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The use of a stratified psychiatry approach that combines electronic health records (EHR) data with machine learning (ML) is one potentially fruitful path toward rapidly improving precision treatment in clinical practice. This strategy, however, requires confronting pervasive methodological flaws as well as deficiencies in transparency and reporting in the current conduct of ML-based studies for treatment prediction. EHR data shares many of the same data quality issues as other types of data used in ML prediction, plus some unique challenges. To fully leverage EHR datas power for patient stratification, increased attention to data quality and collection of patient-reported outcome data is needed.

Abstract The relative conservation of the influenza hemagglutinin (HA) stem compared to that of the immunodominant HA head makes the HA stem an attractive target for broadly protective influenza vaccines. Here we report the first-in-human, dose-escalation, open-label trial (NCT04579250) evaluating an unadjuvanted group 2 stabilized stem ferritin nanoparticle vaccine based on the H10 A/Jiangxi-Donghu/346/2013 influenza HA, H10ssF, in healthy adults. Participants received a single 20 mcg dose (n = 3) or two 60 mcg doses 16 weeks apart (n = 22). Vaccination with H10ssF was safe and well tolerated with only mild systemic and local reactogenicity reported. No serious adverse events occurred. Vaccination significantly increased homologous H10 HA stem binding and neutralizing antibodies at 2 weeks after both first and second vaccinations, and these responses remained above baseline at 40 weeks. Heterologous H3 and H7 binding antibodies also significantly increased after each vaccination and remained elevated throughout the study. These data indicate that the group 2 HA stem nanoparticle vaccine is safe and induces stem-directed binding and neutralizing antibodies.

Rachel Franklin,1 Sam Zorowitz,1 Andrew K Corse,1 Alik S Widge,2 Thilo Deckersbach1 1Division of Neurotherapeutics, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, 2Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA Abstract: Bipolar disorder (BD) is a debilitating and difficult-to-treat psychiatric disease that presents a serious burden to patients’ lives as well as health care systems around the world. The essential diagnostic criterion for BD is episodes of mania or hypomania; however, the patients report that the majority of their time is spent in a depressive phase. Current treatment options for this component of BD have yet to achieve satisfactory remission rates. Lurasidone is a drug in the benzisothiazole class approved by the US Food and Drug Administration in June 2013 for the acute treatment of bipolar depression. Its pharmacological profile features high-affinity antagonism at D2, 5-HT2A, and 5-HT7 receptors; moderate-affinity antagonism at α2C-adrenergic receptors; low- to very low-affinity antagonism at α1A-adrenergic, α2A-adrenergic, H1, M1, and 5-HT2C receptors; and high-affinity partial agonism at 5-HT1A. Preliminary findings from two recent double-blinded clinical trials suggest that lurasidone is efficacious in treating bipolar I depression, with clinical effects manifesting as early as the first 2–3 weeks of treatment (as measured by the Montgomery–Åsberg Depression Rating Scale and Clinical Global Impressions Scale for use in bipolar illness). Its therapeutic benefit appears to be comparable to the current US Food and Drug Administration-indicated treatments: quetiapine and olanzapine–fluoxetine, according to a measure of effect size known as number needed to treat. These studies reported relatively limited extrapyramidal and metabolic side effects as a result of treatment with lurasidone, with the most common side effect being nausea. Safety data drawn from these studies, as well as a more extensive body of schizophrenia research, indicate that in comparison with other atypical antipsychotics, treatment with lurasidone is less likely to result in metabolic side effects such as weight gain or disturbances of serum glucose or lipid levels. Lurasidone holds clinical potential as a novel, efficacious pharmacological treatment for bipolar depression. However, current data on its use for the treatment of BD are limited, and more extensive research, both longer in duration as well as independently conducted, is needed. Keywords: lurasidone, bipolar depression, bipolar disorder, atypical antipsychotic

Since the introduction of the first antidepressant in the 1950s, biological treatments for unipolar depressive disorders have largely focused on altering monoaminergic neurotransmission, with varying degrees of success. In the [...]

ObjectiveDespite advances in the treatment of psychiatric diseases, currently available therapies do not provide sufficient and durable relief for as many as 30-40% of patients. Neuromodulation, including deep brain stimulation (DBS), has emerged as a potential therapy for persistent disabling disease, however it has not yet gained widespread adoption. In 2016, the American Society for Stereotactic and Functional Neurosurgery (ASSFN) convened a meeting with leaders in the field to discuss a roadmap for the path forward. A follow-up meeting in 2022 aimed to review the current state of the field and to identify critical barriers and milestones for progress.DesignThe ASSFN convened a meeting on June 3, 2022 in Atlanta, Georgia and included leaders from the fields of neurology, neurosurgery, and psychiatry along with colleagues from industry, government, ethics, and law. The goal was to review the current state of the field, assess for advances or setbacks in the interim six years, and suggest a future path forward. The participants focused on five areas of interest: interdisciplinary engagement, regulatory pathways and trial design, disease biomarkers, ethics of psychiatric surgery, and resource allocation/prioritization. The proceedings are summarized here.ConclusionThe field of surgical psychiatry has made significant progress since our last expert meeting. Although weakness and threats to the development of novel surgical therapies exist, the identified strengths and opportunities promise to move the field through methodically rigorous and biologically-based approaches. The experts agree that ethics, law, patient engagement, and multidisciplinary teams will be critical to any potential growth in this area.

Background: A developing literature suggests that transcranial magnetic stimulation (TMS) can target anhedonia and suicidal ideation (SI), core symptoms of treatment-resistant depression (TRD). This present naturalistic study extends the existing literature by investigating the connection between changes in anhedonia and suicidal ideation (SI) related to transcranial magnetic stimulation (TMS), independent of any overall changes in depression. Methods: Pre and post treatment PHQ-9 and IDS-SR data were collected from 181 TRD patients who received dorsolateral prefrontal cortex ( dlPFC) TMS using the Figure-8 or H1-coil. Changes in overall depression symptoms, anhedonia, and SI were analyzed using chi square tests, repeated measure ANOVAS, and linear regression for repeated measures. Results: TMS yielded changes in overall depression symptoms (PHQ-9 Cohen’s d = 1.02; IDS-SR Cohen’s d = 1.05), with 23.9 % and 41.7 % of patients experiencing response as measured by IDS-SR and PHQ-9, respectively. TMS treatment was also associated with large changes in both anhedonia (d = 1.03) and SI (d = 0.88), which were similar in magnitude to changes in all other depression symptoms (d = 0.97). Importantly, changes in anhedonia predicted changes in SI, even after controlling for baseline depression severity and change in other depression symptoms. Limitations: The lack of a control arm and a neuroimaging measure temper mechanistic conclusion. Conclusion: Our results reinforce the effectiveness of TMS in TRD and provide new evidence that anhedonia and SI may belong to a broader symptom cluster potentially undergirded by a shared circuitry accessible to dlPFC TMS.

ObjectiveThe aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials.MethodsA systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included.ResultsA total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis."ConclusionsThere is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.

Extracting meaningful information from high-dimensional data poses a formidable modeling challenge, particularly when the data is obscured by noise or represented through different modalities. This research proposes a novel non-parametric modeling approach, leveraging the Gaussian process (GP), to characterize high-dimensional data by mapping it to a latent low-dimensional manifold. This model, named the latent discriminative generative decoder (LDGD), employs both the data and associated labels in the manifold discovery process. A Bayesian solution is derived to infer the latent variables, allowing LDGD to effectively capture inherent stochasticity in the data. Applications of LDGD are demonstrated on both synthetic and benchmark datasets. Not only does LDGD infer the manifold accurately, but its accuracy in predicting data points’ labels surpasses state-of-the-art approaches. In the development of LDGD, inducing points are incorporated to reduce the computational complexity of Gaussian processes for large datasets, enabling batch training for enhanced efficient processing and scalability. Additionally, we show that LDGD can robustly infer manifold and precisely predict labels for scenarios in which data size is limited, demonstrating its capability to characterize high-dimensional data with limited samples efficiently. These collective attributes highlight the importance of developing non-parametric modeling approaches to analyze high-dimensional data.

Background: Fear overgeneralization is a promising pathogenic mechanism of clinical anxiety. A dominant model posits that hippocampal pattern separation failures drive overgeneralization. Hippocampal network–targeted transcranial magnetic stimulation (HNT-TMS) has been shown to strengthen hippocampal-dependent learning/memory processes. However, no study has examined whether HNT-TMS can alter fear learning/memory. Methods: Continuous theta burst stimulation was delivered to individualized left posterior parietal stimulation sites derived via seed-based connectivity, precision functional mapping, and electric field modeling methods. A vertex control site was also stimulated in a within-participant, randomized controlled design. Continuous theta burst stimulation was delivered prior to 2 visual discrimination tasks (1 fear based, 1 neutral). Multilevel models were used to model and test data. Participants were undergraduates with posttraumatic stress symptoms (final n = 25). Results: Main analyses did not indicate that HNT-TMS strengthened discrimination. However, multilevel interaction analyses revealed that HNT-TMS strengthened fear discrimination in participants with lower fear sensitization (indexed by responses to a control stimulus with no similarity to the conditioned fear cue) across multiple indices (anxiety ratings: β = 0.10, 95% CI, 0.04 to 0.17, p = .001; risk ratings: β = 0.07, 95% CI, 0.00 to 0.13, p = .037). Conclusions: Overgeneralization is an associative process that reflects deficient discrimination of the fear cue from similar cues. In contrast, sensitization reflects nonassociative responding unrelated to fear cue similarity. Our results suggest that HNT-TMS may selectively sharpen fear discrimination when associative response patterns, which putatively implicate the hippocampus, are more strongly engaged.

DBS Think Tank IX was held on August 25-27, 2021 in Orlando FL with US based participants largely in person and overseas participants joining by video conferencing technology. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging deep brain stimulation (DBS) technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank IX speakers was that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. After collectively sharing our experiences, it was estimated that globally more than 230,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. As such, this year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia and Australia; cutting-edge technologies, neuroethics, interventional psychiatry, adaptive DBS, neuromodulation for pain, network neuromodulation for epilepsy and neuromodulation for traumatic brain injury.

Obsessive-compulsive disorder (OCD), a leading cause of disability, affects ~1-2% of the population, and can be distressing and disabling. About 1/3 of individuals demonstrate poor responsiveness to conventional treatments. A small proportion of these individuals may be deep brain stimulation (DBS) candidates. Candidacy is assessed through a multidisciplinary process including assessment of illness severity, chronicity, and functional impact. Optimization failure, despite multiple treatments, is critical during screening. Few patients nationwide are eligible for OCD DBS and thus a multi-center approach was necessary to obtain adequate sample size. The study was conducted over a six-year period and was a NIH-funded, eight-center sham-controlled trial of DBS targeting the ventral capsule/ventral striatum (VC/VS) region. There were 269 individuals who initially contacted the sites, in order to achieve 27 participants enrolled. Study enrollment required extensive review for eligibility, which was overseen by an independent advisory board. Disabling OCD had to be persistent for ≥5 years despite exhaustive medication and behavioral treatment. The final cohort was derived from a detailed consent process that included consent monitoring. Mean illness duration was 27.2 years. OCD symptom subtypes and psychiatric comorbidities varied, but all had severe disability with impaired quality of life and functioning. Participants were randomized to receive sham or active DBS for three months. Following this period, all participants received active DBS. Treatment assignment was masked to participants and raters and assessments were blinded. The final sample was consistent in demographic characteristics and clinical features when compared to other contemporary published prospective studies of OCD DBS. We report the clinical trial design, methods, and general demographics of this OCD DBS sample.

Objective.Despite advances in the treatment of psychiatric diseases, currently available therapies do not provide sufficient and durable relief for as many as 30–40% of patients. Neuromodulation, including deep brain stimulation (DBS), has emerged as a potential therapy for persistent disabling disease, however it has not yet gained widespread adoption. In 2016, the American Society for Stereotactic and Functional Neurosurgery (ASSFN) convened a meeting with leaders in the field to discuss a roadmap for the path forward. A follow-up meeting in 2022 aimed to review the current state of the field and to identify critical barriers and milestones for progress.Design.The ASSFN convened a meeting on June 3, 2022 in Atlanta, Georgia and included leaders from the fields of neurology, neurosurgery, and psychiatry along with colleagues from industry, government, ethics, and law. The goal was to review the current state of the field, assess for advances or setbacks in the interim six years, and suggest a future path forward. The participants focused on five areas of interest: interdisciplinary engagement, regulatory pathways and trial design, disease biomarkers, ethics of psychiatric surgery, and resource allocation/prioritization. The proceedings are summarized here.Conclusion.The field of surgical psychiatry has made significant progress since our last expert meeting. Although weakness and threats to the development of novel surgical therapies exist, the identified strengths and opportunities promise to move the field through methodically rigorous and biologically-based approaches. The experts agree that ethics, law, patient engagement, and multidisciplinary teams will be critical to any potential growth in this area.

BackgroundSocial media holds exciting promise for advancing mental health research recruitment, however, the extent and efficacy to which these platforms are currently in use are underexplored.ObjectiveA systematic review was conducted to characterize the current use and efficacy of social media in recruiting participants for mental health research.MethodA literature review was performed using MEDLINE, EMBASE, and PsychINFO. Only non-duplicative manuscripts written in the English language and published between 1/1/2004-3/31/2019 were selected for further screening. Data extracted included study type and design, participant inclusion criteria, social media platform, advertising strategy, final recruited sample size, recruitment location, year, monetary incentives, comparison to other recruitment methods if performed, and final cost per participant.ResultsA total of 176 unique studies that used social media for mental health research recruitment were reviewed. The majority of studies were cross-sectional (62.5%) in design and recruited adults. Facebook was overwhelmingly the recruitment platform of choice (92.6%), with the use of paid advertisements being the predominant strategy (60.8%). Of the reviewed studies, substance abuse (43.8%) and mood disorders (15.3%) were the primary subjects of investigation. In 68.3% of studies, social media recruitment performed as well as or better than traditional recruitment methods in the number and cost of final enrolled participants. The majority of studies used Facebook for recruitment at a median cost per final recruited study participant of $19.47. In 55.6% of the studies, social media recruitment was the more cost-effective recruitment method when compared to traditional methods (e.g., referrals, mailing).ConclusionSocial media appears to be an effective and economical recruitment tool for mental health research. The platform raises methodological and privacy concerns not covered in current research regulations that warrant additional consideration.

Vaccines against the WA1 SARS-CoV2 strain confer protection against other variants. However, the mechanisms underlying cross-protection are not fully understood. Here, the authors develop a method for rapid analysis of single B cells from patient samples and show that infection with a variant elicits convergent, public B cell responses to other variants.

ObjectiveRecent advances in neural engineering have restored mobility to people with paralysis, relieved symptoms of movement disorders, reduced chronic pain, restored the sense of hearing, and provided sensory perception to individuals with sensory deficits.ApproachThis progress was enabled by the team-based, interdisciplinary approaches used by neural engineers. Neural engineers have advanced clinical frontiers by leveraging tools and discoveries in quantitative and biological sciences and through collaborations between engineering, science, and medicine. The movement toward bioelectronic medicines, where neuromodulation aims to supplement or replace pharmaceuticals to treat chronic medical conditions such as high blood pressure, diabetes and psychiatric disorders is a prime example of a new frontier made possible by neural engineering. Although one of the major goals in neural engineering is to develop technology for clinical applications, this technology may also offer unique opportunities to gain insight into how biological systems operate.Main resultsDespite significant technological progress, a number of ethical and strategic questions remain unexplored. Addressing these questions will accelerate technology development to address unmet needs. The future of these devices extends far beyond treatment of neurological impairments, including potential human augmentation applications. Our task, as neural engineers, is to push technology forward at the intersection of disciplines, while responsibly considering the readiness to transition this technology outside of the laboratory to consumer products.SignificanceThis article aims to highlight the current state of the neural engineering field, its links with other engineering and science disciplines, and the challenges and opportunities ahead. The goal of this article is to foster new ideas for innovative applications in neurotechnology.