Reverse Pathway Genetic Approach Identifies Epistasis in Autism Spectrum Disorders

<div><p>Although gene-gene interaction, or epistasis, plays a large role in complex traits in model organisms, genome-wide by genome-wide searches for two-way interaction have limited power in human studies. We thus used knowledge of a biological pathway in order to identify a contribution of epistasis to autism spectrum disorders (ASDs) in humans, a reverse-pathway genetic approach. Based on previous observation of increased ASD symptoms in Mendelian disorders of the Ras/MAPK pathway (RASopathies), we showed that common SNPs in RASopathy genes show enrichment for association signal in GWAS (<i>P</i> = 0.02). We then screened genome-wide for interactors with RASopathy gene SNPs and showed strong enrichment in ASD-affected individuals (<i>P</i> < 2.2 x 10⁻¹⁶), with a number of pairwise interactions meeting genome-wide criteria for significance. Finally, we utilized quantitative measures of ASD symptoms in RASopathy-affected individuals to perform modifier mapping via GWAS. One top region overlapped between these independent approaches, and we showed dysregulation of a gene in this region, <i>GPR141</i>, in a RASopathy neural cell line. We thus used orthogonal approaches to provide strong evidence for a contribution of epistasis to ASDs, confirm a role for the Ras/MAPK pathway in idiopathic ASDs, and to identify a convergent candidate gene that may interact with the Ras/MAPK pathway.</p></div

Ras/MAPK ASD epistasis top results.

<p>The unique epistatic SNP pairs with <i>P</i> < 2.9x10^-9 are listed in the table. For each SNP, the following is listed in order of columns: rsID (Epistatic SNP), chromosome (CHR), position (BP, reference version hg19), minor allele frequency in the ASD dataset (MAF), nearest gene to the epistatic SNP, Ras/MAPK gene associated with the interacting SNP, and <i>P</i>-value for epistasis in cases (Epistasis ASD <i>P</i>) and pseudo-controls (Epistasis Control <i>P</i>). Locus pairs meeting genome-wide significance criteria (<i>P</i> < 7.6 x 10⁻¹⁰) are bolded. Main effects for epistatic and Ras/MAPK SNPs listed here are listed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006516#pgen.1006516.s004" target="_blank">S4 Table</a>, with no SNPs showing <i>P</i> < 0.01.</p

Linkage disequilibrium (LD) map of the region chromosome 7: 37.7Mb– 38.1 Mb.

<p>The graph displays LD between the SNPs rs114490548 (<i>P</i> = 7.8 x10^-11, Ras/MAPK ASD epistasis analysis) and rs62621010 (<i>P</i> = 5.6x10^-7, RASopathy QTL analysis). LD (D′) values for each pairwise comparison of SNPs were calculated based on LD and recombination rate data in 1000 Genomes May 2013 release and plotted using HAPLOVIEW(126) (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006516#sec027" target="_blank">web resources</a>) default settings and standard color theme. The red color corresponds to D’ = 1 and log of odds (LOD) ≥ 2, white corresponds to D’<1 and LOD <2, and blue to D’ = 1 and LOD<2.</p

Enrichment of Ras/MAPK SNPs in ASD association results.

<p>The histogram displays the distribution of results with percent of SNPs meeting q = 0.2 for 100 randomly permuted gene sets compared to the Ras/MAPK SNP set (dashed line, 9.05%) in an ASD transmission disequilibrium test (TDT) for association. The y-axis displays the proportion of permutation results; the x-axis displays the percent SNPs meeting q = 0.2.</p

Comparison of number of Ras/MAPK gene epistasis results in ASD cases versus pseudo-controls.

<p>The graph displays number of epistasis tests (y-axis) in the ASD cases (dark gray, circle) and ASD pseudo-controls (light gray, triangle) with <i>P</i>-value thresholds (x-axis, left to right): <i>P</i> < 2.9x10^-9, < 1.0x10^-8, <i>P</i> < 1.0x10^-7, <i>P</i> < 1.0x10^-6, <i>P</i> < 1.0x10^-5, and <i>P</i> < 1.0x10^-4. The 2x2 chi-square test <i>P</i>-value and odds ratio (OR) are included for the epistasis results meeting nominal significance (<i>P</i> < 10⁻⁶).</p

Gene expression in neural cell lines.

<p>For the genes <i>ELMO1</i>, <i>GPR141</i>, <i>SFRP4</i>, <i>EPDR1</i>, <i>and STARD3NL</i>, the graph displays the normalized mRNA expression relative to controls measured by qPCR for two independent experiments. <i>NME8</i> had undetermined quantities in the first experiment (1) and extreme variance in the second experiment (2) due to low expression level, and therefore was excluded from the graph (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006516#pgen.1006516.s003" target="_blank">S3 Table</a>). The error bars denote the standard error of the sample measurements, and the asterisk denotes a t-test <i>P</i>-value < 0.05 between CFC (dark gray) and control (light gray).</p

Social responsiveness association in RASopathy top results.

<p>The independent SNPs with social responsiveness score (SRS) association in RASopathy (random effects meta-analysis <i>P</i> < 1.0x10^-4) are listed. The data underlying the top six candidate modifiers are graphically illustrated in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006516#pgen.1006516.s014" target="_blank">S6 Fig</a>. For each SNP, the following is listed in order of columns: SNP rsID, chromosome (CHR), position (BP, reference version hg19), minor allele frequency in the dataset (MAF), groups contributing to the RASopathy association (group with the most significant association <i>P</i>-value is listed first and groups with similar direction of effect are in parentheses), Cochran’s Q <i>P</i>-value for all four RASopathy groups, RASopathy (CFC, CS, NF1, and NS) SRS association (random effects meta-analysis) <i>P</i>-value, control sibling SRS <i>P</i>-value (linear regression), gene(s) containing or flanking SNP.</p

A Genome-Wide Survey of Transgenerational Genetic Effects in Autism

<div><p>Effects of parental genotype or parent-offspring genetic interaction are well established in model organisms for a variety of traits. However, these transgenerational genetic models are rarely studied in humans. We have utilized an autism case-control study with 735 mother-child pairs to perform genome-wide screening for maternal genetic effects and maternal-offspring genetic interaction. We used simple models of single locus parent-child interaction and identified suggestive results (<i>P</i><10⁻⁴) that cannot be explained by main effects, but no genome-wide significant signals. Some of these maternal and maternal-child associations were in or adjacent to autism candidate genes including: <i>PCDH9, FOXP1, GABRB3, NRXN1, RELN, MACROD2, FHIT, RORA, CNTN4, CNTNAP2, FAM135B, LAMA1, NFIA, NLGN4X, RAPGEF4</i>, and <i>SDK1</i>. We attempted validation of potential autism association under maternal-specific models using maternal-paternal comparison in family-based GWAS datasets. Our results suggest that further study of parental genetic effects and parent-child interaction in autism is warranted.</p></div

Top results (<i>P</i><10⁻⁵) from CMH test of allele frequencies in main effect and transgenerational effect models.

<p>SNPs with <i>P</i><10⁻⁵ in the EMA discovery sample are listed. The model type (Model) and SNP identity (SNP) are shown. For each SNP, the closest annotated genes are indicated as well as relative SNP position to those genes (Nearest Gene(s) and Location). <i>P</i>-values (CMH <i>P</i>-value) and odds ratios (CMH OR) are shown for a Cochran-Mantel-Haenszel test of pair-type counts in case vs. control pairs from the EMA discovery cohort. In order to show that our models under investigation are not driven by proband main effects (in maternal main effect model) or both maternal and proband main effects (in transgenerational effect models), a comparison between multinomial models is shown (LRT <i>P</i>-value). Replication datasets were imputed to allow maximum coverage of SNPs across different platforms. Replication was performed on trios; results were then combined across replication datasets using random-effects meta-analysis (Rep. <i>P</i>-value, Rep. OR). *Indicates that a merged Rep. <i>P-</i>value and OR are presented rather than the meta-analyzed statistic.</p

Models of Transgenerational Epistasis.

<p>A) “Offspring Heterozygous” model where the offspring has an allele the mother does not vs. pairs where the mother possesses at least one copy of each allele present in the offspring. B) “Maternal Heterozygous” model where the offspring has an allele the mother does not vs. pairs where the mother possesses at least one copy of each allele present in the offspring. C) “Difference” model where the mother and offspring genotypes are identical vs. pairs where they are not identical.</p