A critique of the “ultra‐high risk” and “transition” paradigm

The transdiagnostic expression of psychotic experiences in common mental disorder (anxiety/depression/substance use disorder) is associated with a poorer prognosis, and a small minority of people may indeed develop a clinical picture that meets criteria for schizophrenia. However, it appears neither useful nor valid to observe early states of multidimensional psychopathology in young people through the “schizo”‐prism, and apply misleadingly simple, unnecessary and inefficient binary concepts of “risk” and “transition”. A review of the “ultra‐high risk” (UHR) or “clinical high risk” (CHR) literature indicates that UHR/CHR samples are highly heterogeneous and represent individuals diagnosed with common mental disorder (anxiety/depression/substance use disorder) and a degree of psychotic experiences. Epidemiological research has shown that psychotic experiences are a (possibly non‐causal) marker of the severity of multidimensional psychopathology, driving poor outcome, yet notions of “risk” and “transition” in UHR/CHR research are restrictively defined on the basis of positive psychotic phenomena alone, ignoring how baseline differences in multidimensional psychopathology may differentially impact course and outcome. The concepts of “risk” and “transition” in UHR/CHR research are measured on the same dimensional scale, yet are used to produce artificial diagnostic shifts. In fact, “transition” in UHR/CHR research occurs mainly as a function of variable sample enrichment strategies rather than the UHR/CHR “criteria” themselves. Furthermore, transition rates in UHR/CHR research are inflated as they do not exclude false positives associated with the natural fluctuation of dimensional expression of psychosis. Biological associations with “transition” thus likely represent false positive findings, as was the initial claim of strong effects of omega‐3 polyunsatured fatty acids in UHR samples. A large body of UHR/CHR intervention research has focused on the questionable outcome of “transition”, which shows lack of correlation with functional outcome. It may be more productive to consider the full range of person‐specific psychopathology in all young individuals who seek help for mental health problems, instead of “policing” youngsters for the transdiagnostic dimension of psychosis. Instead of the relatively inefficient medical high‐risk approach, a public health perspective, focusing on improved access to a low‐stigma, high‐hope, small scale and youth‐specific environment with acceptable language and interventions may represent a more useful and efficient strategy.     

At risk or not at risk? A meta‐analysis of the prognostic accuracy of psychometric interviews for psychosis prediction

An accurate detection of individuals at clinical high risk (CHR) for psychosis is a prerequisite for effective preventive interventions. Several psychometric interviews are available, but their prognostic accuracy is unknown. We conducted a prognostic accuracy meta‐analysis of psychometric interviews used to examine referrals to high risk services. The index test was an established CHR psychometric instrument used to identify subjects with and without CHR (CHR+ and CHR?). The reference index was psychosis onset over time in both CHR+ and CHR? subjects. Data were analyzed with MIDAS (STATA13). Area under the curve (AUC), summary receiver operating characteristic curves, quality assessment, likelihood ratios, Fagan's nomogram and probability modified plots were computed. Eleven independent studies were included, with a total of 2,519 help‐seeking, predominately adult subjects (CHR+: N=1,359; CHR?: N=1,160) referred to high risk services. The mean follow‐up duration was 38 months. The AUC was excellent (0.90; 95% CI: 0.87‐0.93), and comparable to other tests in preventive medicine, suggesting clinical utility in subjects referred to high risk services. Meta‐regression analyses revealed an effect for exposure to antipsychotics and no effects for type of instrument, age, gender, follow‐up time, sample size, quality assessment, proportion of CHR+ subjects in the total sample. Fagan's nomogram indicated a low positive predictive value (5.74%) in the general non‐help‐seeking population. Albeit the clear need to further improve prediction of psychosis, these findings support the use of psychometric prognostic interviews for CHR as clinical tools for an indicated prevention in subjects seeking help at high risk services worldwide.     

Psychopathology in 7‐year‐old children with familial high risk of developing schizophrenia spectrum psychosis or bipolar disorder – The Danish High Risk and Resilience Study ‐ VIA 7, a population‐based cohort study

This study aimed to compare the psychopathological profiles of children at familial high risk of schizophrenia spectrum psychosis (FHR‐SZ) or bipolar disorder (FHR‐BP) with population‐based controls. We used Danish nationwide registers to retrieve a cohort of 522 seven‐year‐old children of parents with schizophrenia spectrum psychosis (N=202), bipolar disorder (N=120) or none of these disorders (N=200). Psychopathology was assessed by reports from multiple informants, including children, parents and teachers. Lifetime DSM‐IV diagnoses were ascertained by blinded raters through the Schedule for Affective Disorders and Schizophrenia for School‐Age Children. The dimensional assessment of psychopathology was performed by the Child Behavior Checklist, the Teacher's Report Form, a modified version of the ADHD‐Rating Scale, the Test Observation Form, and the State‐Trait Anxiety Inventory for Children. Current level of functioning was evaluated using the Children's Global Assessment Scale (CGAS). The prevalence of lifetime psychiatric diagnoses was significantly higher in both FHR‐SZ children (38.7%, odds ratio, OR=3.5, 95% confidence interval, CI: 2.2‐5.7, p < 0.001) and FHR‐BP children (35.6%, OR=3.1, 95% CI: 1.8‐5.3, p < 0.001) compared with controls (15.2%). FHR‐SZ children displayed significantly more dimensional psychopathology on all scales and subscales compared with controls except for the Anxious subscale of the Test Observation Form. FHR‐BP children showed higher levels of dimensional psychopathology on several scales and subscales compared with controls, but lower levels compared with FHR‐SZ children. Level of functioning was lower in both FHR‐SZ children (CGAS mean score = 68.2; 95% CI: 66.3‐70.2, p < 0.0001) and FHR‐BP children (73.7; 95% CI: 71.2‐76.3, p < 0.05) compared with controls (77.9; 95% CI: 75.9‐79.9). In conclusion, already at the age of seven, FHR‐SZ and FHR‐BP children show a higher prevalence of a broad spectrum of categorical and dimensional psychopathology compared with controls. These results emphasize the need for developing early intervention strategies towards this vulnerable group of children.     

Improving outcomes of first‐episode psychosis: an overview

Outcomes of psychotic disorders are associated with high personal, familiar, societal and clinical burden. There is thus an urgent clinical and societal need for improving those outcomes. Recent advances in research knowledge have opened new opportunities for ameliorating outcomes of psychosis during its early clinical stages. This paper critically reviews these opportunities, summarizing the state‐of‐the‐art knowledge and focusing on recent discoveries and future avenues for first episode research and clinical interventions. Candidate targets for primary universal prevention of psychosis at the population level are discussed. Potentials offered by primary selective prevention in asymptomatic subgroups (stage 0) are presented. Achievements of primary selected prevention in individuals at clinical high risk for psychosis (stage 1) are summarized, along with challenges and limitations of its implementation in clinical practice. Early intervention and secondary prevention strategies at the time of a first episode of psychosis (stage 2) are critically discussed, with a particular focus on minimizing the duration of untreated psychosis, improving treatment response, increasing patients’ satisfaction with treatment, reducing illicit substance abuse and preventing relapses. Early intervention and tertiary prevention strategies at the time of an incomplete recovery (stage 3) are further discussed, in particular with respect to addressing treatment resistance, improving well‐being and social skills with reduction of burden on the family, treatment of comorbid substance use, and prevention of multiple relapses and disease progression. In conclusion, to improve outcomes of a complex, heterogeneous syndrome such as psychosis, it is necessary to globally adopt complex models integrating a clinical staging framework and coordinated specialty care programmes that offer pre‐emptive interventions to high‐risk groups identified across the early stages of the disorder. Only a systematic implementation of these models of care in the national health care systems will render these strategies accessible to the 23 million people worldwide suffering from the most severe psychiatric disorders.     

Ultra high risk status and transition to psychosis in 22q11.2 deletion syndrome

The 22q11.2 deletion syndrome (22q11DS) is characterized by high rates of psychotic symptoms and schizophrenia, making this condition a promising human model for studying risk factors for psychosis. We explored the predictive value of ultra high risk (UHR) criteria in a sample of patients with 22q11DS. We also examined the additional contribution of socio‐demographic, clinical and cognitive variables to predict transition to psychosis within a mean interval of 32.5 ± 17.6 months after initial assessment. Eighty‐nine participants with 22q11DS (age range: 8‐30 years; mean 16.1 ± 4.7) were assessed using the Structured Interview for Psychosis‐Risk Syndromes. Information on Axis I diagnoses, internalizing and externalizing symptoms, level of functioning and IQ was also collected. At baseline, 22 (24.7%) participants met UHR criteria. Compared to those without a UHR condition, they had a significantly lower functioning, more frequent anxiety disorders, and more severe psychopathology. Transition rate to psychosis was 27.3% in UHR and 4.5% in non‐UHR participants. Cox regression analyses revealed that UHR status significantly predicted conversion to psychosis. Baseline level of functioning was the only other additional predictor. This is the first study investigating the predictive value of UHR criteria in 22q11DS. It indicates that the clinical path leading to psychosis is broadly comparable to that observed in other clinical high‐risk samples. Nevertheless, the relatively high transition rate in non‐UHR individuals suggests that other risk markers should be explored in this population. The role of low functioning as a predictor of transition to psychosis should also be investigated more in depth.     

Age matters in the prevalence and clinical significance of ultra‐high‐risk for psychosis symptoms and criteria in the general population: Findings from the BEAR and BEARS‐kid studies

Early detection of psychosis is an important topic in psychiatry. Yet, there is limited information on the prevalence and clinical significance of high‐risk symptoms in children and adolescents as compared to adults. We examined ultra‐high‐risk (UHR) symptoms and criteria in a sample of individuals aged 8‐40 years from the general population of Canton Bern, Switzerland, enrolled from June 2011 to May 2014. The current presence of attenuated psychotic symptoms (APS) and brief intermittent psychotic symptoms (BLIPS) and the fulfillment of onset/worsening and frequency requirements for these symptoms in UHR criteria were assessed using the Structured Interview for Psychosis Risk Syndromes. Additionally, perceptive and non‐perceptive APS were differentiated. Psychosocial functioning and current non‐psychotic DSM‐IV axis I disorders were also surveyed. Well‐trained psychologists performed assessments. Altogether, 9.9% of subjects reported APS and none BLIPS, and 1.3% met all the UHR requirements for APS. APS were related to more current axis I disorders and impaired psychosocial functioning, indicating some clinical significance. A strong age effect was detected around age 16: compared to older individuals, 8‐15‐year olds reported more perceptive APS, that is, unusual perceptual experiences and attenuated hallucinations. Perceptive APS were generally less related to functional impairment, regardless of age. Conversely, non‐perceptive APS were related to low functioning, although this relationship was weaker in those below age 16. Future studies should address the differential effects of perceptive and non‐perceptive APS, and their interaction with age, also in terms of conversion to psychosis.     

Potential for prediction of psychosis and bipolar disorder in Child and Adolescent Mental Health Services: a longitudinal register study of all people born in Finland in 1987

Current strategies to predict psychosis identify only a small proportion of individuals at risk. Additional strategies are needed to increase capacity for pre­diction and prevention of serious mental illness, ideally during childhood and adolescence. One possible approach would be to investigate systems in which psychosis risk factors are concentrated during childhood. One notable such system is represented by Child and Adolescent Mental Health Services (CAMHS). Although psychotic disorders are uncommon in CAMHS, many risk factors for psychosis are highly prevalent in young people who enter this system. We hypothesized, therefore, that youth attending CAMHS would be a high‐risk group for psychosis if followed into adulthood and, furthermore, that CAMHS systems would capture a substantial proportion of future psychosis cases. We constructed a total population cohort study of all Finns born in 1987 (N=55,875), linking together extensive register data on health care contacts from birth through age 28 years. We identified all individuals diagnosed with a psychotic or bipolar disorder by age 28 (N=1,785). The risk of psychosis/bipolar disorder by age 28 years was 1.8% for individuals who had not attended CAMHS during childhood or adolescence, whereas it was 12.8% for those with a history of any outpatient CAMHS contact (odds ratio, OR=7.9, 95% CI: 7.2‐8.7). Furthermore, the risk of psychosis/bipolar disorder by age 28 years was 2.3% for individuals without a history of inpatient CAMHS admission, whereas it was 24.0% for those with a history of inpatient CAMHS admission (OR=13.3, 95% CI: 11.9‐14.9), and 36.5% for those with a history of inpatient CAMHS admission in adolescence (age 13‐17 years) (OR=24.2, 95% CI: 21.2‐27.6). Individuals who attended CAMHS but received no mental disorder diagnosis had an equally high risk of subsequently developing a psychosis/bipolar disorder as individuals who did receive a diagnosis (OR=0.9, 99.5% CI: 0.7‐1.1). Compared to other CAMHS attendees, individuals who developed psychosis or bipolar disorder were more likely to have had an initial CAMHS diagnosis of depressive or other mood disorder (OR=2.3, 99.5% CI: 1.6‐3.0) and disruptive behaviour disorder (OR=1.7, 99.5% CI: 1.2‐2.5). Of all psychosis/bipolar diagnoses by age 28 years, 50.2% occurred in individuals who had, at some point in childhood or adolescence, attended CAMHS, indicating that CAMHS represent not only a high‐risk but also a high‐capacity system for prediction of psychosis/bipolar disorder. These findings suggest an enormous, untapped potential for large‐scale psychosis/bipolar disorder prediction and prevention research within existing specialist CAMHS.     

Cancer incidence and stage at diagnosis among people with psychotic disorders: Systematic review and meta-analysis

Research regarding the incidence of cancer among people with psychotic disorders relative to the general population is equivocal, although the evidence suggests that they have more advanced stage cancer at diagnosis. We conducted a systematic review and meta-analysis to examine the incidence and stage at diagnosis of cancer among people with, relative to those without, psychotic disorders. We searched the MEDLINE, EMBASE, PsycINFO, and CINAHL databases. Articles were included if they reported the incidence and/or stage at diagnosis of cancer in people with psychotic disorders. Random effects meta-analyses were used to determine risk of cancer and odds of advanced stage cancer at diagnosis in people with psychosis, relative to those without psychotic disorders. A total of 40 articles were included in the review, of which, 31 were included in the meta-analyses. The pooled age-adjusted risk ratio for all cancers in people with psychotic disorders was 1.08 (95% CI: 1.01–1.15), relative to those without psychotic disorders, with significant heterogeneity by cancer site. People with psychotic disorders had a higher incidence of breast, oesophageal, colorectal, testicular, uterine, and cervical cancer, and a lower incidence of skin, prostate, and thyroid cancer. People with psychotic disorders also had 22% higher (95% CI: 2–46%) odds of metastases at diagnosis, compared to those without psychotic disorders. Our systematic review found a significant difference in overall cancer incidence among people diagnosed with psychotic disorders and people with psychotic disorders were more likely to present with advanced stage cancer at diagnosis. This finding may reflect a need for improved access to and uptake of cancer screening for patients diagnosed with psychotic disorders.     

What causes psychosis? An umbrella review of risk and protective factors

Psychosis is a heterogeneous psychiatric condition for which a multitude of risk and protective factors have been suggested. This umbrella review aimed to classify the strength of evidence for the associations between each factor and psychotic disorders whilst controlling for several biases. The Web of Knowledge database was searched to identify systematic reviews and meta‐analyses of observational studies which examined associations between socio‐demographic, parental, perinatal, later factors or antecedents and psychotic disorders, and which included a comparison group of healthy controls, published from 1965 to January 31, 2017. The literature search and data extraction followed PRISMA and MOOSE guidelines. The association between each factor and ICD or DSM diagnoses of non‐organic psychotic disorders was graded into convincing, highly suggestive, suggestive, weak, or non‐significant according to a standardized classification based on: number of psychotic cases, random‐effects p value, largest study 95% confidence interval, heterogeneity between studies, 95% prediction interval, small study effect, and excess significance bias. In order to assess evidence for temporality of association, we also conducted sensitivity analyses restricted to data from prospective studies. Fifty‐five meta‐analyses or systematic reviews were included in the umbrella review, corresponding to 683 individual studies and 170 putative risk or protective factors for psychotic disorders. Only the ultra‐high‐risk state for psychosis (odds ratio, OR=9.32, 95% CI: 4.91‐17.72) and Black‐Caribbean ethnicity in England (OR=4.87, 95% CI: 3.96‐6.00) showed convincing evidence of association. Six factors were highly suggestive (ethnic minority in low ethnic density area, second generation immigrants, trait anhedonia, premorbid IQ, minor physical anomalies, and olfactory identification ability), and nine were suggestive (urbanicity, ethnic minority in high ethnic density area, first generation immigrants, North‐African immigrants in Europe, winter/spring season of birth in Northern hemisphere, childhood social withdrawal, childhood trauma, Toxoplasma gondii IgG, and non‐right handedness). When only prospective studies were considered, the evidence was convincing for ultra‐high‐risk state and suggestive for urbanicity only. In summary, this umbrella review found several factors to be associated with psychotic disorders with different levels of evidence. These risk or protective factors represent a starting point for further etiopathological research and for the improvement of the prediction of psychosis.     

Prevalence,incidence and mortality from cardiovascular disease in patients with pooled and specific severe mental illness: a large‐scale meta‐analysis of 3,211,768 patients and 113,383,368 controls

People with severe mental illness (SMI) – schizophrenia, bipolar disorder and major depressive disorder – appear at risk for cardiovascular disease (CVD), but a comprehensive meta‐analysis is lacking. We conducted a large‐scale meta‐analysis assessing the prevalence and incidence of CVD; coronary heart disease; stroke, transient ischemic attack or cerebrovascular disease; congestive heart failure; peripheral vascular disease; and CVD‐related death in SMI patients (N=3,211,768) versus controls (N=113,383,368) (92 studies). The pooled CVD prevalence in SMI patients (mean age 50 years) was 9.9% (95% CI: 7.4‐13.3). Adjusting for a median of seven confounders, patients had significantly higher odds of CVD versus controls in cross‐sectional studies (odds ratio, OR=1.53, 95% CI: 1.27‐1.83; 11 studies), and higher odds of coronary heart disease (OR=1.51, 95% CI: 1.47‐1.55) and cerebrovascular disease (OR=1.42, 95% CI: 1.21‐1.66). People with major depressive disorder were at increased risk for coronary heart disease, while those with schizophrenia were at increased risk for coronary heart disease, cerebrovascular disease and congestive heart failure. Cumulative CVD incidence in SMI patients was 3.6% (95% CI: 2.7‐5.3) during a median follow‐up of 8.4 years (range 1.8‐30.0). Adjusting for a median of six confounders, SMI patients had significantly higher CVD incidence than controls in longitudinal studies (hazard ratio, HR=1.78, 95% CI: 1.60‐1.98; 31 studies). The incidence was also higher for coronary heart disease (HR=1.54, 95% CI: 1.30‐1.82), cerebrovascular disease (HR=1.64, 95% CI: 1.26‐2.14), congestive heart failure (HR=2.10, 95% CI: 1.64‐2.70), and CVD‐related death (HR=1.85, 95% CI: 1.53‐2.24). People with major depressive disorder, bipolar disorder and schizophrenia were all at increased risk of CVD‐related death versus controls. CVD incidence increased with antipsychotic use (p=0.008), higher body mass index (p=0.008) and higher baseline CVD prevalence (p=0.03) in patients vs. controls. Moreover, CVD prevalence (p=0.007), but not CVD incidence (p=0.21), increased in more recently conducted studies. This large‐scale meta‐analysis confirms that SMI patients have significantly increased risk of CVD and CVD‐related mortality, and that elevated body mass index, antipsychotic use, and CVD screening and management require urgent clinical attention.     

Psychotic experiences as a predictor of the natural course of suicidal ideation: a Swedish cohort study

Psychotic experiences are far more prevalent in the population than psychotic disorders and are associated with a wide range of depressive, anxiety and behavioral disorders, as well as increased risk for psychotic disorder. Recently, psychotic experiences have been highlighted as a potentially valuable clinical marker of risk for suicidal behavior. There have been few studies to date, however, to assess psychotic experiences as a predictor of suicidality over time. We wished to assess whether young persons with suicidal ideation at baseline assessment who reported psychotic experiences were at higher risk for persistence of suicidal ideation at follow‐up than young persons who also reported suicidal ideation at baseline but who did not report co‐occurring psychotic experiences. A total of 2,263 adolescents were assessed at age 13 to 14 years for psychotic experiences, suicidal ideation and internalizing and externalizing psychopathology. Participants were re‐assessed at ages 16 to 17 years and 19 to 20 years. Among 13‐ to 14‐year olds with suicidal ideation, co‐occurring psychotic experiences did not predict an increased odds of persistence of suicidal ideation to age 16 to 17 years (OR=0.94, 95% CI: 0.19‐4.78). Among 16‐ to 17‐year olds with suicidal ideation, however, co‐occurring psychotic experiences predicted a 6‐fold increased odds of persistence of suicidal ideation to age 19 to 20 years (OR=5.53, 95% CI: 1.33‐23.00). Psychotic experiences are an important but under‐recognized marker of risk for persistence of suicidal ideation, in particular from mid‐adolescence. An increased emphasis on the clinical assessment of psychotic experiences in mental health services should be a priority.     

Psychosis as a transdiagnostic and extended phenotype in the general population

A large body of research indicates that weak expressions of positive psychotic symptoms (“psychotic experiences”) can be measured in the general population, and likely represent the behavioural manifestation of distributed multifactorial (genetic and non‐genetic) risk for psychosis. Psychotic experiences are a transdiagnostic phenomenon: the majority of individuals with these experiences have a diagnosis of non‐psychotic disorder, particularly common mental disorder, in which psychotic experiences predict greater illness severity and poorer treatment response. Some of the people with common mental disorder and psychotic experiences will present to mental health services meeting criteria for “clinical high risk”. Treatment of the transdiagnostic dimension of psychosis in individuals with common mental disorder who meet “clinical high risk” criteria thus may improve outcome (which cannot be interpreted as prevention of “schizophrenia”). Subthreshold psychotic experiences are transitory in about 80% of individuals, while around 20% go on to develop persistent psychotic experiences and 7% a psychotic disorder, with an annual transition rate of 0.5‐1%. Persistence is associated, on the one hand, with environmental exposures, particularly childhood trauma, and, on the other, with network‐type dynamic interactions between psychotic experiences themselves (e.g., interactions between hallucinatory experiences and delusional ideation) and between symptom dimensions (e.g., interactions between affective symptoms and psychotic experiences, or interactions between subthreshold negative symptoms and psychotic experiences). The study of psychotic experiences is helping to elucidate the mechanisms by which environmental and genetic influences shape the transdiagnostic expression of psychosis proneness, that is mostly transitory but may first become persistent over time and eventually give rise to transition to a psychotic disorder.     

Persistence of psychosis spectrum symptoms in the Philadelphia Neurodevelopmental Cohort: a prospective two‐year follow‐up

Prospective evaluation of youths with early psychotic‐like experiences can enrich our knowledge of clinical, biobehavioral and environmental risk and protective factors associated with the development of psychotic disorders. We aimed to investigate the predictors of persistence or worsening of psychosis spectrum features among US youth through the first large systematic study to evaluate subclinical symptoms in the community. Based on Time 1 screen of 9,498 youth (age 8‐21) from the Philadelphia Neurodevelopmental Cohort, a subsample of participants was enrolled based on the presence (N=249) or absence (N=254) of baseline psychosis spectrum symptoms, prior participation in neuroimaging, and current neuroimaging eligibility. They were invited to participate in a Time 2 assessment two years on average following Time 1. Participants were administered the Structured Interview for Prodromal Syndromes, conducted blind to initial screen status, along with the Schizotypal Personality Questionnaire and other clinical measures, computerized neurocognitive testing, and neuroimaging. Clinical and demographic predictors of symptom persistence were examined using logistic regression. At Time 2, psychosis spectrum features persisted or worsened in 51.4% of youths. Symptom persistence was predicted by higher severity of subclinical psychosis, lower global functioning, and prior psychiatric medication at baseline. Youths classified as having psychosis spectrum symptoms at baseline but not at follow‐up nonetheless exhibited comparatively higher symptom levels and lower functioning at both baseline and follow‐up than typically developing youths. In addition, psychosis spectrum features emerged in a small number of young people who previously had not reported significant symptoms but who had exhibited early clinical warning signs. Together, our findings indicate that varying courses of psychosis spectrum symptoms are evident early in US youth, supporting the importance of investigating psychosis risk as a dynamic developmental process. Neurocognition, brain structure and function, and genomics may be integrated with clinical data to provide early indices of symptom persistence and worsening in youths at risk for psychosis.     

Impact of mental disorders on clinical outcomes of physical diseases: an umbrella review assessing population attributable fraction and generalized impact fraction

Empirical evidence indicates a significant bidirectional association between mental disorders and physical diseases, but the prospective impact of men­tal disorders on clinical outcomes of physical diseases has not been comprehensively outlined. In this PRISMA- and COSMOS-E-compliant umbrella review, we searched PubMed, PsycINFO, Embase, and Joanna Briggs Institute Database of Systematic Reviews and Implementation Reports, up to March 15, 2022, to identify systematic reviews with meta-analysis that examined the prospective association between any mental disorder and clinical outcomes of physical diseases. Primary outcomes were disease-specific mortality and all-cause mortality. Secondary outcomes were disease-specific incidence, functioning and/or disability, symptom severity, quality of life, recurrence or progression, major cardiac events, and treatment-related outcomes. Additional inclusion criteria were further applied to primary studies. Random effect models were employed, along with I² statistic, 95% prediction intervals, small-study effects test, excess significance bias test, and risk of bias (ROBIS) assessment. Associations were classified into five credibility classes of evidence (I to IV and non-significant) according to established criteria, complemented by sensitivity and subgroup analyses to examine the robustness of the main analysis. Statistical analysis was performed using a new package for conducting umbrella reviews ( https://metaumbrella.org ). Population attributable fraction (PAF) and generalized impact fraction (GIF) were then calculated for class I-III associations. Forty-seven systematic reviews with meta-analysis, encompassing 251 non-overlapping primary studies and reporting 74 associations, were included (68% were at low risk of bias at the ROBIS assessment). Altogether, 43 primary outcomes (disease-specific mortality: n=17; all-cause mortality: n=26) and 31 secondary outcomes were investigated. Although 72% of associations were statistically significant (p<0.05), only two showed convincing (class I) evidence: that between depressive disorders and all-cause mortality in patients with heart failure (hazard ratio, HR=1.44, 95% CI: 1.26-1.65), and that between schizophrenia and cardiovascular mortality in patients with cardiovascular diseases (risk ratio, RR=1.54, 95% CI: 1.36-1.75). Six associations showed highly suggestive (class II) evidence: those between depressive disorders and all-cause mortality in patients with diabetes mellitus (HR=2.84, 95% CI: 2.00-4.03) and with kidney failure (HR=1.41, 95% CI: 1.31-1.51); that between depressive disorders and major cardiac events in patients with myocardial infarction (odds ratio, OR=1.52, 95% CI: 1.36-1.70); that between depressive disorders and dementia in patients with diabetes mellitus (HR=2.11, 95% CI: 1.77-2.52); that between alcohol use disorder and decompensated liver cirrhosis in patients with hepatitis C (RR=3.15, 95% CI: 2.87-3.46); and that between schizophrenia and cancer mortality in patients with cancer (standardized mean ratio, SMR=1.74, 95% CI: 1.41-2.15). Sensitivity/subgroup analyses confirmed these results. The largest PAFs were 30.56% (95% CI: 27.67-33.49) for alcohol use disorder and decompensated liver cirrhosis in patients with hepatitis C, 26.81% (95% CI: 16.61-37.67) for depressive disorders and all-cause mortality in patients with diabetes mellitus, 13.68% (95% CI: 9.87-17.58) for depressive disorders and major cardiac events in patients with myocardial infarction, 11.99% (95% CI: 8.29-15.84) for schizophrenia and cardiovascular mortality in patients with cardiovascular diseases, and 11.59% (95% CI: 9.09-14.14) for depressive disorders and all-cause mortality in patients with kidney failure. The GIFs confirmed the preventive capacity of these associations. This umbrella review demonstrates that mental disorders increase the risk of a poor clinical outcome in several physical diseases. Prevention targeting mental disorders – particularly alcohol use disorders, depressive disorders, and schizophrenia – can reduce the incidence of adverse clinical outcomes in people with physical diseases. These findings can inform clinical practice and trans-speciality preventive approaches cutting across psychiatric and somatic medicine.     

Nature and prevalence of combinations of mental disorders and their association with excess mortality in a population‐based cohort study

The nature and prevalence of combinations of mental disorders and their associations with premature mortality have never been reported in a comprehensive way. We describe the most common combinations of mental disorders and estimate excess mortality associated with these combinations. We designed a population‐based cohort study including all 7,505,576 persons living in Denmark at some point between January 1, 1995 and December 31, 2016. Information on mental disorders and mortality was obtained from national registers. A total of 546,090 individuals (10.5%) living in Denmark on January 1, 1995 were diagnosed with at least one mental disorder during the 22‐year follow‐up period. The overall crude rate of diagnosis of mental disorders was 9.28 (95% CI: 9.26‐9.30) per 1,000 person‐years. The rate of diagnosis of additional mental disorders was 70.01 (95% CI: 69.80‐70.26) per 1,000 person‐years for individuals with one disorder already diagnosed. At the end of follow‐up, two out of five individuals with mental disorders were diagnosed with two or more disorder types. The most prevalent were neurotic/stress‐related/somatoform disorders (ICD‐10 F40‐F48) and mood disorders (ICD‐10 F30‐F39), which – alone or in combination with other disorders – were present in 64.8% of individuals diagnosed with any mental disorder. Mortality rates were higher for people with mental disorders compared to those without mental disorders. The highest mortality rate ratio was 5.97 (95% CI: 5.52‐6.45) for the combination of schizophrenia (ICD‐10 F20‐F29), neurotic/stress‐related/somatoform disorders and substance use disorders (ICD‐10 F10‐F19). Any combination of mental disorders was associated with a shorter life expectancy compared to the general Danish population, with differences in remaining life expectancy ranging from 5.06 years (95% CI: 5.01‐5.11) to 17.46 years (95% CI: 16.86‐18.03). The largest excess mortality was observed for combinations that included substance use disorders. This study reports novel estimates related to the “force of comorbidity” and provides new insights into the contribution of substance use disorders to premature mortality in those with comorbid mental disorders.     

Beyond the “at risk mental state” concept: transitioning to transdiagnostic psychiatry

The “at risk mental state” for psychosis approach has been a catalytic, highly productive research paradigm over the last 25 years. In this paper we review that paradigm and summarize its key lessons, which include the valence of this phenotype for future psychosis outcomes, but also for comorbid, persistent or incident non‐psychotic disorders; and the evidence that onset of psychotic disorder can at least be delayed in ultra high risk (UHR) patients, and that some full‐threshold psychotic disorder may emerge from risk states not captured by UHR criteria. The paradigm has also illuminated risk factors and mechanisms involved in psychosis onset. However, findings from this and related paradigms indicate the need to develop new identification and diagnostic strategies. These findings include the high prevalence and impact of mental disorders in young people, the limitations of current diagnostic systems and risk identification approaches, the diffuse and unstable symptom patterns in early stages, and their pluripotent, transdiagnostic trajectories. The approach we have recently adopted has been guided by the clinical staging model and adapts the original “at risk mental state” approach to encompass a broader range of inputs and output target syndromes. This approach is supported by a number of novel modelling and prediction strategies that acknowledge and reflect the dynamic nature of psychopathology, such as dynamical systems theory, network theory, and joint modelling. Importantly, a broader transdiagnostic approach and enhancing specific prediction (profiling or increasing precision) can be achieved concurrently. A holistic strategy can be developed that applies these new prediction approaches, as well as machine learning and iterative probabilistic multimodal models, to a blend of subjective psychological data, physical disturbances (e.g., EEG measures) and biomarkers (e.g., neuroinflammation, neural network abnormalities) acquired through fine‐grained sequential or longitudinal assessments. This strategy could ultimately enhance our understanding and ability to predict the onset, early course and evolution of mental ill health, further opening pathways for preventive interventions.     

Transdiagnostic dimensions of psychosis in the Bipolar‐Schizophrenia Network on Intermediate Phenotypes (B‐SNIP)

The validity of the classification of non‐affective and affective psychoses as distinct entities has been disputed, but, despite calls for alternative approaches to defining psychosis syndromes, there is a dearth of empirical efforts to identify transdiagnostic phenotypes of psychosis. We aimed to investigate the validity and utility of general and specific symptom dimensions of psychosis cutting across schizophrenia, schizoaffective disorder and bipolar I disorder with psychosis. Multidimensional item‐response modeling was conducted on symptom ratings of the Positive and Negative Syndrome Scale, Young Mania Rating Scale, and Montgomery‐Åsberg Depression Rating Scale in the multicentre Bipolar‐Schizophrenia Network on Intermediate Phenotypes (B‐SNIP) consortium, which included 933 patients with a diagnosis of schizophrenia (N=397), schizoaffective disorder (N=224), or bipolar I disorder with psychosis (N=312). A bifactor model with one general symptom dimension, two distinct dimensions of non‐affective and affective psychosis, and five specific symptom dimensions of positive, negative, disorganized, manic and depressive symptoms provided the best model fit. There was further evidence on the utility of symptom dimensions for predicting B‐SNIP psychosis biotypes with greater accuracy than categorical DSM diagnoses. General, positive, negative and disorganized symptom dimension scores were higher in African American vs. Caucasian patients. Symptom dimensions accurately classified patients into categorical DSM diagnoses. This study provides evidence on the validity and utility of transdiagnostic symptom dimensions of psychosis that transcend traditional diagnostic boundaries of psychotic disorders. Findings further show promising avenues for research at the interface of dimensional psychopathological phenotypes and basic neurobiological dimensions of psychopathology.     

The psychosis spectrum in a young U.S. community sample: findings from the Philadelphia Neurodevelopmental Cohort

Little is known about the occurrence and predictors of the psychosis spectrum in large non‐clinical community samples of U.S. youths. We aimed to bridge this gap through assessment of psychosis spectrum symptoms in the Philadelphia Neurodevelopmental Cohort, a collaborative investigation of clinical and neurobehavioral phenotypes in a prospectively accrued cohort of youths, funded by the National Institute of Mental Health. Youths (age 11‐21; N=7,054) and collateral informants (caregiver/legal guardian) were recruited through the Children's Hospital of Philadelphia and administered structured screens of psychosis spectrum symptoms, other major psychopathology domains, and substance use. Youths were also administered a computerized neurocognitive battery assessing five neurobehavioral domains. Predictors of psychosis spectrum status in physically healthy participants (N=4,848) were examined using logistic regression. Among medically healthy youths, 3.7% reported threshold psychotic symptoms (delusions and/or hallucinations). An additional 12.3% reported significant sub‐psychotic positive symptoms, with odd/unusual thoughts and auditory perceptions, followed by reality confusion, being the most discriminating and widely endorsed attenuated symptoms. A minority of youths (2.3%) endorsed subclinical negative/disorganized symptoms in the absence of positive symptoms. Caregivers reported lower symptom levels than their children. Male gender, younger age, and non‐European American ethnicity were significant predictors of spectrum status. Youths with spectrum symptoms had reduced accuracy across neurocognitive domains, reduced global functioning, and increased odds of depression, anxiety, behavioral disorders, substance use and suicidal ideation. These findings have public health relevance for prevention and early intervention.     

Prediction of psychosis across protocols and risk cohorts using automated language analysis

Language and speech are the primary source of data for psychiatrists to diagnose and treat mental disorders. In psychosis, the very structure of language can be disturbed, including semantic coherence (e.g., derailment and tangentiality) and syntactic complexity (e.g., concreteness). Subtle disturbances in language are evident in schizophrenia even prior to first psychosis onset, during prodromal stages. Using computer‐based natural language processing analyses, we previously showed that, among English‐speaking clinical (e.g., ultra) high‐risk youths, baseline reduction in semantic coherence (the flow of meaning in speech) and in syntactic complexity could predict subsequent psychosis onset with high accuracy. Herein, we aimed to cross‐validate these automated linguistic analytic methods in a second larger risk cohort, also English‐speaking, and to discriminate speech in psychosis from normal speech. We identified an automated machine‐learning speech classifier – comprising decreased semantic coherence, greater variance in that coherence, and reduced usage of possessive pronouns – that had an 83% accuracy in predicting psychosis onset (intra‐protocol), a cross‐validated accuracy of 79% of psychosis onset prediction in the original risk cohort (cross‐protocol), and a 72% accuracy in discriminating the speech of recent‐onset psychosis patients from that of healthy individuals. The classifier was highly correlated with previously identified manual linguistic predictors. Our findings support the utility and validity of automated natural language processing methods to characterize disturbances in semantics and syntax across stages of psychotic disorder. The next steps will be to apply these methods in larger risk cohorts to further test reproducibility, also in languages other than English, and identify sources of variability. This technology has the potential to improve prediction of psychosis outcome among at‐risk youths and identify linguistic targets for remediation and preventive intervention. More broadly, automated linguistic analysis can be a powerful tool for diagnosis and treatment across neuropsychiatry.     

Dopamine and glutamate in individuals at high risk for psychosis: a meta‐analysis of in vivo imaging findings and their variability compared to controls

Dopaminergic and glutamatergic dysfunction is believed to play a central role in the pathophysiology of schizophrenia. However, it is unclear if abnormalities predate the onset of schizophrenia in individuals at high clinical or genetic risk for the disorder. We systematically reviewed and meta‐analyzed studies that have used neuroimaging to investigate dopamine and glutamate function in individuals at increased clinical or genetic risk for psychosis. EMBASE, PsycINFO and Medline were searched form January 1, 1960 to November 26, 2020. Inclusion criteria were molecular imaging measures of striatal presynaptic dopaminergic function, striatal dopamine receptor availability, or glutamate function. Separate meta‐analyses were conducted for genetic high‐risk and clinical high‐risk individuals. We calculated standardized mean differences between high‐risk individuals and controls, and investigated whether the variability of these measures differed between the two groups. Forty‐eight eligible studies were identified, including 1,288 high‐risk individuals and 1,187 controls. Genetic high‐risk individuals showed evidence of increased thalamic glutamate + glutamine (Glx) concentrations (Hedges’ g=0.36, 95% CI: 0.12‐0.61, p=0.003). There were no significant differences between high‐risk individuals and controls in striatal presynaptic dopaminergic function, striatal D2/D3 receptor availability, prefrontal cortex glutamate or Glx, hippocampal glutamate or Glx, or basal ganglia Glx. In the meta‐analysis of variability, genetic high‐risk individuals showed reduced variability of striatal D2/D3 receptor availability compared to controls (log coefficient of variation ratio, CVR=–0.24, 95% CI: –0.46 to –0.02, p=0.03). Meta‐regressions of publication year against effect size demonstrated that the magnitude of differences between clinical high‐risk individuals and controls in presynaptic dopaminergic function has decreased over time (estimate=–0.06, 95% CI: –0.11 to –0.007, p=0.025). Thus, other than thalamic glutamate concentrations, no neurochemical measures were significantly different between individuals at risk for psychosis and controls. There was also no evidence of increased variability of dopamine or glutamate measures in high‐risk individuals compared to controls. Significant heterogeneity, however, exists between studies, which does not allow to rule out the existence of clinically meaningful differences.