AI Tool Helps Link BRSK1 Variants to Neurodevelopmental Disorder

For many families affected by rare genetic conditions, genomic testing does not immediately deliver an answer. Now, researchers have combined artificial intelligence, human genetics, and fruit fly experiments to connect variants in BRSK1 with a complex neurodevelopmental disorder. The findings provide a potential diagnosis for several previously unexplained cases while offering clues about how reduced activity of the gene may disrupt nervous system development.

The study, “Monoallelic variants in BRSK1 are associated with a neurodevelopmental disorder with or without epilepsy,” was led by researchers at Baylor College of Medicine, the Duncan Neurological Research Institute at Texas Children’s Hospital, and the Texome Project, together with collaborating institutions. It was published in the American Journal of Human Genetics.

According to Hugo Bellen, PhD, who is co-lead author of the study, the work began with a child enrolled in the Texome Project, which provides genetic testing to medically underserved people with rare, undiagnosed conditions in Texas. Standard analysis of the child’s and parent’s genomes had not identified a cause. AI-MARRVEL, an artificial intelligence–based tool that analyzes genomic and clinical information to prioritize candidate disease variants, highlighted a rare change in BRSK1. Through GeneMatcher, the researchers identified nine additional affected individuals with rare heterozygous variants in the gene, bringing the group to 10 people from seven unrelated families. The team then modeled three patient-derived variants in Drosophila melanogaster to test their effects in a living organism.

The “affected individuals present with developmental delay and variable phenotypes including anxiety, attention-deficit hyperactivity disorder (ADHD), autism, and seizures,” the authors wrote, adding that the severity and symptoms varied. Symptoms differed even among relatives carrying the same variant, suggesting variable expressivity.

“We studied the fly equivalent of BRSK1, called sff (sugar-free frosting), and found that this gene is active primarily in neurons, mirroring the expression pattern seen in humans,” added Mingxi Deng, PhD, who is first author and a postdoctoral fellow in the Bellen lab. “When the fly gene was disabled, the flies developed difficulties moving, showed increased sensitivity to stressors that can trigger seizure-like behavior, became more vulnerable to heat-induced paralysis and lived shorter lives. These findings indicated that the gene is essential for normal nervous system function.”

Introducing normal human BRSK1 largely corrected the behavioral and neurological defects, whereas three variants (BRSK1p.Ile202Val, BRSK1p.Arg237Cys, and BRSK1p.Thr406Ile) found in affected individuals produced only a partial rescue. The patient variants also failed to normalize neuromuscular junction structure or levels of Futsch, a protein involved in organizing neuronal microtubules. Together, the experiments suggest that the variants partially reduce BRSK1 activity rather than eliminating it.

“Microtubule disruption has been linked to several neurodevelopmental and neurological disorders,” Deng said. “Our findings suggest that reduced BRSK1 function interferes with the cellular machinery needed for healthy brain development and communication between neurons.”

BRSK1 encodes a kinase involved in neuronal polarization, synaptic function, and the internal organization of nerve cells. Reduced activity may therefore interfere with the cellular machinery neurons need to develop and communicate. “This work improves our understanding of the genetic causes of neurodevelopmental disorders and highlights the power of combining AI-driven gene discovery with experimental studies in model organisms to uncover new rare diseases and their underlying biology,” Bellen said.

The diagnosis may help participating families understand the source of their condition and could guide recognition of additional cases. Future studies will be needed to determine why the same variant can produce markedly different symptoms and to define more precisely how altered BRSK1 activity affects the developing brain.

The post AI Tool Helps Link <i>BRSK1</i> Variants to Neurodevelopmental Disorder appeared first on GEN – Genetic Engineering and Biotechnology News.

Adolescent non-suicidal self-injury scale – short form: revision and evaluation of its reliability and validity

ObjectiveNon-suicidal self-injury (NSSI) is a clinically significant concern among adolescents, and its accurate yet efficient assessment is essential for research, early identification, and intervention. Existing Chinese instruments—most notably the 19-item Adolescent Self-Harm Questionnaire (ASHS)—are relatively lengthy and ill-suited to rapid, large-scale screening. The present study had two aims: (a) to develop a short form of the ASHS, the Adolescent Non-Suicidal Self-Injury Scale–Short Form (ANSSI-SF), by integrating classical test theory (CTT) item analysis with genetic algorithm (GA) cross-validation, and (b) to evaluate its reliability, validity, and screening utility relative to the parent scale.MethodsUsing a convenience sample of 1,090 primary and secondary school students, seven items—one for each of seven behavioral categories derived from a functional–typological framework of self-harm—were selected on the basis of CTT item statistics and GA cross-validation. The scale was evaluated through item analysis, internal-consistency and split-half reliability, exploratory and confirmatory factor analysis (EFA/CFA), correlations with theoretically related constructs, known-groups comparisons (gender; smartphone addiction), and consistency and screening-accuracy analyses against the full 19-item ASHS.ResultsIt indicated that all items demonstrated strong correlations with the total score, and both internal consistency and split-half reliability reached satisfactory levels.A unidimensional factor structure also exhibited good model fit. Additionally, scale scores were significantly positively correlated with related psychological indicators such as depression, anxiety, and sleep problems, and effectively differentiated differences in self-injurious behavior across gender and smartphone addiction groups.GA cross-validation confirmed that the selected items balanced parsimony with full coverage of all seven behavioral categories.DiscussionThese findings indicate that the ANSSI-SF is a brief, reliable, and valid instrument that preserves the content breadth of the parent ASHS while substantially reducing administration burden. It is well suited to rapid, large-scale screening and early identification of at-risk adolescents, facilitating timely referral and prevention. Limitations include convenience sampling from a single region and the absence of test–retest reliability; future research should validate the scale in clinical and diverse cultural samples and examine its predictive validity.

The chain-mediating effect of societal pressure on appearance and body image on fear of negative evaluation and social anxiety in women with polycystic ovary syndrome: a cross-lagged panel analysis

Objective(Prospective Longitudinal Observational Study) This study aimed to examine the longitudinal chain mediating roles of physical appearance social pressure and body image in the relationship between fear of negative evaluation (FNE) and social anxiety among women with polycystic ovary syndrome (PCOS), and to clarify the temporal sequencing among these variables.MethodsConvenience sampling was used to recruit 264 women with PCOS. Participants completed the Sociocultural Attitudes Towards Appearance Questionnaire-4 Revised (SATAQ-4R), Body Image States Scale (BISS), Brief Fear of Negative Evaluation Scale (BFNE), and Social Anxiety Scale (SAS) at baseline (T0), 3 months (T1), and 6 months (T2), yielding 242 valid cases. Data were analyzed using measurement invariance testing, cross-lagged panel analysis (CLPA), and bootstrapping.ResultsFull measurement invariance was established across the three timepoints (ΔCFI ≤0.01, ΔTLI ≤0.01). The final CLPA model demonstrated excellent fit (CFI = 0.988, TLI = 0.959, RMSEA = 0.023, 90% CI: 0.021–0.026). T0 FNE positively predicted T1 appearance social pressure (β = 0.25, P <0.001) and T1 SA (β = 0.23, P <0.001), and negatively predicted T1 body image (β = −0.19, P <0.001). T1 appearance social pressure positively predicted T2 SA (β = 0.22, P <0.001). T1 body image negatively predicted T2 SA (β = −0.18, P <0.01). T1 SA positively predicted T2 FNE (β = 0.13, P <0.001). Bootstrap analyses revealed significant indirect effects via T1 appearance social pressure (β = 0.055, 95% CI: 0.028–0.082) and T1 body image (β = 0.034, 95% CI: 0.015–0.053), as well as a significant chain mediation effect (β = 0.018, 95% CI: 0.007–0.029).ConclusionLongitudinal evidence supports a chain mediating pathway wherein elevated fear of negative evaluation at baseline is prospectively associated with subsequent increases in appearance social pressure and declines in body image, which in turn correspond to higher levels of social anxiety in women with PCOS. Findings support the potential utility of early psychological screening and targeted interventions addressing maladaptive cognitions and body image disturbances, although causal efficacy requires validation via randomized controlled trials.

Routine Online Psychological Therapy in an Insurance-Based Care Setting: Retrospective Service Evaluation of Real-World Outcomes

<strong>Background:</strong> Depression, anxiety, and stress-related difficulties represent a major global health burden. Online psychological therapy has emerged as a promising approach to increasing access to care, yet evidence from routine, real-world clinical settings, particularly for services delivered without standardized treatment protocols, remains limited. <strong>Objective:</strong> This study aimed to describe symptom change and patient-reported satisfaction associated with routine online psychological therapy delivered within an insurance-based care setting. <strong>Methods:</strong> A retrospective observational service evaluation was conducted using deidentified routine care data. Clients aged 15 years and older who initiated online psychological therapy and completed baseline and end-of-treatment assessments on all 3 outcome measures were included. Symptoms of depression, anxiety, and perceived stress were measured using the 9-item Patient Health Questionnaire (PHQ-9), 7-item Generalized Anxiety Disorder (GAD-7), and 10-item Perceived Stress Scale (PSS-10), respectively. Changes in symptoms were examined using paired sample <i>t</i> tests, within-sample effect sizes (Cohen <i>d</i> and Cohen <i>d<sub>z</sub></i> with 95% CIs), and reliable change indices. Robustness was assessed with therapist-clustered mixed models and attrition sensitivity analyses. A ≥50% reduction in symptom scores was reported as a descriptive response criterion. Patient satisfaction was assessed with single-item ratings at the end-of-treatment assessment. <strong>Results:</strong> A total of 1221 clients were included. Clients completed a mean of 4.7 (SD 1.67) therapy sessions over an average treatment duration of 62.7 (SD 40.4) days. Significant reductions with large within-sample effect sizes were observed for depression (Cohen <i>d</i>=1.25, 95% CI 1.17-1.32), anxiety (Cohen <i>d</i>=1.49, 95% CI 1.41-1.57), and perceived stress (Cohen <i>d</i>=1.46, 95% CI 1.38-1.54). A ≥50% symptom reduction was observed in 60.7% (741/1220) of clients for depression, 67.5% (824/1221) for anxiety, and 30.8% (376/1221) for perceived stress. At the end-of-treatment assessment, 80.7% (985/1221) scored below the clinical cutoff for depression (PHQ-9&lt;10) and 79.2% (967/1221) for anxiety (GAD-7&lt;8). Reliable improvement was observed in 56% (688/1221) to 65% (794/1221) of clients, with deterioration below 2% on all measures. Mean patient-reported satisfaction scores ranged from 8.55 (SD 1.71) to 8.96 (SD 1.45) on a 10-point scale, and mean recommendation likelihood was 8.61 (SD 1.88). Therapist-level intraclass correlation coefficients were ≤0.029; effect sizes were 1.27-1.50 under inverse-probability weighting and 0.41-0.50 under zero-change imputation for baseline-screened clients without end-of-treatment assessments. <strong>Conclusions:</strong> Routine online psychological therapy delivered within an insurance-based care setting was associated with substantial pre-post symptom reductions, high proportions of clients meeting a descriptive ≥50% reduction criterion and showing reliable improvement, and high patient-reported satisfaction. Because the evaluation used an uncontrolled pre-post design restricted to clients with paired assessments, observed changes cannot be attributed causally to treatment. High satisfaction among responding clients is consistent with acceptability of the model to those clients; feasibility was not formally assessed, and inferences about comparative effectiveness require controlled designs.

Perinatal Mental Health Detection and Prediction Using Mobile Sensing Data: Systematic Review

Background: Perinatal mental health disorders affect approximately 20% of pregnant and postpartum individuals, and are associated with substantial maternal and infant morbidity. Traditional assessment relies on infrequent, subjective self-reports. Mobile devices, including smartphones and wearables, offer opportunities for continuous and objective measurement, but evidence on their assessment utility in perinatal populations remains fragmented. Objective: This review aimed to examine the application of wearable devices and smartphones for detecting and predicting perinatal mental health outcomes, with emphasis on predictive performance, informative features, and methodological rigor. Methods: We conducted a systematic review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines (PROSPERO CRD420251249218). Six databases (PubMed, Web of Science, Scopus, PsycINFO, IEEE Xplore, and ACM Digital Library) were searched initially in January 2026 and supplemented by an amended search in June 2026, with no publication date restrictions. Evidence was synthesized narratively, and the risk of bias was assessed using PROBAST+AI (Prediction Model Risk of Bias Assessment Tool With AI extension). Results: The initial and supplementary searches yielded 1952 unique records after deduplication, of which 10 studies met the inclusion criteria. The included studies covered postpartum depression, prenatal stress, discrete emotions during pregnancy (eg, happiness, anxiety, and sadness), and maternal loneliness. High discrimination metrics were reported for postpartum depression in individual studies, including a multiclass area under the curve of 0.85, a binary area under the curve of 0.871, and an -score of 0.9872. Heart rate variability, GPS-derived mobility, physical activity, and sleep features were most frequently reported as useful, and their interpretation requires perinatal-specific contextualization. Methodological quality was limited, with 80% (12/15) of PROBAST+AI assessment units rated as having high overall quality concern or risk of bias, mainly due to small samples, limited validation, inadequate handling of missing data, and potential overfitting in the analysis domain. Conclusions: Mobile sensing shows preliminary potential for perinatal mental health assessment, but current evidence does not yet support clinical screening or decision-making, and independent external validation in perinatal populations is currently lacking. Progress toward clinical utility requires broader mental health outcome coverage, larger longitudinal cohorts, standardized analytical and reporting practices, adoption of modeling approaches better suited to perinatal trajectories, independent external validation, and human-centered monitoring designs.
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Assessing the Need for Mental Health Support From Free-Text Responses: Development and Validation of Language-Based Assessments in Adults With Internalizing Symptoms

Background: Machine learning and natural language processing have demonstrated significant potential for mental health assessment: describing your mental health in your own words can offer a more ecologically valid approach than traditional rating scales. However, most models focus on specific diagnoses, conditions, or symptoms, which may prematurely assign labels and potentially reinforce stigma in the context of early-stage mental health screening. Objective: This study develops a language-based assessment model that assesses the need for mental health support based on probed natural language and validates it against best-estimate assessments from multiple experienced psychotherapists. Methods: We analyzed an enriched online sample (n=600 for development and n=212 for validation), in which about half reported experiencing internalizing symptoms (depression or anxiety). Participants described their mental health using open-ended responses regarding (1) mental health, (2) suicidal thoughts, (3) medical history, and (4) depression. The responses were converted into contextual word embeddings using a large language model and entered as predictors in a ridge regression using nested cross-validation. Two to three experienced psychotherapists assessed each participant’s need for mental health support on a scale from 1 (no support needed) to 5 (potential crisis). Their assessments were based on longitudinal clinical data (natural language, validated scales, clinical interview, sociodemographics, and clinical history) and were averaged into a best-estimate assessment for model validation. We used the Sequential Evaluation With Model Preregistration framework, which separates model development from validation in a held-out set to support robust estimations and generalizability. Results: The language-based assessments closely aligned with the best-estimate assessments (=0.82) and showed strong correlations with established clinical rating scales for depression (Patient Health Questionnaire-9), anxiety (Generalized Anxiety Disorder 7-Item Scale), stress (Perceived Stress Scale 10), and suicidality (Inventory of Depression and Anxiety Symptoms; =0.62-0.77). Language-based visualizations of topics and word embeddings showed that low need for support assessments was associated with mentioning well-being and good health, while high assessments were related to depression, anxiety, and suicidality. Conclusions: This study demonstrates that natural language responses analyzed through large language models and machine learning can be used to assess individuals’ need for mental health support in close alignment with best-estimate assessments from experienced psychotherapists. Using less than 5 minutes of respondent time, this approach offers a practical tool for early-stage mental health screening in both clinical and self-guided screening contexts.
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Non-motor correlates of anxiety in de novo Parkinson’s disease: a cross-sectional study with exploratory subgroup analyses

ObjectiveAnxiety is a prevalent early non-motor symptom of Parkinson’s disease (PD), but its clinical correlates remain poorly defined in de novo, drug-naïve patients. This retrospective cross-sectional study enrolled 284 medication-naïve de novo PD patients and 147 age- and sex-matched healthy controls to identify non-motor correlates of anxiety after adjustment for demographic and motor covariates, and explore potential subgroup heterogeneity.MethodsAnxiety was assessed with the Hamilton Anxiety Rating Scale; multivariate logistic regression and prespecified stratified analyses by age, sex, disease duration, Hoehn-Yahr stage and motor severity were performed.ResultsClinically significant anxiety was detected in 44.0% of PD patients versus 8.1% of controls (p < 0.001), with psychic anxiety as the dominant subtype. After multivariate adjustment, higher depressive symptom scores were positively associated with anxiety (OR = 1.386), whereas better sleep quality (OR = 0.965) and intact olfactory identification (OR = 0.815) were negatively associated with anxiety; motor severity showed no significant association after multivariable adjustment. Exploratory subgroup analyses revealed heterogeneous patterns of sleep and olfactory correlates across clinical strata. The three-factor predictive model yielded an overall classification accuracy of 84.81%.ConclusionThese findings indicate that non-motor abnormalities, rather than motor impairment, are associated with anxiety in early PD after adjustment for demographic and motor covariates. The distinct correlative patterns across subgroups provide preliminary clinical clues for the heterogeneous neurodegenerative processes underlying PD-related anxiety, and support routine screening of depressive, sleep and olfactory symptoms to facilitate anxiety risk stratification at initial diagnosis.

Prevalence of positive screens for depression, anxiety, and PTSD symptoms among parents of infants admitted to a NICU: a pilot study

IntroductionParents of infants admitted to the Neonatal Intensive Care Unit (NICU) may experience substantial psychological distress. This study aimed to assess the prevalence of positive screens for depressive, anxiety, and post-traumatic stress disorder (PTSD) symptoms and to explore their associations with gender, education level, and parental age. The study also described the coping strategies reported by participants.MethodsThis cross-sectional pilot study assessed 82 parents of infants admitted to the NICU at Thumbay University Hospital, Ajman. Parents who were primary caregivers and provided consent were included. Data were collected from March to July 2025 using self-administered questionnaires; Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and PTSD Checklist for DSM-5 (PCL-5). They were then grouped based on whether they met the positive or negative screen criteria for the respective psychiatric symptoms.ResultsOut of the 82 parents who had participated, 22% screened positive for anxiety symptoms, 13.4% for depression symptoms, and 9.8% for PTSD symptoms. Female participants had a higher proportion of positive screen for depressive symptoms than male participants (20.5% vs. 4.8% in men, p = 0.043), and younger participants (≤30 years) had a higher proportion of positive screens for PTSD symptoms than those aged >30 years (17.5% vs. 2.4%; Fisher’s exact p = 0.027), although the small number of positive cases warrants cautious interpretation. No significant associations were found with education level. The most reported coping strategies were religious/spiritual (34.8%) and physical/behavioral (26.1%) methods.ConclusionA notable proportion of parents of infants admitted to the NICU in this UAE pilot cross-sectional study screened positive for symptoms of depression, anxiety, and PTSD, with female participants and younger participants showing higher proportions of positive screening for depressive and PTSD symptoms, respectively. These findings support consideration of mental health screening, promotion of a socially supportive environment, and culturally appropriate psychosocial support for parents of NICU-admitted infants.

Case Report: Rapid resolution of psychogenic cough in an adolescent following bromazepam treatment

BackgroundSomatic cough syndrome, formerly termed psychogenic cough or habit cough, is an under-recognized cause of chronic cough in pediatric populations, characterized by repetitive, dry, and honking cough that is absent during sleep. Behavioral interventions are first-line treatment with high success rates of 80%–90%. However, when access to behavioral therapy is unavailable, alternative pharmacological interventions, particularly benzodiazepines, have received minimal investigation in this population.Case presentationI report a 13-year-old previously healthy male patient with abrupt-onset, near-continuous dry cough occurring every 2 seconds during waking hours. The cough had a distinctive honking quality and disappeared completely during sleep. The patient presented with severe impairment in function, including inability to eat for 3 days, multiple emergency presentations requiring intravenous hydration, and complete school absence. Medical evaluation, including physical examination, laboratory investigations, spirometry, and chest X-ray, was unremarkable. Empirical trials of inhaled bronchodilators and nasal corticosteroids yielded no improvement. Psychiatric assessment excluded psychotic features, depression, obsessive-compulsive disorder, and tic disorder but noted family stressors, including high expressed emotion and overprotective parenting behavior. Based on the sign of sleep-related cough cessation and exclusion of organic pathology, somatic cough syndrome was diagnosed. Given the severity of impairment and family circumstances precluding immediate behavioral therapy, bromazepam 3 mg orally was initiated. Within 24–36 hours, the cough resolved completely. At 3-month follow-up, the patient remained symptom-free without medication. He had returned to school and demonstrated normal eating patterns.ConclusionThis case demonstrates rapid and sustained resolution at 3-month follow-up of severe psychogenic cough following short-term bromazepam treatment in an adolescent. While behavioral therapy is still an evidence-based first-line treatment, this report suggests using benzodiazepines as a pharmacological intervention alternative when behavioral therapy is unavailable. The rapid response and sustained remission at 3-month follow-up are consistent with the hypothesis that benzodiazepines may interrupt the self-perpetuating cycle of anxiety and cough in somatic cough syndrome. Further research is needed for this case in pediatric populations to establish efficacy, safety, and optimal treatment duration.

Implementing BEAM: A Scalable Digital Mental Health Program, for Families of Children Referred to Neurodevelopmental Services

Conditions: Depression and Anxiety Symptom; Anger; Parenting; Stress (Psychology); Parent Child Relationship; Child Development; Neurodevelopmental Conditions

Interventions: Behavioral: The Building Emotional Awareness and Mental Health (BEAM) Program

Sponsors: University of Manitoba; Children’s Hospital Research Institute of Manitoba; Kids Brain Health Network

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