Associations between schizophrenia genetic risk, anxiety disorders and manic/hypomanic episode in a longitudinal population cohort study

Genetically Informed Study Highlights Income-Independent Effect of Schizophrenia Liability on Mental and Physical Health

BACKGROUND AND HYPOTHESIS

Individuals with schizophrenia (SCZ) suffer from comorbidities that substantially reduce their life expectancy. Socioeconomic inequalities could contribute to many of the negative health outcomes associated with SCZ.

STUDY DESIGN

We investigated genome-wide datasets related to SCZ (52 017 cases and 75 889 controls) from the Psychiatric Genomics Consortium, household income (HI; N = 361 687) from UK Biobank, and 2202 medical endpoints assessed in up to 342 499 FinnGen participants. A phenome-wide genetic correlation analysis of SCZ and HI was performed, also assessing whether SCZ genetic correlations were influenced by the HI effect on SCZ. Additionally, SCZ and HI direct effects on medical endpoints were estimated using multivariable Mendelian randomization (MR).

STUDY RESULTS

SCZ and HI showed overlapping genetic correlations with 70 traits (P < 2.89 × 10-5), including mental health, substance use, gastrointestinal illnesses, reproductive outcomes, liver diseases, respiratory problems, and musculoskeletal phenotypes. SCZ genetic correlations with these traits were not affected by the HI effect on SCZ. Considering Bonferroni multiple testing correction (P < 7.14 × 10-4), MR analysis indicated that SCZ and HI may affect medical abortion (SCZ OR = 1.07; HI OR = 0.78), panic disorder (SCZ OR = 1.20; HI OR = 0.60), personality disorders (SCZ OR = 1.31; HI OR = 0.67), substance use (SCZ OR = 1.2; HI OR = 0.68), and adjustment disorders (SCZ OR = 1.18; HI OR = 0.78). Multivariable MR analysis confirmed that SCZ effects on these outcomes were independent of HI.

CONCLUSIONS

The effect of SCZ genetic liability on mental and physical health may not be strongly affected by socioeconomic differences. This suggests that SCZ-specific strategies are needed to reduce negative health outcomes affecting patients and high-risk individuals.

Household income does not affect the pleiotropy of schizophrenia genetic liability with mental and physical health outcomes

Background and Hypothesis

Individuals with schizophrenia (SCZ) suffer from comorbidities that substantially reduce their life expectancy. Socioeconomic inequalities could contribute to many of the negative health outcomes associated with SCZ.

Study Design

We investigated genome-wide datasets related to SCZ (52,017 cases and 75,889 controls) from the Psychiatric Genomics Consortium, household income (HI; N=361,687) from UK Biobank, and 2,202 medical endpoints assessed in up to 342,499 FinnGen participants. A phenome-wide genetic correlation analysis of SCZ and HI was performed, also assessing whether SCZ genetic correlations were influenced by HI effect on SCZ. Additionally, SCZ and HI direct effects on medical endpoints were estimated using multivariable Mendelian randomization (MR).

Study Results

SCZ and HI showed overlapping genetic correlations with 70 traits (p<2.89×10 -5 ), including mental health, substance use, gastrointestinal illnesses, reproductive outcomes, liver diseases, respiratory problems, and musculoskeletal phenotypes. SCZ genetic correlations with these traits were not affected by HI effect on SCZ. Considering Bonferroni multiple testing correction (p<7.14×10 -4 ), MR analysis indicated that SCZ and HI may affect medical abortion (SCZ odds ratio, OR=1.07; HI OR=0.78), panic disorder (SCZ OR=1.20; HI OR=0.60), personality disorders (SCZ OR=1.31; HI OR=0.67), substance use (SCZ OR=1.2; HI OR=0.68), and adjustment disorders (SCZ OR=1.18; HI OR=0.78). Multivariable MR analysis confirmed that SCZ effects on these outcomes were independent of HI.

Conclusions

The effect of SCZ genetic liability on mental and physical health may not be strongly affected by socioeconomic differences. This suggests that SCZ-specific strategies are needed to reduce negative health outcomes affecting patients and high-risk individuals.

Polygenic liabilities underlying job stress and exhaustion over a 10-year follow-up: A general population study

We investigated whether individuals, who have a high polygenic loading for schizophrenia and major depression (PGL) but have not developed the respective disorders, are still susceptible to experience milder forms of ill-being in terms of job strain or exhaustion. We used the population-based Young Finns Study data (n = 928). PGL was assessed with a cumulative score of the polygenic risk scores for schizophrenia and depression. Participants (24-49-year-olds) evaluated their exhaustion levels and perceived job characteristics over a 10-year follow-up (2001, 2007, 2011). Participants with diagnosed psychotic or affective disorders were excluded. We found that high PGL did not predict less favorable perceptions of job environment (job strain, demands, control, satisfaction, social support at work) but high PGL predicted a higher trajectory of exhaustion in early adulthood and middle age. Additionally, high (vs. low) PGL predicted a stronger increase in exhaustion at increased levels of job strain. These findings remained after controlling for sex, socioeconomic factors, health behaviors, and cognitive performance. In conclusion, individuals with high PGL may have an elevated liability to experience exhaustion especially in early adulthood and middle age (despite they perceive their job environment similarly than others), and especially and at high levels of job strain.

Handedness and anxiety: a review

Handedness is a core phenotype in clinical laterality research and several different disorders such as schizophrenia and autism spectrum disorders have been linked to a higher prevalence of non-right-handedness. Moreover, subclinical personality traits like schizotypy have been linked to a higher prevalence of non-right-handedness. The association with handedness is poorly understood for generalized anxiety disorder and specific phobias, as well as for state and trait anxiety and fear of specific stimuli in nonclinical samples. Therefore, we performed a narrative review of studies investigating handedness in anxiety disorders patients and studies that compared anxiety scores between different handedness groups. Unlike schizophrenia and autism spectrum disorders, there seems to be no strong association between anxiety disorders and handedness in adult patients, except for specific phobias. Studies often had small sample sizes and therefore a high risk to report spurious findings. Similar findings were reported in most non-clinical studies. Importantly, familial handedness affects phobia risk and antenatal maternal anxiety increased the probability of mixed-handedness. This suggests that a transgenerational, developmental perspective is essential to better understand the complex interrelations between handedness and anxiety. Familial and especially maternal handedness and anxiety disorders should be integrated into future studies on handedness and anxiety whenever possible.

Factors associated with anxiety disorder comorbidity

BACKGROUND

Anxiety and depressive disorders often co-occur and the order of their emergence may be associated with different clinical outcomes. However, minimal research has been conducted on anxiety-anxiety comorbidity. This study examined factors associated with anxiety comorbidity and anxiety-MDD temporal sequence.

METHODS

Online, self-report data were collected from the UK-based GLAD and COPING NBR cohorts (N = 38,775). Logistic regression analyses compared differences in sociodemographic, trauma, and clinical factors between single anxiety, anxiety-anxiety comorbidity, anxiety-MDD (major depressive disorder) comorbidity, and MDD-only. Additionally, anxiety-first and MDD-first anxiety-MDD were compared. Differences in familial risk were assessed in those participants with self-reported family history or genotype data.

RESULTS

Anxiety-anxiety and anxiety-MDD had higher rates of self-reported anxiety or depressive disorder diagnoses, younger age of onset, and higher recurrence than single anxiety. Anxiety-MDD displayed greater clinical severity/complexity than MDD only. Anxiety-anxiety had more severe current anxiety symptoms, less severe current depressive symptoms, and reduced likelihood of self-reporting an anxiety/depressive disorder diagnosis than anxiety-MDD. Anxiety-first anxiety-MDD had a younger age of onset, more severe anxiety symptoms, and less likelihood of self-reporting a diagnosis than MDD-first. Minimal differences in familial risk were found.

LIMITATIONS

Self-report, retrospective measures may introduce recall bias. The familial risk analyses were likely underpowered.

CONCLUSIONS

Anxiety-anxiety comorbidity displayed a similarly severe and complex profile of symptoms as anxiety-MDD but distinct features. For anxiety-MDD, first-onset anxiety had an earlier age of onset and greater severity than MDD-first. Anxiety disorders and comorbidity warrant further investigation and attention in research and practice.

Association of Etiological Factors for Hypomanic Symptoms, Bipolar Disorder, and Other Severe Mental Illnesses

IMPORTANCE

Subsyndromal hypomanic symptoms are relatively common in the general population and are linked to the onset of bipolar disorder. Little is known about their etiology and whether this is shared with the etiology of bipolar disorder or other mental illnesses.

OBJECTIVE

To examine the genetic and environmental architecture of hypomanic symptoms in a nonclinical youth sample and compare estimates at varying severity levels and their association with diagnosed bipolar disorder.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used phenotypic and genetic data from the Child and Adolescent Twin Study in Sweden and included individuals with International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis of psychiatric disorders from national registries for residents of Sweden. Associations between hypomania and polygenic risk scores for bipolar disorder, major depressive disorder and schizophrenia were also investigated. Analysis began November 2018 and ended October 2021.

MAIN OUTCOMES AND MEASURES

Hypomanic symptoms were assessed using the parent-rated Mood Disorders Questionnaire when the twins were aged 18 years. Bipolar disorder diagnosis and/or lithium prescription were ascertained from national registries for residents of Sweden. Polygenic risk scores for psychiatric disorders were calculated using independent discovery genetic data.

RESULTS

A total of 8568 twin pairs aged 18 years (9381 [54.7%] female) were included in the study. The hypomania heritability estimate was 59% (95% CI, 52%-64%) for male individuals and 29% (95% CI, 16%-44%) for female individuals. Unique environmental factors accounted for 41% (95% CI, 36%-47%) of the hypomania variance in male individuals and 45% (95% CI, 40%-50%) in female individuals. Shared environmental factors were only detected for female individuals and explained 26% (95% CI, 13%-38%) of the variance. The heritability estimates were fairly consistent across different hypomania severity groups. Moderate genetic (0.40; 95% CI, 0.21-0.58) and shared environmental (0.41; 95% CI, 0.03-0.75) correlations between hypomania and diagnosed bipolar disorder were found. Hypomania was significantly associated with the polygenic risk scores for schizophrenia (β = 0.08; SE = 0.026; P = .002) and major depressive disorder (β = 0.09; SE = 0.027; P = .001) but not bipolar disorder (β = 0.017; SE = 0.03; P = 0.57) (bipolar disorder I [β = 0.014; SE = 0.029; P = .64] or bipolar disorder II [β = 0.045; SE = 0.027; P = .10]).

CONCLUSIONS AND RELEVANCE

Higher heritability for hypomania was found for male compared with female individuals. The results highlight the shared etiologies between hypomanic symptoms, bipolar disorder, major depression, and schizophrenia in youths. Future research should focus on identifying specific shared genetic and environmental factors. These findings support a possible dimensional model of bipolar disorder, with hypomania representing a continuous trait underlying the disorder.

Immune marker levels in severe mental disorders: associations with polygenic risk scores of related mental phenotypes and psoriasis

Several lines of evidence implicate immune abnormalities in the pathophysiology of severe mental disorders (SMD) and comorbid mental disorders. Here, we use the data from genome-wide association studies (GWAS) of autoimmune diseases and mental phenotypes associated with SMD to disentangle genetic susceptibilities of immune abnormalities in SMD. We included 1004 patients with SMD and 947 healthy controls (HC) and measured plasma levels of IL-1Ra, sIL-2R, gp130, sTNFR-1, IL-18, APRIL, and ICAM-1. Polygenic risk scores (PRS) of six autoimmune disorders, CRP, and 10 SMD-related mental phenotypes were calculated from GWAS. General linear models were applied to assess the association of PRS with immune marker abnormalities. We found negative associations between PRS of educational attainment and IL-1Ra (P = 0.01) and IL-18 (P = 0.01). There were nominal positive associations between PRS of psoriasis and sgp130 (P = 0.02) and PRS of anxiety and IL-18 (P = 0.03), and nominal negative associations between PRS of anxiety and sIL-2R (P = 0.02) and PRS of educational attainment and sIL-2R (P = 0.03). Associations explained minor amounts of the immune marker plasma-level difference between SMD and HC. Different PRS and immune marker associations in the SMD group compared to HC were shown for PRS of extraversion and IL-1Ra ([interaction effect (IE), P = 0.002), and nominally for PRS of openness and IL-1Ra (IE, P = 0.02) and sTNFR-1 (IE, P = 0.04). Our findings indicate polygenic susceptibilities to immune abnormalities in SMD involving genetic overlap with SMD-related mental phenotypes and psoriasis. Associations might suggest immune genetic factors of SMD subgroups characterized by autoimmune or specific mental features.

Magical thinking in individuals with high polygenic risk for schizophrenia but no non-affective psychoses-a general population study

A strong genetic background for psychoses is well-established. Most individuals with a high genetic risk for schizophrenia, however, do not develop the disorder. We investigated whether individuals, who have a high genetic risk for schizophrenia but no non-affective psychotic disorders, are predisposed to develop milder forms of deviant thinking in terms of magical thinking. Participants came from the population-based Young Finns Study (n = 1292). The polygenic risk score for schizophrenia (PRS) was calculated on the basis of the most recent genome-wide association study (GWAS). Psychiatric diagnoses over the lifespan were collected up to 2017 from the registry of hospital care. Magical thinking was evaluated with the Spiritual Acceptance Scale (e.g., beliefs in telepathy, miracles, mystical events, or sixth sense) of the Temperament and Character Inventory in 1997, 2001, and 2012 (participants were 20-50-year-olds). We found that, among those who did not develop non-affective psychotic disorders, high PRS predicted higher magical thinking in adulthood (p = 0.001). Further, PRS predicted different developmental courses: a low PRS predicted a steady decrease in magical thinking from age 20 to 50 years, while in individuals with high PRS the decrease in magical thinking ceased in middle age so that their level of magical thinking remained higher than expected for that age. These findings remained when controlling for sex, childhood family environment, and adulthood socioeconomic factors. In conclusion, if high PRS does not lead to a non-affective psychotic disorder, it predicts milder forms of deviant thinking such as elevated magical thinking in adulthood, especially in middle age. The finding enhances our understanding of different outcomes of high genetic psychosis risk.

The risk of anxiety disorders in children of parents with severe psychiatric disorders: a systematic review and meta-analysis

BACKGROUND

Several studies have investigated the association between parental severe psychiatric disorders and anxiety disorder risk in offspring, but the findings across these studies have been inconsistent.

METHODS

Using the PRISMA guideline, a rigorous electronic and manual search was conducted in four electronic databases EMBASE, PubMed, PsychINFO, and Scopus to identify relevant studies. All observation studies (cohort and case-control studies) that examined the association between parental severe psychiatric disorders and the risk of offspring anxiety disorders were identified. Summary risk ratios (RRs) and 95% confidence intervals (95%CI) were synthesized using a fixed and random effect meta-analysis.

RESULTS

Twenty-five studies were included in the final analysis (14 cohort and 11 case-control studies). The meta-analysis showed that parental severe psychiatric disorder was associated with a higher risk of social phobia, panic, obsessive-compulsive, post-traumatic stress, separation anxiety, and generalized anxiety disorders in the offspring. When considering specific severe psychiatric disorders in parents as exposure, parental bipolar disorder was associated with an increased risk of obsessive-compulsive and generalized anxiety disorders in the offspring, whereas parental depressive disorder was associated with an increased risk of social phobia, separation anxiety, and generalized anxiety disorders in the offspring. Conversely, parental schizophrenia was not associated with offspring anxiety disorder CONCLUSION: This review suggests that the offspring of parents with severe psychiatric, bipolar, and depressive disorders are at an increased risk of developing a range of anxiety disorders. These findings suggest that targeted early screening and intervention programs are imperative in exposed offspring.

Polygenic Risk of Psychiatric Disorders Exhibits Cross-trait Associations in Electronic Health Record Data From European Ancestry Individuals

BACKGROUND

Prediction of disease risk is a key component of precision medicine. Common traits such as psychiatric disorders have a complex polygenic architecture, making the identification of a single risk predictor difficult. Polygenic risk scores (PRSs) denoting the sum of an individual's genetic liability for a disorder are a promising biomarker for psychiatric disorders, but they require evaluation in a clinical setting.

METHODS

We developed PRSs for 6 psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, cross disorder, attention-deficit/hyperactivity disorder, and anorexia nervosa) and 17 nonpsychiatric traits in more than 10,000 individuals from the Penn Medicine Biobank with accompanying electronic health records. We performed phenome-wide association analyses to test their association across disease categories.

RESULTS

Four of the 6 psychiatric PRSs were associated with their primary phenotypes (odds ratios from 1.2 to 1.6). Cross-trait associations were identified both within the psychiatric domain and across trait domains. PRSs for coronary artery disease and years of education were significantly associated with psychiatric disorders, largely driven by an association with tobacco use disorder.

CONCLUSIONS

We demonstrated that the genetic architecture of electronic health record-derived psychiatric diagnoses is similar to ascertained research cohorts from large consortia. Psychiatric PRSs are moderately associated with psychiatric diagnoses but are not yet clinically predictive in naïve patients. Cross-trait associations for these PRSs suggest a broader effect of genetic liability beyond traditional diagnostic boundaries. As identification of genetic markers increases, including PRSs alongside other clinical risk factors may enhance prediction of psychiatric disorders and associated conditions in clinical registries.

A Mendelian randomization study of the causal association between anxiety phenotypes and schizophrenia

Schizophrenia shows a genetic correlation with both anxiety disorder and neuroticism, a trait strongly associated with anxiety. However, genetic correlations do not discern causality from genetic confounding. We therefore aimed to investigate whether anxiety-related phenotypes lie on the causal pathway to schizophrenia using Mendelian randomization (MR). Four MR methods, each with different assumptions regarding instrument validity, were used to investigate casual associations of anxiety and neuroticism related phenotypes on schizophrenia, and vice versa: inverse variance weighted (IVW), weighted median, weighted mode, and, when appropriate, MR Egger regression. MR provided evidence of a causal effect of neuroticism on schizophrenia (IVW odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.12-1.59), but only weak evidence of a causal effect of anxiety on schizophrenia (IVW OR: 1.10, 95% CI: 1.01-1.19). There was also evidence of a causal association from schizophrenia liability to anxiety disorder (IVW OR: 1.28, 95% CI: 1.18-1.39) and worry (IVW beta: 0.05, 95% CI: 0.03-0.07), but effect estimates from schizophrenia to neuroticism were inconsistent in the main analysis. The evidence of neuroticism increasing schizophrenia risk provided by our results supports future efforts to evaluate neuroticism- or anxiety-based therapies to prevent onset of psychotic disorders.

Neurodevelopmental pathways in bipolar disorder

Aberrations in neurodevelopmental trajectories have been implicated in the neurobiology of several mental disorders and evidence indicates a pathophysiological and genetic overlap of schizophrenia and bipolar disorder (BD). In this narrative review, we summarize findings related to developmental and perinatal factors as well as epidemiological, clinical, neuropsychological, brain imaging, postmortem brain and genomic studies that provide evidence for a putative neurodevelopmental pathogenesis and etiology of BD. Overall, aberrations in neurodevelopmental pathways have been more consistently implicated in the pathophysiology of schizophrenia compared to BD. Nevertheless, an accumulating body of evidence indicates that dysfunctional neurodevelopmental pathways may be implicated in the underlying pathophysiology of at least a subset of individuals with BD particularly those with an early age of illness onset and those exhibiting psychotic symptoms. A heuristic neurodevelopmental model for the pathophysiology of BD based on the findings of this review is proposed. Furthermore, we critically discuss clinical and research implications of this model. Finally, further research directions for this emerging field are provided.

Treatment-Resistant Schizophrenia: Insights From Genetic Studies and Machine Learning Approaches

Schizophrenia (SCZ) is a severe psychiatric disorder affecting approximately 23 million people worldwide. It is considered the eighth leading cause of disability according to the World Health Organization and is associated with a significant reduction in life expectancy. Antipsychotics represent the first-choice treatment in SCZ, but approximately 30% of patients fail to respond to acute treatment. These patients are generally defined as treatment-resistant and are eligible for clozapine treatment. Treatment-resistant patients show a more severe course of the disease, but it has been suggested that treatment-resistant schizophrenia (TRS) may constitute a distinct phenotype that is more than just a more severe form of SCZ. TRS is heritable, and genetics has been shown to play an important role in modulating response to antipsychotics. Important efforts have been put into place in order to better understand the genetic architecture of TRS, with the main goal of identifying reliable predictive markers that might improve the management and quality of life of TRS patients. However, the number of candidate gene and genome-wide association studies specifically focused on TRS is limited, and to date, findings do not allow the disentanglement of its polygenic nature. More recent studies implemented polygenic risk score, gene-based and machine learning methods to explore the genetics of TRS, reporting promising findings. In this review, we present an overview on the genetics of TRS, particularly focusing our discussion on studies implementing polygenic approaches.