Relation between variants in the neurotrophin receptor gene, NTRK3, and white matter integrity in healthy young adults

Integrative analysis to identify shared mechanisms between schizophrenia and bipolar disorder and their comorbidities

Schizophrenia and bipolar disorder are characterized by highly similar neuropsychological signatures, implying shared neurobiological mechanisms between these two disorders. These disorders also have comorbidities, such as type 2 diabetes mellitus (T2DM). To date, an understanding of the mechanisms that mediate the link between these two disorders remains incomplete. In this work, we identify and investigate shared patterns across multiple schizophrenia, bipolar disorder and T2DM gene expression datasets through multiple strategies. Firstly, we investigate dysregulation patterns at the gene-level and compare our findings against disease-specific knowledge graphs (KGs). Secondly, we analyze the concordance of co-expression patterns across datasets to identify disease-specific as well as common pathways. Thirdly, we examine enriched pathways across datasets and disorders to identify common biological mechanisms between them. Lastly, we investigate the correspondence of shared genetic variants between these two disorders and T2DM as well as the disease-specific KGs. In conclusion, our work reveals several shared candidate genes and pathways, particularly those related to the immune system, such as TNF signaling pathway, IL-17 signaling pathway and NF-kappa B signaling pathway and nervous system, such as dopaminergic synapse and GABAergic synapse, which we propose mediate the link between schizophrenia and bipolar disorder and its shared comorbidity, T2DM.

Microstructural white matter abnormalities in pediatric and adult obsessive-compulsive disorder: A systematic review and meta-analysis

OBJECTIVE

To identify the most prominent and replicable fractional anisotropy (FA) alterations of white matter associated with obsessive-compulsive disorder (OCD) in tract-based spatial statistics (TBSS) studies.

METHODS

We reviewed previous TBSS studies (n = 20) in OCD and performed a meta-analysis (n = 16) of FA differences.

RESULTS

No between-group differences in FA were detected in the pooled meta-analysis. However, reduced FA was identified in the genu and anterior body of corpus callosum (CC) in adult OCD. FA reductions in the anterior body of CC were associated with a later age of onset in adult patients with OCD. For pediatric OCD, decreased FA in earlier adolescence and increased FA in later adolescence were seemingly related to an altered trajectory of brain maturation.

CONCLUSIONS

Absent in the pooled sample but robust in adults, disrupted microstructural organization in the anterior part of CC indicates a bias of deficits toward connections in interhemispheric connections of rostral neocortical regions, which could lead to deficits of interhemispheric communication and thus contribute to cognitive and emotional deficits in adult OCD. The correlation between FA in the anterior body of CC and older illness onset suggests that patients with later adult onset of illness may represent a biologically distinct subgroup. For pediatric OCD, alterations in neurodevelopmental maturation may contribute to inconsistent patterns of FA alteration relative to controls during adolescence. While most studies of OCD have emphasized alterations of within hemisphere fronto-striatal circuits, these results indicate that between hemisphere connectivity of this circuitry may also represent important pathophysiology of the illness.

Neurotrophins as a reliable biomarker for brain function, structure and cognition: A systematic review and meta-analysis

Neurotrophins are signalling molecules involved in the formation and maintenance of synapses in the brain. They can cross the blood-brain barrier and be detected in peripheral blood, suggesting they may be a potential biomarker for brain health and function. In this review, the available literature was systematically searched for studies comparing peripheral neurotrophins levels with MRI and cognitive measures in healthy adults. Twenty-four studies were identified, six of which included a neuroimaging outcome. Fifteen studies measuring cognition were eligible for meta-analysis. The majority of studies measured levels of brain-derived neurotrophic factor (BDNF), with few assessing other neurotrophins. Results revealed BDNF is related to some neuroimaging outcomes, with some studies suggesting older age may be an important factor. A higher proportion of studies who had older samples observed significant effects between cognition and neurotrophin levels. When cognitive studies were pooled together in a meta-analysis, there was a weak non-significant effect between BDNF and cognitive outcomes. There was also a high level of heterogeneity between cognitive studies. Results indicated that gender was a notable source of the heterogeneity, but additional studies employing relevant covariates are necessary to better characterise the inter-relationship between circulating neurotrophins and cognition.

Obsessive-compulsive disorder and growth factors: A comparative review

The goal of this article is to clarify the role of various growth factors in the establishment and progression of obsessive-compulsive disorder (OCD). OCD is a chronic mental disorder with recurrent intrusive thoughts and/or repetitive compulsive behaviors that increase during stressful periods. Growth and neurotrophic factors may be contributing factors in the pathophysiology of OCD. Many of them are synthesized and released within the central nervous system and act as trophic agents in neurons; some of them are involved in brain growth, development, neurogenesis, myelination and plasticity, while others take part in the protection of the nervous system following brain injuries. This paper attempts to identify all articles investigating the relationship between OCD and neurotrophic and growth factors, in both animal and human studies, with a focus on adult brain studies. Based on the PubMed and Scopus and Science Direct search tools, the available articles and studies are reviewed. Out of 230 records in total, the ones related to our review topic were taken into account to further understand the pathophysiological mechanism(s) of OCD, providing methods to improve its symptoms via the modification of neurotrophins and growth factor imbalances.

Discoidin domain receptor 1 gene variants are associated with decreased white matter fractional anisotropy and decreased processing speed in schizophrenia

DDR1 has been linked to schizophrenia (SZ) and myelination. Here, we tested whether DDR1 variants in people at risk for SZ influence white matter (WM) structural variations and cognitive processing speed (PS). First, following a case-control design (Study 1), SZ patients (N = 1193) and controls (N = 1839) were genotyped for rs1264323 and rs2267641 at DDR1, and the frequencies were compared. We replicated the association between DDR1 and SZ (rs1264323, adjusted P = 0.015). Carriers of the rs1264323AA combined with the rs2267641AC or CC genotype are at risk to develop SZ compared to the other genotype combinations. Second, SZ patients (Study 2, N = 194) underwent an evaluation of PS using the Trail Making Test (TMT) and DDR1 genotyping. To compare PS between DDR1 genotype groups, we conducted an analysis of covariance (including rs1264323 as a covariate) and found that SZ patients with the rs2267641CC genotype had decreased PS compared to patients with the AA and AC genotypes. Third, 54 patients (Study 3) from Study 2 were selected based on rs1264323 genotype to undergo reevaluation, including a DTI-MRI brain scan. To test for associations between PS, WM microstructure and DDR1 genotype, we first localized those WM regions where fractional anisotropy (FA) was correlated with PS and tested whether FA showed differences between the rs1264323 genotypes. SZ patients with the rs1264323AA genotype showed decreased FA in WM regions associated with decreased PS. We conclude that DDR1 variants may confer a risk of SZ through WM microstructural alterations leading to cognitive dysfunction.

Identification of a noncoding RNA‑mediated gene pair‑based regulatory module in Alzheimer's disease

Alzheimer's disease (AD) is the most common type of neurological disorder that results from brain cell death; however, not all brain regions are simultaneously affected to the same extent. Despite single biomarkers for AD having been determined on a genome-wide scale, the differential co-expression in gene pairs between regions and interactions with other types of cellular molecules, particularly non-coding (nc)RNAs, are often overlooked in studies investigating the underlying mechanisms associated with AD. In the present study, based on 1,548 samples obtained from a cohort of 90 patients with AD spanning 19 brain regions, a gene-pair based method was established for the classification of 19 brain regions into seven different groups, including marked disparate groupings of six single regions and a cluster of another 13 regions as revealed by principal component analysis (PCA). To further investigate the different underlying mechanisms associated with each group, five highly interconnected functional modules of the protein-protein interaction network were demonstrated to characterize the seven region groups containing six single groups and 13 clustered regions based on 4,731 gene-pairs. Genes in two of the functional modules exhibited a strong association with pathways associated with the nervous system, including cholinergic synapses, circadian entrainment and dopaminergic synapses. Notably, following integration of these two modules with a ncRNA-mediated network, one module demonstrated a strong association with micro (mi)RNAs, which were revealed to interact with numerous long non-coding (lnc)RNAs associated with AD, such as metastasis associated lung adenocarcinoma transcript 1 and taurine upregulated 1. This suggested that mRNAs and lncRNAs may represent competing endogenous RNAs for binding with miRNAs. Thus, these results indicated that the ncRNA-mediated gene regulatory module detected by the established gene pair-based method may further the understanding of underlying mechanisms associated with AD as well as aid the development of novel therapeutic strategies for the treatment of patients with AD.

VariFunNet, an integrated multiscale modeling framework to study the effects of rare non-coding variants in Genome-Wide Association Studies: applied to Alzheimer's Disease

It is a grand challenge to reveal the causal effects of DNA variants in complex phenotypes. Although statistical techniques can establish correlations between genotypes and phenotypes in Genome-Wide Association Studies (GWAS), they often fail when the variant is rare. The emerging Network-based Association Studies aim to address this shortcoming in statistical analysis, but are mainly applied to coding variations. Increasing evidences suggest that non-coding variants play critical roles in the etiology of complex diseases. However, few computational tools are available to study the effect of rare non-coding variants on phenotypes. Here we have developed a multiscale modeling variant-to-function-to-network framework VariFunNet to address these challenges. VariFunNet first predict the functional variations of molecular interactions, which result from the non-coding variants. Then we incorporate the genes associated with the functional variation into a tissue-specific gene network, and identify subnetworks that transmit the functional variation to molecular phenotypes. Finally, we quantify the functional implication of the subnetwork, and prioritize the association of the non-coding variants with the phenotype. We have applied VariFunNet to investigating the causal effect of rare non-coding variants on Alzheimer's disease (AD). Among top 21 ranked causal non-coding variants, 16 of them are directly supported by existing evidences. The remaining 5 novel variants dysregulate multiple downstream biological processes, all of which are associated with the pathology of AD. Furthermore, we propose potential new drug targets that may modulate diverse pathways responsible for AD. These findings may shed new light on discovering new biomarkers and therapies for the prevention, diagnosis, and treatment of AD. Our results suggest that multiscale modeling is a potentially powerful approach to studying causal genotype-phenotype associations.

Reduced Cerebral White Matter Integrity Assessed by DTI in Cognitively Normal H63D-HFE Polymorphism Carriers

BACKGROUND AND PURPOSE

The H63D-HFE single nucleotide polymorphism (SNP) has been associated with brain iron dysregulation; however, the emergent role of this missense variant in brain structure and function has yet to be determined. Previous work has demonstrated that HFE SNP carriers have reduced white matter magnetic resonance imaging (MRI) proton relaxation rates. The mechanism by which white matter alterations perturb MRI relaxation is unknown as is how these metrics are related to myelin integrity.

METHODS

Fifteen subjects heterozygous for the HFE-H63D SNP and 25 controls with wild-type HFE had diffusion-weighted, anatomical MRIs taken, and underwent cognitive assessment. Fractional anisotropy (FA), mean diffusion (MD), and mode of anisotropy (MO) were calculated from the diffusion dataset to investigate the relationship between the H63D-HFE SNP and myelin integrity.

RESULTS

A decrease in FA, an increase in MD, and an increase in MO are demonstrated in multiple H63D-HFE polymorphism carrier white matter tracts. Regions with altered diffusion metrics are notably located in heavily myelinated white matter association fibers, such as the anterior corona radiata and longitudinal fasciculi.

CONCLUSIONS

The MRI data presented here demonstrate that H63D-HFE polymorphism carriers have diffusivity changes in white matter compared to wild-type subjects. The reduced integrity white matter tracts in H63D-HFE carriers are hypothesized to be related to increased susceptibility of these late-myelinating regions to cellular stress induced by oligodendrocyte iron dyshomeostasis.

Association of CACNA1C and SYNE1 in offspring of patients with psychiatric disorders

Schizophrenia (SZ) and bipolar disorder (BD) are severe mental diseases associated with cognitive impairment, mood disturbance, and psychosis. Both disorders are highly heritable and share a common genetic background. The present study assesses, for the first time, differences in genotype frequencies of polymorphisms located in genes involved in neurodevelopment and synaptic plasticity between genetic high-risk individuals (offspring of patients with SZ or BD; N=100: 31 and 69, respectively) and control subjects (offspring of community controls; N=96). Individuals from both groups had similar ages, around 12 years. A higher percentage of men were included in the genetic high-risk group (58%) compared with the control group (40.6%). A total of 244 validated SNPs located in 35 candidate gene regions were analyzed in 196 participants. Multivariate methods based on logistic regression analysis were performed to assess differences in genotype frequencies. Bonferroni correction was applied for the multiple comparisons performed. Two polymorphisms, CACNA1C rs10848683 and SYNE1 rs214950, showed significant differences. The frequency of heterozygotes for CACNA1C rs10848683 in genetic high-risk individuals was double that in controls (OR=3.15; P=0.00016). For SYNE1 rs214950, higher frequencies of heterozygotes (OR=1.97) and homozygotes for the minor allele (OR=17.89; P=0.00020) were found in the genetic high-risk group than in the control group. In conclusion, polymorphisms in CACNA1C and SYNE1 could confer a greater risk of developing SZ and BD in individuals who are already at high risk because of their family history. This could help identify subjects with a very high genetic risk, in whom early detection and early intervention could lead to better prognosis.

A common NTRK2 variant is associated with emotional arousal and brain white-matter integrity in healthy young subjects

Dysregulation of emotional arousal is observed in many psychiatric diseases such as schizophrenia, mood and anxiety disorders. The neurotrophic tyrosine kinase receptor type 2 gene (NTRK2) has been associated with these disorders. Here we investigated the relation between genetic variability of NTRK2 and emotional arousal in healthy young subjects in two independent samples (n1=1171; n2=707). In addition, diffusion tensor imaging (DTI) data in a subgroup of 342 participants were used to identify NTRK2-related white-matter structure differences. After correction for multiple testing, we identified a NTRK2 single nucleotide polymorphism associated with emotional arousal in both samples (n1: Pnominal=0.0003, Pcorrected=0.048; n2: Pnominal=0.0141, Pcorrected=0.036). DTI revealed significant, whole-brain corrected correlations between emotional arousal and brain white-matter mean diffusivity (MD), as well as significant, whole-brain corrected NTRK2 genotype-related differences in MD (PFWE<0.05). Our study demonstrates that genetic variability of NTRK2, a susceptibility gene for psychiatric disorders, is related to emotional arousal and-independently-to brain white-matter properties in healthy individuals.

White matter microstructural characteristics in Bipolar I and Bipolar II Disorder: A diffusion tensor imaging study

BACKGROUND

Diffusion tensor imaging (DTI) studies of bipolar disorder (BD) report contrasting results and are mainly focused on bipolar I (BD-I) samples. We aimed at investigating how and where DTI parameters differ between BD-I and bipolar II (BD-II) and between BD and healthy control subjects (HC).

METHODS

We conducted a tract-based spatial statistics analysis of DTI derived parameters, namely fractional anisotropy (FA), axial diffusivity (AD) and radial diffusivity (RD) in a matched sample of 50 BD (25 BD-I and 25 BD-II) during the chronic course of the illness and 50 HC.

RESULTS

Compared to BD-I and HC, BD-II showed lower FA but no significant AD or RD differences in the right inferior longitudinal fasciculus (ILF). Both patient groups showed lower AD and RD in the left internal capsule and lower AD across the left ILF, the cortico-spinal tract within the right hemisphere and bilaterally in the cerebellum with respect to HC.

LIMITATIONS

Patients were medicated at the time of scanning; the BD-II group had higher Hamilton Rating Scale for Depression scores than the BD-I group.

CONCLUSIONS

BD-II patients differ from BD-I in the ILF. Both BD subtypes showed widespread white matter (WM) changes in the internal capsule, cortico-spinal tract and cerebellum. The loss of WM integrity in BD-II might be due to demyelination whereas WM changes common to both subgroups could be attributable to axonal damage.

Association between genetic variants related to glutamatergic, dopaminergic and neurodevelopment pathways and white matter microstructure in child and adolescent patients with obsessive-compulsive disorder

BACKGROUND

Alterations in white matter (WM) integrity observed in patients with obsessive-compulsive disorder (OCD) may be at least partly determined genetically. Neuroimaging measures of WM microstructure could serve as promising intermediate phenotypes for genetic analysis of the disorder. The objective of the present study was to explore the association between variability in genes related to the pathophysiology of OCD and altered WM microstructure previously identified in child and adolescent patients with the disease.

METHODS

Fractional anisotropy (FA) and mean diffusivity (MD) measured by diffusion tensor imaging (DTI) and 262 single nucleotide polymorphisms (SNPs) in 35 candidate genes were assessed concomitantly in 54 child and adolescent OCD patients.

RESULTS

Six polymorphisms located in the glutamate transporter gene (SLC1A1 rs3087879), dopamine transporter gene (SLC6A3 rs4975646), dopamine receptor D3 (DRD3 rs3773679), nerve growth factor receptor gene (NGFR rs734194 and rs2072446), and cadherin 9 gene (CDH9 rs6885387) showed significant p-values after Bonferroni correction (p≤0.00019). More specifically, the vast majority of these associations were detected with MD in the right and left anterior and posterior cerebellar lobes.

LIMITATIONS

Patients were under pharmacological treatment at the time of the DTI examination. Sample size is limited.

CONCLUSIONS

The results provide the first evidence of the involvement of genetic variants related to glutamatergic, dopaminergic, and neurodevelopmental pathways in determining the WM microstructure of child and adolescent patients with OCD, which could be related to the neurobiology of the disorder.

FVGWAS: Fast voxelwise genome wide association analysis of large-scale imaging genetic data

More and more large-scale imaging genetic studies are being widely conducted to collect a rich set of imaging, genetic, and clinical data to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. Several major big-data challenges arise from testing genome-wide (NC>12 million known variants) associations with signals at millions of locations (NV~10(6)) in the brain from thousands of subjects (n~10(3)). The aim of this paper is to develop a Fast Voxelwise Genome Wide Association analysiS (FVGWAS) framework to efficiently carry out whole-genome analyses of whole-brain data. FVGWAS consists of three components including a heteroscedastic linear model, a global sure independence screening (GSIS) procedure, and a detection procedure based on wild bootstrap methods. Specifically, for standard linear association, the computational complexity is O (nNVNC) for voxelwise genome wide association analysis (VGWAS) method compared with O ((NC+NV)n(2)) for FVGWAS. Simulation studies show that FVGWAS is an efficient method of searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. Finally, we have successfully applied FVGWAS to a large-scale imaging genetic data analysis of ADNI data with 708 subjects, 193,275voxels in RAVENS maps, and 501,584 SNPs, and the total processing time was 203,645s for a single CPU. Our FVGWAS may be a valuable statistical toolbox for large-scale imaging genetic analysis as the field is rapidly advancing with ultra-high-resolution imaging and whole-genome sequencing.

Multivariate genetic determinants of EEG oscillations in schizophrenia and psychotic bipolar disorder from the BSNIP study

Schizophrenia (SZ) and psychotic bipolar disorder (PBP) are disabling psychiatric illnesses with complex and unclear etiologies. Electroencephalogram (EEG) oscillatory abnormalities in SZ and PBP probands are heritable and expressed in their relatives, but the neurobiology and genetic factors mediating these abnormalities in the psychosis dimension of either disorder are less explored. We examined the polygenic architecture of eyes-open resting state EEG frequency activity (intrinsic frequency) from 64 channels in 105 SZ, 145 PBP probands and 56 healthy controls (HCs) from the multisite BSNIP (Bipolar-Schizophrenia Network on Intermediate Phenotypes) study. One million single-nucleotide polymorphisms (SNPs) were derived from DNA. We assessed eight data-driven EEG frequency activity derived from group-independent component analysis (ICA) in conjunction with a reduced subset of 10,422 SNPs through novel multivariate association using parallel ICA (para-ICA). Genes contributing to the association were examined collectively using pathway analysis tools. Para-ICA extracted five frequency and nine SNP components, of which theta and delta activities were significantly correlated with two different gene components, comprising genes participating extensively in brain development, neurogenesis and synaptogenesis. Delta and theta abnormality was present in both SZ and PBP, while theta differed between the two disorders. Theta abnormalities were also mediated by gene clusters involved in glutamic acid pathways, cadherin and synaptic contact-based cell adhesion processes. Our data suggest plausible multifactorial genetic networks, including novel and several previously identified (DISC1) candidate risk genes, mediating low frequency delta and theta abnormalities in psychoses. The gene clusters were enriched for biological properties affecting neural circuitry and involved in brain function and/or development.

Processing speed impairment in schizophrenia is mediated by white matter integrity

BACKGROUND

Processing speed predicts functional outcome and is a potential endophenotype for schizophrenia. Establishing the neural basis of processing speed impairment may inform the treatment and etiology of schizophrenia. Neuroimaging investigations in healthy subjects have linked processing speed to brain anatomical connectivity. However, the relationship between processing speed impairment and white matter (WM) integrity in schizophrenia is unclear.

METHOD

Individuals with schizophrenia and healthy subjects underwent diffusion tensor imaging (DTI) and completed a brief neuropsychological assessment that included measures of processing speed, verbal learning, working memory and executive functioning. Group differences in WM integrity, inferred from fractional anisotropy (FA), were examined throughout the brain and the hypothesis that processing speed impairment in schizophrenia is mediated by diminished WM integrity was tested.

RESULTS

WM integrity of the corpus callosum, cingulum, superior and inferior frontal gyri, and precuneus was reduced in schizophrenia. Average FA in these regions mediated group differences in processing speed but not in other cognitive domains. Diminished WM integrity in schizophrenia was accounted for, in large part, by individual differences in processing speed.

CONCLUSIONS

Cognitive impairment in schizophrenia was mediated by reduced WM integrity. This relationship was strongest for processing speed because deficits in working memory, verbal learning and executive functioning were not mediated by WM integrity. Larger sample sizes may be required to detect more subtle mediation effects in these domains. Interventions that preserve WM integrity or ameliorate WM disruption may enhance processing speed and functional outcome in schizophrenia.

Genetic underpinnings of white matter 'connectivity': heritability, risk, and heterogeneity in schizophrenia

Schizophrenia is a highly heritable disorder. Thus, the combination of genetics and brain imaging may be a useful strategy to investigate the effects of risk genes on anatomical connectivity, and for gene discovery, i.e. discovering the genetic correlates of white matter phenotypes. Following a database search, I review evidence for heritability of white matter phenotypes. I also review candidate gene investigations, examining association of putative risk variants with white matter phenotypes, as well as the recent flurry of research exploring relationships of genome-wide significant risk loci with white matter phenotypes. Finally, I review multivariate and polygene approaches, which constitute a new wave of imaging-genetics research, including large collaborative initiatives aiming to discover new genes that may predict aspects of white matter microstructure. The literature supports the heritability of white matter phenotypes. Loci in genes intimately implicated in oligodendrocyte and myelin development, growth and maintenance, and neurotrophic systems are associated with white matter microstructure. GWAS variants have not yet sufficiently been explored using DTI-based evaluation of white matter to draw conclusions, although micro-RNA 137 is promising due to its potential regulation of other GWAS schizophrenia genes. Many imaging-genetic studies only include healthy participants, which, while helping control for certain confounds, cannot address questions related to disease heterogeneity or symptom expression, and thus more studies should include participants with schizophrenia. With sufficiently large sample sizes, the future of this field lies in polygene strategies aimed at risk prediction and heterogeneity dissection of schizophrenia that can translate to personalized interventions.