Croarkin, Paul E.

Transcranial magnetic stimulation can provide noninvasive measures of cortical excitability and plasticity, but relationships between these measures and clinically observable features of autism are not fully characterized. Nineteen autistic participants aged 15 to 40 years were included in the analysis of a left primary motor cortex continuous theta-burst stimulation (cTBS) biomarker protocol. Motor evoked potentials were measured at baseline and at seven assessments from 5 to 60 min after stimulation. Linear mixed-effects models evaluated whether clinical measures moderated the post-stimulation motor evoked potential log-response ratio over time. Aberrant Behavior Checklist (ABC) and Attenuated Behavior Questionnaire (ABQ) analyses were restricted to the same 15 participants with caregiver-informant assessments. Catatonia severity, social impairment, ABQ Motor Total, ABQ Total, and cognitive ability did not significantly moderate the post-stimulation response. ABC Inappropriate Speech was associated with progressively greater post-stimulation facilitation (standardized Time-by-Inappropriate Speech interaction: beta = +0.688, SE = 0.210, 95% CI +0.276 to +1.099; Holm-adjusted P = .008 across eight informant-rated models). Two individual speech-related items ("Talks excessively" and "Talks to self loudly") survived false-discovery-rate correction. An exploratory eight-item ABC phenotype showed a large descriptive in-sample association (beta = +0.904, SE = 0.200, P less than .001) and directionally positive held-out performance. However, full-pipeline permutation tests were nonsignificant for both Pearson (r = .357, two-sided empirical P = .360) and Spearman correlations (rho = .446, two-sided empirical P = .261). Caregiver-rated inappropriate speech may be associated with altered post-cTBS motor cortical facilitation in autism. The candidate phenotype remains hypothesis-generating and requires independent validation.

ABSTRACT Consumer‐grade wearables, including smartwatches, fitness trackers, and smart rings, are accessible tools for studying pharmacologic responses in real‐time, monitoring participant health in decentralized clinical trials, optimizing outcome measures, and delivering digital interventions that promote behavior change. However, incorporating consumer wearables into clinical studies is not as straightforward as simply purchasing devices and providing them to participants. It requires engaging with a complex engineering ecosystem with multiple investigator decisions on device selection, associated data management practices, and patient/participant engagement and technical support. This tutorial, based on experience running large clinical trials using consumer wearables, outlines the wearables market landscape across varying form factors and manufacturers as well as the data management software products supporting wearable use. It delineates the major decision processes involved in designing studies that incorporate wearables and presents a structured framework to guide the selection of devices and supporting data tools according to study objectives.

Background: Cardiac biomarkers are recognized as potential indicators for brain function, emotion regulation, and psychiatric risk. While research in adults has suggested associations between cardiac variables of autonomic function and neural changes, little is known about these relationships in children and young adults with psychiatric conditions. This systematic review aimed to examine the evidence linking cardiac biomarkers with structural, functional, and connectivity-based brain changes in this population. Methods: A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Multiple databases were searched for studies examining associations between any cardiac biomarker and neuroimaging findings in individuals under 21 years old with psychiatric diagnoses. After screening and full-text review, 11 eligible studies were included. Results: The included studies investigating a range of psychiatric conditions and cardiac biomarkers were associated with brain changes across three domains: structure, connectivity, and neural responses. Associations were most consistent between higher vagal tone and structural and functional integrity of emotion-regulating regions such as the prefrontal cortex, amygdala, and insula. However, findings were heterogeneous and potentially moderated by symptom severity or environmental stressors. Conclusions: This review supports the potential of cardiac biomarkers, particularly high-frequency heart rate variability and root mean square of the successive differences, as proxies of brain changes in youth with psychiatric disorders. While promising, current evidence is too limited and variable for clinical applications. Future research should prioritize large-scale, longitudinal studies using harmonized protocols and wearable technologies to validate these indices as translational tools in child and adolescent psychiatry.

Introduction Sleep is routinely assessed in the management of mental health conditions. Wearable technologies like smartwatches offer a non-intrusive method to quantitatively measure sleep. However, there are limited empirical benchmarks for sleep duration and sleep quality measured by wearables against user reports. This study aims to evaluate the concordance between user-reported and smartwatch-measured hours of sleep and sleep quality. Methods Participants were recruited from two decentralized digital health well-being studies and completed a 7-day sleep diary while simultaneously wearing their smartwatch to sleep (November 7, 2023 - June 30, 2024). Participants self-reported sleep timestamps and perceived sleep quality using the Sleep Quality Scale. Sleep timestamps and quality were also derived from their smartwatches (Garmin Vívoactive 4 2019, Garmin Venu 2 Plus 2022, and Garmin Venu 3/3S 2023). Statistical analyses included paired t-tests, equipercentile linking, and chi-square tests to assess agreement between smartwatch and self-reported sleep parameters. Exploratory analyses established the difference between reported and recorded sleep duration in healthcare shift workers. Results From 841 sleep instances reported by 130 participants wearing three different generation smartwatches, the mean difference in sleep duration between smartwatch-recorded and participant-reported was 21.22 (Garmin Vívoactive), 11.67 (Garmin Venu 2 Plus), and 6.58 (Garmin Venu 3/3S) minutes, respectively. There were statistically significant between-group differences in mean sleep durations assessed by participant self-report vs. Vívoactive 4 smartwatches, but not self-report vs. Venu 2 Plus or Venu 3/3S smartwatches. Equipercentile linking revealed concordance between smartwatch sleep scores and self-reported sleep quality using the Sleep Quality Scale (SQS) between 4 and 7, with disagreements observed at the SQS ranges from 0–4 and 7-10. Conclusions These results suggest that wearables can reliably measure sleep duration, and future research warrants improvements in algorithms that estimate sleep quality with validations across different wearable vendors.

Background Psychiatric comorbidities are increasingly recognised in demyelinating diseases, yet their frequency and timing in myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) are not well defined. We aimed to characterise the spectrum and temporal pattern of psychiatric illness in MOGAD and compare to multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) with aquaporin-4 antibody (AQP4-IgG). Methods We conducted a cross-sectional study of patients with MOGAD (n=388), age-matched and sex-matched MS (n=257) and AQP4-IgG-positive NMOSD (n=58) evaluated at Mayo Clinic (1991–2025). Psychiatric diagnoses, timing relative to the first attack and patient-reported outcomes were extracted from electronic health records (EHRs). Complementary analyses were conducted using the NeuroBlu real-world EHR database. Results Among 388 patients with MOGAD, 54.8% had ≥1 psychiatric disorder, most commonly anxiety (47.7%), depression (36.6%) and attention-deficit/hyperactivity disorder (ADHD, 9%). After the first attack, 33.3% of patients with MOGAD developed a new psychiatric disorder, often within the first year. MOGAD showed a lower frequency of depression versus MS (36.6% vs 47.5%, p=0.02) but similar rates of anxiety and ADHD. Temporal patterns differed: psychiatric disorders often appeared years before onset in MS but clustered shortly after onset in MOGAD. NeuroBlu analyses supported high rates of psychiatric disorders across the three conditions. Conclusion Psychiatric comorbidities are common in MOGAD, particularly depression and anxiety, typically emerging close after onset, whereas in MS they often preceded onset by years. These findings underscore the need for routine psychiatric screening in MOGAD and highlight unresolved questions regarding whether, and to what extent, MOG-IgG-mediated inflammatory demyelination contributes to psychiatric vulnerability.

Introduction Psychiatric disorders have their genesis in early life. Standard screening approaches during well child visits for pathological infant distress, maternal depression, and dysfunctional parenting behaviors are likely inadequate. Microbiome measures and infant vocalizations have promise as scalable psychiatric biomarkers for infants. The purpose of this study was to examine associations among infant gut colonization based on microbiome measurements with maternal distress and maternal depressive symptoms in a sample of infants. Methods This study sought to examine infant microbiome correlates of infant distress, parent-infant interactions, maternal distress, and maternal depressive symptoms. We collected ( N = 31) microbiome samples, infant vocalizations during vaccination, and behavioral measures during a 4 month well child visit (WCV) and did a battery of clinical assessments to assess for maternal depression, parent-child interactions, family characteristics and family stress. Whole-genome SHOTGUN sequencing was utilized to identify three types of associations: alpha-diversity using Shannon and Inverse-Simpson indexes, beta-diversity using Bray-Curtis and Jaccard distances, and differential abundance using LinDA. Spectral measures of infant cries were also modeled to assess potential relationships with clinical assessments and the microbiome. Results There were 19 phyla, 417 genera, and 1246 species identified with taxonomic classification. Maternal distress as measured by PHQ-9 scores obtained when infants were 2 months old were associated with 4 bacterial species ( Actinomyces johnsonii, Bilophila wadsworthia, Clostridium dakarense and Ruminococcus flavefaciens ; FDR < 0.1) and beta-diversity ( p = 0.006-BC; p = 0.005-Jaccard). Infant cries with greater high frequency band power ( p < 0.03) and a greater high-to-mid frequency ratio–metrics ( p < 0.05) were associated with altered α-diversity of the microbiome. No correlations were present between maternal PHQ-9 at 4 months, PSI-IV and microbiome diversity. Conclusion The present findings suggest that an infant stress (assessed by quality of crying) is associated with lower microbiome diversity. Decreased diversity reflects an unhealthy microbiome. Parental depressive symptoms may also influence infant microbiome. Future interventional studies focused on the quality of the infant-caregiver relationship should examine related changes in intestinal microbiota.

Importance The potential utility of real-time digital therapeutics that identify impending behavioral outbursts to proactively apply evidence-based interventions for managing children with disruptive behavior disorder has not been tested. Objectives To evaluate feasibility and adherence of a digitally augmented, real-time, proactive behavioral intervention (smartwatch) for children with disruptive behaviors. Design, Setting, and Participants This randomized clinical trial was conducted between March 1, 2022, and December 31, 2023, at Mayo Clinic in Rochester, Minnesota. The study enrolled children aged 3 to 7 years with externalizing behavior problems rated above the clinically significant range (I score ≥120; T score ≥60) on the Eyberg Child Behavior Inventory (ECBI). Interventions Twelve weekly sessions of parent-child interaction therapy (PCIT) (treatment as usual [TAU] arm) vs artificial intelligence (AI)–enhanced PCIT augmented with real-time behavioral outburst alerts (PCIT-AI arm). Main Outcomes and Measures The primary outcome was achieving the a priori feasibility benchmark set at greater than 70% for both completion of PCIT sessions and daily smartwatch wear. Parental reaction time to behavior prompts was measured in seconds. Secondary outcomes were percentage changes in ECBI and Pediatric Sleep Questionnaire scores. Behavioral outburst duration was examined based on parental logs of start and end times of observed tantrums using a smartphone application. Result This study enrolled 50 children (median [IQR] age, 5.0 [4.0-6.0] years; 34 [68%] male and 16 [32%] female; 28 randomized to the PCIT-AI arm and 22 to the PCIT-TAU arm). Of these children, 37 (74%; 21 in the PCIT-AI arm and 16 in the PCIT-TAU arm) completed PCIT, with children wearing the watch a median (IQR) 75.7% (67.8%-82.9%) of the time, thus achieving the feasibility benchmark (primary outcome). Median (IQR) response time to behavior prompts in the PCIT-AI arm was 3.65 (2.07-7.08) seconds. Assessing between-group differences, there was no statistically significantly greater numerical improvement in ECBI-intensity percentage change (13.86%; 95% CI, −1.41% to 29.14%), ECBI-problem percentage change subscale scores (38.59%; 95% CI, −1.22% to 78.40%), or absolute change in Pediatric Sleep Questionnaire scores (−0.16; 95% CI, −1.85 to 1.53) with the PCIT-AI arm than with the PCIT-TAU arm. Children in the PCIT-AI arm had significantly shorter mean (SD) tantrum durations (10.4 [20.8] minutes vs 22.1 [30.0] minutes; P &amp;lt; .001) and lower odds of tantrums lasting for 15 minutes or more (odds ratio, 3.66; 95% CI, 2.72-4.95). Conclusions and Relevance In this randomized clinical trial, both recruitment and technology feasibility benchmarks were achieved. The findings inform the design of fully powered efficacy study of wearable, digitally augmented PCIT for children with disruptive behaviors. Trial Registration ClinicalTrials.gov Identifier: NCT05077722