The TNF Gene Predicts Hippocampus Volume in Healthy Individuals

Multimodal imaging of a tescalcin (TESC)-regulating polymorphism

(rs7294919) – specific effects on hippocampal gray matter structure

- Supplementary material -

Udo Dannlowski, MD, MA, PhD 1,2,*,#, Hans Jörgen Grabe, MD 3,4,#, Katharina

Wittfeld 4, Johannes Klaus 1, Carsten Konrad, MD 2, Dominik Grotegerd, MSc

1, Ronny Redlich, MA 1, Thomas Suslow, PhD 1,5, Nils Opel 1, Patricia

Ohrmann, MD 1, Jochen Bauer, PhD 1, Peter Zwanzger, MD 1, Inga Laeger,

MA 1, Christa Hohoff, PhD 1, Volker Arolt, MD 1, Walter Heindel, MD 6, Michael

Deppe, PhD 7, Katharina Domschke, MD, MA, PhD 8, David Stacey, PhD 12,

Katrin Hegenscheid, MD 9, Henry Völzke, MD 10, Henriette Meyer zu

Schwabedissen, MD 11, Harald Kugel, PhD 6, and Bernhard T. Baune, MD,

PhD, MPH, FRANZCP 12

1 Department of Psychiatry, University of Münster, Germany; 2 Department of Psychiatry, University of Marburg, Germany; 3 Department of Psychiatry, University Medicine Greifswald, HELIOS-Hospital Stralsund, Germany; 4 German Center for Neurodegenerative Diseases (DZNE), Site Rostock/ Greifswald, Germany; 5 Department of Psychosomatic Medicine and Psychotherapy, University of Leipzig, Germany; 6 Department of Clinical Radiology, University of Münster, Germany; 7 Department of Neurology, University of Münster, Germany; 8 Department of Psychiatry, University of Würzburg, Germany; 9 Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Germany; 10 Institute for Community Medicine, University Medicine Greifswald, Germany, 11 Biopharmacy, Department Pharmaceutical Sciences, University of Basel, Switzerland; 12 Discipline of Psychiatry, School of Medicine, University of Adelaide: North Terrace, Adelaide, Australia Supplementary methods Genotyping. In the Münster sample, genotyping of 1 TESC, 10 RELN,

3 BDNF, 1 TNF-α, 4 IL6, and 5 FKBP5 SNPs was carried out following published protocols applying the multiplex genotyping assay iPLEX™ for use with the MassARRAY platform 1, yielding genotyping completion rates of

98.2%, 97.2%, 97.4%, 99.6%, 99.1%, and 97.8% for the above genes, respectively. 5-HTTLPR (L/S) and rs25531 (A/G) genotypes were ascertained by PCR-RFLP analysis. Briefly, PCR primers were forward (5’ – GGC GTT

GCC GCT CTG AAT GC – 3’) and reverse (5’ – GAG GGA CTG AGC TGG

ACA ACC AC – 3’). PCR products were digested using MspI enzyme from

New England Biolabs (NEB) (Genesearch, Adelaide, Australia), with expected fragment lengths of 297bp for the S allele, 340bp for the L A allele, and 170bp

2 for the LG allele . The completion rate of 5-HTTLPR/rs25531 genotyping was

99.4%. All genotyping was performed by investigators blinded for the study.

In the SHIP-TREND sample, genotyping of rs7294919 was performed using the pre-developed TaqMan® SNP Genotyping Assay C__43496979_10

(Life technologies, Applied Biosystems, Darmstadt, Germany). In detail, reactions were carried out in a 5µl volume containing 1µl genomic DNA,

0.25µl Primer/Probe-Mix, 2.5µl Genotyping Master Mix and 1.25µl water.

Fluorescence was assessed for using the Fast Real-Time PCR system 7900

HT (Applied Biosystems) and the Sequence Detection Software SDS 2.3. All failing samples were repeated at least twice.

VBM methods. Images were bias-corrected, tissue classified, and normalized to MNI-space using linear (12-parameter affine) and non-linear transformations, within a unified model 3 including high-dimensional DARTEL- normalization. Gray matter segments were modulated only by the non-linear components in order to preserve actual gray matter values locally (modulated

GM volumes). Using these procedures, no further correction for total brain volume is required anymore.

Homogeneity of gray matter images was checked using the covariance structure of each image with all other images, as implemented in the check data quality function. The modulated gray matter images were smoothed with a Gaussian kernel of 8 mm FWHW.

Gene x gene interactions. Gene-gene interactions of rs7294919 were explored with genes known to have neurodevelopmental (Reelin), neurotrophic (BDNF), stress (HPA-axis; FKBP5) and neuroinflammatory (IL-6,

TNF-α) relevance as well as 5-HTTLPR/rs25531 which has repeatedly been associated with hippocampal volumes 4. These additional genotypes were only available for the Münster sample. For the analysis of epistasis, we have selected a strategy focusing on the hippocampal area most robustly showing effects of TESC rs7294919 (the overlapping area from both samples).

Therefore, mean gray matter values of the right and left cluster were extracted for all subjects. On each polymorphism investigated for epistasis (n=25, see supplementary table 1 for a complete list), analysis of covariance (ANCOVA) was conducted for each cluster (right and left). rs7294919 genotype (TT vs.

CT/TT) and the SNP in question were entered as separate factors. Each SNP was grouped based on allele frequency to achieve a minimum cell size of

N=20 for the interaction analysis in order to ensure robustness of the results.

Age and gender were added as covariates. In addition to all main effects, the interaction term of rs7294919 and each other polymorphism was modelled. The results were Bonferroni-corrected for the number of investigated SNPs

(pcorrected=.05/25=.002).

Gene x environment interaction. The same two hippocampal clusters as in the gene x gene interaction analyses were used. Gray matter values were extracted for both samples and G x E was tested within each sample separately. Again, rs7294919 genotype (TT vs. CT/TT) was entered as factor into one ANCOVA model for each sample. CTQ-scores, age, and gender were added as covariates. Besides all main effects, the interaction term between CTQ-scores and rs7294919 was modelled.

fMRI task. The task consisted of 4 blocks of a face processing task alternating with 5 blocks of a sensorimotor control task. During the face processing task, participants viewed six trios of faces (all three expressing either anger or fear). For each trio, subjects selected 1 of 2 faces (bottom) that was identical to a target face (top). During the sensorimotor control blocks, participants viewed six trios of geometric shapes (circles and ellipses) and selected 1 of 2 shapes (bottom) that were identical to a target shape

(top). In the face-processing blocks, each of the 6 face trios was presented for

4s with a variable inter-stimulus interval of 2s to 6s (mean, 4s), for a total block length of 48s. In the sensorimotor control blocks, each of the 6 shape trios was presented for 4s with a fixed inter-stimulus interval of 2s, for a total block length of 36s. Total task time was 390s. Participant performance

(accuracy and reaction time) was recorded.

T2* weighted functional data were acquired at the same scanner as the structural images, using a single shot echoplanar sequence with parameters selected to minimize distortion in the region of central interest, while retaining adequate signal to noise ratio (S/N) and T2* sensitivity. Volumes consisting of

34 slices were acquired (matrix 64×64, resolution 3.6mm × 3.6mm × 3.6mm;

TR=2.1s, TE=30ms, FA=90°). The slices were tilted 25° from the AC/PC line in order to minimize drop out artefacts in the orbitofrontal and mediotemporal region. Functional imaging data were realigned and unwarped, spatially normalized to standard MNI space (Montreal Neurological Institute) and smoothed (Gaussian kernel, 6mm FWHM) using Statistical Parametric

Mapping (SPM8, http://www.fil.ion.ucl.ac.uk/spm).

For each participant, one contrast image was generated in each individual fixed-effects 1st-level analysis comparing activation in response to faces with the shapes baseline.

Functional connectivity. We calculated functional connectivity in the fMRI-sample using the hippocampus clusters most robustly affected by

TESC-genotype (the same overlapping area from both sites used for morphometric GxG and GxE analyses) as one (bilateral) seed region. As in previous studies of our group 5 the time series of the seed volume was extracted for each subject separately and these were entered for each subject into a new 1st-level model predicting brain-wide activity by the extracted hippocampus signal, yielding connectivity maps of the hippocampal region of interest. The experimental conditions were also modelled as nuisance regressors to control for co-activation by the task.

As in the standard fMRI analyses, the resulting functional connectivity maps were entered into a 2nd-level group analysis, again using a t-test contrasting TT homozygotes vs. C-carrier with age and gender as nuisance regressors. Supplementary Results

Gene x gene interactions. Four SNPs reached nominal or marginal significance, three in the Reelin gene and one in the IL6 gene (Please see supplementary table 1). However, just one SNP of the Reelin gene

(rs2299403) reached the corrected significance level (right cluster;

F(1,487)=12.72, p=.0004). The main effect of TESC rs7294919 was only found in the group of rs2299403 GG homozygotes (N=346) and not in carriers of one or two T-alleles (N=147). See supplementary figure 1.

Gene x environment interaction. In both samples, there was no evidence for an interaction of rs7294919 and childhood maltreatment (CTQ- scores), Münster sample: right hippocampus, F(1,302)=1.77, p=.18; left hippocampus: F(1,302)=.71, p=.40; SHIP-TREND: right hippocampus,

F(1,650)=1.01, p=.32; left hippocampus: F(1,650)=2.68, p=.1.

Functional connectivity. While across all subjects, strong connectivity patterns with prefrontal and occipital / inferior temporal areas emerged, no significant genotype effects could be discerned at a corrected level of significance. Using the same lenient threshold as used for the other fMRI and

DTI data (p<0.005, k=30), only one cluster survived showing any genotype effects on functional connectivity, mapping to the left middle and inferior occipital gyrus (x=-32, y=-90, z=0, Z=3.67, k=76, p=.0001). TT homozygotes showed higher functional connectivity compared to C-allele carriers. However, this cluster would not survive any kind of correction (e.g., pFWE-corrected=0.689). Supplementary Table 1

Selection of genes/ SNPs, genotype distribution, and p-values of the interaction respective terms with TESC rs7294919 genotype.

SNP Groups Grouping Min. cell Results

size Interaction 2

5HTTLPR 171LL, 232LS, 99SS LL vs. S 32 None (p>.5)

5HTTLPR/ rs255311 132LL, 241LS, 129SS 3 Groups 20 None (p>.5)

RELN_rs12705136 48AA, 198GA, 255GG A vs. GG 39 None (p>.5)

RELN_rs2249372 56AA, 194AG, 251GG A vs. GG 42 None (p>.36)

RELN_rs2299403 13TT,134GT, 346GG T vs. GG 30 p=.0004R,

p=.003L

RELN_rs2528856 48CC, 209CT, 242TT C vs. TT 40 None (p>.26)

RELN_rs2711844 31AA, 156 CA, 314CC A vs. CC 33 p=.056R

RELN_rs362691 5CC,109CG,389GG C vs. GG 20 None (p>.14)

RELN_rs39367 79TT,227CT,194CC T vs. CC 34 p=.014L

RELN_rs4460306 121AA, 251CA,131CC C vs. AA 25 None (p>.5)

RELN_rs4621738 63GG, 198AG, 201AA G vs. AA 35 None (p>.28)

RELN_rs528528 114TT,224CT,149CC 3 Groups 25 None (p>.36)

BDNF_rs6265 12AA,151GA,318 GG GG vs. A 29 None (p>.5)

BDNF_rs7103411 15CC,169CT, 306TT TT vs. C 35 None (p>.5)

BDNF_rs7124442 52CC,214CT,226TT TT vs. C 33 None (p>.43)

TNF-α_rs1800629 15AA, 154GA,333GG A vs. GG 21 None (p>.5)

IL6_rs1800795 76CC, 253GC,174GG GG vs. C 37 None (p>.29)

IL6_rs2069833 77CC, 250TC, 175TT C vs TT 37 None (p>.38)

IL6_rs2069840 69GG,226GC,207CC G vs CC 33 None (p>.26)

IL6_rs7801617 5A,89AG,406GG GG vs. A 16 p=.013R

FKBP5_rs1360780 40TT, 260CC, 200TC T vs CC 43 None (p>.5)

FKBP5_rs3800373 35GG, 195GT, 272TT TT vs G 44 None (p>.28)

FKBP5_rs4713916 40AA,195AG, 265GG GG vs. A 43 None (p>.5)

FKBP5_rs9296158 39AA, 203AG, 259GG GG vs. A 43 None (p>.5)

FKBP5_rs9470080 55TT,208CT, 239CC CC vs T 38 None (p>.14) Bold: nominal or marginal significance. 1 The tri-allelic model was used.

2 Groups were built as carriers of 0,1, or 2 LALA alleles. R, right hippocampus cluster; L, left hippocampus cluster Supplementary Figure 1 Interaction of TESC (rs7294919) and RELN (rs2299403) genotype on right hippocampal gray matter volume. Error bar, S.E.M. References

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