Candidate CSPG4 mutations and induced pluripotent stem cell modeling implicate oligodendrocyte progenitor cell dysfunction in familial schizophrenia

Schizophrenia is highly heritable, yet its underlying pathophysiology remains largely unknown. Among the most well-replicated findings in neurobiological studies of schizophrenia are deficits in myelination and white matter integrity; however, direct etiological genetic and cellular evidence has thus far been lacking. Here, we implement a family-based approach for genetic discovery in schizophrenia combined with functional analysis using induced pluripotent stem cells (iPSCs). We observed familial segregation of two rare missense mutations in Chondroitin Sulfate Proteoglycan 4 (CSPG4) (c.391G > A [p.A131T], MAF 7.79 × 10−5 and c.2702T > G [p.V901G], MAF 2.51 × 10−3). The CSPG4A131T mutation was absent from the Swedish Schizophrenia Exome Sequencing Study (2536 cases, 2543 controls), while the CSPG4V901G mutation was nominally enriched in cases (11 cases vs. 3 controls, P = 0.026, OR 3.77, 95% CI 1.05–13.52). CSPG4/NG2 is a hallmark protein of oligodendrocyte progenitor cells (OPCs). iPSC-derived OPCs from CSPG4A131T mutation carriers exhibited abnormal post-translational processing (P = 0.029), subcellular localization of mutant NG2 (P = 0.007), as well as aberrant cellular morphology (P = 3.0 × 10−8), viability (P = 8.9 × 10−7), and myelination potential (P = 0.038). Moreover, transfection of healthy non-carrier sibling OPCs confirmed a pathogenic effect on cell survival of both the CSPG4A131T (P = 0.006) and CSPG4V901G (P = 3.4 × 10−4) mutations. Finally, in vivo diffusion tensor imaging of CSPG4A131T mutation carriers demonstrated a reduction of brain white matter integrity compared to unaffected sibling and matched general population controls (P = 2.2 × 10−5). Together, our findings provide a convergence of genetic and functional evidence to implicate OPC dysfunction as a candidate pathophysiological mechanism of familial schizophrenia

Social brain, social dysfunction and social withdrawal

The human social brain is complex. Current knowledge fails to define the neurobiological processes underlying social behaviour involving the (patho-) physiological mechanisms that link system-level phenomena to the multiple hierarchies of brain function. Unfortunately, such a high complexity may also be associated with a high susceptibility to several pathogenic interventions. Consistently, social deficits sometimes represent the first signs of a number of neuropsychiatric disorders including schizophrenia (SCZ), Alzheimer's disease (AD) and major depressive disorder (MDD) which leads to a progressive social dysfunction. In the present review we summarize present knowledge linking neurobiological substrates sustaining social functioning, social dysfunction and social withdrawal in major psychiatric disorders. Interestingly, AD, SCZ, and MDD affect the social brain in similar ways. Thus, social dysfunction and its most evident clinical expression (i.e., social withdrawal) may represent an innovative transdiagnostic domain, with the potential of being an independent entity in terms of biological roots, with the perspective of targeted interventions

Structural genomic abnormalities in autism and schizophrenia. With a focus on the 22q11.2 deletion syndrome

The research presented in this thesis is centered around one question: What can we learn from the study of psychiatric phenotypes related to structural genomic abnormalities? In this thesis this subject is examined, with most studies focused on the clinical and genetic aspects of the 22q11.2 deletion syndrome. In chapter 1 a review of all published case-reports on individuals with autism and a concurrent structural genetic abnormality is presented. In chapter 2 findings are presented of a study on the psychiatric phenotype of 22q11DS. In a sample of 60 Dutch children aged with 22q11DS, 50% were diagnosed with an autism spectrum disorder, 12% were diagnosed with a psychotic disorder and 8% were found to have a mood disorder. In chapter 3 the test characteristics of a novel method for the detection of copy number changes, Multiplex Ligation-dependent Probe Amplification (MLPA), are reported. The results demonstrate that MLPA reliably identifies typical and atypical 22q11.2 copy number changes. The sensitivity and specificity of MLPA were 0.99 and 0.97, respectively. However, there were still rare structural genomic abnormalities that would not have been detected by the available MLPA kit,therefore, an effort was made to develop a new MLPA set with an increased density of probes across the 22q11.2 region. The results of this effort are reported in chapter 4. In chapter 5 the MLPA method was used to screen a sample of 311 Dutch patients with schizophrenia for the presence of 22q11.2 deletions. The sample included 146 patients with prominent negative symptoms (deficit schizophrenia). The hypothesis of an increased prevalence of 22q11.2 deletions in this subgroup was not confirmed; indeed none of the 311 patients was found to have a deletion at 22q11.2. In chapter 6 a significant interaction between high plasma proline and the COMTmet allele on a neurophysiologic test paradigm; Smooth Pursuit of the Eye Movement is demonstrated in a sample of children with 22q11DS, In chapter 7 a significant interaction is presented between a previously reported schizophrenia-risk allele of the gene PIK4CA and schizophrenia. The PIK4CA risk allele was significantly more present in a group of adult 22q11DS patients with schizophrenia in comparison to adult 22q11DS patients without schizophrenia. In chapter 8 the clinical and molecular genetic findings are reported concerning a normally intelligent proband with autism who was found to carry a maternally inherited large deletion (~10Mb) of chromosome 13q. Because his mother was not affected with autism, it was hypothesized that the proband could have a functional mutation in a remaining allele of one of the genes located in the deleted region. The results from the sequencing studies confirmed this “double hit” hypothesis; the proband carried a paternally inherited non-synonymous point mutation in DIAPH3, one of the genes in the region affected by the maternally inherited deletion. In conclusion, results of the presented research favor the view that studying psychiatric phenotypes associated with structural genomic abnormalities may generate valuable information about the genetic, and thus the biological factors that lead to psychiatric disorders, such as autism and schizophrenia

Influence of the context of learning a language on the strategic competence of children

The present study was set up to evaluate the extent to which the context in which a foreign language is learned can influence the strategic competence of children. To assess this we conducted a series of think aloud protocols with 101 children. We compared children who have learned an additional language in a formal context (abbreviated LLE, i.e. Language Learning Experience) to those who have acquired two languages in a non-formal context and before the age of 4 (i.e. ‘simultaneous bilingual’ children, abbreviated nLLE, i.e. without a Language Learning Experience). The primary outcome measure consisted of the children’s reactions to situations of communication where they could not understand the language. We hypothesized that LLE children would outperform nLLE children in their awareness of and willingness to use communicative strategies. We found that LLE children accessed more strategies and diversified their strategies more often. These findings are in line with our previous findings and indicate that LLE is a highly relevant factor when studying the strategic competence of children

Untargeted metabolic analysis in dried blood spots reveals metabolic signature in 22q11.2 deletion syndrome

Contains fulltext : 252344.pdf (Publisher’s version ) (Open Access)The 22q11.2 deletion syndrome (22q11.2DS) is characterized by a well-defined microdeletion and is associated with increased risk of neurodevelopmental phenotypes including autism spectrum disorders (ASD) and intellectual impairment. The typically deleted region in 22q11.2DS contains multiple genes with the potential of altering metabolism. Deficits in metabolic processes during early brain development may help explain the increased prevalence of neurodevelopmental phenotypes seen in 22q11.2DS. However, relatively little is known about the metabolic impact of the 22q11.2 deletion, while such insight may lead to increased understanding of the etiology. We performed untargeted metabolic analysis in a large sample of dried blood spots derived from 49 22q11.2DS patients and 87 controls, to identify a metabolic signature for 22q11.2DS. We also examined trait-specific metabolomic patterns within 22q11.2DS patients, focusing on intelligence (intelligence quotient, IQ) and ASD. We used the Boruta algorithm to select metabolites distinguishing patients from controls, patients with ASD from patients without, and patients with an IQ score in the lowest range from patients with an IQ score in the highest range. The relevance of the selected metabolites was visualized with principal component score plots, after which random forest analysis and logistic regression were used to measure predictive performance of the selected metabolites. Analysis yielded a distinct metabolic signature for 22q11.2DS as compared to controls, and trait-specific (IQ and ASD) metabolomic patterns within 22q11.2DS patients. The metabolic characteristics of 22q11.2DS provide insights in biological mechanisms underlying the neurodevelopmental phenotype and may ultimately aid in identifying novel therapeutic targets for patients with developmental disorders

A normative chart for cognitive development in a genetically selected population

Certain pathogenic genetic variants impact neurodevelopment and cause deviations from typical cognitive trajectories. Understanding variant-specific cognitive trajectories is clinically important for informed monitoring and identifying patients at risk for comorbid conditions. Here, we demonstrate a variant-specific normative chart for cognitive development for individuals with 22q11.2 deletion syndrome (22q11DS). We used IQ data from 1365 individuals with 22q11DS to construct variant-specific normative charts for cognitive development (Full Scale, Verbal, and Performance IQ). This allowed us to calculate Z-scores for each IQ datapoint. Then, we calculated the change between first and last available IQ assessments (delta Z-IQ-scores) for each individual with longitudinal IQ data (n = 708). We subsequently investigated whether using the variant-specific IQ-Z-scores would decrease required sample size to detect an effect with schizophrenia risk, as compared to standard IQ-scores. The mean Z-IQ-scores for FSIQ, VIQ, and PIQ were close to 0, indicating that participants had IQ-scores as predicted by the normative chart. The mean delta-Z-IQ-scores were equally close to 0, demonstrating a good fit of the normative chart and indicating that, as a group, individuals with 22q11DS show a decline in IQ-scores as they grow into adulthood. Using variant-specific IQ-Z-scores resulted in 30% decrease of required sample size, as compared to the standard IQ-based approach, to detect the association between IQ-decline and schizophrenia (p < 0.01). Our findings suggest that using variant-specific normative IQ data significantly reduces required sample size in a research context, and may facilitate a more clinically informative interpretation of IQ data. This approach allows identification of individuals that deviate from their expected, variant-specific, trajectory. This group may be at increased risk for comorbid conditions, such as schizophrenia in the case of 22q11DS

A framework for assessing neuropsychiatric phenotypes by using smartphone-based location data

The use of smartphone-based location data to quantify behavior longitudinally and passively is rapidly gaining traction in neuropsychiatric research. However, a standardized and validated preprocessing framework for deriving behavioral phenotypes from smartphone-based location data is currently lacking. Here, we present a preprocessing framework consisting of methods that are validated in the context of geospatial data. This framework aims to generate context-enriched location data by identifying stationary, non-stationary, and recurrent stationary states in movement patterns. Subsequently, this context-enriched data is used to derive a series of behavioral phenotypes that are related to movement. By using smartphone-based location data collected from 245 subjects, including patients with schizophrenia, we show that the proposed framework is effective and accurate in generating context-enriched location data. This data was subsequently used to derive behavioral readouts that were sensitive in detecting behavioral nuances related to schizophrenia and aging, such as the time spent at home and the number of unique places visited. Overall, our results indicate that the proposed framework reliabl