella4,6, William C. Nichols7,8, Richard H. Myers2,
Tatiana Foroud1, Anita L. DeStefano2,9, the PSG–PROGENI and GenePD Investigators, Coordinators and
Molecular Genetic Laboratories
1Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America, 2Department of Neurology,
Boston University School of Medicine, Boston, Massachusetts, United States of America, 3Center for Inherited Disease Research (CIDR), Institute of Genetic Medicine,
Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America, 4Center for Human Genetic Research, Massachusetts General Hospital,
Boston, Massachusetts, United States of America, 5Department of Neurology, Harvard Medical School, Boston, Massachusetts, United States of America, 6Department of
Genetics, Harvard Medical School, Boston, Massachusetts, United States of America, 7Division of Human Genetics, Cincinnati Children’s Hospital Medical Center,
Cincinnati, Ohio, United States of America, 8Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America,
9Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
Copy number variants (CNVs) are known to cause Mendelian forms of Parkinson disease (PD), most notably in SNCA and
PARK2. PARK2 has a recessive mode of inheritance; however, recent evidence demonstrates that a single CNV in PARK2 (but
not a single missense mutation) may increase risk for PD. We recently performed a genome-wide association study for PD
that excluded individuals known to have either a LRRK2 mutation or two PARK2 mutations. Data from the Illumina370Duo
arrays were re-clustered using only white individuals with high quality intensity data, and CNV calls were made using two
algorithms, PennCNV and QuantiSNP. After quality assessment, the final sample included 816 cases and 856 controls. Results
varied between the two CNV calling algorithms for many regions, including the PARK2 locus (genome-wide p=0.04 for
PennCNV and p=0.13 for QuantiSNP). However, there was consistent evidence with both algorithms for two novel genes,
USP32 and DOCK5 (empirical, genome-wide p-values,0.001). PARK2 CNVs tended to be larger, and all instances that were
molecularly tested were validated. In contrast, the CNVs in both novel loci were smaller and failed to replicate using real-
time PCR, MLPA, and gel electrophoresis. The DOCK5 variation is more akin to a VNTR than a typical CNV and the association
is likely caused by artifact due to DNA source. DNA for all the cases was derived from whole blood, while the DNA for all
controls was derived from lymphoblast cell lines. The USP32 locus contains many SNPs with low minor allele frequency
leading to a loss of heterozygosity that may have been spuriously interpreted by the CNV calling algorithms as support for a
deletion. Thus, only the CNVs within the PARK2 locus could be molecularly validated and associated with PD susceptibility.
Citation: Pankratz N, Dumitriu A, Hetrick KN, Sun M, Latourelle JC, et al. (2011) Copy Number Variation in Familial Parkinson Disease. PLoS ONE 6(8): e20988.
Editor: Roland G. Roberts, Public Library of Science, United Kingdom
Received August 27, 2010; Accepted May 17, 2011; Published August 2, 2011
Copyright: ? 2011 Pankratz et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This project was supported by R01 NS37167, R01 NS036711, the Robert P. & Judith N. Goldberg Foundation, the Bumpus Foundation and the Harvard
NeuroDiscovery Center. This study used samples from the NINDS Human Genetics Resource Center DNA and Cell Line Repository (http://ccr.coriell.org/ninds), as
well as clinical data. DNA samples contributed by the Parkinson Institute - Istituti Clinici di Perfezionamento, Milan, Italy were from the ‘‘Human genetic bank of
patients affected by PD and parkinsonisms’’, supported by Italian Telethon grant n. GTB07001 and by the ‘‘Fondazione Grigioni per il Morbo di Parkinson’’.
Genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the National
Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096C. The funders had no role in study design, data collection and analysis,
decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: email@example.com
Copy number variants (CNVs), defined as structural changes in
DNA consisting of deletions or duplications of segments larger
than 1 kb compared to a reference genome , have been shown
to be a disease producing mechanism in disorders such as
Charcot–Marie–Tooth neuropathy, as well as a risk factor in some
common, complex disorders such as schizophrenia and autism
[2,3,4,5]. The sizes of CNVs are quite variable. Some deletions
and duplications span large physical distances encompassing
several genes, while others span only a limited portion of a gene
or no known gene at all.
Parkinson disease (PD) is the second most common neurode-
generative disorder affecting approximately 500,000 Americans.
The genetic etiology of PD is complex, although mutations in five
genes have been identified that lead to either an autosomal
dominant or an autosomal recessive form of the disease .
Detailed analyses of these genes have identified a variety of disease
producing mutations, including point mutations, exon duplications
and deletions, as well as entire gene duplications and triplications.
These findings suggest that CNVs, a term that includes exon or
gene duplications or deletions, are an important disease mecha-
nism contributing to PD pathogenesis.
Mutations in PARK2, the gene that encodes Parkin, are typically
considered to act in an autosomal recessive fashion, with only
those individuals having a mutation on both chromosomes
developing PD. However, multiple reports have suggested that
haploinsufficiency of PARK2 may increase the risk of PD
PLoS ONE | www.plosone.org1 August 2011 | Volume 6 | Issue 8 | e20988
[7,8,9,10]. We have recently shown that PARK2 haploinsuffi-
ciency, specifically for a dosage mutation rather than a point
mutation or small insertion/deletion, is a risk factor for familial PD
and may be associated with earlier age of onset . These data
suggest a broader mechanism in which CNVs may play a role as a
risk factor, increasing the likelihood an individual will develop PD.
In the present study, we replicate in an independent dataset the
association of a single dosage mutation in PARK2 with an
increased risk of PD. This replication provides a positive control
with which to compare different CNV filtering criteria as well as
different genome-wide analysis strategies that can be used to
explore the role of CNVs in a sample of familial PD cases and
neurologically examined controls.
The final sample included 816 cases and 856 controls (Table 1).
Controls tended to be younger than the cases and were more likely
to be female. No control sample had a family history of PD. Whole
blood was the DNA source for all of the cases, while lymphoblast
cell lines (LCLs) was the DNA source for all controls.
The Illumina HumanCNV370 array provided intensity data for
370,404 probes. Illumina’s BeadStudio software transformed the
signal intensity data for these probes into Log R ratio (LRR) and B
allele frequency (BAF) measures that could be used to generate
CNV calls by PennCNV  and QuantiSNP . Due to the
limitations of these CNV calling algorithms, 1,357 markers
(0.37%) within regions of known instability (telomeres, centro-
meres and immunoglobulin regions, boundaries previously
delineated by Need et al. ) were excluded from analysis. An
additional 1,165 autosomal markers (0.31%) demonstrated a
gender-specific pattern indicative of hybridization to a sex
chromosome in addition to, or instead of, the target locus (see
Figure 1) and were similarly removed. CNV calls generated when
including gender-linked markers were compared to those calls
generated when excluding such markers. Exclusion of these
markers resulted in the removal of approximately 1% of identified
CNVs, which were presumably spurious. New deletions and
duplications were also called (an additional 1% of calls) after
excluding the gender-linked markers, indicating that some of these
excluded markers had shown evidence of copy number equal to
two. By removing gender-linked markers that were presumably
showing evidence of two copies, these new deletions and
duplications were then called. The final number of markers used
for CNV detection was 367,882.
Whole chromosomal arm mosaicism was detected by analyzing
the BAF distribution of each chromosomal arm of each individual.
There were 44 chromosomal arms from 35 samples (13 cases, 22
controls) that were flagged as outliers and demonstrated evidence
of mosaicism (Figures 2 and 3), generally for a majority of the
length of the chromosomal arm. While these regions had distinct
BAF patterns indicating mosaicism (i.e. deletions with BAF
values .0 and BAF values ,1), LRR values were not always
significantly increased or decreased, in which case the CNV calling
algorithm did not flag the region as a CNV. Those that were not
called tended to have a lower percentage of mosaicism (BAF
heterozygote bands closer together) and generally included only
one breakpoint (i.e. encompassed the telomere). Those mosaics in
which CNVs were called, frequently had two breakpoints (i.e. did
not encompass a telomere), yielding large chromosomal rear-
rangements, similar to those seen in recent reports on schizophre-
nia [4,5]. These included 3 PD cases with deletions (chr2q/6Mb/
onset=50, chr5q/11Mb/onset=72, chr6q/7Mb/onset=75) and
1 PD case with a duplication (chr21q/10Mb/onset=30). All four
of these PD cases showed evidence of mosaicism (see Figure 2). All
mosaics called as CNVs by PennCNV or QuantiSNP were
excluded from analyses (7 cases, 9 controls; 19 arms; 3 controls
had two mosaic arms).
Previously, an increased risk of PD was found for those having a
single PARK2 dosage mutation . We attempted to replicate this
association using only those samples that are independent of the
discovery set of Pankratz et al. . The replication set used in our
current analyses included 66 PROGENI cases, all 330 GenePD
cases and the 846 Coriell controls. We excluded three individuals
harboring PARK2 CNVs on both alleles (compound heterozy-
gotes). Single CNVs were identified in 10 of the 396 independent
cases and 8 of the 856 controls, yielding an odds ratio of 2.7
Of the ten cases in which CNVs were identified, two had
already been molecularly tested for PARK2 mutations and found to
be heterozygous for an exonic deletion . The two samples
molecularly tested were from the GenePD study and were
independent from the discovery set. Combined with the seven
PROGENI samples from the current GWAS study that
overlapped with the previous study of PARK2 haploinsufficiency
, a total of nine out of nine molecularly tested samples (100%)
replicated with regard to copy number (deletion versus duplica-
tion). The breakpoints were not always precise, which was
presumably due to variation in LRR values and the relatively
sparse marker set. For example, a duplication of exons 5–8 that
was verified using both MLPA and quantitative PCR was called as
a duplication of exons 4–6 by PennCNV. A deletion defined
molecularly as spanning only exon 2 was called as spanning both
exons 2 and 3 by PennCNV. Of note, two mutations that included
exon 2 were called by PennCNV as being restricted to intron 2.
PennCNV called 22,685 CNVs that had a confidence value of 10
or higher and that spanned at least 5 SNPs. Of these, 2,195 (9.8%)
met the Conservative criteria ($20 probes, $100 kb) and 20,073
(88.5%) met the Common criteria ($5 probes and contain at least
one SNP/CNV probe that was observed to be deleted or duplicated
Table 1. Sample demographics.
PD Cases (n=816) Controls
PROGENIGenePD NINDS Coriell Repository
Average age at onset (cases) or at enrollment (controls)62.1610.461.4611.6 54.8613.1
% Male 60.3% 57.8%40.1%
% with parent reported to have PD36.0%23.9%0%
CNVs in Familial PD
PLoS ONE | www.plosone.org2August 2011 | Volume 6 | Issue 8 | e20988
in our dataset 3 or more times). The intersection of the two filters
contained 1,883 CNVs and the union contained 20,385 CNVs.
There were 312 calls meeting the Conservative criteria that were
restricted to regions where only one or two individuals contained
variants and thus failed the Common criteria. There were 2,300
CNV calls (10.1%) that did not meet the criteria for either the
Conservative or Common approach and were not analyzed in the
union set. Of these, 1,568 contained 5–9 markers (avg. size 36 kb),
498 contained 10–14 markers (avg. size 71 kb), 199 contained 15–19
markers (avg. size 110 kb), and 35 with more than 20 markers (but
less than 100 kb; avg. size 79 kb).The Gene-centric approach, which
takes the union of the two other approaches and identifies the subset
that overlaps a portion of at least one RefSeq gene, contained 8,746
CNVs or 42.9% of those possible.
Genome-wide analyses of locus-specific CNV associations were
performed using CNV calls from two different algorithms
(PennCNV and QuantiSNP) and using two different methods
(position and 400 kb windows). Multiple comparisons were
corrected within each analysis via permutation testing. To control
for multiple testing across approaches, a conservative (given the
correlation between the various permutations) Bonferroni correc-
tion of 0.0125 was applied to reach study-wide significance.
PennCNV showed a trend at the PARK2 locus (p=0.04; Figure
S1A) that was not significant after correcting for multiple tests.
Only when analyzed using the Conservative criteria (CNVs
spanning at least 100 kb and 20 markers) and 400 kb windows was
the finding genome-wide significant (p=0.007; see Table S1).
QuantiSNP did not show strong evidence of association for PARK2
using any filtering criteria (p=0.08–0.16). Other regions were
similarly discordant between the two calling algorithms (chr1q,
chr4q, chr5q, chr8p; see Table 2). Only two regions yielded
consistent, genome-wide, and study-wide significant findings
(p,0.0001). Each region contained a single gene: DOCK5 and
USP32 (see Table 2). The CNVs in USP32 were exclusively single
deletions (copy number equal to 1) and were identified in 30 cases
and 8 controls, yielding an odds ratio of 4.0 (Figure S1B). In
contrast, the CNVs in DOCK5 were quite common and included
both deletions and duplications, with copy numbers ranging
between 1 and 3 (Figure S1C). Upon further examination, all
CNV calls in DOCK5 overlapped the same 6 monomorphic CNV
probes in intron 1. When the chromosome was reanalyzed without
these 6 probes, the minority of CNV calls that extended beyond
these markers were not called.
All CNV calls for the USP32 locus overlapped either intron 2 or
exon 2 (see Figure S1B). We therefore designed sets of probes to
capture each of these regions and repeated each region twice to
molecularly validate the CNV calls using real time PCR. In
replicate 1, nine cases with PennCNV deletion calls were
compared to two cases without deletions calls. In replicate 2, the
same nine cases were compared to two cases that not only lacked
deletion calls, but had LRR values near zero across all markers in
the region. In each set of results, the quantity of DNA for each
sample was compared to the mean quantity of the two controls.
Proportions less than 0.80 were flagged as possible deletions and
proportions above 1.20 were flagged as possible duplications.
Results were consistent between the two replicates, with one case
yielding a proportion below the lower limit (mean proportion
across replicates=0.74 for both probes) and one case yielding a
proportion above the upper limit (mean proportion=1.57 for both
probes). Therefore, 89% of the USP32 deletions calls failed to
replicate molecularly using real time PCR.
We also used MLPA as an alternate validation method. Six
samples with and fifteen samples without a PennCNV deletion call
in the USP32 gene (Figure 4) were investigated. No deletion was
detected in any tested sample. All samples yielded similar results
consistent with a copy number of two at all probes targeting the
USP32 gene. The probeson the X chromosome showed onecopyin
male individuals, indicating that the assay worked appropriately.
Analysis of the underlying sequence of the DOCK5 region (See
Figure S2) and of the primer sequences of the 6 probes consistently
Figure 1. Scatter plots of raw probe intensities. A. A good marker, with three distinct clusters and males and females equally distributed in each
cluster; B. Complete co-hybridization to sex chromosome, where all females are called as homozygotes and all males are called as heterozygotes; C. A
monomorphic marker (i.e. a CNV probe) exhibiting partial co-hybridization to a sex chromosome, such that individuals cluster by gender, but mean
Log R ratios do not differ by gender (p=0.49); D. Polymorphic SNP exhibiting partial hybridization to a sex chromosome, where multiple distinct
groups separated by gender.
Figure 2. Plots of large chromosomal rearrangements. Sample A harbors a large duplication with the region indicated by a blue bar (average
Log R ratio is increased, and B allele frequency (BAF; proportion of alleles estimated to be the B allele) match the 4 expected proportions of 0.0=AAA,
0.33=AAB, 0.66=ABB, 1.0=BBB). Sample B harbors a large deletion with the region indicated by a purple bar (decreased Log R ratio, with no
heterozygotes (BAF=0.50)); however, since BAF are not limited to values of 0 and 1, the deletion appears to be mosaic.
CNVs in Familial PD
PLoS ONE | www.plosone.org3August 2011 | Volume 6 | Issue 8 | e20988
deleted and duplicated revealed that the probes capture variable
numbers of a tandem repeat (VNTR) and not the larger deletions
and duplications that are normally included in the definition of a
CNV. The 32-base pair repeats are found in three forms that vary
at only two base pair positions. The reference genome contains 13
copies of form A, 2 copies of form B, and 13 copies of form C (See
Figure S2). Three of these probes are nested, redundant probes for
form A, and the others are nested, redundant probes for form C.
The region containing the VNTR were amplified and separated
by size using gel electrophoresis. Summed allele size (estimated
number of 32 bp repeats for each allele added together) was not
significantly different between samples with a PennCNV deletion
call and a PennCNV duplication call (p=0.69) or with mean LRR
across the 6 monomorphic DOCK5 probes (p=0.99). A shorter
allele with a size around 960 bp (see Figure 5) was noted in 8
subjects; however, this allele was seen in individuals without a
PennCNV deletion call and was seen in equal frequencies in the
52 cases and 43 controls that were genotyped.
Despite the increase in the study of CNVs as a potential disease
risk factor, there is still no consensus on the best approach for the
detection or analysis of CNVs. A prior genome-wide study of CNV
in Parkinson disease using a relatively small sample (273 cases and
275 controls) and visual inspection of LRR and BAF to identify
CNVs, found CNVs within PARK2 in both cases and controls. A
single locus for which CNVs were identified in multiple cases but
not in controls could not be validated by molecular analysis .
Here, we present the results of the first systematic genome-wide
analysis of CNVs for PD using CNV calling algorithms. We
replicated the association of PD susceptibility with PARK2 CNVs
in an independent sample. In addition, we detected CNVs in two
novel genes, DOCK5 and USP32, associated with an increase in
risk for PD at genome-wide significance. However, neither of these
novel loci could be validated with independent molecular tests.
The DOCK5 probes capture a VNTR, and all of the current
Illumina arrays with enhanced copy number probes (370-Duo,
660W-Quad, 1M-Duo, Omni) have the same six CNV probes for
this region. A recent study of CNVs in the Wellcome Trust Case
Control Consortium datasets found artifacts between samples with
Figure 3. Detecting mosaicism. Gray dot=normal Log R ratio (LRR)
and B allele frequency (BAF) distributions; Green dot=mosaic pattern
with a significant enough deviation in mean LRR to be called as a CNV –
such chromosomal arms were removed from analyses; Purple
dot=mosaic pattern without significant LRR deviation – the CNV
calling algorithms did not call these as CNVs; Blue dot=faint mosaics –
not called; Red dot=multiple distinct mosaicism events – chromosomal
arms removed from analyses; Black dot=normal LRR and BAF
distributions – the reason they are outliers is unknown; Pink dot=no
mosaicism pattern, but very noisy – all of these samples had already
been flagged as having unacceptably high LRR standard deviations and
had already been removed from analyses.
Table 2. Results (p-values) for regions with an empirical genome-wide p-value,0.20 for any test.
Union Gene-centric UnionGene-centric
chr1:173049146–17307895085 kb fromP0.17 0.10 1.001.00
PAPPA2W 0.130.071.00 1.00
chr4:71528873–71716513 overlappingP 1.00 1.000.170.12
ENAMW 1.00 1.000.020.01
chr5:151389412–151513092105 kb fromP 0.021.00 0.65 1.00
chr6:162471089–162677104 withinP 0.83 0.640.91 0.79
PARK2W 0.040.02 0.13 0.08
chr8:7575048–7575048 geneP 1.001.00 1.001.00
desertW 0.230.13 1.000.99
DOCK5W 0.00010.00010.0001 0.0001
DLG2W0.200.11 0.02 0.009
chr17:55581582–55809920 withinP 0.00060.0005 0.00070.0002
Those p-values in bold are significant both genome-wide and study-wide.
1Tests were either based on a specific position (P) or based on a 400 kb Window (W).
CNVs in Familial PD
PLoS ONE | www.plosone.org4August 2011 | Volume 6 | Issue 8 | e20988
DNA isolated from LCLs versus samples isolated from whole
blood , particularly at probes tagging regions with known
VNTRs. Because all cases in this study were obtained from whole
blood and all controls were from LCLs, this is likely the reason for
the spurious association at the DOCK5 region.
The finding of USP32 (encoding Ubiquitin-specific protease 32)
was particularly intriguing because it plays a role in the ubiquitin
proteasome system (UPS) that also includes the gene product of
PARK2 (Parkin). However, the USP32 finding also failed to
replicate using either real-time PCR or MLPA. Visualizing the
LRR and BAF values for these regions revealed that most
individuals (with or without a PennCNV call) had BAF values
exclusively at 0 and 1 across this region, which is consistent with a
deletion call. However, this phenomenon was due to a series of
nine SNPs with low minor allele frequencies (MAF,0.05) that
were in tight LD with one another (r2.0.75). Since both
PennCNV and QuantiSNP use BAF values in their calculations
(without comparing allele frequencies or BAF distributions across
individuals), this is one possible explanation why so many deletions
were called in this region, as the frequency of the haplotype
containing the minor allele of all nine SNPs was 0% in those
assigned a deletion call in USP32, compared to 4.1% in the rest of
the sample. However, while the frequency was lower in cases
(3.9%) than it was in controls (4.2%), the difference was not
significant and thus not sufficient to explain why CNV calls were
made more often for cases than for controls. It is possible that
DNA source may have played a role at this locus as well.
Duplications and triplications of SNCA are a well-documented
cause of PD . One case in the present study was identified as
harboring a 3 Mb duplication that contained SNCA as well as 36
other genes (age of onset=44). One additional case (age of
onset=69) was found to be mosaic for a duplication containing
80% of chromosome 4q (including SNCA), and was therefore
excluded from analyses. However, since it is unknown if this
mosaicism is present in the relevant brain regions, we cannot infer
whether or not this duplication is disease causing. No CNVs were
observed in or around PARK6 (PINK1), PARK7 (DJ1), PARK8
(LRRK2) or PARK9 (ATP13A2).
Both of the CNV calling algorithms generated CNVs in USP32
and DOCK5 that were significantly associated with disease.
However, across the genome QuantiSNP, on average, generated
both a higher number of CNVs per person and larger CNVs per
person. Upon manual inspection of LRR plots, QuantiSNP would
frequently call deletions in locations where a small proportion of
markers actually had LRR values above 0, which would normally
indicate a copy number of two, trending towards a copy number of
three. This indicates a lower threshold for calling a CNV and
would explain both the higher frequency and the longer average
length of the CNV calls. While this may lead to fewer false
negatives, it may also lead to more false positives. Conservative
CNV calls in the PARK2 region were significantly associated with
disease when called by PennCNV (genome-wide empirical
p=0.007) but not when called by QuantiSNP (p=0.16).
As described above, multiple filters were used to improve the
quality of CNV calls. In retrospect, the Conservative approach
(.100 kb and $20 markers) had the lowest false positive rate,
since it did not flag DOCK5 or USP32, and the highest power to
detect PARK2, a true positive, at genome-wide significance.
Figure 4. MLPA of USP32 exons. A two color overlay shows a representation of the capillary electrophoresis peak profiles from one sample with a
PennCNV deletion call (shown in red) and one sample without a PennCNV deletion call (shown green) in the USP32 region. Internal control probes are
also indicated. Every probe in the sample presented a normal amplification pattern, suggesting normal dosage for both copies of USP32.
CNVs in Familial PD
PLoS ONE | www.plosone.org5 August 2011 | Volume 6 | Issue 8 | e20988
However, no new CNV associations were detected with the
Conservative criteria. Aside from PARK2, the smallest nominal p-
value observed using the Conservative filter was MACROD2
(nominal p=0.047; genome-wide p=0.98; see Text S1 for more
detail). The Conservative approach also fails to detect nearly all of
the known copy number polymorphisms, which tend to be much
smaller. It also ignores most of the monomorphic probes
specifically added to the 370 Duo and more recent chips to
identify copy number variation, since very few of these regions are
tagged by more than 20 of these markers. Therefore, we also
considered CNVs that overlapped a marker that was reported as
deleted or duplicated three or more times.
Strengths of this study include the exclusive use of familial PD,
which is likely to have a greater genetic contribution and,
therefore, greater power to detect association than idiopathic
PD. In addition, careful quality assessment was performed for the
samples analyzed for CNVs, the markers used in the CNV calling
algorithms, and the filters applied to the CNVs that were called.
Limitations of the study include the relatively sparse marker set on
the Illumina 370Duo compared to newer arrays and the
stratification of DNA source by affection status.
In summary, we have detected association of PD with CNVs in
PARK2 at genome-wide significance, but failed to detect any
additional loci that could be molecularly validated. Our
experience indicates that CNV calls spanning only 5 SNPs should
be met with skepticism. Furthermore, researchers should be wary
of CNV probes meant to tag VNTRs (as opposed to traditional
deletions and duplications), especially if cases and controls come
from different DNA sources. Finally, more work needs to be done
to investigate whether regions with several markers with low minor
allele frequency may lead to spurious deletions calls in algorithms
such as PennCNV and QuantiSNP.
Sample and Genotyping
A genome-wide case control association design was employed
to identify genes contributing to PD susceptibility . All PD
cases had a positive family history of disease and were
ascertained as part of two ongoing studies of familial PD:
PROGENI and GenePD (see Table 1 for demographic
information). All cases completed a uniform neurological
evaluation that employed PD diagnostic criteria based upon a
modified version of the United Kingdom PD Society Brain Bank
Criteria . Whole blood was the DNA source for all PD cases.
Control samples were obtained from LCLs from the NINDS
Human Genetics Resource Center DNA and Cell Line
Repository (Camden, NJ). All control samples were reported to
be white, non-Hispanic. Appropriate written informed consent
was obtained for all samples included in this study. This study
was approved by both the Institutional Review Board of Boston
Institutional Review Board.
Genotyping was performed by the Center for Inherited
Disease Research (CIDR) using the Illumina HumanCNV370
version1_C BeadChips (Illumina, San Diego, CA, USA) and
the Illumina Infinium II assay protocol . Intensity data
were collected for 23,573 probes specifically designed to detect
copy number variation. Detailed review of the data was
performed to assess the quality of the samples . All samples
analyzed in the GWAS were considered for inclusion in the
CNV analyses (857 familial PD cases and 867 controls). Those
samples with high quality intensity data were used as the
reference samples when the data was reclustered (see Text S1
for more detail).
All cases were known to be negative for the LRRK2 G2019S
mutation, and many, but not all, were also screened for mutations
in PARK1 (SNCA; n=702 screened), PARK2 (parkin; n=593),
[9,10,11,19,20,21,22,23,24]. All PD cases with a LRRK2 G2019S
mutation as well as those known to have a mutation in both of
their copies of PARK2 were excluded as potential cases, since these
mutations were believed to be sufficient to cause disease. However,
PD cases with a mutation in only one of their two PARK2 genes
were included, since there was not definitive evidence that a single
PARK2 mutation was sufficient to cause disease. No mutations
were found in those screened for SNCA, DJ1, or NR4A2.
andthe Indiana University
Marker filtering criteria
Due to the limitations of CNV calling algorithms, markers
within regions of known instability (telomeres, centromeres and
immunoglobulin regions, boundaries previously delineated by
Need et al. ) were excluded from analysis. In addition, multiple
criteria were used to identify markers demonstrating evidence of
hybridization to chromosomal regions other than the target locus
(see Figure 1B–D). Predicting gender using allele frequency
differences or mean LRR values were helpful, but not sufficient in
identifying all gender linked makers. Ultimately, three logistic
regression models were used to predict gender. Each regression
model contained two independent variables, which were found to
be more sensitive than testing each of the variables separately
(diagonal separation in two-dimensional space). The three sets of
two independent variables for these models were: 1) normalized
probe intensity pairs, X and Y, 2) R and Theta, and 3) BAF and
Figure 5. Gel electrophoresis of DOCK5 VNTR. This image of 16
samples is representative of all 95 samples run. PennCNV calls are listed
for each sample (normal, deletion, duplication). The mean Log R ratio
for the 6 monomorphic CNV probes in DOCK5 is listed in parentheses. A
few lanes showed evidence of a third band, assumed to be
heteroduplexes of the two alleles. Estimated number of copies of the
32 bp repeat did not correlate with PennCNV calls or with mean Log R
ratio. The finding is likely a result of artifact due to DNA source (blood
CNVs in Familial PD
PLoS ONE | www.plosone.org6 August 2011 | Volume 6 | Issue 8 | e20988
LRR. Markers were removed if the minimum p-value, for any of
the six variables considered, across the three models exceeded
genome-wide significance (p-value,2.261028; based on 370,404
markers and 6 variables). All gender-linked markers were
removed from the final analyses.
Detection of whole chromosomal arm mosaicism
CNVs that span the entire arm of a chromosome have been
detected. Typically, these are the result of somatic loss or gain and
often exhibit a mosaic pattern, with some cells containing a normal
karyotype. The loss of an entire chromosomal arm is frequently an
artifact of the lymphoblast immortalization process, which is
relevant since all controls were from LCLs, and all the cases were
from whole blood; however, in our sample, mosaicism was
frequently seen in DNA derived from whole blood. To detect
whole chromosomal arm mosaicism, each arm of each chromo-
some of each individual was analyzed separately. As described in
Text S1, true germ line deletions will exhibit B alleles only near 0
and 1 (two bands) and duplications will yield four equidistant
bands. If a sample exhibits a mosaic pattern, then a deletion will
yield four bands (See Figure 2B), and a duplication will have the
middle two bands closer to the midline. Chromosomal arms
demonstrating evidence of mosaicism were identified by taking all
BAF values between 0.15 and 0.85 and plotting the standard
deviation of these BAF values on the X axis and the interquartile
range (IQR) of these same values on the Y axis (Figure 3). Outliers
were inspected visually by plotting all LRR and BAF values for the
chromosome of the individual in question (as seen in Figures 2A
and 2B). To eliminate possible bias, all samples demonstrating
evidence of mosaicism for called CNVs were removed from
further analysis (n=16).
CNV calling algorithms
There is currently no consensus regarding the best algorithm to
call CNVs. Therefore, two frequently used CNV calling
algorithms were employed, PennCNV  and QuantiSNP
, and we have compared results from these two algorithms in
our dataset. Commonly used parameters and thresholds for these
programs were used to filter the samples down to the final dataset
of 816 cases and 856 controls (see Text S1 for more detail).
CNV filtering criteria
Two complementary filtering approaches were applied to
minimize false positive CNV calls. The first approach, which we
refer to as Conservative, focused on large CNVs that were greater
than 100 kb and spanned at least 20 markers. Similar to previous
studies , we also employed a second approach, which focused
on common CNVs (Common approach). Less stringent criteria
were applied for this Common approach, because, by definition,
they occur at loci already identified as copy number variable
regions or appear in multiple individuals within a study. Common
CNVs were required to span at least 5 SNPs and to contain at least
one SNP/CNV probe that was observed to be deleted or
duplicated in our dataset 3 or more times. We analyzed the union
of these two sets filtering criteria (see Text S1 for a comparison of
the results of each filtering criteria).
We then performed secondary analyses that limited our analyses
to those CNVs that overlapped a portion of at least one RefSeq
gene (Gene-centric approach). We did not require the CNVs to
specifically overlap an exon, since deletions molecularly confirmed
to span an exon could be called by PennCNV as having
boundaries that are exclusively intronic due to the relatively
sparse marker set employed in the current study.
Replication of the PARK2 locus
Those samples that did not overlap with the previous study of
PARK2 haploinsufficiency  were included in a replication
sample. This included 66 cases from the PROGENI study, 330
cases from the GenePD study, and all 856 controls. CNVs that
passed all filtering criteria and overlapped any portion of PARK2
(chr6:161,688,579–163,068,824) were considered (Gene-centric
CNV definition). Those individuals found to have two hitherto
unknown PARK2 mutations (compound heterozygotes) were not
included in the analysis (n=3). Fisher’s exact test, using 1 df, was
used to determine if cases were more likely than controls to harbor
a single PARK2 CNV. While samples that overlapped with the
prior study of haploinsufficiency were not included in the PARK2
replication analysis, they were used to verify that the CNV calling
algorithms were able to properly call a molecularly validated
Genome-wide association strategies
To test the hypothesis that particular CNVs would be found at
increased frequency in PD cases as compared with controls (one-
sided Fisher’s exact test with significance determined via permuta-
tion), we performed two analyses using PLINK . We first tested
genome-wide whether the presence of a CNV at a particular
position was found more frequently in cases versus controls. We
then defined 400 kb windows across the genome (200 kb up- and
down-stream from every marker) and tested whether the total
number of CNVs within a given window was more common in PD
cases than in controls. These tests were performed for each of the
CNV definitions and empirical, genome-wide p-values were
generated by permuting affection status.
We sought to molecularly validate large statistically significant
deletions and duplications identified in USP32 and PARK2 using
both real-time PCR and multiplex ligation-dependent probe
amplification (MLPA). Applied Biosystems’ Assay by Design
service was used to design fam-labeled TaqMan gene expression
assays for targeted regions. Genomic DNA samples were
quantitated by Pico Green fluorescence in triplicate with the
Quant-iT PicoGreen dsDNA Kit (Molecular Probes, Eugene,
OR). After quantitation, 50 ng of genomic DNA was used in a
real-time absolute quantitation assay for the region in question,
performed on the 7300 Real Time PCR System (Applied
Biosystems) as previously described .
We used MLPA as a second approach to molecularly validate
the inferred large CNVs. A custom assay with 11 probes was
designed to capture exons 2, 3, 5, 12, and 13 of USP32 and intron
2 of USP32, as well as probes on other chromosomes to serve as
controls. The MLPA assay was performed as described previously
[10,11]. Peak height and area were then compared between
samples with and without a PennCNV deletion call. Values
between 0.8 and 1.2 were considered normal.
We also sought to molecularly validate the length of the 32 bp
repeats identified in DOCK5. PCR products obtained by
amplification using primers designed to flank the CNV (sequences
available on request) were molecularly assessed by gel electropho-
resis. After electrophoresis through 1% agarose in 16 TBE,
products were visualized by ethidium bromide staining and UV
light. Gels were run with a 100 bp ladder at a low voltage (40 V)
for an extended period (24 hours) to ensure optimal separation of
the PCR products and then photographed. The resulting PCR
products were sized by comparing the coordinates of the pixel at
the center of the PCR band and coordinates of the two nearest
bands on the 100 bp ladder. Length (in base pairs) was assigned in
CNVs in Familial PD
PLoS ONE | www.plosone.org7 August 2011 | Volume 6 | Issue 8 | e20988
proportion to the distance to the vertical positions of these
reference bands. The number of 32-mer repeats was then
calculated by subtracting the number of base pairs between the
primers and the repeated sequence and dividing by 32. Summed
allele size was then compared between samples with deletion calls
and duplication calls using Student’s t-test.
USP32 (B), and DOCK5 (C). Red=Deletion in a case;
Pink=Duplication in a case; Dark green=Deletion in a
control; Light Green=Duplication in a control; Red followed
by 610 means that ten cases harbored a deletion with the exact
same breakpoints; all CNVs displayed in Panel C overlap the same
six monomorphic CNV probes (the smallest CNV, deleted670 in
cases and 636 in controls); the small arrows in the gene figure
indicate direction, the large arrows indicate that not all of the gene
is displayed, and the bars indicate exons.
Visualization of CNVs within PARK2 (A),
primers for the probes in that region.
Sequence for the DOCK5 region and for the
for regions with an empirical genome-wide p-value ,0.20 for any
Comparison of genome-wide results across CNV filters
Additional Methods and Results.
We particularly thank Justin Paschall from the NCBI dbGaP staff for his
assistance in developing the dataset available at dbGaP. The data
generated from this case control study are available at http://www.ncbi.
nlm.nih.gov/sites/entrez?db=gap through dbGaP accession number:
The following are members of the PROGENI Steering Committee.
University of Tennessee Health Science Center: R. F. Pfeiffer; University
of Rochester: F. Marshall, D. Oakes, A. Rudolph, A. Shinaman; Columbia
University Medical Center: K. Marder; Indiana University School of
Medicine: P.M. Conneally, T. Foroud, C. Halter; University of Kansas
Medical Center: K. Lyons; Eli Lilly & Company: E. Siemers; Medical
College of Ohio: L. Elmers; University of California, Irvine: N.
The following are members of the GenePD Steering Committee.
University of Virginia Health System: G.F. Wooten; UMDNJ-Robert
Wood Johnson Medical School: L. Golbe; Center for Human Genetic
Research, Massachusetts General Hospital, Harvard Medical School: J.F.
Gusella; Boston University School of Medicine: R.H. Myers.
We thank the subjects for their participation in this research study.
PSG-PROGENI Investigators and Coordinators: Albany Med-
ical College: S Factor, D Higgins, S Evans; Barrow Neurological Institute:
H Shill, M Stacy, J Danielson, L Marlor, K Williamson; Baylor College of
Medicine: J Jankovic, C Hunter; Beth Israel Deaconess Medical Center: D
Simon, P Ryan, L Scollins; Beth Israel Medical Center: R Saunders-
Pullman, K Boyar, C Costan-Toth, E Ohmann; Brigham & Women’s
Hospital: L Sudarsky, C Joubert; Brown University (Memorial Hospital of
RI): J Friedman, K Chou, H Fernandez, M Lannon; Cleveland Clinic
Florida-Weston: N Galvez-Jimenez, A Podichetty, K Thompson; Clinical
Neuroscience Center: P Lewitt, M DeAngelis; Colorado Neurological
Institute: C O’Brien, L Seeberger, C Dingmann, D Judd; Columbia
University Medical Center: K Marder, J Fraser, J Harris; Creighton
University: J Bertoni, C Peterson; Evanston Northwestern Healthcare: M
Rezak, G Medalle; Hotel-Dieu Hospital-Chum: S Chouinard, M Panisset,
J Hall, H Poiffaut; Hunter Homes McGuire Veterans Medical Center: V
Calabrese, P Roberge; Indiana University School of Medicine: J
Wojcieszek, J Belden; Institute For Neurodegenerative Disorders: D
Jennings, K Marek, S Mendick; Johns Hopkins University: S Reich, B
Dunlop; London Health Sciences Centre: M Jog, C Horn; Mayo Clinic
Jacksonville: R Uitti, M Turk; McFarland Neurosciences: T Ajax, J
Mannetter; Medical College of Georgia: K Sethi, J Carpenter, B Dill, L
Hatch, K Ligon, S Narayan; Medical College of Wisconsin: K Blindauer,
K Abou-Samra, J Petit; Medical University of Ohio: L Elmer, E Aiken, K
Davis, C Schell, S Wilson; Mount Sinai School of Medicine: M Velickovic,
W Koller (deceased), S Phipps; North Shore-LIJ Health System: A Feigin,
M Gordon, J Hamann, E Licari, M Marotta-Kollarus, B Shannon, R
Winnick; Northwestern University: T Simuni, A Videnovic, A Kaczmarek,
K Williams, M Wolff; Ochsner Clinic Foundation: J Rao, M Cook; Ohio
State University: M Fernandez, S Kostyk, J Hubble, A Campbell, C
Reider, A Seward; Oregon Health & Science University: R Camicioli, J
Carter, J Nutt, P Andrews, S Morehouse, C Stone; Ottawa Hospital Civic
Site: T Mendis, D Grimes, C Alcorn-Costa, P Gray, K Haas, J Vendette;
Pacific Neuroscience Medical Group: J Sutton, B Hutchinson, J Young;
Saskatoon Dist Health Board Royal Univ Hosp: A Rajput, A Rajput, L
Klassen, T Shirley; Scott & White Hospital/Texas A&M University: B
Manyam, P Simpson, J Whetteckey, B Wulbrecht; The Parkinson’s &
Movement Disorder Institute: D Truong, M Pathak, K Frei, N Luong, T
Tra, A Tran, J Vo; Toronto Western Hospital, University Health: A Lang,
G Kleiner-Fisman, A Nieves, L Johnston, J So; UMDNJ-School of
Osteopathic Medicine: G Podskalny, L Giffin; University of Alabama at
Birmingham: P Atchison, C Allen; University of Alberta: W Martin, M
Wieler; University of Calgary: O Suchowersky, S Furtado, M Klimek;
University of California Irvine: N Hermanowicz, S Niswonger; University
of California San Diego: C Shults (deceased), D Fontaine; University of
California San Francisco: M Aminoff, C Christine, M Diminno, J Hevezi;
University of Chicago: A Dalvi, U Kang, J Richman, S Uy, J Young;
University of Cincinnati: A Dalvi, A Sahay, M Gartner, D Schwieterman;
University of Colorado Health Sciences Center: D Hall, M Leehey, S
Culver, T Derian; University of Connecticut: T Demarcaida, S Thurlow;
University of Iowa: R Rodnitzky, J Dobson; University of Kansas Medical
Center: K Lyons, R Pahwa, T Gales, S Thomas; University of Maryland
School of Medicine: L Shulman, S Reich, W Weiner, K Dustin; University
of Miami: K Lyons, C Singer, W Koller (deceased), W Weiner, L Zelaya;
University of Minnesota: P Tuite, V Hagen, S Rolandelli, R Schacherer, J
Kosowicz; University of New Mexico: P Gordon, J Werner; University of
Puerto Rico School of Medicine: C Serrano, S Roque; University of
Rochester: R Kurlan, D Berry, I Gardiner; University of South Florida: R
Hauser, J Sanchez-Ramos, T Zesiewicz, H Delgado, K Price, P Rodriguez,
S Wolfrath; University of Tennessee Health Science Center: R Pfeiffer, L
Davis, B Pfeiffer; University of Texas Southwestern Medical Center: R
Dewey, B Hayward, A Johnson, M Meacham, B Estes; Wake Forest
University School of Medicine: F Walker, V Hunt, C O’Neill; Washington
University: B Racette, L Good, M Rundle.
PROGENI Molecular Genetic Laboratory: Division of Human
Genetics, Cincinnati Children’s Hospital Medical Center: William C.
Nichols, Michael W. Pauciulo, Diane K. Kissell.
GenePD Investigators and Coordinators: University Southern
California School of Medicine: M. Lew; University of Calgary: O.
Suchowersky; University of Lu ¨beck, Germany: C. Klein; UMDNJ-Robert
Wood Johnson Medical School: L. Golbe, M.H. Mark; Massachusetts
General Hospital, Harvard Medical School: J. Growdon, N. Huggins;
University of Virginia Health System: G.F. Wooten; University of Alabama
at Birmingham : R. Watts; University of Toronto: M. Guttman;
Washington University School of Medicine: B. Racette, J. Perlmutter;
Barrow Neurological Institute: L. Marlor, Sun Health Research Institute:
H. Shill; University of Miami: C. Singer; Parkinson Institute, Istituti Clinici
di Perfezionamento, Milano, Italy: S. Goldwurm, G. Pezzoli; Boston
University School of Medicine: M.H. Saint-Hilaire, T. Massood; Cleveland
Clinic Foundation: K. Baker, I. Itin; University of Louisville School of
Medicine: I. Litvan; University of Sydney ANZAC Research Institute,
Concord Hospital, Sydney, Australia: G. Nicholson, A. Corbett; Struthers
Parkinson’s Center, Minneapolis: M. Nance; Port City Neurology,
Scarborough, ME: E. Drasby; Parkinson’s Disease and Movement
Disorder Center of Boca Raton: S. Isaacson; Newcastle University,
Newcastle upon Tyne, UK: D. Burn, P. Chinnery; General Regional
Hospital Bolzano, Bolzano, Italy: P. Pramstaller; University of Arkansas for
Medical Sciences: J. Al-hinti; Aarhus University Hospital, Aarhus,
Denmark: A. Moller, K. Ostergaard; University of Arizona: S. Sherman;
Auckland City Hospital, Auckland, New Zealand: R. Roxburgh, B. Snow;
University of Kentucky College of Medicine: J. Slevin, F. Cambi.
CNVs in Familial PD
PLoS ONE | www.plosone.org8August 2011 | Volume 6 | Issue 8 | e20988
GenePD Molecular Genetics Laboratories: Center for Human
Genetic Research, Massachusetts General Hospital, Harvard Medical
School: J.F. Gusella, M.E. MacDonald, M. Sun, L. Mysore, M.A,
Anderson, D. Lucente; Neurogenetics Laboratory, Boston University
School of Medicine: S. Williamson, M.W. Nagle, R.H. Myers.
Conceived and designed the experiments: NP AD KNH MS JFG JL JBW
RHM TF ALD. Performed the experiments: NP AD KNH MS KFD JFG
WCN ALD. Analyzed the data: NP AD JL JBW KNH ALD. Contributed
reagents/materials/analysis tools: KNH KFD CH WCN JFG. Wrote the
paper: NP AD KNH MS JL JBW CH KFD JFG WCN RHM TF ALD.
Take responsibility for the PSG-PROGENI Investigators, Coordinators
and Molecular Genetic Laboratories: NP WCN TF. Take responsibility for
the GenePD Investigators, Coordinators and Molecular Genetic Labora-
tories: JFG RHM ALD.
1. Feuk L, Carson AR, Scherer SW (2006) Structural variation in the human
genome. Nat Rev Genet 7: 85–97.
2. Sebat J, Lakshmi B, Malhotra D, Troge J, Lese-Martin C, et al. (2007) Strong
association of de novo copy number mutations with autism. Science 316:
3. Stefansson H, Ophoff RA, Steinberg S, Andreassen OA, Cichon S, et al. (2009)
Common variants conferring risk of schizophrenia. Nature 460: 744–747.
4. Need AC, Ge D, Weale ME, Maia J, Feng S, et al. (2009) A genome-wide
investigation of SNPs and CNVs in schizophrenia. PLoS Genet 5: e1000373.
5. Walsh T, McClellan JM, McCarthy SE, Addington AM, Pierce SB, et al. (2008)
Rare structural variants disrupt multiple genes in neurodevelopmental pathways
in schizophrenia. Science 320: 539–543.
6. Pankratz N, Foroud T (2007) Genetics of Parkinson disease. Genet Med 9:
7. Klein C, Pramstaller PP, Kis B, Page CC, Kann M, et al. (2000) Parkin deletions
in a family with adult-onset, tremor-dominant parkinsonism: expanding the
phenotype. Ann Neurol 48: 65–71.
8. Farrer M, Chan P, Chen R, Tan L, Lincoln S, et al. (2001) Lewy bodies and
parkinsonism in families with parkin mutations. Ann Neurol 50: 293–300.
9. Foroud T, Uniacke SK, Liu L, Pankratz N, Rudolph A, et al. (2003)
Heterozygosity for a mutation in the parkin gene leads to later onset Parkinson
disease. Neurology 60: 796–801.
10. Sun M, Latourelle JC, Wooten GF, Lew MF, Klein C, et al. (2006) Influence of
heterozygosity for parkin mutation on onset age in familial Parkinson disease: the
GenePD study. Arch Neurol 63: 826–832.
11. Pankratz N, Kissell DK, Pauciulo MW, Halter CA, Rudolph A, et al. (2009)
Parkin dosage mutations have greater pathogenicity in familial PD than simple
sequence mutations. Neurology 73: 279–286.
12. Wang K, Li M, Hadley D, Liu R, Glessner J, et al. (2007) PennCNV: an
integrated hidden Markov model designed for high-resolution copy number
variation detection in whole-genome SNP genotyping data. Genome Res 17:
13. Colella S, Yau C, Taylor JM, Mirza G, Butler H, et al. (2007) QuantiSNP: an
Objective Bayes Hidden-Markov Model to detect and accurately map copy
number variation using SNP genotyping data. Nucleic Acids Res 35: 2013–2025.
14. Simon-Sanchez J, Scholz S, Matarin Mdel M, Fung HC, Hernandez D, et al.
(2008) Genomewide SNP assay reveals mutations underlying Parkinson disease.
Hum Mutat 29: 315–322.
15. Craddock N, Hurles ME, Cardin N, Pearson RD, Plagnol V, et al. Genome-
wide association study of CNVs in 16,000 cases of eight common diseases and
3,000 shared controls. Nature 464: 713–720.
16. Pankratz N, Wilk JB, Latourelle JC, Destefano AL, Halter C, et al. (2009)
Genomewide association study for susceptibility genes contributing to familial
Parkinson disease. Hum Genet 124: 593–605.
17. Gibb WR, Lees AJ (1988) The relevance of the Lewy body to the pathogenesis of
idiopathic Parkinson’s disease. J Neurol Neurosurg Psychiatry 51: 745–752.
18. Gunderson KL, Steemers FJ, Ren H, Ng P, Zhou L, et al. (2006) Whole-genome
genotyping. Methods Enzymol 410: 359–376.
19. Karamohamed S, Golbe LI, Mark MH, Lazzarini AM, Suchowersky O, et al.
(2005) Absence of previously reported variants in the SCNA (G88C and
G209A), NR4A2 (T291D and T245G) and the DJ-1 (T497C) genes in familial
Parkinson’s disease from the GenePD study. Mov Disord 20: 1188–1191.
20. Nichols WC, Elsaesser VE, Pankratz N, Pauciulo MW, Marek DK, et al. (2007)
LRRK2 mutation analysis in Parkinson disease families with evidence of linkage
to PARK8. Neurology 69: 1737–1744.
21. Nichols WC, Uniacke SK, Pankratz N, Reed T, Simon DK, et al. (2004)
Evaluation of the role of Nurr1 in a large sample of familial Parkinson’s disease.
Mov Disord 19: 649–655.
22. Pankratz N, Pauciulo MW, Elsaesser VE, Marek DK, Halter CA, et al. (2006)
Mutations in LRRK2 other than G2019S are rare in a north American-based
sample of familial Parkinson’s disease. Mov Disord 21: 2257–2260.
23. Pankratz N, Pauciulo MW, Elsaesser VE, Marek DK, Halter CA, et al. (2006)
Mutations in DJ-1 are rare in familial Parkinson disease. Neurosci Lett 408:
24. Pankratz N, Nichols WC, Elsaesser VE, Pauciulo MW, Marek DK, et al. (2009)
Alpha-synuclein and familial Parkinson’s disease. Mov Disord 24: 1125–1131.
25. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, et al. (2007)
PLINK: a tool set for whole-genome association and population-based linkage
analyses. Am J Hum Genet 81: 559–575.
CNVs in Familial PD
PLoS ONE | www.plosone.org9 August 2011 | Volume 6 | Issue 8 | e20988