Statistical epistasis and progressive brain change in schizophrenia: an approach for examining the relationships between multiple genes

Prenatal dexamethasone exposure induces anxiety- and depressive-like behavior of male offspring rats through intrauterine programming of the activation of NRG1-ErbB4 signaling in hippocampal PV interneurons

Dexamethasone is a commonly used synthetic glucocorticoid in the clinic. As a compound that can cross the placental barrier to promote fetal lung maturation, dexamethasone is extensively used in pregnant women at risk of premature delivery. However, the use of glucocorticoids during pregnancy increases the risk of neurodevelopmental disorders. In the present study, we observed anxiety- and depressive-like behavior changes and hyperexcitability of hippocampal neurons in adult rat offspring with previous prenatal dexamethasone exposure (PDE); the observed changes were related to in utero damage of parvalbumin interneurons. A programmed change in neuregulin 1 (NRG1)-Erb-b2 receptor tyrosine kinase 4 (ErbB4) signaling was the key to the damage of parvalbumin interneurons in the hippocampus of PDE offspring. Anxiety- and depressive-like behavior, NRG1-ErbB4 signaling activation, and damage of parvalbumin interneurons in PDE offspring were aggravated after chronic stress. The intervention of NRG1-ErbB4 signaling contributed to the improvement in dexamethasone-mediated injury to parvalbumin interneurons. These results suggested that PDE might cause anxiety- and depressive-like behavior changes in male rat offspring through the programmed activation of NRG1-ErbB4 signaling, resulting in damage to parvalbumin interneurons and hyperactivity of the hippocampus. Intrauterine programming of neuregulin 1 (NRG1)-Erb-b2 receptor tyrosine kinase 4 (ERBB4) overactivation by dexamethasone mediates anxiety- and depressive-like behavior in male rat offspring.

Detecting genetic epistasis by differential departure from independence

Countering prior beliefs that epistasis is rare, genomics advancements suggest the other way. Current practice often filters out genomic loci with low variant counts before detecting epistasis. We argue that this practice is far from optimal because it can throw away strong epistatic patterns. Instead, we present the compensated Sharma-Song test to infer genetic epistasis in genome-wide association studies by differential departure from independence. The test does not require a minimum number of replicates for each variant. We also introduce algorithms to simulate epistatic patterns that differentially depart from independence. Using two simulators, the test performed comparably to the original Sharma-Song test when variant frequencies at a locus are marginally uniform; encouragingly, it has a marked advantage over alternatives when variant frequencies are marginally nonuniform. The test further revealed uniquely clean epistatic variants associated with chicken abdominal fat content that are not prioritized by other methods. Genes involved in most numbers of inferred epistasis between single nucleotide polymorphisms (SNPs) belong to pathways known for obesity regulation; many top SNPs are located on chromosome 20 and in intergenic regions. Measuring differential departure from independence, the compensated Sharma-Song test offers a practical choice for studying epistasis robust to nonuniform genetic variant frequencies.

Association of the brain-derived neurotrophic factor Val66Met polymorphism with negative symptoms severity, but not cognitive function, in first-episode schizophrenia spectrum disorders

Objective

A functional polymorphism of the brain-derived neurotrophic factor gene (BDNF) Val66Met has been associated with cognitive function and symptom severity in patients with schizophrenia. It has been suggested that the Val66Met polymorphism has a role as a modulator in a range of clinical features of the illness, including symptoms severity, therapeutic responsiveness, age of onset, brain morphology and cognitive function. However, little work has been done in first-episode schizophrenia (FES) spectrum disorders. The objective of this study is to investigate the association of the BDNF Val66Met polymorphism on cognitive function and clinical symptomatology in FES patients.

Methods

Using a cross-sectional design in a cohort of 204 patients with FES or a schizophrenia spectrum disorder and 204 healthy matched controls, we performed BDNF Val66Met genotyping and tested its relationship with cognitive testing (attention, working memory, learning/verbal memory and reasoning/problem-solving) and assessment of clinical symptom severity.

Results

There was no significant influence of the BDNF allele frequency on cognitive factor scores in either patients or controls. An augmented severity of negative symptoms was found in FES patients that carried the Met allele.

Conclusions

The results of this study suggest that in patients with a first-episode of schizophrenia or a schizophrenia spectrum disorder, the BDNF Val66Met polymorphism does not exert an influence on cognitive functioning, but is associated with negative symptoms severity. BDNF may serve as suitable marker of negative symptomatology severity in FES patients within the schizophrenia spectrum.

Multivariate Pattern Analysis of Genotype-Phenotype Relationships in Schizophrenia

Genetic risk variants for schizophrenia have been linked to many related clinical and biological phenotypes with the hopes of delineating how individual variation across thousands of variants corresponds to the clinical and etiologic heterogeneity within schizophrenia. This has primarily been done using risk score profiling, which aggregates effects across all variants into a single predictor. While effective, this method lacks flexibility in certain domains: risk scores cannot capture nonlinear effects and do not employ any variable selection. We used random forest, an algorithm with this flexibility designed to maximize predictive power, to predict 6 cognitive endophenotypes in a combined sample of psychiatric patients and controls (N = 739) using 77 genetic variants strongly associated with schizophrenia. Tenfold cross-validation was applied to the discovery sample and models were externally validated in an independent sample of similar ancestry (N = 336). Linear approaches, including linear regression and task-specific polygenic risk scores, were employed for comparison. Random forest models for processing speed (P = .019) and visual memory (P = .036) and risk scores developed for verbal (P = .042) and working memory (P = .037) successfully generalized to an independent sample with similar predictive strength and error. As such, we suggest that both methods may be useful for mapping a limited set of predetermined, disease-associated SNPs to related phenotypes. Incorporating random forest and other more flexible algorithms into genotype-phenotype mapping inquiries could contribute to parsing heterogeneity within schizophrenia; such algorithms can perform as well as standard methods and can capture a more comprehensive set of potential relationships.

Imaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential

Imaging genetics and genomics research has begun to provide insight into the molecular and genetic architecture of neural phenotypes and the neural mechanisms through which genetic risk for psychopathology may emerge. As it approaches its third decade, imaging genetics is confronted by many challenges, including the proliferation of studies using small sample sizes and diverse designs, limited replication, problems with harmonization of neural phenotypes for meta-analysis, unclear mechanisms, and evidence that effect sizes may be more modest than originally posited, with increasing evidence of polygenicity. These concerns have encouraged the field to grow in many new directions, including the development of consortia and large-scale data collection projects and the use of novel methods (e.g., polygenic approaches, machine learning) that enhance the quality of imaging genetic studies but also introduce new challenges. We critically review progress in imaging genetics and offer suggestions and highlight potential pitfalls of novel approaches. Ultimately, the strength of imaging genetics and genomics lies in their translational and integrative potential with other research approaches (e.g., nonhuman animal models, psychiatric genetics, pharmacologic challenge) to elucidate brain-based pathways that give rise to the vast individual differences in behavior as well as risk for psychopathology.

Altered cytokine profile, pain sensitivity, and stress responsivity in mice with co-disruption of the developmental genes Neuregulin-1×DISC1

The complex genetic origins of many human disorders suggest that epistatic (gene×gene) interactions may contribute to a significant proportion of their heritability estimates and phenotypic heterogeneity. Simultaneous disruption of the developmental genes and schizophrenia risk factors Neuregulin-1 (NRG1) and Disrupted-in-schizophrenia 1 (DISC1) in mice has been shown to produce disease-relevant and domain-specific phenotypic profiles different from that observed following disruption of either gene alone. In the current study, anxiety and stress responsivity phenotypes in male and female mutant mice with simultaneous disruption of DISC1 and NRG1 were examined. NRG1×DISC1 mutant mice were generated and adult mice from each genotype were assessed for pain sensitivity (hot plate and tail flick tests), anxiety (light-dark box), and stress-induced hypothermia. Serum samples were assayed to measure circulating levels of pro-inflammatory cytokines. Mice with the NRG1 mutation, irrespective of DISC1 mutation, spent significantly more time in the light chamber, displayed increased core body temperature following acute stress, and decreased pain sensitivity. Basal serum levels of cytokines IL8, IL1β and IL10 were decreased in NRG1 mutants. Mutation of DISC1, in the absence of epistatic interaction with NRG1, was associated with increased serum levels of IL1β. Epistatic effects were evident for IL6, IL12 and TNFα. NRG1 mutation alters stress and pain responsivity, anxiety, and is associated with changes in basal cytokine levels. Epistasis resulting from synergistic NRG1 and DISC1 gene mutations altered pro-inflammatory cytokine levels relative to the effects of each of these genes individually, highlighting the importance of epistatic mechanisms in immune-related pathology.

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.

Genetic Moderation of Stress Effects on Corticolimbic Circuitry

Stress exposure is associated with individual differences in corticolimbic structure and function that often mirror patterns observed in psychopathology. Gene x environment interaction research suggests that genetic variation moderates the impact of stress on risk for psychopathology. On the basis of these findings, imaging genetics, which attempts to link variability in DNA sequence and structure to neural phenotypes, has begun to incorporate measures of the environment. This research paradigm, known as imaging gene x environment interaction (iGxE), is beginning to contribute to our understanding of the neural mechanisms through which genetic variation and stress increase psychopathology risk. Although awaiting replication, evidence suggests that genetic variation within the canonical neuroendocrine stress hormone system, the hypothalamic-pituitary-adrenal axis, contributes to variability in stress-related corticolimbic structure and function, which, in turn, confers risk for psychopathology. For iGxE research to reach its full potential it will have to address many challenges, of which we discuss: (i) small effects, (ii) measuring the environment and neural phenotypes, (iii) the absence of detailed mechanisms, and (iv) incorporating development. By actively addressing these challenges, iGxE research is poised to help identify the neural mechanisms underlying genetic and environmental associations with psychopathology.

Association studies of genomic variants with treatment response to risperidone, clozapine, quetiapine and chlorpromazine in the Chinese Han population

Schizophrenia is a widespread mental disease with a prevalence of about 1% in the world population. Continuous long-term treatment is required to maintain social functioning and prevent symptom relapse of schizophrenia patients. However, there are considerable individual differences in response to the antipsychotic drugs. There is a pressing need to identify more drug-response-related markers. But most pharmacogenomics of schizophrenia have typically focused on a few candidate genes in small sample size. In this study, 995 subjects were selected for discovering the drug-response-related markers. A total of 77 single-nucleotide polymorphisms of 25 genes have been investigated for four commonly used antipsychotic drugs in China: risperidone, clozapine, quetiapine, and chlorpromazine. Significant associations with treatment response for several genes, such as CYP2D6, CYP2C19, COMT, ABCB1, DRD3 and HTR2C have been verified in our study. Also, we found several new candidate genes (TNIK, RELN, NOTCH4 and SLC6A2) and combinations (haplotype rs1544325-rs5993883-rs6269-rs4818 in COMT) that are associated with treatment response to the four drugs. Also, multivariate interactions analysis demonstrated the combination of rs6269 in COMT and rs3813929 in HTR2C may work as a predictor to improve the clinical antipsychotic response. So our study is of great significance to improve current knowledge on the pharmacogenomics of schizophrenia, thus promoting the implementation of personalized medicine in schizophrenia.The Pharmacogenomics Journal advance online publication, 18 August 2015; doi:10.1038/tpj.2015.61.

Epistasis in the risk of human neuropsychiatric disease

Neuropsychiatric disease represents the ideal class of disease to assess the role of epistasis, as more genes are expressed in the brain than in any other tissue. In this chapter, two well-studied neuropsychiatric diseases are examined, Alzheimer's disease (AD) and schizophrenia, which have been shown to have multiple and, often, replicated interactions that associate with clinical endpoints or related phenotypes. In each case, a single gene is represented in a plurality of epistatic interactions, apolipoprotein E (APOE) for AD and catechol-O-methyltransferase for schizophrenia. Interestingly, of the two, only APOE has clear-cut and consistent evidence for a marginal association. Unraveling the underlying reasons is important in understanding both genetic etiology and architecture as well as how to use genetics to provide better personalized treatments.

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Progressive brain changes in schizophrenia related to antipsychotic treatment? A meta-analysis of longitudinal MRI studies

Context

Antipsychotic treatment is the first-line treatment option for schizophrenia. Individual studies suggested they can significantly affect brain structure and account for progressive brain changes observed during the illness.

Objectives

To quantitatively examine the effect of antipsychotics as compared to illness related factors on progressive brain changes in schizophrenia.

Data sources

Electronic databases were searched until April 2012. All magnetic resonance imaging studies reporting progressive brain changes in schizophrenia subjects and antipsychotic exposure were retrieved.

Study selection

30 longitudinal MRI studies with antipsychotic administration in schizophrenia patients met the inclusion criteria.

Data extraction

Brain volumes before and after antipsychotic exposure, duration of illness, severity of psychotic symptoms as well as demographic, clinical, and methodological variables were extracted from each publication, or obtained directly from its authors.

Data synthesis

The overall sample was of 1046 schizophrenia patients and 780 controls for a median duration of follow-up of 72.4 weeks. At baseline, patients showed significant whole brain volume reductions and enlarged lateral ventricle (LV) volumes compared to controls. No baseline volumetric abnormalities were detected in the gray matter volumes (GMV), white matter volumes, cerebrospinal fluid and caudate nucleus. Longitudinally, there were progressive GMV decreases and LV enlargements in patients but not in controls. The GMV decreases were inversely correlated with cumulative exposure to antipsychotic treatments, while no effects were observed for duration of illness or illness severity.

Conclusions

Schizophrenia is characterized by progressive gray matter volume decreases and lateral ventricular volume increases. Some of these neuroanatomical alterations may be associated with antipsychotic treatment.

The DAO gene is associated with schizophrenia and interacts with other genes in the Taiwan Han Chinese population

BACKGROUND

Schizophrenia is a highly heritable disease with a polygenic mode of inheritance. Many studies have contributed to our understanding of the genetic underpinnings of schizophrenia, but little is known about how interactions among genes affect the risk of schizophrenia. This study aimed to assess the associations and interactions among genes that confer vulnerability to schizophrenia and to examine the moderating effect of neuropsychological impairment.

METHODS

We analyzed 99 SNPs from 10 candidate genes in 1,512 subject samples. The permutation-based single-locus, multi-locus association tests, and a gene-based multifactorial dimension reduction procedure were used to examine genetic associations and interactions to schizophrenia.

RESULTS

We found that no single SNP was significantly associated with schizophrenia. However, a risk haplotype, namely A-T-C of the SNP triplet rsDAO7-rsDAO8-rsDAO13 of the DAO gene, was strongly associated with schizophrenia. Interaction analyses identified multiple between-gene and within-gene interactions. Between-gene interactions including DAO*DISC1 , DAO*NRG1 and DAO*RASD2 and a within-gene interaction for CACNG2 were found among schizophrenia subjects with severe sustained attention deficits, suggesting a modifying effect of impaired neuropsychological functioning. Other interactions such as the within-gene interaction of DAO and the between-gene interaction of DAO and PTK2B were consistently identified regardless of stratification by neuropsychological dysfunction. Importantly, except for the within-gene interaction of CACNG2, all of the identified risk haplotypes and interactions involved SNPs from DAO.

CONCLUSIONS

These results suggest that DAO, which is involved in the N-methyl-d-aspartate receptor regulation, signaling and glutamate metabolism, is the master gene of the genetic associations and interactions underlying schizophrenia. Besides, the interaction between DAO and RASD2 has provided an insight in integrating the glutamate and dopamine hypotheses of schizophrenia.

DISC1 genetics, biology and psychiatric illness

Psychiatric disorders are highly heritable, and in many individuals likely arise from the combined effects of genes and the environment. A substantial body of evidence points towards DISC1 being one of the genes that influence risk of schizophrenia, bipolar disorder and depression, and functional studies of DISC1 consequently have the potential to reveal much about the pathways that lead to major mental illness. Here, we review the evidence that DISC1 influences disease risk through effects upon multiple critical pathways in the developing and adult brain.

An odor-specific threshold deficit implicates abnormal cAMP signaling in youths at clinical risk for psychosis

BACKGROUND

While olfactory deficits have been reported in schizophrenia and youths at-risk for psychosis, few studies have linked these deficits to current pathophysiological models of the illness. There is evidence that disrupted cyclic adenosine 3',5'-monophosphate (cAMP) signaling may contribute to schizophrenia pathology. As cAMP mediates olfactory signal transduction, the degree to which this disruption could manifest in olfactory impairment was ascertained. Odor-detection thresholds to two odorants that differ in the degree to which they activate intracellular cAMP were assessed in clinical risk and low-risk participants.

METHOD

Birhinal assessments of odor-detection threshold sensitivity to lyral and citralva were acquired in youths experiencing prodromal symptoms (n=17) and controls at low risk for developing psychosis (n=15). Citralva and lyral are odorants that differ in cAMP activation; citralva is a strong cAMP activator and lyral is a weak cAMP activator.

RESULTS

The overall group-by-odor interaction was statistically significant. At-risk youths showed significantly reduced odor detection thresholds for lyral, but showed intact detection thresholds for citralva. This odor-specific threshold deficit was uncorrelated with deficits in odor identification or discrimination, which were also present. ROC curve analysis revealed that olfactory performance correctly classified at-risk and low-risk youths with greater than 97% accuracy.

CONCLUSIONS

This study extends prior findings of an odor-specific hyposmia implicating cAMP-mediated signal transduction in schizophrenia and unaffected first-degree relatives to include youths at clinical risk for developing the disorder. These results suggest that dysregulation of cAMP signaling may be present during the psychosis prodrome.

The importance of knowing when to stop. A sequential stopping rule for component-wise gradient boosting

OBJECTIVES

Component-wise boosting algorithms have evolved into a popular estimation scheme in biomedical regression settings. The iteration number of these algorithms is the most important tuning parameter to optimize their performance. To date, no fully automated strategy for determining the optimal stopping iteration of boosting algorithms has been proposed.

METHODS

We propose a fully data-driven sequential stopping rule for boosting algorithms. It combines resampling methods with a modified version of an earlier stopping approach that depends on AIC-based information criteria. The new "subsampling after AIC" stopping rule is applied to component-wise gradient boosting algorithms.

RESULTS

The newly developed sequential stopping rule outperformed earlier approaches if applied to both simulated and real data. Specifically, it improved purely AIC-based methods when used for the microarray-based prediction of the recurrence of metastases for stage II colon cancer patients.

CONCLUSIONS

The proposed sequential stopping rule for boosting algorithms can help to identify the optimal stopping iteration already during the fitting process of the algorithm, at least for the most common loss functions.

Mutant mouse models in evaluating novel approaches to antipsychotic treatment

In this review we consider the application of mutant mouse phenotypes to the study of psychotic illness in general and schizophrenia in particular, as they relate to behavioral, psychopharmacological, and cellular phenotypes of putative import for antipsychotic drug development. Mutant models appear to be heuristic at two main levels; firstly, by indicating the functional roles of neuronal components thought to be of relevance to the putative pathobiology of psychotic illness, they help resolve overt behavioral and underlying cellular processes regulated by those neuronal components; secondly, by indicating the functional roles of genes associated with risk for psychotic illness, they help resolve overt behavioral and underlying cellular processes regulated by those risk genes. We focus initially on models of dopaminergic and glutamatergic dysfunction. Then, we consider advances in the genetics of schizophrenia and mutant models relating to replicable risk genes. Lastly, we extend this discussion by exemplifying two new variant approaches in mutant mice that may serve as prototypes for advancing antipsychotic drug development. There is continuing need not only to address numerous technical challenges but also to develop more "real-world" paradigms that reflect the milieu of gene × environment and gene × gene interactions that characterize psychotic illness and its response to antipsychotic drugs.