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Mitochondrial DNA haplogroups and age at onset of schizophrenia.

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American Journal of Medical Genetics Part B (Neuropsychiatric Genetics) 144B:496 –501 (2007)
Mitochondrial DNA Haplogroups and
Age at Onset of Schizophrenia
Chiara Magri,1 Rita Gardella,1 Stefano Davide Barlati,2 Paolo Valsecchi,2,3
Emilio Sacchetti,2,3,4,5 and Sergio Barlati1,5*
1
Division of Biology and Genetics, Department of Biomedical Sciences and Biotechnology,
Brescia University School of Medicine, Brescia, Italy
2
Department of Mental Health, Brescia Spedali Civili, Brescia, Italy
3
University Psychiatric Unit, Brescia University School of Medicine, Brescia, Italy
4
Chair of Psychiatry, Brescia University School of Medicine, Brescia, Italy
5
Centre on Behavioural and Neurodegenerative Disorders, Brescia University and EULO, Brescia, Italy
A number of studies support a possible
link between mitochondrial dysfunction and schizophrenia. To test the hypothesis of a direct
contribution of mitochondrial DNA (mt-DNA) in
susceptibility to DSM-IV-TR-schizophrenia, we
looked for differences in the frequency distribution of the major European haplogroups (hgs) in
142 patients and 190 controls both of Italian
origin. A subgroup of patients (N ¼ 37) and healthy
counterparts (N ¼ 41) was also analyzed for
possible differences in the relative amount of
mt-DNA versus nuclear-DNA in blood cells.
Patients and controls were comparable for hg
frequency distribution and the relative levels
of mt-DNA even after stratification by gender
and schizophrenia subtype. However, patients
harboring the hg J-T showed an anticipated
onset of the disorder. These results indicate that
the J-T hg of mt-DNA may have a modulator
effect on deeper determinants of schizophrenia.
ß 2007 Wiley-Liss, Inc.
KEY WORDS: mitochondrial DNA; schizophrenia; mt-haplogroups; mt-DNA
levels; age at onset
Please cite this article as follows: Magri C, Gardella R,
Barlati SD, Valsecchi P, Sacchetti E, Barlati S. 2007.
Mitochondrial DNA Haplogroups and Age at Onset of
Schizophrenia. Am J Med Genet Part B 144B:496–501.
INTRODUCTION
Several recent studies support a possible link between
mitochondria dysfunction and schizophrenia. Schizophrenialike symptoms have been described in patients with MELAS, a
mitochondrial encephalopatia [Suzuki et al., 1990; Prayson
and Wang, 1998; Thomeer et al., 1998]. Furthermore, a
decrease in ATP levels in the basal ganglia and temporal lobe
[Kegeles et al., 1998], a subnormal number of mitochondria in
caudate and putamen axonal terminals [Kung and Roberts,
1999], and abnormal activity and expression of respiratory
chain components in platelets and brains post-mortem were
observed in patients with schizophrenia [Prince et al., 1999;
Maurer et al., 2001; Dror et al., 2002]. Schizophrenia patients
were also found to have altered expression of genes related
to mitochondrial function in different areas of the brain
[Middleton et al., 2002; Prabakaran et al., 2004; Altar et al.,
2005; Iwamoto et al., 2005]. Finally, some new mitochondrial
DNA (mt-DNA) variants were occasionally reported in patients
with maternal inheritance of schizophrenia [Martorell et al.,
2006].
To date, the question of whether mitochondria dysfunction is
a primary cause of schizophrenia, a cellular response to
alterations in other metabolic pathways, or an effect mediated
by pharmacological treatment has remained unanswered. In
order to test the hypothesis of a direct contribution of mt-DNA
to susceptibility for schizophrenia, we planned a case–control
study, which compared DSM-IV-TR schizophrenia patients
and healthy controls of Italian origin for possible differences in
haplogroups (hgs) distribution. Indeed, the analysis of haplogroup distribution may be a valid approach to reveal the
presence of mt-DNA polymorphisms, associated with specific
haplogroups, which could be involved in susceptibility to a
complex disease like schizophrenia. Moreover, in order to
verify a possible relationship between the quantity of mt-DNA
and schizophrenia, the relative amount of mt-DNA versus
nuclear DNA was assessed. An altered level of mt-DNA could
reflect either a depletion of mt-DNA copy number or a
reduction of the number of mitochondria; both alterations
could generate a decline of mitochondrial respiratory functions, which could contribute to a complex disease like
schizophrenia.
MATERIALS AND METHODS
Samples
Grant sponsor: Health Authority of the Lombardia Region;
Grant number: Project 153; Grant sponsor: Centre on Behavioural
and Neurodegenerative Disorders; Grant sponsor: IDET Centre of
Excellence (MIUR).
*Correspondence to: Prof. Sergio Barlati, Division of Biology
and Genetics, Department of Biomedical Sciences and Biotechnology, Brescia University School of Medicine, Viale Europa 11,
25123 Brescia, Italy. E-mail: barlati@med.unibs.it
Received 23 August 2006; Accepted 19 December 2006
DOI 10.1002/ajmg.b.30496
ß 2007 Wiley-Liss, Inc.
The study included 142 patients and 190 healthy controls of
both sexes, provided that they gave written informed consent,
were unrelated to each others, fulfilled predefined groupspecific inclusion and exclusion criteria, and referred, by oral
interview, to have Italian ancestry of at least two generations
and to live in northern Italy.
The written consent form supplied a concise but unequivocal
explanation about the aims of the study. The invited participants also received an explicit guarantee of anonymity as a
unique number linked all the individual data.
mt-DNA and Schizophrenia
For the patients, the inclusion criteria were a DSM-IV-TR
diagnosis of schizophrenia [American Psychiatric Association,
2000] and a level of understanding and attention judged to be
sufficient to give true informed consent; lifetime comorbidity
with other DSM-IV-TR axis I disorders, nicotine and caffeine
abuse apart, was an exclusion criterion. Patients were also
evaluated for schizophrenia subtype, schizophrenia severity,
and age at onset. Schizophrenia severity was evaluated by the
Positive and Negative Syndrome Scale (PANSS) [Kay et al.,
1987]. Concerning the age at onset, the appearance of the first
psychotic symptom represented the preidentified operational
cut-off. In order to reach as accurate estimate as possible, direct
information from the patients was systematically retrieved
along with data obtained from at least one close relative, plus,
when available, previous medical records.
For the controls, the prerequisites for enrollment were the
absence during their lifespan of any DSM-IV-TR axis I
disorder, once again nicotine and caffeine abuse apart, and a
negative family history for psychoses and mood disorders.
The procedures for the enrollment of participants and the
collection of any supplementary information have been
described in detail in another study [Magri et al., 2006].
Briefly, detailed clinical interviews were implemented, when
required, by ad hoc questionnaires and DSM-IV-TR adjusted
versions of the Structural Clinical Interview for DSM-IV Axis I
Disorders, Clinician Version [First et al., 1996] for patients and
the Diagnostic Interview for Genetic Studies [Nurnberger
et al., 1994] for controls.
Two qualified psychiatrists were in charge of the entire data
collection, after they were trained on the procedures included
in the protocol and had shown valuable reliability. In any case,
discordance between the evaluators precluded the recruitment
or the acquisition of specific information.
The patients were enrolled from those voluntarily admitted
to the Brescia University and Spedali Civili Psychiatric Unit.
The controls were volunteers enrolled among consenting
doctors, nurses, employers, attendants of Brescia Spedali
Civili, and students of Brescia University or their relatives.
Patients and controls did not differ in sex distribution (86/
56 vs. 111/79 male/female ratio; P ¼ 0.69) and age (39 12 vs.
37 14 years; P ¼ 0.14). A paranoid subtype of schizophrenia
was diagnosed in 64% of the patients. For 135 patients
information about age at onset was also available. These
subjects were aged 26.1 7.6 years at the onset of their
disorders, with an earlier onset in males than females
(24.3 6.7 vs. 28.8 8.2; P ¼ 0.001).
DNA Extraction and Quantification
Total DNA was purified from 2 ml of fresh whole blood using
the Puregene Kit (Gentra Systems, Inc, Minneapolis, MN)
according to the manufacturer’s instructions. Exact quantification of the DNA content was carried out with the NanoDrop
spectrophotometer (Celbio NanoDrop Technologies, Wilmington, DE).
Haplogroup Analysis
To classify the most common European mt-hgs H, U, K, J, T,
W, and I, a total of eight single nucleotide polymorphisms
(SNPs) were studied by restriction fragment length polymorphism (RFLP) analysis in a hierarchical way (Fig. 1). The
SNPs and the restriction enzymes used for their characterization are those reported by De Benedictis et al. [1999]. The rare
hgs were not directly analyzed and were grouped in the Other
(10394) class, or in the Other (þ10394) class according to the
absence or the presence of the 10394 DdeI restriction site.
Primers and PCR conditions are available upon request.
Patient–control differences in the distribution of hgs were
evaluated by the w2 test, combining the less frequent hgs W and
497
I into one class, since they share the 8250 HaeIII SNP, and
the not better defined ‘‘Others (10394)’’ and ‘‘Others
(þ10394)’’ into another class.
A full logistic regression analysis with groups (patients vs.
controls) as dependent variable and mt-hgs (hg H vs. remaining hgs), gender, and hgs by gender interaction as independent
variables was utilized to evaluate a putatively different effect
of the hgs in the two sexes.
A multinomial logistic regression analysis with illness status
(control ¼ 1, non-paranoid schizophrenia ¼ 0, paranoid
schizophrenia ¼ 1) as dependent variable and mt-hgs, gender, and hgs by gender interaction as predictive variables was
performed to define possible specific effects of hgs on defined
schizophrenia subtypes. To avoid the reduction of the test
power due to patient sub-classification, the hgs were collapsed
together according to their phylogeny. The sister hgs U and K
as well as J and T were collapsed into two classes since they
share the mutation þ12308 HinfI and 4216, respectively,
whereas the remaining hgs were clustered into the ‘‘all others’’
class, with the exception of the most frequent hg H, which acted
as the reference category. To test the influence of hgs, gender,
and schizophrenia subtypes on age of onset, the same hg
grouping entered in a factorial analysis of variance on the logtransformed age, to improve its approximation to a Gaussian
distribution. Both the full factorial and the main effect model
were considered. The correlation between mt-hgs and age at
onset of schizophrenia was also studied by the Kaplan–Meier
method and the log-rank test for analyses of survival. The
influence of hgs on the severity of schizophrenia was tested
using a factorial analysis of variance on PANSS outcomes.
All analyses were performed with the software SPSS
(version 12.0). The power of the w2 test for global frequency
hg differences between cases and controls was evaluated by the
G* Power software [Faul and Erdfelder, 1992].
Quantitative Analysis of mt-DNA
The mt-DNA levels were analyzed by comparing the ratio
between mt-DNA and nuclear DNA (n-DNA) in a real-time
polymerase chain reaction (PCR) analysis, using a BioRad
iCycler iQ (BioRad Laboratories, Hercules, CA) thermocycler.
The TaqMan1 RNase P Detection Reagents Kit (Applied
Biosystems, Foster City, CA) was used to quantify the nuclear
DNA; this kit detects and quantitates copies of the human
RNase P gene, which encodes the RNA moiety for the RNase P
enzyme. In the absence of a ‘‘ready to use’’ assay, the mt-DNA
quantification was carried out utilizing a Custom TaqMan1
Gene Expression Assay (Applied Biosystems), and selecting
the 16,081–16,569 bp mitochondrial sequence as the target
fragment. For each sample, n-DNA and mt-DNA were
amplified in two independent PCR reactions, simultaneously
(in the same plate) and in triplicate.
Quantitative-PCR (Q-PCR) amplification was performed in
20 ml containing 1 TaqMan1 Universal PCR Master Mix
(Applied Biosystems), 1 mix of primer and labeled probe FAM
dye, and 20 ng of total genomic DNA. The thermal cycling
conditions were 958C for 10 min, 40 cycles of 958C for 15 sec and
608C for 1 min.
Determination of mt-DNA Relative Levels
The raw data on the fluorescence intensity were analyzed by
the iCycler iQ software according to the ‘‘PCR baseline
subtracted curve fit’’ analysis mode. The threshold cycles (Ct)
were evaluated using the fluorescence thresholds indicated by
the thermal cycler.
The relative quantification was performed by comparing DCt
(difference in threshold cycle) of the reference and the target
gene in each sample. The following equation was used:
498
Magri et al.
mt-DNA
¼ EDCt ðmean n-DNAmean mt-DNAÞ
n-DNA
ð1Þ
where E represents the efficiency of the reaction, which in our
study was equal to 2 since Applied Biosystems reported 100%
efficiency for their Taqman assay (Applied Biosystems
Application Note). Mean n-DNA and mean mt-DNA are the
average Ct values of the triplicate assay for each sample.
Group differences were estimated by the Pair Wise Fixed
Reallocation Randomisation Testß implemented in the
RESTß software [Pfaffl et al., 2002]. In order to avoid any
assumption about distribution normality, a non-parametric
test was preferred to the parametric T-test.
Correlations between mt-DNA level and age at onset, age at
collection and the quality of DNA were performed by the
Spearman’s test, whereas the influence of hgs on the mt-DNA
levels was studied by a factorial univariate analysis of
variance. Both the analyses were performed with the software
SPSS (version 12.0).
RESULTS
Haplogroup Analysis
The hgs H, U, K, T, W, I, and J accounted for more than 85%
of the total variability in both cases and controls. As shown in
Table I, patients and healthy comparisons shared similar hg
frequencies, which did not differ from those previously
reported for the Italian population [Ghezzi et al., 2005].
The full logistic regression analysis demonstrated an
absence of direct and interactive gender effects on hgs
distribution and confirmed that none of the investigated hgs
was associated with risk of schizophrenia.
The multinomial logistic regression analysis showed that
healthy controls, paranoid and non-paranoid schizophrenia
patients did not differ from each other in mt-hg distribution,
even when gender and hgs by gender interaction were taken
into account.
The preliminary analysis of the mean age at onset stratified
by hgs (Table II) as well as the Kaplan–Meier method (Fig. 2)
highlighted an earlier age at schizophrenia onset for patients
harboring the J-T hg (Log Rank w2 ¼ 10.298, P ¼ 0.016). Almost
all the patients belonging to hg J-T (92%) had an onset before
28 years, in contrast to 58% observed in those carrying the
remaining hgs (Supplementary Fig. 1). After the subdivision of
patients in two groups according to their age at onset
(<28 years vs. onset 28 years), a binary logistic regression
analysis was performed, using as fixed factor mt-hgs (hg J-T vs.
remaining hgs). This analysis revealed that patients harboring
hg J-T had a 7.8 (95% CI 1.7–34.7) fold increased risk of
developing schizophrenia before 28 years. The factorial
analysis of variance confirmed the significant effect of both
gender (Fdf1 ¼ 12.671, P ¼ 0.001), and mt-hgs (Fdf3 ¼ 3.65,
P ¼ 0.014) on schizophrenia onset and excluded an effect of
schizophrenia subtypes (Supplementary Tables I and II). In
particular, the pairwise comparison of the estimated marginal
means showed that patients with the hg J-T had earlier onset
than those with the hgs H (P ¼ 0.003), UK (P ¼ 0.033), or ‘‘all
others’’ class (P ¼ 0.004) (Supplementary Table III).
The factorial analysis of variance performed on the PANSS
outcomes did not evidence any correlation between the severity
of the disease and the mt-hgs (Fdf3 ¼ 0.997, P ¼ 0.396). The
early age at onset in subjects harboring hg J-T did not
correlate, therefore, with the severity of the disorder.
Quantification of mt-DNA
The quantitative analysis of mt-DNA level by Q-PCR assay
in blood samples involved a subgroup of 37 patients (19 females
and 18 males) and 41 controls (21 females and 20 males). These
two subpopulations were representative of the original total
sample; indeed, when compared with the remaining participants in the study, they did not differ as to sex, age at collection,
mt-hg frequency distribution, and, for patients only, schizophrenia subtypes and age at onset of the disorder.
Patients and controls gave comparable results for the
relative amount of mt-DNA in the blood cells (P ¼ 0.190)
(Fig. 3). Dichotomization for gender and schizophrenia subtype
(Fig. 3) did not generate any difference in relative amounts of
mt-DNA within and between the groups (male controls vs.
male patients, P ¼ 0.700; female controls vs. female patients,
P ¼ 0.147; female patients vs. male patients, P ¼ 0.579; female
controls vs. male controls, P ¼ 0.655; paranoid subtype vs. nonparanoid subtype, P ¼ 0.100).
The analysis of variance excluded a possible influence of mthgs on the mt-DNA levels in patients (Fdf3 ¼ 2.179, P ¼ 0.109),
in controls (Fdf3 ¼ 0.221, P ¼ 0.881) and in the whole sample
(Fdf3 ¼ 1.513, P ¼ 0.219) (Supplementary Fig. 2).
The Spearman’s test showed that there was no correlation
between mt-DNA levels and age at onset (P ¼ 0.601), age at
collection (P ¼ 0.24), and DNA quality (P ¼ 0.20).
DISCUSSION
To our knowledge, this is the first study comparing DSMIV-TR schizophrenia patients and healthy controls for the most
common European mt-hgs and mt-DNA levels in blood cells.
TABLE I. Frequencies of the mt-hgs Analyzed in Our Sample and in Another Sample of the Italian
Population
Haplogroups
H
K
U
J
T
I
W
Other (10394)
Other (þ10394)
Patients (%)
Controls (%)
w2 P-values
Other Italians (%)a
62 (0.437)
10 (0.070)
17 (0.120)
11 (0.077)
14 (0.099)
5 (0.035)
2 (0.014)
17 (0.120)
4 (0.028)
77 (0.405)
13 (0.068)
18 (0.095)
19 (0.100)
26 (0.137)
4 (0.021)
7 (0.037)
19 (0.100)
7 (0.037)
0.57
0.94
0.46
0.48
0.29
0.73b
646 (0.435)
114 (0.077)
186 (0.125)
126 (0.085)
143 (0.096)
36 (0.024)
235 (0.158)d
0.78c
a
This Italian sample is the CT1 group reported by Ghezzi et al. [2005]; globally this sample did not differ
significantly neither from our controls (P ¼ 0.50) nor from our patients (P ¼ 0.99).
b 2
w test was evaluated combining the rare hgs W and I into one class.
c 2
w test was evaluated combining the hgs ‘‘Others (10394)’’ and ‘‘Others (þ10394)’’ into one class.
d
This frequency was obtained summing the ‘‘Other’’ and ‘‘L-M’’ class frequencies of Ghezzi et al. [2005]. This class
includes our W, Other (10394) and Other (þ10394) classes.
mt-DNA and Schizophrenia
499
Fig. 1. Phylogenetic tree of the studied mt-DNA hgs. The diagnostic RFLP markers used for hg classification and their cut-site positions, according to the
mt-DNA revised Cambridge Reference Sequence (rCRS) [Andrews et al., 1999], are reported along the tree branches. A plus indicates the presence of the
restriction site, a minus its absence. The 4,216 mutation has not been investigated. The þ10394 DdeI polymorphism is underlined since recurrent, that
means the þ10394 DdeI mutation observed on hg K, I, and J is the result of three independent mutational events.
In the haplogroup analysis, no hg contributed to schizophrenia susceptibility and patients and controls were homogeneous in their matrilineal ancestry. Some evidence supports
the robustness of this result. Power analysis of the haplogroup
data indicated that the sample size was adequate to detect
differences of heuristic relevance (effect size ¼ 0.3, power > 0.9)
[Cohen, 1988]. Furthermore, stratifications by gender and
schizophrenia subtype did not have any effect on hg frequency
distribution. Finally, the hg distributions of patients and
controls were similar to those reported for a large, representative sample of the general Italian population [Ghezzi et al.,
2005].
Even if mt-hg did not act as a risk factor for schizophrenia,
subjects harboring the hg J-T presented earlier onset of
schizophrenia as compared to patients with different hg
profiles. Indeed, in the J-T group the mean age at onset was
22.08 in respect to 26.98 of all the other hgs. It would
be interesting as prospective to confirm the result in a
larger dataset and verify if particular sub-lineages of J and
T accumulate in the cases with anticipated onset. However, our
preliminary results suggest that distinct entities with their
own onset curves coexist under the common rubric of schizophrenia. Thus, mt-hgs may be a candidate tool for the division
of schizophrenia patients into different, clinically relevant
endophenotypes. Any comment about the mechanisms by
which the hg J-T could anticipate the onset of schizophrenia is
obviously purely speculative. Our results only excluded a
correlation between mt-hgs and mt-DNA level. However, some
evidence in the literature suggests a possible biological
explanation. The hg J has been proposed to harbor mt-DNA
missense mutations that partially uncouple the mitochondrial
oxidative phosphorylation system (OXPHOS) and thus
reduce ATP production [Ruiz-Pesini et al., 2004]. Furthermore,
reduced ATP levels have been reported to occur in some defined
areas of the brain in schizophrenia patients [Fukuzako et al.,
1996; Kegeles et al., 1998; Jensen et al., 2006]. Bridging
together these two indications, it may be reasonable to
hypothesize that a partially uncoupled mt-OXPHOS associated with hg J could anticipate the appearance of schizophrenia, exacerbating an otherwise underlying sub-threshold
ATP deficit.
The relationship between uncoupled mt-OXPHOS and
schizophrenia is also strengthened by a recent article of
Martorell et al. [2006] on mt-DNA analysis of six schizophrenia
patients with an apparent maternal transmission. Interestingly, the most relevant result was the presence in 5 out of
6 patients of a new non-synonymous heteroplasmic mt-variant
at position 12096, which was not found in 95 controls.
According to the authors, this mutation, which falls in the
TABLE II. Mean Age at Onset of Schizophrenia Patients
Stratified by mt-hgs
mt-hgs
H
Female (N ¼ 21)
Male (N ¼ 38)
U-K
Female (N ¼ 16)
Male (N ¼ 10)
J-T
Female (N ¼ 9)
Male (N ¼ 15)
All other hgs
Female (N ¼ 9)
Male (N ¼ 17)
Mean age at onset
95% CI
26.97
31.14
24.66
26.81
27.94
25.00
22.08
23.00
21.53
27.19
30.44
25.47
24.76–29.18
26.77–35.52
22.39–26.92
24.29–29.32
24.39–31.49
21.23–28.77
19.42–24.74
18.99–27.01
17.67–25.40
24.35–30.04
24.74–36.15
22.18–28.76
Fig. 2. A Kaplan–Meier plot showing the earlier age at onset in
schizophrenic patients carrying the mt-hg J-T (Log Rank w2 ¼ 10.298,
P ¼ 0.016).
500
Magri et al.
Fig. 3. Relative amount of mt-DNA in controls, schizophrenia patients and in the same subjects stratified for gender and paranoid non-paranoid
subtypes. Each dot indicates the relative quantity of mt-DNA normalized with RNaseP gene, calculated as in Equation (1).
ND4 complex, could interfere with the Hþ pumping activity of
the NADH-ubiquinone oxidoreductase and might trigger a
reduction in the rate of ATP production.
However, the analysis of all our patients with an apparent
maternal transmission (N ¼ 13) as well as of the 24 patients
with hg J-T, failed to reveal the 12096T > A mutation. These
data suggest that, in our patients, this mutation is not related
with the schizophrenia phenotype or with the anticipated onset
observed in hg J-T patients.
For the relative mt-DNA levels in blood cells, our analysis
seems to exclude the influence of mt-hgs on mt-DNA levels and,
more generally, indicates that the mitochondrial dysfunctions
reported in schizophrenia patients should not be due to a
constitutive quantitative alteration in mt-DNA quantity. This
conclusion agrees with a recent report on the post-mortem
brain [Kakiuchi et al., 2005], where the sole quantitative
difference reported was a marginal excess of the amount of mtDNA in the frontal cortex of female schizophrenia patients in
comparison with female controls and male patients, but the
significance disappeared following Bonferroni correction.
In conclusion, our results point to an association of the hg J-T
with an anticipated onset of the disorder, which is congruent
with the possibility of some modulator effect of mt-DNA on
deeper determinants of schizophrenia.
ACKNOWLEDGMENTS
The authors thank Dr. Silvia Bonomi and Dr. Alessandra
Mosca for their valuable support with clinical evaluation,
Dr. Cristian Bonvicini for his assistance with the statistics, and
Prof. Massimo Gennarelli for his helpful suggestions. This
study was supported by a grant (project 153) from the Health
Authority of the Lombardia Region together with grants from
the Centre on Behavioural and Neurodegenerative Disorders
and the IDET Centre of Excellence (MIUR).
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mt-DNA and Schizophrenia
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