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Determination of genetic changes in etiology of autism spectrum disorder in twins by whole-exome sequencing
Gene Reports 19 (2020) 100618
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Determination of genetic changes in etiology of autism spectrum disorder in twins by whole-exome sequencing
T
Ceyda Hayretdag (M.D., M.D.)a, Pinar Algedik (M.D.)b,d, Cumhur Gokhan Ekmekci (M.D., Ph.D.)c, Ozlem Bozdagi Gunal (M.D., Ph.D.)d, ⁎ Umut Agyuz (M.Sc.)e, Halime Yildirim (M.Sc.)f, Ender Coskunpinar (Ph.D.)d,f, a
Department of Anatomy, School of Medicine, University of Health Sciences, Istanbul, Turkey Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey c LABGEN, Acibadem University, Istanbul, Turkey d Department of Psychiatry, New Jersey Medical School, Rutgers University, USA e Genz Biotech Inc., Ankara, Turkey f Department of Medical Biology, School of Medicine, University of Health Sciences, Istanbul, Turkey b
A R T I C LE I N FO
A B S T R A C T
Keywords: Autism spectrum disorders Genetic mutation Monozygotic Whole exome sequencing FMN2 KCNQ2 NOTCH3 TMRC6A SHANK3 SLC6A4
Twin studies provide strong evidence that genetic factors have a major role in the etiology of autism spectrum disorder (ASD) but in most patients the underlying genetic cause of the disease is unknown. Here we used wholeexome sequencing to study genome-wide differences in twins with autism in order to reveal the genetic changes responsible for the etiology of autism. DNA was isolated from peripheral blood samples from six monozygotic twins and one dizygotic twin and analyzed by OneSeq protocol, on an Illumina NextSeq platform. Bioinformatics analyses have revealed 110 disease-related genes, and after further filtering, we have identified 44 single nucleotide polymorphisms (SNPs). Functional network analysis has identified significant associations for 6 different genes, including known ASD candidate genes: FMN2, KCNQ2, NOTCH3, TMRC6A, SHANK3, and SLC6A4. Our results provide an independent evidence for known ASD genes and highlight other genes, which will further improve the understanding of the genetic basis of ASD.
1. Introduction Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized with impaired communication and mutual social interaction, restricted, repetitive, and stereotyped behavior (DSM-5, 2013). The symptoms arise early in life and may last throughout life (Lord et al., 2020). This phenomenon is a widespread neuropsychiatric condition affecting one out of every 59 children (Baio et al., 2018). As a multifactorial disease that both environmental and genetic factors take part in pathogenesis (Chakrabarti and Fombonne, 2001) high accuracy
detection of underlying genomic mechanisms of ASD is essential for understanding the etiology and create new treatment protocols. With the large-scale detection techniques in recent years, different genomic regions have been recognized having common variants associated with the disorder. Structural differences or copy number variations (CNV) occur in the regions where the examined genome differs from the reference genome as long sequences (> 50 bp) (Pang et al., 2010). These structural variations include insertions, deletions, inversions, and duplications. Whole exome sequencing provides a high-resolution sequencing of the genome and captures both large and small variants that
Abbreviations: ABC, Autism Behavior Checklist; ASD, Autism Spectrum Disorder; BAFME, Benign Adult Familial Myoclonic Epilepsy; CADASIL, Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy; CARS, Childhood Autism Rating Scale; CDF, Computable Document Format; CNV, Copy Number Variation; CRISPR, Clustered Regularly Interspaced Short Palindromic Repeats; DSM-V, Diagnostic and Statistical Manual of Mental Disorders-V; DZ, Di Zygotic; EAE, Experimental Autoimmune Encephalomyelitis; FCMTE, Familial Cortical Myoclonic Tremor with Epilepsy; FMN, Formin; GW, Genome Wide; KCNQ, Potassium Voltage-gated Channel Subfamily Q member; MS, Multiple Sclerosis; MZ, Mono Zygotic; NOTCH, Neurogenic locus notch homolog protein; OD, Optical Density; OMIM, Online Mendelian Inheritance in Man; PMDS, Phelan McDermid Syndrome; PTSD, Post-Traumatic Stress Disorder; rSID, reference SNP Identification number; SCQ, Social Communication Questionnaire; SHANK3, SH3 and Multiple Ankyrin Repeat Domains 3; SLC6A4, Solute Carrier Family 6 Member 4; SNP, Single Nucleotide Polymorphism; VCF, Variant Call format; WES, Whole Exome Sequencing ⁎ Corresponding Author: Ender Coskunpinar, Department of Medical Biology, School of Medicine, University of Health Sciences, Istanbul, Turkey E-mail addresses: [email protected] (C. Hayretdag), [email protected] (P. Algedik), [email protected] (C.G. Ekmekci), [email protected] (O.B. Gunal), [email protected] (U. Agyuz), [email protected] (H. Yildirim), [email protected] (E. Coskunpinar). https://doi.org/10.1016/j.genrep.2020.100618 Received 28 January 2020; Accepted 30 January 2020 Available online 01 February 2020 2452-0144/ © 2020 Published by Elsevier Inc.
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Table 1 Characteristics of cases.
Table 3 The study's protocol used with Covaris system.
Twin pairs
Age
Gender
Epilepsy
Language delay
Premature
Birth weight
Twin pair 1
7 7 8 8 9 9 13 13 5 5 10 10 6 6
M M F F M M M M F F M M M M
No No No No No No No No No No No No No No
Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
No No Yes Yes No No Yes Yes Yes Yes No No Yes Yes
2240 2260 2100 2000 2250 2450 2740 2680 2100 2400 2600 2800 2580 2640
Twin pair 2 Twin pair 3 Twin pair 4 Twin pair 5 Twin pair 6 Twin pair 7
Setting
Value
Duty factor Peak Incident Power (PIP) Cycles per burst Treatment time Bath temperature
10% 175 200 360 s 4° to 8 °C
identified genetic variations that will enhance our understanding of ASD etiology. Comprehensive analysis of relevant copy number changes that might play a role in phenotypic differences will help to generate a list of interesting candidates for future studies and identify the relationship between genetic variation and ASD risk factors. The elucidation of etiopathogenesis is also important in terms of planning appropriate treatment, giving genetic counseling on the course of the disease and the risk of recurrence.
might otherwise be missed. The use of monozygotic (MZ) twins is known to be a very strong strategy in the identification of de novo and hereditary CNVs. Especially using concordant and discordant monozygotic twins with ASD is a strong strategy to define de novo and genetic CNVs (Laplana et al., 2014a). In addition to rare CNVs, single nucleotide polymorphisms (SNPs) have been reported to be associated with autism and may share molecular etiology with schizophrenia (Shaw et al., 2014). Recent studies of copy number analysis have discovered several new variants associated with autism and identified genetic risk loci that involve some candidate genes that can be linked to ASD pathophysiology (Noroozi et al., 2016; Glessner et al., 2014; Safari et al., 2017). Also, it has been thought that coexistence of risk factors is associated with ASD intensity, too. It is thought that because of the same DNA structure in MZ twins after pairing, has seen all phenotypically differences caused by effects of environmental factors except for de novo mutations (Losh et al., 2012). Although the rates for shared genetic and environmental effects in twins vary between studies (Hallmayer et al., 2011; Frazier et al., 2014) in MZ twins with ASD, several studies support a strong genetic effect between 40 and 90%. Especially Frazier et al. have shown that if one MZ twin has ASD, the other twin has a 76% chance for being diagnosed with ASD and more likely to have similar levels of ASD related symptoms (Frazier et al., 2014). Therefore, since MZ twins share 100% of their genetic material and the concordance rates in MZ twins for autism are significantly higher than DZ twins or siblings (Frazier et al., 2014; Ozonoff et al., 2011; Rosenberg et al., 2009; Taniai et al., 2008), genetic studies in MZ twins will provide valuable information to identify genetic components related to autism symptoms. In this study by using whole genome sequencing in a monozygotic and dizygotic twin population of 7 twin pairs we
2. Material and methods 2.1. Study subject information Six autistics monozygotic (MZ) twins and one dizygotic (DZ) twin with unaffected parents were included in this study. The study was approved by the Ethics Committee for Clinic Research of Umraniye Training and Research Hospital (13604-06.20.2017). Written informed consent was obtained from all participants and/or their families. Seven out of the ten contacted families that had ASD twins in different provinces accepted to participate in our study. Three of the families refused to participate due the necessity of taking blood samples. From our patient group, six pairs of concordant MZ twins and a pair of concordant DZ twin diagnosed with ASD were evaluated clinically with their parents in the Umraniye Training and Research Hospital, University of Health Sciences, Turkey. Child psychiatrist with more than eight years of experience diagnosed the twins with ASD according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) (DSM-5, 2013). Sociodemographic data form was composed by the authors and covered comprehensive development history of the twins was taken from the families. Previous medical records were reviewed. Observation notes and videos of special education teachers were collected. According to the detailed medical history and clinical observations, all patients had delayed speech; four pairs of them had premature delivery. None of the patients had epilepsy or any other genetic disease (Table 1). Additionally, Childhood Autism Rating Scale (CARS), Autism Behavior Checklist (ABC) and Social Communication Questionnaire (SCQ, current version) were acquired (Table 2). Based on scores reported by Chebowski et al., the severity of autism symptoms
Table 2 Total CARS and SCQ Scores (according to CARS scoring patients with numbers 3, 4, 6 have severe autism, patients with numbers 1,2,5,7 have mild-moderate autism). Twin pairs
Total CARS score
Total SCQ score
ABC sensory
ABC relating
ABC stereotypes and object use
ABC language
ABC self-help and social
Total ABC score
Twin Pair 1
33,5 32,5 35 33 37 37 57,5 45,5 31 29 42,5 41,5 30 31,5
21 20 23 21 25 26 33 30 17 16 28 28 16 17
10 6 5 5 9 9 15 11 4 4 11 11 0 0
13 10 11 7 14 14 28 25 3 3 22 22 6 9
3 6 13 8 11 11 34 28 3 3 17 17 8 13
18 18 14 12 19 24 8 8 13 0 18 18 12 12
10 8 10 9 18 15 20 17 12 7 15 15 3 10
54 48 53 41 71 73 105 89 37 24 83 83 29 44
Twin Pair 2 Twin Pair 3 Twin Pair 4 Twin Pair 5 Twin Pair 6 Twin Pair 7
2
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Fig. 1. Bioanalyzer 2100 results as quality control to after Covaris study. 3
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Fig. 2. Electropherogram images of DNA fragments.
disease-related genes from Agilent SureSelect Focused Exome Panel. Firstly, enrichment process for Illumina matched end sequencing was conducted with using of OneSeq target enrichment kit in our study. Genomic libraries were prepared for each sample using Covaris e220 or s220 device and genomic DNA samples were 150–200 bp fragmented (Table 3). For quality measurement 2100 Bioanalyzer device and High Sensitivity DNA chip and reagent kit were used. All samples had an electropherogram distribution peak between 120 and 150 bp end of the study (Fig. 1). Sure Select XT Library Prep Kit ILM was used for repairing tips. After end repair, AMPure XP beads were introduced for the selection of the desirable DNA fragment. After the amplification process, Bioanalyzer 2100 was used to see how many bp the DNA fragments are in. As a result of these study electropherogram images of DNA fragments were obtained in between 225 and 275 bp (Fig. 2). For hybridization, required sample concentration was 750 ng, with a volume up 3.4 μL. to 221 ng/uL was required in each 1 μL. At this stage for the purpose of setting sample volume using vacuum concentrator (min ≤ 45 °C) with the Hyb 1, 2, 3 and 4 reagents, Master Mix was prepared and waited for 5 min at 65 °C. Then Sure Select Block Mix was prepared. RNAse Block dilution was made and this mix was incubated with PCR cover heated to 105 °C with mixing at the specified rates at 65 °C for 24 h. All samples were then bead selected using Sure Select Target Enrichment Box-1 and Streptavidin bound beads. Magnetic beads were homogeneously mixed and 50 μL added for each tube, and 200 μL SureSelect Binding Buffer added on it. Tubes were placed on a magnetic stand. When samples were cleaned the supernatant part was separated. This washing process performed 3 times in total. Lastly 200 μL Binding. Buffer was added again and vortex, spin performed and transferred to new tubes. After capturing of hybridized DNA sample, preparation for indexing and multiple sequencing were performed according to NGS protocol (Fig. 3). Each created library was loaded to Illumina NextSeq 2 × 150 bp platforms. Data analyzed with Agilent SureCall Software v3.0 after enough coverage and depth was achieved.
using total CARS score is over 25.5. The sensitivity and specifity of distinguishing ASD children from non-ASD and other developmental disorders is high (Chlebowski et al., 2010). Four pairs of twins were diagnosed with mild-moderate autism and three pairs of twins were diagnosed with severe autism in keeping with DSM-V criteria and CARS. The Autism Diagnostic Observation Schedule and The Autism Diagnostic Interview-Revised have not been translated to Turkish. Thus, we did not use these standardized tests. Inclusion criteria have been defined as being in between 3 and 18 ages, having an ASD diagnosis with a clinic conversation according to DSM-V criteria. Exclusion criteria have been defined as being diagnosed with bipolar mood disorders and psychotic disorder. 2.2. Sample collection and preparation Blood samples were delivered to University of Health Sciences Faculty of Medicine Department of Medical Biology with cold chain on the same day. DNA isolation was done in Department of Medical Biology Laboratory in accordance with the kit protocol. DNA samples were preserved at −80° deep freezer until the study done. Suitable DNA samples for study were detected making concentration measurements with spectrophotometer. The concentration of all samples was arranged so will be 200 ng/μL with the Qubit 3.0 fluorometer system and to determine purity of the genomic DNA the ratio of OD 260/280 to between 1.8 and 2 was provided. Target enrichment was performed using SureSelect with a reference to the first target set is known to be normal for copy number variation throughout genome. To second target area which is low allele frequency, genomic regions with SNP was aimed to detect CnLOH. Third target area was totally used for determining to insertion-deletions and mutation scanning of predetermined regions. OneSeq searching panel is a design with the size of 28 Mb, functionally for one copy number changing (12 Mb), 300 kb with 5 Mb across Genome and cnLOH resolution and can be scanned disease related ClinGen zones with a higher 25–50 kb resolution. Also, all contents (16 Mb) are to aim 4
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Fig. 3. NGS Target Enrichment Workflow.
3. Results
applied to evaluate children with autism are shown on Table 2.
3.1. Clinical evaluations
3.2. Bioinformatics analysis
Seven twins with ASD were selected for the targeted sequencing. Diagnostic evaluations and psychiatric follow-up were made at the same clinic. In the absence of Autism Diagnosis Interview in Turkey, diagnoses were made on clinical observations made by DSM-V-criteria by child psychiatrist with at least 8 years of experience in this field. Sociodemographic data form was used routinely at clinic and it was prepared based on direct clinical observation and main report. If there were any behavioral, emotional and physical problems, detailed medical history (family situation, medical history of family, prenatal and postnatal factors, medical history at birth, pediatric history, medicines, concomitant diseases, hospitalizations, emergency visits), was recorded. Evaluations based on the survey results are given on Table 1. The results of Childhood Autism Rating Scale (CARS), Autism Behavior Control List (ABC) and Social Communication Questionnaire (SCQ)
At the first stage raw data of OneSeq analysis from the Illumina platform were analyzed. After the quality controls and removal of incorrect readings, variable search tool was used to take Variant Call format (VCF) files. At the second stage VCF files containing SNP > 200.000, were filtered according to 3 filters: 1) frequency < 0.01, 2) Quality score AD > 25, 3) damaging and possible damaging), and then analyzed by using R Bioconductor software. After filtering, selected variants were compared between themselves and siblings. Genomic coordinates were read from CDF files by using Ensemble Biomart software and rsIDs were determined with using genomic coordinates. Variants associated with autism were detected according to functions of genes and with a fast keyword filtering, by using R Biocunductor software. After SNP identities (reference SNP identification number-rsIDs) were taken from DbSNP, SNPs that are less common 5
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cytoskeleton organization and cell polarity. Ovarian expression of FMN2 disrupts neuroepithelial integration, neuronal migration and proliferative phenotype and plays a role in degradation of β-catenin that was set out in Mouse embryos. FMN2 activation is arranged by RhoA activation (Laplana et al., 2014b). It has been reported that there are sensorial emotional differences in autism spectrum disorder (ASD) patients. Missense mutations and loss of de novo function that caused neurodevelopmental diseases including FMN2 were identified and de novo candidate variants and rare single nucleotide variants that previously associated with autism spectrum disorders was researched in the study made by Marco and his friends to individuals with sensory dysfunction (Marco et al., 2018). mRNA and protein levels of FMN2 are high in the neurons of human and animal hippocampus. Our study supports these findings in literature, too. Based on the findings that the Alzheimer risk increases with age in the Post-Traumatic Stress Disorder (PTSD) patients of the study that conducted by Agis-Balboa and their friends it was expressed that FMN2 deregulates in PTSD and Alzheimer patients. Also seeing PTSD-like phenotype in young mice with FMN2 deficiency and showing disorders of synaptic plasticity by merging of new memories was not affected from this (Agís-Balboa et al., 2017). KNCQ2 gene codes that voltage-gated ion channel subunits leading to subthreshold potassium flow related with effective in limiting neuronal stimulation. Mutations of KCNQ2 missense dysfunction was detected in Benning Familial Neonatal Epilepsy disease. As Sands and his friends pointed out, as a result of examination in 11 patients R227 and R230 missense variants are characterized with autism spectrum disorder and neurodevelopmental disorder, besides R20H and R230S variants cause to effects of high function gaining in R230C, similar but smaller effects were put forward by R227Q (Sands et al., 2019). In gene silencing study based on CRISPR of Deneault and his friends ASD susceptibility genes including KNCQ2 were knocked-out, in AFF2/FMR2-, ASTN2-, ATRX-, KCNQ2- and SCNA-null neurons decreased synaptic activity was seen (Deneault et al., 2018). In Jiang and his friends' 32 families with ASD study, while detecting pathogenic de novo mutation in 6 families of 32, in 10 families X-linked or autosomal inherited mutations found, WES and epilepsy related genetic variants including KCQ2 gene of genetic variants' clinic relation with ASD has been put forward and WES is indicated as useful in mutation determining and clinical evaluation of individuals and families with ASD (Jiang et al., 2013). In terms of these data we have validated our findings in one place, using the right method in our study and we have demonstrated the consistency of the method. In the research of Long and his friends, considered to individuals with ASD and epilepsy together and voltage-gated ion including KNCQ2 mutations in the genes encoding the DNA channels have been found to common. Consequently, in epilepsy diseased children whose ion channel is gene mutation, necessity of ASD scanning has been suggested (Long et al., 2019). TNRC6A (in other saying GW182) gene, codes a member of repeat containing 6 protein families to the trinucleotide. This gene responsible for post transcriptional gene silencing through RNA interference and miRNA pathways. It has been localized in the area 16p12.1 of chromosome (Nishi et al., 2015). In the study made by Ishiura and his friends with 9 family members from 51 non-BAFME (Benning Adult Familial Myoclonic Epilepsy) and 91 BAFME patients, RAPTEF2 and TTTTA re-expansion was found in two families where no re-expansion was included in SAMD12, RAPGEF2 (in BAFME7 disease) and TNRC6A (in BAFME6 disease). The genes products of SAMD12, TNRC6A and RAPGEF2 are expressed in brain. Repeat sequences of these genes in reference genome, two of them located in poli tails of alu sequences (A) are essentially consist of short extensions of TTTTA repeats. In this study, it has been found that increasing non-coding TTTCA replications of in SAMD12, TNRC6A and RAPGEF expand the predictions of molecular bases of epilepsies and cause to BAFME which should lead to effective therapeutic measures based on illuminated molecular mechanisms of diseases (Ishiura et al., 2018). In a study which leads by Lewkowicz and his friends, in central nervous system tissues Ago, GW182, and FXR1 expression levels were examined
Table 4 Genes that are thought to be related with ASD as a result of WES study (Prefiltering results). ZBTB20
PTCHD1
GRIA3
SHANK3
CTNND2
MKRN3-AS1
WFS1 UBE3A TSC2 TSC1 TMLHE TCF12 TBX1 STS SOX3 SOX2 SNRPN SNORD116-1 SNORD115-1 SMC3 SMC1A SMAD4 SLC9A6 SLC35C1
PROKR2 PRKAR1A PRDM16 PIK3CA PIGL PDE4D PAH OTX2 OPHN1 NPAP1 NLGN4X NLGN3 NIPBL NHS NDP NDN NAGA
GP1BB GJA8 GJA5 GATM GABRD FTSJ1 FRMPD4 FMR1 FLCN FGFR1 EP300 ELN EHMT1 DYRK1A HESX1 HERC2 HDAC8 HDAC4
SETD5 SEMA3E SEC23B SDHD SDHC SDHB SCN8A SATB2 RERE RAI1 RAD21 PWRN1 PWAR1 PTEN SKI SIN3A SIM1
CREBBP COMT CHRNA7 CHD8 CHD7 AUTS2 ATRX ARNT2 ANKRD11 ALMS1 ALG13 ALDH5A1 AKT1 AGTR2 ADSL DYM DPYD DHCR7
MKRN3 MEIS2 MED13L MEC12 MECP2 MAOA MAGEL2 KMT2A KLLN KDM5C IQSEC2 IPW IL1RAPL1 IFNG HNF1B OGG1 BCKDK
than the ExAC database were also checked as less SNP can be added to as a mutation. Explanations were added into selected variants by using SNPnexus after determining the mutual and different SNPs between themselves and siblings. All references and clinic validations were obtained from Clinvar database. References have been added to the end of PIMDs analysis file. According to the values which we obtained with bioinformatics analysis, by using 4 different software, using different cut off values, and by keeping the reliability limits high, we have identified approximately 110 genes in the entire genome that may be related with disease (Table 4). After this stage, the way that reliability of the software in filtering is firstly and with the highest values to be accepted SNP change registered with 44 rs is defined jointly in all patients. All these 44 rs number scanned SNPs were screened for disease relationship first literature review and researched with OMIM data. Changings that related with the ASD pathophysiology both the mechanism of disease formation and thought to be involved in prognosis-oriented processes were marked combining with the clinical data. From this analysis, 6 different genes stand out including one de novo chromosomal locations and OMIM IDs were given (FMN2, KCNQ2, NOTCH3, TMRC6A, SHANK3, and SLC6A4) (Figs. 4, 5). In the next stage compared OneSeq data to each of the twins with rs number, which is common in two patients and prominent separately in two patients, expressed SNPs were detected. They were analyzed according to relevance with clinical data. 4. Discussion In differential diagnosis genetic syndromes with autism, it is an ethical and medical necessity to consider both to manage the required medical approaches, and in terms of taking away from moral and material burdens of patient and the family. With the recent large-scale studies, different genomic areas that have disease-related common variants were determined. Each one of these area and variants in the etiology of autism spectrum disorder can be placed into the biological pathways. As a result of our study 6 separate genes that can be placed in etiopathogenesis and multiple pathways includes these genes were put forward. We evaluated both related with in literature placed and autism or some other neurodegenerative diseases and these genes which are stood out first time in this study, primarily in terms of disease pathophysiology or its effect of function and in accordance with the placed pathways. FMN2 is one of the 15 members of forming homology protein family which is known that it is related with neurodevelopmental disorder and placed in 1q43 chromosome. It is responsible for actin 6
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(caption on next page)
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Fig. 4. A) Protein–protein interaction analysis. B) Genes are thought to be related with ASD as a result of WES study.
Fig. 5. 6 different genes stand out including one de novo chromosomal locations (FMN2, KCNQ2, NOTCH3, TMRC6A, SHANK3, SLC6A4).
of Circ0006916, which has regulatory role in cell growth (Dai et al., 2018). The relationship of FCMTE pathogenesis with abnormal TTTTA and TTTCA re-expansion in SAMD12, TNRC6A and RAPGEF2 was investigated in a study made with 5 families diagnosed with FCME (Familial Cortical Myoclonic Tremor with Epilepsy) disease by Lee and his colleagues. It has been found that insertion of TTTCA expansion is
by making animal model for EAE (Experimental Autoimmune Encephalomyelitis) and MS (Multiple Sclerosis) diseases, however no significant result was found (Lewkowicz et al., 2015). After silencing of TNRC6A gene the circular RNA Circ0006916 expression was found to be decreased in Dai and his friends' study with A549 and H460 lung cell lines. As a result, it was expressed that TNRC6A regulates the biogenesis 8
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0.5% of these cases. The deletion at SHANK3 gene has been shown as the cause of global developmental delay, speech delay, mental disability and Phelan McDermid Syndrome (PMDS) which is a neurodevelopmental disease characterized with ASD and weak motor coordination (Betancur and Buxbaum, 2013). In Kathuri A. and colleagues' study by producing pluripotent stem cells (iPSCs) from 3 ASD patients and 2 control, they suggested that SHANK3 has a critical role in the neuronal morphogenesis at placodal neurons and early defects is related with mutations that related to ASD (Kathuria et al., 2018). SLC6A4 that one of the most studied genes for ASD, the gene is a serotonin carrier which has an important role in modeling of serotonin levels (Coutinho et al., 2004). SLC6A4 found in 17q11.2 chromosome and has 14 exons (International Molecular Genetic Study of Autism Consortium (IMGSAC), 2001). During early development, hyperserotonemia can affect to development of serotonin terminals in negative way when the blood-brain barrier is not yet fully formed. Also, it has been reported that serotonin level is higher in autism patients when comparing to normal people (Mulder et al., 2004). Kim and colleagues showed that there is a relationship between SNPs of SLC6A4 and 115 trios ASD patients (Kim et al., 2002). In a study made by Myungja Ro and colleagues on 195 autism spectrum disorder patients 3 SNP in FGA gene and 16 SNP in SLC6A4 gene was selected based on the results of previous study for analyzing. They examined risks of behavioral phenotypes and ASD according to CARS evaluation criteria and the relationship between FGA genes and SNPs at SLC6A4. Results of the study showed that HTs and SNPs at SLC6A4 are not related with ASD but at FGAs meaningfully are (Ro et al., 2013). Different from our study, Yoo and colleagues suggested that common SNPs of SLC6A4 are not important indicators at Korean ASD relationships when they were evaluating with TDT method by choosing 12 SNP at SLC6A4 gene in their study with 151 Korean ASD patients' trio (Yoo et al., 2009). Enlighten of etiopathogenesis has great importance in terms of planning the proper treatment, course of the disease and genetic counseling related to the risk of recurrence. There is no concrete method to diagnose autism. Molecular tests that will be used in autism diagnosis should be applied according to the result of genetically engineered specific algorithms, genetic irregularities in differential diagnosis and autism-related syndromes should be determined. So, it may be possible to both blocking to potential complications and initiating the proper treatment.
related with FCMTE disease in Chinese families (Lei et al., 2019). Of course, accompanying with epilepsy individuals with ASD is quite high. In this state, KNCQ2 causes to epilepsy by affecting ion channels primarily and maybe in this situation autism can be thought as a secondary state that accompany to epilepsy. This situation is still arguing. NOTCH13 gene is a gene that is found in 19. chromosome and it has 33 exons. This gene responsible for coding a transmembrane receptor related with fate of cells and cell signaling in embryonic development. Most of the NOTCH receptors and cofactors of NOTCH3 gene mutation is expressed from mesenchymal neuroblastoma cells. Different NOTCH paralogs can arrange specific target genes besides sharing of a gene set. Based on the simultaneous activation of NOTCH1, NOTCH2 and NOTCH3 paralogs can cause a wide impact on induction and maintenance of MES condition (van Groningen et al., 2019). CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy), is a hereditary arteriopathy disease that related with differences in NOTCH3 gene placed on 9. chromosome. More than 130 NOTCH3 mutations were found for this disease. In a case report belong to a 50 years old person who has mood disorder and history of progressive cognitive decline, p. Arg558Cys pathogenic variant was determined in NOTCH3 gene and it was expressed that this variant determined only in 2 Portuguese CADASIL patient hemizygously (Anamnart et al., 2019). Beside these single patients result according to Patel and colleagues' mutation study in numerous Alzheimer patients, 5617 Alzheimer patients and 4594 control group included in the study, as a result 24 variants were detected in 19 genes in 10 or more patients. NOTCH3 rs149307620 rare missense mutation determined in 10 patients and with the protein-protein interaction network and gen-set enrichment analysis it was reported that NOTCH3 is relevant with Alzheimer pathways and biological process (Patel et al., 2019). Beside this in a sequence study previously made in a Turkish family, on a Turkish clinical diagnosed with Alzheimer's disease patient from a relative family with a history of complex neurological and immunological disorders all exome sequences study was done and p.1231C in exon 22 determined which was found in CADASIL patients in previous studies (Guerreiro et al., 2012). For the first time in our study of NOTCH3 associated with ASD. In the next stage we are planning to study especially in ASD patients with these genes reported to be numerous and at different stages (mild-moderate-severe). We think it can be placed in algorithms that can be used in molecular genetics diagnosis. SHANK3 is a structural protein which mainly in postsynaptic density. SHANK3 gene found in humans' 22q13 locus and > 1000 22q.13 deletion was reported. In total, 75% of these deletions have autism spectrum disorder and in 95% severe developmental delay can be seen (Jiang and Ehlers, 2013). SHANK3 is responsible for scaffold function in proper placement of protein receptors on postsynaptic membrane. Recent researches related to mouse models and hippocampal neurons with SHANK3 deficiency has shown that this gene has an important role in long-term strengthening by organizing AMPA receptor and affecting spine remodeling, in regulating basal neurotransmission at AMPA glutamate receptors and modeling of PSPA in striatum level. SHANK3 deletion is related with ASD behavioral problems that produce most of the features like social interaction, social communication and mandatory/repetitive actions (Durand et al., 2011; Bozdagi et al., 2010). These findings show that SHANK3 loss of function mutations is related with neurodevelopmental disorders and ASD specifications. Our study was resulted to support these findings. In Sergio I. Nemirovsky and colleagues' study, all genome sequencing was done to determine de novo SHANK3 mutation at familial ASD of 3 twins and it showed that the SHANK3 gene is least identified, quite penetrating, and monogenic cause of ASD (Nemirovsky et al., 2015). In a cohort study made on 133 patients from USA and 83 patients from Italy by Luigi Buccoto and colleagues, 5 deleterious mutations with 2.3% formation rate was determined in SHANK3 gene (Boccuto et al., 2013). Catalina Betancur and colleagues evaluated 32 patients in their study and as a monogenetic cause of ASD; SHANK3 haplo-insufficiency has shown at
Acknowledgements This project was supported by the University of Health Sciences with Project No: 2017/032 and by TUBITAK ( T. C. The Scientific and Technological Research Council of Turkeys, vice presidency science fellowship and grant programs department) with Project No: 1059B191801982. References Agís-Balboa, R.C., Pinheiro, P.S., Rebola, N., Kerimoglu, C., Benito, E., Gertig, M., BahariJavan, S., Jain, G., Burkhardt, S., Delalle, I., Jatzko, A., Dettenhofer, M., Zunszain, P.A., Schmitt, A., Falkai, P., Pape, J.C., Binder, E.B., Mulle, C., Fischer, A., Sananbenesi, F., 2017. Formin 2 links neuropsychiatric phenotypes at young age to an increased risk for dementia. EMBO J. 36 (19), 2815–2828. Anamnart, C., Songsaeng, D., Chanprasert, S., 2019. A large number of cerebral microbleeds in CADASIL patients presenting with recurrent seizures: a case report. BMC Neurol. 19 (1), 106. Baio, J., Wiggins, L., Christensen, D.L., Maenner, M.J., Daniels, J., Warren, Z., KurziusSpencer, M., Zahorodny, W., Robinson, Rosenberg, C., White, T., Durkin, M.S., Imm, P., Nikolaou, L., Yeargin-Allsopp, M., Lee, L.C., Harrington, R., Lopez, M., Fitzgerald, R.T., Hewitt, A., Pettygrove, S., Constantino, J.N., Vehorn, A., Shenouda, J., HallLande, J., Van Naarden, Braun, K., Dowling, N.F., 2018. Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2014. MMWR Surveill. Summ. 67(6):1–23. Betancur, C., Buxbaum, J.D., 2013. SHANK3 haploinsufficiency: a "common" but underdiagnosed highly penetrant monogenic cause of autism spectrum disorders. Mol Autism. 4 (1), 17.
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Boccuto, L., Lauri, M., Sarasua, S.M., Skinner, C.D., Buccella, D., Dwivedi, A., Orteschi, D., Collins, J.S., Zollino. M., Visconti. P., Dupont, B., Tiziano, D., Schroer, R.J., Neri, G., Stevenson, R.E., Gurrieri, F., Schwartz, C.E., 2013. Prevalence of SHANK3 variants in patients with different subtypes of autism spectrum disorders. Eur. J. Hum. Genet. 21(3):310–6. Bozdagi, O., Sakurai, T., Papapetrou, D., Wang, X., Dickstein, D.L., Takahashi, N., Kajiwara, Y., Yang, M., Katz, A.M., Scattoni, M.L., Harris, M.J., Saxena, R., Silverman, J.L., Crawley, J.N., Zhou, Q., Hof, P.R., Buxbaum, J.D., 2010. Haploinsufficiency of the autism-associated Shank3 gene leads to deficits in synaptic function, social interaction, and social communication. Mol Autism. 1 (1), 15. Chakrabarti, S., Fombonne, E., 2001. Pervasive developmental disorders in preschool children. JAMA 285 (24), 3093–3099. Chlebowski, C., Green, J.A., Barton, M.L., Fein, D., 2010. 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Jiang, Y.H., Ehlers, M.D., 2013. Modeling autism by SHANK gene mutations in mice. Neuron. 78 (1), 8–27. Jiang, Y.H., Yuen, R.K., Jin, X., Wang, M., Chen, N., Wu, X., Ju, J., Mei, J., Shi, Y., He, M., Wang, G., Liang, J., Wang, Z., Cao, D., Carter, M.T., Chrysler, C., Drmic, I.E., Howe, J.L., Lau, L., Marshall, C.R., Merico, D., Nalpathamkalam, T., Thiruvahindrapuram, B., Thompson, A., Uddin, M., Walker, S., Luo, J., Anagnostou, E., Zwaigenbaum, L., Ring, R.H., Wang, J., Lajonchere, C., Wang, J., Shih, A., Szatmari, P., Yang, H., Dawson, G., Li, Y., Scherer, S.W., 2013. Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing. Am. J. Hum. Genet. 93 (2), 249–263. Kathuria, A., Nowosiad, P., Jagasia, R., Aigner, S., Taylor, R.D., Andreae, L.C., Gatford, N.J.F., Lucchesi, W., Srivastava, D.P., Price, J., 2018. Stem cell-derived neurons from autistic individuals with SHANK3 mutation show morphogenetic abnormalities during early development. Mol. Psychiatry 23 (3), 735–746. Kim, S.J., Cox, N., Courchesne, R., Lord, C., Corsello, C., Akshoomoff, N., Guter, S., Leventhal, B.L., Courchesne, E., Cook Jr., E.H., 2002. Transmission disequilibrium
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Determination of genetic changes in etiology of autism spectrum disorder in twins by whole-exome sequencing
T
Ceyda Hayretdag (M.D., M.D.)a, Pinar Algedik (M.D.)b,d, Cumhur Gokhan Ekmekci (M.D., Ph.D.)c, Ozlem Bozdagi Gunal (M.D., Ph.D.)d, ⁎ Umut Agyuz (M.Sc.)e, Halime Yildirim (M.Sc.)f, Ender Coskunpinar (Ph.D.)d,f, a
Department of Anatomy, School of Medicine, University of Health Sciences, Istanbul, Turkey Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey c LABGEN, Acibadem University, Istanbul, Turkey d Department of Psychiatry, New Jersey Medical School, Rutgers University, USA e Genz Biotech Inc., Ankara, Turkey f Department of Medical Biology, School of Medicine, University of Health Sciences, Istanbul, Turkey b
A R T I C LE I N FO
A B S T R A C T
Keywords: Autism spectrum disorders Genetic mutation Monozygotic Whole exome sequencing FMN2 KCNQ2 NOTCH3 TMRC6A SHANK3 SLC6A4
Twin studies provide strong evidence that genetic factors have a major role in the etiology of autism spectrum disorder (ASD) but in most patients the underlying genetic cause of the disease is unknown. Here we used wholeexome sequencing to study genome-wide differences in twins with autism in order to reveal the genetic changes responsible for the etiology of autism. DNA was isolated from peripheral blood samples from six monozygotic twins and one dizygotic twin and analyzed by OneSeq protocol, on an Illumina NextSeq platform. Bioinformatics analyses have revealed 110 disease-related genes, and after further filtering, we have identified 44 single nucleotide polymorphisms (SNPs). Functional network analysis has identified significant associations for 6 different genes, including known ASD candidate genes: FMN2, KCNQ2, NOTCH3, TMRC6A, SHANK3, and SLC6A4. Our results provide an independent evidence for known ASD genes and highlight other genes, which will further improve the understanding of the genetic basis of ASD.
1. Introduction Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized with impaired communication and mutual social interaction, restricted, repetitive, and stereotyped behavior (DSM-5, 2013). The symptoms arise early in life and may last throughout life (Lord et al., 2020). This phenomenon is a widespread neuropsychiatric condition affecting one out of every 59 children (Baio et al., 2018). As a multifactorial disease that both environmental and genetic factors take part in pathogenesis (Chakrabarti and Fombonne, 2001) high accuracy
detection of underlying genomic mechanisms of ASD is essential for understanding the etiology and create new treatment protocols. With the large-scale detection techniques in recent years, different genomic regions have been recognized having common variants associated with the disorder. Structural differences or copy number variations (CNV) occur in the regions where the examined genome differs from the reference genome as long sequences (> 50 bp) (Pang et al., 2010). These structural variations include insertions, deletions, inversions, and duplications. Whole exome sequencing provides a high-resolution sequencing of the genome and captures both large and small variants that
Abbreviations: ABC, Autism Behavior Checklist; ASD, Autism Spectrum Disorder; BAFME, Benign Adult Familial Myoclonic Epilepsy; CADASIL, Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy; CARS, Childhood Autism Rating Scale; CDF, Computable Document Format; CNV, Copy Number Variation; CRISPR, Clustered Regularly Interspaced Short Palindromic Repeats; DSM-V, Diagnostic and Statistical Manual of Mental Disorders-V; DZ, Di Zygotic; EAE, Experimental Autoimmune Encephalomyelitis; FCMTE, Familial Cortical Myoclonic Tremor with Epilepsy; FMN, Formin; GW, Genome Wide; KCNQ, Potassium Voltage-gated Channel Subfamily Q member; MS, Multiple Sclerosis; MZ, Mono Zygotic; NOTCH, Neurogenic locus notch homolog protein; OD, Optical Density; OMIM, Online Mendelian Inheritance in Man; PMDS, Phelan McDermid Syndrome; PTSD, Post-Traumatic Stress Disorder; rSID, reference SNP Identification number; SCQ, Social Communication Questionnaire; SHANK3, SH3 and Multiple Ankyrin Repeat Domains 3; SLC6A4, Solute Carrier Family 6 Member 4; SNP, Single Nucleotide Polymorphism; VCF, Variant Call format; WES, Whole Exome Sequencing ⁎ Corresponding Author: Ender Coskunpinar, Department of Medical Biology, School of Medicine, University of Health Sciences, Istanbul, Turkey E-mail addresses: [email protected] (C. Hayretdag), [email protected] (P. Algedik), [email protected] (C.G. Ekmekci), [email protected] (O.B. Gunal), [email protected] (U. Agyuz), [email protected] (H. Yildirim), [email protected] (E. Coskunpinar). https://doi.org/10.1016/j.genrep.2020.100618 Received 28 January 2020; Accepted 30 January 2020 Available online 01 February 2020 2452-0144/ © 2020 Published by Elsevier Inc.
Gene Reports 19 (2020) 100618
C. Hayretdag, et al.
Table 1 Characteristics of cases.
Table 3 The study's protocol used with Covaris system.
Twin pairs
Age
Gender
Epilepsy
Language delay
Premature
Birth weight
Twin pair 1
7 7 8 8 9 9 13 13 5 5 10 10 6 6
M M F F M M M M F F M M M M
No No No No No No No No No No No No No No
Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
No No Yes Yes No No Yes Yes Yes Yes No No Yes Yes
2240 2260 2100 2000 2250 2450 2740 2680 2100 2400 2600 2800 2580 2640
Twin pair 2 Twin pair 3 Twin pair 4 Twin pair 5 Twin pair 6 Twin pair 7
Setting
Value
Duty factor Peak Incident Power (PIP) Cycles per burst Treatment time Bath temperature
10% 175 200 360 s 4° to 8 °C
identified genetic variations that will enhance our understanding of ASD etiology. Comprehensive analysis of relevant copy number changes that might play a role in phenotypic differences will help to generate a list of interesting candidates for future studies and identify the relationship between genetic variation and ASD risk factors. The elucidation of etiopathogenesis is also important in terms of planning appropriate treatment, giving genetic counseling on the course of the disease and the risk of recurrence.
might otherwise be missed. The use of monozygotic (MZ) twins is known to be a very strong strategy in the identification of de novo and hereditary CNVs. Especially using concordant and discordant monozygotic twins with ASD is a strong strategy to define de novo and genetic CNVs (Laplana et al., 2014a). In addition to rare CNVs, single nucleotide polymorphisms (SNPs) have been reported to be associated with autism and may share molecular etiology with schizophrenia (Shaw et al., 2014). Recent studies of copy number analysis have discovered several new variants associated with autism and identified genetic risk loci that involve some candidate genes that can be linked to ASD pathophysiology (Noroozi et al., 2016; Glessner et al., 2014; Safari et al., 2017). Also, it has been thought that coexistence of risk factors is associated with ASD intensity, too. It is thought that because of the same DNA structure in MZ twins after pairing, has seen all phenotypically differences caused by effects of environmental factors except for de novo mutations (Losh et al., 2012). Although the rates for shared genetic and environmental effects in twins vary between studies (Hallmayer et al., 2011; Frazier et al., 2014) in MZ twins with ASD, several studies support a strong genetic effect between 40 and 90%. Especially Frazier et al. have shown that if one MZ twin has ASD, the other twin has a 76% chance for being diagnosed with ASD and more likely to have similar levels of ASD related symptoms (Frazier et al., 2014). Therefore, since MZ twins share 100% of their genetic material and the concordance rates in MZ twins for autism are significantly higher than DZ twins or siblings (Frazier et al., 2014; Ozonoff et al., 2011; Rosenberg et al., 2009; Taniai et al., 2008), genetic studies in MZ twins will provide valuable information to identify genetic components related to autism symptoms. In this study by using whole genome sequencing in a monozygotic and dizygotic twin population of 7 twin pairs we
2. Material and methods 2.1. Study subject information Six autistics monozygotic (MZ) twins and one dizygotic (DZ) twin with unaffected parents were included in this study. The study was approved by the Ethics Committee for Clinic Research of Umraniye Training and Research Hospital (13604-06.20.2017). Written informed consent was obtained from all participants and/or their families. Seven out of the ten contacted families that had ASD twins in different provinces accepted to participate in our study. Three of the families refused to participate due the necessity of taking blood samples. From our patient group, six pairs of concordant MZ twins and a pair of concordant DZ twin diagnosed with ASD were evaluated clinically with their parents in the Umraniye Training and Research Hospital, University of Health Sciences, Turkey. Child psychiatrist with more than eight years of experience diagnosed the twins with ASD according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) (DSM-5, 2013). Sociodemographic data form was composed by the authors and covered comprehensive development history of the twins was taken from the families. Previous medical records were reviewed. Observation notes and videos of special education teachers were collected. According to the detailed medical history and clinical observations, all patients had delayed speech; four pairs of them had premature delivery. None of the patients had epilepsy or any other genetic disease (Table 1). Additionally, Childhood Autism Rating Scale (CARS), Autism Behavior Checklist (ABC) and Social Communication Questionnaire (SCQ, current version) were acquired (Table 2). Based on scores reported by Chebowski et al., the severity of autism symptoms
Table 2 Total CARS and SCQ Scores (according to CARS scoring patients with numbers 3, 4, 6 have severe autism, patients with numbers 1,2,5,7 have mild-moderate autism). Twin pairs
Total CARS score
Total SCQ score
ABC sensory
ABC relating
ABC stereotypes and object use
ABC language
ABC self-help and social
Total ABC score
Twin Pair 1
33,5 32,5 35 33 37 37 57,5 45,5 31 29 42,5 41,5 30 31,5
21 20 23 21 25 26 33 30 17 16 28 28 16 17
10 6 5 5 9 9 15 11 4 4 11 11 0 0
13 10 11 7 14 14 28 25 3 3 22 22 6 9
3 6 13 8 11 11 34 28 3 3 17 17 8 13
18 18 14 12 19 24 8 8 13 0 18 18 12 12
10 8 10 9 18 15 20 17 12 7 15 15 3 10
54 48 53 41 71 73 105 89 37 24 83 83 29 44
Twin Pair 2 Twin Pair 3 Twin Pair 4 Twin Pair 5 Twin Pair 6 Twin Pair 7
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Fig. 1. Bioanalyzer 2100 results as quality control to after Covaris study. 3
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Fig. 2. Electropherogram images of DNA fragments.
disease-related genes from Agilent SureSelect Focused Exome Panel. Firstly, enrichment process for Illumina matched end sequencing was conducted with using of OneSeq target enrichment kit in our study. Genomic libraries were prepared for each sample using Covaris e220 or s220 device and genomic DNA samples were 150–200 bp fragmented (Table 3). For quality measurement 2100 Bioanalyzer device and High Sensitivity DNA chip and reagent kit were used. All samples had an electropherogram distribution peak between 120 and 150 bp end of the study (Fig. 1). Sure Select XT Library Prep Kit ILM was used for repairing tips. After end repair, AMPure XP beads were introduced for the selection of the desirable DNA fragment. After the amplification process, Bioanalyzer 2100 was used to see how many bp the DNA fragments are in. As a result of these study electropherogram images of DNA fragments were obtained in between 225 and 275 bp (Fig. 2). For hybridization, required sample concentration was 750 ng, with a volume up 3.4 μL. to 221 ng/uL was required in each 1 μL. At this stage for the purpose of setting sample volume using vacuum concentrator (min ≤ 45 °C) with the Hyb 1, 2, 3 and 4 reagents, Master Mix was prepared and waited for 5 min at 65 °C. Then Sure Select Block Mix was prepared. RNAse Block dilution was made and this mix was incubated with PCR cover heated to 105 °C with mixing at the specified rates at 65 °C for 24 h. All samples were then bead selected using Sure Select Target Enrichment Box-1 and Streptavidin bound beads. Magnetic beads were homogeneously mixed and 50 μL added for each tube, and 200 μL SureSelect Binding Buffer added on it. Tubes were placed on a magnetic stand. When samples were cleaned the supernatant part was separated. This washing process performed 3 times in total. Lastly 200 μL Binding. Buffer was added again and vortex, spin performed and transferred to new tubes. After capturing of hybridized DNA sample, preparation for indexing and multiple sequencing were performed according to NGS protocol (Fig. 3). Each created library was loaded to Illumina NextSeq 2 × 150 bp platforms. Data analyzed with Agilent SureCall Software v3.0 after enough coverage and depth was achieved.
using total CARS score is over 25.5. The sensitivity and specifity of distinguishing ASD children from non-ASD and other developmental disorders is high (Chlebowski et al., 2010). Four pairs of twins were diagnosed with mild-moderate autism and three pairs of twins were diagnosed with severe autism in keeping with DSM-V criteria and CARS. The Autism Diagnostic Observation Schedule and The Autism Diagnostic Interview-Revised have not been translated to Turkish. Thus, we did not use these standardized tests. Inclusion criteria have been defined as being in between 3 and 18 ages, having an ASD diagnosis with a clinic conversation according to DSM-V criteria. Exclusion criteria have been defined as being diagnosed with bipolar mood disorders and psychotic disorder. 2.2. Sample collection and preparation Blood samples were delivered to University of Health Sciences Faculty of Medicine Department of Medical Biology with cold chain on the same day. DNA isolation was done in Department of Medical Biology Laboratory in accordance with the kit protocol. DNA samples were preserved at −80° deep freezer until the study done. Suitable DNA samples for study were detected making concentration measurements with spectrophotometer. The concentration of all samples was arranged so will be 200 ng/μL with the Qubit 3.0 fluorometer system and to determine purity of the genomic DNA the ratio of OD 260/280 to between 1.8 and 2 was provided. Target enrichment was performed using SureSelect with a reference to the first target set is known to be normal for copy number variation throughout genome. To second target area which is low allele frequency, genomic regions with SNP was aimed to detect CnLOH. Third target area was totally used for determining to insertion-deletions and mutation scanning of predetermined regions. OneSeq searching panel is a design with the size of 28 Mb, functionally for one copy number changing (12 Mb), 300 kb with 5 Mb across Genome and cnLOH resolution and can be scanned disease related ClinGen zones with a higher 25–50 kb resolution. Also, all contents (16 Mb) are to aim 4
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Fig. 3. NGS Target Enrichment Workflow.
3. Results
applied to evaluate children with autism are shown on Table 2.
3.1. Clinical evaluations
3.2. Bioinformatics analysis
Seven twins with ASD were selected for the targeted sequencing. Diagnostic evaluations and psychiatric follow-up were made at the same clinic. In the absence of Autism Diagnosis Interview in Turkey, diagnoses were made on clinical observations made by DSM-V-criteria by child psychiatrist with at least 8 years of experience in this field. Sociodemographic data form was used routinely at clinic and it was prepared based on direct clinical observation and main report. If there were any behavioral, emotional and physical problems, detailed medical history (family situation, medical history of family, prenatal and postnatal factors, medical history at birth, pediatric history, medicines, concomitant diseases, hospitalizations, emergency visits), was recorded. Evaluations based on the survey results are given on Table 1. The results of Childhood Autism Rating Scale (CARS), Autism Behavior Control List (ABC) and Social Communication Questionnaire (SCQ)
At the first stage raw data of OneSeq analysis from the Illumina platform were analyzed. After the quality controls and removal of incorrect readings, variable search tool was used to take Variant Call format (VCF) files. At the second stage VCF files containing SNP > 200.000, were filtered according to 3 filters: 1) frequency < 0.01, 2) Quality score AD > 25, 3) damaging and possible damaging), and then analyzed by using R Bioconductor software. After filtering, selected variants were compared between themselves and siblings. Genomic coordinates were read from CDF files by using Ensemble Biomart software and rsIDs were determined with using genomic coordinates. Variants associated with autism were detected according to functions of genes and with a fast keyword filtering, by using R Biocunductor software. After SNP identities (reference SNP identification number-rsIDs) were taken from DbSNP, SNPs that are less common 5
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cytoskeleton organization and cell polarity. Ovarian expression of FMN2 disrupts neuroepithelial integration, neuronal migration and proliferative phenotype and plays a role in degradation of β-catenin that was set out in Mouse embryos. FMN2 activation is arranged by RhoA activation (Laplana et al., 2014b). It has been reported that there are sensorial emotional differences in autism spectrum disorder (ASD) patients. Missense mutations and loss of de novo function that caused neurodevelopmental diseases including FMN2 were identified and de novo candidate variants and rare single nucleotide variants that previously associated with autism spectrum disorders was researched in the study made by Marco and his friends to individuals with sensory dysfunction (Marco et al., 2018). mRNA and protein levels of FMN2 are high in the neurons of human and animal hippocampus. Our study supports these findings in literature, too. Based on the findings that the Alzheimer risk increases with age in the Post-Traumatic Stress Disorder (PTSD) patients of the study that conducted by Agis-Balboa and their friends it was expressed that FMN2 deregulates in PTSD and Alzheimer patients. Also seeing PTSD-like phenotype in young mice with FMN2 deficiency and showing disorders of synaptic plasticity by merging of new memories was not affected from this (Agís-Balboa et al., 2017). KNCQ2 gene codes that voltage-gated ion channel subunits leading to subthreshold potassium flow related with effective in limiting neuronal stimulation. Mutations of KCNQ2 missense dysfunction was detected in Benning Familial Neonatal Epilepsy disease. As Sands and his friends pointed out, as a result of examination in 11 patients R227 and R230 missense variants are characterized with autism spectrum disorder and neurodevelopmental disorder, besides R20H and R230S variants cause to effects of high function gaining in R230C, similar but smaller effects were put forward by R227Q (Sands et al., 2019). In gene silencing study based on CRISPR of Deneault and his friends ASD susceptibility genes including KNCQ2 were knocked-out, in AFF2/FMR2-, ASTN2-, ATRX-, KCNQ2- and SCNA-null neurons decreased synaptic activity was seen (Deneault et al., 2018). In Jiang and his friends' 32 families with ASD study, while detecting pathogenic de novo mutation in 6 families of 32, in 10 families X-linked or autosomal inherited mutations found, WES and epilepsy related genetic variants including KCQ2 gene of genetic variants' clinic relation with ASD has been put forward and WES is indicated as useful in mutation determining and clinical evaluation of individuals and families with ASD (Jiang et al., 2013). In terms of these data we have validated our findings in one place, using the right method in our study and we have demonstrated the consistency of the method. In the research of Long and his friends, considered to individuals with ASD and epilepsy together and voltage-gated ion including KNCQ2 mutations in the genes encoding the DNA channels have been found to common. Consequently, in epilepsy diseased children whose ion channel is gene mutation, necessity of ASD scanning has been suggested (Long et al., 2019). TNRC6A (in other saying GW182) gene, codes a member of repeat containing 6 protein families to the trinucleotide. This gene responsible for post transcriptional gene silencing through RNA interference and miRNA pathways. It has been localized in the area 16p12.1 of chromosome (Nishi et al., 2015). In the study made by Ishiura and his friends with 9 family members from 51 non-BAFME (Benning Adult Familial Myoclonic Epilepsy) and 91 BAFME patients, RAPTEF2 and TTTTA re-expansion was found in two families where no re-expansion was included in SAMD12, RAPGEF2 (in BAFME7 disease) and TNRC6A (in BAFME6 disease). The genes products of SAMD12, TNRC6A and RAPGEF2 are expressed in brain. Repeat sequences of these genes in reference genome, two of them located in poli tails of alu sequences (A) are essentially consist of short extensions of TTTTA repeats. In this study, it has been found that increasing non-coding TTTCA replications of in SAMD12, TNRC6A and RAPGEF expand the predictions of molecular bases of epilepsies and cause to BAFME which should lead to effective therapeutic measures based on illuminated molecular mechanisms of diseases (Ishiura et al., 2018). In a study which leads by Lewkowicz and his friends, in central nervous system tissues Ago, GW182, and FXR1 expression levels were examined
Table 4 Genes that are thought to be related with ASD as a result of WES study (Prefiltering results). ZBTB20
PTCHD1
GRIA3
SHANK3
CTNND2
MKRN3-AS1
WFS1 UBE3A TSC2 TSC1 TMLHE TCF12 TBX1 STS SOX3 SOX2 SNRPN SNORD116-1 SNORD115-1 SMC3 SMC1A SMAD4 SLC9A6 SLC35C1
PROKR2 PRKAR1A PRDM16 PIK3CA PIGL PDE4D PAH OTX2 OPHN1 NPAP1 NLGN4X NLGN3 NIPBL NHS NDP NDN NAGA
GP1BB GJA8 GJA5 GATM GABRD FTSJ1 FRMPD4 FMR1 FLCN FGFR1 EP300 ELN EHMT1 DYRK1A HESX1 HERC2 HDAC8 HDAC4
SETD5 SEMA3E SEC23B SDHD SDHC SDHB SCN8A SATB2 RERE RAI1 RAD21 PWRN1 PWAR1 PTEN SKI SIN3A SIM1
CREBBP COMT CHRNA7 CHD8 CHD7 AUTS2 ATRX ARNT2 ANKRD11 ALMS1 ALG13 ALDH5A1 AKT1 AGTR2 ADSL DYM DPYD DHCR7
MKRN3 MEIS2 MED13L MEC12 MECP2 MAOA MAGEL2 KMT2A KLLN KDM5C IQSEC2 IPW IL1RAPL1 IFNG HNF1B OGG1 BCKDK
than the ExAC database were also checked as less SNP can be added to as a mutation. Explanations were added into selected variants by using SNPnexus after determining the mutual and different SNPs between themselves and siblings. All references and clinic validations were obtained from Clinvar database. References have been added to the end of PIMDs analysis file. According to the values which we obtained with bioinformatics analysis, by using 4 different software, using different cut off values, and by keeping the reliability limits high, we have identified approximately 110 genes in the entire genome that may be related with disease (Table 4). After this stage, the way that reliability of the software in filtering is firstly and with the highest values to be accepted SNP change registered with 44 rs is defined jointly in all patients. All these 44 rs number scanned SNPs were screened for disease relationship first literature review and researched with OMIM data. Changings that related with the ASD pathophysiology both the mechanism of disease formation and thought to be involved in prognosis-oriented processes were marked combining with the clinical data. From this analysis, 6 different genes stand out including one de novo chromosomal locations and OMIM IDs were given (FMN2, KCNQ2, NOTCH3, TMRC6A, SHANK3, and SLC6A4) (Figs. 4, 5). In the next stage compared OneSeq data to each of the twins with rs number, which is common in two patients and prominent separately in two patients, expressed SNPs were detected. They were analyzed according to relevance with clinical data. 4. Discussion In differential diagnosis genetic syndromes with autism, it is an ethical and medical necessity to consider both to manage the required medical approaches, and in terms of taking away from moral and material burdens of patient and the family. With the recent large-scale studies, different genomic areas that have disease-related common variants were determined. Each one of these area and variants in the etiology of autism spectrum disorder can be placed into the biological pathways. As a result of our study 6 separate genes that can be placed in etiopathogenesis and multiple pathways includes these genes were put forward. We evaluated both related with in literature placed and autism or some other neurodegenerative diseases and these genes which are stood out first time in this study, primarily in terms of disease pathophysiology or its effect of function and in accordance with the placed pathways. FMN2 is one of the 15 members of forming homology protein family which is known that it is related with neurodevelopmental disorder and placed in 1q43 chromosome. It is responsible for actin 6
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(caption on next page)
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Fig. 4. A) Protein–protein interaction analysis. B) Genes are thought to be related with ASD as a result of WES study.
Fig. 5. 6 different genes stand out including one de novo chromosomal locations (FMN2, KCNQ2, NOTCH3, TMRC6A, SHANK3, SLC6A4).
of Circ0006916, which has regulatory role in cell growth (Dai et al., 2018). The relationship of FCMTE pathogenesis with abnormal TTTTA and TTTCA re-expansion in SAMD12, TNRC6A and RAPGEF2 was investigated in a study made with 5 families diagnosed with FCME (Familial Cortical Myoclonic Tremor with Epilepsy) disease by Lee and his colleagues. It has been found that insertion of TTTCA expansion is
by making animal model for EAE (Experimental Autoimmune Encephalomyelitis) and MS (Multiple Sclerosis) diseases, however no significant result was found (Lewkowicz et al., 2015). After silencing of TNRC6A gene the circular RNA Circ0006916 expression was found to be decreased in Dai and his friends' study with A549 and H460 lung cell lines. As a result, it was expressed that TNRC6A regulates the biogenesis 8
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0.5% of these cases. The deletion at SHANK3 gene has been shown as the cause of global developmental delay, speech delay, mental disability and Phelan McDermid Syndrome (PMDS) which is a neurodevelopmental disease characterized with ASD and weak motor coordination (Betancur and Buxbaum, 2013). In Kathuri A. and colleagues' study by producing pluripotent stem cells (iPSCs) from 3 ASD patients and 2 control, they suggested that SHANK3 has a critical role in the neuronal morphogenesis at placodal neurons and early defects is related with mutations that related to ASD (Kathuria et al., 2018). SLC6A4 that one of the most studied genes for ASD, the gene is a serotonin carrier which has an important role in modeling of serotonin levels (Coutinho et al., 2004). SLC6A4 found in 17q11.2 chromosome and has 14 exons (International Molecular Genetic Study of Autism Consortium (IMGSAC), 2001). During early development, hyperserotonemia can affect to development of serotonin terminals in negative way when the blood-brain barrier is not yet fully formed. Also, it has been reported that serotonin level is higher in autism patients when comparing to normal people (Mulder et al., 2004). Kim and colleagues showed that there is a relationship between SNPs of SLC6A4 and 115 trios ASD patients (Kim et al., 2002). In a study made by Myungja Ro and colleagues on 195 autism spectrum disorder patients 3 SNP in FGA gene and 16 SNP in SLC6A4 gene was selected based on the results of previous study for analyzing. They examined risks of behavioral phenotypes and ASD according to CARS evaluation criteria and the relationship between FGA genes and SNPs at SLC6A4. Results of the study showed that HTs and SNPs at SLC6A4 are not related with ASD but at FGAs meaningfully are (Ro et al., 2013). Different from our study, Yoo and colleagues suggested that common SNPs of SLC6A4 are not important indicators at Korean ASD relationships when they were evaluating with TDT method by choosing 12 SNP at SLC6A4 gene in their study with 151 Korean ASD patients' trio (Yoo et al., 2009). Enlighten of etiopathogenesis has great importance in terms of planning the proper treatment, course of the disease and genetic counseling related to the risk of recurrence. There is no concrete method to diagnose autism. Molecular tests that will be used in autism diagnosis should be applied according to the result of genetically engineered specific algorithms, genetic irregularities in differential diagnosis and autism-related syndromes should be determined. So, it may be possible to both blocking to potential complications and initiating the proper treatment.
related with FCMTE disease in Chinese families (Lei et al., 2019). Of course, accompanying with epilepsy individuals with ASD is quite high. In this state, KNCQ2 causes to epilepsy by affecting ion channels primarily and maybe in this situation autism can be thought as a secondary state that accompany to epilepsy. This situation is still arguing. NOTCH13 gene is a gene that is found in 19. chromosome and it has 33 exons. This gene responsible for coding a transmembrane receptor related with fate of cells and cell signaling in embryonic development. Most of the NOTCH receptors and cofactors of NOTCH3 gene mutation is expressed from mesenchymal neuroblastoma cells. Different NOTCH paralogs can arrange specific target genes besides sharing of a gene set. Based on the simultaneous activation of NOTCH1, NOTCH2 and NOTCH3 paralogs can cause a wide impact on induction and maintenance of MES condition (van Groningen et al., 2019). CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy), is a hereditary arteriopathy disease that related with differences in NOTCH3 gene placed on 9. chromosome. More than 130 NOTCH3 mutations were found for this disease. In a case report belong to a 50 years old person who has mood disorder and history of progressive cognitive decline, p. Arg558Cys pathogenic variant was determined in NOTCH3 gene and it was expressed that this variant determined only in 2 Portuguese CADASIL patient hemizygously (Anamnart et al., 2019). Beside these single patients result according to Patel and colleagues' mutation study in numerous Alzheimer patients, 5617 Alzheimer patients and 4594 control group included in the study, as a result 24 variants were detected in 19 genes in 10 or more patients. NOTCH3 rs149307620 rare missense mutation determined in 10 patients and with the protein-protein interaction network and gen-set enrichment analysis it was reported that NOTCH3 is relevant with Alzheimer pathways and biological process (Patel et al., 2019). Beside this in a sequence study previously made in a Turkish family, on a Turkish clinical diagnosed with Alzheimer's disease patient from a relative family with a history of complex neurological and immunological disorders all exome sequences study was done and p.1231C in exon 22 determined which was found in CADASIL patients in previous studies (Guerreiro et al., 2012). For the first time in our study of NOTCH3 associated with ASD. In the next stage we are planning to study especially in ASD patients with these genes reported to be numerous and at different stages (mild-moderate-severe). We think it can be placed in algorithms that can be used in molecular genetics diagnosis. SHANK3 is a structural protein which mainly in postsynaptic density. SHANK3 gene found in humans' 22q13 locus and > 1000 22q.13 deletion was reported. In total, 75% of these deletions have autism spectrum disorder and in 95% severe developmental delay can be seen (Jiang and Ehlers, 2013). SHANK3 is responsible for scaffold function in proper placement of protein receptors on postsynaptic membrane. Recent researches related to mouse models and hippocampal neurons with SHANK3 deficiency has shown that this gene has an important role in long-term strengthening by organizing AMPA receptor and affecting spine remodeling, in regulating basal neurotransmission at AMPA glutamate receptors and modeling of PSPA in striatum level. SHANK3 deletion is related with ASD behavioral problems that produce most of the features like social interaction, social communication and mandatory/repetitive actions (Durand et al., 2011; Bozdagi et al., 2010). These findings show that SHANK3 loss of function mutations is related with neurodevelopmental disorders and ASD specifications. Our study was resulted to support these findings. In Sergio I. Nemirovsky and colleagues' study, all genome sequencing was done to determine de novo SHANK3 mutation at familial ASD of 3 twins and it showed that the SHANK3 gene is least identified, quite penetrating, and monogenic cause of ASD (Nemirovsky et al., 2015). In a cohort study made on 133 patients from USA and 83 patients from Italy by Luigi Buccoto and colleagues, 5 deleterious mutations with 2.3% formation rate was determined in SHANK3 gene (Boccuto et al., 2013). Catalina Betancur and colleagues evaluated 32 patients in their study and as a monogenetic cause of ASD; SHANK3 haplo-insufficiency has shown at
Acknowledgements This project was supported by the University of Health Sciences with Project No: 2017/032 and by TUBITAK ( T. C. The Scientific and Technological Research Council of Turkeys, vice presidency science fellowship and grant programs department) with Project No: 1059B191801982. References Agís-Balboa, R.C., Pinheiro, P.S., Rebola, N., Kerimoglu, C., Benito, E., Gertig, M., BahariJavan, S., Jain, G., Burkhardt, S., Delalle, I., Jatzko, A., Dettenhofer, M., Zunszain, P.A., Schmitt, A., Falkai, P., Pape, J.C., Binder, E.B., Mulle, C., Fischer, A., Sananbenesi, F., 2017. Formin 2 links neuropsychiatric phenotypes at young age to an increased risk for dementia. EMBO J. 36 (19), 2815–2828. Anamnart, C., Songsaeng, D., Chanprasert, S., 2019. A large number of cerebral microbleeds in CADASIL patients presenting with recurrent seizures: a case report. BMC Neurol. 19 (1), 106. Baio, J., Wiggins, L., Christensen, D.L., Maenner, M.J., Daniels, J., Warren, Z., KurziusSpencer, M., Zahorodny, W., Robinson, Rosenberg, C., White, T., Durkin, M.S., Imm, P., Nikolaou, L., Yeargin-Allsopp, M., Lee, L.C., Harrington, R., Lopez, M., Fitzgerald, R.T., Hewitt, A., Pettygrove, S., Constantino, J.N., Vehorn, A., Shenouda, J., HallLande, J., Van Naarden, Braun, K., Dowling, N.F., 2018. Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2014. MMWR Surveill. Summ. 67(6):1–23. Betancur, C., Buxbaum, J.D., 2013. SHANK3 haploinsufficiency: a "common" but underdiagnosed highly penetrant monogenic cause of autism spectrum disorders. Mol Autism. 4 (1), 17.
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