Impact of schizophrenia genetic liability on the association between schizophrenia and physical illness: data-linkage study

Association between genetic liability to physical health conditions and comorbidities in individuals with severe mental illness: an analysis of two cross-sectional observational studies in the UK

BACKGROUND

Individuals with severe mental illness, including schizophrenia and bipolar disorder, have elevated rates of physical health conditions, contributing to increased morbidity and mortality. While environmental factors such as adverse effects from medication and lifestyle changes play a role, the contribution of genetic liability to physical health comorbidities remains underexplored. We investigated whether genetic risk for physical health conditions influences comorbidities in people with severe mental illness and compared these effects with those in the general population. Additionally, we explored the effects of psychiatric genetic liabilities and the occurrence of physical health problems in those with severe mental illness.

METHODS

We analysed two UK cross-sectional cohorts of people with severe mental illness-the Cardiff Cognition in Schizophrenia study (CardiffCOGS) cohort and the National Centre for Mental Health (NCMH) cohort. Individuals were selected for analyses if they responded to a validated self-report questionnaire of physical health problems and if their genetic data passed quality control. These subsets of individuals were used to test associations between polygenic risk scores for six physical health conditions (high cholesterol, type 2 diabetes, hypertension, asthma, heart disease, and rheumatoid arthritis) and corresponding physical health conditions in this population. Models were further adjusted for demographic and clinical covariates (sex, age, smoking, and clozapine use). Effect sizes from these analyses were compared in magnitude to those reported in studies conducted in the general population. We also evaluated associations between psychiatric polygenic risk scores (schizophrenia, bipolar disorder, major depressive disorder, and ADHD) and physical comorbidities. People with lived experience were involved in the analysis planning and guided the choices of outcomes analysed.

FINDINGS

Following exclusions due to missing phenotypic or genetic data (403 individuals in CardiffCOGS; 1704 individuals in NCMH), our analyses included 721 individuals from the CardiffCOGS cohort (mean age 43·7 years [SD 12·1], 267 [37·0%] females, 454 [63·0%] males, and 703 [97·5%] with self-reported White ethnicity) and 1011 from the NCMH cohort (mean age 47·6 years [SD 13·7], 553 [54·7%] females, 458 (45·3%) males, and 928 [91·8%] with self-reported White ethnicity). Polygenic risk scores for physical health conditions were associated with corresponding conditions in one or both of these cohorts, explaining between 1·4% and 6·5% of the variability in these comorbidities. Polygenic risk score effect sizes for at least one of the cohorts overlapped with the reported effects (within 84% CIs) in the general population. Adjustments for clinical and demographic factors had minimal impact on these associations. Psychiatric polygenic risk scores showed weaker and less consistent associations with physical comorbidities.

INTERPRETATION

Our findings support the role of genetic risk in physical health comorbidities among individuals with severe mental illness. Genetic liability to physical health conditions was more strongly associated with comorbidities than psychiatric genetic liability, highlighting its additive contribution alongside environmental and clinical factors. These findings indicate that there would be value in incorporating genetic risk information into predictive algorithms for physical health comorbidities in those with severe mental illness, and that polygenic risk scores should be included in research studies developing and validating such algorithms.

FUNDING

EU Horizon 2020 programme.

Relationship between quality of life of patients with severe mental illnesses and family burden of disease: the mediating effect of caregivers' social support

BACKGROUND

Severe mental illnesses (SMIs) have become one of the public health problems of great concern in society, which not only bring physical and mental pain to patients but also heavy burden to families. It is known that the health-related quality of life (HRQoL) of patients and caregivers' social support are correlated with caregivers' family burden of disease, but the interaction mechanism among them is not clear. The purpose of this study was to investigate the association between HRQoL in patients with SMIs and the family burden of disease and to examine the mediating role of caregivers' social support.

METHODS

From January to July 2022, this cross-sectional study was conducted in 23 community health service centers in Nanjing, China. We recruited 924 patients with SMIs and their caregivers, using a random sampling method. Hayes' PROCESS macro was used to test the mediation effect of caregivers' social support in the relationship between patients' HRQoL and family burden of disease. Indirect effects were tested using bootstrapped confidence intervals (CI).

RESULTS

The SF-36 score of patients with SMIs was 57.85 (49.59, 63.64), while the caregivers' social support was measured at 32.00 (27.00, 35.00), and the family burden of disease scored 16.00 (8.00, 24.00). Spearman correlation analysis revealed a negative correlation between the patients' HRQoL and the family burden of disease (r = -0.54, p < 0.01). Furthermore, caregivers' social support was negatively correlated with the family burden of disease (r = -0.19, p < 0.01). The mediating role of caregivers' social support between the patients' HRQoL and the family burden of disease was confirmed by the Bootstrap test (p < 0.01), with a mediating effect of 2.75% (β = -0.016, 95% CI = -0.031, -0.002).

CONCLUSIONS

This study highlights that caregivers experience a heavy family burden of disease. The patients' HRQoL not only directly affects the family burden of disease but also indirectly influences it through the caregivers' social support. Therefore, relevant departments need to prioritize improving patients' HRQoL and expanding caregivers' social support networks when developing targeted intervention programs to reduce the family burden of SMIs.

Genetic and Phenotypic Features of Schizophrenia in the UK Biobank

Importance

Large-scale biobanks provide important opportunities for mental health research, but selection biases raise questions regarding the comparability of individuals with those in clinical research settings.

Objective

To compare the genetic liability to psychiatric disorders in individuals with schizophrenia in the UK Biobank with individuals in the Psychiatric Genomics Consortium (PGC) and to compare genetic liability and phenotypic features with participants recruited from clinical settings.

Design, Setting, and Participants

This cross-sectional study included participants from the population-based UK Biobank and schizophrenia samples recruited from clinical settings (CLOZUK, CardiffCOGS, Cardiff F-Series, and Cardiff Affected Sib-Pairs). Data were collected between January 1993 and July 2021. Data analysis was conducted between July 2021 and June 2023.

Main Outcomes and Measures

A genome-wide association study of UK Biobank schizophrenia case-control status was conducted, and the results were compared with those from the PGC via genetic correlations. To test for differences with the clinical samples, polygenic risk scores (PRS) were calculated for schizophrenia, bipolar disorder, depression, and intelligence using PRS-CS. PRS and phenotypic comparisons were conducted using pairwise logistic regressions. The proportions of individuals with copy number variants associated with schizophrenia were compared using Firth logistic regression.

Results

The sample of 517 375 participants included 1438 UK Biobank participants with schizophrenia (550 [38.2%] female; mean [SD] age, 54.7 [8.3] years), 499 475 UK Biobank controls (271 884 [54.4%] female; mean [SD] age, 56.5 [8.1] years), and 4 schizophrenia research samples (4758 [28.9%] female; mean [SD] age, 38.2 [21.0] years). Liability to schizophrenia in UK Biobank was highly correlated with the latest genome-wide association study from the PGC (genetic correlation, 0.98; SE, 0.18) and showed the expected patterns of correlations with other psychiatric disorders. The schizophrenia PRS explained 6.8% of the variance in liability for schizophrenia case status in UK Biobank. UK Biobank participants with schizophrenia had significantly lower schizophrenia PRS than 3 of the clinically ascertained samples and significantly lower rates of schizophrenia-associated copy number variants than the CLOZUK sample. UK Biobank participants with schizophrenia had higher educational attainment and employment rates than the clinically ascertained schizophrenia samples, lower rates of smoking, and a later age of onset of psychosis.

Conclusions and Relevance

Individuals with schizophrenia in the UK Biobank, and likely other volunteer-based biobanks, represent those less severely affected. Their inclusion in wider studies should enhance the representation of the full spectrum of illness severity.

The Finnish Adoptive Family Study of Schizophrenia: differences in somatic diseases and conditions between adoptees with high or low genetic risk for schizophrenia spectrum disorders

BACKGROUND AND AIMS

There is some evidence that offspring of patients with schizophrenia have higher somatic morbidity, which is thought to be partially due to genetic links between somatic disorders and schizophrenia. This study explored differences in somatic diseases and conditions of adoptees with high genetic risk (HR) or low genetic risk (LR) for schizophrenia spectrum disorders.

MATERIAL AND METHODS

The study is part of the Finnish Adoptive Family Study of Schizophrenia. The adoptive research design used made it possible to examine how the somatic health of adoptees raised in similar adoptive families, is affected by their genetic susceptibility to schizophrenia. The study sample consisted of 373 adoptees, of whom 190 had HR and 183 had LR for schizophrenia spectrum disorders. Data on somatic morbidity were gathered from the hospital records and from the national registers of the Care Register of Health Care and the Social Insurance Institution.

RESULTS

The only statistically significant difference found was in genitourinary diseases, the likelihood being twofold higher in HR adoptees compared to LR adoptees (16.8% vs. 8.2%; adj. OR = 2.13, 95% CI 1.06-4.25, p = .033). Adoptees who were female and aged over 40 had a higher prevalence of genitourinary illnesses than non-adoptees.

CONCLUSION

The significant prevalence of genitourinary diseases in adoptees at risk for schizophrenia spectrum disorders suggests that some specific somatic diseases and schizophrenia may have a shared hereditary etiology. More research is required for specific somatic diseases in study populations that can differentiate between the effects of genetic and environmental factors.

Weight change, cardio-metabolic risk factors and cardiovascular incidence in people with serious mental illness: protocol of a population-based cohort study in the UK from 1998 to 2020

INTRODUCTION

People with serious mental illness (SMI), which includes people with diagnoses of schizophrenia spectrum and bipolar disorders, face significant health inequality. This includes a life expectancy reduced by 15-20 years mostly due to premature cardiovascular disease (CVD) compared with the general population. Excess weight gain and related comorbidities are preventable risk factors for CVD. To improve the understanding and management of CVD in people with SMI, we will examine the association between SMI and: (1) weight change; (2) cardio-metabolic risk factors for CVD; and (3) incidence of and mortality from CVD. We will also (4) examine the incidence of referral to weight management services for people with SMI compared with people without SMI.

METHODS AND ANALYSIS

In this retrospective cohort study, we will link general practice records from the UK Clinical Practice Research Datalink Aurum database. We will establish a cohort of patients diagnosed with SMI between 1998 and 2020 who are matched with up to four controls on age, sex, general practice and calendar year. We will use multivariable mixed-effects linear regression models and Cox proportional hazard models with sequential adjustment for potential confounders identified by separate directed acyclic graphs.

ETHICS AND DISSEMINATION

This study has been reviewed and approved by the Independent Scientific Advisory Committee for Medicines and Healthcare products Regulatory Agency database research. The results will be published in a peer-reviewed journal.