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BackgroundClozapine remains the only evidence-based antipsychotic for treatment-resistant schizophrenia (TRS). The ability to predict which patients with their first onset of schizophrenia would subsequently meet criteria for treatment resistance (TR) could help to diminish the severe functional disability which may ensue if TR is not recognized and correctly treated.MethodThis is a 5-year longitudinal assessment of clinical outcomes in a cohort of 246 first-episode schizophrenia spectrum patients recruited as part of the NIHR Genetics and Psychosis (GAP) study conducted in South London from 2005 to 2010. We examined the relationship between baseline demographic and clinical measures and the emergence of TR. TR status was determined from a review of electronic case records. We assessed for associations with early-, and late-onset TR, and non-TR, and differences between those TR patients treated with clozapine and those who were not.ResultsSeventy per cent (n = 56) of TR patients, and 23% of the total study population (n = 246) were treatment resistant from illness onset. Those who met criteria for TR during the first 5 years of illness were more likely to have an early age of first contact for psychosis (<20 years) [odds ratio (OR) 2.49, 95% confidence interval (CI) 1.25–4.94] compared to those with non-TR. The relationship between an early age of first contact (<20 years) and TR was significant in patients of Black ethnicity (OR 3.71, 95% CI 1.44–9.56); and patients of male gender (OR 3.13 95% CI 1.35–7.23).ConclusionsFor the majority of the TR group, antipsychotic TR is present from illness onset, necessitating increased consideration for the earlier use of clozapine. [ABSTRACT FROM PUBLISHER]

Background and Aims: The extent to which heavy smoking and retirement risk are causally related remains to be determined. To overcome the endogeneity of heavy smoking behaviour, we employed a novel approach by exploiting the genetic predisposition to heavy smoking, as measured with a polygenic risk score (PGS), in a Mendelian Randomisation approach., Methods: 8164 participants (mean age 68.86 years) from the English Longitudinal Study of Ageing had complete data on smoking behaviour, employment and a heavy smoking PGS. Heavy smoking was indexed as smoking at least 20 cigarettes a day. A time-to-event Mendelian Randomization (MR) analysis, using a complementary log-log (cloglog) link function, was employed to model the retirement risk., Results: Our results show that being a heavy smoker significantly increases the risk of retirement (β = 1.324, standard error = 0.622, p < 0.05). Results were robust to a battery of checks and a placebo analysis considering the never-smokers., Conclusions: Overall, our findings support a causal pathway from heavy smoking to earlier retirement., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Background: A clinical tool to estimate the risk of treatment-resistant schizophrenia (TRS) in people with first-episode psychosis (FEP) would inform early detection of TRS and overcome the delay of up to 5 years in starting TRS medication., Aims: To develop and evaluate a model that could predict the risk of TRS in routine clinical practice., Method: We used data from two UK-based FEP cohorts (GAP and AESOP-10) to develop and internally validate a prognostic model that supports identification of patients at high-risk of TRS soon after FEP diagnosis. Using sociodemographic and clinical predictors, a model for predicting risk of TRS was developed based on penalised logistic regression, with missing data handled using multiple imputation. Internal validation was undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. Interviews and focus groups with clinicians were conducted to establish clinically relevant risk thresholds and understand the acceptability and perceived utility of the model., Results: We included seven factors in the prediction model that are predominantly assessed in clinical practice in patients with FEP. The model predicted treatment resistance among the 1081 patients with reasonable accuracy; the model's C-statistic was 0.727 (95% CI 0.723-0.732) prior to shrinkage and 0.687 after adjustment for optimism. Calibration was good (expected/observed ratio: 0.999; calibration-in-the-large: 0.000584) after adjustment for optimism., Conclusions: We developed and internally validated a prediction model with reasonably good predictive metrics. Clinicians, patients and carers were involved in the development process. External validation of the tool is needed followed by co-design methodology to support implementation in early intervention services.

Dog ownership has been associated with several complex traits, and there is evidence of genetic influence. We performed a genome-wide association study of dog ownership through a meta-analysis of 31,566 Swedish twins in 5 discovery cohorts and an additional 65,986 European-ancestry individuals in 3 replication cohorts from Sweden, Norway, and the United Kingdom. Association tests with >7.4 million single-nucleotide polymorphisms were meta-analyzed using a fixed effect model after controlling for population structure and relatedness. We identified 2 suggestive loci using discovery cohorts, which did not reach genome-wide significance after meta-analysis with replication cohorts. Single-nucleotide polymorphism-based heritability of dog ownership using linkage disequilibrium score regression was estimated at 0.123 (CI 0.038-0.207) using the discovery cohorts and 0.018 (CI -0.002 to 0.039) when adding in replication cohorts. Negative genetic correlation with complex traits including type 2 diabetes, depression, neuroticism, and asthma was only found using discovery summary data. Furthermore, we did not identify any genes/gene-sets reaching even a suggestive level of significance. This genome-wide association study does not, by itself, provide clear evidence on common genetic variants that influence dog ownership among European-ancestry individuals., Competing Interests: Conflict of interest KHL, CT, and the members of 23andMe Research Team are listed as authors or were employed by and hold stock or stock options in 23andMe, Inc., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.)

Background: This study aims to understand the mechanisms contributing to the elevated risk of depression among sexual minority older adults compared to heterosexuals. Specifically, the role of loneliness as a potential mediator is investigated to inform targeted interventions for preventing depression in sexual minority populations., Methods: Data from the English Longitudinal Study of Ageing, focusing on adults aged over 50, were analysed. Sexual orientation (sexual minority or heterosexual) and loneliness scores (UCLA scale) were assessed at wave six (2010-2011), while depressive symptoms (CESD) were assessed at wave seven (2013-14). Linear regression models and mediation analyses, using g-computation formula and adjusted for confounders, were conducted., Results: The sample included 6794 participants, with 478 (7.0 %) identifying as sexual minorities. After adjustments, sexual minorities scored higher on depressive symptoms at wave seven (mean difference): 0.23, 95 % CI 0.07 to 0.39) and loneliness at wave six (MD: 0.27, 95 % CI 0.08 to 0.46). Loneliness was positively associated with depressive symptoms (coefficient: 0.27, 95 % CI 0.26 to 0.29). In mediation analyses, loneliness explained 15 % of the association between sexual orientation and subsequent depressive symptoms., Limitations: The dataset used sexual behaviour rather than desire and identity, potentially skewing representation of sexual minorities. Additionally, transgender older adults were not included due to limited gender diversity reported within the ELSA dataset., Conclusions: Loneliness appears to be a significant modifiable mechanism contributing to the heightened risk of depressive symptoms in sexual minority older adults compared with their heterosexual counterparts., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to declare., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objective: Understanding prognosis is critical to anticipating public health needs and providing care to individuals with psychotic disorders. However, the long-term course of remission and recovery remains unclear. In this study, the most common trajectories of illness course are described for a cohort of individuals followed for 25 years since first admission for psychosis., Methods: Participants are from the Suffolk County Mental Health Project, an epidemiological study of first-admission psychosis. Data for the present study was collected from six follow-ups, with 311 individuals assessed at the 25-year follow-up. Common patterns of remission and recovery were assessed in the baseline cohort of 591 individuals and the subsample from the 25-year follow up., Results: In the baseline cohort and the 25-year subsample, the most common trajectory for individuals with schizophrenia spectrum disorders was no remission and no recovery. Among individuals with other psychotic disorders, in both the baseline and 25-year cohorts, the modal pattern was one of intermittent remission and recovery. Individuals with other psychotic disorders were more likely to experience stable remission (15.1%) and stable recovery (21.1%), outcomes that were rare among individuals with schizophrenia spectrum disorders (0% and 0.6%, respectively)., Conclusions: The modal longitudinal pattern for individuals with other psychoses is one of multiple transitions into and out of symptomatic and functional recovery. Engagement in a long-term health care plan may help individuals detect and respond to these changes. Sustained remission and recovery are rare among people with schizophrenia spectrum disorders. Efforts should be directed toward developing more effective treatments for this population., Competing Interests: Dr. Jonas has served as a consultant for Allia Health. The other authors report no financial relationships with commercial interests.

Psychosocial stress exposure can disturb communication signals between the immune, nervous, and endocrine systems that are intended to maintain homeostasis. This dysregulation can provoke a negative feedback loop between each system that has high pathological risk. Here, we explore patterns of immune-neuroendocrine activity and the role of stress. Using data from the English Longitudinal Study of Ageing (ELSA), we first identified the latent structure of immune-neuroendocrine activity (indexed by high sensitivity C-reactive protein [CRP], fibrinogen [Fb], hair cortisol [cortisol], and insulin growth-factor-1 [IGF-1]), within a population-based cohort using latent profile analysis (LPA). Then, we determined whether life stress was associated with membership of different immune-neuroendocrine profiles. We followed 4,934 male and female participants, with a median age of 65 years, over a four-year period (2008-2012). A three-class LPA solution offered the most parsimonious fit to the underlying immune-neuroendocrine structure in the data, with 36 %, 40 %, and 24 % of the population belonging to profiles 1 (low-risk), 2 (moderate-risk), and 3 (high-risk), respectively. After adjustment for genetic predisposition, sociodemographics, lifestyle, and health, higher exposure to stress was associated with a 61 % greater risk of belonging to the high-risk profile (RRR: 1.61; 95 %CI = 1.23-2.12, p = 0.001), but not the moderate-risk profile (RRR = 1.10, 95 %CI = 0.89-1.35, p = 0.401), as compared with the low-risk profile four years later. Our findings extend existing knowledge on psychoneuroimmunological processes, by revealing how inflammation and neuroendocrine activity cluster in a representative sample of older adults, and how stress exposure was associated with immune-neuroendocrine responses over time., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

To deepen the understanding of genetic mechanisms influencing mortality risk, we investigated the impact of genetic predisposition to longevity and APOE-ε4, on all-cause mortality and specific causes of mortality. We further investigated the mediating effects of dementia on these relationships. Using data on 7 131 adults aged ≥50 years (mean = 64.7 years, standard deviation [SD] = 9.5) from the English Longitudinal Study of Aging, genetic predisposition to longevity was calculated using the polygenic score approach (PGSlongevity). APOE-ε4 status was defined according to the absence or presence of ε4 alleles. The causes of death were ascertained from the National Health Service central register, which was classified into cardiovascular diseases, cancers, respiratory illness, and all other causes of mortality. Of the entire sample, 1 234 (17.3%) died during an average 10-year follow-up. One-SD increase in PGSlongevity was associated with a reduced risk for all-cause mortality (hazard ratio [HR] = 0.93, 95% confidence interval [CI]: 0.88-0.98, p = .010) and mortalities due to other causes (HR = 0.81, 95% CI: 0.71-0.93, p = .002) in the following 10 years. In gender-stratified analyses, APOE-ε4 status was associated with a reduced risk for all-cause mortality and mortalities related to cancers in women. Mediation analyses estimated that the percent excess risk of APOE-ε4 on other causes of mortality risk explained by the dementia diagnosis was 24%, which increased to 34% when the sample was restricted to adults who were aged ≤75 years old. To reduce the mortality rate in adults who are aged ≥50 years old, it is essential to prevent dementia onset in the general population., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America.)

Suboptimal sleep durations and depression frequently cooccur. Short-sleep and long-sleep are commonly thought of as symptoms of depression, but a growing literature suggests that they may be prodromal. While each represents a process of mutual influence, the directionality between them remains unclear. Using polygenic scores (PGS), we investigate the prospective direction involved in suboptimal sleep durations and depression. Male and female participants, aged ≥50, were recruited from the English Longitudinal Study of Ageing (ELSA). PGS for sleep duration, short-sleep, and long-sleep were calculated using summary statistics data from the UK Biobank cohort. Sleep duration, categorised into short-sleep ("≤5 h"), optimal-sleep (">5 to <9 h"), and long-sleep ("≥9 h"), was measured at baseline and across an average 8-year follow-up. Subclinical depression (Centre for Epidemiological Studies Depression Scale [≥4 of 7]) was also ascertained at baseline and across an average 8-year follow-up. One standard deviation increase in PGS for short-sleep was associated with 14% higher odds of depression onset (95% CI = 1.03-1.25, p = 0.008). However, PGS for sleep duration (OR = 0.92, 95% CI = 0.84-1.00, p = 0.053) and long-sleep (OR = 0.97, 95% CI = 0.89-1.06, p = 0.544) were not associated with depression onset during follow-up. During the same period, PGS for depression was not associated with overall sleep duration, short-sleep, or long-sleep. Polygenic predisposition to short-sleep was associated with depression onset over an average 8-year period. However, polygenic predisposition to depression was not associated with overall sleep duration, short-sleep or long-sleep, suggesting different mechanisms underlie the relationship between depression and the subsequent onset of suboptimal sleep durations in older adults., (© 2023. Springer Nature Limited.)

Objectives: An association between type 2 diabetes (T2DM) and schizophrenia has long been observed, and recent research revealed presence of shared genetic factors. However, epidemiological evidence was inconsistent, some reported insignificant contribution of genetic factors to T2DM-schizophrenia comorbidity. Prior works studied people with schizophrenia, particularly, antipsychotic-naive patients, or those during the first psychotic experience to limit schizophrenia-related environmental factors. In contrast, we controlled such factors by utilizing a general population sample of individuals undiagnosed with schizophrenia. We hypothesized that if schizophrenia genetics impact T2DM development and such impact is not fully mediated by schizophrenia-related environment, people with high polygenic schizophrenia risk would exhibit elevated T2DM incidence., Methods: Using a population-representative sample of adults aged ≥50 from English Longitudinal Study of Ageing ( n  = 5968, 493 T2DM cases, average follow-up 8.7 years), we investigated if schizophrenia polygenic risk score (PGS-SZ) is associated with T2DM onset. A proportional hazards model with interval censoring was adjusted for age and sex (Model 1), and age, sex, BMI, hypertension, cardiovascular diseases, exercise, smoking, depressive symptoms and T2DM polygenic risk score (Model 2). According to the power calculations, hazard rates > 1.14 per standard deviation in PGS-SZ could be detected., Results: We did not observe a significant association between PGS-SZ and T2DM incidence (hazard ratio 1.04; 95% CI 0.93-1.15; and 1.01, 95% CI 0.94-1.09)., Conclusion: Our results suggest low contribution of the intrinsic biological mechanisms driven by the polygenic risk of schizophrenia on future T2DM onset. Further research is needed., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Considering the co-morbidity of major psychiatric disorders and intelligence with smoking, to increase our understanding of why some people take up smoking or continue to smoke, while others stop smoking without progressing to nicotine dependence, we investigated the genetic propensities to psychiatric disorders and intelligence as determinants of smoking initiation, heaviness of smoking and smoking cessation in older adults from the general population., Results: Having utilised data from the English Longitudinal Study of Ageing (ELSA), our results showed that one standard deviation increase in MDD-PGS was associated with increased odds of being a moderate-heavy smoker (odds ratio [OR] = 1.11, SE = 0.04, 95%CI = 1.00-1.24, p = 0.028). There were no other significant associations between SZ-PGS, BD-PGS, or IQ-PGS and smoking initiation, heaviness of smoking and smoking cessation in older adults from the general population in the UK., Conclusions: Smoking is a behaviour that does not appear to share common genetic ground with schizophrenia, bipolar disorders, and intelligence in older adults, which may suggest that it is more likely to be modifiable by smoking cessation interventions. Once started to smoke, older adults with a higher polygenic predisposition to major depressive disorders are more likely to be moderate to heavy smokers, implying that these adults may require targeted smoking cessation services., (© 2023. The Author(s).)

Background: As an accelerated cognitive decline frequently heralds onset of severe neuropathological disorders, understanding the source of individual differences in withstanding the onslaught of cognitive ageing may highlight how best cognitive abilities may be retained into advanced age., Methods: Using a population representative sample of 5088 adults aged •50 years from the English Longitudinal Study of Ageing, we investigated relationships of polygenic predisposition to general cognition with a rate of change in cognition during a 10-year follow-up period. Polygenic predisposition was measured with polygenic scores for general cognition (GC-PGS). Cognition was measured employing tests for verbal memory and semantic fluency., Results: The average baseline memory score was 11.1 (s.d. = 2.9) and executive function score was 21.5 (s.d. = 5.8). An increase in GC-PGS by one standard deviation (1-s.d.) was associated with a higher baseline verbal memory by an average 0.27 points (95% CI 0.19-0.34, p < 0.001). Similarly, 1-s.d. increase in GC-PGS was associated with a higher semantic fluency score at baseline in the entire sample ( β = 0.45, 95% CI 0.27-0.64, p < 0.001). These associations were significant for women and men, and all age groups. Nonetheless, 1-s.d. increase in GC-PGS was not associated with decreases in verbal memory nor semantic fluency during follow-up in the entire sample, as well stratified models by sex and age., Conclusion: Although common genetic variants associated with general cognition additively are associated with a stable surplus to cognition in adults, a polygenic predisposition to general cognition is not associated with age-related cognitive decline during a 10-year follow-up.

Background: Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia, with recent research finding systematic biological differences between antipsychotic resistant and responsive patients. Our aim was to determine whether cognitive impairment at first episode significantly differs between future antipsychotic responders and resistant cases., Methods: Analysis of data from seven international cohorts of first-episode psychosis (FEP) with cognitive data at baseline (N = 683) and follow-up data on antipsychotic treatment response: 605 treatment responsive and 78 treatment resistant cases. Cognitive measures were grouped into seven cognitive domains based on the pre-existing literature. We ran multiple imputation for missing data and used logistic regression to test for associations between cognitive performance at FEP and treatment resistant status at follow-up., Results: On average patients who were future classified as treatment resistant reported poorer performance across most cognitive domains at baseline. Univariate logistic regressions showed that antipsychotic treatment resistance cases had significantly poorer IQ/general cognitive functioning at FEP (OR = 0.70, p = .003). These findings remained significant after adjusting for additional variables in multivariable analyses (OR = 0.76, p = .049)., Conclusions: Although replication in larger studies is required, it appears that deficits in IQ/general cognitive functioning at first episode are associated with future treatment resistance. Cognitive variables may be able to provide further insight into neurodevelopmental factors associated with treatment resistance or act as early predictors of treatment resistance, which could allow prompt identification of refractory illness and timely interventions., Competing Interests: Declaration of competing interest J.T.R.W. is an investigator on a grant from Takeda Pharmaceuticals Ltd. to Cardiff University, for a project unrelated to the work presented here. S.E.S. is employed on this grant. M.D.F. has received a fee for educational seminars from Lundbeck and Janssen. O.A.A. is a consultant to HealthLytix and has received speakers honorarium from Lundbeck and Sunovion. T.R.E.B. has been a member of an advisory board for Gedeon Richter. B.C.F. has received honoraria for participation as a consultant and/or as a speaker at educational events from ADAMED, Mylan, Angelini, Janssen Johnson & Johnson, Lundbeck, and Otsuka Pharmaceuticals. R.M.M. has received payments for non-promotional lectures from Janssen, Otsuka, Sunovian, and Lundbeck. J.H.M. has received research funding from H Lundbeck., (Copyright © 2023. Published by Elsevier B.V.)

Background and Hypothesis: It is argued that availability of diagnostic models will facilitate a more rapid identification of individuals who are at a higher risk of first episode psychosis (FEP). Therefore, we developed, evaluated, and validated a diagnostic risk estimation model to classify individual with FEP and controls across six countries., Study Design: We used data from a large multi-center study encompassing 2627 phenotypically well-defined participants (aged 18-64 years) recruited from six countries spanning 17 research sites, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions study. To build the diagnostic model and identify which of important factors for estimating an individual risk of FEP, we applied a binary logistic model with regularization by the least absolute shrinkage and selection operator. The model was validated employing the internal-external cross-validation approach. The model performance was assessed with the area under the receiver operating characteristic curve (AUROC), calibration, sensitivity, and specificity., Study Results: Having included preselected 22 predictor variables, the model was able to discriminate adults with FEP and controls with high accuracy across all six countries (ranges AUROC  = 0.84-0.86). Specificity (range = 73.9-78.0%) and sensitivity (range = 75.6-79.3%) were equally good, cumulatively indicating an excellent model accuracy; though, calibration slope for the diagnostic model showed a presence of some overfitting when applied specifically to participants from France, the UK, and The Netherlands., Conclusions: The new FEP model achieved a good discrimination and good calibration across six countries with different ethnic contributions supporting its robustness and good generalizability., Competing Interests: R.M.M. has received honoraria from Janssen, Sunovian, Lundbeck and Otsuka. M.B. has been a consultant for, received grant/research support and honoraria from, and been on the speakers/advisory board of ABBiotics, Adamed, Angelini, Casen Recordati, Janssen-Cilag, Menarini, Rovi and Takeda. Other authors declare that they have no conflict of interest. All other authors declare no conflict of interest., (© The Author(s) 2023. Published by Oxford University Press on behalf of the University of Maryland's school of medicine, Maryland Psychiatric Research Center.)

Background: Adverse childhood experiences (ACEs) and genetic liability are important risk factors for depression and inflammation. However, little is known about the gene-environment (G × E) mechanisms underlying their aetiology. For the first time, we tested the independent and interactive associations of ACEs and polygenic scores of major depressive disorder (MDD-PGS) and C-reactive protein (CRP-PGS) with longitudinal trajectories of depression and chronic inflammation in older adults., Methods: Data were drawn from the English longitudinal study of ageing ( N ~3400). Retrospective information on ACEs was collected in wave3 (2006/07). We calculated a cumulative risk score of ACEs and also assessed distinct dimensions separately. Depressive symptoms were ascertained on eight occasions, from wave1 (2002/03) to wave8 (2016/17). CRP was measured in wave2 (2004/05), wave4 (2008/09), and wave6 (2012/13). The associations of the risk factors with group-based depressive-symptom trajectories and repeated exposure to high CRP (i.e. ⩾3 mg/L) were tested using multinomial and ordinal logistic regression., Results: All types of ACEs were independently associated with high depressive-symptom trajectories (OR 1.44, 95% CI 1.30-1.60) and inflammation (OR 1.08, 95% CI 1.07-1.09). The risk of high depressive-symptom trajectories (OR 1.47, 95% CI 1.28-1.70) and inflammation (OR 1.03, 95% CI 1.01-1.04) was also higher for participants with higher MDD-PGS. G×E analyses revealed that the associations between ACEs and depressive symptoms were larger among participants with higher MDD-PGS (OR 1.13, 95% CI 1.04-1.23). ACEs were also more strongly related to inflammation in participants with higher CRP-PGS (OR 1.02, 95% CI 1.01-1.03)., Conclusions: ACEs and polygenic susceptibility were independently and interactively associated with elevated depressive symptoms and chronic inflammation, highlighting the clinical importance of assessing both ACEs and genetic risk factors to design more targeted interventions.

Depression is one of the leading causes of disability worldwide and is a major contributor to the global burden of disease among older adults. The study aimed to investigate the interplay between socio-economic markers (education and financial resources) and polygenic predisposition influencing individual differences in depressive symptoms and their change over time in older adults, which is of central relevance for preventative strategies. The sample encompassing n = 6202 adults aged ≥50 years old with a follow-up period of 14 years was utilised from the English Longitudinal Study of Ageing. Polygenic scores for depressive symptoms were calculated using summary statistics for (1) single-trait depressive symptoms (PGS-DS single ), and (2) multi-trait including depressive symptoms, subjective well-being, neuroticism, loneliness, and self-rated health (PGS-DS multi-trait ). The depressive symptoms over the past week were measured using the eight-item Centre for Epidemiologic Studies Depression Scale. One standard deviation increase in each PGS was associated with a higher baseline score in depressive symptoms. Each additional year of completed schooling was associated with lower baseline depression symptoms (β = -0.06, 95%CI = -0.07 to -0.05, p < 0.001); intermediate and lower wealth were associated with a higher baseline score in depressive symptoms. Although there was a weak interaction effect between PGS-DSs and socio-economic status in association with the baseline depressive symptoms, there were no significant relationships of PGS-DSs, socio-economic factors, and rate of change in the depressive symptoms during the 14-year follow-up period. Common genetic variants for depressive symptoms are associated with a greater number of depressive symptoms onset but not with their rate of change in the following 14 years. Lower socio-economic status is an important factor influencing individual levels of depressive symptoms, independently from polygenic predisposition to depressive symptoms., (© 2023. The Author(s).)

Introduction: Our aim was to, firstly, identify characteristics at first-episode of psychosis that are associated with later antipsychotic treatment resistance (TR) and, secondly, to develop a parsimonious prediction model for TR., Methods: We combined data from ten prospective, first-episode psychosis cohorts from across Europe and categorised patients as TR or non-treatment resistant (NTR) after a mean follow up of 4.18 years (s.d. = 3.20) for secondary data analysis. We identified a list of potential predictors from clinical and demographic data recorded at first-episode. These potential predictors were entered in two models: a multivariable logistic regression to identify which were independently associated with TR and a penalised logistic regression, which performed variable selection, to produce a parsimonious prediction model. This model was internally validated using a 5-fold, 50-repeat cross-validation optimism-correction., Results: Our sample consisted of N = 2216 participants of which 385 (17 %) developed TR. Younger age of psychosis onset and fewer years in education were independently associated with increased odds of developing TR. The prediction model selected 7 out of 17 variables that, when combined, could quantify the risk of being TR better than chance. These included age of onset, years in education, gender, BMI, relationship status, alcohol use, and positive symptoms. The optimism-corrected area under the curve was 0.59 (accuracy = 64 %, sensitivity = 48 %, and specificity = 76 %)., Implications: Our findings show that treatment resistance can be predicted, at first-episode of psychosis. Pending a model update and external validation, we demonstrate the potential value of prediction models for TR., Competing Interests: Declaration of competing interest The Authors declare no Competing Non-Financial Interests but the following Competing Financial Interests: J.T.R.W. is an investigator on a grant from Takeda Pharmaceuticals Ltd. to Cardiff University, for a project unrelated to the work presented here. S.E.S. is employed on this grant. M.D.F. has received a fee for educational seminars from Lundbeck and Janssen. O.A.A. is a consultant to HealthLytix and has received speakers honorarium from Lundbeck and Sunovion. T.R.E.B. has been a member of an advisory board for Gedeon Richter. C.B.E. received honoraria for conferences from Forum pour la formation médicale, Janssen-Cilag, Lundbeck, Otsuka, Sandoz, Servier, Sunovion, Sysmex Suisse AG, Takeda, Vifor-Pharma, and Zeller in the past 3 years. B.C.F. has received honoraria for participation as a consultant and/or as a speaker at educational events from ADAMED, Mylan, Angelini, Janssen Johnson & Johnson, Lundbeck, and Otsuka Pharmaceuticals. R.M.M. has received payments for non-promotional lectures from Janssen, Otsuka, Sunovian, and Lundbeck. J.H.M. has received research funding from H Lundbeck., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Growing evidence about the link between cognitive and physical decline suggests the early changes in physical functioning as a potential biomarker for cognitive impairment. Thus, we compared grip-strength trajectories over 12-16 years in three groups classified according to their cognitive status (two stable patterns, normal and impaired cognitive performance, and a declining pattern) in two representative UK and Chilean older adult samples. The samples consisted of 7069 UK (ELSA) and 1363 Chilean participants (ALEXANDROS). Linear Mixed models were performed. Adjustments included socio-demographics and health variables. The Declined and Impaired group had significantly lower grip-strength at baseline when compared to the Non-Impaired. In ELSA, the Declined and Impaired showed a faster decline in their grip strength compared to the Non-Impaired group but differences disappeared in the fully adjusted models. In ALEXANDROS, the differences were only found between the Declined and Non-Impaired and they were partially attenuated by covariates. Our study provides robust evidence of the association between grip strength and cognitive performance and how socio-economic factors might be key to understanding this association and their variability across countries. This has implications for future epidemiological research, as hand-grip strength measurements have the potential to be used as an indicator of cognitive performance.

Introduction: Treatment-resistant schizophrenia (TRS) is associated with significant impairment of functioning and high treatment costs. Identification of patients at high risk of TRS at the time of their initial diagnosis may significantly improve clinical outcomes and minimise social and functional disability. We aim to develop a prognostic model for predicting the risk of developing TRS in patients with first-episode schizophrenia and to examine its potential utility and acceptability as a clinical decision tool., Methods and Analysis: We will use two well-characterised longitudinal UK-based first-episode psychosis cohorts: Aetiology and Ethnicity in Schizophrenia and Other Psychoses and Genetics and Psychosis for which data have been collected on sociodemographic and clinical characteristics. We will identify candidate predictors for the model based on current literature and stakeholder consultation. Model development will use all data, with the number of candidate predictors restricted according to available sample size and event rate. A model for predicting risk of TRS will be developed based on penalised regression, with missing data handled using multiple imputation. Internal validation will be undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. The clinical utility of the model in terms of clinically relevant risk thresholds will be evaluated using net benefit and decision curves (comparative to competing strategies). Consultation with patients and clinical stakeholders will determine potential thresholds of risk for treatment decision-making. The acceptability of embedding the model as a clinical tool will be explored using qualitative focus groups with up to 20 clinicians in total from early intervention services. Clinicians will be recruited from services in Stafford and London with the focus groups being held via an online platform., Ethics and Dissemination: The development of the prognostic model will be based on anonymised data from existing cohorts, for which ethical approval is in place. Ethical approval has been obtained from Keele University for the qualitative focus groups within early intervention in psychosis services (ref: MH-210174). Suitable processes are in place to obtain informed consent for National Health Service staff taking part in interviews or focus groups. A study information sheet with cover letter and consent form have been prepared and approved by the local Research Ethics Committee. Findings will be shared through peer-reviewed publications, conference presentations and social media. A lay summary will be published on collaborator websites., Competing Interests: Competing interests: DS is expert advisor to the NICE centre for guidelines. The views expressed are the authors’ and not those of NICE., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Importance: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts., Objective: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples., Design, Setting, and Participants: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G])., Main Outcomes and Measures: GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition., Results: The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04)., Conclusions and Relevance: In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.

Background: Attention deficit hyperactivity disorder (ADHD) is a highly heritable, neurodevelopmental disorder known to associate with more than double the risk of death compared with people without ADHD. Because most research on ADHD has focused on children and adolescents, among whom death rates are relatively low, the impact of a high polygenic predisposition to ADHD on accelerating mortality risk in older adults is unknown. Thus, the aim of the study was to investigate if a high polygenetic predisposition to ADHD exacerbates the risk of all-cause mortality in older adults from the general population in the UK., Methods: Utilising data from the English Longitudinal Study of Ageing, which is an ongoing multidisciplinary study of the English population aged ≥ 50 years, polygenetic scores for ADHD were calculated using summary statistics for (1) ADHD (PGS-ADHD single ) and (2) chronic obstructive pulmonary disease and younger age of giving first birth, which were shown to have a strong genetic correlation with ADHD using the multi-trait analysis of genome-wide association summary statistics; this polygenic score was referred to as PGS-ADHD multi-trait . All-cause mortality was ascertained from the National Health Service central register that captures all deaths occurring in the UK., Results: The sample comprised 7133 participants with a mean age of 64.7 years (SD = 9.5, range = 50-101); of these, 1778 (24.9%) died during a period of 11.2 years. PGS-ADHD single was associated with a greater risk of all-cause mortality (hazard ratio [HR] = 1.06, 95% CI = 1.02-1.12, p = 0.010); further analyses showed this relationship was significant in men (HR = 1.07, 95% CI = 1.00-1.14, p = 0.043). Risk of all-cause mortality increased by an approximate 11% for one standard deviation increase in PGS-ADHD multi-trait (HR = 1.11, 95% CI = 1.06-1.16, p < 0.001). When the model was run separately for men and women, the association between PGS-ADHD multi-trait and an increased risk of all-cause mortality was significant in men (HR = 1.10, 95% CI = 1.03-1.18, p = 0.003) and women (HR = 1.11, 95% CI = 1.04-1.19, p = 0.003)., Conclusions: A high polygenetic predisposition to ADHD is a risk factor for all-cause mortality in older adults. This risk is better captured when incorporating genetic information from correlated traits., (© 2022. The Author(s).)

Background: Understanding how polygenic scores for ageing-related traits interact with diet in determining a future dementia including Alzheimer's diagnosis (AD) would increase our understanding of mechanisms underlying dementia onset., Methods: Using 6784 population representative adults aged ≥50 years from the English Longitudinal Study of Ageing, we employed accelerated failure time survival model to investigate interactions between polygenic scores for AD (AD-PGS), schizophrenia (SZ-PGS) and general cognition (GC-PGS) and the baseline daily fruit and vegetable intake in association with dementia diagnosis during a 10-year follow-up. The baseline sample was obtained from waves 3-4 (2006-2009); follow-up data came from wave 5 (2010-2011) to wave 8 (2016-2017)., Results: Consuming < 5 portions of fruit and vegetables a day was associated with 33-37% greater risk for dementia in the following 10 years depending on an individual polygenic propensity. One standard deviation (1-SD) increase in AD-PGS was associated with 24% higher risk of dementia and 47% higher risk for AD diagnosis. 1-SD increase in SZ-PGS was associated with an increased risk of AD diagnosis by 66%(95%CI = 1.05-2.64) in participants who consumed < 5 portions of fruit or vegetables. There was a significant additive interaction between GC-PGS and < 5 portions of the baseline daily intake of fruit and vegetables in association with AD diagnosis during the 10-year follow-up (RERI = 0.70, 95%CI = 0.09-4.82; AP = 0.36, 95%CI = 0.17-0.66)., Conclusion: A diet rich in fruit and vegetables is an important factor influencing the subsequent risk of dementia in the 10 years follow-up, especially in the context of polygenetic predisposition to AD, schizophrenia, and general cognition., (© 2022. The Author(s).)

Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs' prediction accuracies, we constructed them using genome-wide association studies-some not previously published-from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the 'additive SNP factor'. Regressions in which the true regressor is this factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Treatment resistance (TR) in patients with first-episode psychosis (FEP) is a major cause of disability and functional impairment, yet mechanisms underlying this severe disorder are poorly understood. As one view is that TR has neurodevelopmental roots, we investigated whether its emergence relates to disruptions in synchronized cortical maturation quantified using gyrification-based connectomes. Seventy patients with FEP evaluated at their first presentation to psychiatric services were followed up using clinical records for 4 years; of these, 17 (24.3%) met the definition of TR and 53 (75.7%) remained non-TR at 4 years. Structural MRI images were obtained within 5 weeks from first exposure to antipsychotics. Local gyrification indices were computed for 148 contiguous cortical regions using FreeSurfer; each subject's contribution to group-based structural covariance was quantified using a jack-knife procedure, providing a single deviation matrix for each subject. The latter was used to derive topological properties that were compared between TR and non-TR patients using a Functional Data Analysis approach. Compared to the non-TR patients, TR patients showed a significant reduction in small-worldness (Hedges's g = 2.09, P < .001) and a reduced clustering coefficient (Hedges's g = 1.07, P < .001) with increased length (Hedges's g = -2.17, P < .001), indicating a disruption in the organizing principles of cortical folding. The positive symptom burden was higher in patients with more pronounced small-worldness (r = .41, P = .001) across the entire sample. The trajectory of synchronized cortical development inferred from baseline MRI-based structural covariance highlights the possibility of identifying patients at high-risk of TR prospectively, based on individualized gyrification-based connectomes., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Identifying how socioeconomic positioning and genetic factors interact in the development of obesity is imperative for population-level obesity prevention strategies. The current study investigated whether social positioning, either independently or through interaction with a polygenic score for Body Mass Index (BMI-PGS), influences BMI trajectories across older adulthood. Data were analysed from 7,183 individuals from the English Longitudinal Study of Aging (ELSA). Interactions between the BMI-PGS and; lower educational attainment, self-perceived social status (SSS), and income, on BMI trajectories over 12 years across older adulthood were investigated through linear mixed effects models. Lower educational attainment, SSS and income were each associated with a higher baseline BMI for women, but not for men. There were interaction effects between BMI-PGS and social positioning such that men aged > 65 with a lower educational attainment (β = 0.62; 95%CI 0.00 - 1.24, p < 0.05), men aged ≤ 65 of a lower income (β = - 0.72, 95%CI - 1.21 - - 0.23, p < 0.01) and women aged ≤ 65 of lower SSS (β = - 1.41; 95%CI - 2.46 - 0.36, p < 0.01) showed stronger associations between the BMI-PGS and baseline BMI. There were few associations between markers of socioeconomic position and rate of change in BMI over the follow-up period. In sum, lower socioeconomic positioning showed adverse associations with women's BMI in older adulthood. Moreover, the expression of the BMI-PGS, or extent to which it translates to a higher BMI, was subtly influenced by socioeconomic standing in both women and in men., (© 2021. The Author(s).)

As employment and relationship status are important long-term outcomes in individuals with a diagnosis of first episode psychosis (FEP) disorders, there is a need to elucidate more accurately the extent of these social deficits in people with FEP. This in turn can aid treatment planning and policy development ultimately ensuring more complete and sustainable recoveries. We carried out a systematic review and meta-analysis of longitudinal studies in FEP reporting on employment and relationship status during the illness course. Random effects meta-analyses and meta-regression analyses were employed. Seventy-four studies were included with a sample totalling 15,272 (range = 20-1724) FEP cases with an average follow-up duration of 8.3 years (SD = 7.2). 32.5% (95%CI = 28.5-36.9) of people with a diagnosis of FEP disorders were employed and 21.3% (95%CI = 16.5-27.1) were in a relationship at the end of follow-up. Studies from high-income countries and Europe had a higher proportion of people in employment at the end of follow-up compared to middle-income nations and non-European countries. The inverse was found for relationship status. The proportion of people with a diagnosis of FEP in employment decreased significantly with longer follow-up. Living with family, being in a relationship at first contact and Black and White ethnicities were identified as significant moderators of these outcomes. These findings highlight marked functional recovery deficits for people with FEP, although cultural factors need to be considered. They support the need for interventions to improve employment opportunities, and social functioning, both in early psychosis and during the longitudinal illness course., Competing Interests: Declaration of competing interest R.M.M. has received honoraria from Janssen, Astra-Zeneca, Lilly, and BMS. A.S.D. has received honoraria from Janssen and Roche Pharmaceuticals. F.G. has received honoraria for advisory work and lectures from Lundbeck, Otsuka and Sunovion and has a family member with professional links to Lilly and GSK. The other authors (OA, BS, JL, EF) have no conflict of interest to declare., (Crown Copyright © 2021. Published by Elsevier B.V. All rights reserved.)

Background: In increasingly ageing populations, there is an emergent need to develop a robust prediction model for estimating an individual absolute risk for all-cause mortality, so that relevant assessments and interventions can be targeted appropriately. The objective of the study was to derive, evaluate and validate (internally and externally) a risk prediction model allowing rapid estimations of an absolute risk of all-cause mortality in the following 10 years., Methods: For the model development, data came from English Longitudinal Study of Ageing study, which comprised 9154 population-representative individuals aged 50-75 years, 1240 (13.5%) of whom died during the 10-year follow-up. Internal validation was carried out using Harrell's optimism-correction procedure; external validation was carried out using Health and Retirement Study (HRS), which is a nationally representative longitudinal survey of adults aged ≥50 years residing in the United States. Cox proportional hazards model with regularisation by the least absolute shrinkage and selection operator, where optimisation parameters were chosen based on repeated cross-validation, was employed for variable selection and model fitting. Measures of calibration, discrimination, sensitivity and specificity were determined in the development and validation cohorts., Results: The model selected 13 prognostic factors of all-cause mortality encompassing information on demographic characteristics, health comorbidity, lifestyle and cognitive functioning. The internally validated model had good discriminatory ability (c-index=0.74), specificity (72.5%) and sensitivity (73.0%). Following external validation, the model's prediction accuracy remained within a clinically acceptable range (c-index=0.69, calibration slope β=0.80, specificity=71.5% and sensitivity=70.6%). The main limitation of our model is twofold: 1) it may not be applicable to nursing home and other institutional populations, and 2) it was developed and validated in the cohorts with predominately white ethnicity., Conclusions: A new prediction model that quantifies absolute risk of all-cause mortality in the following 10-years in the general population has been developed and externally validated. It has good prediction accuracy and is based on variables that are available in a variety of care and research settings. This model can facilitate identification of high risk for all-cause mortality older adults for further assessment or interventions.