Torque Teno Virus (TTV) is a non-pathogenic virus that is highly prevalent among kidney transplant recipients (KTRs). Its circulating load is associated with an immunological status in KTR and is considered a promising tool for guiding immunosuppression. To allow for optimal guidance, it is important to identify other determinants of TTV load. We aimed to investigate the potential association of smoking and alcohol intake with TTV load. For this cross-sectional study, serum TTV load was measured using PCR in stable kidney transplant recipients at ≥1 year after transplantation, and smoking status and alcohol intake were assessed through questionnaires and measurements of urinary cotinine and ethyl glucuronide. A total of 666 KTRs were included (57% male). A total of 549 KTR (82%) had a detectable TTV load (3.1 ± 1.5 log₁₀ copies/mL). In KTR with a detectable TTV load, cyclosporin and tacrolimus use were positively associated with TTV load (St. β = 0.46, p < 0.001 and St. β = 0.66, p < 0.001, respectively), independently of adjustment for potential confounders. Current smoking and alcohol intake of >20 g/day were negatively associated with TTV load (St. β = −0.40, p = 0.004 and St. β = −0.33, p = 0.009, respectively), independently of each other and of adjustment for age, sex, kidney function, time since transplantation and calcineurin inhibitor use. This strong association of smoking and alcohol intake with TTV suggests a need to account for the smoking status and alcohol intake when applying TTV guided immunosuppression in KTR.

Heterogeneity is the main challenge in the traditional classification of mental disorders, including schizophrenia spectrum disorders (SSD). This can be partly attributed to the absence of objective diagnostic criteria and the multidimensional nature of symptoms and their associated factors. This article provides an overview of findings from the Genetic Risk and Outcome of Psychosis (GROUP) cohort study on the deep clinical phenotyping of schizophrenia spectrum disorders targeting positive and negative symptoms, cognitive impairments and psychosocial functioning. Three to four latent subtypes of positive and negative symptoms were identified in patients, siblings and controls, whereas four to six latent cognitive subtypes were identified. Five latent subtypes of psychosocial function—multidimensional social inclusion and premorbid adjustment—were also identified in patients. We discovered that the identified subtypes had mixed profiles and exhibited stable, deteriorating, relapsing and ameliorating longitudinal courses over time. Baseline positive and negative symptoms, premorbid adjustment, psychotic-like experiences, health-related quality of life and PRS_SCZ were found to be the strong predictors of the identified subtypes. Our findings are comprehensive, novel and of clinical interest for precisely identifying high-risk population groups, patients with good or poor disease prognosis and the selection of optimal intervention, ultimately fostering precision psychiatry by tackling diagnostic and treatment selection challenges pertaining to heterogeneity.

Purpose: We aimed to explore the multidimensional nature of social inclusion (mSI) among patients diagnosed with schizophrenia spectrum disorder (SSD), and to identify the predictors of 3-year mSI and the mSI prediction using traditional and data-driven approaches. Methods: We used the baseline and 3-year follow-up data of 1119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) cohort in the Netherlands. The outcome mSI was defined as clusters derived from combined analyses of thirteen subscales from the Social Functioning Scale and the brief version of World Health Organization Quality of Life questionnaires through K-means clustering. Prediction models were built through multinomial logistic regression (Model_MLR) and random forest (Model_RF), internally validated via bootstrapping and compared by accuracy and the discriminability of mSI subgroups. Results: We identified five mSI subgroups: “very low (social functioning)/very low (quality of life)” (8.58%), “low/low” (12.87%), “high/low” (49.24%), “medium/high” (18.05%), and “high/high” (11.26%). The mSI was robustly predicted by a genetic predisposition for SSD, premorbid adjustment, positive, negative, and depressive symptoms, number of met needs, and baseline satisfaction with the environment and social life. The Model_RF (61.61% [54.90%, 68.01%]; P =0.013) was cautiously considered outperform the Model_MLR (59.16% [55.75%, 62.58%]; P =0.994). Conclusion: We introduced and distinguished meaningful subgroups of mSI, which were modestly predictable from baseline clinical characteristics. A possibility for early prediction of mSI at the clinical stage may unlock the potential for faster and more impactful social support that is specifically tailored to the unique characteristics of the mSI subgroup to which a given patient belongs.

Background. Psychotic disorders have a strong negative impact on people’s lives, including their financial situation. This study aimed to examine differences in unmet financial needs between people with psychotic disorders, parents, siblings, and controls. Secondly, we aimed to examine whether family clustering contributes to unmet financial needs. Lastly, we aimed to examine to what extent demographic, economic, psychiatric, functional, and cognitive characteristics and substance use predict unmet financial needs in people with psychosis. Methods. Data from the first assessment of people with psychosis (n = 956), siblings (n = 889), parents (n = 858), and controls (n = 496) included in the Genetic Risk and Outcome of Psychosis study were used. Group differences were assessed with Kruskal–Wallis tests (aim 1), while a mixed-effects logistic regression analysis and explorative and confirmative ordinal logistic regression analyses were conducted for aims 2 and 3, respectively. Results. Twenty-four percent of people with psychotic disorders reported unmet financial needs. These levels of unmet financial needs were significantly higher than levels for siblings, parents, and controls. We found a negligible influence of (direct) familial clustering on unmet financial needs. Lastly, cannabis and tobacco use significantly and consistently predicted higher levels of unmet financial needs of people with psychosis. Conclusions. Relatively high levels of unmet financial needs occurred in a heterogeneous group of people with psychosis, especially when people used cannabis or tobacco. Unmet financial needs can have detrimental consequences for mental health, stigmatization, leisure time activities, and social engagement. Thus, it is pivotal to recognize unmet financial needs, especially combined with substance use, as a crucial stressor for people with psychosis.

Social inclusion is poor among patients with chronic disorders such as schizophrenia spectrum disorder (SSD). It significantly impacts patient life, healthcare and society. We aimed to study multidimensional social inclusion (mSI) among patients diagnosed with SSD, and to test the prediction of mSI. We used the baseline and 3-year follow-up data of 1,119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) cohort. The mSI was conceptualized by all subscales from social functioning (measured by Social Functioning Scale [SFS]) and quality of life (measured by the brief version of World Health Organization Quality of Life [WHOQOL-BREF]) questionnaires. K-means clustering was applied to identify mSI subgroups. Prediction models were built and internally validated via multinomial logistic regression (MLR) and random forest (RF) methods. Model fittings were compared by common factors, accuracy and the discriminability of mSI subgroups. We identified five mSI groups: “very low (social functioning)/very low (quality of life)”, “low/low”, “high/low”, “medium/high”, and “high/high”. The mSI was robustly predicted by genetic predisposition, premorbid social functioning, symptoms (i.e., positive, negative and depressive), number of met needs and baseline satisfaction with the environment and social life. The RF model was cautiously regarded to outperform the MLR model. We distinguished meaningful subgroups of mSI by combining rather than using two measurements standalone. The mSI subgroups were modestly predictable. The mSI has the potentials for personalized interventions to improve social recovery in patients. Different from conventional outcomes, we introduced mSI which has implications beyond clinics and could be applied to other disorders.

Growing evidence reveals relative stability in long-term clinical and functional outcomes of schizophrenia spectrum disorders (SSD), and links poor premorbid adjustment (PA) to worse prognoses. This study investigated associations between PA across developmental stages and long-term outcomes. Data on 496 participants (age 26.8 ± 6.5, male 58.5%) from the Danish randomised OPUS I trial were used (January 1998–December 2000; NCT00157313). Participants, with a first diagnosis within SSD, were recruited from outpatient and inpatient mental health services in Denmark and followed up for twenty years (retention = 29.0%). PA was assessed retrospectively at baseline using the Premorbid Adjustment Scale. Academic and social domain scores in childhood, and their subsequent changes in early and late adolescence, were used. Mixed models examined their effects on social functioning (Global Assessment of Functioning) and negative symptoms (Scales for the Assessment of Negative Symptoms). Low social functioning was associated with worse Social (β[95%CI] = 6.46 [0.54, 12.38], P ≤ 0.033) and Academic (9.40 [3.35, 15.44]; P ≤ 0.002) PA in childhood. Severe negative symptoms were associated with impaired Social PA in childhood (1.23 [0.73, 1.73], P ≤ 0.001), deterioration of Social PA in early adolescence (1.64 [0.93, 2.35], P ≤ 0.001), and declined Academic PA in late adolescence (0.77 [0.14, 1.39], P ≤ 0.016). Poor PA in childhood and PA decline during adolescence are related to Severer negative symptoms and lower social functioning 20 years after SSD onset. Our findings suggest that early signs may emerge in childhood, alongside age-dependent vulnerability-accumulation processes, when developing SSD. Support for maladjusting individuals during development is necessary to mitigate long-term impairments.