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Antipsychotics are the mainstay treatment for schizophrenia. There is large variability between individuals in their response to antipsychotics, both in efficacy and adverse effects of treatment. While the source of interindividual variability in antipsychotic response is not completely understood, genetics is a major contributing factor. The identification of pharmacogenetic markers that predict antipsychotic efficacy and adverse reactions is a growing area of research and holds the potential to replace the current trial-and-error approach to treatment selection in schizophrenia with a personalized medicine approach.In this chapter, we provide an overview of the current state of pharmacogenetics in schizophrenia treatment. The most promising pharmacogenetic findings are presented for both antipsychotic response and commonly studied adverse reactions. The application of pharmacogenetics to schizophrenia treatment is discussed, with an emphasis on the clinical utility of pharmacogenetic testing and directions for future research.

The complement system is a set of immune proteins involved in first-line defense against pathogens and removal of waste materials. Recent evidence has implicated the complement cascade in diseases involving the central nervous system, including schizophrenia. Here, we provide an up-to-date narrative review and critique of the literature on the relationship between schizophrenia and complement gene polymorphisms, gene expression, protein concentration, and pathway activity. A literature search identified 23 new studies since the first review on this topic in 2008. Overall complement pathway activity appears to be elevated in schizophrenia. Recent studies have identified complement component 4 (C4) and CUB and Sushi Multiple Domains 1 (CSMD1) as potential genetic markers of schizophrenia. In particular, there is some evidence of higher rates of C4B/C4S deficiency, reduced peripheral C4B concentration, and elevated brain C4A mRNA expression in schizophrenia patients compared to controls. To better elucidate the additive effects of multiple complement genotypes, we also conducted gene- and gene-set analysis through MAGMA which supported the role of Human Leukocyte Antigen class (HLA) III genes and, to a lesser extent, CSMD1 in schizophrenia; however, the HLA-schizophrenia association was likely driven by the C4 gene. Lastly, we identified several limitations of the literature on the complement system and schizophrenia, including: small sample sizes, inconsistent methodologies, limited measurements of neural concentrations of complement proteins, little exploration of the link between complement and schizophrenia phenotype, and lack of studies exploring schizophrenia treatment response. Overall, recent findings highlight complement components-in particular, C4 and CSMD1-as potential novel drug targets in schizophrenia. Given the growing availability of complement-targeted therapies, future clinical studies evaluating their efficacy in schizophrenia hold the potential to accelerate treatment advances.

BACKGROUND: The genetic risk factors of schizophrenia (SCZ), a severe psychiatric disorder, are not yet fully understood. Multiple lines of evidence suggest mitochondrial dysfunction may play a role in SCZ, but comprehensive association studies are lacking. We hypothesized that variants in nuclear-encoded mitochondrial genes influence susceptibility to SCZ. METHODS: We conducted gene-based and gene-set analyses using summary association results from the Schizophrenia Psychiatric Genomics Consortium GWAS (PGC-SCZ2) comprising 35,476 cases and 46,839 controls. We applied the MAGMA method to three sets of nuclear-encoded mitochondrial genes: oxidative phosphorylation genes, other nuclear-encoded mitochondrial genes, and genes involved in nucleus-mitochondria crosstalk. Furthermore, we conducted a replication study using the iPSYCH SCZ sample of 2,290 cases and 21,621 controls. RESULTS: In the PGC-SCZ2 sample, 1,186 mitochondrial genes were analyzed among which 159 had p-values

Several studies have indicated infectious and immune-related abnormalities in schizophrenia (Scz), including elevated serum C-reactive protein (CRP) - a well-known proxy for infections/immune abnormalities. A portion of the genetic risk for Scz can be estimated using the polygenic risk score (PGRS). It is not known whether there is an interaction in the risks traceable to CRP and PGRS. Patients with Scz and individuals without psychosis were evaluated systematically using DSM IV criteria (N=794, N=446, respectively). To estimate risk for Scz attributable to CRP and PGRS, serum from these participants was assayed for CRP levels using enzyme linked immunosorbent assays. PGRS was estimated from common DNA polymorphisms associated with Scz from genome wide association studies. CRP level and PGRS were not significantly correlated. Using a generalized linear logistic model, case/control status was evaluated in relation to the following predictors: CRP, PGRS, and demographic variables. CRP and PGRS were individually associated with case status; CRP: odds ratio (OR) 1.27, 95% confidence intervals (95% CI) 1.12, 1.43; p = 0.0001; PGRS: OR 1.66, 95% CI 1.47, 1.89; p = 1.28 ×10-15. There were no significant interactions between PGRS and CRP for predicting Scz versus control status.

BackgroundFamily history is a long-standing and readily obtainable risk factor for schizophrenia (SCZ). Low-cost genotyping technologies have enabled large genetic studies of SCZ, and the results suggest the utility of genetic risk scores (GRS, direct assessments of inherited common variant risk). Few studies have evaluated family history and GRS simultaneously to ask whether one can explain away the other.MethodsWe studied 5959 SCZ cases and 8717 controls from four Nordic countries. All subjects had family history data from national registers and genome-wide genotypes that were processed through the quality control procedures used by the Psychiatric Genomics Consortium. Using external training data, GRS were estimated for SCZ, bipolar disorder (BIP), major depression, autism, educational attainment, and body mass index. Multivariable modeling was used to estimate effect sizes.ResultsUsing harmonized genomic and national register data from Denmark, Estonia, Norway, and Sweden, we confirmed that family history of SCZ and GRS for SCZ and BIP were risk factors for SCZ. In a joint model, the effects of GRS for SCZ and BIP were essentially unchanged, and the effect of family history was attenuated but remained significant. The predictive capacity of a model including GRS and family history neared the minimum for clinical utility.ConclusionsCombining national register data with measured genetic risk factors represents an important investigative approach for psychotic disorders. Our findings suggest the potential clinical utility of combining GRS and family history for early prediction and diagnostic improvements.

A positive correlation between antipsychotic-induced weight gain (AIWG) and the antagonist effect of antipsychotic drugs at the histamine H1 receptor (HRH1) as well as the agonist effect at the histamine H3 receptor (HRH3) in the brain has been consistently demonstrated. We investigated the potential impact of single-nucleotide polymorphisms (SNPs) in HRH1 and HRH3 genes on AIWG.We analysed 40 tagSNPs in HRH1 (n = 34) and HRH3 (n = 6) in schizophrenia/schizoaffective disorder patients (n = 193) primarily treated with clozapine or olanzapine for up to 14 weeks. Linear regression was used to evaluate the association between SNPs and AIWG, with baseline weight and treatment duration as covariates.In HRH1, a nominal association of rs7639145 with AIWG was observed in patients of European ancestry treated with either clozapine or olanzapine (PThe current study suggests that SNPs in HRH1 and HRH3 may not have a major role in AIWG.

Many immune diseases occur at different rates among people with schizophrenia compared to the general population. Here, we evaluated whether this phenomenon might be explained by shared genetic risk factors. We used data from large genome-wide association studies to compare the genetic architecture of schizophrenia to 19 immune diseases. First, we evaluated the association with schizophrenia of 581 variants previously reported to be associated with immune diseases at genome-wide significance. We identified five variants with potentially pleiotropic effects. While colocalization analyses were inconclusive, functional characterization of these variants provided the strongest evidence for a model in which genetic variation at rs1734907 modulates risk of schizophrenia and Crohn’s disease via altered methylation and expression of EPHB4—a gene whose protein product guides the migration of neuronal axons in the brain and the migration of lymphocytes towards infected cells in the immune system. Next, we investigated genome-wide sharing of common variants between schizophrenia and immune diseases using cross-trait LD score regression. Of the 11 immune diseases with available genome-wide summary statistics, we observed genetic correlation between six immune diseases and schizophrenia: inflammatory bowel disease (rg = 0.12 ± 0.03, P = 2.49 × 10−4), Crohn’s disease (rg = 0.097 ± 0.06, P = 3.27 × 10−3), ulcerative colitis (rg = 0.11 ± 0.04, P = 4.05 × 10–3), primary biliary cirrhosis (rg = 0.13 ± 0.05, P = 3.98 × 10−3), psoriasis (rg = 0.18 ± 0.07, P = 7.78 × 10–3) and systemic lupus erythematosus (rg = 0.13 ± 0.05, P = 3.76 × 10–3). With the exception of ulcerative colitis, the degree and direction of these genetic correlations were consistent with the expected phenotypic correlation based on epidemiological data. Our findings suggest shared genetic risk factors contribute to the epidemiological association of certain immune diseases and schizophrenia., This research was supported in part by a number of funding sources. This research uses resources provided by the Genetic Association Information Network (GAIN), obtained from the database of Genotypes and Phenotypes (dbGaP) found at http://www.ncbi.nlm.nih.gov/gap through dbGaP accession number phs000021.v3.p2; samples and associated phenotype data for this study were provided by the Molecular Genetics of Schizophrenia Collaboration (PI: Pablo V. Gejman, Evanston Northwestern Healthcare and Northwestern University, Evanston, IL, USA). Fulbright Canada, the Weston Foundation, and Brain Canada through the Canada Brain Research Fund—a public-private partnership established by the Government of Canada (to J.G.P.); the National Research Foundation of Korea (NRF) [grant 2016R1C1B2013126 to B.H.] and the Bio & Medical Technology Development Program of the NRF [grant 2017M3A9B6061852 to B.H.] funded by the Korean government, Ministry of Science and ICT; the Finnish Cultural Foundation and Academy of Finland [grant 309643 to H.M.O.]; the Spanish Ministry of Economy and Competitiveness and P12-BIO-1395 from Consejería de Innovación, Ciencia y Tecnología, Junta de Andalucía (Spain) [grant SAF2015-66761-P to J.M.]; the US National Institutes of Health (NIH) [grants R01AR045584, R01AR056292, X01HG007484 and P30AR057212 to Y.J., S.A.S. and R.S.]; the US NIH [grants N01AR02251 and R01AR05528 to M.D.M.]; the US NIH [grants 1R01AR063759, 1R01AR062886, 1UH2AR067677-01 and U19AI111224-01 to S.R.] and Doris Duke Charitable Foundation [grant 2013097 to S.R.]. Funding for the GAIN schizophrenia sample was provided by the US NIH [grants R01 MH67257, R01 MH59588, R01 MH59571, R01 MH59565, R01 MH59587, R01 MH60870, R01 MH59566, R01 MH59586, R01 MH61675, R01 MH60879, R01 MH81800, U01 MH46276, U01 MH46289, U01 MH46318, U01 MH79469 and U01 MH79470] and the genotyping of samples was provided through GAIN. The funding sources did not influence the study design, data analysis or writing of this manuscript.

The XXIIIrd World Congress of Psychiatric Genetics (WCPG) meeting, sponsored by the International Society of Psychiatric Genetics (ISPG), was held in Toronto, ON, Canada, on October 16-20, 2015. Approximately 700 participants attended to discuss the latest state-of-the-art findings in this rapidly advancing and evolving field. The following report was written by trainee travel awardees. Each was assigned one session as a rapporteur. This manuscript represents the highlights and topics that were covered in the plenary sessions, symposia, and oral sessions during the conference, and contains major notable and new findings.

Schizophrenia is a severe psychiatric disorder of complex etiology. Immune processes have long been proposed to contribute to the development of schizophrenia, and accumulating evidence supports immune involvement in at least a subset of cases. In recent years, large-scale genetic studies have provided new insights into the role of the immune system in this disease. Here, we provide an overview of the immunogenetic architecture of schizophrenia based on findings from genome-wide association studies (GWAS). First, we review individual immune loci identified in secondary analyses of GWAS, which implicate over 30 genes expressed in both immune and brain cells. The function of the proteins encoded by these immune candidates highlight the role of the complement system, along with regulation of apoptosis in both immune and neuronal cells. Next, we review hypothesis-free pathway analyses which have so far been inconclusive with respect to identifying immune pathways involved in schizophrenia. Finally, we explore the genetic overlap between schizophrenia and immune-mediated diseases. Although there have been some inconsistencies across studies, genome-wide pleiotropy has been reported between schizophrenia and Crohn's disease, multiple sclerosis, rheumatoid arthritis, systemic lupus erythematosus, type 1 diabetes, and ulcerative colitis. Overall, there are multiple lines of evidence supporting the role of immune genes in schizophrenia. Current evidence suggests that specific immune pathways are involved-likely those with dual functions in the central nervous system. Future studies focused on further elucidating the relevant pathways hold the potential to identify novel biomarkers and therapeutic targets for schizophrenia.

Background Schizophrenia (SCZ) is a severe psychiatric disorder wherein the genetic risk factors are far from being fully understood. Multiple lines of evidence have suggested mitochondrial dysfunction in SCZ, but association of mitochondrial variants with SCZ has not been extensively investigated. Methods We conducted gene-based and gene-set analyses to test the hypothesis that variants in nuclear-encoded mitochondrial genes influence susceptibility to SCZ, using results from the most recent release of the Schizophrenia Psychiatric Genomics Consortium GWAS (35,476 cases and 46,839 controls). We applied the MAGMA statistical tool to three gene sets: oxidative phosphorylation genes, other nuclear-encoded mitochondrial genes, and genes involved in nucleus-mitochondria communication signaling. Results For gene-based analysis, a total of 1,187 mitochondrial genes were analyzed and 19 were significant after correction for multiple testing. We applied the method for an independent sample (iPSYCH study, 2,290 SCZ cases and 21,621 controls) and 12 genes had replication p-values Discussion Overall, our study showed evidence that mitochondria play a role in SCZ. Results from our study, combined with future availability of mitochondrial DNA data, will assist researchers to evaluate the role of mitochondrial genomics, potentially across all complex genetic disorders.

Antipsychotic medications are the gold-standard treatment for schizophrenia, and are often prescribed for other mental conditions. However, the efficacy and side-effect profiles of these drugs are heterogeneous, with large interindividual variability. As a result, treatment selection remains a largely trial-and-error process, with many failed treatment regimens endured before finding a tolerable balance between symptom management and side effects. Much of the interindividual variability in response and side effects is due to genetic factors (heritability, h(2)~ 0.60-0.80). Pharmacogenetics is an emerging field that holds the potential to facilitate the selection of the best medication for a particular patient, based on his or her genetic information. In this review we discuss the most promising genetic markers of antipsychotic treatment outcomes, and present current translational research efforts that aim to bring these pharmacogenetic findings to the clinic in the near future.

There has been intense debate over the immunological basis of schizophrenia, and the potential utility of adjunct immunotherapies. The major histocompatibility complex is consistently the most powerful region of association in genome-wide association studies (GWASs) of schizophrenia and has been interpreted as strong genetic evidence supporting the immune hypothesis. However, global pathway analyses provide inconsistent evidence of immune involvement in schizophrenia, and it remains unclear whether genetic data support an immune etiology per se. Here we empirically test the hypothesis that variation in immune genes contributes to schizophrenia. We show that there is no enrichment of immune loci outside of the MHC region in the largest genetic study of schizophrenia conducted to date, in contrast to 5 diseases of known immune origin. Among 108 regions of the genome previously associated with schizophrenia, we identify 6 immune candidates (DPP4, HSPD1, EGR1, CLU, ESAM, NFATC3) encoding proteins with alternative, nonimmune roles in the brain. While our findings do not refute evidence that has accumulated in support of the immune hypothesis, they suggest that genetically mediated alterations in immune function may not play a major role in schizophrenia susceptibility. Instead, there may be a role for pleiotropic effects of a small number of immune genes that also regulate brain development and plasticity. Whether immune alterations drive schizophrenia progression is an important question to be addressed by future research, especially in light of the growing interest in applying immunotherapies in schizophrenia.

There is growing evidence of shared risk alleles for complex traits (pleiotropy), including autoimmune and neuropsychiatric diseases. This might be due to sharing among all individuals (whole-group pleiotropy) or a subset of individuals in a genetically heterogeneous cohort (subgroup heterogeneity). Here we describe the use of a well-powered statistic, BUHMBOX, to distinguish between those two situations using genotype data. We observed a shared genetic basis for 11 autoimmune diseases and type 1 diabetes (T1D; P1 × 10(-4)) and for 11 autoimmune diseases and rheumatoid arthritis (RA; P1 × 10(-3)). This sharing was not explained by subgroup heterogeneity (corrected PBUHMBOX0.2; 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (P1 × 10(-9)) had significant evidence of subgroup heterogeneity, suggesting a subgroup of seropositive-like cases within seronegative cases (PBUHMBOX = 0.008; 2,406 seronegative RA cases). We also observed a shared genetic basis for major depressive disorder (MDD) and schizophrenia (P1 × 10(-4)) that was not explained by subgroup heterogeneity (PBUHMBOX = 0.28; 9,238 MDD cases).

SLC6A3, which encodes the primary regulator of extracellular dopamine (DA) concentration, the DA transporter, has been implicated in schizophrenia (SCZ). However, the details of its genetic effect on risk remain largely unknown. The purpose of this candidate gene study was to identify a specific SLC6A3 activity associated with SCZ by using functional genetic approaches. We first examined gene activity in DA neurons isolated from case-control postmortem nigral tissue and found that the average SLC6A3 mRNA level in controls was only 0.37-fold of that in cases (P = .0034). To understand this expression difference, we examined the association of 10 genetic markers, mostly located in the promoter region, with SCZ in 1717 subjects collected from Toronto and McLean cohorts, including 881 controls and 836 cases and identified the 5′ promoter SNP rs1478435 as having a significant association signal (uncorrected P value: .00462; adjusted P value: .0319) in unrelated Caucasians. Allele T was over-represented in controls (OR = .75); T-carrier controls had decreased mRNA levels in nigral DA neurons, contributing to the reduced activity in the controls. In vitro functional analysis confirmed that T carriers displayed attenuated enhancement of promoter activity. These findings collectively suggest that increased nigral SLC6A3 activity may be a risk factor for SCZ, and may help to explain high rates of comorbidity with substance abuse.

Shared genetic architecture between phenotypes may be driven by a common genetic basis (pleiotropy) or a subset of genetically similar individuals (heterogeneity). We developed BUHMBOX, a well-powered statistical method to distinguish pleiotropy from heterogeneity using genotype data. We observed a shared genetic basis between 11 of 17 tested autoimmune diseases and type I diabetes (T1D, p0.2 using 6,670 T1D cases and 7,279 RA cases), suggesting that shared genetic features in autoimmunity are due to pleiotropy. We observed a shared genetic basis between seronegative and seropostive RA (p

Antipsychotic medications are the gold-standard treatment for schizophrenia, and are often prescribed for other mental conditions. However, the efficacy and side-effect profiles of these drugs are heterogeneous, with large interindividual variability. As a result, treatment selection remains a largely trial-and-error process, with many failed treatment regimens endured before finding a tolerable balance between symptom management and side effects. Much of the interindividual variability in response and side effects is due to genetic factors (heritability, h(2)~ 0.60-0.80). Pharmacogenetics is an emerging field that holds the potential to facilitate the selection of the best medication for a particular patient, based on his or her genetic information. In this review we discuss the most promising genetic markers of antipsychotic treatment outcomes, and present current translational research efforts that aim to bring these pharmacogenetic findings to the clinic in the near future.Los antípsicóticos son los medícamentos utilizados como gold standard para el tratamiento de la esquizofrenía y además se emplean con frecuencia para otros trastornos mentales. Sin embargo, los perfiles de eficacia y efectos secundarios de estos fármacos son heterogéneos y con gran varíabílidad ínterindividual. A raíz de esto, la selección del tratamiento sígue siendo un largo proceso de ensayo-error, con muchas fallas terapéuticas que se deben soportar antes de encontrar un balance aceptable entre el manejo sintomático y los efectos secundarios. Mucha de la varíabílidad ínterindividual en la respuesta y los efectos secundarios se debe a factores genéticos (heredabilidad, hLes médicaments antipsychotiques, traitement de référence pour la schizophrénie, sont souvent prescrits pour d'autres maladies mentales. Néanmoins, leur efficacité et leurs effets indésirables sont hétérogenes, avec une grande variabilité selon les individus. En conséquence, le choix du traitement procède en grande partie par tâtonnements, beaucoup de schémas thérapeutiques échouant avant que soit trouvé un rapport correct entre les effets sur les symptômes et les effets indésirables. Des facteurs génétiques sont responsables de la majeure partie de la variabilité interindividuelle dans les réponses au traitement et les effets indésirables (héritabilité, h

Aim: TSPO is a neuroinflammatory biomarker and emerging therapeutic target in psychiatric disorders. We evaluated whether TSPO polymorphisms contribute to interindividual variability in schizophrenia, antipsychotic efficacy and antipsychotic-induced weight gain. Patients & methods: We analyzed TSPO polymorphisms in 670 schizophrenia cases and 775 healthy controls. Gene–gene interactions between TSPO and other mitochondrial membrane protein-encoding genes (VDAC1 and ANT1) were explored. Positive findings were evaluated in two independent samples (Munich, n = 300; RUPP, n = 119). Results: TSPO rs6971 was independently associated with antipsychotic-induced weight gain in the discovery (puncor = 0.04) and RUPP samples (p = 3.00 × 10-3), and interacted with ANT1 rs10024068 in the discovery (p = 1.15 × 10-3) and RUPP samples (p = 2.76 × 10-4). Conclusion: Our findings highlight TSPO as a candidate for future investigations of antipsychotic-induced weight gain, and support the involvement of mitochondrial membrane components in this serious treatment side effect. Original submitted 20 August 2014; Revision submitted 3 November 2014

Antipsychotics are the mainstay treatment for schizophrenia. There is large variability between individuals in their response to antipsychotics, both in efficacy and adverse effects of treatment. While the source of interindividual variability in antipsychotic response is not completely understood, genetics is a major contributing factor. The identification of pharmacogenetic markers that predict antipsychotic efficacy and adverse reactions is a growing area of research, and holds the potential to replace the current trial-and-error approach to treatment selection in schizophrenia with a personalized medicine approach.In this chapter, we provide an overview of the current state of pharmacogenetics in schizophrenia treatment. The most promising pharmacogenetic findings are presented for both antipsychotic response and commonly studied adverse reactions. The application of pharmacogenetics to schizophrenia treatment is discussed, with an emphasis on the clinical utility of pharmacogenetic testing and directions for future research.

Antipsychotics are the mainstay treatment for schizophrenia. There is large variability between individuals in their response to antipsychotics, both in efficacy and adverse effects of treatment. While the source of interindividual variability in antipsychotic response is not completely understood, genetics is a major contributing factor. The identification of pharmacogenetic markers that predict antipsychotic efficacy and adverse reactions is a growing area of research, and holds the potential to replace the current trial-and-error approach to treatment selection in schizophrenia with a personalized medicine approach.In this chapter, we provide an overview of the current state of pharmacogenetics in schizophrenia treatment. The most promising pharmacogenetic findings are presented for both antipsychotic response and commonly studied adverse reactions. The application of pharmacogenetics to schizophrenia treatment is discussed, with an emphasis on the clinical utility of pharmacogenetic testing and directions for future research.

Video presentation can be accessed here . Background and purpose : Antipsychotics (APs) are the primary method of treatment for schizophrenia and other psychotic disorders. Unfortunately, lengthy trial-and-error approaches are typically required to find the optimal medication and dosage due to a large interindividual variability with outcome to AP treatment. The literature has shown abundant evidence for a genetic component in individuals’ responses to APs. Pharmacogenetic studies analyze specific genetic markers and their association with symptom improvement and occurrence of side effects with APs. This research aims to optimize AP drug treatment by usage of predictive testing and to personalize medicine. Recent findings : This review will highlight the most consistent findings in pharmacogenetics of APs and will update the reader on the clinical implications. This will include how genetic variants modulate AP drug levels, side effects, and therapeutic symptom improvement (i.e. response) to AP treatment. Summary : Several promising findings were obtained implicating gene variants of the dopamine receptor genes in addition to gene variants of serotonin receptors for response and common side effects. Notably, effect sizes appear to be particularly high in the genetics of side effects compared to response. One example is antipsychotic-induced weight gain where the leptin, HTR2C and in particular the melanocortin-4-receptor ( MC4R ) genes have been implicated in weight gain in children and adolescents. Consistent findings were also obtained for genes implicated in tardive dyskinesia and agranulocytosis. However, the most clinically relevant findings pertain to genes involved in drug metabolism such as the CYP2D6 and CYP2C19 genes which have been included in the first genetic test kits such as the Amplichip ® CYP450 Test and more recently the DMET™ Plus Panel, the Genecept™ Assay, the Genomas HILOmet PhyzioType™ System, and the GeneSight ® Test. Keywords : pharmacogenetics; antipsychotics; response; side effects; CYP450 (Published: 18 July 2014) Citation: Translational Developmental Psychiatry 2014, 2 : 24663 - http://dx.doi.org/10.3402/tdp.v2.24663 A Corrigendum has been published for this paper. Please see http://www.translationaldevelopmentalpsychiatry.net/coaction/index.php/tdp/article/view/25715