Online Resources

Page Title

2 Online Resource 1. The R file “Matrix_eQTL_cis.r”

4 Online Resource 2. Linkage disequilibrium among SCN1A SNPs

6 Online Resource 3. SCN2A mRNA brain expression vs. rs2082366 genotype

7 Online Resource 4. Studies for meta-analysis of SCN1AIVS5N+5G>A and epilepsy

Online Resource 1.The R file“Matrix_eQTL_cis.r”

# Matrix eQTL by Andrey A. Shabalin

#

#

# Be sure to use an up to date version of R and Matrix eQTL.

#

# Set working directory:

setwd("C:/Users/Public/Documents/Protocols/Epilepsy/Expression");

#

# source("Matrix_eQTL_R/Matrix_eQTL_engine.r");

library(MatrixEQTL)

## Settings

# Linear model to use, modelANOVA, modelLINEAR, or modelLINEAR_CROSS

useModel = modelANOVA ; # modelANOVA, modelLINEAR, or modelLINEAR_CROSS

# Genotype file name

SNP_file_name = "genotype_expression_data/matrix_mdata_eqtl_Myers.txt";

snps_location_file_name = "genotype_expression_data/snp2loci_Myers_Affy500k_hg19.txt";

# Gene expression file name

expression_file_name = "genotype_expression_data/SCN_Myers.txt";

gene_location_file_name = "genotype_expression_data/geneid2loci_hapmap_hg19_4cols.txt";

# Covariates file name

# Set to character() for no covariates

covariates_file_name = character();

# Output file name

output_file_name_cis = "eQTL_results_R_cis.txt";

output_file_name_tra = "eQTL_results_R_tra.txt";

# Only associations significant at this level will be saved

pvOutputThreshold_cis = 1;

pvOutputThreshold_tra = 1e-5;

# Error covariance matrix

# Set to numeric() for identity.

errorCovariance = numeric();

# errorCovariance = read.table("genotype_expression_data/errorCovariance.txt");

cisDist = 1e5;

## Load genotype data

snps = SlicedData$new();

snps$fileDelimiter = "\t"; # the TAB character

snps$fileOmitCharacters = "NA"; # denote missing values;

snps$fileSkipRows = 1; # one row of column labels

snps$fileSkipColumns = 1; # one column of row labels

snps$fileSliceSize = 2000; # read file in pieces of 2,000 rows

snps$LoadFile(SNP_file_name);

## Load gene expression data

gene = SlicedData$new();

gene$fileDelimiter = "\t"; # the TAB character

gene$fileOmitCharacters = "NA"; # denote missing values;

gene$fileSkipRows = 1; # one row of column labels

gene$fileSkipColumns = 1; # one column of row labels

gene$fileSliceSize = 1; # read file in pieces of 1 rows

gene$LoadFile(expression_file_name);

## Load covariates

cvrt = SlicedData$new();

cvrt$fileDelimiter = "\t"; # the TAB character

cvrt$fileOmitCharacters = "NA"; # denote missing values;

cvrt$fileSkipRows = 1; # one row of column labels

cvrt$fileSkipColumns = 1; # one column of row labels

cvrt$fileSliceSize = 1; # read file in one piece

if(length(covariates_file_name)>0) {

cvrt$LoadFile(covariates_file_name);

}

## Run the analysis

snpspos = read.table(snps_location_file_name, header = TRUE, stringsAsFactors = FALSE);

genepos = read.table(gene_location_file_name, header = TRUE, stringsAsFactors = FALSE);

me = Matrix_eQTL_main(

snps = snps,

gene = gene,

cvrt = cvrt,

output_file_name = output_file_name_tra,

pvOutputThreshold = pvOutputThreshold_tra,

useModel = useModel,

errorCovariance = errorCovariance,

verbose = TRUE,

output_file_name.cis = output_file_name_cis,

pvOutputThreshold.cis = pvOutputThreshold_cis,

snpspos = snpspos,

genepos = genepos,

cisDist = cisDist,

pvalue.hist = "qqplot");

## Plot the Q-Q plot of local and distant p-values

plot(me)

Online Resource 2.Linkage disequilibrium among SCN1A SNPs

Genotypes from each ethnic group were analyzed in Haploview. Values displayed are r2 between pairs of SNPs. Darkness of gray in each diamond is proportional to r2.

Hong Kong Chinese

Malaysia Chinese

Malaysia Malay

MalaysiaIndian

Online Resource 3.SCN2A mRNA brain expression vs. rs2082366 genotype

SCN2A mRNA was measured by real-time PCR in post-mortem human frontal cortex brain samples from 193 subjects without neurological disease, and amounts were compared among genotypes of SCN2A rs2082366. Boxes display medians and quartiles, and error bars indicate predicted limit of each distribution. The GG genotype tended to reduce expression (p=0.096).

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Online Resource 4.Studiesfor meta-analysis of SCN1AIVS5N+5G>A and epilepsy

Reference / Ethnicity / Epilepsy with or without febrile seizures / Odds ratio for
G allele (P) / Allele frequency in patients / Alleles in patients / Alleles in controls
G / A / G / A / G
Schlachter et al., 20091 / European / With febrile seizures / a0.60 (<0.001) / 31% / 125 / 55 / 725 / 677
Petrovski et al., 20092 / European / With febrile seizures / a / 42% / 88 / 64
Le Gal et al., 20113 / European / With febrile seizures / 0.76 (0.19) / 39% / 76 / 48 / 217 / 181
Balan et al., 20124 / Indian / With febrile seizures / 0.61 (0.001) / 38% / 172 / 104 / 284 / 280
Zhang et al., 20105 / Chinese / With febrile seizures / 0.90 (0.50) / 40% / 117 / 77 / 967 / 707
Schlachter et al., 20091 / European / Without febrile seizures / a0.93 (0.28) / 47% / 516 / 456 / 725 / 677
Petrovski et al., 20092 / European / Without febrile seizures / a / 46% / 522 / 442
Le Gal et al., 20113 / European / Without febrile seizures / 1.04 (0.81) / 46% / 121 / 105 / 217 / 181
Balan et al., 20124 / Indian / Without febrile seizures / 0.57 (0.005) / 36% / 83 / 47 / 284 / 280
Zhang et al., 20105 / Chinese / Without febrile seizures / 0.85 (0.04) / 38% / 770 / 480 / 967 / 707
Schlachter et al., 20091 / European / All epilepsy / a0.85 (0.05) / 44% / 641 / 511 / 725 / 677
Petrovski et al., 20092 / European / All epilepsy / a / 45% / 610 / 506
Le Gal et al., 20113 / European / All epilepsy / 0.93 (0.63) / 44% / 197 / 153 / 217 / 181
Grover et al., 20106 / Indian / All epilepsy / 1.04 (0.80) / 46% / 388 / 336 / 94 / 78
Balan et al., 20124 / Indian / All epilepsy / 0.60 (0.001) / 37% / 255 / 151 / 284 / 280
Kumari et al., 20137 / Indian / All epilepsy / 0.50 (<0.001) / 40% / 585 / 385 / 268 / 328
Current study / Indian / All epilepsy / 0.76 (0.07) / 34% / 198 / 104 / 268 / 200
Hung et al., 20128 / Chinese / All epilepsy / 1.03 (0.83) / 39% / 285 / 183 / 233 / 145
Zhang et al., 20105 / Chinese / All epilepsy / b
Current study / Chinese / All epilepsy / 0.86 (0.009) / 38% / 1370 / 832 / 1529 / 1085
Current study / Malay / All epilepsy / 0.87 (0.23) / 39% / 298 / 188 / 413 / 301
Total / All / All epilepsy / 4827 / 3349 / 4051 / 3275

Published studies used for meta-analysis of the association of SCN1AIVS5N+5G>A with epilepsy.

aThe controls for the study by Petrovski et al were the same as those used in the Schlachter et al study, thus the two studies were combined for odds ratio calculation and meta-analysis.

bFor analysis of all epilepsy patients, the Zhang et al study comprised a subset of subjects in the current study and thus was not included in the meta-analysis.

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References

1. Schlachter K, Gruber-Sedlmayr U, Stogmann E, et al. A splice site variant in the sodium channel gene SCN1A confers risk of febrile seizures. Neurology. 2009;72(1526-632; 11):974-978.

2. Petrovski S, Scheffer IE, Sisodiya SM, O'Brien TJ, Berkovic SF, EPIGEN Consortium. Lack of replication of association between scn1a SNP and febrile seizures.Neurology. 2009;73(22):1928-1930.

3. Le Gal F, Salzmann A, Crespel A, Malafosse A. Replication of association between a SCN1A splice variant and febrile seizures. Epilepsia. 2011;52(10):e135-8.

4. Balan S, Vellichirammal NN, Banerjee M, Radhakrishnan K. Failure to find association between febrile seizures and SCN1A rs3812718 polymorphism in south Indian patients with mesial temporal lobe epilepsy and hippocampal sclerosis. Epilepsy Res. 2012;101(3):288-292.

5. Zhang C, Wong V, Ng PW, et al. Failure to detect association between polymorphisms of the sodium channel gene SCN1A and febrile seizures in Chinese patients with epilepsy. Epilepsia. 2010;51(1528-1167; 0013-9580; 9):1878-1881.

6. Grover S, Gourie-Devi M, Baghel R, et al. Genetic profile of patients with epilepsy on first-line antiepileptic drugs and potential directions for personalized treatment. Pharmacogenomics. 2010;11(7):927-941.

7. Kumari R, Lakhan R, Kumar S, et al. SCN1AIVS5-91G>A polymorphism is associated with susceptibility to epilepsy but not with drug responsiveness. Biochimie. 2013;95(6):1350-1353.

8. Hung CC, Chang WL, Ho JL, et al. Association of polymorphisms in EPHX1, UGT2B7, ABCB1, ABCC2, SCN1A and SCN2A genes with carbamazepine therapy optimization. Pharmacogenomics. 2012;13(2):159-169.

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