The association of schizophrenia polygenic scores with continuously-hospitalized, treatment-resistant schizophrenia.

Genetic architecture of treatment-resistant schizophrenia across East Asian and European cohorts: insights from GWAS, TWAS, and synaptic pathway analyses

Neurodevelopmental Impact of Copy Number Variants in Patients With Treatment-Resistant Schizophrenia.

Copy number variations (CNVs) are a major contributor to the etiology and phenotypic variability in schizophrenia. CNVs are also independently associated with certain neurological, cognitive, and behavioral conditions, yet their role in early neurodevelopment in the context of treatment-resistant schizophrenia remain largely unexplored. This study aimed to investigate the contribution of neurodevelopmental CNVs to early development among individuals with treatment-resistant schizophrenia (TRS). We conducted a structured, systematic, retrospective record review within a case-control analytic framework. Our cases were the group of neurodevelopmental disorder (NDD) CNV carriers (N = 25) identified in the Pennsylvania State Hospital (PASH) cohort of individuals with treatment resistant psychotic symptoms; non-CNV controls were demographically matched individuals with treatment resistant psychotic symptoms (N = 24) from the PASH cohort. We examined the differences in early NDD phenotypes between cases and controls. CNV carriers had a higher total NDD burden score compared to non-CNV controls (z = 2.20, unadjusted p = 0.03, adjusted p = 0.08). Learning disabilities were significantly more prevalent among CNV carriers compared to non-CNV controls (χ2 = 13.437, df = 1, unadjusted p = 0.0002, adjusted p = 0.0015), with 88% of CNV carriers having a history of learning disabilities relative to 38% of non-CNV controls. CNVs carriers with TRS had a higher prevalence of early NDDs compared to non-CNV controls, particularly in learning disabilities. Prospective studies are needed to elucidate the mechanisms linking CNVs, neurodevelopmental phenotypes, and disease progression in treatment resistant schizophrenia.

Polygenic associations with phenotypic classes across the psychosis-affective spectrum

Introduction Limitations of current classifications of schizophrenia, schizoaffective disorder, and bipolar disorder are evident from their overlapping symptoms, aetiologies, treatments, and outcomes, and present a barrier to novel treatment discovery. Alternative conceptualisations are needed to address nosological validity, align diagnosis to aetiology, and improve prognostication and treatment choice. We aimed to identify latent classes across the psychosis spectrum based on premorbid functioning and outcomes, and assess these in relation to genetic liability and symptom dimensions. Method Participants with a diagnosis of schizophrenia, schizoaffective disorder, or bipolar disorder type 1, were ascertained from four UK clinical cohorts (total n=5,043). Latent class analysis was conducted using phenotypes not included within the diagnostic criteria, including premorbid functioning, age at illness onset, and measures of severity and course. Polygenic scores (PGS) for psychiatric disorders and behavioural traits were tested for associations with latent classes. We tested if diagnosis explained associations between PGS and classes. Results A three-class model provided the best fit. Class one had poorer premorbid functioning, lower rates of recovery, and higher PGS for schizophrenia and ADHD. Class three had the highest functioning, higher rates of psychosocial stressors before onset, higher intelligence PGS and lower PGS for psychiatric disorders. Class two was intermediate between classes one and three on measures of functioning, but was characterised by high levels of involuntary hospital admissions and high bipolar disorder PGS. Diagnosis only partially explained associations between PGS and class membership. Conclusions We identified classes across the psychosis spectrum characterised by different premorbid functioning and outcomes, that cut across diagnostic categories and captured genetic liability not explained by diagnosis. Our findings suggest alternative conceptualisations of psychotic disorders may complement diagnoses in mapping to the aetiology of these conditions, and could be useful to advance precision psychiatry.

The Role of Glutamatergic and Dopaminergic Genes in Resistant Schizophrenia: A Systematic Review.

Psychosis is a heterogeneous disorder, with approximately one-third of patients experiencing treatment resistance, predominantly among individuals diagnosed with Schizophrenia. Treatment-resistant schizophrenia (TRS) may stem from a distinct biological signature, involving abnormalities in the dopaminergic and glutamatergic systems. However, generalizing research findings has been challenged by inconsistent definition of resistance. Following PRISMA guidelines, a systematic literature search was conducted across four databases (PubMed, Embase, PsycINFO, and Medline) utilizing the treatment response and resistance in psychosis criteria to standardize the definition of resistance. The objective was to identify concordant genetic findings in key dopaminergic and glutamatergic pathways related to TRS, ultimately seeking genetic markers for diagnosis. Eighteen studies of moderate quality were included. The findings tentatively implicate specific glutamatergic and dopaminergic abnormalities in treatment-resistant patients, particularly involving loci within the DRD2, COMT, and NMDAR genes. Despite this concordance, the generalizability of results remains limited by factors like patient heterogeneity, varied study designs, and differences in treatment protocols. Candidate gene studies implicated genes from both dopaminergic and glutamatergic pathways in TRS but demonstrated genetic heterogeneity. Future research should advance beyond candidate-gene studies to use more robust methods, such as polygenic risk scoring, to improve the predictive accuracy of markers characterizing the TRS diagnosis.

Psychiatric genetic liability is associated with the severity of COVID-19 and other acute respiratory infections: an observational study across five Northern European countries

Pre-existing psychiatric disorders have been associated with the severity of acute respiratory infections, including COVID-19, particularly in hospitalized populations. However, the underlying mechanisms, especially in community-based populations, remain unknown, limiting preparedness for future pandemics. We investigated the role of genetic liability for psychiatric disorders and related traits in COVID-19 and other respiratory infection severity among individuals reporting SARS-CoV-2 testing and available respiratory symptom data. We included population-based cohort data from Denmark, Estonia, Iceland, Norway, and the United Kingdom (N = 78,507; 62% female; 41% SARS-CoV-2-positive; May 2020—March 2023). Respiratory infection severity was defined by self-reported days bedridden and an eleven-symptom composite score during the acute illness phase. Polygenic scores (PGSs) for eight psychiatric disorders and the personality trait neuroticism indexed genetic liability. Meta-analysed estimates from stepwise-adjusted regression analyses controlling for education, lifestyle, and psychiatric and somatic diagnosis history were used to assess associations between PGSs and acute respiratory infection severity, stratified by COVID-19 status. Higher genetic liability to insomnia, major depression (MD), and neuroticism was consistently associated with longer time bedridden (relative risk ratios per 1 SD change in PGS: 1.07–1.14, 95% confidence intervals [CIs]: 1.03–1.21) and more symptoms (incident rate ratios [IRRs]: 1.02–1.04, 95% CIs: 1.01–1.05) due to COVID-19. PGSs for insomnia, MD, neuroticism, anxiety disorder, bipolar disorder, and schizophrenia were also linked to higher non-COVID-19 symptom count (IRRs: 1.01–1.05, 95% CIs: 1.00–1.07). These associations remained robust after adjustment for lifestyle, education and medical comorbidities. Individuals in the highest MD PGS decile reported 20% more symptoms in non-COVID-19 illness and 10% more in COVID-19 compared with the bottom decile. No consistent associations were detected with attention-deficit/hyperactivity disorder, alcohol dependence and post-traumatic stress disorder. No genetic link was observed with ischaemic heart disease or type 2 diabetes. Shared genetics may contribute to the link between psychiatric conditions and respiratory infection severity in community settings. Our results underscore the role of psychiatric genetic liability, beyond diagnosed psychiatric disorders, in contributing to both COVID-19 and other respiratory infection severity. These findings provide insights that may improve future risk stratification and public health strategies targeting respiratory viruses.

The prospective incidence of treatment-resistant schizophrenia: analysis of the CATIE trial using the TRRIP consensus

Background The true incidence of treatment-resistant schizophrenia (TRS) remains uncertain, largely because earlier studies relied on heterogeneous definitions and retrospective assessments. The Treatment Response and Resistance in Psychosis (TRRIP) consensus established standardised diagnostic criteria, but these have rarely been applied prospectively. Aims To estimate the incidence of TRS prospectively by using operationalised TRRIP criteria within a large community-based trial, and to examine whether baseline demographic or clinical variables predict its emergence. Method We applied TRRIP criteria to 1334 participants with chronic schizophrenia enrolled in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study. TRS was defined as persistent symptoms and functional impairment following two adequate antipsychotic trials, each meeting TRRIP thresholds for duration, dose and adherence. Incidence was estimated with bootstrap resampling, and logistic regression examined associations between baseline variables and TRS onset. Results Of 1334 participants, 782 (58.6%) met TRRIP absolute symptom thresholds at baseline; 77 (9.8%) fulfilled full criteria for TRS during follow-up. The incidence rate was 5.68 per 100 person-years (95% CI 4.51–7.02) overall and 9.20 per 100 person-years (95% CI 7.43–11.39) among above-threshold participants. Higher baseline Positive and Negative Syndrome Scale positive and negative subscale scores and greater global illness severity were associated with TRS, although predictive performance was poor. Conclusions This first prospective application of TRRIP criteria to a randomised trial data-set provides robust estimates of TRS incidence. Routine clinical and demographic variables have limited predictive value, supporting the need for longitudinal, biologically informed studies that use TRRIP-aligned frameworks.