- Email: [email protected]
Reelin (RELN) DNA methylation in the peripheral blood of schizophrenia
Accepted Manuscript Reelin (RELN) DNA methylation in peripheral blood of schizophrenia Rahim Mohd Nabil Fikri, A. Talib Norlelawati, Abdul Rahim Nour El-Huda, Mohd Noor Hanisah, Abdullah Kartini, Kuzaifah Norsidah, Abdullah Nor Zamzila PII:
S0022-3956(16)30329-6
DOI:
10.1016/j.jpsychires.2016.12.020
Reference:
PIAT 3033
To appear in:
Journal of Psychiatric Research
Received Date: 5 September 2016 Revised Date:
28 December 2016
Accepted Date: 31 December 2016
Please cite this article as: Nabil Fikri RM, Norlelawati AT, Nour El-Huda AR, Hanisah MN, Kartini A, Norsidah K, Zamzila AN, Reelin (RELN) DNA methylation in peripheral blood of schizophrenia, Journal of Psychiatric Research (2017), doi: 10.1016/j.jpsychires.2016.12.020. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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REELIN
(RELN)
DNA
METHYLATION
IN
PERIPHERAL
BLOOD
OF
SCHIZOPHRENIA
b
,Abdul Rahim Nour El-Hudaa, Mohd
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Rahim Mohd Nabil Fikri a, A. Talib Norlelawati*
Noor Hanisahc, Abdullah Kartinic, Kuzaifah Norsidaha, Abdullah Nor Zamzilab.
a
Department of Basic Medical Sciences, Kulliyyah of Medicine, International Islamic
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University Malaysia, bDepartment of Pathology & Laboratory Medicine, Kulliyyah of
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Medicine, International Islamic University Malaysia, , c Department of Psychiatry ,Kulliyyah of Medicine, International Islamic University Malaysia
Corresponding author:
Assoc. Prof Dr Norlelawati A Talib (MD, PhD)
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Department of Pathology and Laboratory Medicine, Kulliyyah of Medicine, International Islamic University Malaysia.
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Email: [email protected]
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REELIN (RELN) DNA METHYLATION IN THE PERIPHERAL BLOOD OF SCHIZOPHRENIA
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ABSTRACT The epigenetic changes of RELN that are involved in the development of dopaminergic neurons may fit the developmental theory of schizophrenia. However, evidence
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regarding the association of RELN DNA methylation with schizophrenia is far from sufficient, as studies have only been conducted on a few limited brain samples. As DNA
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methylation in the peripheral blood may mirror the changes taking place in the brain, the use of peripheral blood for a DNA methylation study in schizophrenia is feasible due to the scarcity of brain samples. Therefore, the aim of our study was to examine the relationship of DNA methylation levels of RELN promoters with schizophrenia using genomic DNA derived from the peripheral blood of patients with the disorder. The case control studies
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consisted of 110 schizophrenia participants and 122 healthy controls who had been recruited from the same district. After bisufhite conversion, the methylation levels of the DNA samples were calculated based on their differences of the Cq values assayed using the highly sensitive
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real-time MethyLight TaqMan® procedure. A significantly higher level of methylation of the RELN promoter was found in patients with schizophrenia compared to controls (p=0.005)
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and also in males compared with females (p=0.004). Subsequently, the RELN expression of the methylated group was 25 fold less than that of the non-methylated group. Based upon the assumption of parallel methylation changes in the brain and peripheral blood, we concluded that RELN DNA methylation might contribute to the pathogenesis of schizophrenia. However, the definite effects of methylation on RELN function during development and also in adult life still require further elaboration. Keywords: RELN; Schizophrenia; DNA methylation
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INTRODUCTION Schizophrenia is a chronic psychiatric disorder that affects approximately 1% of the world’s population; its exact cause remains unknown. Evidence of various genetic defects,
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such as gene mutations, translocation, polymorphisms, and copied numbers, in schizophrenia (Rees et al., 2015) explains only a fraction of the cases (Farrell et al., 2015; Maric and Svrakic, 2012). Historical adoption (Kety et al., 1994) and twin studies (Gottesman and
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Bertelsen, 1989) in schizophrenia have produced unequivocal evidence for genetic heritability in schizophrenia as well as crucial interactions between the candidate genes and
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the environment (epigenetic) for the manifestation of schizophrenia. Epigenetic factors may explain the less than 100% concordance rate for schizophrenia in monozygotic twins; there is still no consensus on the trans-generational inheritance of DNA methylation in humans. Nevertheless, some reports suggest that trans-generational similarity in DNA methylation is attributable to genetic effects (McRae et al., 2014). DNA methylation is among the epigenetic
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mechanisms that have been linked to schizophrenia either as a causative factor or as an effect of the pharmacological approach in the management of schizophrenia (Castellani et al., 2015; Nestler et al., 2015). Methylation studies in schizophrenia have also been conducted either by
2016).
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focusing on selected candidate genes or examining the entire genome (Teroganova et al.,
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RELN (previously, reelin: NC_000007.14 Chromosome 7 Reference GRCh38.p2) is one gene that has consistently been linked with schizophrenia on the basis of its hypothetical functions and its gene variations’ relationship with schizophrenia (Li et al., 2015). Functionally, RELN participates in the migration and positioning of dopaminergic neurons as the brain develops (Nishikawa et al., 2003). A recent report has also reiterated its function in neuron migration during early postnatal development (Sharaf et al., 2015). The earliest direct evidence of RELN’s association with schizophrenia was based on post-mortem studies that
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reported a reduction of up to 50% in the RELN mRNA in several regions of the brains of schizophrenia patients (Impagnatiello et al., 1998; Guidotti et al., 2000). Additionally, the gene’s methylation status determines the mRNA expression of RELN in several types of
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cells, including neuronal cells (Chen et al., 2002). Association studies between RELN and DNA methylation in schizophrenia have produced conflicting but interesting results. The earliest study by Abdolmaleky et al. (2005)
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on the post-mortem brain samples of both normal and schizophrenic patients revealed a significant relationship between the hyper-methylation status of RELN and schizophrenia.
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These findings, however, were not confirmed by a different study that used a pyrosequencing technique (Tochigi et al., 2008) or another recent study that utilized MSP and bisulfite sequencing involving only 29 schizophrenia and 4 normal brain specimens (Alelu-Paz et al., 2015). All these studies apparently lacked statistical robustness as only a limited number of brain samples were analyzed. Furthermore, when DNA methylation as a part of human
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variation (Heyn et al., 2013) is considered, a much larger sample size will be required to identify a definite association between DNA methylation and schizophrenia susceptibility. Unfortunately, few researchers have the privilege of using brain samples.
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Additionally, in some cultures and regions, the donation of the body or organs after death is considered a taboo, which makes it difficult to obtain the brain tissue of patients with
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schizophrenia. Consequently, the use of peripheral blood for a DNA methylation study in living schizophrenia patients could be a better option. It has been reported that some methylation markers were similarly altered in both the brain and the peripheral blood, which suggests a common epigenetic dysregulation in both sites; therefore, the outcome of a study that used peripheral blood will most likely be comparable to a brain tissue study (Auta et al., 2013). The author further proposed that the overall mechanism of epigenetic regulation in peripheral blood lymphocytes and the brain is parallel and these alterations could be a
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primary cause of the illness and not a simply consequence of the disease (Auta et al., 2013). Another independent study suggested that methylation changes in the peripheral blood may mirror the changes in the brain (Aberg et al., 2013). Although extensive methylome profiling
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across the brain and blood has identified highly tissue-specific DNA methylation, there were distinct patterns of DNA-methylation across the brain and the blood that were highly correlated (Davies et al., 2012).
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Our study’s aim was to assess the methylation differences between schizophrenia patients and healthy controls by obtaining DNA from the peripheral blood. This approach
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may provide some clues regarding the status of peripheral RELN methylation and its relationship with schizophrenia. The converted, bisulfite-treated DNA was subjected to a MethyLight Taqman® Assay for highly sensitive and reproducible methylation quantification
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(Eads et al., 2000; Olkhov-Mitsel et al., 2014).
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MATERIALS AND METHODS Ethics approval This study was registered under the National Medical Research Registry of Malaysia
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(NMRR-10-832-6366). The protocol was approved by both the Medical Research and Ethics Committee (MREC), the Ministry of Health in Malaysia and the International Islamic
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University Malaysia (IIUM) Research Ethics Committee (ID no: IREC 466).
Sample collection
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The sample size was calculated using OpenEpi (www.OpenEpi.com) for a sample size that compared two means. If the current study used all previous data on RELN DNA methylation, fewer than 10 samples from both the schizophrenia and healthy control groups would be required for an 80% power of the study at a 95% confidence interval (CI). The size approximation was based on a study by Ikegame et al. (2013), which utilized peripheral
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blood and therefore aimed for a size of 100 schizophrenia cases and 100 healthy controls. At the end of the recruitment period, 110 schizophrenia patients who attended the Psychiatry Clinic at the Hospital Tengku Ampuan Afzan in Pahang who agreed to participate were
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included. The controls (n = 122) were randomly selected from the database of DNA samples of the healthy population archived in the Molecular Research Laboratory of the Department
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of Pathology and Laboratory Medicine at IIUM and were sex- and age-matched to the case subjects. The collection of the normal samples was carried out in a previous study (Norlelawati et al., 2015). A trained psychiatrist diagnosed all patients using the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria for schizophrenia. Patients were required to have had symptoms for at least the past six months, and the psychosis must also not be deemed to be secondary to substance use or neurological disorders. Mentally handicapped patients and those who were younger than 18 years of age were not included.
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The Positive and Negative Syndrome Scale (PANSS) was administered to each patient, whilst other clinical information was retrieved from available medical records.
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DNA extraction and bisulphite modification Genomic DNA was extracted from whole-blood samples (approximately 5 mL) using a Gentra Puregene Blood Kit (Qiagen, Germany) following the manufacturer’s protocol. The
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DNA concentration was measured by a Qubit® 3.0 Fluorometer (ThermoFisher Scientific, US). Universal Methylated and Non-Methylated Human DNA Standard (Zymo Research,
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US) were used as the 100% methylated and 0% methylated controls, respectively. The DNA concentrations of both control samples were also verified using a Qubit® 3.0 Fluorometer (ThermoFisher Scientific, US). Two µg of genomic DNA, universal methylated and nonmethylated DNA were treated with sodium bisulphite modification using a Zymogen EZ DNA Methylation Gold Kit (Zymo Research, US) as per the manufacturer’s instructions. A
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30-µl M-Elution buffer was used for the final elution step. The bisulphite-converted DNA was then diluted to a final concentration of 10 ng/µl.
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MethyLight primer and probe sequences
The primers and probe were designed specifically for the targeted gene, whilst the primer and
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probe for ALU as the reference gene was based on the study by Olkhov-Mitsel et al. (2014). The primer and probe for RELN were developed using the MethyLight Primer Express v 1.0 (Applied Biosystems, US) and Methprimer (http://www.urogene.org/methprimer/) (Li and Dahiya, 2002) for CpG island prediction as well as the preliminary selection of the primer sequence based on methylated methyl-specific primer (MSP) tools. The primer sequence was determined using the protocol of Wojdacz et al. (2008), which proposed a proportional amplification of both methylated and unmethylated templates of bisulphite-modified DNA.
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The probe was designed based on the basic property requirement of Taqman probes. The promoter sequences for RELN were retracted from the ensemble genome browser (www.ensemble.org) (RELN: EN SG00000189056). The details of the primers and probe for
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RELN and the reference ALU (Olkhov-Mitsel et al., 2014) are shown in Table 1, whilst the flanking sequence and the available CpG islands are shown in Figure 1. All primers and
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Determining the assay efficiency and MethyLight assay
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probes were bundled together as PrimeTime®qPCR Primers (https://www.idtdna.com/).
To assess the assay’s efficiency, the converted DNA from both control samples was prepared according to the protocol suggested by Olkhov-Mitsel et al. (2014). The efficiency of the MethyLight assay was tested by analysing both the ALU and RELN assays for a decreasing amount of methylated DNA. For this process, 70 ng of bisulphite-converted universal
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methylated DNA and 140 ng of universal non-methylated DNA were mixed and serially diluted into three-fold increments from 1:3 (1.67 ng/µl) up to 1:19683 (0.0003 ng/µl). The 10 µl polymerase chain reaction (PCR) consisted of 2 µl of each dilution of DNA, a 1X
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concentration of 2X SensiFAST™ PROBE mix (Bioline, UK) and a 1X PrimeTime®qPCR Primers mix (IDTDNA, US) that was run in triplicate on a BioRad CFX96™ Real-Time
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System with polymerase activation at 95°C for 10 minutes, followed by denaturation at 95°C for 10 seconds and annealing and extension at 60°C for 30 seconds. The denaturation and annealing/extension were repeated for 40 cycles. The stability of the ALU reaction, which was chosen as the control reference in the MethyLight assay, was validated by calculating the coefficient of variation (CV) of the reactions involving the methylated DNA of schizophrenia cases run on a single 96-well plate. The formula for calculating the CV% is (standard deviation/mean) x 100%.
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The same PCR reaction protocol was applied to run the samples. In brief, the 10 µl qPCR reaction mixture contained 2 µl of bisulphite-converted DNA (20 ng), 5 µl of the SensiFAST™ Probe, 2.5 µl of nuclease-free water and 0.5 µl of 20X PrimeTime® probe and
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primer mix. The reaction utilized a 96-well PCR plate and was run on the BioRad CFX96™ real-time PCR (RT-PCR) platform with an initial denaturation at 95°C for 10 minutes, followed by 60 cycles at 95°C for 10 seconds and 60°C for 30 seconds. The 60 cycles were
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extended from the initial 40-cycle optimization steps to cover minimal amplification copies. The same 96-well PCR plate contained DNA from the samples, controls and the 100%
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Universal Methylated DNA reference. Each sample’s Cq values for the target and reference gene were obtained to calculate the DNA methylation percentage ratio based on the formula proposed by Olkhov-Mitsel et al. (2014), which was adapted from Eads et al. (2000). The formula is [(RELN/ALU) sample/(RELN/ALU) Universal Methylated Human DNA] x
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100%.
Analysis of RELN expression by relative quantitative RT-PCR After the methylation percentage of the RELN gene had been determined, samples of
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schizophrenia cases that represented a high methylation status and a low methylation status were chosen for the determination of the RELN mRNA expression. The blood samples of
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selected cases that had been stored in RNAlater were traced and subjected to RNA purification using a RiboPure™-Blood Kit (ThermoFisher Scientific, US) according to the manufacturer’s protocols. In each extract, the yield of the RNA was established by its absorbance at 260/280 nm. Samples with a ratio below 1.8 were rejected. The integrity of the RNA was assessed using denaturing agarose gel electrophoresis by evaluating the sharpness of the two ribosome RNA bands (28s and 18s). Prior to cDNA synthesis, the total RNA concentration of all purified RNA was standardized to a concentration of 25 ng/µl and treated
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with DNAase 1 (BioRad) to eliminate any genomic DNA contamination. The cDNA was synthesized using iSript™ Reverse Transcription Supermix (Bio-Rad, US) following the manufacturer’s protocol with 125 ng RNA for each sample. The primer for the targeted gene,
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RELN (Hs_RELN_1_SG QuantiTect Primer Assay (QT00025592), and two reference genes, GAPDH (Hs_GAPDH_1_SG Quanti Tect Primer Assay (QT00079247)] and ACTB [Hs_ACTB_1_SG Quanti Tect Primer Assay (QT00095431)], were chosen from a database
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of pre-designed QuantiTect Primer Assays (Qiagen, US) (www.qiagen.com/geneglobe/). The cDNA was then used in a quantitative RT-PCR experiment undergoing the SsoFast™
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EvaGreen® Supermix (BioRad) reaction in a 96-well plate on the CFX-96 BioRad real-time platform. For each gene [two reference genes (ACTB and GADPH) and one target gene (RELN)], a standard curve of six 1-in-10 dilutions of mixtures of all samples of cDNA was assayed followed by a melting curve analysis that was set up to run from 90°C to a 50°C decrement. At the same time, the gene expression of the methylation status groups (the
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low/un-methylated vs. the methylated group) was measured to determine the relative quantitation of gene expression using RT quantitative PCR with the same instruments and reagents. The quantitation utilized the mean Cq value for each group and calculated this value
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according to the comparative Ct method (∆∆Ct method) proposed by Pfall (2001).
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Statistical analyses
All the statistical analyses were performed using the Statistical Package for the Social
Sciences (SPSS), version 22. The demographic data, including age, sex, and race, were calculated using descriptive statistics. The categorical data were presented as frequencies and percentages (%). The numerical data were reported as the mean and standard deviation (SD) along with a 95% confidence interval (95% CI). An analysis of covariance (ANCOVA) test was utilized in both analyses to compare the RELN methylation percentage between
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schizophrenia patients and controls and also to examine the relationship of several factors in schizophrenia. The percentage methylation ratio (PMR) is presented as the estimated marginal mean (EMM) (adjusted for covariates) with the 95% CI. Predictions of certain
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value <0.05 was considered statistically significant.
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variables of RELN methylation were assessed through multiple regression analyses. A p-
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RESULTS Demographic characteristics This study included 122 healthy controls and 110 schizophrenia cases. There were no
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significant differences in age, sex or race between the healthy controls and the schizophrenia patients. The detailed demographic characteristics of both groups are summarized in Table 2.
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Assay efficiency and validation of the MethyLight experimental conditions
The amplification plots of ALU and RELN that have been serially diluted in three-fold
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increments (from 1:3 to 1:19683) of bisulphite-modified methylated DNA are shown in Figure 2. The ALU and RELN reactions exhibited decreasing detection levels of methylated alleles in subsequent dilutions, as indicated by the increasing cycle number at which each reaction signal crossed the detection threshold. The ALU control reaction sensitivity of detection was the 1:19683 dilution (0.00005 ng). In contrast, the sensitivity limit of RELN
methylated DNA.
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methylation was only up to the 1:27 dilution, which is estimated to contain 0.37 ng of
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For the coefficient of variation of the ALU reaction, the Cq value of the ALU reaction was used to calculate the standard deviation and mean. A good CV (<20%) was achieved for
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all the plate assays. The CV% ranged from 6.4–17.0%, with a mean CV% of 8% (The MethyLight was run on seven different assay plates). An example of an ALU reaction on one plate assay and its corresponding CV% is illustrated in Figure 3, which involved 45 tested samples (23 controls and 23 schizophrenia patients).
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Percentage methylation ratio of RELN in schizophrenia. All bisulphite-treated DNA samples of the cases and controls were successfully amplified for RELN and the reference ALU. The PMR is the ratio of methylation copies of a
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sample against a commercially known reference [(Universal Human Methylated DNA (Zymo, US)] that is presumed to provide 100% copies of methylated DNA. In this study, the target RELN amplification sites contained eight CpG spots (Figure 1), and the probe was
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used to cover one CpG spot. Our study found a significant difference of the percentage methylation ratio between the cases and controls (p=0.005); the mean PMR was higher in
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schizophrenia patients [1.39 (1.37-1.41)] than it was in the controls [1.35 (1.33-1.37)] (Table 3).
Relationship between DNA methylation with age and sex
The relationship between DNA methylation levels and confounding factors (age and sex) was
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tested in the controls. There was no significant correlation between the DNA methylation level and age (Pearson correlation; p=0.445). Similarly, there was no difference in the DNA methylation value between both sexes in the control participants (independent t-test; p=0.482,
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t= -0.705, df=120). A similar insignificant relationship of age (Pearson correlation; p= 0.567) and sex (independent t-test; p=0.341) with a methylation level was also noted among the
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schizophrenia participants.
Subgroup analysis in schizophrenia. The analysis of the DNA methylation level in a specific subgroup of the schizophrenia patients found a significantly higher DNA methylation value in male schizophrenic patients compared to healthy controls [1.40(1.38-1.43) vs 1.34(1.32-1.36), p=0.001]; this level was insignificant among females [1.38(1.34-1.41) vs 1.36 (1.32-1.40); p=0.467] (Table 3).
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Further analysis revealed that the DNA methylation value has no relationship with the patient’s smoking status or the type of schizophrenia (Table 4). There were also insignificant correlations between the DNA methylation level and the age of patients and the PANSS
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dimension score of schizophrenia (Table 5).
RELN mRNA expression
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Since the percentage methylation ratios of all cases were below 2.00, six schizophrenia cases with a PMR of more than 1.70 (methylated) and three cases with a PMR less than 1.20
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(unmethylated) were chosen to analyse the mRNA expression. There was significant down regulation of the RELN mRNA expression in the group of methylated schizophrenia samples
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relative to those with unmethylated DNA (Figure 4).
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DISCUSSION The existence of an epigenetic contributor to the etiology of schizophrenia was proposed during the past decade and has gained experimental support. However, the
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epigenetic data on schizophrenia are scarce and have mostly been derived from gene-specific studies involving brain tissue (Nishioka et al., 2012), which is virtually inaccessible in living patients. Therefore, studies of DNA methylation in schizophrenia patients are still limited,
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and the majority has been conducted in a small sample size of patients (Zong et al., 2015). Walton et al. (2016) used the temporal lobe of the brain in epilepsy patients and their
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corresponding peripheral blood samples to investigate the feasibility of blood samples as a surrogate marker for the brain. He suggested that some subsets of peripheral methylation data may serve as a proxy to the methylation status of brain tissue. Walton et al. (2016) also reported that the altered methylation profiles in schizophrenia involved pathways related to precursor metabolites and signaling peptides. Additionally, a number of epigenetic studies
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that targeted psychiatric diseases have proposed that epigenetic changes are not limited to post-mortem brain tissue but can also be detected in other peripheral tissues, such as blood, urine, and saliva (Carrard et al., 2011; Dempster et al., 2013; Melas et al., 2012). There was
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evidence of the broad impact of maternal rearing on DNA-methylation in both the brain and in the T-cells of Rhesus Macaque, which supported the suggestion that environmental insults
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are systemic, affect the entire genome, and persist into adulthood (Provencal et al., 2012). The methylome-wide approach study by Davies et al. (2012) reported that distinct patterns of DNA-methylation across the brain and the blood are highly correlated. In addition, a study by Klengel et al. (2013) on the relationship between genes and childhood trauma suggested that demethylation has a global effect on the function of both immune cells and brain-associated areas.
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One note of caution is that the peripheral blood cannot entirely substitute for the complex nature of brain tissue and its cell constituents. There are higher degrees of DNA methylation variability between the cerebellum, cortex, and peripheral blood than there are
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for the variability between different cortical regions (Marzi et al., 2016), with the correlation of selected variables being closer between BA9 and the peripheral blood than those for the cerebellum and peripheral blood (Marzi et al., 2016). Microglia, which have been attributed
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to the neuroinflammatory (Monji et al., 2013) and neurodevelopmental (Frick et al., 2013) hypotheses of schizophrenia, are probably more similarly related to blood than neuronal cells
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since earlier investigations described their origin from blood monocytes that had differentiated from hemopoietic cell precursors (Ginhoux et al., 2013). Thus, irrespective of whether there are similar changes in both the brain and blood, the differences in RELN methylation between the cases and controls in our study could indicate a unique feature of schizophrenia, a peripheral biomarker, or be related to a particular treatment.
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Previous studies have detected RELN proteins and mRNA during both development and adulthood in the blood and other peripheral organs (Smalheiser et al., 2000). Although the increased non-neuronal RELN expression has been well documented in
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hepatic (Kobold et al., 2002) and ocular (Pulido et al., 2007) injuries, an event that leads to RELN expression in the blood is not well established. There could be a connection between
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RELN and the immune system; an earlier study reported a higher expression of RELN in plasma cells (the mature form of B-lymphocytes) than in the precursor B-lymphocyte cells (Underhill et al., 2003). If epigenetic methylation regulation between the brain and the peripheral blood is parallel (Auta et al., 2013), the methylation status of the RELN in the peripheral blood could be used to reflex for its role in schizophrenia. Our study assessed the methylation differences between schizophrenia patients and healthy controls using the peripheral blood as the DNA source, while the possible effects of methylation on RELN
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function were assessed through relative gene expression. These approaches may provide some clues about the status of peripheral RELN methylation and its relationship with schizophrenia.
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The relationship between RELN and schizophrenia is based on several functional observations that Reelin, the protein encoded by the RELN gene, is crucial in brain development as this protein plays a role in several brain processes, such as the extension of
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axons and dendrites that are essential for the transmission of nerve impulses (Curran and D'Arcangelo, 1998; D’Arcangelo, 2014). It is also known that unmethylated CpGs are
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usually clustered together in the ‘CpG Islands’ found in the promoter region of many genes; thus, it is predicted that DNA methylation plays an important role in regulating gene expression in view of its role in gene transcription (Bird, 1986; Lim and Maher, 2010). Although methylation and gene expression are often correlated, there have not always been in opposite directions than the promoter CpG (Wagner et al., 2014).
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In this study, we detected a significantly higher level of DNA methylation at the CpG sites of the RELN promoter in schizophrenia patients compared to the controls. This finding was compatible with the studies of Abdolmaleky et al. (2005) and Grayson et al. (2005),
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although both used non-quantitative, methyl-specific PCR (MSP) to determine the methylation, and their study sample size was only about 10 brain tissues each from the
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controls and the schizophrenia patients. In contrast, two additional studies reported insignificant findings (Alelu-Paz et al., 2015; Tochigi et al., 2008). Again, both studies had limited brain tissues available. Tochigi et al. (2008) utilized a quantitative pyrosequencing approach and reported that DNA methylation in both schizophrenics and in control participants was less than 5%, which was similar to our findings. Although the current study used a different approach for quantitation, we found that the DNA methylation levels of both the schizophrenia cases and controls were very low but were significantly higher in patients
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with schizophrenia. Subsequently, the effect of DNA methylation on the functional expression of the RELN gene was assessed. It was found that the RELN expression of samples with a higher methylation level was much depressed relative to those with lower
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methylation values. Therefore, this finding supported the theory that DNA methylation of the RELN promoter sites affected gene expression. It is therefore postulated that epigenetic DNA methylation of the RELN gene participates in the aetiology and pathogenesis of
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schizophrenia.
It is generally acknowledged that DNA methylation is influenced by multiple factors,
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such as age, sex, ethnicity or even the early life economy status of healthy control participants (Lam et al., 2012). Our study found no significant relationship for either age or sex according to the DNA methylation levels in the controls and in the schizophrenia patients. However, there were significantly higher DNA methylation values in male patients with schizophrenia compared to the healthy male controls. It was also noted that female
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patients with schizophrenia had a higher level of DNA methylation compared to the controls, but the difference was not statistically significant. As males provided a better sampling power (160 males vs. 72 females), any further conclusions regarding sex-dependent methylation
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differences may require a better sampling representation. In adults, it was suggested that the down regulation of RELN-integrin interaction is
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the basis for the decrease in dendritic spine densities in psychiatric patients (Rodriguez et al., 2000). Dendritic spines are considered the central highways of synaptic connections (Sala and Segal, 2014). Given that dopamine D2 and serotonin 5-HT2A receptors are influential in the development of schizophrenia symptoms and that RELN expression maybe reduced as a consequence of hypermethylation, our study attempted to determine the association of RELN methylation levels with the psychological symptoms of schizophrenia. However, we found no correlations between the RELN methylation levels and the psychological symptoms of
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schizophrenia. Nevertheless, it is likely too early to state that these findings reflect the actual association of RELN methylation levels and the psychological symptoms of schizophrenia since our samples were mainly obtained from patients who were currently taking psychiatric
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medications. Furthermore, our samples likely contained other confounding factors of DNA methylation as described by Nishioka et al. (2012). In addition, the effects of drugs on the methylation level require further clarification since studies among bipolar disorder patients
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have found that some anti-psychotics were not associated with DNA methylation signatures (Houtepen et al., 2016). In a study that assessed the expression of 11 genes related to
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neurotransmitters or neurodevelopments (RELN was not included), it was found that the majority of the genes showed an insignificant difference of mRNA expression between schizophrenia patients and healthy controls (Ota et al., 2014). It thus advisable to conduct a specific study to assess the mRNA expression of RELN in untreated patients who are also naïve to anti-psychotics and consequently assess their relationship with DNA methylation
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values.
There are several limitations to our study. Melas et al., (2012) reported a relationship between peripheral leucocytes DNA methylation and anti-psychotic medication. The effects
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of anti-psychotic medications on DNA methylation must be considered because our participants included many stable schizophrenia patients; the outcome of this study might
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have been different if it were conducted using schizophrenia patients who were antipsychotic-free. However, this option was not explored due to sampling accessibility and difficulty procuring acute schizophrenia patient samples. The medication data obtained from the participants were also complex and challenging for the multivariate analyses. With regard to the methodology, although the MethyLight approach was robust, sensitive, and highly specific (Trinh et al., 2001; Zhang et al., 2010) for the DNA methylation quantification, it was only able to cover a few CpG islands per run. In our study, the methyl probe only
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covered one CpG island. However, this method is the most suitable for a high-throughput assay, which was conducted in our study (Zhang et al., 2010). In conclusion, we identified a difference in the DNA methylation of the RELN
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promoter in the peripheral blood of patients with schizophrenia. As a result, the mRNA expression of RELN in those with a high amount of methylation was relatively suppressed compared to those in the low methylation group. Although the definite effects of methylation
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on RELN function during development and also in adult life will require further elaboration and studies that include actual brain tissues and should be guided by the assumption of
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parallel methylation changes in both the brain and peripheral blood, we suggest that an
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epigenetic aberration of RELN may contribute to the pathogenesis of schizophrenia.
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Funding source The study is funded by the Fundamental Research Grant Scheme (Grant No: FRGS-14-101-
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0342) provided by the Ministry of Education, Malaysia.
Contributors
Norlelawati designed the study. Nabil, Nour el Huda, Hanisah and Kartini conducted Norlelawati and Nabil conducted the statistical analyses.
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sample and data collection.
Norlelawati and Nabil wrote the manuscript. All co-authors provided critical feedback on the
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manuscript, suggested additional analyses and critical revisions, and edited the manuscript for clarity and precision. All authors contributed to and approved the final manuscript.
Conflict of interest
The authors have no conflicts of interest that are directly relevant to the content of this
Acknowledgment
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manuscript.
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The authors thank staff and patients of Psychiatry Clinic, Tengku Ampuan Afzan Hospital,
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Kuantan, Pahang & Molecular Research Laboratory, Kulliyyah of Medicine, IIUM.
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Smalheiser, N.R., Costa, E., Guidotti, A., Impagnatiello, F., Auta, J., Lacor, P., Kriho, V., Pappas, G.D., 2000. Expression of reelin in adult mammalian blood, liver, pituitary pars intermedia, and adrenal chromaffin cells. Proc Natl Acad Sci U S A 97 (3), 12811286. Teroganova, N., Girshkin, L., Suter, C.M., Green, M.J., 2016. DNA methylation in peripheral tissue of schizophrenia and bipolar disorder: a systematic review. BMC Genet 17 (1), 27. Tochigi, M., Iwamoto, K., Bundo, M., Komori, A., Sasaki, T., Kato, N., Kato, T., 2008. Methylation status of the reelin promoter region in the brain of schizophrenic patients. Biol Psychiatry 63 (5), 530-533. Trinh, B.N., Long, T.I., Laird, P.W., 2001. DNA methylation analysis by MethyLight technology. Methods 25 (4), 456-462. Underhill, G.H., George, D., Bremer, E.G., Kansas, G.S., 2003. Gene expression profiling reveals a highly specialized genetic program of plasma cells. Blood 101 (10), 40134021. Wagner, J.R., Busche, S., Ge, B., Kwan, T., Pastinen, T., Blanchette, M., 2014. The relationship between DNA methylation, genetic and expression inter-individual variation in untransformed human fibroblasts. Genome Biology 15 (2), 1-17. Walton, E., Hass, J., Liu, J., Roffman, J.L., Bernardoni, F., Roessner, V., Kirsch, M., Schackert, G., Calhoun, V., Ehrlich, S., 2016. Correspondence of DNA Methylation Between Blood and Brain Tissue and Its Application to Schizophrenia Research. Schizophr Bull 42 (2), 406-414. Wojdacz, T.K., Dobrovic, A., Hansen, L.L., 2008. Methylation-sensitive high-resolution melting. Nat Protoc 3 (12), 1903-1908. Zhang, Z., Gao, J., Qin, C., Liu, L., Lin, H., Shen, Y., Gao, S., Zhao, M., Ding, H., Pan, G., 2010. A High-Through Technique to Measure DNA Methylation. Genetics & Epigenetics. 3, 5-13. Zong, X., Hu, M., Li, Z., Cao, H., Chen, X., Tang, J., 2015. DNA methylation in schizophrenia: progress and challenges. Science Bulletin 60 (2), 149-155.
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Table 1: Primer and probe sequence used for the MethyLight assay Primer Names
Sequence (5’-3’)
ALU sequence
ALU-F ALU-R ALU-probe
GGTTAGGTATAGTGGTTTATATTTGTAATTTTAGTA ATTAACTAAACTAATCTTAAACTCCTAACCTCA /56-FAM/CCTACCTTA/Zen/ACCTCCC/3IABkFQ/
RELN
RELN-F AGATAAAGAAATCGCCGTTAGCG CACCTCCCGTCCAACTATCTAAA RELN-R RELN-probe /56FAM/ACCAACCCC/ZEN/TTTAACCGTCAATATACCCT/ 3IABkFQ/
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Target
Table II: A comparison of the demographic data from the control and schizophrenic subjects Schizophrenia (n = 110) n (%)
p-value
Sex Male Female
89 (73.0%) 33 (27.0%)
71 (64.5%) 39 (35.5%)
0.167
Race Malay Chinese Indian
112 (91.8%) 8 (6.6%) 2 (1.6%)
99 (90.0%) 7 (6.3%) 4 (3.6%)
0.633
Control (n = 122) Mean (SD)
Schizophrenia (n = 110) Mean (SD)
p-value
40.26 (8.38)
0.052
Age
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Control (n = 122) n (%)
Variables#
37.92 (9.76)
Chi-square test, +Independent Sample T-Test (p-value < 0.05 is taken as statistically significant at a 95% confidence interval).
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Table III: Differences in the percentage methylation ratio (PMR) between schizophrenia patients and healthy controls. PMR EMM (95% CI)
F-stat (df)
Patients (110)
1.39 (1.37–1.41)
Controls (122)
1.35 (1.33–1.37)
7.960 (1.00)
Males Patients (71)
1.40 (1.38–1.43)
Controls (89)
1.34(1.32–1.36)
Females Patients (39)
1.38 (1.34–1.41)
Controls (33)
1.36 (1.32–1.40)
0.005
0.001
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11.70 (1)
p-value
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Fixed factors (n)
0.467
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0.536 (1)
ANCOVA test, n = number of participants, EMM = estimated marginal means, CI = confidence interval, F-stat = F statistic; df = degree of freedom. Adjusted for age, sex, and race. Statistical significance was set at p<0.05 with a 95% confidence interval.
factors in schizophrenia
PMR EMM (95% CI)
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Fixed factors (n)
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Table IV: The relationship between the percentage methylation ratio (PMR) and several
Smoking status*
Smoker (59)
1.38 (1.35–1.41)
Non-smoker (51)
1.39 (1.35–1.42)
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Types of Paranoid (37) schizophrenia ** Disorganized (40)
F-sat (df)
p-value
0.046 (1)
0.831
1.102 (4)
0.360
1.40 (1.36–1.43) 1.40 (1.36–1.43)
Catatonic (2)
1.32 (1.17–1.47)
Residual (13)
1.36 (1.31–1.42)
Undifferentiated disorder (18)
1.35 (1.30–1.40)
ANCOVA test, n = number of participants, PMR = percentage methylation ratio, EMM = estimated marginal means, CI = confidence interval, F-stat = F statistic; df = degree of freedom. Adjusted for age, sex, race, body mass index, and type of schizophrenia* or smoking status**. Statistical significance was set at p<0.05 with a 95% confidence interval.
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Table V: The PANSS five factor domains, age, and BMI predictions for the percentage methylation ratio Model 1
Coefficients Predictors SE
t
p
R2
Adjusted R2
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B -0.001
0.006
-0.178
0.859
Negative
-0.004
0.003
-1.095
0.276
0.002
0.004
0.703
0.484
-0.010
0.006
-1.793
0.010
0.005
1.962
Age
-0.001
0.001
-0.574
0.567
0.003
-0.006
BMI
0.004
0.002
2.702
0.008
0.066
0.057
Excited Depressed
0.040
0.076
0.052
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Disorganized
0.084
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Positive
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Regression analyses: PANSS: Positive and Negative Syndrome Scale; BMI = body mass index; SE = standard error; R2: coefficient of determination. Significance was set at p<0.05.
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Figure 1: The forward, reverse and probe sequences selected for the RELN MethyLight assay. The parameters for the CpG island search include Window: 200; Window shift: 1bp; Obs/Exp CpG: 0.6 and GC%: 50.0. http://www.urogene.org/methprimer/.
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Figure 2: Amplification plots for ALU and RELN serially diluted in three-fold increments of A: ALU and C: RELN show a decreasing reaction (increasing cycle reaction) in
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subsequent dilutions. D: RELN sensitivity (D) is limited to only the 1:27 dilution as compared to the B: ALU sensitivity, which reached a full 1:19683 dilution. Both reactions exhibited an R2 of >90%.
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Figure 3: A: Amplification plots for the ALU reaction for 45 samples (run per-plate assay) where the mean Cq values for control participants and schizophrenia patients were 13.6 (SD=1.05) and 14.5 (SD=1.36), respectively. The calculated CV% was 7.7% for the controls
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and 9.4% for the schizophrenia patients. The combined CV% for both samples was 9.1%.
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1.
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0.00
-9.38
-18.75
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RELN Regulation Threshold
9.38
-25.12
-28.13
Methylated
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Unmethylated
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Figure 4: Gene expression of RELN. The RELN expression was normalized to GAPDH and ACTB in unmethylated (low PMR<1.20) and methylated (PMR>1.70) peripheral blood mRNA of schizophrenia samples. The differences between groups were tested using an unpaired t-test. Significant down-regulation was observed (p=0.020).
S0022-3956(16)30329-6
DOI:
10.1016/j.jpsychires.2016.12.020
Reference:
PIAT 3033
To appear in:
Journal of Psychiatric Research
Received Date: 5 September 2016 Revised Date:
28 December 2016
Accepted Date: 31 December 2016
Please cite this article as: Nabil Fikri RM, Norlelawati AT, Nour El-Huda AR, Hanisah MN, Kartini A, Norsidah K, Zamzila AN, Reelin (RELN) DNA methylation in peripheral blood of schizophrenia, Journal of Psychiatric Research (2017), doi: 10.1016/j.jpsychires.2016.12.020. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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REELIN
(RELN)
DNA
METHYLATION
IN
PERIPHERAL
BLOOD
OF
SCHIZOPHRENIA
b
,Abdul Rahim Nour El-Hudaa, Mohd
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Rahim Mohd Nabil Fikri a, A. Talib Norlelawati*
Noor Hanisahc, Abdullah Kartinic, Kuzaifah Norsidaha, Abdullah Nor Zamzilab.
a
Department of Basic Medical Sciences, Kulliyyah of Medicine, International Islamic
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University Malaysia, bDepartment of Pathology & Laboratory Medicine, Kulliyyah of
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Medicine, International Islamic University Malaysia, , c Department of Psychiatry ,Kulliyyah of Medicine, International Islamic University Malaysia
Corresponding author:
Assoc. Prof Dr Norlelawati A Talib (MD, PhD)
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Department of Pathology and Laboratory Medicine, Kulliyyah of Medicine, International Islamic University Malaysia.
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Email: [email protected]
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REELIN (RELN) DNA METHYLATION IN THE PERIPHERAL BLOOD OF SCHIZOPHRENIA
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ABSTRACT The epigenetic changes of RELN that are involved in the development of dopaminergic neurons may fit the developmental theory of schizophrenia. However, evidence
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regarding the association of RELN DNA methylation with schizophrenia is far from sufficient, as studies have only been conducted on a few limited brain samples. As DNA
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methylation in the peripheral blood may mirror the changes taking place in the brain, the use of peripheral blood for a DNA methylation study in schizophrenia is feasible due to the scarcity of brain samples. Therefore, the aim of our study was to examine the relationship of DNA methylation levels of RELN promoters with schizophrenia using genomic DNA derived from the peripheral blood of patients with the disorder. The case control studies
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consisted of 110 schizophrenia participants and 122 healthy controls who had been recruited from the same district. After bisufhite conversion, the methylation levels of the DNA samples were calculated based on their differences of the Cq values assayed using the highly sensitive
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real-time MethyLight TaqMan® procedure. A significantly higher level of methylation of the RELN promoter was found in patients with schizophrenia compared to controls (p=0.005)
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and also in males compared with females (p=0.004). Subsequently, the RELN expression of the methylated group was 25 fold less than that of the non-methylated group. Based upon the assumption of parallel methylation changes in the brain and peripheral blood, we concluded that RELN DNA methylation might contribute to the pathogenesis of schizophrenia. However, the definite effects of methylation on RELN function during development and also in adult life still require further elaboration. Keywords: RELN; Schizophrenia; DNA methylation
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INTRODUCTION Schizophrenia is a chronic psychiatric disorder that affects approximately 1% of the world’s population; its exact cause remains unknown. Evidence of various genetic defects,
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such as gene mutations, translocation, polymorphisms, and copied numbers, in schizophrenia (Rees et al., 2015) explains only a fraction of the cases (Farrell et al., 2015; Maric and Svrakic, 2012). Historical adoption (Kety et al., 1994) and twin studies (Gottesman and
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Bertelsen, 1989) in schizophrenia have produced unequivocal evidence for genetic heritability in schizophrenia as well as crucial interactions between the candidate genes and
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the environment (epigenetic) for the manifestation of schizophrenia. Epigenetic factors may explain the less than 100% concordance rate for schizophrenia in monozygotic twins; there is still no consensus on the trans-generational inheritance of DNA methylation in humans. Nevertheless, some reports suggest that trans-generational similarity in DNA methylation is attributable to genetic effects (McRae et al., 2014). DNA methylation is among the epigenetic
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mechanisms that have been linked to schizophrenia either as a causative factor or as an effect of the pharmacological approach in the management of schizophrenia (Castellani et al., 2015; Nestler et al., 2015). Methylation studies in schizophrenia have also been conducted either by
2016).
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focusing on selected candidate genes or examining the entire genome (Teroganova et al.,
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RELN (previously, reelin: NC_000007.14 Chromosome 7 Reference GRCh38.p2) is one gene that has consistently been linked with schizophrenia on the basis of its hypothetical functions and its gene variations’ relationship with schizophrenia (Li et al., 2015). Functionally, RELN participates in the migration and positioning of dopaminergic neurons as the brain develops (Nishikawa et al., 2003). A recent report has also reiterated its function in neuron migration during early postnatal development (Sharaf et al., 2015). The earliest direct evidence of RELN’s association with schizophrenia was based on post-mortem studies that
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reported a reduction of up to 50% in the RELN mRNA in several regions of the brains of schizophrenia patients (Impagnatiello et al., 1998; Guidotti et al., 2000). Additionally, the gene’s methylation status determines the mRNA expression of RELN in several types of
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cells, including neuronal cells (Chen et al., 2002). Association studies between RELN and DNA methylation in schizophrenia have produced conflicting but interesting results. The earliest study by Abdolmaleky et al. (2005)
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on the post-mortem brain samples of both normal and schizophrenic patients revealed a significant relationship between the hyper-methylation status of RELN and schizophrenia.
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These findings, however, were not confirmed by a different study that used a pyrosequencing technique (Tochigi et al., 2008) or another recent study that utilized MSP and bisulfite sequencing involving only 29 schizophrenia and 4 normal brain specimens (Alelu-Paz et al., 2015). All these studies apparently lacked statistical robustness as only a limited number of brain samples were analyzed. Furthermore, when DNA methylation as a part of human
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variation (Heyn et al., 2013) is considered, a much larger sample size will be required to identify a definite association between DNA methylation and schizophrenia susceptibility. Unfortunately, few researchers have the privilege of using brain samples.
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Additionally, in some cultures and regions, the donation of the body or organs after death is considered a taboo, which makes it difficult to obtain the brain tissue of patients with
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schizophrenia. Consequently, the use of peripheral blood for a DNA methylation study in living schizophrenia patients could be a better option. It has been reported that some methylation markers were similarly altered in both the brain and the peripheral blood, which suggests a common epigenetic dysregulation in both sites; therefore, the outcome of a study that used peripheral blood will most likely be comparable to a brain tissue study (Auta et al., 2013). The author further proposed that the overall mechanism of epigenetic regulation in peripheral blood lymphocytes and the brain is parallel and these alterations could be a
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primary cause of the illness and not a simply consequence of the disease (Auta et al., 2013). Another independent study suggested that methylation changes in the peripheral blood may mirror the changes in the brain (Aberg et al., 2013). Although extensive methylome profiling
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across the brain and blood has identified highly tissue-specific DNA methylation, there were distinct patterns of DNA-methylation across the brain and the blood that were highly correlated (Davies et al., 2012).
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Our study’s aim was to assess the methylation differences between schizophrenia patients and healthy controls by obtaining DNA from the peripheral blood. This approach
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may provide some clues regarding the status of peripheral RELN methylation and its relationship with schizophrenia. The converted, bisulfite-treated DNA was subjected to a MethyLight Taqman® Assay for highly sensitive and reproducible methylation quantification
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(Eads et al., 2000; Olkhov-Mitsel et al., 2014).
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MATERIALS AND METHODS Ethics approval This study was registered under the National Medical Research Registry of Malaysia
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(NMRR-10-832-6366). The protocol was approved by both the Medical Research and Ethics Committee (MREC), the Ministry of Health in Malaysia and the International Islamic
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University Malaysia (IIUM) Research Ethics Committee (ID no: IREC 466).
Sample collection
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The sample size was calculated using OpenEpi (www.OpenEpi.com) for a sample size that compared two means. If the current study used all previous data on RELN DNA methylation, fewer than 10 samples from both the schizophrenia and healthy control groups would be required for an 80% power of the study at a 95% confidence interval (CI). The size approximation was based on a study by Ikegame et al. (2013), which utilized peripheral
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blood and therefore aimed for a size of 100 schizophrenia cases and 100 healthy controls. At the end of the recruitment period, 110 schizophrenia patients who attended the Psychiatry Clinic at the Hospital Tengku Ampuan Afzan in Pahang who agreed to participate were
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included. The controls (n = 122) were randomly selected from the database of DNA samples of the healthy population archived in the Molecular Research Laboratory of the Department
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of Pathology and Laboratory Medicine at IIUM and were sex- and age-matched to the case subjects. The collection of the normal samples was carried out in a previous study (Norlelawati et al., 2015). A trained psychiatrist diagnosed all patients using the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria for schizophrenia. Patients were required to have had symptoms for at least the past six months, and the psychosis must also not be deemed to be secondary to substance use or neurological disorders. Mentally handicapped patients and those who were younger than 18 years of age were not included.
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The Positive and Negative Syndrome Scale (PANSS) was administered to each patient, whilst other clinical information was retrieved from available medical records.
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DNA extraction and bisulphite modification Genomic DNA was extracted from whole-blood samples (approximately 5 mL) using a Gentra Puregene Blood Kit (Qiagen, Germany) following the manufacturer’s protocol. The
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DNA concentration was measured by a Qubit® 3.0 Fluorometer (ThermoFisher Scientific, US). Universal Methylated and Non-Methylated Human DNA Standard (Zymo Research,
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US) were used as the 100% methylated and 0% methylated controls, respectively. The DNA concentrations of both control samples were also verified using a Qubit® 3.0 Fluorometer (ThermoFisher Scientific, US). Two µg of genomic DNA, universal methylated and nonmethylated DNA were treated with sodium bisulphite modification using a Zymogen EZ DNA Methylation Gold Kit (Zymo Research, US) as per the manufacturer’s instructions. A
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30-µl M-Elution buffer was used for the final elution step. The bisulphite-converted DNA was then diluted to a final concentration of 10 ng/µl.
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MethyLight primer and probe sequences
The primers and probe were designed specifically for the targeted gene, whilst the primer and
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probe for ALU as the reference gene was based on the study by Olkhov-Mitsel et al. (2014). The primer and probe for RELN were developed using the MethyLight Primer Express v 1.0 (Applied Biosystems, US) and Methprimer (http://www.urogene.org/methprimer/) (Li and Dahiya, 2002) for CpG island prediction as well as the preliminary selection of the primer sequence based on methylated methyl-specific primer (MSP) tools. The primer sequence was determined using the protocol of Wojdacz et al. (2008), which proposed a proportional amplification of both methylated and unmethylated templates of bisulphite-modified DNA.
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The probe was designed based on the basic property requirement of Taqman probes. The promoter sequences for RELN were retracted from the ensemble genome browser (www.ensemble.org) (RELN: EN SG00000189056). The details of the primers and probe for
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RELN and the reference ALU (Olkhov-Mitsel et al., 2014) are shown in Table 1, whilst the flanking sequence and the available CpG islands are shown in Figure 1. All primers and
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Determining the assay efficiency and MethyLight assay
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probes were bundled together as PrimeTime®qPCR Primers (https://www.idtdna.com/).
To assess the assay’s efficiency, the converted DNA from both control samples was prepared according to the protocol suggested by Olkhov-Mitsel et al. (2014). The efficiency of the MethyLight assay was tested by analysing both the ALU and RELN assays for a decreasing amount of methylated DNA. For this process, 70 ng of bisulphite-converted universal
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methylated DNA and 140 ng of universal non-methylated DNA were mixed and serially diluted into three-fold increments from 1:3 (1.67 ng/µl) up to 1:19683 (0.0003 ng/µl). The 10 µl polymerase chain reaction (PCR) consisted of 2 µl of each dilution of DNA, a 1X
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concentration of 2X SensiFAST™ PROBE mix (Bioline, UK) and a 1X PrimeTime®qPCR Primers mix (IDTDNA, US) that was run in triplicate on a BioRad CFX96™ Real-Time
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System with polymerase activation at 95°C for 10 minutes, followed by denaturation at 95°C for 10 seconds and annealing and extension at 60°C for 30 seconds. The denaturation and annealing/extension were repeated for 40 cycles. The stability of the ALU reaction, which was chosen as the control reference in the MethyLight assay, was validated by calculating the coefficient of variation (CV) of the reactions involving the methylated DNA of schizophrenia cases run on a single 96-well plate. The formula for calculating the CV% is (standard deviation/mean) x 100%.
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The same PCR reaction protocol was applied to run the samples. In brief, the 10 µl qPCR reaction mixture contained 2 µl of bisulphite-converted DNA (20 ng), 5 µl of the SensiFAST™ Probe, 2.5 µl of nuclease-free water and 0.5 µl of 20X PrimeTime® probe and
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primer mix. The reaction utilized a 96-well PCR plate and was run on the BioRad CFX96™ real-time PCR (RT-PCR) platform with an initial denaturation at 95°C for 10 minutes, followed by 60 cycles at 95°C for 10 seconds and 60°C for 30 seconds. The 60 cycles were
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extended from the initial 40-cycle optimization steps to cover minimal amplification copies. The same 96-well PCR plate contained DNA from the samples, controls and the 100%
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Universal Methylated DNA reference. Each sample’s Cq values for the target and reference gene were obtained to calculate the DNA methylation percentage ratio based on the formula proposed by Olkhov-Mitsel et al. (2014), which was adapted from Eads et al. (2000). The formula is [(RELN/ALU) sample/(RELN/ALU) Universal Methylated Human DNA] x
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100%.
Analysis of RELN expression by relative quantitative RT-PCR After the methylation percentage of the RELN gene had been determined, samples of
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schizophrenia cases that represented a high methylation status and a low methylation status were chosen for the determination of the RELN mRNA expression. The blood samples of
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selected cases that had been stored in RNAlater were traced and subjected to RNA purification using a RiboPure™-Blood Kit (ThermoFisher Scientific, US) according to the manufacturer’s protocols. In each extract, the yield of the RNA was established by its absorbance at 260/280 nm. Samples with a ratio below 1.8 were rejected. The integrity of the RNA was assessed using denaturing agarose gel electrophoresis by evaluating the sharpness of the two ribosome RNA bands (28s and 18s). Prior to cDNA synthesis, the total RNA concentration of all purified RNA was standardized to a concentration of 25 ng/µl and treated
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with DNAase 1 (BioRad) to eliminate any genomic DNA contamination. The cDNA was synthesized using iSript™ Reverse Transcription Supermix (Bio-Rad, US) following the manufacturer’s protocol with 125 ng RNA for each sample. The primer for the targeted gene,
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RELN (Hs_RELN_1_SG QuantiTect Primer Assay (QT00025592), and two reference genes, GAPDH (Hs_GAPDH_1_SG Quanti Tect Primer Assay (QT00079247)] and ACTB [Hs_ACTB_1_SG Quanti Tect Primer Assay (QT00095431)], were chosen from a database
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of pre-designed QuantiTect Primer Assays (Qiagen, US) (www.qiagen.com/geneglobe/). The cDNA was then used in a quantitative RT-PCR experiment undergoing the SsoFast™
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EvaGreen® Supermix (BioRad) reaction in a 96-well plate on the CFX-96 BioRad real-time platform. For each gene [two reference genes (ACTB and GADPH) and one target gene (RELN)], a standard curve of six 1-in-10 dilutions of mixtures of all samples of cDNA was assayed followed by a melting curve analysis that was set up to run from 90°C to a 50°C decrement. At the same time, the gene expression of the methylation status groups (the
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low/un-methylated vs. the methylated group) was measured to determine the relative quantitation of gene expression using RT quantitative PCR with the same instruments and reagents. The quantitation utilized the mean Cq value for each group and calculated this value
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according to the comparative Ct method (∆∆Ct method) proposed by Pfall (2001).
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Statistical analyses
All the statistical analyses were performed using the Statistical Package for the Social
Sciences (SPSS), version 22. The demographic data, including age, sex, and race, were calculated using descriptive statistics. The categorical data were presented as frequencies and percentages (%). The numerical data were reported as the mean and standard deviation (SD) along with a 95% confidence interval (95% CI). An analysis of covariance (ANCOVA) test was utilized in both analyses to compare the RELN methylation percentage between
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schizophrenia patients and controls and also to examine the relationship of several factors in schizophrenia. The percentage methylation ratio (PMR) is presented as the estimated marginal mean (EMM) (adjusted for covariates) with the 95% CI. Predictions of certain
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value <0.05 was considered statistically significant.
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variables of RELN methylation were assessed through multiple regression analyses. A p-
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RESULTS Demographic characteristics This study included 122 healthy controls and 110 schizophrenia cases. There were no
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significant differences in age, sex or race between the healthy controls and the schizophrenia patients. The detailed demographic characteristics of both groups are summarized in Table 2.
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Assay efficiency and validation of the MethyLight experimental conditions
The amplification plots of ALU and RELN that have been serially diluted in three-fold
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increments (from 1:3 to 1:19683) of bisulphite-modified methylated DNA are shown in Figure 2. The ALU and RELN reactions exhibited decreasing detection levels of methylated alleles in subsequent dilutions, as indicated by the increasing cycle number at which each reaction signal crossed the detection threshold. The ALU control reaction sensitivity of detection was the 1:19683 dilution (0.00005 ng). In contrast, the sensitivity limit of RELN
methylated DNA.
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methylation was only up to the 1:27 dilution, which is estimated to contain 0.37 ng of
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For the coefficient of variation of the ALU reaction, the Cq value of the ALU reaction was used to calculate the standard deviation and mean. A good CV (<20%) was achieved for
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all the plate assays. The CV% ranged from 6.4–17.0%, with a mean CV% of 8% (The MethyLight was run on seven different assay plates). An example of an ALU reaction on one plate assay and its corresponding CV% is illustrated in Figure 3, which involved 45 tested samples (23 controls and 23 schizophrenia patients).
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Percentage methylation ratio of RELN in schizophrenia. All bisulphite-treated DNA samples of the cases and controls were successfully amplified for RELN and the reference ALU. The PMR is the ratio of methylation copies of a
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sample against a commercially known reference [(Universal Human Methylated DNA (Zymo, US)] that is presumed to provide 100% copies of methylated DNA. In this study, the target RELN amplification sites contained eight CpG spots (Figure 1), and the probe was
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used to cover one CpG spot. Our study found a significant difference of the percentage methylation ratio between the cases and controls (p=0.005); the mean PMR was higher in
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schizophrenia patients [1.39 (1.37-1.41)] than it was in the controls [1.35 (1.33-1.37)] (Table 3).
Relationship between DNA methylation with age and sex
The relationship between DNA methylation levels and confounding factors (age and sex) was
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tested in the controls. There was no significant correlation between the DNA methylation level and age (Pearson correlation; p=0.445). Similarly, there was no difference in the DNA methylation value between both sexes in the control participants (independent t-test; p=0.482,
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t= -0.705, df=120). A similar insignificant relationship of age (Pearson correlation; p= 0.567) and sex (independent t-test; p=0.341) with a methylation level was also noted among the
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schizophrenia participants.
Subgroup analysis in schizophrenia. The analysis of the DNA methylation level in a specific subgroup of the schizophrenia patients found a significantly higher DNA methylation value in male schizophrenic patients compared to healthy controls [1.40(1.38-1.43) vs 1.34(1.32-1.36), p=0.001]; this level was insignificant among females [1.38(1.34-1.41) vs 1.36 (1.32-1.40); p=0.467] (Table 3).
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Further analysis revealed that the DNA methylation value has no relationship with the patient’s smoking status or the type of schizophrenia (Table 4). There were also insignificant correlations between the DNA methylation level and the age of patients and the PANSS
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dimension score of schizophrenia (Table 5).
RELN mRNA expression
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Since the percentage methylation ratios of all cases were below 2.00, six schizophrenia cases with a PMR of more than 1.70 (methylated) and three cases with a PMR less than 1.20
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(unmethylated) were chosen to analyse the mRNA expression. There was significant down regulation of the RELN mRNA expression in the group of methylated schizophrenia samples
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relative to those with unmethylated DNA (Figure 4).
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DISCUSSION The existence of an epigenetic contributor to the etiology of schizophrenia was proposed during the past decade and has gained experimental support. However, the
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epigenetic data on schizophrenia are scarce and have mostly been derived from gene-specific studies involving brain tissue (Nishioka et al., 2012), which is virtually inaccessible in living patients. Therefore, studies of DNA methylation in schizophrenia patients are still limited,
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and the majority has been conducted in a small sample size of patients (Zong et al., 2015). Walton et al. (2016) used the temporal lobe of the brain in epilepsy patients and their
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corresponding peripheral blood samples to investigate the feasibility of blood samples as a surrogate marker for the brain. He suggested that some subsets of peripheral methylation data may serve as a proxy to the methylation status of brain tissue. Walton et al. (2016) also reported that the altered methylation profiles in schizophrenia involved pathways related to precursor metabolites and signaling peptides. Additionally, a number of epigenetic studies
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that targeted psychiatric diseases have proposed that epigenetic changes are not limited to post-mortem brain tissue but can also be detected in other peripheral tissues, such as blood, urine, and saliva (Carrard et al., 2011; Dempster et al., 2013; Melas et al., 2012). There was
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evidence of the broad impact of maternal rearing on DNA-methylation in both the brain and in the T-cells of Rhesus Macaque, which supported the suggestion that environmental insults
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are systemic, affect the entire genome, and persist into adulthood (Provencal et al., 2012). The methylome-wide approach study by Davies et al. (2012) reported that distinct patterns of DNA-methylation across the brain and the blood are highly correlated. In addition, a study by Klengel et al. (2013) on the relationship between genes and childhood trauma suggested that demethylation has a global effect on the function of both immune cells and brain-associated areas.
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One note of caution is that the peripheral blood cannot entirely substitute for the complex nature of brain tissue and its cell constituents. There are higher degrees of DNA methylation variability between the cerebellum, cortex, and peripheral blood than there are
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for the variability between different cortical regions (Marzi et al., 2016), with the correlation of selected variables being closer between BA9 and the peripheral blood than those for the cerebellum and peripheral blood (Marzi et al., 2016). Microglia, which have been attributed
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to the neuroinflammatory (Monji et al., 2013) and neurodevelopmental (Frick et al., 2013) hypotheses of schizophrenia, are probably more similarly related to blood than neuronal cells
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since earlier investigations described their origin from blood monocytes that had differentiated from hemopoietic cell precursors (Ginhoux et al., 2013). Thus, irrespective of whether there are similar changes in both the brain and blood, the differences in RELN methylation between the cases and controls in our study could indicate a unique feature of schizophrenia, a peripheral biomarker, or be related to a particular treatment.
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Previous studies have detected RELN proteins and mRNA during both development and adulthood in the blood and other peripheral organs (Smalheiser et al., 2000). Although the increased non-neuronal RELN expression has been well documented in
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hepatic (Kobold et al., 2002) and ocular (Pulido et al., 2007) injuries, an event that leads to RELN expression in the blood is not well established. There could be a connection between
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RELN and the immune system; an earlier study reported a higher expression of RELN in plasma cells (the mature form of B-lymphocytes) than in the precursor B-lymphocyte cells (Underhill et al., 2003). If epigenetic methylation regulation between the brain and the peripheral blood is parallel (Auta et al., 2013), the methylation status of the RELN in the peripheral blood could be used to reflex for its role in schizophrenia. Our study assessed the methylation differences between schizophrenia patients and healthy controls using the peripheral blood as the DNA source, while the possible effects of methylation on RELN
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function were assessed through relative gene expression. These approaches may provide some clues about the status of peripheral RELN methylation and its relationship with schizophrenia.
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The relationship between RELN and schizophrenia is based on several functional observations that Reelin, the protein encoded by the RELN gene, is crucial in brain development as this protein plays a role in several brain processes, such as the extension of
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axons and dendrites that are essential for the transmission of nerve impulses (Curran and D'Arcangelo, 1998; D’Arcangelo, 2014). It is also known that unmethylated CpGs are
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usually clustered together in the ‘CpG Islands’ found in the promoter region of many genes; thus, it is predicted that DNA methylation plays an important role in regulating gene expression in view of its role in gene transcription (Bird, 1986; Lim and Maher, 2010). Although methylation and gene expression are often correlated, there have not always been in opposite directions than the promoter CpG (Wagner et al., 2014).
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In this study, we detected a significantly higher level of DNA methylation at the CpG sites of the RELN promoter in schizophrenia patients compared to the controls. This finding was compatible with the studies of Abdolmaleky et al. (2005) and Grayson et al. (2005),
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although both used non-quantitative, methyl-specific PCR (MSP) to determine the methylation, and their study sample size was only about 10 brain tissues each from the
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controls and the schizophrenia patients. In contrast, two additional studies reported insignificant findings (Alelu-Paz et al., 2015; Tochigi et al., 2008). Again, both studies had limited brain tissues available. Tochigi et al. (2008) utilized a quantitative pyrosequencing approach and reported that DNA methylation in both schizophrenics and in control participants was less than 5%, which was similar to our findings. Although the current study used a different approach for quantitation, we found that the DNA methylation levels of both the schizophrenia cases and controls were very low but were significantly higher in patients
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with schizophrenia. Subsequently, the effect of DNA methylation on the functional expression of the RELN gene was assessed. It was found that the RELN expression of samples with a higher methylation level was much depressed relative to those with lower
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methylation values. Therefore, this finding supported the theory that DNA methylation of the RELN promoter sites affected gene expression. It is therefore postulated that epigenetic DNA methylation of the RELN gene participates in the aetiology and pathogenesis of
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schizophrenia.
It is generally acknowledged that DNA methylation is influenced by multiple factors,
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such as age, sex, ethnicity or even the early life economy status of healthy control participants (Lam et al., 2012). Our study found no significant relationship for either age or sex according to the DNA methylation levels in the controls and in the schizophrenia patients. However, there were significantly higher DNA methylation values in male patients with schizophrenia compared to the healthy male controls. It was also noted that female
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patients with schizophrenia had a higher level of DNA methylation compared to the controls, but the difference was not statistically significant. As males provided a better sampling power (160 males vs. 72 females), any further conclusions regarding sex-dependent methylation
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differences may require a better sampling representation. In adults, it was suggested that the down regulation of RELN-integrin interaction is
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the basis for the decrease in dendritic spine densities in psychiatric patients (Rodriguez et al., 2000). Dendritic spines are considered the central highways of synaptic connections (Sala and Segal, 2014). Given that dopamine D2 and serotonin 5-HT2A receptors are influential in the development of schizophrenia symptoms and that RELN expression maybe reduced as a consequence of hypermethylation, our study attempted to determine the association of RELN methylation levels with the psychological symptoms of schizophrenia. However, we found no correlations between the RELN methylation levels and the psychological symptoms of
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schizophrenia. Nevertheless, it is likely too early to state that these findings reflect the actual association of RELN methylation levels and the psychological symptoms of schizophrenia since our samples were mainly obtained from patients who were currently taking psychiatric
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medications. Furthermore, our samples likely contained other confounding factors of DNA methylation as described by Nishioka et al. (2012). In addition, the effects of drugs on the methylation level require further clarification since studies among bipolar disorder patients
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have found that some anti-psychotics were not associated with DNA methylation signatures (Houtepen et al., 2016). In a study that assessed the expression of 11 genes related to
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neurotransmitters or neurodevelopments (RELN was not included), it was found that the majority of the genes showed an insignificant difference of mRNA expression between schizophrenia patients and healthy controls (Ota et al., 2014). It thus advisable to conduct a specific study to assess the mRNA expression of RELN in untreated patients who are also naïve to anti-psychotics and consequently assess their relationship with DNA methylation
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values.
There are several limitations to our study. Melas et al., (2012) reported a relationship between peripheral leucocytes DNA methylation and anti-psychotic medication. The effects
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of anti-psychotic medications on DNA methylation must be considered because our participants included many stable schizophrenia patients; the outcome of this study might
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have been different if it were conducted using schizophrenia patients who were antipsychotic-free. However, this option was not explored due to sampling accessibility and difficulty procuring acute schizophrenia patient samples. The medication data obtained from the participants were also complex and challenging for the multivariate analyses. With regard to the methodology, although the MethyLight approach was robust, sensitive, and highly specific (Trinh et al., 2001; Zhang et al., 2010) for the DNA methylation quantification, it was only able to cover a few CpG islands per run. In our study, the methyl probe only
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covered one CpG island. However, this method is the most suitable for a high-throughput assay, which was conducted in our study (Zhang et al., 2010). In conclusion, we identified a difference in the DNA methylation of the RELN
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promoter in the peripheral blood of patients with schizophrenia. As a result, the mRNA expression of RELN in those with a high amount of methylation was relatively suppressed compared to those in the low methylation group. Although the definite effects of methylation
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on RELN function during development and also in adult life will require further elaboration and studies that include actual brain tissues and should be guided by the assumption of
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parallel methylation changes in both the brain and peripheral blood, we suggest that an
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epigenetic aberration of RELN may contribute to the pathogenesis of schizophrenia.
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Funding source The study is funded by the Fundamental Research Grant Scheme (Grant No: FRGS-14-101-
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0342) provided by the Ministry of Education, Malaysia.
Contributors
Norlelawati designed the study. Nabil, Nour el Huda, Hanisah and Kartini conducted Norlelawati and Nabil conducted the statistical analyses.
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sample and data collection.
Norlelawati and Nabil wrote the manuscript. All co-authors provided critical feedback on the
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manuscript, suggested additional analyses and critical revisions, and edited the manuscript for clarity and precision. All authors contributed to and approved the final manuscript.
Conflict of interest
The authors have no conflicts of interest that are directly relevant to the content of this
Acknowledgment
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manuscript.
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The authors thank staff and patients of Psychiatry Clinic, Tengku Ampuan Afzan Hospital,
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Kuantan, Pahang & Molecular Research Laboratory, Kulliyyah of Medicine, IIUM.
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Table 1: Primer and probe sequence used for the MethyLight assay Primer Names
Sequence (5’-3’)
ALU sequence
ALU-F ALU-R ALU-probe
GGTTAGGTATAGTGGTTTATATTTGTAATTTTAGTA ATTAACTAAACTAATCTTAAACTCCTAACCTCA /56-FAM/CCTACCTTA/Zen/ACCTCCC/3IABkFQ/
RELN
RELN-F AGATAAAGAAATCGCCGTTAGCG CACCTCCCGTCCAACTATCTAAA RELN-R RELN-probe /56FAM/ACCAACCCC/ZEN/TTTAACCGTCAATATACCCT/ 3IABkFQ/
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Table II: A comparison of the demographic data from the control and schizophrenic subjects Schizophrenia (n = 110) n (%)
p-value
Sex Male Female
89 (73.0%) 33 (27.0%)
71 (64.5%) 39 (35.5%)
0.167
Race Malay Chinese Indian
112 (91.8%) 8 (6.6%) 2 (1.6%)
99 (90.0%) 7 (6.3%) 4 (3.6%)
0.633
Control (n = 122) Mean (SD)
Schizophrenia (n = 110) Mean (SD)
p-value
40.26 (8.38)
0.052
Age
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Control (n = 122) n (%)
Variables#
37.92 (9.76)
Chi-square test, +Independent Sample T-Test (p-value < 0.05 is taken as statistically significant at a 95% confidence interval).
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Table III: Differences in the percentage methylation ratio (PMR) between schizophrenia patients and healthy controls. PMR EMM (95% CI)
F-stat (df)
Patients (110)
1.39 (1.37–1.41)
Controls (122)
1.35 (1.33–1.37)
7.960 (1.00)
Males Patients (71)
1.40 (1.38–1.43)
Controls (89)
1.34(1.32–1.36)
Females Patients (39)
1.38 (1.34–1.41)
Controls (33)
1.36 (1.32–1.40)
0.005
0.001
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11.70 (1)
p-value
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Fixed factors (n)
0.467
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0.536 (1)
ANCOVA test, n = number of participants, EMM = estimated marginal means, CI = confidence interval, F-stat = F statistic; df = degree of freedom. Adjusted for age, sex, and race. Statistical significance was set at p<0.05 with a 95% confidence interval.
factors in schizophrenia
PMR EMM (95% CI)
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Table IV: The relationship between the percentage methylation ratio (PMR) and several
Smoking status*
Smoker (59)
1.38 (1.35–1.41)
Non-smoker (51)
1.39 (1.35–1.42)
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Types of Paranoid (37) schizophrenia ** Disorganized (40)
F-sat (df)
p-value
0.046 (1)
0.831
1.102 (4)
0.360
1.40 (1.36–1.43) 1.40 (1.36–1.43)
Catatonic (2)
1.32 (1.17–1.47)
Residual (13)
1.36 (1.31–1.42)
Undifferentiated disorder (18)
1.35 (1.30–1.40)
ANCOVA test, n = number of participants, PMR = percentage methylation ratio, EMM = estimated marginal means, CI = confidence interval, F-stat = F statistic; df = degree of freedom. Adjusted for age, sex, race, body mass index, and type of schizophrenia* or smoking status**. Statistical significance was set at p<0.05 with a 95% confidence interval.
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Table V: The PANSS five factor domains, age, and BMI predictions for the percentage methylation ratio Model 1
Coefficients Predictors SE
t
p
R2
Adjusted R2
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B -0.001
0.006
-0.178
0.859
Negative
-0.004
0.003
-1.095
0.276
0.002
0.004
0.703
0.484
-0.010
0.006
-1.793
0.010
0.005
1.962
Age
-0.001
0.001
-0.574
0.567
0.003
-0.006
BMI
0.004
0.002
2.702
0.008
0.066
0.057
Excited Depressed
0.040
0.076
0.052
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Disorganized
0.084
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Positive
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Regression analyses: PANSS: Positive and Negative Syndrome Scale; BMI = body mass index; SE = standard error; R2: coefficient of determination. Significance was set at p<0.05.
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Figure 1: The forward, reverse and probe sequences selected for the RELN MethyLight assay. The parameters for the CpG island search include Window: 200; Window shift: 1bp; Obs/Exp CpG: 0.6 and GC%: 50.0. http://www.urogene.org/methprimer/.
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Figure 2: Amplification plots for ALU and RELN serially diluted in three-fold increments of A: ALU and C: RELN show a decreasing reaction (increasing cycle reaction) in
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subsequent dilutions. D: RELN sensitivity (D) is limited to only the 1:27 dilution as compared to the B: ALU sensitivity, which reached a full 1:19683 dilution. Both reactions exhibited an R2 of >90%.
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Figure 3: A: Amplification plots for the ALU reaction for 45 samples (run per-plate assay) where the mean Cq values for control participants and schizophrenia patients were 13.6 (SD=1.05) and 14.5 (SD=1.36), respectively. The calculated CV% was 7.7% for the controls
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and 9.4% for the schizophrenia patients. The combined CV% for both samples was 9.1%.
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1.
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0.00
-9.38
-18.75
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RELN Regulation Threshold
9.38
-25.12
-28.13
Methylated
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Unmethylated
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Figure 4: Gene expression of RELN. The RELN expression was normalized to GAPDH and ACTB in unmethylated (low PMR<1.20) and methylated (PMR>1.70) peripheral blood mRNA of schizophrenia samples. The differences between groups were tested using an unpaired t-test. Significant down-regulation was observed (p=0.020).