Precision clinical trials: a framework for getting to precision medicine for neurobehavioural disorders

From Serendipity to Precision: Integrating AI, Multi-Omics, and Human-Specific Models for Personalized Neuropsychiatric Care

Background/Objectives: The dual forces of structured inquiry and serendipitous discovery have long shaped neuropsychiatric research, with groundbreaking treatments such as lithium and ketamine resulting from unexpected discoveries. However, relying on chance is becoming increasingly insufficient to address the rising prevalence of mental health disorders like depression and schizophrenia, which necessitate precise, innovative approaches. Emerging technologies like artificial intelligence, induced pluripotent stem cells, and multi-omics have the potential to transform this field by allowing for predictive, patient-specific interventions. Despite these advancements, traditional methodologies such as animal models and single-variable analyses continue to be used, frequently failing to capture the complexities of human neuropsychiatric conditions. Summary: This review critically evaluates the transition from serendipity to precision-based methodologies in neuropsychiatric research. It focuses on key innovations such as dynamic systems modeling and network-based approaches that use genetic, molecular, and environmental data to identify new therapeutic targets. Furthermore, it emphasizes the importance of interdisciplinary collaboration and human-specific models in overcoming the limitations of traditional approaches. Conclusions: We highlight precision psychiatry's transformative potential for revolutionizing mental health care. This paradigm shift, which combines cutting-edge technologies with systematic frameworks, promises increased diagnostic accuracy, reproducibility, and efficiency, paving the way for tailored treatments and better patient outcomes in neuropsychiatric care.

Understanding human papillomavirus vaccine response and efficacy in people living with HIV: A systematic mixed studies review and meta-analysis

Coinfection with human papillomavirus (HPV) and HIV compounds the risks of developing cervical, anal, and HPV-associated oral neoplasia. Safe prophylactic vaccines are available to prevent HPV infections in people with HIV(PWH). Yet, vaccine efficacy and duration of protection remain questionable. Historically, the efficacy of vaccines has been suboptimal in PWH compared to people without HIV (PWoH).A systematic review of HPV vaccine trials in PWH was conducted using PRISMA guidelines. Outcomes of interest were vaccine efficacy, immunogenicity, and predictors of HPV vaccine efficacy. A secondary outcome was to assess age and sex differences. Efficacy was reviewed as cervical/anal/oral lesions or neoplasia, and incident or persistent HPV infection following vaccination. A random effects meta-analysis was performed comparing geometric mean titer (GMT) in PWH to PWoH. Twenty-eight studies out of 988 were eligible for inclusion in our study, and qualitatively synthesized. Eight of these studies were meta-analyzed. GMT results of HPV16 and HPV18 genotypes were significantly lower in PWH; Hedges's g -0.434 (95% CI: -0.823, -0.046) and Hedges's g -0.57 (95% CI: -0.72, -0.43), respectively. The mean difference in GMT for HPV18 between PWH and PWoH was -536.23 (95% CI: -830.66, -241.81); approximately 22 times higher than HPV18 seropositivity cut-offs, assuming milli-Merck Units per milliliter. Risk factors for incident or persistent infections in PWH included: failure to seroconvert after vaccination, baseline CD4+ T-cell count <500 cells/mm3, early age of sexual debut, HIV viral load ≥ 400 copies/mL. There was a trend towards decreased HPV vaccine efficacy in studies that included enrollees with a history of AIDS or AIDS-defining illness.Applying existing evidence of HPV vaccine efficacy on meaningful clinical outcomes in PWH is questionable. This could be influenced by the diversity of eligibility criteria across clinical trials of HPV vaccine efficacy. Precision medicine may offer novel alternatives for evaluating HPV vaccine efficacy in PWH.

Initial evaluation of a personalized advantage index to determine which individuals may benefit from mindfulness-based cognitive therapy for suicide prevention

OBJECTIVE

Develop and evaluate a treatment matching algorithm to predict differential treatment response to Mindfulness-Based Cognitive Therapy for suicide prevention (MBCT-S) versus enhanced treatment-as-usual (eTAU).

METHODS

Analyses used data from Veterans at high-risk for suicide assigned to either MBCT-S (n = 71) or eTAU (n = 69) in a randomized clinical trial. Potential predictors (n = 55) included available demographic, clinical, and neurocognitive variables. Random forest models were used to predict risk of suicidal event (suicidal behaviors, or ideation resulting in hospitalization or emergency department visit) within 12 months following randomization, characterize the prediction, and develop a Personalized Advantage Index (PAI).

RESULTS

A slightly better prediction model emerged for MBCT-S (AUC = 0.70) than eTAU (AUC = 0.63). Important outcome predictors for participants in the MBCT-S arm included PTSD diagnosis, decisional efficiency on a neurocognitive task (Go/No-Go), prior-year mental health residential treatment, and non-suicidal self-injury. Significant predictors for participants in the eTAU arm included past-year acute psychiatric hospitalizations, past-year outpatient psychotherapy visits, past-year suicidal ideation severity, and attentional control (indexed by Stroop task). A moderation analysis showed that fewer suicidal events occurred among those randomized to their PAI-indicated optimal treatment.

CONCLUSIONS

PAI-guided treatment assignment may enhance suicide prevention outcomes. However, prior to real-world application, additional research is required to improve model accuracy and evaluate model generalization.

Precision Functional Mapping to Advance Developmental Psychiatry Research

Many psychiatric conditions have their roots in early development. Individual differences in prenatal brain function (which is influenced by a combination of genetic risk and the prenatal environment) likely interact with individual differences in postnatal experience, resulting in substantial variation in brain functional organization and development in infancy. Neuroimaging has been a powerful tool for understanding typical and atypical brain function and holds promise for uncovering the neurodevelopmental basis of psychiatric illness; however, its clinical utility has been relatively limited thus far. A substantial challenge in this endeavor is the traditional approach of averaging brain data across groups despite individuals varying in their brain organization, which likely obscures important clinically relevant individual variation. Precision functional mapping (PFM) is a neuroimaging technique that allows the capture of individual-specific and highly reliable functional brain properties. Here, we discuss how PFM, through its focus on individuals, has provided novel insights for understanding brain organization across the life span and its promise in elucidating the neural basis of psychiatric disorders. We first summarize the extant literature on PFM in normative populations, followed by its limited utilization in studying psychiatric conditions in adults. We conclude by discussing the potential for infant PFM in advancing developmental precision psychiatry applications, given that many psychiatric disorders start during early infancy and are associated with changes in individual-specific functional neuroanatomy. By exploring the intersection of PFM, development, and psychiatric research, this article underscores the importance of individualized approaches in unraveling the complexities of brain function and improving clinical outcomes across development.

Points to consider when initiating clinical investigations in autistic paediatric populations-A White Paper

Many individuals with autism spectrum disorder (ASD) experience various degrees of impairment in social interaction and communication, restricted, repetitive behaviours, interests/activities. These impairments make a significant contribution to poorer everyday adaptive functioning. Yet, there are no pharmacological therapies to effectively treat the core symptoms of ASD. Since symptoms of ASD likely emerge from a complex interplay of vulnerabilities, environmental factors and compensatory mechanisms during the early developmental period, pharmacological interventions arguably would have the greatest impact to improve long-term outcomes when implemented at a young age. It is essential therefore, that clinical development programmes of investigational drugs in ASD include the paediatric population early on in clinical trials. Such trials need to offer the prospect of direct benefit (PDB) for participants. In most cases in drug development this prospect is supported by evidence of efficacy in adults. However, the effectiveness of treatment approaches may be age-dependent, so that clinical trials in adults may not provide sufficient evidence for a PDB in children. In this white paper, we consolidate recommendations from regulatory guidelines, as well as advice from the Food and Drug Administration, USA (FDA) and the Committee for Human Medicinal Products (CHMP) consultations on various development programmes on: 1) elements to support a PDB to participants in early paediatric clinical trials in ASD, including single-gene neurodevelopment disorders, 2) aspects of study design to allow for a PDB. This white paper is intended to be complementary to existing regulatory guidelines in guiding industry and academic sponsors in their conduct of early paediatric clinical trials in ASD.

Adapting dose-response methodology to improve clinical trial design for psychotherapies

OBJECTIVE

Conventional randomized controlled trials (RCTs) have long served as the foundation of research in clinical psychology; however, most treatments for eating disorders show only modest effects on reduction of symptoms and maintenance of long-term remission. New options for psychotherapy treatment development research, beyond continuing to pursue additive or subpopulation approaches, are needed.

METHODS

One option is to apply dose-response designs, which are commonplace in studies of pharmacology, toxicology, and medical research, and characterized by the evaluation of the amount of exposure (dose) to an intervention, and the resulting changes in body function or health (response).

RESULTS

Eating disorder interventions are particularly well-suited for dose-response treatment designs. The deadly nature of eating disorders makes it imperative that patients are not turned away for not being "ready" to engage with treatment. By identifying optimal doses, research will likely yield a more parsimonious course of treatment, which will lend itself to reduced costs, greater uptake, and reduced drop-out.

DISCUSSION

Limited use of within-subject designs in trials for patients with eating disorders has produced fast-track efficacy studies and omitted key elements in the treatment development pathway. To decrease reliance on RCT's, dose-response methods should be applied as an alternative study design.

PUBLIC SIGNIFICANCE

Eating disorders are associated with medical and psychiatric comorbidities, poor quality of life, and high mortality. Access to evidence-based services for patients with eating disorders is limited, and identifying additional effective treatment options can be difficult because of challenges inherent to randomized-controlled trials. This manuscript describes an alternative trial methodology to maximize the information that can be gathered prior to utilizing a standard large-scale efficacy design.

Pragmatic clinical trials to advance research in children and adolescents with eating disorders

OBJECTIVE

To discuss the utility of pragmatic clinical trials (PCTs) to help advance research in eating disorders (EDs).

METHODS

We describe challenges associated with traditional explanatory research trials and examine PCTs as an alternative, including a review of the PRECIS-2 tool.

RESULTS

There are many challenges associated with the design and completion of traditional RCTs within the field of EDs. Pragmatic clinical trials are studies that closely align with conditions available in everyday practice and focus on outcomes that are relevant to patients and clinicians. Results of PCTS maximize applicability and generalizability to clinical settings.

DISCUSSION

Available therapies established for the treatment of EDs provide remission rates that rarely exceed 50%, implying a need for additional research on new or adjunctive treatments. In addition to a general overview of PCTs, we draw upon published literature and our own experiences involving adjunctive olanzapine for the treatment of children and youth with anorexia nervosa to help highlight challenges associated with randomized controlled trial (RCT) design and implementation, and offer pragmatic suggestions that would allow patients greater choice in treatment trials, while at the same time capturing outcomes that are most likely to advance treatment efforts.

CONCLUSIONS

Pragmatic clinical trials provide alternatives to RCT design that can help bolster research in EDs that aims to explore real-world effects of interventions.

PUBLIC SIGNIFICANCE

Available therapies established for the treatment of eating disorders (EDs) in children and adolescents provide remission rates that rarely exceed 50%, implying a need for additional research on new or adjunctive treatments. In this article, we discuss the utility of pragmatic trials to help promote research that can help advance knowledge that is relevant to clinical care settings.

Brexanolone Treatment in a Real-World Patient Population: A Case Series and Pilot Feasibility Study of Precision Neuroimaging

PURPOSE/BACKGROUND

Brexanolone is approved for postpartum depression (PPD) by the United States Food and Drug Administration. Brexanolone has outperformed placebo in clinical trials, but less is known about the efficacy in real-world patients with complex social and medical histories. Furthermore, the impact of brexanolone on large-scale brain systems such as changes in functional connectivity (FC) is unknown.

METHODS/PROCEDURES

We tracked changes in depressive symptoms across a diverse group of patients who received brexanolone at a large medical center. Edinburgh Postnatal Depression Scale (EPDS) scores were collected through chart review for 17 patients immediately prior to infusion through approximately 1 year postinfusion. In 2 participants, we performed precision functional neuroimaging (pfMRI), including before and after treatment in 1 patient. pfMRI collects many hours of data in individuals for precision medicine applications and was performed to assess the feasibility of investigating changes in FC with brexanolone.

FINDINGS/RESULTS

The mean EPDS score immediately postinfusion was significantly lower than the mean preinfusion score (mean change [95% CI]: 10.76 [7.11-14.40], t (15) = 6.29, P < 0.0001). The mean EPDS score stayed significantly lower at 1 week (mean difference [95% CI]: 9.50 [5.23-13.76], t (11) = 4.90, P = 0.0005) and 3 months (mean difference [95% CI]: 9.99 [4.71-15.27], t (6) = 4.63, P = 0.0036) postinfusion. Widespread changes in FC followed infusion, which correlated with EPDS scores.

IMPLICATIONS/CONCLUSIONS

Brexanolone is a successful treatment for PPD in the clinical setting. In conjunction with routine clinical care, brexanolone was linked to a reduction in symptoms lasting at least 3 months. pfMRI is feasible in postpartum patients receiving brexanolone and has the potential to elucidate individual-specific mechanisms of action.

Digital and precision clinical trials: innovations for testing mental health medications, devices, and psychosocial treatments

Mental health treatment advances - including neuropsychiatric medications and devices, psychotherapies, and cognitive treatments - lag behind other fields of clinical medicine such as cardiovascular care. One reason for this gap is the traditional techniques used in mental health clinical trials, which slow the pace of progress, produce inequities in care, and undermine precision medicine goals. Newer techniques and methodologies, which we term digital and precision trials, offer solutions. These techniques consist of (1) decentralized (i.e., fully-remote) trials which improve the speed and quality of clinical trials and increase equity of access to research, (2) precision measurement which improves success rate and is essential for precision medicine, and (3) digital interventions, which offer increased reach of, and equity of access to, evidence-based treatments. These techniques and their rationales are described in detail, along with challenges and solutions for their utilization. We conclude with a vignette of a depression clinical trial using these techniques.

Novel mechanism-based treatments for pediatric anxiety and depressive disorders

Pediatric anxiety and depressive disorders are common, can be highly impairing, and can persist despite the best available treatments. Here, we review research into novel treatments for childhood anxiety and depressive disorders designed to target underlying cognitive, emotional, and neural circuit mechanisms. We highlight three novel treatments lying along a continuum relating to clinical impact of the disorder and the intensity of clinical management required. We review cognitive training, which involves the lowest risk and may be applicable for problems with mild to moderate impact; psychotherapy, which includes a higher level of clinical involvement and may be sufficient for problems with moderate impact; and brain stimulation, which has the highest potential risks and is therefore most appropriate for problems with high impact. For each treatment, we review the specific underlying cognitive, emotional, and brain circuit mechanisms that are being targeted, whether treatments modify those underlying mechanisms, and efficacy in reducing symptoms. We conclude by highlighting future directions, including the importance of work that leverages developmental windows of high brain plasticity to time interventions to the specific epochs in childhood that have the largest and most enduring life-long impact.

The Buzz Surrounding Precision Medicine: The Imperative of Incorporating It into Evidence-Based Medical Practice

Precision medicine (PM), through the integration of omics and environmental data, aims to provide a more precise prevention, diagnosis, and treatment of disease. Currently, PM is one of the emerging approaches in modern healthcare and public health, with wide implications for health care delivery, public health policy making formulation, and entrepreneurial endeavors. In spite of its growing popularity and the buzz surrounding it, PM is still in its nascent phase, facing considerable challenges that need to be addressed and resolved for it to attain the acclaim for which it strives. In this article, we discuss some of the current methodological pitfalls of PM, including the use of big data, and provide a perspective on how these challenges can be overcome by bringing PM closer to evidence-based medicine (EBM). Furthermore, to maximize the potential of PM, we present real-world illustrations of how EBM principles can be integrated into a PM approach.

Better Biomarkers, Faster Drugs, Stronger Models: Progress Towards Precision Psychiatry

The 21st century has brought novel therapies and new therapeutic targets for major depressive disorder (MDD). Until recently all antidepressant medications targeted monoamines-serotonin, norepinephrine, and dopamine- and their regulatory systems. But growing evidence has suggested that individuals who fail to respond to a monoaminergic treatment are likely to fail to respond to other monoaminergic options. The emergence in recent years of treatment targets beyond the monoaminergic systems (e.g. κ-opioid antagonists, ketamine and other NMDA modulators, neurosteroids) has cultivated hopes for not only greater efficacy in treating depression, but also improved precision in targeting specific phenotypes and symptoms. Concurrently, an expanding repertoire of diagnostic and assessment tools-such as smartphone-based experience sampling and brain imaging-is moving the field toward more reliable and symptom-specific measurement with greater descriptive and prescriptive power. Taken together, these diagnostic tools and treatment options herald a new era of "precision psychiatry"-the selection and implementation of an optimal treatment for an individual patient's particular needs. Anhedonia offers an example of the new precision psychiatry. Anhedonia has moved from merely one among several criteria for depression to a transdiagnostic psychopathology which can be understood neurobiologically, assessed quantitatively, and centered as a primary target in research and development of novel pharmacotherapies. We describe functional testing of reward circuits in the development of kappa-opioid antagonists for anhedonia. This offers a lens for understanding how and under what circumstances other novel treatments, such as psychedelics, might find a place in the future landscape of precision psychiatric care.

Mediating Effects of Neural Targets on Depression, Weight, and Anxiety Outcomes of an Integrated Collaborative Care Intervention: The ENGAGE-2 Mechanistic Pilot Randomized Clinical Trial

Background

Integrated treatments for comorbid depression (often with anxiety) and obesity are lacking; mechanisms are poorly investigated.

Methods

In a mechanistic pilot trial, adults with body mass index ≥30 and Patient Health Questionnaire-9 scores ≥10 were randomized to usual care (n = 35) or an integrated behavioral intervention (n = 71). Changes at 6 months in body mass index and Depression Symptom Checklist-20 scores were co-primary outcomes, and Generalized Anxiety Disorder Scale-7 score was a secondary outcome. Changes at 2 months in the activation and functional connectivity of regions of interest in the negative affect circuit were primary neural targets, and secondary targets were in the cognitive control, default mode, and positive affect circuits.

Results

Participants were 47.0 years (SD = 11.9 years), 76% women, 55% Black, and 20% Latino. Depression Symptom Checklist-20 (between-group difference, -0.3 [95% CI: -0.6 to -0.1]) and Generalized Anxiety Disorder Scale-7 (-2.9 [-4.7 to -1.1]) scores, but not body mass index, decreased significantly at 6 months in the intervention versus usual care groups. Only Generalized Anxiety Disorder Scale-7 score changes at 6 months significantly correlated with neural target changes at 2 months in the negative affect (anterior insula, subgenual/pregenual anterior cingulate cortex, amygdala) and cognitive control circuits (dorsal lateral prefrontal cortex, dorsal anterior cingulate cortex). Effects were medium to large (0.41-1.18 SDs). Neural target changes at 2 months in the cognitive control circuit only differed by treatment group. Effects were medium (0.58-0.79 SDs).

Conclusions

Compared with usual care, the study intervention led to significantly improved depression but not weight loss, and the results on neural targets were null for both outcomes. The significant intervention effect on anxiety might be mediated through changes in the cognitive control circuit, but this warrants replication.

An intensive longitudinal examination of topiramate treatment for alcohol use disorder: a secondary analysis of data from a randomized controlled trial

BACKGROUND AND AIMS

Previous findings have been equivocal as to whether a single-nucleotide polymorphism (rs2832407) in GRIK1, which encodes a glutamate receptor subunit, moderates the effects of topiramate treatment for drinking reduction. We leveraged intensive longitudinal data to provide greater precision and allow an examination of intermediate outcomes addressing this question. We used data from a randomized controlled trial (RCT) to test the hypotheses that topiramate treatment reduces daily heavy drinking, desire to drink and positive alcohol expectancies and that these effects are stronger in rs2832407*C-allele homozygotes.

DESIGN

Secondary data analysis of a randomized controlled trial.

SETTING

University of Pennsylvania Treatment Research Center in the United States.

PARTICIPANTS/CASES

Participants were 164 individuals (70.1% male, mean age = 51.42, 36.0% rs2832407*C-allele homozygotes) who sought to reduce or stop drinking.

INTERVENTION AND COMPARATOR

Participants were assigned to medication (topiramate or placebo), with stratification by genotype group (CC versus AA/AC) and treatment goal (reduce versus abstain).

MEASUREMENTS

During the 12-week treatment period, participants completed daily interactive voice response (IVR) surveys.

FINDINGS

On any given day during treatment, participants who received topiramate had lower odds of IVR-reported heavy drinking [odds ratio (OR) = 0.259, b (standard error, SE) = -1.351 (0.334), P < 0.001] and lower levels of desire to drink [b (SE) = -0.323 (0.122), P = 0.009] and positive alcohol expectancies [b (SE) = -0.347 (0.138), P = 0.013] than those who received placebo. Participants who received topiramate also reported greater reductions in positive alcohol expectancies during the first 2 weeks of treatment than those who received placebo [b (SE) = -0.028 (0.008), P = 0.001], but topiramate did not impact the daily rate of change in heavy drinking or desire to drink. Genotype did not moderate the effects of topiramate on any outcomes examined (P > 0.05).

CONCLUSIONS

Topiramate is an effective medication for individuals seeking to reduce heavy drinking. The effects are not moderated by the single-nucleotide polymorphism rs2832407.

Mind-Body Intervention for Dysfunctional Breathing in Chronic Obstructive Pulmonary Disease: Feasibility Study and Lessons Learned

Purpose: Dysfunctional breathing behaviors are prevalent in chronic obstructive pulmonary disease (COPD). Although these behaviors contribute to dyspnea, abnormal carbon dioxide (CO2) levels, and COPD exacerbations, they are modifiable. Current dyspnea treatments for COPD are suboptimal, because they do not adequately address dysfunctional breathing behaviors and anxiety together. We developed a complementary mind-body breathlessness therapy, called capnography-assisted respiratory therapy (CART), that uses real-time CO2 biofeedback at the end of exhalation (end-tidal CO2 or ETCO2), to target dysfunctional breathing habits and improve dyspnea treatment and pulmonary rehabilitation (PR) adherence in COPD. The study aim was to test the feasibility of integrating CART with a traditional, clinic-based PR program in an urban setting. Methods: We used a feasibility pre- and post-test design, with 2:1 randomization to CART+PR or control (PR-alone) groups, to test and refine CART. Multi-component CART consisted of six, 1-h weekly sessions of slow breathing and mindfulness exercises, ETCO2 biofeedback, motivational counseling, and a home program. All participants were offered twice weekly, 1-h sessions of PR over 10 weeks (up to 20 sessions). Results: Thirty-one participants with COPD were enrolled in the study. Approximately a third of participants had symptoms of psychological distress. Results showed that CART was feasible and acceptable based on 74% session completion and 91.7% homework exercise completion (n = 22). Within-group effect sizes for CART+PR were moderate to large (Cohen's d = 0.51-1.22) for reduction in resting Borg dyspnea (anticipatory anxiety) and respiratory rate, St. George's Respiratory Questionnaire (SGRQ) respiratory symptoms; and increase in Patient-Reported Outcomes Measurement Information System (PROMIS) physical function and physical activity; all p < 0.05. Conclusions: CART is a new mind-body breathing therapy that targets eucapnic breathing, interoceptive function, and self-regulated breathing to relieve dyspnea and anxiety symptoms in COPD. Study findings supported the feasibility of CART and showed preliminary signals that CART may improve exercise tolerance, reduce dyspnea, and enhance PR completion by targeting reduced dysfunctional breathing patterns (CTR No. NCT03457103).

Optimizing and Accelerating the Development of Precision Pain Treatments for Chronic Pain: IMMPACT Review and Recommendations

Large variability in the individual response to even the most-efficacious pain treatments is observed clinically, which has led to calls for a more personalized, tailored approach to treating patients with pain (ie, "precision pain medicine"). Precision pain medicine, currently an aspirational goal, would consist of empirically based algorithms that determine the optimal treatments, or treatment combinations, for specific patients (ie, targeting the right treatment, in the right dose, to the right patient, at the right time). Answering this question of "what works for whom" will certainly improve the clinical care of patients with pain. It may also support the success of novel drug development in pain, making it easier to identify novel treatments that work for certain patients and more accurately identify the magnitude of the treatment effect for those subgroups. Significant preliminary work has been done in this area, and analgesic trials are beginning to utilize precision pain medicine approaches such as stratified allocation on the basis of prespecified patient phenotypes using assessment methodologies such as quantitative sensory testing. Current major challenges within the field include: 1) identifying optimal measurement approaches to assessing patient characteristics that are most robustly and consistently predictive of inter-patient variation in specific analgesic treatment outcomes, 2) designing clinical trials that can identify treatment-by-phenotype interactions, and 3) selecting the most promising therapeutics to be tested in this way. This review surveys the current state of precision pain medicine, with a focus on drug treatments (which have been most-studied in a precision pain medicine context). It further presents a set of evidence-based recommendations for accelerating the application of precision pain methods in chronic pain research. PERSPECTIVE: Given the considerable variability in treatment outcomes for chronic pain, progress in precision pain treatment is critical for the field. An array of phenotypes and mechanisms contribute to chronic pain; this review summarizes current knowledge regarding which treatments are most effective for patients with specific biopsychosocial characteristics.

Mindfulness Training for Depressed Older Adults Using Smartphone Technology: Protocol for a Fully Remote Precision Clinical Trial

BACKGROUND

Precision medicine, optimized interventions, and access to care are catchphrases for the future of behavioral treatments. Progress has been slow due to the dearth of clinical trials that optimize interventions' benefits, individually tailor interventions to meet individual needs and preferences, and lead to rapid implementation after effectiveness is demonstrated. Two innovations have emerged to meet these challenges: fully remote trials and precision clinical trials.

OBJECTIVE

This paper provides a detailed description of Mindful MyWay, a study designed to test online mindfulness training in older adults with depression. Consistent with the concept of fully remote trials using a smartphone app, the study requires no in-person contact and can be conducted with participants anywhere in the United States. Based upon the precision medicine framework, the study assesses participants using high-frequency assessments of symptoms, cognitive performance, and patient preferences to both understand the individualized nature of treatment response and help individually tailor the intervention.

METHODS

Mindful MyWay is an open-label early-phase clinical trial for individuals 65 years and older with current depression. A smartphone app was developed to help coordinate the study, deliver the intervention, and evaluate the acceptability of the intervention, as well as predictors and outcomes of it. The curriculum for the fully remote intervention parallels the mindfulness-based stress reduction curriculum, a protocolized group-based mindfulness training that is typically provided in person. After consent and screening, participants download The Healthy Mind Lab mobile health smartphone app from the Apple App Store, allowing them to complete brief smartphone-based assessments of depressive symptoms and cognitive performance 4 times each day for 4 weeks prior to and after completing the intervention. The intervention consists of an introduction video and 10 weekly mindfulness training sessions, with the expectation to practice mindfulness at home daily. The app collects participant preference data throughout the 10-week intervention period; these high-frequency assessments identify participants' individually dynamic preferences toward the goal of optimizing the intervention in future iterations.

RESULTS

Participant recruitment and data collection began in March 2019. Final end point assessments will be collected in May 2022. The paper describes lessons learned regarding the critical role of early-phase testing prior to moving to a randomized trial.

CONCLUSIONS

The Mindful MyWay study is an exemplar of innovative clinical trial designs that use smartphone technology in behavioral and neuropsychiatric conditions. These include fully remote studies that can recruit throughout the United States, including hard-to-access areas, and collect high-frequency data, which is ideal for idiographic assessment and individualized intervention optimization. Our findings will be used to modify our methods and inform future randomized controlled trials within a precision medicine framework.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03922217; https://clinicaltrials.gov/ct2/show/NCT03922217.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/39233.

Dysregulation of adult hippocampal neuroplasticity in major depression: pathogenesis and therapeutic implications

Major depressive disorder (MDD) was previously hypothesized to be a disease of monoamine deficiency in which low levels of monoamines in the synaptic cleft were believed to underlie depressive symptoms. More recently, however, there has been a paradigm shift toward a neuroplasticity hypothesis of depression in which downstream effects of antidepressants, such as increased neurogenesis, contribute to improvements in cognition and mood. This review takes a top-down approach to assess how changes in behavior and hippocampal-dependent circuits may be attributed to abnormalities at the molecular, structural, and synaptic level. We conclude with a discussion of how antidepressant treatments share a common effect in modulating neuroplasticity and consider outstanding questions and future perspectives.

Pragmatic Precision Psychiatry-A New Direction for Optimizing Treatment Selection

IMPORTANCE

Clinical trials have identified numerous prescriptive predictors of mental disorder treatment response, ie, predictors of which treatments are best for which patients. However, none of these prescriptive predictors is strong enough alone to guide precision treatment planning. This has prompted growing interest in developing precision treatment rules (PTRs) that combine information across multiple prescriptive predictors, but this work has been much less successful in psychiatry than some other areas of medicine. Study designs and analysis schemes used in research on PTR development in other areas of medicine are reviewed, key challenges for implementing similar studies of mental disorders are highlighted, and recent methodological advances to address these challenges are described here.

OBSERVATIONS

Discovering prescriptive predictors requires large samples. Three approaches have been used in other areas of medicine to do this: conduct very large randomized clinical trials, pool individual-level results across multiple smaller randomized clinical trials, and develop preliminary PTRs in large observational treatment samples that are then tested in smaller randomized clinical trials. The third approach is most feasible for research on mental disorders. This approach requires working with large real-world observational electronic health record databases; carefully selecting samples to emulate trials; extracting information about prescriptive predictors from electronic health records along with other inexpensive data augmentation strategies; estimating preliminary PTRs in the observational data using appropriate methods; implementing pragmatic trials to validate the preliminary PTRs; and iterating between subsequent observational studies and quality improvement pragmatic trials to refine and expand the PTRs. New statistical methods exist to address the methodological challenges of implementing this approach.

CONCLUSIONS AND RELEVANCE

Advances in pragmatic precision psychiatry will require moving beyond the current focus on randomized clinical trials and adopting an iterative discovery-confirmation process that integrates observational and experimental studies in real-world clinical populations.

Going remote: Implementing digital research methods at an academic medical center during COVID-19

COVID-19 has forced medical research institutions to conduct clinical research remotely. Here, we describe how a university's mHealth Research Core helped facilitate the shift to remote research during the COVID-19 pandemic. In 2019 (pre-pandemic), we conducted stakeholder interviews and leadership group sessions to identify, create, and implement resources and core functions to support investigator-initiated mHealth research. Between April 2019 and February 2020, we identified four investigator needs: 1) a seminar series on trends in mHealth research, 2) mHealth case consultation services, 3) liaison services with institutional regulatory compliance groups, and 4) online navigation tools for implementation of mHealth methods (e.g., eConsent) and for building partnerships with technology vendors. To date, the mHealth Research Core has held seven seminars, completed 71 case consultations, assisted four COVID-related clinical studies, advised the IRB on shifting to remote research, and widely disseminated eConsent navigation tools. Although pre-pandemic stakeholder and investigator needs led to the creation of the mHealth Research Core, this institutional resource played a critical role in continuing clinical research during the pandemic by assisting investigators in rapidly shifting to remote study methodology.

Precision Psychiatry: Machine learning as a tool to find new pharmacological targets

There is an increasing amount of data arising from neurobehavioral sciences and medical records that cannot be adequately analyzed by traditional research methods. New drugs develop at a slow rate and seem unsatisfactory for the majority of neurobehavioral disorders. Machine learning (ML) techniques, instead, can incorporate psychopathological, computational, cognitive, and neurobiological underpinning knowledge leading to a refinement of detection, diagnosis, prognosis, treatment, research, and support. Machine and deep learning methods are currently used to accelerate the process of discovering new pharmacological targets and drugs.

OBJECTIVE

The present work reviews current evidence regarding the contribution of machine learning to the discovery of new drug targets.

METHODS

Scientific articles from PubMed, SCOPUS, EMBASE, and Web of Science Core Collection published until May 2021 were included in this review.

RESULTS

The most significant areas of research are schizophrenia, depression and anxiety, Alzheimer´s disease, and substance use disorders. ML techniques have pinpointed target gene candidates and pathways, new molecular substances, and several biomarkers regarding psychiatric disorders. Drug repositioning studies using ML have identified multiple drug candidates as promising therapeutic agents.

CONCLUSION

Next-generation ML techniques and subsequent deep learning may power new findings regarding the discovery of new pharmacological agents by bridging the gap between biological data and chemical drug information.

Problem-solving therapy-induced amygdala engagement mediates lifestyle behavior change in obesity with comorbid depression: a randomized proof-of-mechanism trial

BACKGROUND

Depression hinders obesity treatment; elucidating mechanisms may enable treatment enhancements.

OBJECTIVES

The aim was to investigate whether changes in neural targets in the negative affect circuit following psychotherapy mediate subsequent changes in weight and behaviors.

METHODS

Adults (n = 108) with obesity and depression were randomly assigned to usual care or an intervention that delivered problem-solving therapy (PST) for depression over 2 mo. fMRI for brain imaging was performed at baseline and 2 mo. BMI, physical activity, and diet were measured at baseline and 12 mo. Mediation analysis assessed between-group differences in neural target changes using t test and correlations between neural target changes and outcome changes (simple and interaction effect) using ordinary least-squares regression.

RESULTS

Compared with usual care, PST led to reductions in left amygdala activation (-0.75; 95% CI: -1.49, -0.01) and global scores of the negative affect circuit (-0.43; -0.81, -0.06), engaged by threat stimuli. Increases in amygdala activation and global circuit scores at 2 mo correlated with decreases in physical activity outcomes at 12 mo in the usual-care group; these relations were altered by PST. In relation to change in leisure-time physical activity, standardized β-coefficients were -0.67 in usual care and -0.01 in the intervention (between-group difference: 0.66; 0.02, 1.30) for change in left amygdala activation and -2.02 in usual care and -0.11 in the intervention (difference: 1.92; 0.64, 3.20) for change in global circuit scores. In relation to change in total energy expenditure, standardized β-coefficients were -0.65 in usual care and 0.08 in the intervention (difference: 0.73; 0.29, 1.16) for change in left amygdala activation and -1.65 in usual care and 0.08 in the intervention (difference: 1.74; 0.85, 2.63) for change in global circuit scores. Results were null for BMI and diet.

CONCLUSIONS

Short-term changes in the negative affect circuit engaged by threat stimuli following PST for depression mediated longer-term changes in physical activity. This trial was registered at www.clinicaltrials.gov as NCT02246413 (https://clinicaltrials.gov/ct2/show/NCT02246413).

Depression and executive functioning bidirectionally impair one another across 9 years: Evidence from within-person latent change and cross-lagged models

BACKGROUND

Scar and vulnerability models assert that increased psychopathology may predict subsequent executive functioning (EF) deficits (and vice versa) over protracted timescales, yet most prior work on this topic has been cross-sectional. Thus, we tested the within- and between-person relations between EF, depression, and anxiety.

METHODS

Older adult participants (n = 856) were assessed across four waves, approximately 2 years apart. Performance-based EF and caregiver-rated symptom measures were administered. Bivariate latent change score and random-intercept cross-lagged panel models were conducted.

RESULTS

Within persons, random-intercept cross-lagged panel models revealed that prior greater depression forecasted lower subsequent EF, and vice versa (d = -0.292 vs. -0.292). Bivariate dual latent change score models showed that within-person rise in depression predicted EF decreases, and vice versa (d = -0.245 vs. -0.245). No within-person, cross-lagged, EF-anxiety relations emerged. Further, significant negative between-person EF-symptom relations were observed (d = -0.264 to -0.395).

CONCLUSION

Prospective, within-person findings offer some evidence for developmental scar and vulnerability models.