Rare copy number variation in posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) is a heritable (h2 = 24-71%) psychiatric illness. Copy number variation (CNV) is a form of rare genetic variation that has been implicated in the etiology of psychiatric disorders, but no large-scale investigation of CNV in PTSD has been performed. We present an association study of CNV burden and PTSD symptoms in a sample of 114,383 participants (13,036 cases and 101,347 controls) of European ancestry. CNVs were called using two calling algorithms and intersected to a consensus set. Quality control was performed to remove strong outlier samples. CNVs were examined for association with PTSD within each cohort using linear or logistic regression analysis adjusted for population structure and CNV quality metrics, then inverse variance weighted meta-analyzed across cohorts. We examined the genome-wide total span of CNVs, enrichment of CNVs within specified gene-sets, and CNVs overlapping individual genes and implicated neurodevelopmental regions. The total distance covered by deletions crossing over known neurodevelopmental CNV regions was significant (beta = 0.029, SE = 0.005, P = 6.3 × 10-8). The genome-wide neurodevelopmental CNV burden identified explains 0.034% of the variation in PTSD symptoms. The 15q11.2 BP1-BP2 microdeletion region was significantly associated with PTSD (beta = 0.0206, SE = 0.0056, P = 0.0002). No individual significant genes interrupted by CNV were identified. 22 gene pathways related to the function of the nervous system and brain were significant in pathway analysis (FDR q < 0.05), but these associations were not significant once NDD regions were removed. A larger sample size, better detection methods, and annotated resources of CNV are needed to explore this relationship further

Combining mindfulness and cognitive training in children with attention deficit hyperactivity disorder : study protocol of a pilot randomized controlled trial (the NeuroMind study)

Altres ajuts: The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The authors are grateful to the CIBER of Epidemiology and Public Health (CIBERESP CB22/02/00052; ISCIII), CIBER of Mental Health (CIBERSAM), and CIBER of Obesity and Nutrition (CIBEROBN) for their support. AF-S is a Serra Húnter Fellow (Generalitat de Catalunya; reference number UAB-LE8015).Introduction: Attention Deficit Hyperactivity Disorder (ADHD) has a global mean prevalence of 5%. Cognitive Training (CT) and Mindfulness-Based Interventions (MBIs) have shown promising results in managing ADHD symptoms, but they are not its Treatment-As-Usual (TAU). The NeuroMind Study aims to evaluate the preliminary effectiveness and feasibility of three interventions: Mindfulness for Health (M4H), CT using the NeuronUP® platform (CT), and a combination of both, Mindfulness Cognitive Training (MCT). There is empirical evidence supporting the effectiveness of the M4H and NeuronUP® platform; however, this study explores for the first time the effectiveness of MCT and CT, as well as the integration of M4H into TAU. The objectives of this 5-month Randomized Controlled Trial (RCT) are: (1) To analyze the preliminary effectiveness and feasibility of M4H, CT or a combination of both (MCT) added to TAU for children with ADHD; (2) To evaluate the role of psychological process variables (mindfulness and emotional regulation) as mediators of 5-month follow-up clinical outcomes; (3) To preliminarily explore whether specific sociodemographic and clinical characteristics can predict the short-and medium-term clinical response to the specific treatments. Methods and analysis: Participants will be 120 children (7 to 12 years) with ADHD recruited at Child and Adolescent Mental Health Service (CAMHS) Sant Joan de Déu Terres de Lleida (Spain) randomly allocated to one of the four study arms: TAU vs. TAU + CT vs. TAU + M4H vs. TAU + MCT. An assessment to collect ADHD symptoms, Executive Functions (EF), comorbid symptoms and global functioning will be conducted pre-intervention, post-intervention (2 months after baseline) and at the 5-month follow-up. Linear mixed models and mediational models will be computed. Discussion: If the preliminary effectiveness and feasibility of the MCT are demonstrated, this study could be a preliminary basis to do a full RCT with a larger sample to definitively validate the intervention. The MCT could be applied in clinical practice if it is definitively validated. Clinical trial registration:ClinicalTrials.gov, identifier, NCT05937347. https://clinicaltrials.gov/study/NCT05937347?locStr=Spain&country=Spain&cond=ADHD&intr=Mindfulness&rank=1

Apoptosis-Like Cell Death Induction and Aberrant Fibroblast Properties in Human Incisional Hernia Fascia

Incisional hernia often occurs following laparotomy and can be a source of serious problems. Although there is evidence that a biological cause may underlie its development, the mechanistic link between the local tissue microenvironment and tissue rupture is lacking. In this study, we used matched tissue-based and in vitro primary cell culture systems to examine the possible involvement of fascia fibroblasts in incisional hernia pathogenesis. Fascia biopsies were collected at surgery from incisional hernia patients and non-incisional hernia controls. Tissue samples were analyzed by histology and immunoblotting methods. Fascia primary fibroblast cultures were assessed at morphological, ultrastructural, and functional levels. We document tissue and fibroblast loss coupled to caspase-3 activation and induction of apoptosis-like cell-death mechanisms in incisional hernia fascia. Alterations in cytoskeleton organization and solubility were also observed. Incisional hernia fibroblasts showed a consistent phenotype throughout early passages in vitro, which was characterized by significantly enhanced cell proliferation and migration, reduced adhesion, and altered cytoskeleton properties, as compared to non-incisional hernia fibroblasts. Moreover, incisional hernia fibroblasts displayed morphological and ultrastructural alterations compatible with autophagic processes or lysosomal dysfunction, together with enhanced sensitivity to proapoptotic challenges. Overall, these data suggest an ongoing complex interplay of cell death induction, aberrant fibroblast function, and tissue loss in incisional hernia fascia, which may significantly contribute to altered matrix maintenance and tissue rupture in vivo

Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects

Artificial intelligence (AI) is transforming the field of medical imaging and has the potential to bring medicine from the era of 'sick-care' to the era of healthcare and prevention. The development of AI requires access to large, complete, and harmonized real-world datasets, representative of the population, and disease diversity. However, to date, efforts are fragmented, based on single-institution, size-limited, and annotation-limited datasets. Available public datasets (e.g., The Cancer Imaging Archive, TCIA, USA) are limited in scope, making model generalizability really difficult. In this direction, five European Union projects are currently working on the development of big data infrastructures that will enable European, ethically and General Data Protection Regulation-compliant, quality-controlled, cancer-related, medical imaging platforms, in which both large-scale data and AI algorithms will coexist. The vision is to create sustainable AI cloud-based platforms for the development, implementation, verification, and validation of trustable, usable, and reliable AI models for addressing specific unmet needs regarding cancer care provision. In this paper, we present an overview of the development efforts highlighting challenges and approaches selected providing valuable feedback to future attempts in the area

Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects

Abstract Artificial intelligence (AI) is transforming the field of medical imaging and has the potential to bring medicine from the era of ‘sick-care’ to the era of healthcare and prevention. The development of AI requires access to large, complete, and harmonized real-world datasets, representative of the population, and disease diversity. However, to date, efforts are fragmented, based on single–institution, size-limited, and annotation-limited datasets. Available public datasets (e.g., The Cancer Imaging Archive, TCIA, USA) are limited in scope, making model generalizability really difficult. In this direction, five European Union projects are currently working on the development of big data infrastructures that will enable European, ethically and General Data Protection Regulation-compliant, quality-controlled, cancer-related, medical imaging platforms, in which both large-scale data and AI algorithms will coexist. The vision is to create sustainable AI cloud-based platforms for the development, implementation, verification, and validation of trustable, usable, and reliable AI models for addressing specific unmet needs regarding cancer care provision. In this paper, we present an overview of the development efforts highlighting challenges and approaches selected providing valuable feedback to future attempts in the area. Key points • Artificial intelligence models for health imaging require access to large amounts of harmonized imaging data and metadata. • Main infrastructures adopted either collect centrally anonymized data or enable access to pseudonymized distributed data. • Developing a common data model for storing all relevant information is a challenge. • Trust of data providers in data sharing initiatives is essential. • An online European Union meta-tool-repository is a necessity minimizing effort duplication for the various projects in the area

Rare copy number variation in posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) is a heritable (h2 = 24-71%) psychiatric illness. Copy number variation (CNV) is a form of rare genetic variation that has been implicated in the etiology of psychiatric disorders, but no large-scale investigation of CNV in PTSD has been performed. We present an association study of CNV burden and PTSD symptoms in a sample of 114,383 participants (13,036 cases and 101,347 controls) of European ancestry. CNVs were called using two calling algorithms and intersected to a consensus set. Quality control was performed to remove strong outlier samples. CNVs were examined for association with PTSD within each cohort using linear or logistic regression analysis adjusted for population structure and CNV quality metrics, then inverse variance weighted meta-analyzed across cohorts. We examined the genome-wide total span of CNVs, enrichment of CNVs within specified gene-sets, and CNVs overlapping individual genes and implicated neurodevelopmental regions. The total distance covered by deletions crossing over known neurodevelopmental CNV regions was significant (beta = 0.029, SE = 0.005, P = 6.3 × 10-8). The genome-wide neurodevelopmental CNV burden identified explains 0.034% of the variation in PTSD symptoms. The 15q11.2 BP1-BP2 microdeletion region was significantly associated with PTSD (beta = 0.0206, SE = 0.0056, P = 0.0002). No individual significant genes interrupted by CNV were identified. 22 gene pathways related to the function of the nervous system and brain were significant in pathway analysis (FDR q < 0.05), but these associations were not significant once NDD regions were removed. A larger sample size, better detection methods, and annotated resources of CNV are needed to explore this relationship further