No Association Between Polygenic Risk for Schizophrenia and Brain Volume in the General Population

Correspondence No Association Between Polygenic Risk for Schizophrenia and Brain Volume in the General Population To the Editor: Schizophrenia is a highly heritable disorder and is associated with gray matter structural brain abnormalities (1). Two studies on the effect of polygenic risk scores (PRS) for schizophrenia on brain volume measures in healthy subjects were published recently with contradicting results. Terwisscha van Scheltinga et al. (2) reported a decrease in total brain volume and white matter volume with increasing burden of risk variants for schizophrenia in 142 healthy subjects, whereas Papiol et al. (3) found no association in a healthy sample of 122 individuals. Both studies relied on relatively small sample sizes and were based on the genome-wide association study (GWAS) results from 9394 cases of schizophrenia (4), which were updated considerably by the recent GWAS including nearly 37,000 cases of schizophrenia (5). We aimed to investigate the putative association between the PRS derived from the new GWAS results (5) and alterations of brain volume in subjects from the general population. We analyzed data from subjects participating in the Study of Health in Pomerania (SHIP-2) and the independent SHIPTREND-0 study (6). All participants were scanned with the same scanner (1.5-tesla MAGNETOM Avanto; Siemens Healthcare, Erlangen, Germany) with a T1-weighted magnetization prepared rapid acquisition gradient-echo (MPRAGE) sequence and the following parameters: axial plane, repetition time 5 1900 msec, echo time 5 3.4 msec, flip angle 5 151, and original resolution of 1.0 mm3 3 1.0 mm3 3 1.0 mm3 image processing (7). After exclusion of medical conditions or technical reasons, complete data sets including genome-wide single nucleotide polymorphism (SNP) typing data were available for 1828 subjects. Applying an age cutoff ,65 years, 1470 subjects remained. Genotyping was performed using Human SNP Array 6.0 (Affymetrix, Santa Clara, California) for SHIP-2 and HumanOmni2.5-Quad (Illumina, Inc., San Diego, California) for a subset of the TREND-0 subjects (n 5 986) (for details and imputation see Völzke et al. (6) and Köttgen et al. (8)). The genetic profile scoring was based on the summary results from the recent meta-analysis on schizophrenia (SNP information including p values and odds ratios) (5) using PLINK (9). To identify polygenic effects owing to independent SNPs in linkage equilibrium, SNPs were pruned based on variance inflation and a pairwise R2 threshold of .25 and a sliding window of 50 SNPs shifting 5 SNPs at each step. We excluded SNPs on chromosomes X and Y, mitochondrial SNPs, and SNPs with a minor allele frequency ,.01, genotype missing rate ..05, deviation from Hardy-Weinberg equilibrium (p , .001), and SNP information score , .9 (imputation quality) in the GWAS on schizophrenia. The PRS for each subject were calculated for different p value thresholds (i.e., 1E-5, 1E-4, .001, .01, .05, .1). For each SNP, the number of risk variants (0–2) in individual carriers was multiplied by the logarithm of

Biological Psychiatry

the odds ratio for the particular variant from the GWAS results. The PRS were z-transformed to aid interpretation of results. Primarily, we analyzed the effects of the different PRS on total brain gray matter (GM), white matter (WM), and total brain volume (TBV) separately using linear regression with age, sex, and total intracranial volume as covariates. We chose restricted cubic splines (10) for age to ensure an adequate model fit because age was not linearly related to brain volumes (neither in SHIP-2 nor in TREND-0). Additionally, we performed hypothesis-free whole-brain analyses (adjusted for age and sex) in which putative effects of the PRS on local GM volumes were analyzed in voxel-based morphometry analyses. The statistical threshold for voxels was puncorrected , .001 with subsequent familywise error correction for peak and cluster level significance using SPM8 (http://www.fil.ion.ucl.ac.uk/ spm/software/spm8/). Brain volume measures were approximately normally distributed in both samples (via Q-Q plots). The variance explained by the PRS was obtained by comparing the adjusted R2 from a model with all covariates and from a model including covariates plus the PRS. Statistical analyses were performed for SHIP-2 and TREND-0 separately with STATA/MP, version 13 (StataCorp LP, College Station, Texas). G*Power version 3.1 (11) was used for power calculation. The target samples comprised 763 subjects in SHIP-2 (n 5 358 men, n 5 405 women) and 707 subjects in TREND-0 (n 5 305 men, n 5 402 women). Participants of SHIP-2 were significantly older than the participants in TREND0 (SHIP-2, 50.1 6 9.4 years old; TREND-0, 46.2 6 11.2 years old). Mean volume measurements in ml were TBV (SHIP-2, 1193.7 6 122.6; TREND-0, 1194 6 120.2), WM (SHIP-2, 612.7 6 76.1; TREND-0, 603.7 6 75.6), and GM (SHIP-2, 581 6 60.3; TREND-0, 591 6 61.2). None of the PRS were associated (p . .05) with TBV, WM, or GM volumes in SHIP-2, TREND-0, or in sex-stratified analyses (Table 1; sex-stratified results not shown). No trends of decreased or increased volume in TBV, WM, or GM could be observed. The increase of variance explained through the PRS was minimal (R2 change ,.1% in all analyses). Also, the voxel-based morphometry whole-brain analyses revealed no statistically significant GM cluster for any of the PRS in SHIP-2 or in TREND-0. Even when pooling both samples (adjusting for study participation), no significant associations between PRS, TBV, WM, GM, or local GM volumes in voxel-based morphometry analyses emerged. Our findings suggest that there is no overall effect of PRS for schizophrenia on brain volume measures (TBV, WM, GM) in the general population. We were able to replicate the lack of any effect in two independent samples with sufficient size to reveal a putative association (80% power to detect R2 change of .1.1% in the smaller sample) and confirmed the negative findings reported by Papiol et al. (3). Compared with the study by Terwisscha van Scheltinga et al. (2), in which a variance explained of .4.8% was reported between PRS and brain volumes, we would have been able to detect the effect. Compared with the two previous studies, our approach had the following advantages: 1) We used the genetic data from a

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Correspondence

Table 1. Association Between Polygenic Risk Scores and Brain Volume Measures in SHIP-2 and TREND-0 Total Brain Volume p Value Cutoff

p Value

β

White Matter p Value

β

Gray Matter p Value

β

SHIP-2 10E-5

.737

.32

.934

.08

.820

10E-4

.528

.58

.919

2.09

.512

.24 .67

.001

.898

2.12

.941

.07

.859

2.18

.01

.862

2.16

.974

2.03

.897

2.13

.05

.965

.04

.733

2.32

.713

.37

.1

.904

.11

.552

2.56

.489

.68

10E-5

.597

2.45

.220

21.14

.485

.69

10E-4

.921

.09

.376

2.85

.339

.94

.001

.517

2.57

.528

2.62

.963

.04

.01

.872

2.14

.527

2.62

.605

.48

.05

.655

2.40

.284

21.03

.495

.63

.1

.593

2.48

.193

21.23

.406

.76

SHIP-TREND-0

Individualized Medicine (GANI_MED) was funded by the Federal Ministry of Education and Research Grant No. 03IS2061A and the German Research Foundation Grant No. GR 1912/5-1. HJG has received funding by the German Research Foundation, the German Federal Ministry of Education and Research, the DAMP Foundation, and speakers honoraria from Servier and Eli Lilly and Company. The other authors report no biomedical financial interests or potential conflicts of interest.

Article Information From the Department of Psychiatry and Psychotherapy (SVdA, HJG), University Medicine Greifswald; German Center for Neurodegenerative Diseases (SVdA, KW, HJG), Site Rostock/Greifswald; Interfaculty Institute for Genetics and Functional Genomics (GH), University of Greifswald; Institute for Community Medicine (AT); Institute of Diagnostic Radiology and Neuroradiology (KH), University Medicine Greifswald, Greifswald; and Department of Psychiatry and Psychotherapy (HJG), University Medicine Greifswald, HELIOS Hospital Stralsund, Stralsund, Germany. Address correspondence to Sandra Van der Auwera, Ms, Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Ellernholzstraße 1-2, 17489 Greifswald, Germany; E-mail: [email protected].

SHIP, Study of Health in Pomerania.

References recent GWAS with nearly four times more cases and 108 independent genome-wide significantly associated genetic loci; 2) we corrected for nonlinear effects of age on brain volume and excluded participants .65 years old, minimizing the impact of age on the analyses; and 3) we used two independent samples each considerably larger than the previous studies. The increase in sample size should prevent against false-positive findings that may occur in smaller subsamples (12). In conclusion, genetic risk variants for schizophrenia summarized within PRS did not show any overall effect on brain structure. Further region-specific and pathway-specific analyses should be performed to identify any structural effects of genetic risk for schizophrenia in the general population. Sandra Van der Auwera Katharina Wittfeld Georg Homuth Alexander Teumer Katrin Hegenscheid Hans Jörgen Grabe

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Acknowledgments and Disclosures This work was supported by the German Federal Ministry of Education and Research within the framework of the e:Med research and funding concept (Integrament) Grant No. 01ZX1314E. Study of Health in Pomerania is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research Grant Nos. 01ZZ9603, 01ZZ0103, and 01ZZ0403; the Ministry of Cultural Affairs; and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide data were supported by the Federal Ministry of Education and Research Grant No. 03ZIK012 and a joint grant from Siemens Healthcare, Erlangen, Germany, and the Federal State of Mecklenburg-West Pomerania. The Greifswald Approach to

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