<p>Wirgenes et al.</p><p>Supplemental information</p><p>Supplemental Methods and Materials</p><p>MR image acquisition and processing</p><p>To obtain the subcortical volumes, each voxel in the MRI volume was automatically assigned a neuroanatomical label based on probabilistic information estimated automatically from a manual training set (1). The validity of the volumes as obtained by FreeSurfer has been tested against manual tracings, and the agreement between automated and manual volume measures has been reported to be comparable to that obtained by comparing the manual volume measures of different experts (1). To obtain measures of cortical thickness a 3-dimensional model of the cortical surface was created (2;3) and cortical thickness was estimated as the distance between the gray/white matter boundary and the pial surface at approximately 160 </p><p>000 points (vertices) in each hemisphere, the vertices are arranged in a triangular grid with approximately 1 mm spacing. Topological defects in the gray/white matter boundary were manually fixed by laboratory assistants blinded to diagnostic group identity. Maps were smoothed and averaged across participants using a non-rigid high-dimensional spherical averaging method to align cortical folding patterns (4). This procedure provides accurate matching of morphologically homologous cortical locations across subjects on the basis of each individual's anatomy while minimizing metric distortion. The maps thus produced are not restricted to the voxel resolution of the original images and are capable of detecting sub millimeter differences between groups (5). Estimates of cortical area were obtained by computing the area of each triangle in a standardized, spherical atlas space surface tessellation, when mapped into the individual subject space.</p><p>Genotyping and SNP selection</p><p>1 Wirgenes et al.</p><p>Overall, low-yield samples (call rate less than 95%), one of two duplicates, one of two relatives (IBD>0.1875), samples with a reported gender differing from that determined by X chromosome marker homozygosity, samples with outlying levels of heterozygosity and samples with non-European ancestry (as calculated by pairwise genomewide identity-by-state </p><p>(IBS)) were excluded. SNPs were excluded based on deviation from Hardy–Weinberg equilibrium (P < 1 × 10−6), low-yield (<95% in controls) or with minor allele frequencies below 0.10.</p><p>RNA measures</p><p>Reactions were done in duplicates in MicroAmp Optical 384-well plates covered by Optical </p><p>Adhesive Film (Applied Biosystems). The PCR program was 95°C for 10 min before 40 cycles of 95°C for 15 s, and 60°C for 1 min. Relative mRNA levels were obtained by the comparative threshold (Ct) method (2- Ct method; User Bulletin No. 2, Applied Biosystems) using 40 cycles as calibration Ct. Variations in input of RNA amounts were compensated for by normalizing with ACTB RNA levels. The data were analyzed with Applied Biosystems </p><p>RQ Manager, Version 1.2.</p><p>Table S1. Number of patients within each diagnosis spectrum Diagnostic spectrum Diagnosis Number Schizophrenia Schizophrenia 225 Schizophreniform 23 Schizoaffective 52 Bipolar disorder Bipolar type 1 131 Bipolar type 2 2 60 Bipolar disorder NOS 13 Major depressive disorder, psychotic 19 Other psychosis Psychosis NOS 73 NOS: not otherwise specified. Wirgenes et al.</p><p>Table S2. Number of subjects in each analysis. Symptoms Neurocognition vs MRI vs RNA vs RNA vs Diagnosis vs SNP SNP SNP SNP diagnosis Schizophrenia 300 225 106 155 232 Bipolar disorder 223 223 123 147 200 Other psychoses 73 62 39 40 73 Controls - 385 212 182 212 Total 596 895 480 542 717 SNP: Single nucleotide polymorphism. MRI: Magnetic resonance imaging. RNA: ribonucleic acid.</p><p>3 Wirgenes et al.</p><p>Table S3.</p><p>Association with schizophrenia Minor / major MAF - MAF - HWE - Chi SNP Position allele patients controls Genotype1 controls square 2 P OR</p><p> rs8087654 52871764 A/G 0.4327 0.4236 252/648/435 0.7545 0.03217 0.8577 1.020</p><p> rs1788014 52886436 G/A 0.4398 0.4196 270/653/446 0.535 0.5063 0.4767 1.079</p><p> rs11665032 52886611 A/G 0.31 0.298 132/576/659 0.3998 1.02 0.3124 1.123</p><p> rs1261086 52888825 C/T 0.4389 0.4196 269/654/447 0.535 0.4273 0.5133 1.073</p><p> rs11152291 52889067 A/G 0.2505 0.2449 85/512/768 0.274 0.058 0.8097 1.030</p><p>4 Wirgenes et al.</p><p> rs1261085 52889967 G/A 0.4025 0.3839 229/631/509 0.5217 0.2831 0.5947 1.06</p><p> rs2276195 52896509 A/G 0.3284 0.3162 135/601/604 0.1972 0.7327 0.392 1.103</p><p> rs1261073 52907820 G/T 0.4098 0.3895 217/673/476 0.4554 0.1683 0.6816 1.046</p><p> rs1261076 52908326 C/T 0.5005 0.4745 333/687/350 0.4783 0.5584 0.4549 1.083</p><p> rs1942265 52915567 G/C 0.3326 0.3278 146/619/605 0.3018 0.01914 0.89 1.016</p><p> rs7241077 52915706 A/T 0.3326 0.3278 146/619/605 0.3018 0.01914 0.89 1.016</p><p> rs1893431 52918500 A/G 0.4156 0.3962 223/675/465 0.5269 0.0432 0.8353 1.023</p><p> rs4800988 52919906 A/T 0.3311 0.3265 145/617/608 0.3024 0.03623 0.849 1.022</p><p> rs1539951 52921673 C/T 0.329 0.3252 139/616/603 0.1678 0.0005721 0.9809 0.9973</p><p> rs1261134 52931763 T/A 0.3974 0.3878 212/659/499 0.7497 0.006281 0.9368 1.009</p><p> rs1788027 52942827 T/C 0.492 0.4666 300/697/341 0.8385 0.7248 0.3946 1.096</p><p> rs3794894 52968200 A/C 0.2256 0.2411 68/493/806 0.336 0.8488 0.3569 0.89</p><p> rs1660242 53038676 T/A 0.4117 0.4247 238/663/467 0.6064 1.077 0.2993 0.8938</p><p> rs1440476 53040066 G/C 0.4048 0.4054 220/663/477 0.8343 0.4328 0.5106 0.9308</p><p> rs1788025 53048678 G/T 0.418 0.4286 235/684/449 0.1798 0.4441 0.5051 0.9307</p><p> rs17594301 53048885 C/T 0.1145 0.1033 19/269/1082 1 0.2307 0.631 1.085</p><p> rs1788019 53050523 A/G 0.2586 0.2877 91/548/728 0.02592* 2.088 0.1484 0.8405</p><p> rs9958125 53053585 C/T 0.1549 0.1365 35/342/993 0.5175 0.5397 0.4626 1.117</p><p> rs9320010 53053897 G/A 0.4041 0.4133 220/677/473 0.3486 0.7669 0.3812 0.9094</p><p> rs3794891 53055212 A/C 0.2471 0.2769 75/539/733 0.1641 2.578 0.1084 0.8213</p><p> rs12607679 53059748 C/T 0.2505 0.2789 82/535/733 0.04359* 2.629 0.1049 0.82</p><p> rs1020169 53066079 A/T 0.2508 0.2806 86/539/745 0.03296* 2.767 0.0962 0.817</p><p> rs2958186 53077795 T/C 0.269 0.2943 99/556/708 0.03813* 2.949 0.08595 0.8135</p><p> rs2119292 53082974 C/T 0.1194 0.1008 14/284/1070 0.7827 0.4106 0.5217 1.116</p><p> rs2919451 53084300 T/C 0.395 0.4041 194/682/466 0.01486 * 0.3428 0.5582 0.9376</p><p> rs2958163 53085412 C/T 0.4392 0.4437 257/677/415 0.2149 0.1138 0.7359 0.9642</p><p> rs1377243 53134652 T/C 0.4083 0.3839 226/647/497 0.2855 1.482 0.2235 1.141</p><p> rs2958183 53150076 C/T 0.286 0.3048 130/537/703 0.006165* 0.0006317 0.9799 1.003</p><p> rs2060889 53159541 C/A 0.2879 0.2982 124/541/694 0.02867* 0.1428 0.7055 1.045</p><p> rs2958188 53165959 T/C 0.4392 0.412 259/664/444 0.7552 0.7532 0.3855 1.098</p><p> rs17597288 53177208 G/A 0.1184 0.1295 20/292/1041 0.8219 1.029 0.3104 0.8465</p><p> rs9957668 53177670 C/T 0.3829 0.338 202/612/556 0.9104 3.166 0.07517 1.217 5 Wirgenes et al.</p><p> rs9954890 53177740 A/T 0.3658 0.3282 180/606/571 1 2.346 0.1256 1.187</p><p> rs9964328 53177774 C/G 0.3675 0.3248 179/607/569 1 3.112 0.07773 1.217</p><p> rs627685 53186092 G/A 0.3139 0.3491 135/613/618 0.4385 5.058 0.02451* 0.7732</p><p> rs9949107 53193424 A/G 0.3674 0.3359 168/641/548 0.6506 0.4879 0.4849 1.081</p><p> rs4801158 53195888 T/C 0.3636 0.3385 162/645/546 1 0.1783 0.6729 1.049</p><p> rs9636107 53200117 G/A 0.4609 0.4604 284/685/393 1 0.3783 0.5385 1.068</p><p> rs41396445 53242137 A/C 0.3358 0.375 173/600/588 0.9142 0.9697 0.3248 0.896</p><p> rs618869 53248151 T/C 0.131 0.1266 24/308/1034 0.4891 0.6187 0.4315 1.131</p><p> rs12457949 53258609 C/T 0.1862 0.2105 46/436/887 0.128 2.36 0.1244 0.8135</p><p> rs13381608 53259146 A/G 0.2241 0.2092 61/483/825 1 0.3127 0.5761 0.9291</p><p> rs17061809 53267742 G/C 0.127 0.1483 17/329/1019 0.6884 2.166 0.1411 0.7937</p><p> rs17514172 53269093 A/G 0.1872 0.2121 49/429/880 0.3624 3.125 0.07712 0.7869</p><p> rs682245 53270531 T/C 0.4912 0.4349 326/651/393 0.7578 3.152 0.07584 1.209</p><p> rs17514242 53270902 G/C 0.3171 0.3495 150/594/626 0.1488 0.3046 0.581 0.9398</p><p> rs12455205 53272160 G/A 0.1857 0.2105 46/434/886 0.128 2.654 0.1033 0.8027</p><p> rs12458118 53276116 A/T 0.4922 0.4413 328/654/388 0.6087 2.519 0.1125 1.184</p><p> rs9951280 53276523 G/A 0.4922 0.4413 328/653/388 0.6087 2.519 0.1125 1.184</p><p> rs10871582 53276589 A/C 0.3174 0.3504 149/596/623 0.2214 0.42 0.5169 0.9296</p><p> rs7236100 53302321 G/A 0.3118 0.2911 132/556/651 0.9016 0.02342 0.8784 1.018</p><p> rs1421024 53309114 T/C 0.4657 0.4273 302/641/424 0.3547 1.322 0.2503 1.131</p><p> rs9946669 53311559 T/C 0.4692 0.4309 303/644/415 0.3555 1.124 0.2891 1.12</p><p> rs11151206 53316911 A/G 0.4692 0.4298 303/645/416 0.3543 1.755 0.1852 1.153</p><p>SNP information. MAF: Minor allele frequency. HWE: Hardy- Weinberg equilibrium. OR: odds ratio. * Significant results p<0,05. 1 Genotype count. 2 Allelic chi square tests for association with schizophrenia.</p><p>6 Wirgenes et al.</p><p>Table S4. TCF4 mRNA in relation to medication.</p><p>Schizophrenia Bipolar disorder Other psychoses Total patient (n = 232) (n = 200) (n = 73) sample (n = 505)</p><p>Single antipsychotic (n = 139) 9.87 (0.44) 9.73 (0.60) 9.74 (0.46) 9.85 (0.47) Multiple antipsychotics (n = 31) 9.81 (0.47) 9.98 (0.14) 9.67 (0.51) 9.81 0.45) Lithium (n =3) - 10.21 (0.71) - 10.21 (0.71) Anticonvulsiva (n = 18) 10.28 (0.44) 9.58 (0.63) - 9.66 (0.64) Antidepressants (n = 26) 9.77 (0.60) 9.78 (0.43) 9.97 (0.49) 9.80 (0.49) Polypharmacy 1 (n = 214) 10.02 (0.48) 9.92 (0.60) 9.90 (0.55) 9.95 (0.55) Unmedicated (n = 74) 9.66 (0.49) 9.74 (0.49) 10.00 (0.34) 9.68 (0.52) Mean (standard deviation) are presented.</p><p>1 Polypharmacy: Combinational treatment of more than one type of psychotropic.</p><p>7 Wirgenes et al.</p><p>Table S5.</p><p>8 Wirgenes et al.</p><p>Digit Frontal Tempora Positive Negative Symbol Verbal Verbal cortical l cortical Cerebell Ventricul Hippoca Frontal Tempora TCF4 sympto sympto Coding Inhibition/ Verbal fluency - fluency - thicknes thicknes Brain ar ar mpal cortical l cortical expression ms ms CVLT 1 Test 2 Inhibition switching fluency-1 2 3 IQ s s volume volume volume volume area area TCF4 Pearson 1 expression Correlation Sig. (2- tailed) N 717 Positive Pearson ,067 1 symptoms Correlation Sig. (2- 0,13* tailed) N 499 1055 Negative Pearson ,100 ,421 1 symptoms Correlation Sig. (2- 0,025* <0.0005 tailed) N 499 1054 1056 CVLT 1 Pearson -,118 -,182 -,223 1 Correlation Sig. (2- 0,0034* <0.0005 <0.0005 tailed) N 616 824 824 1304 Digit symbol Pearson -,183 -,203 -,300 ,499 1 coding test 2 Correlation Sig. (2- <0.0005* <0.0005 <0.0005 <0.0005 tailed) N 618 826 826 1303 1308 Inhibition Pearson ,099 ,174 ,197 -,410 -,592 1 Correlation Sig. (2- ,014 <0.0005 <0.0005 <0.0005 <0.0005 tailed) N 614 823 823 1296 1298 1299 Inhibition/ Pearson ,055 ,155 ,194 -,392 -,599 ,760 1 switching Correlation Sig. (2- ,169 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 tailed) N 615 823 823 1299 1301 1299 1302 Verbal fluency -1 Pearson -,072 -,183 -,308 ,406 ,499 -,423 -,436 1 Correlation Sig. (2- ,076 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 tailed) N 616 819 819 1294 1295 1289 1292 1296 Vebal fluency -2 Pearson -,130 -,201 -,341 ,446 ,578 -,512 -,477 ,706 1 Correlation Sig. (2- 0,0012* <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 tailed) N 615 817 817 1292 1293 1287 1290 1294 1294 Verbal fluency -3 Pearson -,121 -,206 -,324 ,429 ,543 -,486 -,422 ,532 ,656 1 Correlation Sig. (2- 0,0026* <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 tailed) N 615 817 817 1292 1293 1287 1290 1294 1293 1294 IQ Pearson -,124 -,214 -,286 ,446 ,567 -,509 -,462 ,592 ,576 ,480 1 Correlation Sig. (2- 0,0022* <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 tailed) N 609 809 809 1284 1286 1279 1282 1284 1283 1283 1287 Frontal cortical Pearson -,145 ,003 -,019 ,190 ,203 -,146 -,177 ,061 ,077 ,078 ,119 1 thickness Correlation Sig. (2- ,007 ,956 ,711 <0.0005 <0.0005 <0.0005 <0.0005 ,130 ,055 ,052 ,003 tailed) N 342 391 392 615 617 613 615 614 614 614 611 648 Temporal Pearson -,112 -,050 ,030 ,186 ,177 -,163 -,175 ,074 ,104 ,080 ,185 ,777 1 cortical Correlation thickness Sig. (2- ,038 ,328 ,554 <0.0005 <0.0005 <0.0005 <0.0005 ,066 ,010 ,049 <0.0005 <0.0005 tailed) N 342 391 392 615 617 613 615 614 614 614 611 648 648 Brain volume Pearson -,032 ,058 ,065 -,060 ,118 -,051 -,088 ,061 ,146 ,009 ,293 ,174 ,263 1 Correlation Sig. (2- ,556 ,252 ,196 ,136 ,003 ,210 ,029 ,134 <0.0005 ,831 <0.0005 <0.0005 <0.0005 tailed) N 342 391 392 615 617 613 615 614 614 614 611 648 648 648 Cerebellar Pearson -,003 ,063 ,116 -,057 ,102 -,042 -,049 ,048 ,102 -,001 ,263 ,157 ,213 ,735 1 volume Correlation Sig. (2- ,954 ,213 ,022 ,159 ,011 ,303 ,226 ,238 ,012 ,975 <0.0005 <0.0005 <0.0005 <0.0005 tailed) N 342 391 392 615 617 613 615 614 614 614 611 648 648 648 648 Ventricular Pearson ,117 -,007 -,028 -,197 -,145 ,134 ,166 ,002 -,050 -,120 -,019 -,249 -,169 ,199 ,151 1 volume Correlation Sig. (2- ,031 ,893 ,575 <0.0005 <0.0005 ,001 <0.0005 ,954 ,213 ,003 ,641 <0.0005 <0.0005 <0.0005 <0.0005 tailed) N 342 391 392 615 617 613 615 614 614 614 611 648 648 648 648 648 Hippocampal Pearson -,048 ,028 ,060 ,016 ,141 -,050 -,074 ,034 ,136 ,068 ,211 ,166 ,233 ,623 ,513 -,100 1 volume Correlation Sig. (2- ,376 ,576 ,237 ,701 <0.0005 ,214 ,067 ,395 ,001 ,094 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 ,011 tailed) N 342 391 392 615 617 613 615 614 614 614 611 648 648 648 648 648 648 Frontal cortical Pearson -,002 ,036 ,073 -,080 ,053 -,009 -,036 ,006 ,092 -,032 ,246 -,049 ,099 ,883 ,612 ,225 ,562 1 area Correlation Sig. (2- ,964 ,473 ,150 ,046 ,190 ,831 ,378 ,873 ,023 ,426 <0.0005 ,212 ,012 <0.0005 <0.0005 <0.0005 <0.0005 tailed) N 342 391 392 615 617 613 615 614 614 614 611 648 648 648 648 648 648 648 Temporal Pearson ,021 ,037 ,050 -,081 ,057 -,013 -,046 ,033 ,109 -,001 ,277 -,035 ,066 ,885 ,635 ,227 ,579 ,918 1 cortical area Correlation Sig. (2- ,703 ,466 ,325 ,044 ,160 ,755 ,257 ,409 ,007 ,987 <0.0005 ,372 ,091 <0.0005 <0.0005 <0.0005 <0.0005 <0.0005 tailed) N 342 391 392 615 617 613 615 614 614 614 611 648 648 648 648 648 648 648 648</p><p>Pearson correlation between all phenotypes in the current study. N: number. Results remaining significant after controlling for age in a Partial correlation analysis between TCF4 mRNA and symptoms, between mRNA and cognitive tests and between mRNA and brain morphological summary measures are marked with a star *. 1 California Verbal Learning Test-Second edition (CVLT –II). 2 Digit Symbol Coding Test (WAIS-III). 9 Wirgenes et al.</p><p>Table S6. TCF4 mRNA levels and association with diagnosis. Diagnosis (A) Diagnosis (B) Mean difference (A-B) SE p Schizophrenia (n= 232) Bipolar disorder 0.043 0.050 0.82 Other psychoses 0.033 0.070 0.96</p><p>10 Wirgenes et al.</p><p>Controls 0.21 0.049 0.000086 Bipolar disorder (n= 200) Other psychoses -0.0098 0.071 1 Controls 0.17 0.051 0.005 Other psychoses (n= 73) Controls 0.18 0.070 0.049 SE: standard error. Results from the ANOVA post hoc Tukey test comparing RNA level between groups. </p><p>Table S7. TCF4 mRNA level vs TCF4 SNPs and negative symptoms TCF4 mRNA Negative symptoms TCF4 mRNA - r =0.10, p= 0.004 1 TCF4 mRNA - r =0.14, p= 0.016 2 rs11151206 Beta = -0.12, p= 0.025 Beta = -1.05, p= 0.042 rs1421024 Beta = -0.11, p= 0.029 -</p><p>11 Wirgenes et al. rs9946669 Beta = -0.10, p= 0.046 - rs682245 Beta = -0.10, p= 0.046 - Results from the analysis of TCF4 SNPs and TCF4 mRNA level and the correlation with negative symptoms. The results from the SNP analysis are specific to schizophrenia, and only SNPs associated with mRNA level at a nominal p-vale < 0.05 are presented. P values are uncorrected. 1 Partial correlation, total sample. 2 Partial correlation, schizophrenia sample.</p><p>Figure S1 (A)</p><p>12 Wirgenes et al.</p><p>Figure S1 (B)</p><p>Figure S1. (A) LD between the five schizophrenia SNPs. (B) LD spanning all the investigated SNPs in the TCF4 region. LD: linkage disequilibrium. TCF4: transcription factor 4. SNP: single nucleotide polymorphism. Data was lacking for rs1261073.</p><p>Reference List</p><p>13 Wirgenes et al.</p><p>(1) Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C et al. Whole brain </p><p> segmentation: automated labeling of neuroanatomical structures in the human brain. </p><p>Neuron 2002; 33: 341-355.</p><p>(2) Dale AM, Sereno MI. Improved localization of cortical activity by combining EEG and </p><p>MEG with MRI cortical surface reconstruction: A linear approach. Journal of Cognitive</p><p>Neuroscience 1993; 5: 162-176.</p><p>(3) Dale AM, Fischl B, Sereno MI. Cortical surface-based analysis. I. Segmentation and </p><p> surface reconstruction. Neuroimage 1999; 9:179-194.</p><p>(4) Fischl B, Sereno MI, Dale AM. Cortical surface-based analysis. II: Inflation, flattening, </p><p> and a surface-based coordinate system. Neuroimage 1999; 9:195-207.</p><p>(5) Fischl B, Dale AM. Measuring the thickness of the human cerebral cortex from </p><p> magnetic resonance images. Proc Natl Acad Sci U S A 2000; 97:11050-5.</p><p>14</p>