Polygenic risk for schizophrenia and bipolar disorder in relation to cardiovascular biomarkers

Individuals with schizophrenia and bipolar disorder are at an increased risk of cardiovascular disease (CVD), and a range of biomarkers related to CVD risk have been found to be abnormal in these patients. Common genetic factors are a putative underlying mechanism, alongside lifestyle factors and antipsychotic medication. However, the extent to which the altered CVD biomarkers are related to genetic factors involved in schizophrenia and bipolar disorder is unknown. In a sample including 699 patients with schizophrenia, 391 with bipolar disorder, and 822 healthy controls, we evaluated 8 CVD risk biomarkers, including BMI, and fasting plasma levels of CVD biomarkers from a subsample. Polygenic risk scores (PGRS) were obtained from genome-wide associations studies (GWAS) of schizophrenia and bipolar disorder from the Psychiatric Genomics Consortium. The CVD biomarkers were used as outcome variables in linear regression models including schizophrenia and bipolar disorder PGRS as predictors, age, sex, diagnostic category, batch and 10 principal components as covariates, controlling for multiple testing by Bonferroni correction for the number of independent tests. Bipolar disorder PGRS was significantly (p = 0.03) negatively associated with BMI after multiple testing correction, and schizophrenia PGRS was nominally negatively associated with BMI. There were no other significant associations between bipolar or schizophrenia PGRS, and other investigated CVD biomarkers. Despite a range of abnormal CVD risk biomarkers in psychotic disorders, we only found a significant negative association between bipolar disorder PGRS and BMI. This has previously been shown for schizophrenia PGRS and BMI, and warrants further exploration.

An evolutionary timeline of the oxytocin signaling pathway

Oxytocin is a neuropeptide associated with both psychological and somatic processes like parturition and social bonding. Although oxytocin homologs have been identified in many species, the evolutionary timeline of the entire oxytocin signaling gene pathway has yet to be described. Using protein sequence similarity searches, microsynteny, and phylostratigraphy, we assigned the genes supporting the oxytocin pathway to different phylostrata based on when we found they likely arose in evolution. We show that the majority (64%) of genes in the pathway are 'modern'. Most of the modern genes evolved around the emergence of vertebrates or jawed vertebrates (540 - 530 million years ago, 'mya'), including OXTR, OXT and CD38. Of those, 45% were under positive selection at some point during vertebrate evolution. We also found that 18% of the genes in the oxytocin pathway are 'ancient', meaning their emergence dates back to cellular organisms and opisthokonta (3500-1100 mya). The remaining genes (18%) that evolved after ancient and before modern genes were classified as 'medium-aged'. Functional analyses revealed that, in humans, medium-aged oxytocin pathway genes are highly expressed in contractile organs, while modern genes in the oxytocin pathway are primarily expressed in the brain and muscle tissue.

Phenotype-informed polygenic risk scores are associated with worse outcome in individuals at risk of Alzheimer's disease

Introduction

Patients with predementia Alzheimer's disease (AD) and at-risk subjects are targets for promising disease-modifying treatments, and improved polygenic risk scores (PRSs) could improve early-stage case selection.

Methods

Phenotype-informed PRSs were developed by selecting AD-associated variants conditional on relevant inflammatory or cardiovascular traits. The primary outcome was longitudinal changes in measures of AD pathology, namely development of pathological amyloid deposition, medial temporal lobe atrophy, and cognitive decline in a prospective cohort study including 394 adults without AD dementia.

Results

High-risk groups defined by phenotype-informed AD PRSs had significantly steeper volume decline in medial temporal cortices, and the high-risk group defined by the cardiovascular-informed AD PRS had significantly increased hazard ratio of pathological amyloid deposition, compared to low-risk groups.

Discussion

AD PRSs informed by inflammatory disorders or cardiovascular risk factors and diseases are associated with development of AD pathology markers and may improve identification of subjects at risk for progression of AD.

Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology

BACKGROUND

Schizophrenia is a complex polygenic disorder with subtle, distributed abnormalities in brain morphology. There are indications of shared genetic architecture between schizophrenia and brain measures despite low genetic correlations. Through the use of analytical methods that allow for mixed directions of effects, this overlap may be leveraged to improve our understanding of underlying mechanisms of schizophrenia and enrich polygenic risk prediction outcome.

METHODS

We ran a multivariate genome-wide analysis of 175 brain morphology measures using data from 33,735 participants of the UK Biobank and analyzed the results in a conditional false discovery rate together with schizophrenia genome-wide association study summary statistics of the Psychiatric Genomics Consortium (PGC) Wave 3. We subsequently created a pleiotropy-enriched polygenic score based on the loci identified through the conditional false discovery rate approach and used this to predict schizophrenia in a nonoverlapping sample of 743 individuals with schizophrenia and 1074 healthy controls.

RESULTS

We found that 20% of the loci and 50% of the genes significantly associated with schizophrenia were also associated with brain morphology. The conditional false discovery rate analysis identified 428 loci, including 267 novel loci, significantly associated with brain-linked schizophrenia risk, with functional annotation indicating high relevance for brain tissue. The pleiotropy-enriched polygenic score explained more variance in liability than conventional polygenic scores across several scenarios.

CONCLUSIONS

Our results indicate strong genetic overlap between schizophrenia and brain morphology with mixed directions of effect. The results also illustrate the potential of exploiting polygenetic overlap between brain morphology and mental disorders to boost discovery of brain tissue-specific genetic variants and its use in polygenic risk frameworks.

Neural correlates of user learning during long-term BCI training for the Cybathlon competition

Background

Brain-computer interfaces (BCIs) are systems capable of translating human brain patterns, measured through electroencephalography (EEG), into commands for an external device. Despite the great advances in machine learning solutions to enhance the performance of BCI decoders, the translational impact of this technology remains elusive. The reliability of BCIs is often unsatisfactory for end-users, limiting their application outside a laboratory environment.

Methods

We present the analysis on the data acquired from an end-user during the preparation for two Cybathlon competitions, where our pilot won the gold medal twice in a row. These data are of particular interest given the mutual learning approach adopted during the longitudinal training phase (8 months), the long training break in between the two events (1 year) and the demanding evaluation scenario. A multifaceted perspective on long-term user learning is proposed: we enriched the information gathered through conventional metrics (e.g., accuracy, application performances) by investigating novel neural correlates of learning in different neural domains.

Results

First, we showed that by focusing the training on user learning, the pilot was capable of significantly improving his performance over time even with infrequent decoder re-calibrations. Second, we revealed that the analysis of the within-class modifications of the pilot’s neural patterns in the Riemannian domain is more effective in tracking the acquisition and the stabilization of BCI skills, especially after the 1-year break. These results further confirmed the key role of mutual learning in the acquisition of BCI skills, and particularly highlighted the importance of user learning as a key to enhance BCI reliability.

Conclusion

We firmly believe that our work may open new perspectives and fuel discussions in the BCI field to shift the focus of future research: not only to the machine learning of the decoder, but also in investigating novel training procedures to boost the user learning and the stability of the BCI skills in the long-term. To this end, the analyses and the metrics proposed could be used to monitor the user learning during training and provide a marker guiding the decoder re-calibration to maximize the mutual adaptation of the user to the BCI system.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-022-01047-x.

Dissecting the shared genetic basis of migraine and mental disorders using novel statistical tools

Migraine is three times more prevalent in people with bipolar disorder or depression. The relationship between schizophrenia and migraine is less certain although glutamatergic and serotonergic neurotransmission are implicated in both. A shared genetic basis to migraine and mental disorders has been suggested but previous studies have reported weak or non-significant genetic correlations and five shared risk loci. Using the largest samples to date and novel statistical tools, we aimed to determine the extent to which migraine's polygenic architecture overlaps with bipolar disorder, depression and schizophrenia beyond genetic correlation, and to identify shared genetic loci. Summary statistics from genome-wide association studies were acquired from large-scale consortia for migraine (n cases = 59 674; n controls = 316 078), bipolar disorder (n cases = 20 352; n controls = 31 358), depression (n cases = 170 756; n controls = 328 443) and schizophrenia (n cases = 40 675, n controls = 64 643). We applied the bivariate causal mixture model to estimate the number of disorder-influencing variants shared between migraine and each mental disorder, and the conditional/conjunctional false discovery rate method to identify shared loci. Loci were functionally characterized to provide biological insights. Univariate MiXeR analysis revealed that migraine was substantially less polygenic (2.8 K disorder-influencing variants) compared to mental disorders (8100-12 300 disorder-influencing variants). Bivariate analysis estimated that 800 (SD = 300), 2100 (SD = 100) and 2300 (SD = 300) variants were shared between bipolar disorder, depression and schizophrenia, respectively. There was also extensive overlap with intelligence (1800, SD = 300) and educational attainment (2100, SD = 300) but not height (1000, SD = 100). We next identified 14 loci jointly associated with migraine and depression and 36 loci jointly associated with migraine and schizophrenia, with evidence of consistent genetic effects in independent samples. No loci were associated with migraine and bipolar disorder. Functional annotation mapped 37 and 298 genes to migraine and each of depression and schizophrenia, respectively, including several novel putative migraine genes such as L3MBTL2, CACNB2 and SLC9B1. Gene-set analysis identified several putative gene sets enriched with mapped genes including transmembrane transport in migraine and schizophrenia. Most migraine-influencing variants were predicted to influence depression and schizophrenia, although a minority of mental disorder-influencing variants were shared with migraine due to the difference in polygenicity. Similar overlap with other brain-related phenotypes suggests this represents a pool of 'pleiotropic' variants that influence vulnerability to diverse brain-related disorders and traits. We also identified specific loci shared between migraine and each of depression and schizophrenia, implicating shared molecular mechanisms and highlighting candidate migraine genes for experimental validation.

Dose-dependent transcriptional effects of lithium and adverse effect burden in a psychiatric cohort

Lithium is the first-line treatment for bipolar disorder (BD), but there is a large variation in response rate and adverse effects. Although the molecular effects of lithium have been studied extensively, the specific mechanisms of action remain unclear. In particular, the molecular changes underlying lithium adverse effects are little known. Multiple linear regression analyses of lithium serum concentrations and global gene expression levels in whole blood were carried out using a large case-control sample (n = 1450). Self-reported adverse effects of lithium were assessed with the "Udvalg for Kliniske Undersøgelser" (UKU) adverse effect rating scale, and regression analysis was used to identify significant associations between lithium-related genes and six of the most common adverse effects. Serum concentrations of lithium were significantly associated with the expression levels of 52 genes (FDR < 0.01), largely replicating previous results. We found 32 up-regulated genes and 20 down-regulated genes in lithium users compared to non-users. The down-regulated gene set was enriched for several processes related to the translational machinery. Two adverse effects were significantly associated (p < 0.01) with three or more lithium-associated genes: tremor (FAM13A-AS1, FAR2, ITGAX, RWDD1, and STARD10) and xerostomia (ANKRD13A, FAR2, RPS8, and RWDD1). The adverse effect association with the largest effect was between CAMK1D expression and nausea/vomiting. These results suggest putative transcriptional mechanisms that may predict lithium adverse effects, and could thus have a large potential for informing clinical practice.

Oxytocin-pathway polygenic scores for severe mental disorders and metabolic phenotypes in the UK Biobank

Oxytocin is a neuromodulator and hormone that is typically associated with social cognition and behavior. In light of its purported effects on social cognition and behavior, research has investigated its potential as a treatment for psychiatric illnesses characterized by social dysfunction, such as schizophrenia and bipolar disorder. While the results of these trials have been mixed, more recent evidence suggests that the oxytocin system is also linked with cardiometabolic conditions for which individuals with severe mental disorders are at a higher risk for developing. To investigate whether the oxytocin system has a pleiotropic effect on the etiology of severe mental illness and cardiometabolic conditions, we explored oxytocin's role in the shared genetic liability of schizophrenia, bipolar disorder, type-2 diabetes, and several phenotypes linked with cardiovascular disease and type 2 diabetes risk using a polygenic pathway-specific approach. Analysis of a large sample with about 480,000 individuals (UK Biobank) revealed statistically significant associations across the range of phenotypes analyzed. By comparing these effects to those of polygenic scores calculated from 100 random gene sets, we also demonstrated the specificity of many of these significant results. Altogether, our results suggest that the shared effect of oxytocin-system dysfunction could help partially explain the co-occurrence of social and cardiometabolic dysfunction in severe mental illnesses.

Characterising the shared genetic determinants of bipolar disorder, schizophrenia and risk-taking

Increased risk-taking is a central component of bipolar disorder (BIP) and is implicated in schizophrenia (SCZ). Risky behaviours, including smoking and alcohol use, are overrepresented in both disorders and associated with poor health outcomes. Positive genetic correlations are reported but an improved understanding of the shared genetic architecture between risk phenotypes and psychiatric disorders may provide insights into underlying neurobiological mechanisms. We aimed to characterise the genetic overlap between risk phenotypes and SCZ, and BIP by estimating the total number of shared variants using the bivariate causal mixture model and identifying shared genomic loci using the conjunctional false discovery rate method. Summary statistics from genome wide association studies of SCZ, BIP, risk-taking and risky behaviours were acquired (n = 82,315-466,751). Genomic loci were functionally annotated using FUMA. Of 8.6-8.7 K variants predicted to influence BIP, 6.6 K and 7.4 K were predicted to influence risk-taking and risky behaviours, respectively. Similarly, of 10.2-10.3 K variants influencing SCZ, 9.6 and 8.8 K were predicted to influence risk-taking and risky behaviours, respectively. We identified 192 loci jointly associated with SCZ and risk phenotypes and 206 associated with BIP and risk phenotypes, of which 68 were common to both risk-taking and risky behaviours and 124 were novel to SCZ or BIP. Functional annotation implicated differential expression in multiple cortical and sub-cortical regions. In conclusion, we report extensive polygenic overlap between risk phenotypes and BIP and SCZ, identify specific loci contributing to this shared risk and highlight biologically plausible mechanisms that may underlie risk-taking in severe psychiatric disorders.

Identification of genetic overlap and novel risk loci for attention-deficit/hyperactivity disorder and bipolar disorder

Differential diagnosis between childhood onset attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) remains a challenge, mainly due to overlapping symptoms and high rates of comorbidity. Despite this, genetic correlation reported for these disorders is low and non-significant. Here we aimed to better characterize the genetic architecture of these disorders utilizing recent large genome-wide association studies (GWAS). We analyzed independent GWAS summary statistics for ADHD (19,099 cases and 34,194 controls) and BD (20,352 cases and 31,358 controls) applying the conditional/conjunctional false discovery rate (condFDR/conjFDR) statistical framework that increases the power to detect novel phenotype-specific and shared loci by leveraging the combined power of two GWAS. We observed cross-trait polygenic enrichment for ADHD conditioned on associations with BD, and vice versa. Leveraging this enrichment, we identified 19 novel ADHD risk loci and 40 novel BD risk loci at condFDR <0.05. Further, we identified five loci jointly associated with ADHD and BD (conjFDR < 0.05). Interestingly, these five loci show concordant directions of effect for ADHD and BD. These results highlight a shared underlying genetic risk for ADHD and BD which may help to explain the high comorbidity rates and difficulties in differentiating between ADHD and BD in the clinic. Improving our understanding of the underlying genetic architecture of these disorders may aid in the development of novel stratification tools to help reduce these diagnostic difficulties.

Genetic control of variability in subcortical and intracranial volumes

Sensitivity to external demands is essential for adaptation to dynamic environments, but comes at the cost of increased risk of adverse outcomes when facing poor environmental conditions. Here, we apply a novel methodology to perform genome-wide association analysis of mean and variance in ten key brain features (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, intracranial volume, cortical surface area, and cortical thickness), integrating genetic and neuroanatomical data from a large lifespan sample (n = 25,575 individuals; 8-89 years, mean age 51.9 years). We identify genetic loci associated with phenotypic variability in thalamus volume and cortical thickness. The variance-controlling loci involved genes with a documented role in brain and mental health and were not associated with the mean anatomical volumes. This proof-of-principle of the hypothesis of a genetic regulation of brain volume variability contributes to establishing the genetic basis of phenotypic variance (i.e., heritability), allows identifying different degrees of brain robustness across individuals, and opens new research avenues in the search for mechanisms controlling brain and mental health.

Phenotype-specific differences in polygenicity and effect size distribution across functional annotation categories revealed by AI-MiXeR

Motivation

Determining the relative contributions of functional genetic categories is fundamental to understanding the genetic etiology of complex human traits and diseases. Here, we present Annotation Informed-MiXeR, a likelihood-based method for estimating the number of variants influencing a phenotype and their effect sizes across different functional annotation categories of the genome using summary statistics from genome-wide association studies.

Results

Extensive simulations demonstrate that the model is valid for a broad range of genetic architectures. The model suggests that complex human phenotypes substantially differ in the number of causal variants, their localization in the genome and their effect sizes. Specifically, the exons of protein-coding genes harbor more than 90% of variants influencing type 2 diabetes and inflammatory bowel disease, making them good candidates for whole-exome studies. In contrast, <10% of the causal variants for schizophrenia, bipolar disorder and attention-deficit/hyperactivity disorder are located in protein-coding exons, indicating a more substantial role of regulatory mechanisms in the pathogenesis of these disorders.

Availability and implementation

The software is available at: https://github.com/precimed/mixer.

Supplementary information

Supplementary data are available at Bioinformatics online.

Optimising classification of proximal arm strength impairment in wheelchair rugby: A proof of concept study

This study examined the relationship between proximal arm strength and mobility performance in wheelchair rugby (WR) athletes and examined whether a valid structure for classifying proximal arm strength impairment could be determined. Fifty-seven trained WR athletes with strength impaired arms and no trunk function performed six upper body isometric strength tests and three 10 m sprints in their rugby wheelchair. All strength measures correlated with 2 m and 10 m sprint times (r ≥ -0.43; p ≤ 0.0005) and were entered into k-means cluster analyses with 4-clusters (to mirror the current International Wheelchair Rugby Federation [IWRF] system) and 3-clusters. The 3-cluster structure provided a more valid structure than both the 4-cluster and existing IWRF system, as evidenced by clearer differences in strength (Effect sizes [ES] ≥ 1.0) and performance (ES ≥ 1.1) between adjacent clusters and stronger mean silhouette coefficient (0.64). Subsequently, the 3-cluster structure for classifying proximal arm strength impairment would result in less overlap between athletes from adjacent classes and reduce the likelihood of athletes being disadvantaged due to their impairment. This study demonstrated that the current battery of isometric strength tests and cluster analyses could facilitate the evidence-based development of classifying proximal arm strength impairment in WR.

In vivo hippocampal subfield volumes in bipolar disorder—A mega‐analysis from The Enhancing Neuro Imaging Genetics through Meta‐Analysis Bipolar Disorder Working Group

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed‐effects models and mega‐analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = −0.20), cornu ammonis (CA)1 (d = −0.18), CA2/3 (d = −0.11), CA4 (d = −0.19), molecular layer (d = −0.21), granule cell layer of dentate gyrus (d = −0.21), hippocampal tail (d = −0.10), subiculum (d = −0.15), presubiculum (d = −0.18), and hippocampal amygdala transition area (d = −0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non‐users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.

Identification of Genetic Loci Shared Between Attention-Deficit/Hyperactivity Disorder, Intelligence, and Educational Attainment

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is consistently associated with lower levels of educational attainment. A recent large genome-wide association study identified common gene variants associated with ADHD, but most of the genetic architecture remains unknown.

METHODS

We analyzed independent genome-wide association study summary statistics for ADHD (19,099 cases and 34,194 controls), educational attainment (N = 842,499), and general intelligence (N = 269,867) using a conditional/conjunctional false discovery rate (FDR) statistical framework that increases power of discovery by conditioning the FDR on overlapping associations. The genetic variants identified were characterized in terms of function, expression, and biological processes.

RESULTS

We identified 58 linkage disequilibrium-independent ADHD-associated loci (conditional FDR < 0.01), of which 30 were shared between ADHD and educational attainment or general intelligence (conjunctional FDR < 0.01) and 46 were novel risk loci for ADHD.

CONCLUSIONS

These results expand on previous genetic and epidemiological studies and support the hypothesis of a shared genetic basis between these phenotypes. Although the clinical utility of the identified loci remains to be determined, they can be used as resources to guide future studies aiming to disentangle the complex etiologies of ADHD, educational attainment, and general intelligence.

Shared Genetic Loci Between Body Mass Index and Major Psychiatric Disorders: A Genome-wide Association Study

Importance

People with major psychiatric disorders (MPDs) have a 10- to 20-year shorter life span than the rest of the population, and this difference is mainly due to comorbid cardiovascular diseases. Genome-wide association studies have identified common variants involved in schizophrenia (SCZ), bipolar disorder (BIP), and major depression (MD) and body mass index (BMI), a key cardiometabolic risk factor. However, genetic variants jointly influencing MPD and BMI remain largely unknown.

Objective

To assess the extent of the overlap between the genetic architectures of MPDs and BMI and identify genetic loci shared between them.

Design, Setting, and Participants

Using a conditional false discovery rate statistical framework, independent genome-wide association study data on individuals with SCZ (n = 82 315), BIP (n = 51 710), MD (n = 480 359), and BMI (n = 795 640) were analyzed. The UK Biobank cohort (n = 29 740) was excluded from the MD data set to avoid sample overlap. Data were collected from August 2017 to May 2018, and analysis began July 2018.

Main Outcomes and Measures

The primary outcomes were a list of genetic loci shared between BMI and MPDs and their functional pathways.

Results

Genome-wide association study data from 1 380 284 participants were analyzed, and the genetic correlation between BMI and MPDs varied (SCZ: r for genetic = -0.11, P = 2.1 × 10-10; BIP: r for genetic = -0.06, P = .0103; MD: r for genetic = 0.12, P = 6.7 × 10-10). Overall, 63, 17, and 32 loci shared between BMI and SCZ, BIP, and MD, respectively, were analyzed at conjunctional false discovery rate less than 0.01. Of the shared loci, 34% (73 of 213) in SCZ, 52% (36 of 69) in BIP, and 57% (56 of 99) in MD had risk alleles associated with higher BMI (conjunctional false discovery rate <0.05), while the rest had opposite directions of associations. Functional analyses indicated that the overlapping loci are involved in several pathways including neurodevelopment, neurotransmitter signaling, and intracellular processes, and the loci with concordant and opposite association directions pointed mostly to different pathways.

Conclusions and Relevance

In this genome-wide association study, extensive polygenic overlap between BMI and SCZ, BIP, and MD were found, and 111 shared genetic loci were identified, implicating novel functional mechanisms. There was mixture of association directions in SCZ and BMI, albeit with a preponderance of discordant ones.

Associations between schizophrenia polygenic risk and apathy in schizophrenia spectrum disorders and healthy controls

OBJECTIVE

Apathy is a central predictor of a poor functional outcome in schizophrenia. Schizophrenia polygenic risk scores (PRSs) are used to detect genetic associations to key clinical phenotypes in schizophrenia. We explored the associations between schizophrenia PRS and apathy levels in schizophrenia spectrum disorders (n = 281) and matched healthy controls (n = 298), and further how schizophrenia PRS contributed in predicting apathy when added to premorbid and clinical factors in the patient sample.

METHOD

Schizophrenia PRSs were computed for each participant. Apathy was assessed with the Apathy Evaluation Scale. Bivariate correlation analyses were used to investigate associations between schizophrenia PRS and apathy, and between apathy and premorbid and clinical factors. Multiple hierarchical regression analyses were employed to evaluate the contributions of clinical variables and schizophrenia PRS to apathy levels.

RESULTS

We found no significant associations between schizophrenia PRS and apathy in patients and healthy controls. Several premorbid and clinical characteristics significantly predicted apathy in patients, but schizophrenia PRS did not.

CONCLUSION

Since the PRSs are based on common genetic variants, our results do not preclude associations to other types of genetic factors. The results could also indicate that environmentally based biological or psychological factors contribute to apathy levels in schizophrenia.

Kinematic bidimensional analysis of the propulsion technique in wheelchair rugby athletes

Wheelchair rugby is a sport ideated for individuals with cervical spinal cord injury (CSCI) which is extremely important for maintaining their neuromuscular abilities and improving their social and psychological wellbeing. However, due to the frequent changes in direction and speed it considerably stresses the players’ upper limbs. 13 athletes have undergone two sports-related tests on an inertial drum bench and several kinematic parameters have been registered. Most athletes use a semi-circular pattern which is considered protective for the upper limb. With increasing speed, range of motion (ROM) increases. Release angles increment and contact angles reduce, displacing the push angle forward to increase speed. Instead, the more anterior late push angle used to increase velocity is a factor which further loads the shoulder joint. However, other factors affecting propulsion technique, such as posture and wheelchair set up should be studied to further reduce loading on the upper limb.

Childhood maltreatment and polygenic risk in bipolar disorders

BACKGROUND

Childhood maltreatment is a well-known risk factor for developing a more severe and complex form of bipolar disorders (BD). However, knowledge is scarce about the interactions between childhood maltreatment and underlying genetic vulnerability on the clinical expression of BD.

METHOD

We assigned a BD-polygenic risk score (BD-PRS), calculated from the Psychiatric Genomics Consortium, to each individual in a sample of 402 cases with BD. The lifetime clinical expression of BD was characterized using structured interviews and patients completed the Childhood Trauma Questionnaire (CTQ) to assess the severity of childhood maltreatment.

RESULTS

Cases who reported more severe childhood maltreatment had a lower BD-PRS (rho = -0.12, P = .01), especially when considering emotional abuse (rho = -0.16, P = .001). An interaction between BD-PRS and childhood maltreatment was observed for the risk of rapid cycling (P = .01). No further interactions between BD-PRS and childhood maltreatment were observed for other clinical characteristics (age at onset, suicide attempts, number of mood episodes, mixed features, substance use disorders and psychotic symptoms).

CONCLUSION

Our study is the first to show that less genetic risk may be needed to develop a more unstable form of BD when exposed to childhood maltreatment. Our study supports childhood trauma as an independent risk factor for BD.

Author Correction: Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer's disease risk

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Autism spectrum disorder polygenic scores are associated with every day executive function in children admitted for clinical assessment

Autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDs) are behaviorally defined disorders with overlapping clinical features that are often associated with higher-order cognitive dysfunction, particularly executive dysfunction. Our aim was to determine if the polygenic score (PGS) for ASD is associated with parent-reported executive dysfunction in everyday life using the Behavior Rating Inventory of Executive Function (BRIEF). Furthermore, we investigated if PGS for general intelligence (INT) and attention deficit/hyperactivity disorder (ADHD) also correlate with BRIEF. We included 176 children, adolescents and young adults aged 5-22 years with full-scale intelligence quotient (IQ) above 70. All were admitted for clinical assessment of ASD symptoms and 68% obtained an ASD diagnosis. We found a significant difference between low and high ASD PGS groups in the BRIEF behavior regulation index (BRI) (P = 0.015, Cohen's d = 0.69). A linear regression model accounting for age, sex, full-scale IQ, Social Responsiveness Scale (SRS) total score, ASD, ADHD and INT PGS groups as well as genetic principal components, significantly predicted the BRI score; F(11,130) = 8.142, P < 0.001, R2 = 0.41 (unadjusted). Only SRS total (P < 0.001), ASD PGS 0.1 group (P = 0.018), and sex (P = 0.022) made a significant contribution to the model. This suggests that the common ASD risk gene variants have a stronger association to behavioral regulation aspects of executive dysfunction than ADHD risk or INT variants in a clinical sample with ASD symptoms. Autism Res 2020, 13: 207-220. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: People with autism spectrum disorder (ASD) often have difficulties with higher-order cognitive processes that regulate thoughts and actions during goal-directed behavior, also known as executive function (EF). We studied the association between genetics related to ASD and EF and found a relation between high polygenic score (PGS) for ASD and difficulties with behavior regulation aspects of EF in children and adolescents under assessment for ASD. Furthermore, high PGS for general intelligence was related to social problems.

Brain scans from 21,297 individuals reveal the genetic architecture of hippocampal subfield volumes

The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimer's disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields' genetic architecture. T1-weighted brain scans (n = 21,297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, co-varying for whole hippocampal volume. We further calculated the single-nucleotide polymorphism (SNP)-based heritability of 12 subfields, as well as their genetic correlation with each other, with other structural brain features and with AD and schizophrenia. All outcome measures were corrected for age, sex and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from 0.14 to 0.27, all p < 1 × 10^-16) and clustered together based on their genetic correlations compared with other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.

Examining the association between genetic liability for schizophrenia and psychotic symptoms in Alzheimer's disease

Psychosis (delusions or hallucinations) in Alzheimer's disease (AD + P) occurs in up to 50% of individuals and is associated with significantly worse clinical outcomes. Atypical antipsychotics, first developed for schizophrenia, are commonly used in AD + P, suggesting shared mechanisms. Despite this implication, little empirical research has been conducted to examine whether there are mechanistic similarities between AD + P and schizophrenia. In this study, we tested whether polygenic risk score (PRS) for schizophrenia was associated with AD + P. Schizophrenia PRS was calculated using Psychiatric Genomics Consortium data at ten GWAS p value thresholds (PT) in 3111 AD cases from 11 cohort studies characterized for psychosis using validated, standardized tools. Association between PRS and AD + P status was tested by logistic regression in each cohort individually and the results meta-analyzed. The schizophrenia PRS was associated with AD + P at an optimum PT of 0.01. The strongest association was for delusions where a one standard deviation increase in PRS was associated with a 1.18-fold increased risk (95% CI: 1.06-1.3; p = 0.001). These new findings point towards psychosis in AD-and particularly delusions-sharing some genetic liability with schizophrenia and support a transdiagnostic view of psychotic symptoms across the lifespan.

Author Correction: GBA and APOE ε4 associate with sporadic dementia with Lewy bodies in European genome wide association study

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Common brain disorders are associated with heritable patterns of apparent aging of the brain

Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.