Shaping tomorrow's support: baseline clinical characteristics predict later social functioning and quality of life in schizophrenia spectrum disorder.

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 (ModelMLR) and random forest (ModelRF), 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 ModelRF (61.61% [54.90%, 68.01%]; P =0.013) was cautiously considered outperform the ModelMLR (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.

The association between childhood trauma and tobacco smoking in patients with psychosis, unaffected siblings, and healthy controls.

In patients with psychosis, rates of tobacco smoking and childhood trauma are significantly higher compared to the general population. Childhood trauma has been proposed as a risk factor for tobacco smoking. However, little is known about the relationship between childhood trauma and smoking in psychosis. In a subsample of the Genetic Risk and Outcome of Psychosis study (760 patients with psychosis, 991 unaffected siblings, and 491 healthy controls), tobacco smoking was assessed using the Composite International Diagnostic Interview and childhood trauma was measured with the Childhood Trauma Questionnaire. Logistic regression models were used to assess associations between trauma and smoking, while correcting for confounders. Positive associations were found between total trauma, abuse, and neglect, and an increased risk for smoking in patients, while correcting for age and gender (ORtrauma 1.77, 95% CI 1.30-2.42, p < 0.001; ORabuse 1.69, 95% CI 1.23-2.31, p = 0.001; ORneglect 1.48, 95% CI 1.08-2.02, p = 0.014). In controls, total trauma and abuse were positively associated with smoking, while correcting for age and gender (ORtrauma 2.40, 95% CI 1.49-3.88, p < 0.001; ORabuse 2.02, 96% CI 1.23-3.32, p = 0.006). All associations lost their significance after controlling for additional covariates and multiple testing. Findings suggest that the association between childhood trauma and tobacco smoking can be mainly explained by confounders (gender, cannabis use, and education) in patients with psychosis. These identified aspects should be acknowledged in tobacco cessation programs.

Moving from supported to independent living: what are the barriers and facilitators for individuals with psychosis?

PURPOSE: Living independently, as opposed to in sheltered housing or with caregivers, is an important aim in the recovery of individuals with psychosis, but the transition to independence can be challenging. This study aims to investigate how individuals with psychosis move between living arrangements and to identify the barriers and facilitators of moving towards independence. METHODS: The living arrangements of 1119 individuals with non-affective psychosis from the Genetic Risk and Outcome of Psychosis study were assessed at baseline, at three- and six-year follow-ups and further categorized as either supported (sheltered housing or with parents) or independent (single or with partner/family). We estimated the probabilities of transitioning between the living statuses and investigated the influence of demographic characteristics, symptomatology, cognition, social support, and premorbid social adjustment on transition using Markov chain modelling. RESULTS: The majority of individuals living in supported housing remained there during the six-year follow-up period (~ 60%). The likelihood of moving from supported to independent living was twice as high for participants who were younger, five-to-six times higher for women, twice as high for individuals with better overall cognition, and five times higher for those with a course of low positive symptoms. CONCLUSION: This study highlights that a large group of individuals with psychosis in supported housing is unlikely to move to independent living. Older men with cognitive impairments and who show continuous severe positive symptoms are the least likely to move living independently. Tailored interventions for these at-risk individuals could increase their chances of moving to independent living.

Diet and physical activity as risk-reducing factors for hidradenitis suppurativa.

BACKGROUND: Hidradenitis suppurativa (HS) is a multifactorial inflammatory skin disease that is considered to be an immune-mediated inflammatory disease (IMID). Up till now, the impact of lifestyle on (the development of) HS has not been thoroughly investigated. OBJECTIVES: To investigate the effect of dietary intake and physical activity (PA) on (the development of) HS. MATERIALS AND METHODS: A nested case-control study was performed within the longitudinal Lifelines Cohort Study, that took place in the Northern Netherlands, and identified 1004 adult eligible HS patients and 5000 age-matched controls. Dietary data were collected using a validated food frequency questionnaire, subsequently translated to the Lifelines Diet Score (LLDS), alternate Mediterranean Diet Score (aMED) and Dutch Dietary Guidelines score (DDG), with higher scores reflecting healthier dietary habits. PA was measured by the Short Questionnaire to Assess Health-enhancing PA score. Logistic regression analyses were performed between dietary/PA scores, and the prevalence/development and severity of HS. RESULTS: Compared to controls, HS patients scored lower on the LLDS [OR = 0.98; 95% CI 0.96-0.99], aMED [0.93; 0.89-0.97] and DDG [0.93; 0.88-0.97] with multivariable regression analysis. Overall, this indicates less adherence to dietary recommendations and consumption of a low-quality diet in the HS population. Lower adherence to the LLDS and DDG was also significantly associated with a higher likelihood to HS development in univariable regression analysis [0.96; 0.94-0.99 and 0.91; 0.84-0.99, respectively], and a trend of decreased adherence to the aMED [0.93; 0.85-1.02] was noted. Besides, PA levels were found significantly lower in HS patients (p ≤ 0.001). CONCLUSIONS AND RELEVANCE: Poor diet quality and lower quantities of PA were associated with HS in the general population. Identifying dietary and PA habits of HS patients can contribute to the development of prevention strategies for HS specifically, and for IMIDs in general.

Association of clinical symptoms and cardiometabolic dysregulations in patients with schizophrenia spectrum disorders.

BACKGROUND: Patients with schizophrenia spectrum disorders (SSD) have a shortened life expectancy related to cardiovascular diseases. We investigated the association of cognitive, positive, and negative symptoms with cardiometabolic dysregulations in SSD patients. METHODS: Overall, 1,119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) study were included. Cognitive function, positive and negative symptoms were assessed at baseline, 3-year, and 6-year. Cardiometabolic biomarkers were measured at 3-year follow-up. We used linear and multinomial logistic regression models to test the association between cardiometabolic biomarkers and clinical trajectories and performed mediation analyzes, while adjusting for clinical and demographic confounders. RESULTS: Cognitive performance was inversely associated with increased body mass index (mean difference [ß], ßhigh = -1.24, 95% CI = -2.28 to 0.20, P = 0.02) and systolic blood pressure (ßmild = 2.74, 95% CI = 0.11 to 5.37, P = 0.04). The severity of positive symptoms was associated with increased glycated hemoglobin (HbA1c) levels (ßlow = -2.01, 95% CI = -3.21 to -0.82, P = 0.001). Increased diastolic blood pressure (ORhigh-decreased = 1.04, 95% CI = 1.01 to 1.08, P = 0.02; ORhigh-increased = 1.04, 95% CI = 1.00 to 1.08, P = 0.048) and decreased high-density lipoprotein (OR high-increased = 6.25, 95% CI = 1.81 to 21.59, P = 0.004) were associated with more severe negative symptoms. Increased HbA1c (ORmoderate = 1.05, 95% CI = 1.01 to 1.10, P = 0.024; ORhigh = 1.08, 95% CI = 1.02 to 1.14, P = 0.006) was associated with more severe positive symptoms. These associations were not mediated by antipsychotics. CONCLUSIONS: We showed an association between cardiometabolic dysregulations and clinical and cognitive symptoms in SSD patients. The observed associations underscore the need for early identification of patients at risk of cardiometabolic outcomes.

The association between clinical, sociodemographic, familial, and environmental factors and treatment resistance in schizophrenia: A machine-learning-based approach.

BACKGROUND: Prediction of treatment resistance in schizophrenia (TRS) would be helpful to reduce the duration of ineffective treatment and avoid delays in clozapine initiation. We applied machine learning to identify clinical, sociodemographic, familial, and environmental variables that are associated with TRS and could potentially predict TRS in the future. STUDY DESIGN: Baseline and follow-up data on trait(-like) variables from the Genetic Risk and Outcome of Psychosis (GROUP) study were used. For the main analysis, we selected patients with non-affective psychotic disorders who met TRS (n = 200) or antipsychotic-responsive criteria (n = 423) throughout the study. For a sensitivity analysis, we only selected patients who met TRS (n = 76) or antipsychotic-responsive criteria (n = 123) at follow-up but not at baseline. Random forest models were trained to predict TRS in both datasets. SHapley Additive exPlanation values were used to examine the variables' contributions to the prediction. STUDY RESULTS: Premorbid functioning, age at onset, and educational degree were most consistently associated with TRS across both analyses. Marital status, current household, intelligence quotient, number of moves, and family loading score for substance abuse also consistently contributed to the prediction of TRS in the main or sensitivity analysis. The diagnostic performance of our models was modest (area under the curve: 0.66-0.69). CONCLUSIONS: We demonstrate that various clinical, sociodemographic, familial, and environmental variables are associated with TRS. Our models only showed modest performance in predicting TRS. Prospective large multi-centre studies are needed to validate our findings and investigate whether the model's performance can be improved by adding data from different modalities.

Pharmacogenetics of Long-Term Outcomes of Schizophrenia Spectrum Disorders: The Functional Role of CYP2D6 and CYP2C19.

Schizophrenia spectrum disorders (SSD) are complex mental disorders, and while treatment with antipsychotics is important, many patients do not respond or develop serious side effects. Genetic variation has been shown to play a considerable role in determining an individual's response to antipsychotic medication. However, previous pharmacogenetic (PGx) studies have been limited by small sample sizes, lack of consensus regarding relevant genetic variants, and cross-sectional designs. The current study aimed to investigate the association between PGx variants and long-term clinical outcomes in 691 patients of European ancestry with SSD. Using evidence from the literature on candidate genes involved in antipsychotic pharmacodynamics, we created a polygenic risk score (PRS) to investigate its association with clinical outcomes. We also created PRS using core variants of psychotropic drug metabolism enzymes CYP2D6 and CYP2C19. Furthermore, the CYP2D6 and CYP2C19 functional activity scores were calculated to determine the relationship between metabolism and clinical outcomes. We found no association for PGx PRSs and clinical outcomes; however, an association was found with CYP2D6 activity scores by the traditional method. Higher CYP2D6 metabolism was associated with high positive and high cognitive impairment groups relative to low symptom severity groups. These findings highlight the need to test PGx efficacy with different symptom domains. More evidence is needed before pharmacogenetic variation can contribute to personalized treatment plans.

Risk factors for suicidality across psychosis vulnerability spectrum.

BACKGROUND: Suicide is a leading cause of death in individuals with psychotic disorders. Risk factors for suicidality across the psychosis vulnerability spectrum are insufficiently known. METHODS: For patients (n = 830), siblings (n = 664) and controls (n = 444), suicidality was assessed by the use of a clinical interview. Multilevel modelling was used to investigate risk factors of suicidality. Lastly, risk factor × familial risk interaction effects were examined. RESULTS: Multivariable models revealed a significant relation between suicidality and depressive symptoms across all three groups, and childhood trauma in patients and siblings. The association between suicidality and psychotic-like experiences is more pronounced in siblings compared to controls. CONCLUSION: Across the psychosis vulnerability spectrum, depressive symptoms and childhood trauma have been associated with suicidality. Clinicians should pay attention to suicidality in individuals at high familial risk for psychosis with psychotic-like experiences.

Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis.

BACKGROUND AND HYPOTHESIS: Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes. STUDY DESIGN: We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score. STUDY RESULTS: After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores. CONCLUSIONS: Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models.

Lifestyle factors related to prevalent chronic disease multimorbidity: A population-based cross-sectional study.

BACKGROUND: Multimorbidity is associated with poor quality of life, polypharmacy, health care costs and mortality, with those affected potentially benefitting from a healthy lifestyle. We assessed a comprehensive set of lifestyle factors in relation to multimorbidity with major chronic diseases. METHODS: This cross-sectional study utilised baseline data for adults from the prospective Lifelines Cohort in the north of the Netherlands (N = 79,345). We defined multimorbidity as the co-existence of two or more chronic diseases (i.e. cardiovascular disease, cancer, respiratory disease, type 2 diabetes) and evaluated factors in six lifestyle domains (nutrition, physical (in)activity, substance abuse, sleep, stress, relationships) among groups by the number of chronic diseases (≥2, 1, 0). Multinomial logistic regression models were created, adjusted for appropriate confounders, and odds ratios (OR) with 95% confidence intervals (95%CI) were reported. RESULTS: 3,712 participants had multimorbidity (4.7%, age 53.5 ± 12.5 years), and this group tended to have less healthy lifestyles. Compared to those without chronic diseases, those with multimorbidity reported physical inactivity more often (OR, 1.15; 95%CI, 1.06-1.25; not significant for one condition), chronic stress (OR, 2.14; 95%CI, 1.92-2.38) and inadequate sleep (OR, 1.70; 95%CI, 1.41-2.06); as expected, they more often watched television (OR, 1.70; 95%CI, 1.42-2.04) and currently smoked (OR, 1.91; 95%CI, 1.73-2.11), but they also had lower alcohol intakes (OR, 0.66; 95%CI, 0.59-0.74). CONCLUSIONS: Chronic stress and poor sleep, in addition to physical inactivity and smoking, are lifestyle factors of great concern in patients with multimorbidity.

Deep Clinical Phenotyping of Schizophrenia Spectrum Disorders Using Data-Driven Methods: Marching towards Precision Psychiatry.

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 PRSSCZ 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.

Six-year trajectories and associated factors of positive and negative symptoms in schizophrenia patients, siblings, and controls: Genetic Risk and Outcome of Psychosis (GROUP) study.

Positive and negative symptoms are prominent but heterogeneous characteristics of schizophrenia spectrum disorder (SSD). Within the framework of the Genetic Risk and Outcome of Psychosis (GROUP) longitudinal cohort study, we aimed to distinguish and identify the genetic and non-genetics predictors of homogenous subgroups of the long-term course of positive and negative symptoms in SSD patients (n = 1119) and their unaffected siblings (n = 1059) in comparison to controls (n = 586). Data were collected at baseline, and after 3- and 6-year follow-ups. Group-based trajectory modeling was applied to identify latent subgroups using positive and negative symptoms or schizotypy scores. A multinomial random-effects logistic regression model was used to identify predictors of latent subgroups. Patients had decreasing, increasing, and relapsing symptoms course. Unaffected siblings and healthy controls had three to four subgroups characterized by stable, decreasing, or increasing schizotypy. PRSSCZ did not predict the latent subgroups. Baseline symptoms severity in patients, premorbid adjustment, depressive symptoms, and quality of life in siblings predicted long-term trajectories while were nonsignificant in controls. In conclusion, up to four homogenous latent subgroups of symptom course can be distinguished within patients, siblings, and controls, while non-genetic factors are the main factors associated with the latent subgroups.

Role of circ-FOXO3 and miR-23a in radiosensitivity of breast cancer.

Identifying the radiosensitivity of cells before radiotherapy (RT) in breast cancer (BC) patients allows appropriate switching between routinely used treatment regimens and reduces adverse side effects in exposed patients. In this study, blood was collected from 60 women diagnosed with Invasive Ductal Carcinoma (IDC) BC and 20 healthy women. To predict cellular radiosensitivity, a standard G2-chromosomal assay was performed. From these 60 samples, 20 BC patients were found to be radiosensitive based on the G2 assay. Therefore, molecular studies were finally performed on two equal groups (20 samples each) of patients with and without cellular radiosensitivity. QPCR was performed to examine the expression levels of circ-FOXO3 and miR-23a in peripheral blood mononuclear cells (PBMCs) and RNA sensitivity and specificity were determined by plotting Receiver Operating Characteristic (ROC) curves. Binary logistic regression was performed to identify RNA involvement in BC and cellular radiosensitivity (CR) in BC patients. Meanwhile, qPCR was used to compare differential RNA expression in the radiosensitive MCF-7 and radioresistant MDA-MB-231 cell lines. An annexin -V FITC/PI binding assay was used to measure cell apoptosis 24 and 48 h after 2 Gy, 4 Gy, and 8 Gy gamma-irradiation. Results indicated that circ-FOXO3 was downregulated and miR-23a was upregulated in BC patients. RNA expression levels were directly associated with CR. Cell line results showed that circ-FOXO3 overexpression induced apoptosis in the MCF-7 cell line and miR-23a overexpression inhibited apoptosis in the MDA-MB-231 cell line. Evaluation of the ROC curves revealed that both RNAs had acceptable specificity and sensitivity in predicting CR in BC patients. Binary logistic regression showed that both RNAs were also successful in predicting breast cancer. Although only circ-FOXO3 has been shown to predict CR in BC patients, circ-FOXO3 may function as a tumor suppressor and miR-23a may function as oncomiR in BC. Circ-FOXO3 and miR-23a may be promising potential biomarkers for BC prediction. Furthermore, Circ-FOXO3 could be a potential biomarker for predicting CR in BC patients.

Age-Related Social Cognitive Performance in Individuals With Psychotic Disorders and Their First-Degree Relatives.

BACKGROUND: Social cognitive impairment is a recognized feature of psychotic disorders. However, potential age-related differences in social cognitive impairment have rarely been studied. STUDY DESIGN: Data came from 905 individuals with a psychotic disorder, 966 unaffected siblings, and 544 never-psychotic controls aged 18-55 who participated in the Genetic Risk and Outcome of Psychosis (GROUP) study. Multilevel linear models were fitted to study group main effects and the interaction between group and age on emotion perception and processing (EPP; degraded facial affect recognition) and theory of mind (ToM; hinting task) performance. Age-related differences in the association between socio-demographic and clinical factors, and EPP and ToM were also explored. STUDY RESULTS: Across groups, EPP performance was associated with age (ß = -0.02, z = -7.60, 95% CI: -0.02, -0.01, P < .001), with older participants performing worse than younger ones. A significant group-by-age interaction on ToM (X2(2) = 13.15, P = .001) indicated that older patients performed better than younger ones, while no age-related difference in performance was apparent among siblings and controls. In patients, the association between negative symptoms and ToM was stronger for younger than older patients (z = 2.16, P = .03). CONCLUSIONS: The findings point to different age-related performance patterns on tests of 2 key social cognitive domains. ToM performance was better in older individuals, although this effect was only observed for patients. EPP was less accurate in older compared with younger individuals. These findings have implications with respect to when social cognitive training should be offered to patients.

Neurodevelopment in patients with biliary atresia up to toddler age: Outcomes and predictability.

AIM: To assess neurodevelopment in young patients with biliary atresia (BA) and to determine the predictive value of General Movement Assessment (GMA) at infant age for neurodevelopmental impairments at toddler age. METHOD: Infants diagnosed with BA were prospectively included in a longitudinal study. Neurodevelopmental status was previously assessed before Kasai porto-enterostomy (KPE) and one month after KPE using Prechtl's GMA, including motor optimality scores. At 2-3 years, neurodevelopment was assessed using the Bayley Scales of Infant Development, and compared to the Dutch norm population. The predictive value of GMA at infant age for motor skills and cognition at toddler age was determined. RESULTS: Neurodevelopment was assessed in 41 BA patients. At toddler age (n = 38, age 29 ± 5 months, 70 % liver transplantation), 13 (39 %) patients scored below-average on motor skills, and 6 (17 %) patients on cognition. Abnormal GMA after KPE predicted both below-average motor skills and cognitive score at toddler age (sensitivity, 91 % and 80 %; specificity 83 % and 67 %; negative predictive value, 94 % and 94 %; and, positive predictive value, 77 % and 33 %, resp.). INTERPRETATION: One-third of toddlers with BA show impaired motor skills. GMA post-KPE has a high predictive value to identify infants with BA at risk of neurodevelopmental impairments.

Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study.

BACKGROUND AND HYPOTHESIS: Current rates of poor social functioning (SF) in people with psychosis history reach 80% worldwide. We aimed to identify a core set of lifelong predictors and build prediction models of SF after psychosis onset. STUDY DESIGN: We utilized data of 1119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) longitudinal Dutch cohort. First, we applied group-based trajectory modeling to identify premorbid adjustment trajectories. We further investigated the association between the premorbid adjustment trajectories, six-year-long cognitive deficits, positive, and negative symptoms trajectories, and SF at 3-year and 6-year follow-ups. Next, we checked associations between demographics, clinical, and environmental factors measured at the baseline and SF at follow-up. Finally, we built and internally validated 2 predictive models of SF. STUDY RESULTS: We found all trajectories were significantly associated with SF (P < .01), explaining up to 16% of SF variation (R2 0.15 for 3- and 0.16 for 6-year follow-up). Demographics (sex, ethnicity, age, education), clinical parameters (genetic predisposition, illness duration, psychotic episodes, cannabis use), and environment (childhood trauma, number of moves, marriage, employment, urbanicity, unmet needs of social support) were also significantly associated with SF. After validation, final prediction models explained a variance up to 27% (95% CI: 0.23, 0.30) at 3-year and 26% (95% CI: 0.22, 0.31) at 6-year follow-up. CONCLUSIONS: We found a core set of lifelong predictors of SF. Yet, the performance of our prediction models was moderate.

The Progress and Pitfalls of Pharmacogenetics-Based Precision Medicine in Schizophrenia Spectrum Disorders: A Systematic Review and Meta-Analysis.

The inadequate efficacy and adverse effects of antipsychotics severely affect the recovery of patients with schizophrenia spectrum disorders (SSD). We report the evidence for associations between pharmacogenetic (PGx) variants and antipsychotics outcomes, including antipsychotic response, antipsychotic-induced weight/BMI gain, metabolic syndrome, antipsychotic-related prolactin levels, antipsychotic-induced tardive dyskinesia (TD), clozapine-induced agranulocytosis (CLA), and drug concentration level (pharmacokinetics) in SSD patients. Through an in-depth systematic search in 2010-2022, we identified 501 records. We included 29 meta-analyses constituting pooled data from 298 original studies over 69 PGx variants across 39 genes, 4 metabolizing phenotypes of CYP2D9, and 3 of CYP2C19. We observed weak unadjusted nominal significant (p < 0.05) additive effects of PGx variants of DRD1, DRD2, DRD3, HTR1A, HTR2A, HTR3A, and COMT (10 variants) on antipsychotic response; DRD2, HTR2C, BDNF, ADRA2A, ADRB3, GNB3, INSIG2, LEP, MC4R, and SNAP25 (14 variants) on weight gain; HTR2C (one variant) on metabolic syndrome; DRD2 (one variant) on prolactin levels; COMT and BDNF (two variants) on TD; HLA-DRB1 (one variant) on CLA; CYP2D6 (four phenotypes) and CYP2C19 (two phenotypes) on antipsychotics plasma levels. In the future, well-designed longitudinal naturalistic multi-center PGx studies are needed to validate the effectiveness of PGx variants in antipsychotic outcomes before establishing any reproducible PGx passport in clinical practice.