The presence of genetic influences on general intelligence or g is well established and the various studies converge on a heritability estimate between 0.60 and 0.80.1,2 Genetic factors accounted for most of the individual differences in whole brain (90%) and white matter (88%) volumes.3 In 14 studies of about 700 individuals, correlations between brain volume and g are about 0.40,4,5 indicating that individuals with larger brain volumes have higher g scores. Furthermore, g is related to the volume of white matter.6 Interestingly, the correlation between white matter volume and g seems to be due to genetic factors.6 Establishing that the correlation between brain volumes and cognitive abilities is mediated by shared genetic factors is only the first step in unveiling the relation between them. The next step is to identify specific genes that influence both, brain volume and cognitive abilities. Based on a candidate gene approach, we have recently shown that methionine homozygosity at codon 129 in the prion protein is associated with white matter reduction and enlargement of CSF compartments in a group of healthy volunteers and schizophrenic patients.7
The prion protein (PrP), a copper-binding sialoglycoprotein, is expressed in the central nervous system, particularly in the neurons, and to a lesser extent in extraneuronal tissues.8 In neurons, it appears to have a predominantly presynaptic localization.9 This is congruent with data suggesting that prion protein knockout mice have deficiencies in long-term potentiation.10 Although the exact function of prion protein is not fully understood, several lines of evidence strongly suggest that it is involved in the removal of reactive oxygen species in neurons, leading to neuroprotection. It has been shown that the prion protein might influence the uptake of copper into neurons where it can be utilized for synaptic release11 or incorporation into enzymes such as Cu/Zn superoxide dismutase.12 Alternatively, it might act itself as a superoxide dismutase.13 Furthermore, the prion protein is strongly upregulated during cell fate restriction towards the neural lineage14 suggesting a role in neurodevelopment. Disruption of the prion protein gene (PRNP) results in an aberrant regulation of genes important for cell proliferation, differentiation and survival, as recently demonstrated using DNA arrays.15 A common polymorphism at codon 129 in the PRNP gene causes the translation of either methionine or valine on a short 
-sheet region in the C–terminal domain of the protein.
Based on the findings suggesting that the correlation between brain volumes and cognitive abilities is mediated by common genetic factors, and our finding that a genetic variation in the prion protein is associated with variations in white matter volumes, we investigated the relation between the M129V polymorphism in the PRNP gene and variations in cognitive abilities in 335 community-based healthy volunteers.
The genotype distribution was in Hardy–Weinberg equilibrium (
2=0.03, df=2, P=0.985). Sample char-acteristics of the genotype subgroups are given in Table 1. Between these subgroups there were no differences in gender (2=0.992, df=2, P=0.609), age (F=1.446, df=2/332, P=0.237), educational level (2=1.343, df=4, P=0.854), marital (2=1.238, df=4, P=0.872) and professional status (2=3.540, df=4, P=0.472).
Table 1 - Sociodemographic comparisons between the genotype groups defined by the M129 V polymorphism in the PRNP gene.
![Table 1 - Sociodemographic comparisons between the genotype groups defined by the M129[thinsp]V polymorphism in the PRNP gene - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author](/common/images/table_thumb.gif)
Full table First, two separate ANOVAs were computed for Full Scale IQ (which is age-corrected) by integrating the factors: genotype (M/M, M/V, V/V) or allele (M, V) and gender (male, female) controlled for educational level. Genotype had a main effect (F=4.38, df=2/317, P=0.013) and accounted for 2.7% of the total variability in Full Scale IQ (partial 
2=0.027). The relation between genotype and Full Scale IQ is illustrated in Figure 1. Furthermore, an interaction effect was seen between genotype and educational level; the association was stronger in the less educated individuals (F=2.65, df=4/317, P=0.034). Similarly, when looking at allele distribution, allele had a main effect (F=8.04, df=1/658, P=0.005). Two exploratory multivariate analyses of variance (MANOVAs) were conducted to determine whether the effect is driven by specific HAWIE-R (German version of the Wechsler Adult Intelligence Scale, Revised) subscales by integrating the factors: genotype (M/M, M/V, V/V) or allele (M, V) and gender (male, female) controlled for age and educational level. These analyses revealed association with several HAWIE-R subscales (Table 2); the association with the Digit Symbol subtest remained significant after correction for multiple testing (genotype: F=7.61, df=2/316, P=0.0006; allele: F=15.54, df=1/657, P=0.00009, Figure 2). Genotype accounted for 4.6% of the total variability in the Digit Symbol subtest (partial 2=0.046). Nevertheless, the association is not significantly stronger than that for other subtests.
Figure 1.
HAWIE-R Full Scale IQ (mean
95% confidence interval) as a function of M129V prion protein genotype.
Figure 2.
HAWIE-R Digit Symbol subtest (mean95% confidence interval) as a function of M129V prion protein genotype.
The main results of the present study are that a common variation in the prion protein gene is associated with Full Scale IQ and with performance in the Digit Symbol subtest of HAWIE-R in a community-based sample of German healthy volunteers. These findings are further strengthened by the observation that the effect occurs in a gene dose-dependent manner. A somehow unexpected finding is that the PrP–IQ association is strongest in the less educated individuals, while quantitative genetic research points towards the opposite direction showing that genetic influence on IQ is higher among higher educated families.16
Genotype groups did not differ with regard to sociodemographic variables. Furthermore, to minimize ethnic stratification, we included only healthy volunteers of German origin. Nevertheless, these potentially highly important findings warrant further replication prior to generalization, in order to exclude spurious associations, due to, for example, sampling errors.
The functional relevance of the genetic variation under study is not understood. Although the copper–binding ability and the level of superoxide dismutase activity do not seem to be altered, copper-binding results in different allele-dependent conformations and thus structures.17 This finding strongly suggests that this polymorphism probably alters, yet unidentified, properties of the protein. Alternatively, another genetic variation in the PRNP gene, or in a gene located in close proximity, which is in linkage disequilibrium with the M129V polymorphism could be responsible for this association. Thus, the mechanisms by which the M129V variation or, alternatively, linked genetic variations might actually act on cognitive performance can only be speculated about and require further investigation. To our knowledge, this is the first study that examines the relation between a variation in the PRNP gene and cognitive abilities and one of the very first reports on the influence of a common genetic polymorphism on individual differences of cognitive abilities in healthy individuals.
Methods
Community-based healthy volunteers and assessment
Unrelated healthy volunteers of German descent (ie both their parents were German) were randomly selected from the general population of Munich, Germany, and contacted by mail. In order to exclude subjects with neuropsychiatric disorders or subjects who had first-degree relatives with neuropsychiatric disorders, we conducted several screenings before the volunteers were enrolled in the study. First, subjects who responded were initially screened by phone. Their detailed medical and psychiatric histories and those of their first-degree relatives were assessed. Second, they were invited to a comprehensive interview including the German version of the Structured Clinical Interview for DSM-IV, SKID I and SKID II18,19 to evaluate their lifetime Axis I and II disorders. Psychiatric diagnoses among their first-degree relatives were also assessed using the Family History Assessment Module.20 Subjects with relevant somatic diseases or a lifetime history of any Axis I or II psychiatric disorder were excluded. Subjects who had first-degree relatives with a lifetime history of a mental disorder were also excluded. Finally, 335 healthy subjects (149 males and 186 females) were included. Their mean age was 44.614.0 (range: 19–65) years.
HAWIE-R was administered and scored according to the standardized procedures outlined in the manual.21 It allows to calculate Full Scale IQ, and has the possibility to calculate Verbal IQ (consisting of the subtests Information, Digit Span, Vocabulary, Arithmetic, Comprehension, Similarities) and Performance IQ (consisting of the subtests Picture Completion, Picture Arrangement, Block Design, Matrix Reasoning, Digit Symbol-Coding).
Genotyping
Genomic DNA was prepared from 10 ml blood using the QIAamp DNA Blood Maxi Kit (Qiagen, Hilden, Germany) following the suppliers' instructions. A 339 bp region containing the biallelic codon 129 polymorphism was amplified by PCR. The forward primer was 5'-AAC GTC GGT CTC GGT GAA GT-3' and the reverse primer was 5'-TCA AGG AGG TGG CAC CCA CA-3'. The PCR reaction was performed in a final volume of 50 
l using 50 ng genomic DNA, 15 pmol of each primer, 1 U Taq polymerase, 400 M dNTP, 2 mM MgCl2, 60 mM Tris-HCl and 15 mM ammonium sulfate at pH 9.5. An initial denaturation step at 94°C for 2 min was followed by 40 cycles (1 min at 94°C, 1 min at 60°C, 1 min at 72°C) and then by a final extension at 72°C for 6 min. The products were digested with 5 U of Bsa AI at 37°C for 10 h, analyzed by electrophoresis on a 1.5% agarose gel containing ethidium bromide, and visualized under UV light. Digestion resulted in two fragments of 226 and 113 bp, whereas the absence of the Bsa AI recognition site left the 339 bp PCR product intact.
Statistical analysis
Statistics were performed using the SPSS 11.0. Software (Statistical Package for Social Sciences, SPSS Inc., Chicago, 2001). t-Tests or 2-tests were performed, as appropriate for the measurement, to test for differences concerning sociodemographic variables between the genotype subgroups. The presence of Hardy–Weinberg equilibrium was tested by the 2-test. First, two separate ANOVAs were computed for Full Scale IQ by integrating the factors: genotype (M/M, M/V, V/V) or allele (M, V) and gender (male, female) controlled for educational level (low, middle, high). Full Scale IQ, in contrast to the subscales, is age-corrected and thus, age was not included. Next, two exploratory two-factor MANOVAs were computed integrating the 11 subscales of the HAWIE-R (Information, Digit Span, Vocabulary, Arithmetic, Comprehension, Similarities, Picture Completion, Picture Arrangement, Block design, Object assembly, Digit symbol), as well as the factors: genotype (M/M, M/V, V/V) or allele (M, V) and gender (male, female) controlled for age and educational level (low, middle, high). Analyses used two-tailed estimation of significance, an 
-significance level of P<0.05 was defined to be statistically significant. Bonferroni corrections were performed when appropriate.
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Acknowledgements
We thank Stephany Fulda for helpful discussions. Parts of this work are taken from the MD thesis of Tanja Schulz.
