Eur Child Adolesc Psychiatry DOI 10.1007/s00787-014-0537-8
ORIGINAL CONTRIBUTION
Weak association of glyoxalase 1 (GLO1) variants with autism spectrum disorder Jernej Kovacˇ • Katarina Trebusˇak Podkrajsˇek Marta Macedoni Luksˇicˇ • Tadej Battelino
•
Received: 23 August 2013 / Accepted: 7 March 2014 Ó Springer-Verlag Berlin Heidelberg 2014
Abstract The prevalence of the autism spectrum disorder (ASD) was recently estimated to 1 in 88 children by the CDC MMWR. In up to 25 % of the cases, the genetic cause can be identified. Past studies identified increased level of advanced glycation end products (AGE) in the brain samples of ASD patients. The methylglyoxal (MG) is one of the main precursors for AGE formation. Humans developed effective mechanism of the MG metabolism involving two enzymes glyoxalase 1 (GLO1) and hydroxyacylglutathione hydrolase (HAGH). Our aim was to analyse genetic variants of GLO1 and HAGH in population of 143 paediatric participants with ASD. We detected 7 genetic variants in GLO1 and 16 variants in HAGH using high-resolution melting (HRM) analysis. A novel association between variant rs1049346 and ASD [OR (allele C)] = 1.5; 95 % CI = 1.1–2.2 and p \ 0.05) was Electronic supplementary material The online version of this article (doi:10.1007/s00787-014-0537-8) contains supplementary material, which is available to authorized users. J. Kovacˇ T. Battelino (&) Department of Endocrinology, Diabetes and Metabolic Diseases, UMC Ljubljana, University Children’s Hospital, Bohoricˇeva ulica 20, 1000 Ljubljana, Slovenia e-mail:
[email protected] J. Kovacˇ K. T. Podkrajsˇek Centre of Medical Genetics, UMC Ljubljana, University Children’s Hospital, Vrazov trg 1, 1000 Ljubljana, Slovenia M. M. Luksˇicˇ Department of Child, Adolescent and Developmental Neurology, Centre for Autism, UMC Ljubljana, University Children’s Hospital, Bohoricˇeva ulica 20, 1000 Ljubljana, Slovenia T. Battelino Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia
identified, and weak association between ASD and variant rs2736654 [OR (allele A)] = 2.2; 95 % CI = 0.99–4.9; p = 0.045) was confirmed. Additionally, a novel genetic variant (GLO1 c.484G [ A, p.Ala161Thr) with predicted potentially damaging effect on the activity of the glyoxalase 1 that may contribute to the aetiology of ASD was identified in one participant with ASD. No association between genetic variants of the HAGH gene and ASD was found. Increased level of MG and, consequently, AGEs can induce oxidative stress, mitochondrial dysfunction and inflammation all of which have been implicated to act in the aetiology of the ASD. Our results indicate potential importance of MG metabolism in ASD. However, these results must be interpreted with caution until a causative relation is demonstrated. Keywords ASD Association study Genetics Glyoxalase 1 Methylglyoxal
Introduction The autism spectrum disorder (ASD) is a heterogeneous pervasive developmental disorder, hallmarked with different levels of communication and social interaction impairment, restricted, stereotypical interests and repetitive behaviour [1]. According to the CDC Morbidity and Mortality Weekly Report in 2012, the prevalence of the ASD in population is 1 in 88 children. It marks 23 % increase since 2009 and 78 % increase since 2007. The ASD is almost five times more common in male population compared to female population [2]. The ASD is a highly hereditary syndrome and in up to 25 % of the cases the genetic cause can be identified [3]. The genetic background of the ASD is extremely diverse with more than 100
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candidate genes and more than 40 genomic loci reported in subjects with ASD [4]. There is a large plethora of identified de novo mutations and copy number variations that influence the aetiology of ASD and account for up to 10 % of the ASD cases [5]. Those genetic changes impact wide spectrum of biochemical pathways—from neural synapse formation to small molecules metabolism [4]. Additionally, the level of advanced glycation end products (AGE) was increased in brain samples of eight ASD patients [6]. Methylglyoxal is one of the major factors that contribute to the increase in AGE levels [7]. Methlyglyoxal (MG) or 2-oxopropanal is a non-enzymatic side product of different metabolic pathways including the metabolism of threonine, lipid peroxidation and glycolysis [8]. The glycolysis is a major pathway of the MG production through the non-enzymatic phosphate elimination from glyceraldehyde-3-phosphate and dihydroxy acetone phosphate molecules [9]. Free MG is able to interact with proteins, lipids and nucleotides, altering protein function, inducing genetic changes and formation of AGE [10]. The resulting protein damage can lead to mitochondria dysfunction and to an increase in the production of reactive nitrogen and oxygen species (RNS/ROS) [11]. Consequently, the cells are prone to apoptosis [12]. At physiological concentrations, MG can act as GABAA receptor agonist, thus broadening the set of mechanisms
that affect the homeostasis of the organism [13]. To eliminate excessive concentration of MG, organisms developed effective mechanism of the MG metabolism involving glutathione molecule and two enzymes: glyoxalase 1 (GLO1) and hydroxyacylglutathione hydrolase (HAGH). The MG reacts non-enzymatically with the glutathione molecule; the resulting hemithioacetal is converted by the glyoxalase 1 into the S-D-lactoylglutathione, which is subsequently converted into the D-lactate by hydroxyacylglutathione hydrolase (Fig. 1) [14]. Efficient removal of MG from the cell is crucial for the maintenance of homeostasis, and any disruption of this process may lead to pathological changes and disease. The increased levels of MG and disturbance of glyoxalase 1 function are associated with several pathological processes and/or their complications including diabetes, obesity, depression, schizophrenia, autism, cancer, neurodegeneration and ageing [9, 12, 14, 15]. The a-Oxoaldehydes degrading enzyme glyoxalase 1 is a ubiquitously expressed cytosolic metalloprotein with a zinc ion located in its active site and with the molecular mass of 46 kDa [7]. The expression of GLO1 in prenatal period is approximately three times higher compared to the expression in postnatals [6]. Additionally, expression ofGLO1 is increasing till the age of 55, followed by decreasing expression later on [16]. The gene GLO1 has not been singled out in any genome-wide association study
Fig. 1 The biochemistry of MG degradation. The glutathione acts as a cofactor of glyoxalase 1 in transformation of MG into S-D-lactoylglutathione. The glutathione and D-lactic acid are released after the S-D-lactoylglutathione enzymatic degradation by hydroxyacylglutathione
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(GWAS), but the loci 6p21.2 where it is located emerged as a plausible ASD-risk loci candidate in the microarray analysis of 1,491 unrelated ASD cases [17]. The reduced expression of GLO1 has been detected in mood disorder patients [18], and genetic variant of GLO1 gene (rs2736654)has been associated with ASD [6]. Nevertheless, the association between ASD and genetic variants of GLO1 is not present in all analysed populations. For example, there was only a weak evidence for linkage in Finnish population between GLO1 polymorphism rs2736654 and ASD [19] and no significant association in Han ethnic group [20], while another study detected its protective effect against ASD [21]. This discrepancy between different studies is possibly due to the variation in the allele frequency of analysed genetic variants across different populations [22]. The analysis of rs2736654 variant functional impact on glyoxalase 1 revealed hyperphosphorylation of the enzyme and change in its function[22]. Furthermore, the accumulation of MG due to the impaired enzymatic capacity of the glyoxalase 1 or increase of its generation in the cell results in the increase of the AGE formation and promotion of the receptor for AGE products (RAGE) expression and RAGE-mediated downstream signalling cascade [22]. The activation of RAGE signalling pathway results in the activation of NADPH oxidase increasing the level of the superoxide [23], as well as in upregulation of pro-inflammatory mediators [24]. The excessive activation of RAGE signalling pathways has been shown to inhibit neurite outgrowth [25]. As shown above, the MG and dysfunction of the MG metabolism can influence several biochemical processes and impact cell differentiation and development through AGEformation and RAGE signalling activation [22, 26]. Our aim was to analyse genetic variants of GLO1 and HAGH in a population of ASD participants, compare them with an apparently healthy control group using high-resolution melting (HRM) analysis and to estimate the impact of novel genetic variants on protein function with bioinformatics tools.
Methods Participants One hundred and forty-three participants diagnosed with autism spectrum disorder by the national team of experts were recruited to participate in the study. The median age of participants was 8.16 years, ranging from 2.4 to 19.5 years. There were 121 males and 22 females. Samples from the 150 healthy individuals of the Slovenian ethnicity were included in the study as healthy controls. The gender ratio of between males and females in control group was
3:1. The median age of healthy controls was higher compared to the age of the participants with ASD (22.42 years) to ensure that healthy controls did not develop any pervasive developmental (ASD), mental (schizophrenia) or metabolic disorder (diabetes) that could be attributed or associated with genetic variants of methylglyoxal metabolic system. All participants or their legal guardians signed an informed consent to participate in the study. The protocol was approved by the Slovenian National Medical Ethics Committee (no: 24/10/09). Blood samples and DNA isolation Five millilitres of the whole blood was taken, and DNA was isolated according to the established laboratory protocols using FlexiGene isolation kit (Qiagen, Germany). The quality and the concentration of the isolated DNA were assessed with a spectrophotometer, and consequently DNA samples were diluted to a final concentration of 5 ng/uL. PCR primer selection and high-resolution melting analysis The PCR primers (Online resource 1 and 2) were designed according to the established laboratory protocol. The reference sequence for each amplicon was acquired from ENSEMBL database (http://www.ensembl.org) [27]. Optimal primers were designed by the Primer3 [28] online tool and analysed for possible polymorphisms with the SNPcheck tool [29]. The suitability of the constructed primers for the PCR reaction was tested by the MOPS online tools (Eurofins MWG Operon, Germany). HRM analysis was performed on the 7500 Fast RT-PCR System (Applied Biosystems, USA) using Type-IT HRM master mix (Qiagen, Germany). 10 ng of DNA was used together with 5lL of the Type-IT HRM master mix, and with a selected forward and reverse primers per sample for each HRM reaction. The temperature protocol was adopted from the suggested protocols provided by the supplier of the HRM master mix. The melting curves were recorded between 70 and 98 °C with 1 % temperature ramp and aligned and normalised with the HRM v2.0.1 software (Applied Biosystems, USA), followed by the adopted clustering analysis described by Reja et al. [30] and performed by the open source Rapid-Miner v5.2 software [31]. The results of the clustering analysis were visualised by the open source Tableau Public v7.0 software (http://www. tableausoftware.com). DNA sequencing The HRM samples chosen for sequencing were diluted in the ratio 1:4 with distilled water. 2.5 lL of this solution
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was used for further sequence analysis. The primers from the HRM reaction were removed in the first step with the use of the ExoSap-IT enzyme mix (Affymetrix, USA), followed by a sequence reaction with the BigDye Terminator sequencing master mix (Applied Biosystems, USA) according to the established laboratory protocol. The sequencing was performed on the ABI 3500 Genetic Analyser (Applied Biosystems, USA). Sequences were analysed with the Sequencing Analysis Software v5.4. (Applied Biosystems, USA) and aligned to reference sequence using Clustal X v2.0.12 [32]. In silico analysis of gene variant effect on protein stability and functionality We performed the in silico analysis of the missense coding gene variants effect on the stability of analysed proteins using SDM online tool developed by Blundell and colleagues (http://mordred.bioc.cam.ac.uk/*sdm/sdm.php). The SDM accounts the local structural environment of the wild type and mutant residues, defined by main chain conformation, solvent accessibility and hydrogen bonding class, to calculate the stability score (pseudo DDG) of the protein. The stability score indicates if the amino acid change is destabilising (negative score) or stabilising (positive score). The values of the stability score above 2 and below -2 are predicted to be disease associated [33]. The protein models with changed amino acid sequence were constructed with Swiss model server (http://swissmo del.expasy.org/) and visualised with UCSF Chimera software (http://www.cgl.ucsf.edu/chimera). Additionally, the effect of missense coding variants was evaluated using SIFT and PolyPhen predictors available on Ensembl. Statistics The statistical significance of the results (p), the odds ratio (OR) and the 95 % confidence interval (95 % CI) for comparison of healthy vs. ASD population was calculated using the Fisher exact statistical test, run on open source RStudio software based on the statistical programming language R (http://www.rstudio.com). The p value of \0.05 was considered to be statistically significant. The allele count was reported as the minor allele frequency (MAF). To assess and evaluate the effect of population stratification, we calculated the FST factor for both statistically significantly associated genetic variants with ASD. [34]. The linkage disequilibrium (LD) was analysed to assess the full impact of a ASD-associated genetic variants using tools available on the ENSEMBL webpage (http:// www.ensembl.org). Data from the ENSEMBL were used to calculate the LD, and determine the location of those variants relative to the analysed genes. The data for
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variants with r2 = 1 were extracted and analysed for the presence of regulatory regions that could influence the expression of GLO1 and HAGH genes.
Results Seven genetic variants in GLO1 and 16 variants in HAGH (Table 1) were identified. Three variants in GLO1 gene were novel, two of them (GLO1 c.94T [ C and GLO1 c.484G [ A) were located in coding regions and GLO1 c.167 ? 23C [ A was located in second intronic region of the gene. The remaining four variants were already reported in HGMD (http://www.hgmd.org) and/or dbSNP (http:// www.ncbi.nlm.nih.gov/SNP) databases: two of these variants with rs-numbers rs1130534 (GLO1 c.372A [ T) and rs2736654 (GLO1 c.332C [ A) were located in coding regions, and the other two variants with rs-numbers rs1049346 (GLO1 c.-7C [ T) and rs2277109 (GLO1 c.84 ? 39G [ T) in the non-coding regions of the GLO1 gene. Variants c.94T [ C and c.372A [ T (rs1130534) are synonymous. The variant c.84 ? 39G [ T (rs2277109) is a rare SNP, and was detected in one participant from the ASD group and one participant from the control group. The c.484G [ A variant changes alanine at the site 161 into threonine amino acid residue (p.Ala161Thr). The bioinformatics analysis with SDM tools revealed the change as high-instability inducing and probable diseasecausing variant (pseudo DDG = -2.16). The visualisation of this amino acid change revealed its relatively close position to the active site of the enzyme (Fig. 2). This variant was present in one participant with ASD and was not detected in control group. The variant c.484G [ A is also not reported in 1,000 genomes project catalogue of human genetic variants. The analysis with Ensembl online tools showed that this amino acid residue is highly conserved in primates (100 %), and modestly conserved in a group of placental mammals (66 %). The carrier of this variant is a 6-year-old boy with ASD, developmental delay and severe communication difficulties. The patient was born at gestation age of 41 weeks, and weighed 3,359 g. At the age of 2, the development regression begun and he was diagnosed with autism at the age of 3. The MRI of the brain indicated increased T2 and FLAIR signals of white brain matter at the edge of occipital lobes. The results of serum organic acids analysis, plasma amino acid analysis, karyotype and molecular karyotyping (array comparative genomic hybridization—aCGH) were normal. Psychosocial interactions and established eye contact were almost non-existent. The allele A frequency of the variant c.332C [ A (rs2736654; p.Ala111Glu) in our ASD and control population was 54.3 and 49.4 %,
Eur Child Adolesc Psychiatry Table 1 The list of all detected variants in GLO1 and HAGH Gene
Variant
rs#
AA change
SIFT score
PolyPhen score
Minor allele frequency (controls)
GLO1
c.-7C [ Ta,b
rs1049346
/
/
/
0.45
HAGH
c.84 ? 39G [ T
rs2277109
/
/
/
\0.01
c.94T [ C
Novel
Synonymous
/
/
\0.01
c.167 ? 23C [ A
Novel
/
/
/
\0.01
c.332C [ Aa,b
rs2736654
p.Ala111Glu
0.59
0.002
0.49
c.372A [ T
rs1130534
Synonymous
/
/
0.11
c.484G [ Ac c.-387C [ T
Novel rs28364709
p.Ala162Thr /
0 /
1 /
\0.01 NA
c.-363G [ A
Novel
/
/
/
\0.01
c.-286G [ A
Novel
/
/
/
\0.01
c.-219_-218insGCC
rs76260324
/
/
/
\0.01
c.-181T [ G
Novel
/
/
/
\0.01
c.314 ? 87T [ C
Novel
/
/
/
\0.01
c.314 ? 114A [ G
rs55791023
/
/
/
NA
c.315 - 43_315 23delCCTCAGCTCAGCAGGCAGCCC
rs144480059
/
/
/
0.3
c.343G [ A
rs114352351
p.Val115Ile
0.47
0.002
\0.01
c.348G [ A
Novel
Synonymous
/
/
NA
c.356C [ T c.542 - 73C [ T
rs115389912 Novel
p.Ser119Leu /
0.02 /
0.42 /
\0.01 \0.01
c.747 ? 21G [ A
rs11862755
/
/
/
NA
c.827 ? 25C [ T
rs2745199
/
/
/
NA
c.869T [ C
rs151314474
p.Val290Ala
0.16
0.792
\0.01
c.916C [ T
Novel
p.Pro306Ser
0
0.986
\0.01
The nomenclature is listed in the ‘‘Variant’’ column with designated rs-numbers, amino acid (AA) change, SIFT score, PolyPhen score and MAF in the following columns. The MAF for synonymous and intronic variants of HAGH was not determined a
Statistically significantly associated variants of GLO1 with ASD
b
The calculated FST for variants rs1049346 and rs2736654 was 0.014 and 0.011, respectively The calculated pseudo DDG was -2.16 classifying c.484G [ A variant as highly protein destabilising and potentially disease-causing variant
c
respectively [OR (A/A) = 2.2; 95 % CI = 0.99–4.9; p = 0.045; FST = 0.011). The variant c.-7C [ T (rs1049346) had higher frequency within ASD group compared to control group for allele C (56.5 vs. 45.6 % for ASD and control population, respectively; OR (C/C) = 1.5; 95 % CI = 1.1–2.2 and p \ 0.05; FST = 0.014). The analysis with Ensembl online tools showed that this amino acid residue is highly conserved in primates (100 %) and in a group of placental mammals (97 %). The analysis of HAGH gene revealed seven novel and nine previously described variants. Two novel variants (HAGH c.348G [ A and HAGH c.916C [ T) were located in coding regions of the gene. The variant c.348G [ A is a synonymous mutation and was detected only in one participant from the ASD group. The variant c.916C [ T codes the change Pro258Ser. According to the result of SDM analysis, this variant is protein destabilising but not a disease-causing change (pseudo DDG = -1.69), and it
was present in one participant from the ASD group and one participant from the control group.
Discussion Increased level of AGE in the brain of the ASD subjects and an association of GLO1 variant rs2736654 with ASD was previously reported [6]. Recently, a complex combination of genetic factors affecting GSH metabolism, function of glyoxalase 1 and mitochondria coupled with increased dietary exposure to AGEs and/or AGE precursor MG was proposed to act in the aetiology of ASD [10]. There are several indirect indices of possible involvement of MG in ASD cases besides population genetic studies. Increased level of MG and consequently AGEs can induce oxidative stress, mitochondrial dysfunction and inflammation [10, 11]. The oxidative stress as well as mitochondrial
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Fig. 2 The visualisation of glyoxalase 1 amino acid change p.Ala161Thr (red arrow). The change is located in relatively close proximity of the active site (green AS) of the enzyme. The pseudo DDG, determined with SDM analysis was -2.16, classifying this change as highly destabilising and possibly disease associated. This visualisation was made using Chimera 1.7 software and 3vw9 PDB file as a source for the 3D structure of glyoxalase 1
dysfunction and deregulated immune response have been implicated in the aetiology of ASD [35–38]. The activity of glyoxalase 1 is highly dependent on the availability of glutathione. The level of glutathione is reduced in ASD patients indicating possible dysfunction of glyoxalase enzyme system [39]. Additionally, there are evidences that increased level of MG and AGE in maternal blood correlates with increased level of MG and AGE in the blood of newborns, implying the possible effect of MG and AGE on prenatal development [10]. But there is still no direct proof that MG is either a cause of or a part of the ASD aetiology. Our results must therefore be interpreted with caution. The variant rs1049346 located 7 bp from the start codon of the GLO1 conveyed and increased the risk for ASD. The variant could affect the expression GLO1, however this needs to be confirmed with gene expression experiments. As demonstrated previously [6], the variant rs2736654 also conveyed an increased risk for ASD, however the association was statistically relatively weak. The weak association between rs2736654 and ASD found in our population confirms previous reports from two studies [6, 19], this variant was also associated with decreased activity of
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glyoxalase 1 [22]. To the other side, a study in Chinese Han population did not find an association [20]. Moreover, the 419A allele was more common in non-affected siblings from patients with ASD, suggesting a protective role [21]. Therefore, the precise role of rs2736654 warrants further evaluation. The analysis of LD for both variants returned no extra polymorphisms that could shed more light on the background of the connection between them and the ASD. Although the calculated FST values for both ASD associated variants were relatively low, additional association research of GLO1 variants and ASD in larger and more heterogeneous ASD populations is needed, especially since there are several studies that report no firm association between the genetic variants of the MG metabolism genes and ASD [19, 20]. At the same time, the number of genetic variants used for calculation of FST factor was too low to completely exclude the effect of population stratification on the association analysis [34]. Nevertheless, it is shown that the rs2736654 variant negatively influences enzymatic activity of glyoxalase 1, causing the build-up of the MG and rise in the level of its cytotoxic products [22]. The metabolic dependency of glyoxalase 1 function on sufficient supply of glutathione (GSH) molecules additionally support the role of MG in the aetiology of ASD, because there are many studies that report decreased level of reduced GSH in the blood of ASD population [40]. Insufficient supply of reduced GSH can impair the function of glyoxalase 1, and the removal of the MG is disrupted causing MG levels to rise and inflict damage to the organism. The same effect is expected when protein function-damaging genetic variants are present in the GLO1 gene. The discovery of the novel variant c.484G [ A in GLO1 with possible disease-causing consequences according to SDM analysis is another potential marker of MG involvement into the aetiology of ASD. Additionally, this mutation was not discovered in the control group. Recent research indicated that disturbed GABAergic signalling is potentially associated with disturbed chloride equilibrium in ASD. Dysfunctional glyoxalase 1 may influence the mood of patients with ASD associated with dysfunctional GABAergic signalling in two possible ways: firstly, MG acts as GABAA receptor agonist and increased level of MG due to glyoxalase 1 dysfunction may influence the signalling cascade of GABAA receptor, and secondly, MG can modify the function of protein channels and other proteins that regulate chloride level in the cell, thus causing chloride disequilibrium and consequently disturbance of GABAergic signalling. This could be of clinical relevance as bumetanide, a diuretic that decreases the level of chloride ions in the cell, was recently demonstrated to improve the clinical symptoms of ASD in children [41]. Although these results indicated a possible contribution of this genetic variant to glyoxalase 1 enzyme
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malfunction, the additional functional analysis is required to confirm this hypothesis. On the contrary, the novel variant c.-286G [ A in HAGH gene was present in both ASD and control group in accordance with the results of protein stability analysis with SDM tools where this mutation was annotated as protein destabilizing, but not disease-causing. Another interesting feature of HAGH gene was two tandem repeat variants rs76260324 and rs144480059. Although tandem repeats are associated with more than 20 neurological disorders [42], the two detected in our ASD population were not associated with ASD. Because the functional interpretation of non-coding genetic variants is difficult without gene expression studies, we focused our analysis on other coding and tandem repeat variants in HAGH but none of them were associated with ASD. The possible reason for this may lay in the fact that glyoxalase 1 catalyses the conversion of toxic MG into S-Dlactoylglutathione. The possible diminished activity of hydroxyacylglutathione hydrolase due to the genetic variants in HAGH and subsequent S-D-lactoylglutathione build-up may not affect the biochemistry of neural system development. The S-D-lactoylglutathione has been shown to have low toxicity for differentiated and non-malignant cells [43]. On the other hand, anti-proliferation effects of SD-lactoylglutathione on human leukaemia 60 (HL60) cells have been reported and, thus, the impact on the other tissues cannot be completely excluded [44].
Conclusion A novel association between variant rs1049346 and ASD was detected in a cohort of 143 patients with ASD. Additionally, a novel variant (GLO1 c.484G [ A, p.Ala161Thr) in the GLO1 was described. No association between the HAGH genetic variants and ASD was established. This results provide an additional evidence for the possible involvement of MG metabolism and AGE products in the aetiology of ASD. Additional research on a larger ASD cohort is required to minimise the effect of population stratification and group sampling. Acknowledgments This study was supported by the Slovenian National Research Agency grants J3-2412 and P3-0343. No potential conflicts of interest relevant to this article were reported. We would like to express our gratitude to Jurka Ferran and Eva Ðalic´ for their expert technical assistance.
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