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Individuals with a family history of bipolar disorder are at increased risk of developing affective psychopathology. Longitudinal imaging studies in young people with familial risk have been limited, and cortical developmental trajectories in the progression towards illness remain obscure.
Aims
To establish high-resolution longitudinal differences in cortical structure that are associated with risk of bipolar disorder.
Method
Using structural magnetic resonance imaging data from 217 unrelated ‘Bipolar Kids and Sibs study’ participants (baseline n = 217, follow-up n = 152), we examined changes over a 2-year period in cortical area, thickness and volume, measured at each vertex across the cortical surface. Groups comprised 105 ‘high-risk’ participants with a first-degree relative with bipolar disorder (female n = 64; age in years: M (mean) = 20.9, s.d. = 5.5) and 112 controls with no familial psychiatric history (females n = 60; age in years: M = 22.4, s.d. = 3.7).
Results
Accelerated thickness and volume reductions over time were observed in ‘high-risk’ individuals across multiple cortical regions, relative to controls, including right lateral orbitofrontal thickness (β = 0.033, P < 0.001) and inferior frontal volume (β = 0.021, P < 0.001). These differences were observed after controlling for age, sex, ancestry, current medication status, lifetime psychiatric diagnoses and measures of gross brain morphology.
Conclusions
Longitudinal group differences suggest the presence of thicker cortex in familial ‘high-risk’ individuals at earlier developmental stages, followed by accelerated thinning towards the typical age of bipolar disorder onset. Future examination of genetic and environmental components of familial risk and the mechanistic nature (pathological or protective) of cortical-trajectory differences over time may facilitate the identification of prodromal biomarkers and opportunities for early clinical intervention.
Rallidae are frequent colonists of oceanic islands and are often susceptible to introduced predators. The Tristan Moorhen Gallinula nesiotis was endemic to Tristan da Cunha, South Atlantic and is thought to have gone extinct in the late nineteenth century. The closely related Gough Moorhen G. comeri was introduced to Tristan da Cunha from neighbouring Gough Island in 1956. We report historical records of their spread across Tristan da Cunha and the results of a population survey undertaken in February–March 2024. Gough Moorhens are now found across the entire island wherever there is suitable habitat from sea level to above 900 m elevation. Gough Moorhens prefer fern bush habitat on the Base, the plateau above the steep coastal cliffs. The total population is approximately 41,500 birds (95% confidence interval 24,000–72,000). Our density estimates (3–6 birds/ha) are similar to estimates for Gough Moorhens on Gough Island before the post-2021 population decline and are at the higher end of densities reported for oceanic island rallids, suggesting that the Tristan da Cunha population may be near carrying capacity.
Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).
Aims
We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.
Method
Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.
Results
Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.
Conclusions
We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.
Wilkins’s Finch Nesospiza wilkinsi is endemic to Nightingale Island (2.5 km2), Tristan da Cunha. It feeds on the woody fruits of the Island Tree Phylica arborea and in 2017 had a population of 120 breeding pairs. In 2021 it was uplisted from “Endangered” to “Critically Endangered” following damage to P. arborea woodland during severe storms in 2019. During a brief visit to Nightingale in February 2024, we confirmed that the finch population in the area of storm-damaged woodland has decreased by up to 75%, but the density in other areas was similar to that prior to 2019. Extrapolating from the 2017 survey, we estimated the current population to be 60–90 breeding pairs. Surveys of P. arborea structure in the storm-affected area indicated that some large trees had survived, despite being flattened, that recruitment of new trees is occurring, and that fruit loads on surviving trees are similar to those in 2017. Satellite imagery from 2005 showed similar woodland loss during another severe storm in 2001 to that experienced in 2019, indicating that the finch has survived similar events in the past. Coupled with the successful release of a biological control agent to limit the impact of the introduced brown soft scale Coccus hesperidum on Phylica fruit production, the future prospect for Wilkins’s Finch is less bleak than previously thought. However, the risk that global warming is increasing the frequency of severe storms remains a concern. Planting more woodland patches in sheltered areas would help to offset future storm damage.
Refugees are at an elevated risk of some mental disorders with studies highlighting the contributing role of post-migration factors. Studies of migrant groups show neighborhood social composition, such as ethnic density, to be important. This is the first longitudinal study to examine this question for refugees and uses a novel quasi-experimental design.
Methods
We followed a cohort of 44 033 refugees from being first assigned housing under the Danish dispersal policy, operating from 1986 to 1998, until 2019. This comprised, in effect, a natural experiment whereby the influence of assigned neighborhood could be determined independently of endogenous factors. We examined three aspects of neighborhood social composition: proportion of co-nationals, refugees, and first-generation migrants; and subsequent incidence of different mental disorders.
Results
Refugees assigned to neighborhoods with fewer co-nationals (lowest v. highest quartile) were more likely to receive a subsequent diagnosis of non-affective psychosis, incident rate ratio (IRR) 1.25 (95% confidence interval (CI) 1.06–1.48), and post-traumatic stress disorder (PTSD), IRR 1.21 (95% CI I.05–1.39). A comparable but smaller effect was observed for mood disorders but none observed for stress disorders overall. Neighborhood proportion of refugees was less clearly associated with subsequent mental disorders other than non-affective psychosis, IRR 1.24 (95% CI 1.03–1.50). We found no statistically significant associations with proportion of migrants.
Conclusions
For refugees, living in a neighborhood with a lower proportion of co-nationals is related to subsequent increased risk of diagnosed mental disorders particularly non-affective psychosis and PTSD.
Globally, mental disorders account for almost 20% of disease burden and there is growing evidence that mental disorders are socially determined. Tackling the United Nations Sustainable Development Goals (UN SDGs), which address social determinants of mental disorders, may be an effective way to reduce the global burden of mental disorders. We conducted a systematic review of reviews to examine the evidence base for interventions that map onto the UN SDGs and seek to improve mental health through targeting known social determinants of mental disorders. We included 101 reviews in the final review, covering demographic, economic, environmental events, neighborhood, and sociocultural domains. This review presents interventions with the strongest evidence base for the prevention of mental disorders and highlights synergies where addressing the UN SDGs can be beneficial for mental health.
Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.
Methods:
We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.
Results:
BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.
Conclusions:
We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
Aims
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
Method
This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
Results
The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
Conclusions
Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
While previous studies have suggested that higher levels of cognitive performance may be related to greater wellbeing and resilience, little is known about the associations between neural circuits engaged by cognitive tasks and wellbeing and resilience, and whether genetics or environment contribute to these associations.
Methods
The current study consisted of 253 monozygotic and dizygotic adult twins, including a subsample of 187 early-life trauma-exposed twins, with functional Magnetic Resonance Imaging data from the TWIN-E study. Wellbeing was measured using the COMPAS-W Wellbeing Scale while resilience was defined as a higher level of positive adaptation (higher levels of wellbeing) in the presence of trauma exposure. We probed both sustained attention and working memory processes using a Continuous Performance Task in the scanner.
Results
We found significant negative associations between resilience and activation in the bilateral anterior insula engaged during sustained attention. Multivariate twin modelling showed that the association between resilience and the left and right insula activation was mostly driven by common genetic factors, accounting for 71% and 87% of the total phenotypic correlation between these variables, respectively. There were no significant associations between wellbeing/resilience and neural activity engaged during working memory updating.
Conclusions
The findings suggest that greater resilience to trauma is associated with less activation of the anterior insula during a condition requiring sustained attention but not working memory updating. This possibly suggests a pattern of ‘neural efficiency’ (i.e. more efficient and/or attenuated activity) in people who may be more resilient to trauma.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
Aims
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Method
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Results
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
Conclusions
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Although mental wellbeing has been linked with positive health outcomes, including longevity and improved emotional and cognitive functioning, studies examining the underlying neural mechanisms of both subjective and psychological wellbeing have been sparse. We assessed whether both forms of wellbeing are associated with neural activity engaged during positive and negative emotion processing and the extent to which this association is driven by genetics or environment.
Methods
We assessed mental wellbeing in 230 healthy adult monozygotic and dizygotic twins using a previously validated questionnaire (COMPAS-W) and undertook functional magnetic resonance imaging during a facial emotion viewing task. We used linear mixed models to analyse the association between COMPAS-W scores and emotion-elicited neural activation. Univariate twin modelling was used to evaluate heritability of each brain region. Multivariate twin modelling was used to compare twin pairs to assess the contributions of genetic and environmental factors to this association.
Results
Higher levels of wellbeing were associated with greater neural activity in the dorsolateral prefrontal cortex, localised in the right inferior frontal gyrus (IFG), in response to positive emotional expressions of happiness. Univariate twin modelling showed activity in the IFG to have 20% heritability. Multivariate twin modelling suggested that the association between wellbeing and positive emotion-elicited neural activity was driven by common variance from unique environment (r = 0.208) rather than shared genetics.
Conclusions
Higher mental wellbeing may have a basis in greater engagement of prefrontal neural regions in response to positive emotion, and this association may be modifiable by unique life experiences.
Many studies report an ethnic density effect whereby psychosis incidence among ethnic minority groups is higher in low co-ethnic density areas. It is unclear whether an equivalent density effect applies with other types of socioeconomic disadvantages.
Methods
We followed a population cohort of 2 million native Danes comprising all those born on 1st January 1965, or later, living in Denmark on their 15th birthday. Socioeconomic disadvantage, based on parents' circumstances at age 15 (low income, manual occupation, single parent and unemployed), was measured alongside neighbourhood prevalence of these indices.
Results
Each indicator was associated with a higher incidence of non-affective psychosis which remained the same, or was slightly reduced, if neighbourhood levels of disadvantage were lower. For example, for individuals from a low-income background there was no difference in incidence for those living in areas where a low-income was least common [incidence rate ratio (IRR) 1.01; 95% confidence interval (CI) 0.93–1.10 v. those in the quintile where a low income was most common. Typically, differences associated with area-level disadvantage were the same whether or not cohort members had a disadvantaged background; for instance, for those from a manual occupation background, incidence was lower in the quintile where this was least v. most common (IRR 0.83; 95% CI 0.71–0.97), as it was for those from a non-manual background (IRR 0.77; 95% CI 0.67–0.87).
Conclusion
We found little evidence for group density effects in contrast to previous ethnic density studies. Further research is needed with equivalent investigations in other countries to see if similar patterns are observed.
Psychosis is more prevalent among people in prison compared with the community. Early detection is important to optimise health and justice outcomes; for some, this may be the first time they have been clinically assessed.
Aims
Determine factors associated with a first diagnosis of psychosis in prison and describe time to diagnosis from entry into prison.
Method
This retrospective cohort study describes individuals identified for the first time with psychosis in New South Wales (NSW) prisons (2006–2012). Logistic regression was used to identify factors associated with a first diagnosis of psychosis. Cox regression was used to describe time to diagnosis from entry into prison.
Results
Of the 38 489 diagnosed with psychosis for the first time, 1.7% (n = 659) occurred in prison. Factors associated with an increased likelihood of being diagnosed in prison (versus community) were: male gender (odds ratio (OR) = 2.27, 95% CI 1.79–2.89), Aboriginality (OR = 1.81, 95% CI 1.49–2.19), older age (OR = 1.70, 95% CI 1.37–2.11 for 25–34 years and OR = 1.63, 95% CI 1.29–2.06 for 35–44 years) and disadvantaged socioeconomic area (OR = 4.41, 95% CI 3.42–5.69). Eight out of ten were diagnosed within 3 months of reception.
Conclusions
Among those diagnosed with psychosis for the first time, only a small number were identified during incarceration with most identified in the first 3 months following imprisonment. This suggests good screening processes are in place in NSW prisons for detecting those with serious mental illness. It is important these individuals receive appropriate care in prison, have the opportunity to have matters reheard and possibly diverted into treatment, and are subsequently connected to community mental health services on release.
With significant numbers of individuals in the criminal justice system having mental health problems, court-based diversion programmes and liaison services have been established to address this problem.
Aims
To examine the effectiveness of the New South Wales (Australia) court diversion programme in reducing re-offending among those diagnosed with psychosis by comparing the treatment order group with a comparison group who received a punitive sanction.
Method
Those with psychoses were identified from New South Wales Ministry of Health records between 2001 and 2012 and linked to offending records. Cox regression models were used to identify factors associated with re-offending.
Results
A total of 7743 individuals were identified as diagnosed with a psychotic disorder prior to their court finalisation date for their first principal offence. Overall, 26% of the cohort received a treatment order and 74% received a punitive sanction. The re-offending rate in the treatment order group was 12% lower than the punitive sanction group. ‘Acts intended to cause injury’ was the most common type of the first principal offence for the treatment order group compared with the punitive sanction group (48% v. 27%). Drug-related offences were more likely to be punished with a punitive sanction than a treatment order (12% v. 2%).
Conclusions
Among those with a serious mental illness (i.e. psychosis), receiving a treatment order by the court rather than a punitive sanction was associated with reduced risk for subsequent offending. We further examined actual mental health treatment received and found that receiving no treatment following the first offence was associated with an increased risk of re-offending and, so, highlighting the importance of treatment for those with serious mental illness in the criminal justice system.
Depression is associated with increased mortality, however, little is known about its variation by ethnicity.
Methods
We conducted a cohort study of individuals with ICD-10 unipolar depression from secondary mental healthcare, from an ethnically diverse location in southeast London, followed for 8 years (2007–2014) linked to death certificates. Age- and sex- standardised mortality ratios (SMRs), with the population of England and Wales as a standard population were derived. Hazard ratios (HRs) for mortality were derived through multivariable regression procedures.
Results
Data from 20 320 individuals contributing 91 635 person-years at risk with 2366 deaths were used for analyses. SMR for all-cause mortality in depression was 2.55(95% CI 2.45–2.65), with similar trends by ethnicity. Within the cohort with unipolar depression, adjusted HR (aHRs) for all-cause mortality in ethnic minority groups relative to the White British group were 0.62(95% CI 0.53–0.74) (Black Caribbean), 0.53(95% CI 0.39–0.72) (Black African) and 0.69(95% CI 0.52–0.90) (South Asian). Male sex and alcohol/substance misuse were associated with an increased all-cause mortality risk [aHR:1.94 (95% CI 1.68–2.24) and aHR:1.18 (95% CI 1.01–1.37) respectively], whereas comorbid anxiety was associated with a decreased risk [aHR: 0.72(95% CI 0.58–0.89)]. Similar associations were noted for natural-cause mortality. Alcohol/substance misuse and male sex were associated with a near-doubling in unnatural-cause mortality risk, whereas Black Caribbean individuals with depression had a reduced unnatural-cause mortality risk, relative to White British people with depression.
Conclusions
Although individuals with depression experience an increased mortality risk, marked heterogeneity exists by ethnicity. Research and practice should focus on addressing tractable causes underlying increased mortality in depression.
This article looks at the use of large datasets of health records, typically linked with other data sources, in mental health research. The most comprehensive examples of this kind of ‘big data’ are typically found in Scandinavian countries, although there are also many useful sources in the UK. There are a number of promising methodological innovations from studies using big data in UK mental health research, including: hybrid study designs, data linkage and enhanced study recruitment. It is, however, important to be aware of the limitations of research using big data, particularly the various pitfalls in analysis. We therefore caution against abandoning traditional research designs, and argue that other data sources are equally valuable and, ideally, research should incorporate data from a range of sources.
LEARNING OBJECTIVES
• Be aware of major big data resources relevant to mental health research
• Be aware of key advantages and innovative study designs using these data sources
• Understand the inherent limitations to studies reliant on big data alone
To assess the association of fish consumption with risk of dementia and its dose–response relationship, and investigate variations in the association among low-, middle- and high-income countries.
Design
A new community-based cross-sectional study and a systematic literature review.
Settings
Urban and rural communities in China; population-based studies systematically searched from worldwide literature.
Subjects
Chinese adults aged ≥60 years in six provinces (n 6981) took part in a household health survey of dementia prevalence and risk factors. In addition, 33 964 participants from eleven published and eligible studies were included in the systematic review and meta-analysis.
Results
In the new study in China, 326 participants were diagnosed with dementia (4·7 %); those who consumed any amount of fish in the past two years v. those who consumed no fish had reduced risk of dementia (adjusted OR=0·73, 95 % CI 0·64, 0·99), but the dose–response relationship was not statistically significant. The meta-analysis of available data from the literature and the new study showed relative risk (RR) of dementia of 0·80 (95 % CI 0·74, 0·87) for people with fish consumption; the impact was similar among countries with different levels of income. Pooled dose–response data revealed RR (95 % CI) of 0·84 (0·72, 0·98), 0·78 (0·68, 0·90) and 0·77 (0·61, 0·98) in people with low, middle and high consumption of fish, respectively. Corresponding figures for Alzheimer’s disease were 0·88 (0·74, 1·04), 0·79 (0·65, 0·96) and 0·67 (0·58, 0·78), respectively.
Conclusions
Greater consumption of fish is associated with a lower risk of dementia. Increasing fish consumption may help prevent dementia worldwide regardless of income level.
Advances in information technology and data storage, so-called ‘big data’, have the potential to dramatically change the way we do research. We are presented with the possibility of whole-population data, collected over multiple time points and including detailed demographic information usually only available in expensive and labour-intensive surveys, but at a fraction of the cost and effort. Typically, accounts highlight the sheer volume of data available in terms of terabytes (1012) and petabytes (1015) of data while charting the exponential growth in computing power we can use to make sense of this. Presented with resources of such dizzying magnitude it is easy to lose sight of the potential limitations when the amount of data itself appears unlimited. In this short account I look at some recent advances in electronic health data that are relevant for mental health research while highlighting some of the potential pitfalls.
Bipolar disorder is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for bipolar disorder in the expression quantitative trait loci (eQTL) in the brain.
Aims
We sought to assess the impact of eQTL variants on bipolar disorder risk by combining data from both bipolar disorder genome-wide association studies (GWAS) and brain eQTL.
Method
To detect single nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with bipolar disorder, we jointly analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (n = 5775) and cognitive performance(n = 342) among healthy individuals.
Results
Integrative analysis revealed a significant association between a brain eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes factor = 5.48; bipolar disorder P = 5.85×10–5). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and bipolar disorder susceptibility (P =3.54×10–8). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy individuals.
Conclusions
Our findings suggest that 20q11.22 is likely a risk region for bipolar disorder; they also highlight the informative value of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex disorders, such as bipolar disorder.