Descriptive and numeric estimation of risk for psychotic disorders among affected individuals and relatives: implications for clinical practice

Psychosis Prognosis Predictor: A continuous and uncertainty-aware prediction of treatment outcome in first-episode psychosis

INTRODUCTION

Machine learning models have shown promising potential in individual-level outcome prediction for patients with psychosis, but also have several limitations. To address some of these limitations, we present a model that predicts multiple outcomes, based on longitudinal patient data, while integrating prediction uncertainty to facilitate more reliable clinical decision-making.

MATERIAL AND METHODS

We devised a recurrent neural network architecture incorporating long short-term memory (LSTM) units to facilitate outcome prediction by leveraging multimodal baseline variables and clinical data collected at multiple time points. To account for model uncertainty, we employed a novel fuzzy logic approach to integrate the level of uncertainty into individual predictions. We predicted antipsychotic treatment outcomes in 446 first-episode psychosis patients in the OPTiMiSE study, for six different clinical scenarios. The treatment outcome measures assessed at both week 4 and week 10 encompassed symptomatic remission, clinical global remission, and functional remission.

RESULTS

Using only baseline predictors to predict different outcomes at week 4, leave-one-site-out validation AUC ranged from 0.62 to 0.66; performance improved when clinical data from week 1 was added (AUC = 0.66-0.71). For outcome at week 10, using only baseline variables, the models achieved AUC = 0.56-0.64; using data from more time points (weeks 1, 4, and 6) improved the performance to AUC = 0.72-0.74. After incorporating prediction uncertainties and stratifying the model decisions based on model confidence, we could achieve accuracies above 0.8 for ~50% of patients in five out of the six clinical scenarios.

CONCLUSION

We constructed prediction models utilizing a recurrent neural network architecture tailored to clinical scenarios derived from a time series dataset. One crucial aspect we incorporated was the consideration of uncertainty in individual predictions, which enhances the reliability of decision-making based on the model's output. We provided evidence showcasing the significance of leveraging time series data for achieving more accurate treatment outcome prediction in the field of psychiatry.

Consumer attitudes and preferences toward psychiatric genetic counselling and educational resources: A scoping review

INTRODUCTION

The etiology of psychiatric disorders is multifactorial including genomic and environmental risk factors. Psychiatric genetic counseling is an emerging field that may promote processes of adaptation to, and the management of, psychiatric disorders. Many countries lack dedicated services leading to a gap in care. This scoping review will inform the development of psychiatric genetics-based educational resources.

OBJECTIVES

To explore individuals with a psychiatric disorder and their relatives' attitudes and beliefs toward psychiatric genetics, genetic counseling, and genetics-based education. To evaluate how best to convey education to consumers.

METHOD

Database literature searches occurred on May 2nd, 2023, using PubMed, Medline, and PsycINFO. Reviews, letters to the editor, case reports, and publications before 2003 were excluded.

RESULTS

Twenty-four papers met the inclusion criteria. Results suggest individuals with a psychiatric disorder and their relatives tended to overestimate risk, and express concern about reproductive decision- making. Genetic counseling and educational resources were perceived to be useful and empowering.

CONCLUSION

Affected individuals and relatives are interested in gaining greater insight into their own and/or their relative's psychiatric disorder, management strategies, and understanding familial risks.

PRACTICE IMPLICATIONS

The evidence from this review may inform the development of genetics-based educational resources or guide future research.

Preference Variation: Where Does Health Risk Attitude Come Into the Equation?

OBJECTIVES

Decisions about health often involve risk, and different decision makers interpret and value risk information differently. Furthermore, an individual's attitude toward health-specific risks can contribute to variation in health preferences and behavior. This study aimed to determine whether and how health-risk attitude and heterogeneity of health preferences are related.

METHODS

To study the association between health-risk attitude and preference heterogeneity, we selected 3 discrete choice experiment case studies in the health domain that included risk attributes and accounted for preference heterogeneity. Health-risk attitude was measured using the 13-item Health-Risk Attitude Scale (HRAS-13). We analyzed 2 types of heterogeneity via panel latent class analyses, namely, how health-risk attitude relates to (1) stochastic class allocation and (2) systematic preference heterogeneity.

RESULTS

Our study did not find evidence that health-risk attitude as measured by the HRAS-13 distinguishes people between classes. Nevertheless, we did find evidence that the HRAS-13 can distinguish people's preferences for risk attributes within classes. This phenomenon was more pronounced in the patient samples than in the general population sample. Moreover, we found that numeracy and health literacy did distinguish people between classes.

CONCLUSIONS

Modeling health-risk attitude as an individual characteristic underlying preference heterogeneity has the potential to improve model fit and model interpretations. Nevertheless, the results of this study highlight the need for further research into the association between health-risk attitude and preference heterogeneity beyond class membership, a different measure of health-risk attitude, and the communication of risks.

Could Polygenic Risk Scores Be Useful in Psychiatry?: A Review

IMPORTANCE

Polygenic risk scores (PRS) are predictors of the genetic susceptibility to diseases, calculated for individuals as weighted counts of thousands of risk variants in which the risk variants and their weights have been identified in genome-wide association studies. Polygenic risk scores show promise in aiding clinical decision-making in many areas of medical practice. This review evaluates the potential use of PRS in psychiatry.

OBSERVATIONS

On their own, PRS will never be able to establish or definitively predict a diagnosis of common complex conditions (eg, mental health disorders), because genetic factors only contribute part of the risk and PRS will only ever capture part of the genetic contribution. Combining PRS with other risk factors has potential to improve outcome prediction and aid clinical decision-making (eg, determining follow-up options for individuals seeking help who are at clinical risk of future illness). Prognostication of adverse physical health outcomes or response to treatment in clinical populations are of great interest for psychiatric practice, but data from larger samples are needed to develop and evaluate PRS.

CONCLUSIONS AND RELEVANCE

Polygenic risk scores will contribute to risk assessment in clinical psychiatry as it evolves to combine information from molecular, clinical, and lifestyle metrics. The genome-wide genotype data needed to calculate PRS are inexpensive to generate and could become available to psychiatrists as a by-product of practices in other medical specialties. The utility of PRS in clinical psychiatry, as well as ethical issues associated with their use, should be evaluated in the context of realistic expectations of what PRS can and cannot deliver. Clinical psychiatry has lagged behind other fields of health care in its use of new technologies and routine clinical data for research. Now is the time to catch up.

Psychiatric genetic counseling for serious mental illness: Impact on psychopathology and psychotropic medication adherence

For people with serious mental illness (SMI) (schizophrenia, bipolar disorder, schizoaffective disorder), psychiatric genetic counseling (PGC) has been shown to significantly increase empowerment and illness management self-efficacy. While these outcomes are important, they are also theoretical precursors for behavior changes (e.g. improved medication adherence), and improved mental health. Therefore, we conducted the first study (repeated-measures/within-subjects design) to test the hypothesis that PGC would reduce psychiatric symptoms due to increased medication adherence. Between 2013-2018, we recruited N = 109 individuals (age 19-72) with SMI and administered the short Positive and Negative Syndrome Scale (short-PANSS) and Brief Adherence Rating Scale (BARS) at four timepoints; twice Pre-PGC (T1: 1-month Pre-PGC and T2: immediately Pre-PGC), to assess change in adherence/symptoms without any intervention (internal control condition), and twice Post-PGC (T3: 1-month and T4: 2-months Post-PGC), to assess impact of PGC. A quantile regression model investigated the relationships between short-PANSS, timepoints, and BARS. There was a significant relationship between short-PANSS and timepoints at the 75th (T4 short-PANSS scores < T1 and T2) and 90th quantiles (T4 short-PANSS scores < T2), but these results were not explained by improved medication adherence. PGC for SMI may reduce psychiatric symptoms, but confirmatory work and studies to examine mechanism are needed.

Genetic Risk Assessment in Psychiatry

Most psychiatric disorders of pediatric and adult onset are caused by a complex interplay of genetic and environmental risk factors. Risk assessment in genetic counseling is correspondingly complicated. Outside of neurodevelopmental conditions, genetic and genomic testing has not achieved clinical utility. Genetic counselors most often base risk assessment on the client's medical and family history and empiric recurrence risk data. In rare cases significant familial risk may arise from variants of large effect. New approaches such as polygenic risk scores have the potential to inform diagnosis and management of affected individuals and risk status for at-risk individuals. Research on the genetic and environmental factors that increase risk for schizophrenia and etiologically related disorders are reviewed, guidance in determining and communicating risks to families is delivered, and new opportunities and challenges that will come with translating new research findings to psychiatric risk assessment and genetic counseling are anticipated.

Genetics of Eating Disorders: What the Clinician Needs to Know

Anorexia nervosa (AN), bulimia nervosa (BN), and binge-eating disorder (BED) are heritable conditions that are influenced by both genetic and environmental factors. Recent genome-wide association studies (GWAS) of AN have identified specific genetic loci implicated in AN, and genetic correlations have implicated both psychiatric and metabolic factors in its origin. No GWAS have been performed for BN or BED. Genetic counseling is an important tool and can aid families and patients in understanding risk for these illnesses.

Should we intervene at stage 0? A qualitative study of attitudes of asymptomatic youth at increased risk of developing bipolar disorders and parents with established disease

BACKGROUND

Studies of potential interventions for asymptomatic individuals at risk of severe mental disorders (ie, clinical stage 0) have focused on genetic counselling or the views of adults with established disease. No study has interviewed youth at risk of bipolar disorders (BD).

METHODS

Qualitative analysis of interviews with asymptomatic adolescent offspring of adults with BD (OSBD = 7) and unrelated parents with bipolar disorders (PBD = 6) to examine manifest and latent themes in the dialogue.

RESULTS

Core themes in both groups were ignorance regarding the magnitude of risk of BD onset in offspring and greater concerns for the health of other family members than for oneself. Parents expressed anxieties in coping with the uncertainty about whether their children would inherit BD and their desire to reduce this risk was partly driven by guilt and their sense of responsibility; PBD favoured the introduction of specialized clinical OSBD services. In contrast, the priority for OSBD was advice on coping with a parent with BD; OSBD favoured access to generic non-clinical peer group support, which they perceived as less stigmatizing than specialist services.

CONCLUSION

The study highlights that youth at risk of BD should be allowed to express their ideas on what interventions they believe are likely to be most beneficial for them, as their views may differ from other advocates who are routinely consulted, such as PBD. A noteworthy finding was that OSBD thought that being included in the clinical dialogue about their parents' BD would decrease rather than increase their stress levels.

Making sense of genetic risk: A qualitative focus-group study of healthy participants in genomic research

OBJECTIVE

It is well known that research participants want to receive genetic risk information that is about high risks, serious diseases and potential preventive measures. The aim of this study was to explore, by qualitative means, something less well known: how do healthy research participants themselves make sense of genetic risk information?

METHOD

A phenomenographic approach was chosen to explore research participants' understanding and assessment of genetic risk. We conducted four focus-group (N=16) interviews with participants in a research programme designed to identify biomarkers for cardiopulmonary disease.

RESULTS

Among the research participants, we found four ways of understanding genetic risk: as a binary concept, as an explanation, as revealing who I am (knowledge of oneself) and as affecting life ahead.

CONCLUSION

Research participants tend to understand genetic risk as a binary concept. This does not necessarily imply a misunderstanding of, or an irrational approach to, genetic risk. Rather, it may have a heuristic function in decision-making.

PRACTICAL IMPLICATIONS

Risk communication may be enhanced by tailoring the communication to the participants' own lay conceptions. For example, researchers and counselors should address risk in binary terms, maybe looking out for how individual participants search for threshold figures.

Prenatal genetic counselling for psychiatric disorders

Psychiatric disorders like schizophrenia, bipolar disorder, depression, anxiety, and obsessive-compulsive disorder are common disorders with complex aetiology. They can exact a heavy toll on the individual with the condition and can have significant impact on family members too. Accordingly, psychiatric disorders can arise as a concern in the prenatal context - couples may be interested in learning about the chance for their child to develop the illness that manifests in the family and may be interested in discussing options for prenatal testing. However, the complex nature of these conditions can present challenges for clinicians who seek to help families with these issues. We established the world's first specialist genetic counselling service of its kind in Vancouver, Canada, in 2012, and to date, have provided counselling for ~500 families and have demonstrated increases in patients' empowerment and self efficacy after genetic counselling. We draw on our accumulated clinical experience to outline the process by which we approach prenatal genetic counselling for psychiatric disorders to assist other clinicians in providing thoughtful, comprehensive support to couples seeking out this service. © 2016 John Wiley & Sons, Ltd.

Theories for Psychotherapeutic Genetic Counseling: Fuzzy Trace Theory and Cognitive Behavior Theory

Psychotherapeutic genetic counseling is an increasingly relevant practice description. In this paper we aim to demonstrate how psychotherapeutic genetic counseling can be achieved by using psychological theories to guide one's approach to working with clients. We describe two illustrative examples, fuzzy trace theory and cognitive behavior theory, and apply them to two challenging cases. The theories were partially derived from evidence of beneficial client outcomes using a psychotherapeutic approach to patient care in other settings. We aim to demonstrate how these two specific theories can inform psychotherapeutic genetic counseling practice, and use them as examples of how to take a psychological theory and effectively apply it to genetic counseling.

Ethical issues associated with genetic counseling in the context of adolescent psychiatry

Genetic counseling is a well-established healthcare discipline that provides individuals and families with health information about disorders that have a genetic component in a supportive counseling encounter. It has recently been applied in the context of psychiatric disorders (like schizophrenia, bipolar disorder, schizoaffective disorder, obsessive compulsive disorder, depression and anxiety) that typically appear sometime during later childhood through to early adulthood. Psychiatric genetic counseling is emerging as an important service that fills a growing need to reframe understandings of the causes of mental health disorders. In this review, we will define psychiatric genetic counseling, and address important ethical concerns (we will particularly give attention to the principles of autonomy, beneficence, non-maleficence and justice) that must be considered in the context of its application in adolescent psychiatry, whilst integrating evidence regarding patient outcomes from the literature. We discuss the developing capacity and autonomy of adolescents as an essential and dynamic component of genetic counseling provision in this population and discuss how traditional viewpoints regarding beneficence and non-maleficence should be considered in the unique situation of adolescents with, or at risk for, psychiatric conditions. We argue that thoughtful and tailored counseling in this setting can be done in a manner that addresses the important health needs of this population while respecting the core principles of biomedical ethics, including the ethic of care.

Ethical issues in the use of genetic testing of patients with schizophrenia and their families

PURPOSE OF REVIEW

This review outlines the positive and negative aspects of DNA testing and provides an account of the issues particularly relevant to schizophrenia.

RECENT FINDINGS

Modern technology has changed the field of medicine so rapidly that patients and their families have become much more independent in their healthcare decisions than in the previous decade. Simply by finding information on the Internet, they gain knowledge about disease diagnosis, treatment options and their side-effects. No medical field likely has been more affected and more controversial than that of genetics. It is now possible to sequence the individual human genome and detect single nucleotide variations, microdeletions and duplications within it. Commercial companies have sprung up in a similar manner to the software or electronic industries and have begun to market direct-to-consumer DNA testing. Much of this may be performed to satisfy curiosity about one's ancestry; but commercially available results that appear incidentally can also be distributed to the consumer.

SUMMARY

Ethicists, genetics researchers, clinicians and government agencies are currently in discussion about concerns raised about commercially available DNA testing, while at the same time recognizing its value in some instances to be able to predict very serious disabilities.

Genetic testing of children for predisposition to mood disorders: anticipating the clinical issues

Large-scale sequencing information may provide a basis for genetic tests for predisposition to common disorders. In this study, participants in the Coriell Personalized Medicine Collaborative (N = 53) with a personal and/or family history of Major Depressive Disorder or Bipolar Disorder were interviewed based on the Health Belief Model around hypothetical intention to test one’s children for probability of developing a mood disorder. Most participants (87 %) were interested in a hypothetical test for children that had high (“90 %”) positive predictive value, while 51 % of participants remained interested in a modestly predictive test (“20 %”). Interest was driven by beliefs about effects of test results on parenting behaviors and on discrimination. Most participants favored testing before adolescence (64 %), and were reluctant to share results with asymptomatic children before adulthood. Participants anticipated both positive and negative effects of testing on parental treatment and on children’s self-esteem. Further investigation will determine whether these findings will generalize to other complex disorders for which early intervention is possible but not clearly demonstrated to improve outcomes. More information is also needed about the effects of childhood genetic testing and sharing of results on parent–child relationships, and about the role of the child in the decision-making process.

Risk of mental illness in offspring of parents with schizophrenia, bipolar disorder, and major depressive disorder: a meta-analysis of family high-risk studies

OBJECTIVE

Offspring of parents with severe mental illness (SMI; schizophrenia, bipolar disorder, major depressive disorder) are at an increased risk of developing mental illness. We aimed to quantify the risk of mental disorders in offspring and determine whether increased risk extends beyond the disorder present in the parent.

METHOD

Meta-analyses of absolute and relative rates of mental disorders in offspring of parents with schizophrenia, bipolar disorder, or depression in family high-risk studies published by December 2012.

RESULTS

We included 33 studies with 3863 offspring of parents with SMI and 3158 control offspring. Offspring of parents with SMI had a 32% probability of developing SMI (95% CI: 24%-42%) by adulthood (age >20). This risk was more than twice that of control offspring (risk ratio [RR] 2.52; 95% CI 2.08-3.06, P < .001). High-risk offspring had a significantly increased rate of the disorder present in the parent (RR = 3.59; 95% CI: 2.57-5.02, P < .001) and of other types of SMI (RR = 1.92; 95% CI: 1.48-2.49, P < .001). The risk of mood disorders was significantly increased among offspring of parents with schizophrenia (RR = 1.62; 95% CI: 1.02-2.58; P = .042). The risk of schizophrenia was significantly increased in offspring of parents with bipolar disorder (RR = 6.42; 95% CI: 2.20-18.78, P < .001) but not among offspring of parents with depression (RR = 1.71; 95% CI: 0.19-15.16, P = .631).

CONCLUSIONS

Offspring of parents with SMI are at increased risk for a range of psychiatric disorders and one third of them may develop a SMI by early adulthood.