Imaging the genetics of brain structure and function

Multimodal covarying brain patterns mediate genetic and psychological contributions to individual differences in pain sensitivity

ABSTRACT

Individuals vary significantly in their pain sensitivity, with contributions from the brain, genes, and psychological factors. However, a multidimensional model integrating these factors is lacking due to their complex interactions. To address this, we measured pain sensitivity (ie, pain threshold and pain tolerance) using the cold pressor test, collected magnetic resonance imaging (MRI) data and genetic data, and evaluated psychological factors (ie, pain catastrophizing, pain-related fear, and pain-related anxiety) from 450 healthy participants with both sexes (160 male, 290 female). Using multimodal MRI fusion methods, we identified 2 pairs of covarying structural and functional brain patterns associated with pain threshold and tolerance, respectively. These patterns primarily involved regions related to self-awareness, sensory-discriminative, cognitive-evaluative, motion preparation and execution, and emotional aspects of pain. Notably, pain catastrophizing was negatively correlated with pain tolerance, and this relationship was mediated by the multimodal covarying brain patterns in male participants only. Furthermore, we identified an association between the single-nucleotide polymorphism rs4141964 within the fatty acid amide hydrolase gene and pain threshold, mediated by the identified multimodal covarying brain patterns across all participants. In summary, we suggested a model that integrates the brain, genes, and psychological factors to elucidate their role in shaping interindividual variations in pain sensitivity, highlighting the important contribution of the multimodal covarying brain patterns as important biological mediators in the associations between genes/psychological factors and pain sensitivity.

Apolipoprotein E Gene Revisited: Contribution of Rare Variants to Alzheimer's Disease Susceptibility in Southern Chinese

BACKGROUND

APOE ε4 is the best-known risk factor for late-onset alzheimer's disease (AD). Population studies have demonstrated a relatively low prevalence of APOE ε4 among Chinese population, implying additional risk factors that are Chinese-specific may exist. Apart from - alleles, genetic variation profile along the full-length APOE has rarely been investigated.

OBJECTIVE

In this study, we filled this gap by comprehensively determining all genetic variations in APOE and investigated their potential associations with late-onset AD and mild cognitive impairment (MCI) in southern Chinese.

METHODS

Two hundred and fifty-seven southern Chinese participants were recruited, of whom 69 were AD patients, 83 had MCI, and 105 were normal controls. Full-length APOE from promoter to 3'UTR regions were sequenced. Genetic variants were identified and compared among the three groups.

RESULTS

While APOE ε4 was more significantly found in AD patients, the prevalence of APOE ε4 in southern Chinese AD patients was the lowest when compared to other areas of China and nearby regions, as well as other countries worldwide. We further identified 13 rare non-singleton variants in APOE. Significantly more AD patients carried any of the rare non-singleton variants than MCI and normal subjects. Such difference was observed in the non-carriers of ε4-allele only. Among the identified rare variants, the potential functional impact was predicted for rs532314089, rs553874843, rs533904656 and rs370594287.

CONCLUSION

Our study suggests an ethnic difference in genetic risk composition of AD in southern Chinese. Rare variants on APOE are a potential candidate for AD risk stratification biomarker in addition to APOE-ε4.

CACNA1C Risk Variant and Mood Stabilizers Effects in the Prefrontal Cortical Thickness of Mexican Patients with Bipolar Disorder

PURPOSE

Bipolar disorder (BD) is a condition associated with structural alterations in the prefrontal cortex (PFC); some genetic variants and mood stabilizer medications like lithium or valproate are associated with these changes. CACNA1C is a gene involved in BD pathology and brain function; carriers of the A allele of rs1006737 are reported to have increased risk for BD and increased cortical thickness (CT) in the PFC compared to non-carriers. Lithium is also associated with increased CT in the PFC of BD subjects compared to the ones on valproate. The influence of these treatments and gene variants over the PFC structure of Mexican subjects has not been explored. Therefore, we evaluate the effects of mood stabilizers and risk A allele of CACNA1C rs1006737 on the prefrontal cortical thickness of Mexican BD patients treated with lithium or valproate.

PATIENTS AND METHODS

A cross-sectional study of 40 BD type I euthymic adult outpatients (20 treated with lithium and 20 with valproate) who underwent a 3T T1-weighted 3D brain scan and genotyping for CACNA1C risk allele rs1006737 was conducted. We performed a cortical thickness analysis of the dorsolateral and orbitofrontal regions of the prefrontal cortex with BrainVoyager 20.6. The effects of treatment and gene variants were analyzed with a two-way multivariate analysis of covariance.

RESULTS

There was no association of CACNA1C risk allele rs1006737 with CT measures of both PFCs nor significant interaction between the genetic variant and treatment. Mood stabilizers reported the main effect on the CT measures of the right PFC of our sample. Patients on treatment with lithium showed higher mean CT on the right orbitofrontal cortex.

CONCLUSION

We did not find any association between the prefrontal CT and CACNA1C risk A allele rs1006737 in BD Mexican patients treated with lithium or valproate. Our results suggest that mood stabilizers had the main effect in the CT of the right PFC.

A Set-Based Mixed Effect Model for Gene-Environment Interaction and Its Application to Neuroimaging Phenotypes

Imaging genetics is an emerging field for the investigation of neuro-mechanisms linked to genetic variation. Although imaging genetics has recently shown great promise in understanding biological mechanisms for brain development and psychiatric disorders, studying the link between genetic variants and neuroimaging phenotypes remains statistically challenging due to the high-dimensionality of both genetic and neuroimaging data. This becomes even more challenging when studying gene-environment interaction (G×E) on neuroimaging phenotypes. In this study, we proposed a set-based mixed effect model for gene-environment interaction (MixGE) on neuroimaging phenotypes, such as structural volumes and tensor-based morphometry (TBM). MixGE incorporates both fixed and random effects of G×E to investigate homogeneous and heterogeneous contributions of multiple genetic variants and their interaction with environmental risks to phenotypes. We discuss the construction of score statistics for the terms associated with fixed and random effects of G×E to avoid direct parameter estimation in the MixGE model, which would greatly increase computational cost. We also describe how the score statistics can be combined into a single significance value to increase statistical power. We evaluated MixGE using simulated and real Alzheimer's Disease Neuroimaging Initiative (ADNI) data, and showed statistical power superior to other burden and variance component methods. We then demonstrated the use of MixGE for exploring the voxelwise effect of G×E on TBM, made feasible by the computational efficiency of MixGE. Through this, we discovered a potential interaction effect of gene ABCA7 and cardiovascular risk on local volume change of the right superior parietal cortex, which warrants further investigation.

Neuregulin-1 mutant mice indicate motor and sensory deficits, indeed few references for schizophrenia endophenotype model

Neuregulins (Nrg) are a gene family that binds to tyrosine kinase receptors of the ErbB family. The protein of Nrg1 is to be involved in heart formation, migration of neurons, axonal pathfinding and synaptic function. A relation between Nrg1 and schizophrenia is assumed. Chronic impairment in schizophrenia is characterized by different positive and negative symptoms. Detectable markers of this disease in human and in animal models are activity, social behavior and sensory processing. In this study we compared heterozygous Nrg1 mutant mice in behavior and quantification of dopaminergic and serotoninergic neurons with wild type-like littermates. In the Nrg1 mutant mice the epidermal growth factor-like domain is replaced by the neomycin resistance gene. We found significant differences in locomotor and pain perception behavior. No differences were found in specific schizophrenia social interaction and prepulse inhibition behavior. The number of dopaminergic and serotoninergic neurons did not differ in the investigated regions ventral tegmental area, substantia nigra, periaqueductal grey and raphe nuclei. In conclusion, this analyzed Nrg1 mutant mice model did not serve as a complete schizophrenia model. Particular aspects of schizophrenia disease in locomotor and sensory behavior deficits could represent in this Nrg1 mutant mice. Beside several different models could Nrg1 deficiency represent an endophenotype of schizophrenia disease.

Preliminary findings on the heritability of the neural correlates of response inhibition

Imaging genetics examines genetic influences on brain structure and function. This preliminary study tested a fundamental assumption of that approach by estimating the heritability of the blood oxygen level dependent (BOLD) signal during antisaccades, a measure of response inhibition impaired in different psychiatric conditions. One hundred thirty-two healthy same-sex reared-together twins (90 monozygotic (MZ; 32 male) and 42 dizygotic (DZ; 24 male)) performed antisaccades in the laboratory. Of these, 96 twins (60 MZ, 28 male; 36 DZ, 22 male) subsequently underwent functional magnetic resonance imaging (fMRI) during antisaccades. Variation in antisaccade direction errors in the laboratory showed significant heritability (47%; 95% confidence interval (CI) 22-65). In fMRI, the contrast of antisaccades with prosaccades yielded BOLD signal in fronto-parietal-subcortical networks. Twin modelling provided tentative evidence of significant heritability (50%, 95% CI: 18-72) of BOLD in the left thalamus only. However, due to the limited power to detect heritability in this study, replications in larger samples are needed.

Involvement of the BDNF gene in loneliness in adolescence: a report of opposite gene effects in boys and girls

Previous research has shown that loneliness has a heritable component and that genes within the serotonin-, dopamine-, and oxytocin systems are related to loneliness in adolescence. In the present study, the relation between the BDNF Val66Met polymorphism and loneliness in adolescent boys and girls was examined in a longitudinal study spanning five annual waves (N = 305). Latent growth curve modeling (LGCM) was used to examine the baseline level and the change in loneliness over time. The main finding was that the BDNF gene was not related to loneliness in the total sample. A BDNF by sex interaction was found, in that Met carrying girls had the highest levels of loneliness at baseline, whereas in boys the ValVal genotype was related to higher levels of loneliness. Our results underline the importance of sex-stratified analyses when examining effects of the BDNF genotype and the necessity of conducting gene studies to intermediate phenotypes of loneliness.

BDNF Val66Met polymorphism alters spinal DC stimulation-induced plasticity in humans

The brain-derived neurotrophic factor gene (BDNF) is one of many genes thought to influence neuronal survival, synaptic plasticity, and neurogenesis. A common single nucleotide polymorphism (SNP) of the BDNF gene due to valine-to-methionine substitution at codon 66 (BDNF Val66Met) in the normal population has been associated with complex neuronal phenotype, including differences in brain morphology, episodic memory, or cortical plasticity following brain stimulation and is believed to influence synaptic changes following motor learning task. However, the effect of this polymorphism on spinal plasticity remains largely unknown. Here, we used anodal transcutaneous spinal direct current stimulation (tsDCS), a novel noninvasive technique that induces plasticity of spinal neuronal circuits in healthy subjects. To investigate whether the susceptibility of tsDCS probes of spinal plasticity is significantly influenced by BDNF polymorphism, we collected stimulus-response curves of the soleus (Sol) H reflex before, during, at current offset, and 15 min after anodal tsDCS delivered at Th11 (2.5 mA, 15 min, 0.071 mA/cm2, and 64 mC/cm2) in 17 healthy, Met allele carriers and 17 Val homozygotes who were matched for age and sex. Anodal tsDCS induced a progressive leftward shift of recruitment curve of the H reflex during the stimulation that persisted for at least 15 min after current offset in Val/Val individuals. In contrast, this shift was not observed in Met allele carriers. Our findings demonstrate for the first time that the BDNF Val66Met genotype impacts spinal plasticity in humans, as assessed by tsDCS, and may be one factor influencing the natural response of the spinal cord to injury or disease.

Decreased medial temporal lobe activation in BDNF (66)Met allele carriers during memory encoding

The Met allele of the Brain-derived neurotrophic factor (BDNF) Val(66)Met polymorphism has been associated with impaired activity-dependent secretion of BDNF protein and decreased memory performance. Results from imaging studies relating Val(66)Met to brain activation during memory processing have been inconsistent, with reports of both increased and decreased activation in the Medial Temporal Lobe (MTL) in Met carriers relative to Val homozygotes. Here, we extensively studied BDNF Val(66)Met in relation to brain activation and white matter integrity as well as memory performance in a large imaging (n=194) and behavioral (n=2229) sample, respectively. Functional magnetic resonance imaging (fMRI) was used to investigate MTL activation in healthy participants in the age of 55-75 years during a face-name episodic encoding and retrieval task. White matter integrity was measured using diffusion tensor imaging. BDNF Met allele carriers had significantly decreased activation in the MTL during encoding processes, but not during retrieval processes. In contrast to previous proposals, the effect was not modulated by age and the polymorphism was not related to white matter integrity. Met carriers had lower memory performance than Val homozygotes, but differences were subtle and not significant. In conclusion, the BDNF Met allele has a negative influence on MTL functioning, preferentially during encoding processes, which might translate into impaired episodic memory function.

The role of the catechol-O-methyltransferase (COMT) gene in personality and related psychopathological disorders

This review provides a short overview of the most significant biologically oriented theories of human personality. Personality concepts of Eysenck, Gray and McNaughton, Cloninger and Panksepp will be introduced and the focal evidence for the heritability of personality will be summarized. In this context, a synopsis of a large number of COMT genetic association studies (with a focus on the COMT Val158Met polymorphism) in the framework of the introduced biologically oriented personality theories will be given. In line with the theory of a continuum model between healthy anxious behavior and related psychopathological behavior, the role of the COMT gene in anxiety disorders will be discussed. A final outlook considers new research strategies such as genetic imaging and epigenetics for a better understanding of human personality.

Neuroimaging and genetics: exploring, searching, and finding

This issue on the genetics of brain imaging phenotypes is a celebration of the happy marriage between two of science's highly interesting fields: neuroscience and genetics. The articles collected here are ample evidence that a good deal of synergy exists in this marriage. A wide selection of papers is presented that provide many different perspectives on how genes cause variation in brain structure and function, which in turn influence behavioral phenotypes (including psychopathology). They are examples of the many different methodologies in contemporary genetics and neuroscience research. Genetic methodology includes genome-wide association (GWA), candidate-gene association, and twin studies. Sources of data on brain phenotypes include cortical gray matter (GM) structural/volumetric measures from magnetic resonance imaging (MRI); white matter (WM) measures from diffusion tensor imaging (DTI), such as fractional anisotropy; functional- (activity-) based measures from electroencephalography (EEG), and functional MRI (fMRI). Together, they reflect a combination of scientific fields that have seen great technological advances, whether it is the single-nucleotide polymorphism (SNP) array in genetics, the increasingly high-resolution MRI imaging, or high angular resolution diffusion imaging technique for measuring WM connective properties.

Predicting white matter integrity from multiple common genetic variants

Several common genetic variants have recently been discovered that appear to influence white matter microstructure, as measured by diffusion tensor imaging (DTI). Each genetic variant explains only a small proportion of the variance in brain microstructure, so we set out to explore their combined effect on the white matter integrity of the corpus callosum. We measured six common candidate single-nucleotide polymorphisms (SNPs) in the COMT, NTRK1, BDNF, ErbB4, CLU, and HFE genes, and investigated their individual and aggregate effects on white matter structure in 395 healthy adult twins and siblings (age: 20-30 years). All subjects were scanned with 4-tesla 94-direction high angular resolution diffusion imaging. When combined using mixed-effects linear regression, a joint model based on five of the candidate SNPs (COMT, NTRK1, ErbB4, CLU, and HFE) explained ≈ 6% of the variance in the average fractional anisotropy (FA) of the corpus callosum. This predictive model had detectable effects on FA at 82% of the corpus callosum voxels, including the genu, body, and splenium. Predicting the brain's fiber microstructure from genotypes may ultimately help in early risk assessment, and eventually, in personalized treatment for neuropsychiatric disorders in which brain integrity and connectivity are affected.

A systematic review of the A118G (Asn40Asp) variant of OPRM1 in relation to smoking initiation, nicotine dependence and smoking cessation

Candidate gene studies on smoking behaviors mainly focused on dopaminergic and serotonergic genes, but genes within the µ-opioid system might also be involved. The A118G variant within the OPRM1 gene has been most often examined in relation to smoking, yielding inconsistent findings. It is largely unknown which of the alleles increases susceptibility for smoking behaviors. The aim of this review was to merge findings of OPRM1 gene studies in relation to smoking behaviors and to elaborate on the underlying biological mechanism of the A118G variant. It appeared that A118 was more likely to increase susceptibility to smoking behaviors than 118G, especially with regard to nicotine dependence, but less with smoking initiation and cessation. The proposed functioning of the OPRM1 gene is further explained.

Genetic and environmental influences on neuroimaging phenotypes: a meta-analytical perspective on twin imaging studies

Because brain structure and function are affected in neurological and psychiatric disorders, it is important to disentangle the sources of variation in these phenotypes. Over the past 15 years, twin studies have found evidence for both genetic and environmental influences on neuroimaging phenotypes, but considerable variation across studies makes it difficult to draw clear conclusions about the relative magnitude of these influences. Here we performed the first meta-analysis of structural MRI data from 48 studies on >1,250 twin pairs, and diffusion tensor imaging data from 10 studies on 444 twin pairs. The proportion of total variance accounted for by genes (A), shared environment (C), and unshared environment (E), was calculated by averaging A, C, and E estimates across studies from independent twin cohorts and weighting by sample size. The results indicated that additive genetic estimates were significantly different from zero for all meta-analyzed phenotypes, with the exception of fractional anisotropy (FA) of the callosal splenium, and cortical thickness (CT) of the uncus, left parahippocampal gyrus, and insula. For many phenotypes there was also a significant influence of C. We now have good estimates of heritability for many regional and lobar CT measures, in addition to the global volumes. Confidence intervals are wide and number of individuals small for many of the other phenotypes. In conclusion, while our meta-analysis shows that imaging measures are strongly influenced by genes, and that novel phenotypes such as CT measures, FA measures, and brain activation measures look especially promising, replication across independent samples and demographic groups is necessary.

Individual differences in cognition, affect, and performance: behavioral, neuroimaging, and molecular genetic approaches

We describe the use of behavioral, neuroimaging, and genetic methods to examine individual differences in cognition and affect, guided by three criteria: (1) relevance to human performance in work and everyday settings; (2) interactions between working memory, decision-making, and affective processing; and (3) examination of individual differences. The results of behavioral, functional MRI (fMRI), event-related potential (ERP), and molecular genetic studies show that analyses at the group level often mask important findings associated with sub-groups of individuals. Dopaminergic/noradrenergic genes influencing prefrontal cortex activity contribute to inter-individual variation in working memory and decision behavior, including performance in complex simulations of military decision-making. The interactive influences of individual differences in anxiety, sensation seeking, and boredom susceptibility on evaluative decision-making can be systematically described using ERP and fMRI methods. We conclude that a multi-modal neuroergonomic approach to examining brain function (using both neuroimaging and molecular genetics) can be usefully applied to understanding individual differences in cognition and affect and has implications for human performance at work.

Genetic influence demonstrated for MEG-recorded somatosensory evoked responses

We tested for a genetic influence on magnetoencephalogram (MEG)-recorded somatosensory evoked fields (SEFs) in 20 monozygotic (MZ) and 14 dizygotic (DZ) twin pairs. Previous electroencephalogram (EEG) studies that demonstrated a genetic contribution to evoked responses generally focused on characteristics of representative brain potentials. Here we demonstrate significantly smaller amplitude differences within MZ compared to DZ twin pairs for the complete SEF time series (across left and right hand SEFs: 0.37 vs. 0.60 pT(2) and 0.28 vs. 0.39 pT(2) for primary [SI] and secondary [SII] sensory cortex activation) and higher MZ than DZ wave shape correlations (.71 vs. .44 and .52 vs. .35 for SI and SII activation). Our findings indicate a genetic influence on MEG-recorded evoked brain activity and also confirm our recent conclusion (van 't Ent, van Soelen, Stam, De Geus, & Boomsma, 2009) that higher MZ resemblance for EEG amplitudes is not trivially reflecting greater MZ concordance in intervening biological tissues.

Brain-derived neurotrophic factor val66met polymorphism and hippocampal activation during episodic encoding and retrieval tasks

Brain-derived neurotrophic factor (BDNF) is a neurotrophin which has been shown to regulate cell survival and proliferation, as well as synaptic growth and hippocampal long-term potentiation. A naturally occurring single nucleotide polymorphism in the human BDNF gene (val66met) has been associated with altered intercellular trafficking and regulated secretion of BDNF in met compared to val carriers. Additionally, previous studies have found a relationship between the BDNF val66met genotype and functional activity in the hippocampus during episodic and working memory tasks in healthy young adults. Specifically, studies have found that met carriers exhibit both poorer performance and reduced neural activity within the medial temporal lobe (MTL) when performing episodic memory tasks. However, these studies have not been well replicated and have not considered the role of behavioral differences in the interpretation of neural differences. The current study sought to control for cognitive performance in investigating the role of the BDNF val66met genotype on neural activity associated with episodic memory. Across item and relational memory tests, met carriers exhibited increased MTL activation during both encoding and retrieval stages, compared to noncarriers. The results suggest that met carriers are able to recruit MTL activity to support successful memory processes, and reductions in cognitive performance observed in prior studies are not a ubiquitous effect associated with variants of the BDNF val66met genotype.

Brain-derived neurotrophic factor (BDNF) gene polymorphisms shape cortical plasticity in humans

BACKGROUND

The brain-derived neurotrophic factor (BDNF) gene is involved in mechanisms of synaptic plasticity in the adult brain. It has been demonstrated that BDNF also plays a significant role in shaping externally induced human brain plasticity. Plasticity induced in the human motor cortex by intermittent theta-burst stimulation (iTBS) was impaired in individuals expressing the Val66Met polymorphism.

METHODS

To explore whether this polymorphism is also important for other neuroplasticity-inducing tools in humans with modes of action differing from that of iTBS, namely, transcranial direct current (tDCS) and random noise stimulation (tRNS), we retrospectively analyzed the data of 64 subjects studied in our laboratory with regard to BDNF genotype.

RESULTS

Fifteen subjects with the Val66Met allele, 46 subjects with the Val66Val allele, and 3 Met66Met carriers were identified. The response of the Val66Met allele carriers to stimulation differed in two protocols compared with the response of Val66Val individuals. For iTBS (15 subjects, 5 heterozygotes), plasticity could be only induced in the Val66Val allele carriers. However, for facilitatory tDCS (24 subjects, 10 heterozygotes), as well as for inhibitory tDCS, (19 subjects, 8 heterozygotes), carriers of the Val66Met allele displayed enhanced plasticity, whereas for transcranial random noise stimulation (29 subjects, 8 heterozygotes), the difference between groups was not so pronounced.

CONCLUSIONS

BDNF polymorphism has a definite impact on plasticity in humans, which might differ according to the mechanism of plasticity induction. This impact of BDNF on plasticity should be taken into account for future studies, as well as having wider ranging implications for the treatment of neuropsychiatric disorders with transcranial stimulation tools, as it may predetermine their efficacy for the treatment of disease and rehabilitation.

BDNF Val66Met polymorphism influences age differences in microstructure of the Corpus Callosum

Brain-derived neurotrophic factor (BDNF) plays an important role in neuroplasticity and promotes axonal growth, but its secretion, regulated by a BDNF gene, declines with age. The low-activity (met) allele of common polymorphism BDNF val66met is associated with reduced production of BDNF. We examined whether age-related reduction in the integrity of cerebral white matter (WM) depends on the BDNF val66met genotype. Forty-one middle-aged and older adults participated in the study. Regional WM integrity was assessed by fractional anisotropy (FA) computed from manually drawn regions of interest in the genu and splenium of the corpus callosum on diffusion tensor imaging scans. After controlling for effects of sex and hypertension, we found that only the BDNF 66met carriers displayed age-related declines in the splenium FA, whereas no age-related declines were shown by BDNF val homozygotes. No genotype-related differences were observed in the genu of the corpus callosum. This finding is consistent with a view that genetic risk for reduced BDNF affects posterior regions that otherwise are considered relatively insensitive to normal aging. Those individuals with a genetic predisposition for decreased BDNF expression may not be able to fully benefit from BDNF-based plasticity and repair mechanisms.

Mathematical learning disabilities in children with 22q11.2 deletion syndrome: a review

Mathematical learning disabilities (MLD) occur frequently in children with specific genetic disorders, like Turner syndrome, fragile X syndrome and neurofibromatosis. This review focuses on MLD in children with chromosome 22q11.2 deletion syndrome (22q11DS). This syndrome is the most common known microdeletion syndrome with a prevalence of at least 1:4000 to 1:6000 live births. Although the clinical presentation of 22q11DS is quite variable, its major characteristics include velopharyngeal abnormalities, congenital cardiac anomalies, mild facial dysmorphism and learning difficulties. Children with 22q11DS show considerable difficulties in mathematics, despite relatively normal reading performance. While fact retrieval seems to be preserved, impairments in procedural calculation and word problem solving are particularly prominent. Children with 22q11DS also have substantial difficulties in understanding and representing numerical quantities, possibly related to poor visuospatial attention, which all might stem from their underlying abnormalities in the inferior parietal cortex. This review ends with a discussion on how research on genetic disorders might aid our understanding of MLD in general.

Gene discovery through imaging genetics: identification of two novel genes associated with schizophrenia

We have discovered two genes, RSRC1 and ARHGAP18, associated with schizophrenia and in an independent study provided additional support for this association. We have both discovered and verified the association of two genes, RSRC1 and ARHGAP18, with schizophrenia. We combined a genome-wide screening strategy with neuroimaging measures as the quantitative phenotype and identified the single nucleotide polymorphisms (SNPs) related to these genes as consistently associated with the phenotypic variation. To control for the risk of false positives, the empirical P-value for association significance was calculated using permutation testing. The quantitative phenotype was Blood-Oxygen-Level Dependent (BOLD) Contrast activation in the left dorsal lateral prefrontal cortex measured during a working memory task. The differential distribution of SNPs associated with these two genes in cases and controls was then corroborated in a larger, independent sample of patients with schizophrenia (n=82) and healthy controls (n=91), thus suggesting a putative etiological function for both genes in schizophrenia. Up until now these genes have not been linked to any neuropsychiatric illness, although both genes have a function in prenatal brain development. We introduce the use of functional magnetic resonance imaging activation as a quantitative phenotype in conjunction with genome-wide association as a gene discovery tool.

A genome-wide association study of schizophrenia using brain activation as a quantitative phenotype

BACKGROUND

Genome-wide association studies (GWASs) are increasingly used to identify risk genes for complex illnesses including schizophrenia. These studies may require thousands of subjects to obtain sufficient power. We present an alternative strategy with increased statistical power over a case-control study that uses brain imaging as a quantitative trait (QT) in the context of a GWAS in schizophrenia.

METHODS

Sixty-four subjects with chronic schizophrenia and 74 matched controls were recruited from the Functional Biomedical Informatics Research Network (FBIRN) consortium. Subjects were genotyped using the Illumina HumanHap300 BeadArray and were scanned while performing a Sternberg Item Recognition Paradigm in which they learned and then recognized target sets of digits in an functional magnetic resonance imaging protocol. The QT was the mean blood oxygen level-dependent signal in the dorsolateral prefrontal cortex during the probe condition for a memory load of 3 items.

RESULTS

Three genes or chromosomal regions were identified by having 2 single-nucleotide polymorphisms (SNPs) each significant at P < 10(-6) for the interaction between the imaging QT and the diagnosis (ROBO1-ROBO2, TNIK, and CTXN3-SLC12A2). Three other genes had a significant SNP at <10(-6) (POU3F2, TRAF, and GPC1). Together, these 6 genes/regions identified pathways involved in neurodevelopment and response to stress.

CONCLUSION

Combining imaging and genetic data from a GWAS identified genes related to forebrain development and stress response, already implicated in schizophrenic dysfunction, as affecting prefrontal efficiency. Although the identified genes require confirmation in an independent sample, our approach is a screening method over the whole genome to identify novel SNPs related to risk for schizophrenia.

Age-related decline in brain resources modulates genetic effects on cognitive functioning

Individual differences in cognitive performance increase from early to late adulthood, likely reflecting influences of a multitude of factors. We hypothesize that losses in neurochemical and anatomical brain resources in normal aging modulate the effects of common genetic variations on cognitive functioning. Our hypothesis is based on the assumption that the function relating brain resources to cognition is nonlinear, so that genetic differences exert increasingly large effects on cognition as resources recede from high to medium levels in the course of aging. Direct empirical support for this hypothesis comes from a study by Nagel et al. (2008), who reported that the effects of the Catechol-O-Methyltransferase (COMT) gene on cognitive performance are magnified in old age and interacted with the Brain-Derived Neurotrophic Factor (BDNF) gene. We conclude that common genetic polymorphisms contribute to the increasing heterogeneity of cognitive functioning in old age. Extensions of the hypothesis to other polymorphisms are discussed. (150 of 150 words)