Supplementary Data from Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma (2023)

&lt;p&gt;Supplementary Figure 1: Quantile-Quantile Plots of -log10 (P-value) associations. (a) TWAS for GBM glioma; (b) TWAS for GBM glioma (lower 90% of associations); (c) TWAS for non-GBM glioma; (d) TWAS for non-GBM glioma (lower 90% of associations); (e) GWAS meta-analysis for GBM glioma; (f) GWAS meta-analysis for GBM glioma (lower 90% of associations); (g) GWAS meta-analysis for non-GBM glioma; (h) GWAS meta-analysis for non-GBM glioma (lower 90% of associations). Supplementary Figure 2: Manhattan Plots of SNP genomic co-ordinates against GWAS meta-analysis -log10 (P-value). (a) GBM glioma; (b) Non-GBM glioma. The red line represents the Bonferroni-corrected threshold of P{less than or equal to}5Ã-10-8. Supplementary Figure 3: Dendograms to display gene module clustering in brain tissues. Clustering was performed using the WGCNA (11) package for each tissue. (a) Amygdala; (b) Anterior cingulate cortex (BA24); (c) Caudate (basal ganglia); (d) Cerebellar Hemisphere; (e) Cerebellum; (f) Cortex; (g) Frontal Cortex (BA9); (h) Hippocampus; (i) Hypothalamus; (j) Nucleus accumbens (basal ganglia); (k) Putamen (basal ganglia); (l) Spinal cord (cervical c-1); (m) Substantia nigra. Supplementary Figure 4: Heatmaps illustrating gene module correlations in brain tissues. Darker colours indicate stronger associations. (a) Amygdala; (b) Anterior cingulate cortex (BA24); (c) Caudate (basal ganglia); (d) Cerebellar Hemisphere; (e) Cerebellum; (f) Cortex; (g) Frontal Cortex (BA9); (h) Hippocampus; (i) Hypothalamus; (j) Nucleus accumbens (basal ganglia); (k) Putamen (basal ganglia); (l) Spinal cord (cervical c-1); (m) Substantia nigra. Supplementary Figure 5: Module clustering of brain tissues with amygdala. Modules were created by clustering according to the amygdala tissue using WGCNA (11). These modules were applied to each tissue in turn and the Z statistic is a quantitative measure of module preservation. (a) Amygdala (reference); (b) Anterior cingulate cortex (BA24); (c) Caudate (basal ganglia); (d) Cerebellar Hemisphere; (e) Cerebellum; (f) Cortex; (g) Frontal Cortex (BA9); (h) Hippocampus; (i) Hypothalamus; (j) Nucleus accumbens (basal ganglia); (k) Putamen (basal ganglia); (l) Spinal cord (cervical c-1); (m) Substantia nigra. Supplementary Figure 6: TWAS power plots. Simulation analysis based on 12,488 glioma cases (6,183 GBM, 5,820 non-GBM) and 18,169 controls. Gene expression was generated from the distribution of gene expression levels from the respective brain tissue. Statistical power was calculated at P&lt;5.69x10-6 (the significance threshold used in the main TWAS analysis) according to various cis-heritability (h2) thresholds which are assumed to be equivalent to gene expression prediction models (R2). Power calculations were per 1 s.d. increase or decrease in gene expression based on 1,000 replicates. i) GBM glioma; ii) Non-GBM glioma; (a) Brain Amygdala; (b) Brain Anterior cingulate cortex (BA24); (c) Brain Caudate (basal ganglia); (d) Brain Cerebellar Hemisphere; (e) Brain Cerebellum; (f) Brain Cortex; (g) Brain Frontal Cortex (BA9); (h) Brain Hippocampus; (i) Brain Hypothalamus; (j) Brain Nucleus accumbens (basal ganglia); (k) Brain Putamen (basal ganglia); (l) Brain Spinal cord (cervical c-1); (m) Brain Substantia nigra. Supplementary Figure 7: Association between rs3782473 genotype and GALNT6 expression in GTEx v7 brain tissue. Reference and alternate alleles for rs3782473 are T and C respectively. (a) Caudate (basal ganglia); (b) Putamen (basal ganglia); (c) Frontal Cortex (BA9); (d) Amygdala; (e) Cerebellum; (f) Spinal cord (cervical c-1); (g) Substantia nigra; (h) Cortex; (i) Hypothalamus; (j) Nucleus accumbens (basal ganglia). Supplementary Figure 8: Association plots at glioma risk regions before and after adjusting for eSNPs at significant TWAS genes. (a) 1p31.3 (GBM): i) unadjusted ii) JAK1 eSNP; (b) 5p15.33 (GBM): i) unadjusted ii) TERT eSNP iii) NKD2 eSNP iv) combined eSNP; (c) 5p15.33 (non-GBM): i) unadjusted ii) TERT eSNP; (d) 7p11.2 (GBM): i) unadjusted ii) EGFR eSNP; (e) 9p21.3 (GBM): i) unadjusted ii) CDKN2B eSNP; (f) 11q23.3 (non-GBM): i) unadjusted ii) PHLDB1 eSNP iii) RPL5P30 eSNP iv) TMEM25 eSNP v) TREH eSNP vi) combined eSNP; (g) 12q13.1 (GBM): i) unadjusted ii) GALNT6 eSNP; (h) 16p13.3 (GBM): i) unadjusted ii) IL9RP3 eSNP; (i) 16q12.1 (GBM): i) unadjusted ii) HEATR3 eSNP; (j) 20q13.33 (GBM): i) unadjusted ii) ARFRP1 eSNP iii) DIDO1 eSNP iv) GMEB2 eSNP v) HAR1A eSNP vi) LIME1 eSNP vii) OPRL1 eSNP viii) PCMTD2 eSNP ix) SLC2A4RG eSNP x) STMN3 eSNP xi) TCEA2 eSNP xii) ZGPAT eSNP xiii) combined eSNP; (k) 20q13.33 (non-GBM): i) unadjusted ii) LIME1 eSNP iii) SLC2A4RG eSNP iv) ZGPAT eSNP v) combined eSNP; (l) 22q13.1 (GBM): i) unadjusted ii) BAIAP2L2 eSNP iii) CTA-228A9.3 eSNP iv) PICK1 eSNP v) SLC16A8 eSNP vi) combined eSNP. Each plot shows association results of both genotyped (triangles) and imputed (circles) SNPs in the GWAS samples. â^'log10 P values (y axes) of the SNPs are shown according to their chromosomal positions (x axes). The lead SNP is shown as a large circle. The colour intensity of each symbol reflects the extent of LD with the top genotyped SNP, white (r2 = 0) through to dark red (r2 = 1.0). Genetic recombination rates, estimated using HapMap samples from Utah residents of western and northern European ancestry (CEU), are shown with a light blue line. Physical positions are based on NCBI build 37 of the human genome. Below each plot the location of gene eSNPs are indicated, as well as the relative positions of GENCODE v19 genes mapping to the region of association. Supplementary Table 1: Details of glioma GWAS and SNPs imputed. Successfully imputed SNPs in each discovery series GWAS were those with INFO &gt; 0.4, case and control MAF &gt; 0.01, PHWE in controls &gt; 1x10-8. For the meta-analysis we considered all SNPs meeting the above criteria in all eight studies as well as having heterogeneity I2 &lt; 75 in GBM/non-GBM glioma. a For the UCSF/Mayo study an imputation threshold of &gt; 0.8 was applied. Supplementary Table 2: Prediction models trained on GTEx v7 data and covariance files obtained from http://predictdb.org/. Genes were retained if nested cross-validated correlation between predicted and actual levels &gt; 0.10 (R2&gt;1%) and P-value of the correlation test &lt; 0.05. Supplementary Table 3: Previously reported glioma risk SNPs. Supplementary Table 4: Brain tissue, soft power threshold and number of independent genes. Soft power thresholds were chosen at the 90% threshold unless otherwise indicated. + For Cerebellar Hemisphere and Cerebellum, the 90% threshold was not achieved and 80% was imposed. For this reason such tissues were excluded from median calculations for soft power and number of independent genes. Supplementary Table 8: S-PrediXcan results for 31 genes in 922 whole-blood samples from the Depression Genes and Networks (DGN) study. Supplementary Table 9: Annotation of identified genes by presence within COSMIC cancer gene census and overlap with tumour copy number changes. *Cosmic cancer gene census annotation for CDKN2A was used.&lt;/p&gt;