Identification of potentially pathogenic variants for autism spectrum disorders using gene-burden analysis

Abstract

Gene- burden analyses have lately become a very successful way for the identification of genes carrying risk variants underlying the analysed disease. This approach is also suitable for complex disorders like autism spectrum disorder (ASD). The gene-burden analysis using Testing Rare Variants with Public Data (TRAPD) software was conducted on whole exome sequencing data of Slovenian patients with ASD to determine potentially novel disease risk variants in known ASD-associated genes as well as in others. To choose the right control group for testing, principal component analysis based on the 1000 Genomes and ASD cohort samples was conducted. The subsequent protein structure and ligand binding analysis usingI-TASSER package were performed to detect changes in protein structure and ligand binding to determine a potential pathogenic consequence of observed mutation. The obtained results demonstrate an association of two variants-p.Glu198Lys (PPP2R5D:c.592G>A) and p.Arg253Gln (PPP2R5D:c.758G>A) with the ASD. Substitution p.Glu198Lys (PPP2R5D:c.592G>A) is a variant, previously described as pathogenic in association with ASD combined with intellectual disability, whereas p.Arg253Gln (PPP2R5D:c.758G>A) has not been described as an ASD-associated pathogenic variant yet. The results indicate that the filtering process was suitable and could be used in the future for detection of novel pathogenic variants when analysing groups of ASD patients.

Fig 1. Flow chart for variant detection and prioritizing for gene-burden testing.

Fig 2. PCA based on the 1000 Genomes and ASD cohort samples.

Fig 3. Quantile-quantile plot showing the–log₁₀ of p values of the burden testing considering only synonymous, rare variants versus the expected–log₁₀ of p values.

Values are given for genes (black dots). The black line represents the ratio between expected and observed p values when the distribution of p values is uniform, and the blue, dotted line represents the actual ratio when genes are considered that fall in the range between the 50^th and 90^th percentile. The most significantly associated gene is NOL4.

Fig 4. The results of burden testing for rare, probable pathogenic mutations.

PPP2R5D is the most significantly associated gene, and has more mutations than expected.

Fig 5. Sanger sequencing results for variant p.Arg253Gln.

On the left side is the sequence of a person without mutation and on the right side is the sequence of the patient heterozygous for p.Arg253Gln mutation.

Fig 6. Sanger sequencing results for variant p.Glu198Lys.

On the left side is the sequence of a person without mutation and on the right side is the sequence of the patient heterozygous for p.Glu198Lys mutation.

Fig 7. Results of PCR-RFLP analysis of p.Arg253Gln mutation.

Lane 1: 100 bp DNA ladder, lane 2: A person without mutation, lane 3: The patient, heterozygous for p.Arg253Gln mutation.

Fig 8

Results of ligand binding site prediction for the original (A) and mutant (B) protein sequences. Software I-TASSER suggests the ligand most likely to bind to the analysed protein. The binding protein residues are shown in blue, and the predicted binding ligands are shown in green-yellow.