Seasonality shows evidence for polygenic architecture and genetic correlation with schizophrenia and bipolar disorder

Seasonality of brain function: role in psychiatric disorders

Seasonality patterns are reported in various psychiatric disorders. The current paper summarizes findings on brain adaptations associated with seasonal changes, factors that contribute to individual differences and their implications for psychiatric disorders. Changes in circadian rhythms are likely to prominently mediate these seasonal effects since light strongly entrains the internal clock modifying brain function. Inability of circadian rhythms to accommodate to seasonal changes might increase the risk for mood and behavior problems as well as worse clinical outcomes in psychiatric disorders. Understanding the mechanisms that account for inter-individual variations in seasonality is relevant to the development of individualized prevention and treatment for psychiatric disorders. Despite promising findings, seasonal effects are still understudied and only controlled as a covariate in most brain research. Rigorous neuroimaging studies with thoughtful experimental designs, powered sample sizes and high temporal resolution alongside deep characterization of the environment are needed to better understand the seasonal adaptions of the human brain as a function of age, sex, and geographic latitude and to investigate the mechanisms underlying the alterations in seasonal adaptation in psychiatric disorders.

Seasonality of hospitalization for schizophrenia and mood disorders: A single-center cross-sectional study in China

BACKGROUND

Seasonal patterns exist in many disorders and even serve as potential drivers of some disorders, but in schizophrenia and affective disorders, there is no uniform conclusion on the seasonal pattern.

METHODS

A total of 100,621 inpatients were surveyed in this study over 16 years, and 21,668 inpatients were ultimately included in the count after standard exclusion criteria were applied.

RESULTS

There was an uneven seasonal distribution of mental illness admissions (χ2 = 48.299, df = 18, P < .001). The peak of schizophrenia admissions occurred in the winter and the trough in the spring (52.6 % vs 50 %, P < .05). The peaks for depression and bipolar disorder were in the fall and spring, respectively, while the troughs were in the winter and fall, respectively (24.7 % vs 21.7 %, P < .05; 15.2 % vs 13.2 %, P < .05). Admissions for childhood mood disorders peaked in the fall (P < .05). We also found that the length of stay was also correlated with the season of admission, and that this seasonal fluctuation was not consistent across male and female populations.

LIMITATIONS

To avoid the effect of repeated hospitalizations, we maintained a registry of each patient's first admission only, which also resulted in our inability to explore the seasonal pattern of each disease recurrence at the individual level.

CONCLUSIONS

We found that the seasonal distribution of psychiatric admissions was not uniform. And there was also an uneven seasonal distribution of length of stay for patients admitted in different seasons. This may imply that certain environmental factors that vary with the seasons are potential drivers of mental illness.

A Nile rat transcriptomic landscape across 22 organs by ultra-deep sequencing and comparative RNA-seq pipeline (CRSP)

RNA sequencing (RNA-seq) has been a widely used high-throughput method to characterize transcriptomic dynamics spatiotemporally. However, RNA-seq data analysis pipelines typically depend on either a sequenced genome and/or corresponding reference transcripts. This limitation is a challenge for species lacking sequenced genomes and corresponding reference transcripts. The Nile rat (Arvicanthis niloticus) has two key features - it is daytime active, and it is prone to diet-induced diabetes, which makes it more similar to humans than regular laboratory rodents. However, at the time of this study, neither a Nile rat genome nor a reference transcript set were available, making it technically challenging to perform large-scale RNA-seq based transcriptomic studies. This genome-independent work progressed concurrently with our generation of a Nile rat genome. A well-annotated genome requires several iterations of manually reviewing curated transcripts and takes years to achieve. Here, we developed a Comparative RNA-Seq Pipeline (CRSP), integrating a comparative species strategy independent of a specific sequenced genome or species-matched reference transcripts. We performed benchmarking to validate that our CRSP tool can accurately quantify gene expression levels. In this study, we generated the first ultra-deep (2.3 billion × 2 paired-end) Nile rat RNA-seq data from 59 biopsy samples representing 22 major organs, providing a unique resource and spatial gene expression reference for Nile rat researchers. Importantly, CRSP is not limited to the Nile rat species and can be applied to any species without prior genomic knowledge. To facilitate a general use of CRSP, we also characterized the number of RNA-seq reads required for accurate estimation via simulation studies. CRSP and documents are available at: https://github.com/pjiang1105/CRSP.

Cohort profile: the Swedish National Quality Register for bipolar disorder(BipoläR)

PURPOSE

The Swedish National Quality Register for bipolar affective disorder, BipoläR, was established in 2004 to provide nationwide indicators for quality assessment and development in the clinical care of individuals with bipolar spectrum disorder. An ancillary aim was to provide data for bipolar disorder research.

PARTICIPANTS

Inclusion criteria for registration in BipoläR is a diagnosis of bipolar spectrum disorder (ICD codes: F25.0, F30.1-F30.2, F30.8-F31.9, F34.0) and treatment at an outpatient clinic in Sweden. BipoläR collects data from baseline and annual follow-up visits throughout Sweden. Data is collected using questionnaires administered by healthcare staff. The questions cover sociodemographic, diagnostic, treatment, outcomes and patient reported outcome variables. The register currently includes 39 583 individual patients with a total of 75 423 baseline and follow-up records.

FINDINGS TO DATE

Data from BipoläR has been used in several peer-reviewed publications. Studies have provided knowledge on effectiveness, side effects and use of pharmacological and psychological treatment in bipolar disorder. In addition, findings on the diagnosis of bipolar disorder, risk factors for attempted and completed suicide and health economics have been reported. The Swedish Bipolar Collection project has contributed to a large number of published studies and provides important information on the genetic architecture of bipolar disorder, the impact of genetic variation on disease characteristics and treatment outcome.

FUTURE PLANS

Data collection is ongoing with no fixed end date. Currently, approximately 5000 new registrations are added each year. Cohort data are available via a formalised request procedure from Centre of Registers Västra Götaland (e-mail: registercentrum@vgregion.se). Data requests for research purposes require an entity responsible for the research and an ethical approval.

The Australian Genetics of Depression Study: New Risk Loci and Dissecting Heterogeneity Between Subtypes

BACKGROUND

Major depressive disorder (MDD) is a common and highly heterogeneous psychiatric disorder, but little is known about the genetic characterization of this heterogeneity. Understanding the genetic etiology of MDD can be challenging because large sample sizes are needed for gene discovery-often achieved with a trade-off in the depth of phenotyping.

METHODS

The Australian Genetics of Depression Study is the largest stand-alone depression cohort with both genetic data and in-depth phenotyping and comprises a total of 15,792 participants of European ancestry, 92% of whom met diagnostic criteria for MDD. We leveraged the unique nature of this cohort to conduct a meta-analysis with the largest publicly available depression genome-wide association study to date and subsequently used polygenic scores to investigate genetic heterogeneity across various clinical subtypes of MDD.

RESULTS

We increased the number of known genome-wide significant variants associated with depression from 103 to 126 and found evidence of association of novel genes implicated in neuronal development. We found that a polygenic score for depression explained 5.7% of variance in MDD liability in our sample. Finally, we found strong support for genetic heterogeneity in depression with differential associations of multiple psychiatric and comorbid traits with age of onset, longitudinal course, and various subtypes of MDD.

CONCLUSIONS

Until now, this degree of detailed phenotyping in such a large sample of MDD cases has not been possible. Along with the discovery of novel loci, we provide support for differential pathways to illness models that recognize the overlap with other common psychiatric disorders as well as pathophysiological differences.

The darkness and the light: diurnal rodent models for seasonal affective disorder

The development of animal models is a critical step for exploring the underlying pathophysiological mechanisms of major affective disorders and for evaluating potential therapeutic approaches. Although most neuropsychiatric research is performed on nocturnal rodents, differences in how diurnal and nocturnal animals respond to changing photoperiods, combined with a possible link between circadian rhythm disruption and affective disorders, has led to a call for the development of diurnal animal models. The need for diurnal models is most clear for seasonal affective disorder (SAD), a widespread recurrent depressive disorder that is linked to exposure to short photoperiods. Here, we briefly review what is known regarding the etiology of SAD and then examine progress in developing appropriate diurnal rodent models. Although circadian disruption is often invoked as a key contributor to SAD, a mechanistic understanding of how misalignment between endogenous circadian physiology and daily environmental rhythms affects mood is lacking. Diurnal rodents show promise as models of SAD, as changes in affective-like behaviors are induced in response to short photoperiods or dim-light conditions, and symptoms can be ameliorated by brief exposure to intervals of bright light coincident with activity onset. One exciting avenue of research involves the orexinergic system, which regulates functions that are disturbed in SAD, including sleep cycles, the reward system, feeding behavior, monoaminergic neurotransmission and hippocampal neurogenesis. However, although diurnal models make intuitive sense for the study of SAD and are more likely to mimic circadian disruption, their utility is currently hampered by a lack of genomic resources needed for the molecular interrogation of potential mechanisms.

Impact of Season of Birth on Psychiatric Disorder Susceptibility and Drug Abuse Incidence in a Population from the Köppen Tropical Savanna Region of Brazil

BACKGROUND

Despite much evidence that season of birth (SOB) my influence the vulnerability to psychiatric disorders, divergence has been reported, in particular between populations born in the northern and southern hemispheres. We analyzed the potential modified risk by SOB to psychiatric disorder or drug addiction comorbidity in a population born in the Triângulo Mineiro region, a southern hemisphere Köppen tropical savanna region in Brazil.

METHOD

We accessed the records of 98,457 of patients and healthy controls of the National Datacenter of Medical Promptuary to evaluate the influence of SOB as a modifying factor on the occurrence of mental disorders and drug abuse conditions among individuals born from the year 2000 to 2016.

RESULTS

The data revealed significant modification of the relative incidence of major depressive disorder (MDD) (F11, 72 = 2.898; p = 0.003; eta-squared, ES = 0.313; ⍺ = 0.97), anxiety-related disorder (ARD) (F11, 81 =2.389; p = 0.013; ES = 0.241; ⍺ = 0.932), and schizophrenia (SZ) (F11, 83 = 2.764; p = 0.005; ES = 0.303; α = 0.963), while there was no increase in the number of healthy controls born in any month of the year (F11, 71 = 1.469; p = 0.163). Post hoc analyses indicated a significant higher vulnerability to MDD or ARD if the patient was born in August, or October to December, respectively. A relative increase in the incidence of SZ was also observed in patients born from August to October, compared to patients born from November to January.

CONCLUSIONS

SOB may influence the risk for psychiatric disorders in the TMR population. Regional particularities associated with the climatic regime may account for the apparent divergence between studies.

The Psychopharmacology Algorithm Project at the Harvard South Shore Program: An update on bipolar depression

BACKGROUND

The Psychopharmacology Algorithm Project at the Harvard South Shore Program (PAPHSS) published algorithms for bipolar depression in 1999 and 2010. Developments over the past 9 years suggest that another update is needed.

METHODS

The 2010 algorithm and associated references were reevaluated. A literature search was conducted on PubMed for recent studies and review articles to see what changes in the recommendations were justified. Exceptions to the main algorithm for special patient populations, including those with attention-deficit hyperactivity disorder (ADHD), posttraumatic stress disorder (PTSD), substance use disorders, anxiety disorders, and women of childbearing potential, and those with common medical comorbidities were considered.

RESULTS

Electroconvulsive therapy (ECT) is still the first-line option for patients in need of urgent treatment. Five medications are recommended for early usage in acute bipolar depression, singly or in combinations when monotherapy fails, the order to be determined by considerations such as side effect vulnerability and patient preference. The five are lamotrigine, lurasidone, lithium, quetiapine, and cariprazine. After trials of these, possible options include antidepressants (bupropion and selective serotonin reuptake inhibitors are preferred) or valproate (very small evidence-base). In bipolar II depression, the support for antidepressants is a little stronger but depression with mixed features and rapid cycling would usually lead to further postponement of antidepressants. Olanzapine+fluoxetine, though Food and Drug Administration (FDA) approved for bipolar depression, is not considered until beyond this point, due to metabolic side effects. The algorithm concludes with a table of other possible treatments that have some evidence.

CONCLUSIONS

This revision incorporates the latest FDA-approved treatments (lurasidone and cariprazine) and important new studies and organizes the evidence systematically.

Cross-sectional and within-subject seasonality and regularity of hospitalizations: A population study in mood disorders and schizophrenia

BACKGROUND

Seasonal peaks in hospitalizations for mood disorders and schizophrenia are well recognized and often replicated. The within-subject tendency to experience illness episodes in the same season, that is, seasonal course, is much less established, as certain individuals may temporarily meet criteria for seasonal course purely by chance.

AIMS

In this population, prospective cohort study, we investigated whether between and within-subject seasonal patterns of hospitalizations occurred more frequently than would be expected by chance.

METHODS

Using a compulsory, standardized national register of hospitalizations, we analyzed all admissions for mood disorders and schizophrenia in the Czech Republic between 1994 and 2013. We used bootstrap tests to compare the observed numbers of (a) participants with seasonal/regular course and (b) hospitalizations in individual months against empirical distributions obtained by simulations.

RESULTS

Among 87 184 participants, we found uneven distribution of hospitalizations, with hospitalization peaks for depression in April and November (X² (11) = 363.66, P < .001), for mania in August (X² (11) = 50.36, P < .001) and for schizophrenia in June (X² (11) = 70.34, P < .001). Significantly more participants than would be expected by chance, had two subsequent rehospitalizations in the same 90 days in different years (7.36%, bootstrap P < .01) or after a regular, but non-seasonal interval (6.07%, bootstrap P < .001). The proportion of participants with two consecutive hospitalizations in the same season was below chance level (7.06%).

CONCLUSIONS

Psychiatric hospitalizations were unevenly distributed throughout the year (cross-sectional seasonality), with evidence for regularity, but not seasonality of hospitalizations within subjects. Our data do not support the validity of seasonal pattern specifier. Season may be a general risk factor, which increases the risk of hospitalizations across psychiatric participants.

Daily and Seasonal Variation in Light Exposure among the Old Order Amish

Exposure to artificial bright light in the late evening and early night, common in modern society, triggers phase delay of circadian rhythms, contributing to delayed sleep phase syndrome and seasonal affective disorder. Studying a unique population like the Old Order Amish (OOA), whose lifestyles resemble pre-industrial societies, may increase understanding of light’s relationship with health. Thirty-three participants (aged 25–74, mean age 53.5; without physical or psychiatric illnesses) from an OOA community in Lancaster, PA, were assessed with wrist-worn actimeters/light loggers for at least 2 consecutive days during winter/spring (15 January–16 April) and spring/summer (14 May–10 September). Daily activity, sleep–wake cycles, and their relationship with light exposure were analyzed. Overall activity levels and light exposure increased with longer photoperiod length. While seasonal variations in the amount and spectral content of light exposure were equivalent to those reported previously for non-Amish groups, the OOA experienced a substantially (~10-fold) higher amplitude of diurnal variation in light exposure (darker nights and brighter days) throughout the year than reported for the general population. This pattern may be contributing to lower rates of SAD, short sleep, delayed sleep phase, eveningness, and metabolic dysregulation, previously reported among the OOA population.

Seasonality in schizophrenia-An analysis of a nationwide registry with 110,735 hospital admissions

Background.

Seasonal patterns in hospitalizations have been observed in various psychiatric disorders, however, it is unclear whether they also exist in schizophrenia. Previous studies found mixed results and those reporting the presence of seasonality differ regarding the characteristics of these patterns. Further, they are inconclusive whether sex is an influencing factor. The aim of this study was therefore to examine if seasonal patterns in hospitalizations can be found in schizophrenia, with special regard to a possible influence of sex, by using a large national dataset.

Methods.

Data on all hospital admissions within Austria due to schizophrenia (F20.0–F20.6) for the time period of 2003–2016 were included. Age standardized monthly variation of hospitalization for women and men was analyzed and the level of significance adjusted for multiple testing.

Results.

The database comprised of 110,735 admissions (59.6% men). Significant seasonal variations were found in the total sample with hospitalization peaks in January and June and a trough in December (p < 0.0001). No significant difference in these patterns was found between women and men with schizophrenia (p < 0.0001).

Conclusion.

Our study shows that schizophrenia-related hospitalizations follow a seasonal pattern in both men and women. The distribution of peaks might be influenced by photoperiod changes which trigger worsening of symptoms and lead to exacerbations in schizophrenia. Further research is necessary to identify underlying factors influencing seasonal patterns and to assess whether a subgroup of patients with schizophrenia is especially vulnerable to the impact of seasonal variations.

Nick Martin and the Genetics of Depression: Sample Size, Sample Size, Sample Size

Nick Martin is a pioneer in recognizing the need for large sample size to study the complex, heterogeneous and polygenic disorders of common mental disorders. In the predigital era, questionnaires were mailed to thousands of twin pairs around Australia. Always quick to adopt new technology, Nick's studies progressed to phone interviews and then online. Moreover, Nick was early to recognize the value of collecting DNA samples. As genotyping technologies improved over the years, these twin and family cohorts were used for linkage, candidate gene and genome-wide association studies. These cohorts have underpinned many analyses to disentangle the complex web of genetic and lifestyle factors associated with mental health. With characteristic foresight, Nick is chief investigator of our Australian Genetics of Depression Study, which has recruited 16,000 people with self-reported depression (plus DNA samples) over a time frame of a few months - analyses are currently ongoing. The mantra of sample size, sample size, sample size has guided Nick's research over the last 30 years and continues to do so.

Seasonal affective disorder and seasonal changes in weight and sleep duration are inversely associated with plasma adiponectin levels

Overlapping pathways between mood and metabolic regulation have increasingly been reported. Although impaired regulation of adiponectin, a major metabolism-regulating hormone, has been implicated in major depressive disorder, its role in seasonal changes in mood and seasonal affective disorder-winter type (SAD), a disorder characterized by onset of mood impairment and metabolic dysregulation (e.g., carbohydrate craving and weight gain) in fall/winter and spontaneous alleviation in spring/summer, has not been previously studied. We studied a convenience sample of 636 Old Order Amish (mean (± SD), 53.6 (±14.8) years; 50.1% males), a population with self-imposed restriction on network electric light at home, and low prevalence of total SAD (t-SAD = syndromal + subsyndromal). We calculated the global seasonality score (GSS), estimated SAD and subsyndromal-SAD after obtaining Seasonal Pattern Assessment Questionnaires (SPAQs), and measured overnight fasting plasma adiponectin levels. We then tested associations between plasma adiponectin levels and GSS, t-SAD, winter-summer difference in self-reported sleep duration, and self-reported seasonal weight change, by using analysis of co-variance (ANCOVA) and linear regression analysis after adjusting for age, gender, and BMI. Participants with t-SAD (N = 14; 2.2%) had significantly lower plasma adiponectin levels (mean ± SEM, 8.76 ± 1.56 μg/mL) than those without t-SAD (mean ± SEM, 11.93 ± 0.22 μg/mL) (p = 0.035). In addition, there was significant negative association between adiponectin levels and winter-summer difference in self-reported sleep duration (p = 0.025) and between adiponectin levels and self-reported seasonal change in weight (p = 0.006). There was no significant association between GSS and adiponectin levels (p = 0.88). To our knowledge, this is the first study testing the association of SAD with adiponectin levels. Replication and extension of our findings longitudinally and, then, interventionally, may implicate low adiponectin as a novel target for therapeutic intervention in SAD.

Polygenic risk for schizophrenia and season of birth within the UK Biobank cohort

BACKGROUND

There is strong evidence that people born in winter and in spring have a small increased risk of schizophrenia. As this 'season of birth' effect underpins some of the most influential hypotheses concerning potentially modifiable risk exposures, it is important to exclude other possible explanations for the phenomenon.

METHODS

Here we sought to determine whether the season of birth effect reflects gene-environment confounding rather than a pathogenic process indexing environmental exposure. We directly measured, in 136 538 participants from the UK Biobank (UKBB), the burdens of common schizophrenia risk alleles and of copy number variants known to increase the risk for the disorder, and tested whether these were correlated with a season of birth.

RESULTS

Neither genetic measure was associated with season or month of birth within the UKBB sample.

CONCLUSIONS

As our study was highly powered to detect small effects, we conclude that the season of birth effect in schizophrenia reflects a true pathogenic effect of environmental exposure.

Has the sun set for seasonal affective disorder and HPA axis studies? A systematic review and future prospects

OBJECTIVE

Seasonal Affective Disorder (SAD) is a form of cyclic mood disorder that tends to manifest as winter depression. SAD has anecdotally been described as a hypocortisolemic condition. However, there are no systematic reviews on SAD and Hypothalamic-Pituitary-Adrenal (HPA) axis function. This review intends to summarize these findings.

METHODS

Using the PRISMA (2009) guideline recommendations we searched for relevant articles indexed in databases including MEDLINE, EMBASE, PsycINFO, and PsychArticles. The following keywords were used: "Seasonal affective disorder", OR "Winter Depression", OR "Seasonal depression" associated with: "HPA Axis" OR "cortisol" OR "CRH" OR "ACTH".

RESULTS

Thirteen papers were included for qualitative analysis. Studies used both heterogeneous methods and populations. The best evidence comes from a recent study showing that SAD patients tend to demonstrate an attenuated Cortisol Awakening Response (CAR) in winter, but not in summer, compared to controls. Dexamethasone Suppression Test (DST) studies suggest SAD patients have normal suppression of the HPA axis.

CONCLUSION

There is still insufficient evidence to classify SAD as a hypocortisolemic condition when compared to controls. Heterogeneous methods and samples did not allow replication of results. We discuss the limitations of these studies and provide new methods and targets to probe HPA axis function in this population. SAD can provide a unique window of opportunity to study HPA axis in affective disorders, since it is highly predictable and can be followed before, during and after episodes subsides.

Genome-wide association study of seasonal affective disorder

Family and twin studies have shown a genetic component to seasonal affective disorder (SAD). A number of candidate gene studies have examined the role of variations within biologically relevant genes in SAD susceptibility, but few genome-wide association studies (GWAS) have been performed to date. The authors aimed to identify genetic risk variants for SAD through GWAS. The authors performed a GWAS for SAD in 1380 cases and 2937 controls of European-American (EA) origin, selected from samples for GWAS of major depressive disorder and of bipolar disorder. Further bioinformatic analyses were conducted to examine additional genomic and biological evidence associated with the top GWAS signals. No susceptibility loci for SAD were identified at a genome-wide significant level. The strongest association was at an intronic variant (rs139459337) within ZBTB20 (odds ratio (OR) = 1.63, p = 8.4 × 10-7), which encodes a transcriptional repressor that has roles in neurogenesis and in adult brain. Expression quantitative trait loci (eQTL) analysis showed that the risk allele "T" of rs139459337 is associated with reduced mRNA expression of ZBTB20 in human temporal cortex (p = 0.028). Zbtb20 is required for normal murine circadian rhythm and for entrainment to a shortened day. Of the 330 human orthologs of murine genes directly repressed by Zbtb20, there were 32 associated with SAD in our sample (at p < 0.05), representing a significant enrichment of ZBTB20 targets among our SAD genetic association signals (fold = 1.93, p = 0.001). ZBTB20 is a candidate susceptibility gene for SAD, based on a convergence of genetic, genomic, and biological evidence. Further studies are necessary to confirm its role in SAD.

The use of polygenic risk scores to identify phenotypes associated with genetic risk of bipolar disorder and depression: A systematic review

BACKGROUND

Identifying the phenotypic manifestations of increased genetic liability for depression (MDD) and bipolar disorder (BD) can enhance understanding of their aetiology. The polygenic risk score (PRS) derived using data from genome-wide-association-studies can be used to explore how genetic risk is manifest in different samples.

AIMS

In this systematic review, we review studies that examine associations between the MDD and BD polygenic risk scores and phenotypic outcomes.

METHODS

Following PRISMA guidelines, we searched EMBASE, Medline and PsycINFO (from August 2009 - 14th March 2016) and references of included studies. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate.

RESULTS

Twenty-five studies were included. Overall, both polygenic risk scores were associated with other psychiatric disorders (not the discovery sample disorder) such as depression, schizophrenia and bipolar disorder, greater symptom severity of depression, membership of a creative profession and greater educational attainment. Both depression and bipolar polygenic risk scores explained small amounts of variance in most phenotypes (< 2%).

LIMITATIONS

Many studies did not report standardised effect sizes. This prevented us from conducting a meta-analysis.

CONCLUSIONS

Polygenic risk scores for BD and MDD are associated with a range of phenotypes and outcomes. However, they only explain a small amount of the variation in these phenotypes. Larger discovery and adequately powered target samples are required to increase power of the PRS approach. This could elucidate how genetic risk for bipolar disorder and depression is manifest and contribute meaningfully to stratified medicine.

The use of polygenic risk scores to identify phenotypes associated with genetic risk of schizophrenia: Systematic review

Studying the phenotypic manifestations of increased genetic liability for schizophrenia can increase our understanding of this disorder. Specifically, information from alleles identified in genome-wide association studies can be collapsed into a polygenic risk score (PRS) to explore how genetic risk is manifest within different samples. In this systematic review, we provide a comprehensive assessment of studies examining associations between schizophrenia PRS (SZ-PRS) and several phenotypic measures. We searched EMBASE, Medline and PsycINFO (from August 2009-14th March 2016) plus references of included studies, following PRISMA guidelines. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate. Overall, SZ-PRS was associated with increased risk for psychiatric disorders such as depression and bipolar disorder, lower performance IQ and negative symptoms. SZ-PRS explained up to 6% of genetic variation in psychiatric phenotypes, compared to <0.7% in measures of cognition. Future gains from using the PRS approach may be greater if used for examining phenotypes that are more closely related to biological substrates, for scores based on gene-pathways, and where PRSs are used to stratify individuals for study of treatment response. As it was difficult to interpret findings across studies due to insufficient information provided by many studies, we propose a framework to guide robust reporting of PRS associations in the future.

Adverse obstetric and neonatal outcomes complicated by psychosis among pregnant women in the United States

Background

Adverse obstetric and neonatal outcomes among women with psychosis, particularly affective psychosis, has rarely been studied at the population level. We aimed to assess the risk of adverse obstetric and neonatal outcomes among women with psychosis (schizophrenia, affective psychosis, and other psychoses).

Methods

From the 2007 – 2012 National (Nationwide) Inpatient Sample, 23,507,597 delivery hospitalizations were identified. From the same hospitalization, International Classification of Diseases diagnosis codes were used to identify maternal psychosis and outcomes. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were obtained using logistic regression.

Results

The prevalence of psychosis at delivery was 698.76 per 100,000 hospitalizations. After adjusting for sociodemographic characteristics, smoking, alcohol/substance abuse, and pregnancy-related hypertension, women with psychosis were at a heightened risk for cesarean delivery (aOR = 1.26; 95% CI: 1.23 - 1.29), induced labor (aOR = 1.05; 95% CI: 1.02 - 1.09), antepartum hemorrhage (aOR = 1.22; 95% CI: 1.14 - 1.31), placental abruption (aOR = 1.22; 95% CI: 1.13 - 1.32), postpartum hemorrhage (aOR = 1.18; 95% CI: 1.10 - 1.27), premature delivery (aOR = 1.40; 95% CI: 1.36 - 1.46), stillbirth (aOR = 1.37; 95% CI: 1.23 - 1.53), premature rupture of membranes (aOR = 1.22; 95% CI: 1.15 - 1.29), fetal abnormalities (aOR = 1.49; 95% CI: 1.38 - 1.61), poor fetal growth (aOR = 1.26; 95% CI: 1.19 - 1.34), and fetal distress (aOR = 1.14; 95% CI: 1.10 - 1.18). Maternal death during hospitalizations (aOR = 1.00; 95% CI: 0.30 - 3.31) and excessive fetal growth (aOR = 1.06; 95% CI: 0.98 - 1.14) were not statistically significantly associated with psychosis.

Conclusions

Pregnant women with psychosis have elevated risk of several adverse obstetric and neonatal outcomes. Efforts to identify and manage pregnancies complicated by psychosis may contribute to improved outcomes.

Electronic supplementary material

The online version of this article (10.1186/s12884-018-1750-0) contains supplementary material, which is available to authorized users.