Lack of association of the rs1344706 ZNF804A variant with cognitive functions and DTI indices of white matter microstructure in two independent healthy populations

Genetic impact of ZNF804A on cognitive function in patients with bipolar I disorder

Our previous genetic study identified a variant rs1344706 in the zinc finger protein 804A (ZNF804A) gene conferring susceptibility to bipolar disorder subtype I (BD-I) in Han Chinese. Literature documented that this variant may affect brain structure and function. As such, we attempted to identify whether the rs1344706 polymorphism influences cognitive function in patients with bipolar disorder I. We recruited 177 patients with bipolar disorder in remission period. Cognitive function was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). The single nucleotide polymorphisms (SNP) rs1344706 was genotyped using TaqMan assays. Analysis of covariance (ANCOVA) analysis showed a significant genotypic effect on RBANS immediate memory (P = 0.002) and total score (P = 0.001). Post hoc analysis showed that the patients with T/T genotype have lower RBANS immediate memory and total scores than those with T/G or G/G genotypes. When the patients were stratified by sex, such significances are only seen in male patients, but not female patients. Our findings suggested a sex-specific effect of ZNF804A rs1344706 polymorphism on cognitive function in patients with bipolar disorder-I.

[Results and promises of genetics of cognitive impairment in schizophrenia: molecular-genetic approaches]

This review highlights the basic paradigms and directions of molecular genetic studies of cognitive deficits in schizophrenia. Along with the traditional approach based on functional candidate genes, it covers genome-wide association studies (GWAS) for cognition in general population and schizophrenic patients, attempts to integrate GWAS results in polygenic profiles that can be used in personalized care of schizophrenic patients, and a search for biological pathways implicated in the development of cognitive impairments with bioinformatics methods. However, despite significant advances in understanding the genetic basis of the disease and a rapidly growing amount of data on genes associated with cognitive functions, most of the variability of cognitive impairments in patients remains unexplained. The data on the functional complexity of the genome accumulated in the fields of molecular biology and genetics underscore the importance of studying epigenetic mechanisms of cognitive deficits in schizophrenia.

Imaging genetics of schizophrenia in the post-GWAS era

Imaging genetics is a research methodology studying the effect of genetic variation on brain structure, function, behavior, and risk for psychopathology. Since the early 2000s, imaging genetics has been increasingly used in the research of schizophrenia (SZ). SZ is a severe mental disorder with no precise knowledge of its underlying neurobiology, however, new genetic and neurobiological data generate a climate for new avenues. The accumulating data of genome wide association studies (GWAS) continuously decode SZ risk genes. Global neuroimaging consortia produce collections of brain phenotypes from tens of thousands of people. In this context, imaging genetics will be strategically important both for the validation and discovery of SZ related findings. Thus, the study of GWAS supported risk variants as candidate genes to validate by neuroimaging is one trend. The study of epigenetic differences in relation to variations of brain phenotypes and the study of large scale multivariate analysis of genome wide and brain wide associations are other trends. While these studies hold a big potential for understanding the neurobiology of SZ, the problem of reproducibility appears as a major challenge, which requires standardizations in study designs and compensations of methodological limitations such as sensitivity and specificity. On the other hand, advancements of neuroimaging, optical and electron microscopy along with the use of genetically encoded fluorescent probes and robust statistical approaches will not only catalyze integrative methodologies but also will help better design the imaging genetics studies. In this invited paper, I will discuss the current perspective of imaging genetics and emerging opportunities of SZ research.

Genome-wide discovered psychosis-risk gene ZNF804A impacts on white matter microstructure in health, schizophrenia and bipolar disorder

Background. Schizophrenia (SZ) and bipolar disorder (BD) have both been associated with reduced microstructural white matter integrity using, as a proxy, fractional anisotropy (FA) detected using diffusion tensor imaging (DTI). Genetic susceptibility for both illnesses has also been positively correlated in recent genome-wide association studies with allele A (adenine) of single nucleotide polymorphism (SNP) rs1344706 of the ZNF804A gene. However, little is known about how the genomic linkage disequilibrium region tagged by this SNP impacts on the brain to increase risk for psychosis. This study aimed to assess the impact of this risk variant on FA in patients with SZ, in those with BD and in healthy controls. Methods. 230 individuals were genotyped for the rs1344706 SNP and underwent DTI. We used tract-based spatial statistics (TBSS) followed by an analysis of variance, with threshold-free cluster enhancement (TFCE), to assess underlying effects of genotype, diagnosis and their interaction, on FA. Results. As predicted, statistically significant reductions in FA across a widely distributed brain network (p < 0.05, TFCE-corrected) were positively associated both with a diagnosis of SZ or BD and with the double (homozygous) presence of the ZNF804A rs1344706 risk variant (A). The main effect of genotype was medium (d = 0.48 in a 44,054-voxel cluster) and the effect in the SZ group alone was large (d = 1.01 in a 51,260-voxel cluster), with no significant effects in BD or controls, in isolation. No areas under a significant diagnosis by genotype interaction were found. Discussion. We provide the first evidence in a predominantly Caucasian clinical sample, of an association between ZNF804A rs1344706 A-homozygosity and reduced FA, both irrespective of diagnosis and particularly in SZ (in overlapping brain areas). This suggests that the previously observed involvement of this genomic region in psychosis susceptibility, and in impaired functional connectivity, may be conferred through it inducing abnormalities in white matter microstructure.

Genetics of structural connectivity and information processing in the brain

Understanding the genetic factors underlying brain structural connectivity is a major challenge in imaging genetics. Here, we present results from genome-wide association studies (GWASs) of whole-brain white matter (WM) fractional anisotropy (FA), an index of microstructural coherence measured using diffusion tensor imaging. Data from independent GWASs of 355 Swedish and 250 Norwegian healthy adults were integrated by meta-analysis to enhance power. Complementary GWASs on behavioral data reflecting processing speed, which is related to microstructural properties of WM pathways, were performed and integrated with WM FA results via multimodal analysis to identify shared genetic associations. One locus on chromosome 17 (rs145994492) showed genome-wide significant association with WM FA (meta P value = 1.87 × 10^-08). Suggestive associations (Meta P value <1 × 10^-06) were observed for 12 loci, including one containing ZFPM2 (lowest meta P value = 7.44 × 10^-08). This locus was also implicated in multimodal analysis of WM FA and processing speed (lowest Fisher P value = 8.56 × 10^-07). ZFPM2 is relevant in specification of corticothalamic neurons during brain development. Analysis of SNPs associated with processing speed revealed association with a locus that included SSPO (lowest meta P value = 4.37 × 10^-08), which has been linked to commissural axon growth. An intergenic SNP (rs183854424) 14 kb downstream of CSMD1, which is implicated in schizophrenia, showed suggestive evidence of association in the WM FA meta-analysis (meta P value = 1.43 × 10^-07) and the multimodal analysis (Fisher P value = 1 × 10^-07). These findings provide novel data on the genetics of WM pathways and processing speed, and highlight a role of ZFPM2 and CSMD1 in information processing in the brain.