Causal associations of intelligence with schizophrenia and bipolar disorder: A Mendelian randomization analysis

Principles and elements of patient-centredness in mental health services: a thematic analysis of a systematic review of reviews

INTRODUCTION

Mental health disorders, particularly depression and anxiety, are widespread globally and necessitate effective solutions. The patient-centred approach has been identified as a viable and effective method for addressing these challenges. This paper synthesised the principles of patient-centred mental health services and provides a comprehensive review of the existing literature.

MATERIALS AND METHODS

This is a qualitative content analysis study conducted in a systematic review framework in 2022. PubMed, Scopus, ProQuest and Cochrane databases were systematically searched, and by screening the titles, abstracts, and the texts of studies related to the purpose of the research, the data were extracted. Evaluation of the quality of the studies was done using the CASP checklist for qualitative studies. After selecting the final studies based on the entry and exit criteria, subsequently, a thematic analysis of findings was conducted on the data obtained from the systematic review.

RESULTS

The database search produced 6649 references. After screening, 11 studies met the inclusion criteria. The quality scores indicated the studies were of high level of quality with acceptable risk of bias. The thematic analysis identified six major principles of patient-centredness in mental health services: education, involvement and cooperation, access, effectiveness and safety, health and well-being, and ethics.

CONCLUSIONS

Patient-centredness is a complex approach in mental health services. The principles and elements of patient-centredness foster positive patient outcomes, enhance healthcare quality and ensure compassionate and effective care. Upholding these principles is crucial for delivering patient-centred, ethical and effective mental health services. Furthermore, the study found that patient education can boost adherence and satisfaction, and decrease unnecessary hospitalisations. Patient involvement in decision-making is influenced by their age and the relationship with their psychologists. And, effective leadership and resource management can enhance clinical processes and patient-centredness in mental health services.

Executive Function as an Underlying Mechanism of Alcohol Use, Aggression, and ADHD

Background

Executive functioning (EF) has been proposed as a transdiagnostic risk factor for externalizing disorders and behavior more broadly, including attention-deficit/hyperactivity disorder (ADHD), aggression, and alcohol use. Previous research has demonstrated both phenotypic and genetic overlap among these behaviors, but has yet to examine EF as a common causal mechanism. The current study examined reciprocal causal associations between EF and several externalizing behaviors using a Mendelian randomization (MR) approach.

Methods

Two-sample MR was conducted to test causal associations between EF and externalizing behaviors. Summary statistics from several genome-wide association studies (GWASs) were used in these analyses, including GWASs of EF, ADHD diagnostic status, drinks per week, aggressive behavior, and alcohol use disorder (AUD) diagnostic status. Multiple estimation methods were employed to account for horizontal pleiotropy (e.g., inverse variance weighted, MR-PRESSO, MR-MIX).

Results

EF demonstrated significant causal relationships with ADHD (P < 0.01), AUD (P < 0.03), and alcohol consumption (P < 0.01) across several estimation methods. Reciprocally, ADHD showed a significant causal influence on EF (P < 0.03). Nonetheless, caution should be used when interpreting these findings as there was some evidence for horizontal pleiotropy in the effect of EF on ADHD and significant heterogeneity in variant effects in the other relations tested. There were no significant findings for aggression.

Conclusions

Findings suggest that EF may be a causal mechanism underlying some externalizing behaviors, including ADHD and alcohol use, and that ADHD may also lead to lower performance on EF tasks.

Mendelian randomization: causal inference leveraging genetic data

Mendelian randomization (MR) leverages genetic information to examine the causal relationship between phenotypes allowing for the presence of unmeasured confounders. MR has been widely applied to unresolved questions in epidemiology, making use of summary statistics from genome-wide association studies on an increasing number of human traits. However, an understanding of essential concepts is necessary for the appropriate application and interpretation of MR. This review aims to provide a non-technical overview of MR and demonstrate its relevance to psychiatric research. We begin with the origins of MR and the reasons for its recent expansion, followed by an overview of its statistical methodology. We then describe the limitations of MR, and how these are being addressed by recent methodological advances. We showcase the practical use of MR in psychiatry through three illustrative examples - the connection between cannabis use and psychosis, the link between intelligence and schizophrenia, and the search for modifiable risk factors for depression. The review concludes with a discussion of the prospects of MR, focusing on the integration of multi-omics data and its extension to delineating complex causal networks.

Socioenvironmental Adversity and Adolescent Psychotic Experiences: Exploring Potential Mechanisms in a UK Longitudinal Cohort

BACKGROUND AND HYPOTHESIS

Children exposed to socioenvironmental adversities (eg, urbanicity, pollution, neighborhood deprivation, crime, and family disadvantage) are more likely to subsequently develop subclinical psychotic experiences during adolescence (eg, hearing voices, paranoia). However, the pathways through which this occurs have not been previously investigated. We hypothesized that cognitive ability and inflammation would partly explain this association.

STUDY DESIGN

Data were utilized from the Environmental-Risk Longitudinal Twin Study, a cohort of 2232 children born in 1994-1995 in England and Wales and followed to age 18. Socioenvironmental adversities were measured from birth to age 10 and classified into physical risk (defined by high urbanicity and air pollution) and socioeconomic risk (defined by high neighborhood deprivation, neighborhood disorder, and family disadvantage). Cognitive abilities (overall, crystallized, fluid, and working memory) were assessed at age 12; and inflammatory markers (C-reactive protein, interleukin-6, soluble urokinase plasminogen activator receptor) were measured at age 18 from blood samples. Participants were interviewed at age 18 regarding psychotic experiences.

STUDY RESULTS

Higher physical risk and socioeconomic risk were associated with increased odds of psychotic experiences in adolescence. The largest mediation pathways were from socioeconomic risk via overall cognitive ability and crystallized ability, which accounted for ~11% and ~19% of the association with psychotic experiences, respectively. No statistically significant pathways were found via inflammatory markers in exploratory (partially cross-sectional) analyses.

CONCLUSIONS

Cognitive ability, especially crystallized ability, may partly explain the association between childhood socioenvironmental adversity and adolescent psychotic experiences. Interventions to support cognitive development among children living in disadvantaged settings could buffer them against developing subclinical psychotic phenomena.

Cognitive performances across individuals at high genetic risk for schizophrenia, high genetic risk for bipolar disorder, and low genetic risks: a combined polygenic risk score approach

BACKGROUND

Individuals with schizophrenia (SCZ) and bipolar disorder (BD) display cognitive impairments, but the impairments in those with SCZ are more prominent, supported by genetic overlap between SCZ and cognitive impairments. However, it remains unclear whether cognitive performances differ between individuals at high and low genetic risks for SCZ or BD.

METHODS

Using the latest Psychiatric Genomics Consortium (PGC) data, we calculated PGC3 SCZ-, PGC3 BD-, and SCZ v. BD polygenic risk scores (PRSs) in 173 SCZ patients, 70 unaffected first-degree relatives (FRs) and 196 healthy controls (HCs). Based on combinations of three PRS deciles, individuals in the genetic SCZ, genetic BD and low genetic risk groups were extracted. Cognitive performance was assessed by the Brief Assessment of Cognition in Schizophrenia.

RESULTS

SCZ-, BD-, SCZ v. BD-PRSs were associated with case-control status (R2 = 0.020-0.061), and SCZ-PRS was associated with relative-control status (R2 = 0.023). Furthermore, individuals in the highest decile for SCZ PRSs had elevated BD-PRSs [odds ratio (OR) = 6.33] and SCZ v. BD-PRSs (OR = 1.86) compared with those in the lowest decile. Of the three genetic risk groups, the low genetic risk group contained more HCs, whereas the genetic BD and SCZ groups contained more SCZ patients (p < 0.05). SCZ patients had widespread cognitive impairments, and FRs had cognitive impairments that were between those of SCZ patients and HCs (p < 0.05). Cognitive differences between HCs in the low genetic risk group and SCZ patients in the genetic BD or genetic SCZ groups were more prominent (Cohen's d > -0.20) than those between HCs and SCZ patients in the no genetic risk group. Furthermore, SCZ patients in the genetic SCZ group displayed lower scores in verbal fluency and attention than those in the genetic BD group (d > -0.20).

CONCLUSIONS

Our findings suggest that cognitive impairments in SCZ are partially mediated through genetic loadings for SCZ but not BD.

Can Intelligence Affect Alcohol-, Smoking-, and Physical Activity-Related Behaviors? A Mendelian Randomization Study

People with high levels of intelligence are more aware of risk factors, therefore choosing a healthier lifestyle. This assumption seems reasonable, but is it true? Previous studies appear to agree and disagree. To cope with the uncertainty, we designed a mendelian randomization (MR) study to examine the causal effects of genetically proxied intelligence on alcohol-, smoking-, and physical activity (PA)-related behaviors. We obtained genome-wide association study (GWAS) datasets concerning these variables from separate studies or biobanks and used inverse-variance weighted (IVW) or MR-Egger estimator to evaluate the causal effects according to an MR protocol. The MR-Egger intercept test, MR-PRESSO, and funnel plots were employed for horizontal pleiotropy diagnosis. The Steiger test (with reliability test), Cochran's Q test, MR-PRESSO, and leave-one-out method were employed for sensitivity analysis. We found significant or potential effects of intelligence on alcohol dependence (OR = 0.749, p = 0.003), mental and behavioral disorders due to alcohol (OR = 0.814, p = 0.009), smoking (OR = 0.585, p = 0.005), and smoking cessation (OR = 1.334, p = 0.001). Meanwhile, we found significant or potential effects on walking duration (B = -0.066, p < 0.001), walking frequency (B = -0.055, p = 0.031), moderate PA frequency (B = -0.131, p < 0.001), and vigorous PA frequency (B = -0.070, p = 0.001), but all in a negative direction. In conclusion, our findings reinforce some existing knowledge, indicate the complexity of the health impacts of human intelligence, and underline the value of smoking and alcohol prevention in less intelligent populations. Given the existing limitations in this study, particularly the potential reverse causality in some estimations, re-examinations are warranted in future research.

How do nurses work in chronic management in the age of artificial intelligence? development and future prospects

AI is undeniably revolutionizing medical research and patient care across diverse fields. Chronic disease nursing care, a pivotal aspect of clinical management, has significantly reaped the benefits of AI across numerous dimensions. Understanding the operational principles of artificial intelligence before implementation is crucial, avoiding indiscriminate replacement of all tasks with AI. Nurses serve as the primary force in symptom group research, expanding beyond diabetes to encompass various chronic diseases; their primary responsibility involves recording patients' daily symptoms and vital signs. However, a substantial portion of current AI research excludes nurses from the developmental phase, encompassing them solely in user and feedback populations. The comprehensive design of the symptom analysis and long-term management approach necessitates the guidance and oversight of nurses; however, their current insufficient involvement might stem from nursing staff's comparatively limited comprehension of AI and their ambiguous perception of their role's value in AI. Therefore, an imperative exploration of nurses' roles in symptom analysis and long-term management, leveraging the latest research in these areas, is vital to pinpoint breakthroughs in nurses' AI involvement in the future.

Investigating genetic overlaps of the genetic factor differentiating schizophrenia from bipolar disorder with cognitive function and hippocampal volume

Schizophrenia and bipolar disorder display clinical similarities and dissimilarities. We investigated whether the genetic factor differentiating schizophrenia from bipolar disorder is genetically associated with cognitive phenotypes and hippocampal volumes. We revealed genetic overlaps of the genetic differentiating factor with low general cognitive ability, low childhood IQ, low educational attainment and reduced hippocampal volumes. The genetic correlations with low general cognitive ability and reduced hippocampal volumes were associated with risk of schizophrenia, whereas the genetic correlations with high childhood IQ and educational attainment were associated with risks of bipolar disorder. These findings suggest these disorders have disorder-specific genetic factors related to clinical phenotypes.