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Biallelic pathogenic variants in CCN6 cause progressive pseudorheumatoid dysplasia (PPD), a rare skeletal dysplasia. The predominant features include noninflammatory progressive joint stiffness and enlargement, which are not unique to this condition. Nearly 100% of the reported variants are single nucleotide variants or small indels, and missing of a second variant has been reported. Genome sequencing (GS) covers various types of variants and deep phenotyping (DP) provides detailed and precise information facilitating genetic data interpretation. The combination of GS and DP improves diagnostic yield, especially in rare and undiagnosed diseases. We identified a novel compound heterozygote involving a disease‐causing copy number variant (g.112057664_112064205del) in trans with a single nucleotide variant (c.624dup(p.Cys209MetfsTer21)) in CCN6 in a pair of monozygotic twins, through the methods of GS and DP. The twins had received three nondiagnostic results before. The g.112057664_112064205del variant was missed by all the tests, and the recorded phenotypes were inaccurate or even misleading. The twins were diagnosed with PPD, ending a 13‐year diagnostic odyssey. There may be other patients with PPD experiencing underdiagnosis and misdiagnosis due to inadequate genetic testing or phenotyping methods. This case highlights the critical role of GS and DP in facilitating an accurate and timely diagnosis. [ABSTRACT FROM AUTHOR]

ABSTRACT De novo heterozygous variants in RNU4‐2, a component of the major spliceosome, were recently found to cause a novel neurodevelopmental disorder. Preliminary evidence suggests that this newly discovered syndrome is one of the most common monogenic causes of neurodevelopmental disorders. It is characterised by developmental delay and intellectual disability, microcephaly, short stature and hypotonia. However, much remains to be elucidated regarding the phenotype of the affected individuals. We report on four novel individuals affected by the condition, two of which were identified following targeted sequencing based solely on the facial features that were similar to those of the first patient we identified. This strongly suggests that this syndrome entails a recognisable morphological phenotype, which is particularly relevant for resource‐limited regions where whole genome sequencing is not readily available, and in view of retro‐active selection/prioritisation of individuals with hitherto negative genetic testing. [ABSTRACT FROM AUTHOR]

Phenotypes play a fundamental role in medical genetics, serving as external manifestations of underlying genotypes. Deep phenotyping, a cornerstone of precision medicine, involves precise multi-system phenotype assessments, facilitating disease subtyping and genetic understanding. Despite their significance, the field lacks standardized protocols for accurate phenotype evaluation, hindering clinical comprehension and research comparability. We present a comprehensive workflow of deep phenotyping for rare bone diseases from the Genetics Clinic of Skeletal Deformity at Peking Union Medical College Hospital. Our workflow integrates referral, informed consent, and detailed phenotype evaluation through HPO standards, capturing nuanced phenotypic characteristics using clinical examinations, questionnaires, and multimedia documentation. Genetic testing and counseling follow, based on deep phenotyping results, ensuring personalized interventions. Multidisciplinary team consultations facilitate comprehensive patient care and clinical guideline development. Regular follow-up visits emphasize dynamic phenotype reassessment, ensuring treatment strategies remain responsive to evolving patient needs. In conclusion, this study highlights the importance of deep phenotyping in rare bone diseases, offering a standardized framework for phenotype evaluation, genetic analysis, and multidisciplinary intervention. By enhancing clinical care and research outcomes, this approach contributes to the advancement of precision medicine in the field of medical genetics. [ABSTRACT FROM AUTHOR]

Key message: AOX gene family in motion marks in-born efficiency of respiration adjustment; can serve for primer screening, genotype ranking, in vitro-plant discrimination and a SMART perspective for multiple-resilient plant holobiont selection. The bacteria Xylella fastidiosa (Xf) is a climate-dependent, global threat to many crops of high socio-economic value, including grapevine. Currently designed breeding strategies for Xf-tolerant or -resistant genotypes insufficiently address the danger of biodiversity loss by focusing on selected threats, neglecting future environmental conditions. Thus, breeding strategies should be validated across diverse populations and acknowledge temperature changes and drought by minimizing the metabolic-physiologic effects of multiple stress-induced oxygen shortages. This research hypothesizes that multiple-resilient plant holobionts achieve lifelong adaptive robustness through early molecular and metabolic responses in primary stress target cells, which facilitate efficient respiration adjustment and cell cycle down-regulation. To validate this concept open-access transcriptome data were analyzed of xylem tissues of Xf-tolerant and –resistant Vitis holobionts from diverse trials and genetic origins from early hours to longer periods after Xf-inoculation. The results indicated repetitive involvement of alternative oxidase (AOX) transcription in episodes of down-regulated transcripts of cytochrome c oxidase (COX) at various critical time points before disease symptoms emerged. The relation between transcript levels of COX and AOX (‘relCOX/AOX’) was found promising for plant discrimination and primer screening. Furthermore, transcript levels of xylem-harbored bacterial consortia indicated common regulation with Xf and revealed stress-induced early down-regulation and later enhancement. LPS priming promoted the earlier increase in bacterial transcripts after Xf-inoculation. This proof-of-principle study highlights a SMART perspective for AOX-assisted plant selection towards multiple-resilience that includes Xf-tolerance. It aims to support timely future plant diagnostics and in-field substitution, sustainable agro-management, which protects population diversity and strengthens both conventional breeding and high-tech, molecular breeding research. Furthermore, the results suggested early up-regulation of bacterial microbiota consortia in vascular-enriched tissues as a novel additional trait for future studies on Xf-tolerance. [ABSTRACT FROM AUTHOR]

Children with autism spectrum disorder (ASD) often face challenges in early social communication skills, prompting the need for a detailed exploration of specific behaviors and their impact on cognitive and adaptive functioning. This study aims to address this gap by examining the developmental trajectories of early social communication skills in preschoolers with ASD aged 18–60 months, comparing them to age‐matched typically developing (TD) children. Utilizing the early social communication scales (ESCS), the research employs a longitudinal design to capture changes over time. We apply a principal component analysis (PCA) to ESCS variables to identify underlying components, and cluster analysis to identify subgroups based on preverbal communication profiles. The results reveal consistent differences in early social communication skills between ASD and TD children, with ASD children exhibiting reduced skills. PCA identifies two components, distinguishing objects‐directed behaviors and social interaction‐directed behaviors. Cluster analysis identifies three subgroups of autistic children, each displaying specific communication profiles associated with distinct cognitive and adaptive functioning trajectories. In conclusion, this study provides a nuanced understanding of early social communication development in ASD, emphasizing the importance of low‐level behaviors. The identification of subgroups and their unique trajectories contributes to a more comprehensive understanding of ASD heterogeneity. These findings underscore the significance of early diagnosis, focusing on specific behaviors predicting cognitive and adaptive functioning outcomes. The study encourages further research to explore the sequential development of these skills, offering valuable insights for interventions and support strategies. Lay Summary: This study highlights the significance of preverbal communication skills in autistic preschoolers, emphasizing their crucial role in language acquisition and social development. By analyzing a longitudinal dataset of 171 children, including 103 with ASD, the study identifies deficits in preverbal communication among children with ASD, with these deficits tending to diminish around the age of five. The research also reveals distinctive early socio‐communicative profiles within the ASD group, providing valuable insights into the diverse developmental trajectories of these children. [ABSTRACT FROM AUTHOR]

Background: Achondroplasia and mandibulofacial dysostosis with microcephaly (MFDM) are rare monogenic, dominant disorders, caused by gain-of-function fibroblast growth factor receptor 3 (FGFR3) gene variants and loss-of-function elongation factor Tu GTP binding domain-containing 2 (EFTUD2) gene variants, respectively. The coexistence of two distinct Mendelian disorders in a single individual is uncommon and challenges the traditional paradigm of a single genetic disorder explaining a patient's symptoms, opening new avenues for diagnosis and management. Case Presentation: We present a case of a female patient initially diagnosed with achondroplasia due to a maternally inherited pathogenic FGFR3 variant. She was referred to our genetic department due to her unusually small head circumference and short stature, which were both significantly below the expected range for achondroplasia. Additional features included distinctive facial characteristics, significant speech delay, conductive hearing loss, and epilepsy. Given the complexity of her phenotype, she was recruited to the DDD (Deciphering Developmental Disorders) study and the 100,000 Genomes project for further investigation. Subsequent identification of a complex EFTUD2 intragenic rearrangement confirmed an additional diagnosis of mandibulofacial dysostosis with microcephaly (MFDM). Conclusion: This report presents the first case of a dual molecular diagnosis of achondroplasia and mandibulofacial dysostosis with microcephaly in the same patient. This case underscores the complexity of genetic diagnoses and the potential for coexistence of multiple genetic syndromes in a single patient. This case expands our understanding of the molecular basis of dual Mendelian disorders and highlights the importance of considering the possibility of dual molecular diagnoses in patients with phenotypic features that are not fully accounted for by their primary diagnosis. [ABSTRACT FROM AUTHOR]

Abstract Phenotypes play a fundamental role in medical genetics, serving as external manifestations of underlying genotypes. Deep phenotyping, a cornerstone of precision medicine, involves precise multi-system phenotype assessments, facilitating disease subtyping and genetic understanding. Despite their significance, the field lacks standardized protocols for accurate phenotype evaluation, hindering clinical comprehension and research comparability. We present a comprehensive workflow of deep phenotyping for rare bone diseases from the Genetics Clinic of Skeletal Deformity at Peking Union Medical College Hospital. Our workflow integrates referral, informed consent, and detailed phenotype evaluation through HPO standards, capturing nuanced phenotypic characteristics using clinical examinations, questionnaires, and multimedia documentation. Genetic testing and counseling follow, based on deep phenotyping results, ensuring personalized interventions. Multidisciplinary team consultations facilitate comprehensive patient care and clinical guideline development. Regular follow-up visits emphasize dynamic phenotype reassessment, ensuring treatment strategies remain responsive to evolving patient needs. In conclusion, this study highlights the importance of deep phenotyping in rare bone diseases, offering a standardized framework for phenotype evaluation, genetic analysis, and multidisciplinary intervention. By enhancing clinical care and research outcomes, this approach contributes to the advancement of precision medicine in the field of medical genetics.

Abstract Background Achondroplasia and mandibulofacial dysostosis with microcephaly (MFDM) are rare monogenic, dominant disorders, caused by gain-of-function fibroblast growth factor receptor 3 (FGFR3) gene variants and loss-of-function elongation factor Tu GTP binding domain-containing 2 (EFTUD2) gene variants, respectively. The coexistence of two distinct Mendelian disorders in a single individual is uncommon and challenges the traditional paradigm of a single genetic disorder explaining a patient’s symptoms, opening new avenues for diagnosis and management. Case Presentation We present a case of a female patient initially diagnosed with achondroplasia due to a maternally inherited pathogenic FGFR3 variant. She was referred to our genetic department due to her unusually small head circumference and short stature, which were both significantly below the expected range for achondroplasia. Additional features included distinctive facial characteristics, significant speech delay, conductive hearing loss, and epilepsy. Given the complexity of her phenotype, she was recruited to the DDD (Deciphering Developmental Disorders) study and the 100,000 Genomes project for further investigation. Subsequent identification of a complex EFTUD2 intragenic rearrangement confirmed an additional diagnosis of mandibulofacial dysostosis with microcephaly (MFDM). Conclusion This report presents the first case of a dual molecular diagnosis of achondroplasia and mandibulofacial dysostosis with microcephaly in the same patient. This case underscores the complexity of genetic diagnoses and the potential for coexistence of multiple genetic syndromes in a single patient. This case expands our understanding of the molecular basis of dual Mendelian disorders and highlights the importance of considering the possibility of dual molecular diagnoses in patients with phenotypic features that are not fully accounted for by their primary diagnosis.

The Ehlers-Danlos syndromes (EDS) are a group of rare hereditary connective tissue disorders characterized by joint hypermobility, skin hyperextensibility, and tissue fragility. The clinical and genetic hetero- geneity of EDS frequently leads to underdiagnosis and misdiagnosis. Genetic testing is an essential approach to clarify the underlying diagnosis. Recent research has preliminarily established genotype-phenotype correlations and introduced the novel concept of " disease spectrum" in some subtypes. These studies deepen our understanding of EDS etiology and provide important insights into clinical management. Published in 2023, the Chinese Guidelines for Diagnosis and Treatment of the Ehlers-Danlos Syndromes(the Guidelines) recommend performing genetic testing with deep phenotyping for patients who meet the clinical diagnostic criteria or are suspected of having EDS. However, it should be noted that the clinical diagnosis might differ from the molecular diagnosis. Furthermore, cutting-edge approaches such as periodic data reanalysis, integration of RNA sequencing into family-based whole-genome sequencing, and third-generation sequencing may facilitate the reclassification of variants of uncertain significance or resolve undiagnosed cases. This article summarizes recent progress in the genetics research of EDS, with the hope of offering a valuable resource for clinical diagnosis, treatment and scientific research to optimize the quality of life of patients with EDS.

Background Bipolar disorder (BD) shows heterogeneous illness presentation both cross-sectionally and longitudinally. This phenotypic heterogeneity might reflect underlying genetic heterogeneity. At the same time, overlapping characteristics between BD and other psychiatric illnesses are observed at clinical and biomarker levels, which implies a shared biological mechanism between them. Incorporating these two issues in a single study design, this study investigated whether phenotypically heterogeneous subtypes of BD have a distinct polygenic basis shared with other psychiatric illnesses. Methods Six lifetime phenotype dimensions of BD identified in our previous study were used as target phenotypes. Associations between these phenotype dimensions and polygenic risk scores (PRSs) of major psychiatric illnesses from East Asian (EA) and other available populations were analyzed. Results Each phenotype dimension showed a different association pattern with PRSs of mental illnesses. PRS for EA schizophrenia showed a significant negative association with the cyclicity dimension (p = 0.044) but a significant positive association with the psychotic/irritable mania dimension (p = 0.001). PRS of EA major depressive disorder demonstrated a significant negative association with the elation dimension (p = 0.003) but a significant positive association with the comorbidity dimension (p = 0.028). Conclusion This study demonstrates that well-defined phenotype dimensions of lifetime-basis in BD have distinct genetic risks shared with other major mental illnesses. This finding supports genetic heterogeneity in BD and suggests a pleiotropy among BD subtypes and other psychiatric disorders beyond BD. Further genomic analyses adopting deep phenotyping across mental illnesses in ancestrally diverse populations are warranted to clarify intra-diagnosis heterogeneity and inter-diagnoses commonality issues in psychiatry. [ABSTRACT FROM AUTHOR]

Objectives: Oculodentodigital dysplasia (ODDD) is a rare autosomal dominant congenital malformation syndrome characterized by high penetrance and great phenotypic heterogeneity. Neurological manifestations are thought to occur in about one third of cases, but systematic studies are not available. We performed deep neurological phenotyping of 10 patients in one ODDD pedigree. Methods: Retrospective case series. We analyzed in depth the neurological phenotype of a three-generation family segregating the heterozygous c.416 T > C, p.(Ile139Thr) in GJA1. Clinical and neuroradiological features were retrospectively evaluated. Brain MRI and visual evoked potentials were performed in 8 and 6 cases, respectively. Results: Central nervous system manifestations occurred in 5 patients, the most common being isolated ataxia either in isolation or combined with spasticity. Furthermore, sphincteric disturbances (neurogenic bladder and fecal incontinence) were recognized as the first manifestation in most of the patients. Subclinical electrophysiological alteration of the optic pathway occurred in all the examined patients. Neuroimaging was significant for supratentorial hypomyelination pattern and hyperintense superior cerebellar peduncle in all examined patients. Conclusion: The neurological involvement in ODDD carriers is often missed but peculiar clinical and radiological patterns can be recognized. Deep neurological phenotyping is needed to help untangle ODDD syndrome complexity and find genotype–phenotype correlations. [ABSTRACT FROM AUTHOR]

The Global Alliance for Genomics and Health (GA4GH) is developing a suite of coordinated standards for genomics for healthcare. The Phenopacket is a new GA4GH standard for sharing disease and phenotype information that characterizes an individual person, linking that individual to detailed phenotypic descriptions, genetic information, diagnoses, and treatments. A detailed example is presented that illustrates how to use the schema to represent the clinical course of a patient with retinoblastoma, including demographic information, the clinical diagnosis, phenotypic features and clinical measurements, an examination of the extirpated tumor, therapies, and the results of genomic analysis. The Phenopacket Schema, together with other GA4GH data and technical standards, will enable data exchange and provide a foundation for the computational analysis of disease and phenotype information to improve our ability to diagnose and conduct research on all types of disorders, including cancer and rare diseases.

Disease ontologies facilitate the semantic organization and representation of domain-specific knowledge. In the case of prostate cancer (PCa), large volumes of research results and clinical data have been accumulated and needed to be standardized for sharing and translational researches. A formal representation of PCa-associated knowledge will be essential to the diverse data standardization, data sharing and the future knowledge graph extraction, deep phenotyping and explainable artificial intelligence developing. In this study, we constructed an updated PCa ontology (PCAO2) based on the ontology development life cycle. An online information retrieval system was designed to ensure the usability of the ontology. The PCAO2 with a subclass-based taxonomic hierarchy covers the major biomedical concepts for PCa-associated genotypic, phenotypic and lifestyle data. The current version of the PCAO2 contains 633 concepts organized under three biomedical viewpoints, namely, epidemiology, diagnosis and treatment. These concepts are enriched by the addition of definition, synonym, relationship and reference. For the precision diagnosis and treatment, the PCa-associated genes and lifestyles are integrated in the viewpoint of epidemiological aspects of PCa. PCAO2 provides a standardized and systematized semantic framework for studying large amounts of heterogeneous PCa data and knowledge, which can be further, edited and enriched by the scientific community. The PCAO2 is freely available at https://bioportal.bioontology.org/ontologies/PCAO , http://pcaontology.net/ and http://pcaontology.net/mobile/. [ABSTRACT FROM AUTHOR]

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The condition known as 22q11.2 deletion syndrome (MIM #188400) is a rare disease with a highly variable clinical presentation including more than 180 features; specific guidelines for screening individuals have been used to support clinical suspicion before confirmatory tests by Brazil's Craniofacial Project. Of the 2568 patients listed in the Brazilian Database on Craniofacial Anomalies, 43 individuals negative for the 22q11.2 deletion syndrome were further investigated through whole-exome sequencing. Three patients (6.7%) presented with heterozygous pathogenic variants in the KMT2A gene, including a novel variant (c.6158+1del) and two that had been previously reported (c.173dup and c.3241C>T); reverse phenotyping concluded that all three patients presented features of Wiedemann–Steiner syndrome, such as neurodevelopmental disorders and dysmorphic facial features (n = 3), hyperactivity and anxiety (n = 2), thick eyebrows and lower-limb hypertrichosis (n = 2), congenital heart disease (n = 1), short stature (n = 1), and velopharyngeal insufficiency (n = 2). Overlapping features between 22q11.2 deletion syndrome and Wiedemann–Steiner syndrome comprised neuropsychiatric disorders and dysmorphic characteristics involving the eyes and nose region; velopharyngeal insufficiency was seen in two patients and is an unreported finding in WDSTS. Therefore, we suggest that both conditions should be included in each other's differential diagnoses. [ABSTRACT FROM AUTHOR]

Background: The severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) pandemic causes a high burden of acute and long-term morbidity and mortality worldwide despite global efforts in containment, prophylaxis, and therapy. With unprecedented speed, the global scientific community has generated pivotal insights into the pathogen and the host response evoked by the infection. However, deeper characterization of the pathophysiology and pathology remains a high priority to reduce morbidity and mortality of coronavirus disease 2019 (COVID-19). Methods: NAPKON-HAP is a multi‐centered prospective observational study with a long‐term follow‐up phase of up to 36 months post-SARS-CoV-2 infection. It constitutes a central platform for harmonized data and biospecimen for interdisciplinary characterization of acute SARS-CoV-2 infection and long-term outcomes of diverging disease severities of hospitalized patients. Results: Primary outcome measures include clinical scores and quality of life assessment captured during hospitalization and at outpatient follow-up visits to assess acute and chronic morbidity. Secondary measures include results of biomolecular and immunological investigations and assessment of organ-specific involvement during and post-COVID-19 infection. NAPKON-HAP constitutes a national platform to provide accessibility and usability of the comprehensive data and biospecimen collection to global research. Conclusion: NAPKON-HAP establishes a platform with standardized high-resolution data and biospecimen collection of hospitalized COVID-19 patients of different disease severities in Germany. With this study, we will add significant scientific insights and provide high-quality data to aid researchers to investigate COVID-19 pathophysiology, pathology, and chronic morbidity. [ABSTRACT FROM AUTHOR]

Deep phenotyping is a precise and comprehensive approach used for the precise analysis and comprehensive assessment of multi-system phenotypes of the patients. The approach uses symptoms, signs, various medical examination and laboratory results, and other relevant medical information. In the clinical diagnosis and medical research of rare bone diseases, deep phenotyping plays a pivotal role. The realization of precision medicine primarily comprises three key dimensions: deep phenotyping, stratified medicine, and targeted therapy. The deep phenotyping is the basis for the latter two. Deep phenotyping not only facilitates fine subtyping of diseases, but also allows for the in-depth understanding of genetic data. The use of deep phenotyping requires stand- ardized terminology and specific procedures. Moreover, deep phenotyping shows substantial potential using the application of artificial intelligence technology particularly when combining with multi-omics techniques.

Abstract Background 22q11.2 deletion syndrome (22q11.2DS) is the most common chromosomal interstitial-deletion disorder, occurring in approximately 1 in 2000 to 6000 live births. Affected individuals exhibit variable clinical phenotypes that can include velopharyngeal anomalies, heart defects, T-cell-related immune deficits, dysmorphic facial features, neurodevelopmental disorders, including autism, early cognitive decline, schizophrenia, and other psychiatric disorders. Developing comprehensive treatments for 22q11.2DS requires an understanding of both the psychophysiological and neural mechanisms driving clinical outcomes. Our project probes the core psychophysiological abnormalities of 22q11.2DS in parallel with molecular studies of stem cell-derived neurons to unravel the basic mechanisms and pathophysiology of 22q11.2-related psychiatric disorders, with a primary focus on psychotic disorders. Our study is guided by the central hypothesis that abnormal neural processing associates with psychophysiological processing and underlies clinical diagnosis and symptomatology. Here, we present the scientific background and justification for our study, sharing details of our study design and human data collection protocol. Methods Our study is recruiting individuals with 22q11.2DS and healthy comparison subjects between the ages of 16 and 60 years. We are employing an extensive psychophysiological assessment battery (e.g., EEG, evoked potential measures, and acoustic startle) to assess fundamental sensory detection, attention, and reactivity. To complement these unbiased measures of cognitive processing, we will develop stem-cell derived neurons and examine neuronal phenotypes relevant to neurotransmission. Clinical characterization of our 22q11.2DS and control participants relies on diagnostic and research domain criteria assessments, including standard Axis-I diagnostic and neurocognitive measures, following from the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) and the North American Prodrome Longitudinal Study (NAPLS) batteries. We are also collecting measures of autism spectrum (ASD) and attention deficit/hyperactivity disorder (ADHD)-related symptoms. Discussion Studying 22q11.2DS in adolescence and adulthood via deep phenotyping across multiple clinical and biological domains may significantly increase our knowledge of its core disease processes. Our manuscript describes our ongoing study’s protocol in detail. These paradigms could be adapted by clinical researchers studying 22q11.2DS, other CNV/single gene disorders, or idiopathic psychiatric syndromes, as well as by basic researchers who plan to incorporate biobehavioral outcome measures into their studies of 22q11.2DS.

ABSTRACT: Background: Heart failure (HF) most commonly occurs in patients who have had a myocardial infarction (MI), but factors other than MI size may be deterministic. Fibrosis of myocardium remote from the MI is associated with adverse remodeling. We aimed to 1) investigate the association between remote myocardial fibrosis, measured using cardiovascular magnetic resonance (CMR) extracellular volume fraction (ECV), and HF and death following MI, 2) identify predictors of remote myocardial fibrosis in patients with evidence of MI and determine the relationship with infarct size. Methods: Multicenter prospective cohort study of 1199 consecutive patients undergoing CMR with evidence of MI on late gadolinium enhancement. Median follow-up was 1133 (895–1442) days. Cox proportional hazards modeling was used to identify factors predictive of the primary outcome, a composite of first hospitalization for HF (HHF) or all-cause mortality, post-CMR. Linear regression modeling was used to identify determinants of remote ECV. Results: Remote myocardial fibrosis was a strong predictor of primary outcome (χ2: 15.6, hazard ratio [HR]: 1.07 per 1% increase in ECV, 95% confidence interval [CI]: 1.04–1.11, p

Background: The majority of genetic epilepsies remain unsolved in terms of specific genotype. Phenotype‐based genomic analyses have shown potential to strengthen genomic analysis in various ways, including improving analytical efficacy. Methods: We have tested a standardised phenotyping method termed 'Phenomodels' for integrating deep‐phenotyping information with our in‐house developed clinical whole exome/genome sequencing analytical pipeline. Phenomodels includes a user‐friendly epilepsy phenotyping template and an objective measure for selecting which template terms to include in individualised Human Phenotype Ontology (HPO) gene panels. In a pilot study of 38 previously solved cases of developmental and epileptic encephalopathies, we compared the sensitivity and specificity of the individualised HPO gene panels with the clinical epilepsy gene panel. Results: The Phenomodels template showed high sensitivity for capturing relevant phenotypic information, where 37/38 individuals' HPO gene panels included the causative gene. The HPO gene panels also had far fewer variants to assess than the epilepsy gene panel. Conclusion: We have demonstrated a viable approach for incorporating standardised phenotype information into clinical genomic analyses, which may enable more efficient analysis. [ABSTRACT FROM AUTHOR]

Background: 22q11.2 deletion syndrome (22q11.2DS) is the most common chromosomal interstitial-deletion disorder, occurring in approximately 1 in 2000 to 6000 live births. Affected individuals exhibit variable clinical phenotypes that can include velopharyngeal anomalies, heart defects, T-cell-related immune deficits, dysmorphic facial features, neurodevelopmental disorders, including autism, early cognitive decline, schizophrenia, and other psychiatric disorders. Developing comprehensive treatments for 22q11.2DS requires an understanding of both the psychophysiological and neural mechanisms driving clinical outcomes. Our project probes the core psychophysiological abnormalities of 22q11.2DS in parallel with molecular studies of stem cell-derived neurons to unravel the basic mechanisms and pathophysiology of 22q11.2-related psychiatric disorders, with a primary focus on psychotic disorders. Our study is guided by the central hypothesis that abnormal neural processing associates with psychophysiological processing and underlies clinical diagnosis and symptomatology. Here, we present the scientific background and justification for our study, sharing details of our study design and human data collection protocol. Methods: Our study is recruiting individuals with 22q11.2DS and healthy comparison subjects between the ages of 16 and 60 years. We are employing an extensive psychophysiological assessment battery (e.g., EEG, evoked potential measures, and acoustic startle) to assess fundamental sensory detection, attention, and reactivity. To complement these unbiased measures of cognitive processing, we will develop stem-cell derived neurons and examine neuronal phenotypes relevant to neurotransmission. Clinical characterization of our 22q11.2DS and control participants relies on diagnostic and research domain criteria assessments, including standard Axis-I diagnostic and neurocognitive measures, following from the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) and the North American Prodrome Longitudinal Study (NAPLS) batteries. We are also collecting measures of autism spectrum (ASD) and attention deficit/hyperactivity disorder (ADHD)-related symptoms. Discussion: Studying 22q11.2DS in adolescence and adulthood via deep phenotyping across multiple clinical and biological domains may significantly increase our knowledge of its core disease processes. Our manuscript describes our ongoing study's protocol in detail. These paradigms could be adapted by clinical researchers studying 22q11.2DS, other CNV/single gene disorders, or idiopathic psychiatric syndromes, as well as by basic researchers who plan to incorporate biobehavioral outcome measures into their studies of 22q11.2DS. [ABSTRACT FROM AUTHOR]

Heterogeneity is the main challenge in the traditional classification of mental disorders, including schizophrenia spectrum disorders (SSD). This can be partly attributed to the absence of objective diagnostic criteria and the multidimensional nature of symptoms and their associated factors. This article provides an overview of findings from the Genetic Risk and Outcome of Psychosis (GROUP) cohort study on the deep clinical phenotyping of schizophrenia spectrum disorders targeting positive and negative symptoms, cognitive impairments and psychosocial functioning. Three to four latent subtypes of positive and negative symptoms were identified in patients, siblings and controls, whereas four to six latent cognitive subtypes were identified. Five latent subtypes of psychosocial function—multidimensional social inclusion and premorbid adjustment—were also identified in patients. We discovered that the identified subtypes had mixed profiles and exhibited stable, deteriorating, relapsing and ameliorating longitudinal courses over time. Baseline positive and negative symptoms, premorbid adjustment, psychotic-like experiences, health-related quality of life and PRSSCZ were found to be the strong predictors of the identified subtypes. Our findings are comprehensive, novel and of clinical interest for precisely identifying high-risk population groups, patients with good or poor disease prognosis and the selection of optimal intervention, ultimately fostering precision psychiatry by tackling diagnostic and treatment selection challenges pertaining to heterogeneity. [ABSTRACT FROM AUTHOR]

This review presents data indicating that the formation of the psychopathological symptoms of schizophrenia is due to complex and diverse genetic factors associated with various functional and metabolic pathways at different stages of ontogenesis. Although the genetic basis of the main pathophysiological manifestations of schizophrenia – positive and negative symptoms – currently remains largely unknown, the ongoing level of research allows some associations, both common and unique to positive and negative disorders, to be identified. Literature analysis demonstrates the specificity of the association of genetic variants with negative symptoms of schizophrenia, and it is also suggested that immune system genes may be specifically associated with the negative symptoms of schizophrenia. The relevance of studying the relationship between immune system genes, in particular those for pro- and anti-inflammatory cytokines, with the dimensional characteristics of negative symptoms (the abulia-apathy and expressive deficiency factors) has good grounds. Studies of this type have not yet been conducted despite evidence indicating that heterogeneity in negative symptoms is based on different neurobiological mechanisms. It is concluded that the immunological and molecular genetic study of the subdomains of psychopathological symptoms may be promising as part of the transition to deep phenotyping, which seems to be particularly relevant for investigations of a disease with such extreme clinical heterogeneity as schizophrenia. Progress in this direction is important for solving the challenges of precision medicine, which aims to provide the most effective therapy for individual patients by stratifying the disease into subclasses, taking account of their biological bases. [ABSTRACT FROM AUTHOR]

PURPOSE: Deep phenotyping is an emerging trend in precision medicine for genetic disease. The shape of the face is affected in 30-40% of known genetic syndromes. Here, we determine whether syndromes can be diagnosed from 3D images of human faces. METHODS: We analyzed variation in three-dimensional (3D) facial images of 7057 subjects: 3327 with 396 different syndromes, 727 of their relatives, and 3003 unrelated, unaffected subjects. We developed and tested machine learning and parametric approaches to automated syndrome diagnosis using 3D facial images. RESULTS: Unrelated, unaffected subjects were correctly classified with 96% accuracy. Considering both syndromic and unrelated, unaffected subjects together, balanced accuracy was 73% and mean sensitivity 49%. Excluding unrelated, unaffected subjects substantially improved both balanced accuracy (78.1%) and sensitivity (56.9%) of syndrome diagnosis. The best predictors of classification accuracy were phenotypic severity and facial distinctiveness of syndromes. Surprisingly, unaffected relatives of syndromic subjects were frequently classified as syndromic, often to the syndrome of their affected relative. CONCLUSION: Deep phenotyping by quantitative 3D facial imaging has considerable potential to facilitate syndrome diagnosis. Furthermore, 3D facial imaging of unaffected relatives may identify unrecognized cases or may reveal novel examples of semidominant inheritance.

Abstract Background Recurrent gene dosage disorders impart substantial risk for psychopathology. Yet, understanding that risk is hampered by complex presentations that challenge classical diagnostic systems. Here, we present a suite of generalizable analytic approaches for parsing this clinical complexity, which we illustrate through application to XYY syndrome. Method We gathered high-dimensional measures of psychopathology in 64 XYY individuals and 60 XY controls, plus additional interviewer-based diagnostic data in the XYY group. We provide the first comprehensive diagnostic description of psychiatric morbidity in XYY syndrome and show how diagnostic morbidity relates to functioning, subthreshold symptoms, and ascertainment bias. We then map behavioral vulnerabilities and resilience across 67 behavioral dimensions before borrowing techniques from network science to resolve the mesoscale architecture of these dimensions and links to observable functional outcomes. Results Carriage of an extra Y-chromosome increases risk for diverse psychiatric diagnoses, with clinically impactful subthreshold symptomatology. Highest rates are seen for neurodevelopmental and affective disorders. A lower bound of

Abstract Background The majority of genetic epilepsies remain unsolved in terms of specific genotype. Phenotype‐based genomic analyses have shown potential to strengthen genomic analysis in various ways, including improving analytical efficacy. Methods We have tested a standardised phenotyping method termed ‘Phenomodels’ for integrating deep‐phenotyping information with our in‐house developed clinical whole exome/genome sequencing analytical pipeline. Phenomodels includes a user‐friendly epilepsy phenotyping template and an objective measure for selecting which template terms to include in individualised Human Phenotype Ontology (HPO) gene panels. In a pilot study of 38 previously solved cases of developmental and epileptic encephalopathies, we compared the sensitivity and specificity of the individualised HPO gene panels with the clinical epilepsy gene panel. Results The Phenomodels template showed high sensitivity for capturing relevant phenotypic information, where 37/38 individuals' HPO gene panels included the causative gene. The HPO gene panels also had far fewer variants to assess than the epilepsy gene panel. Conclusion We have demonstrated a viable approach for incorporating standardised phenotype information into clinical genomic analyses, which may enable more efficient analysis.

Abstract Background Malan syndrome (MALNS) is a recently described ultrarare syndrome lacking guidelines for diagnosis, management and monitoring of evolutive complications. Less than 90 patients are reported in the literature and limited clinical information are available to assure a proper health surveillance. Results A multidisciplinary team with high expertise in MALNS has been launched at the “Ospedale Pediatrico Bambino Gesù”, Rome, Italy. Sixteen Italian MALNS individuals with molecular confirmed clinical diagnosis of MALNS were enrolled in the program. For all patients, 1-year surveillance in a dedicated outpatient Clinic was attained. The expert panel group enrolled 16 patients and performed a deep phenotyping analysis directed to clinically profiling the disorder and performing critical revision of previously reported individuals. Some evolutive complications were also assessed. Previously unappreciated features (e.g., high risk of bone fractures in childhood, neurological/neurovegetative symptoms, noise sensitivity and Chiari malformation type 1) requiring active surveillance were identified. A second case of neoplasm was recorded. No major cardiovascular anomalies were noticed. An accurate clinical description of 9 new MALNS cases was provided. Conclusions Deep phenotyping has provided a more accurate characterization of the main clinical features of MALNS and allows broadening the spectrum of disease. A minimal dataset of clinical evaluations and follow-up timeline has been proposed for proper management of patients affected by this ultrarare disorder.

Abstract The Global Alliance for Genomics and Health (GA4GH) is developing a suite of coordinated standards for genomics for healthcare. The Phenopacket is a new GA4GH standard for sharing disease and phenotype information that characterizes an individual person, linking that individual to detailed phenotypic descriptions, genetic information, diagnoses, and treatments. A detailed example is presented that illustrates how to use the schema to represent the clinical course of a patient with retinoblastoma, including demographic information, the clinical diagnosis, phenotypic features and clinical measurements, an examination of the extirpated tumor, therapies, and the results of genomic analysis. The Phenopacket Schema, together with other GA4GH data and technical standards, will enable data exchange and provide a foundation for the computational analysis of disease and phenotype information to improve our ability to diagnose and conduct research on all types of disorders, including cancer and rare diseases.

Background: Recurrent gene dosage disorders impart substantial risk for psychopathology. Yet, understanding that risk is hampered by complex presentations that challenge classical diagnostic systems. Here, we present a suite of generalizable analytic approaches for parsing this clinical complexity, which we illustrate through application to XYY syndrome. Method: We gathered high-dimensional measures of psychopathology in 64 XYY individuals and 60 XY controls, plus additional interviewer-based diagnostic data in the XYY group. We provide the first comprehensive diagnostic description of psychiatric morbidity in XYY syndrome and show how diagnostic morbidity relates to functioning, subthreshold symptoms, and ascertainment bias. We then map behavioral vulnerabilities and resilience across 67 behavioral dimensions before borrowing techniques from network science to resolve the mesoscale architecture of these dimensions and links to observable functional outcomes. Results: Carriage of an extra Y-chromosome increases risk for diverse psychiatric diagnoses, with clinically impactful subthreshold symptomatology. Highest rates are seen for neurodevelopmental and affective disorders. A lower bound of < 25% of carriers are free of any diagnosis. Dimensional analysis of 67 scales details the profile of psychopathology in XYY, which survives control for ascertainment bias, specifies attentional and social domains as the most impacted, and refutes stigmatizing historical associations between XYY and violence. Network modeling compresses all measured symptom scales into 8 modules with dissociable links to cognitive ability, adaptive function, and caregiver strain. Hub modules offer efficient proxies for the full symptom network. Conclusions: This study parses the complex behavioral phenotype of XYY syndrome by applying new and generalizable analytic approaches for analysis of deep-phenotypic psychiatric data in neurogenetic disorders. [ABSTRACT FROM AUTHOR]

With the increasing worldwide application of the Prechtl general movements assessment (GMA) beyond its original field of the early prediction of cerebral palsy (CP), substantial knowledge has been gained on early neuromotor repertoires across a broad spectrum of diagnostic groups. Here, we aimed to profile the neuromotor functions of infants with Prader-Willi syndrome (PWS) and to compare them with two other matched groups. One group included infants with CP; the other included patients who were treated at the same clinic and turned out to have inconspicuous developmental outcomes (IOs). The detailed GMA, i.e., the motor optimality score-revised (MOS-R), was used to prospectively assess the infants' (N = 54) movements. We underwent cross-condition comparisons to characterise both within-group similarities and variations and between-group distinctions and overlaps in infants' neuromotor functions. Although infants in both the PWS and the CP groups scored similarly low on MOS-R, their motor patterns were different. Frog-leg and mantis-hand postures were frequently seen in the PWS group. However, a PWS-specific general movements pattern was not observed. We highlight that pursuing in-depth knowledge within and beyond the motor domain in different groups has the potential to better understand different conditions, improve accurate diagnosis and individualised therapy, and contribute to deep phenotyping for precision medicine. [ABSTRACT FROM AUTHOR]

In the context of medical concept extraction, it is critical to determine if clinical signs or symptoms mentioned in the text were present or absent, experienced by the patient or their relatives. Previous studies have focused on the NLP aspect but not on how to leverage this supplemental information for clinical applications. In this paper, we aim to use the patient similarity networks framework to aggregate different phenotyping modalities. NLP techniques were applied to extract phenotypes and predict their modalities from 5470 narrative reports of 148 patients with ciliopathies (a group of rare diseases). Patient similarities were computed using each modality separately for aggregation and clustering. We found that aggregating negated phenotypes improved patient similarity, but further aggregating relatives' phenotypes worsened the result. We suggest that different modalities of phenotypes can contribute to patient similarity, but they should be aggregated carefully and with appropriate similarity metrics and aggregation models. [ABSTRACT FROM AUTHOR]

[Display omitted] Language aptitude has recently regained interest in cognitive neuroscience. Traditional language aptitude testing included phonemic coding ability, associative memory, grammatical sensitivity and inductive language learning. Moreover, domain-general cognitive abilities are associated with individual differences in language aptitude, together with factors that have yet to be elucidated. Beyond domain-general cognition, it is also likely that aptitude and experience in domain- specific but non-linguistic fields (e.g. music or numerical processing) influence and are influenced by language aptitude. We investigated some of these relationships in a sample of 152 participants, using exploratory graph analysis, across different levels of regularisation, i.e. sensitivity. We carried out a meta cluster analysis in a second step to identify variables that are robustly grouped together. We discuss the data, as well as their meta-network groupings, at a baseline network sensitivity level, and in two analyses, one including and the other excluding dyslexic readers. Our results show a stable association between language and cognition, and the isolation of multilingual language experience, musicality and literacy. We highlight the necessity of a more comprehensive view of language and of cognition as multivariate systems. [ABSTRACT FROM AUTHOR]

Identification and delineation of craniofacial characteristics support the clinical and molecular diagnosis of genetic syndromes. Deep learning (DL) frameworks for syndrome identification from 2D facial images are trained on large clinical datasets using standard convolutional neural networks for classification. In contrast, despite the increased availability of 3D scanners in clinical setups, similar frameworks remain absent for 3D facial photographs. The main challenges involve working with smaller datasets and the need for DL operations applicable to 3D geometric data. Therefore, to date, most 3D methods refrain from working across multiple syndromic groups and/or are solely based on traditional machine learning. The first contribution of this work is the use of geometric deep learning with spiral convolutions in a triplet-loss architecture. This geometric encoding (GE) learns a lower dimensional metric space from 3D facial data that is used as input to linear discriminant analysis (LDA) performing multiclass classification. Benchmarking is done against principal component analysis (PCA), a common technique in 3D facial shape analysis, and related work based on 65 distinct 3D facial landmarks as input to LDA. The second contribution of this work involves a part-based implementation to 3D facial shape analysis and multi-class syndrome classification, and this is applied to both GE and PCA. Based on 1,786 3D facial photographs of controls and individuals from 13 different syndrome classes, a five-fold cross-validation was used to investigate both contributions. Results indicate that GE performs better than PCA as input to LDA, and this especially so for more compact (lower dimensional) spaces. In addition, a part-based approach increases performance significantly for both GE and PCA, with a more significant improvement for the latter. I.e., this contribution enhances the power of the dataset. Finally, and interestingly, according to ablation studies within the part-based approach, the upper lip is the most distinguishing facial segment for classifying genetic syndromes in our dataset, which follows clinical expectation. This work stimulates an enhanced use of advanced part-based geometric deep learning methods for 3D facial imaging in clinical genetics.

Substantial advancement in the diagnosis and treatment of psychiatric disorders may come from assembling diverse data streams from clinical notes, neuroimaging, genetics, and real-time digital footprints from smartphones and wearable devices. This is called "deep phenotyping" and often involves machine learning. We argue that incidental findings arising in deep phenotyping research have certain special, morally and legally salient features: They are specific, actionable, numerous, and probabilistic. We consider ethical and legal implications of these features and propose a practical ethics strategy for managing them. [ABSTRACT FROM AUTHOR]

Biallelic mutations in the TTC5 gene have been associated with autosomal recessive intellectual disability (ARID) and subsequently with an ID syndrome including severe speech impairment, cerebral atrophy, and hypotonia as clinical cornerstones. A TTC5 role in IDs has been proposed based on the physical interaction of TTC5 with p300, and possibly reducing p300 co‐activator complex activity, similarly to what was observed in Menke‐Hennekam 1 and 2 patients (MKHK1 and 2) carrying, respectively, mutations in exon 30 and 31 of CREBBP and EP300, which code for the TTC5‐binding region. Recently, TTC5‐related brain malformation has been linked to tubulinopathies due to the function of TTC5 in tubulins' dynamics. We reported seven new patients with novel or recurrent TTC5 variants. The deep characterization of the molecular and phenotypic spectrum confirmed TTC5‐related disorder as a recognizable, very severe neurodevelopmental syndrome. In addition, other relevant clinical aspects, including a severe pre‐ and postnatal growth retardation, cryptorchidism, and epilepsy, have emerged from the reversal phenotype approach and the review of already published TTC5 cases. Microcephaly and facial dysmorphism resulted in being less variable than that documented before. The TTC5 clinical features have been compared with MKHK1 published cases in the hypothesis that clinical overlap in some characteristics of the two conditions was related to the common p300 molecular pathway. [ABSTRACT FROM AUTHOR]

Purpose: Despite ever-increasing knowledge of the genetic etiologies of neurodevelopmental disorders, approximately half remain undiagnosed after exome or genome sequencing. Here, we provide a deep clinical characterization of 11 previously unreported patients with a recently described neurodevelopmental disorder (NDD) due to pathogenic variants in RNU4-2., Methods: The 11 patients were identified in a pool of 70 patients selected for targeted RNU4-2 sequencing on the basis of their clinical phenotypes from a cohort of 1032 individuals with a NDD and without a prior genetic diagnosis., Results: The 11 patients were aged between 13 months and 36 years. All patients showed moderate to severe developmental delay and/or intellectual disability. Height and weight were below 10th percentile and most showed microcephaly. In almost 50% of the patients, intrauterine growth retardation was detected. All patients showed a distinctive pattern of dysmorphic features, including hooded upper eyelid and epicanthus, full cheeks, tented philtrum, mouth constantly slightly open with an everted lower lip vermilion, high palate, and profuse drooling. Of 11 patients, 64% also presented with ophthalmological problems (mainly strabismus, nystagmus, and refraction errors) and 64% had musculoskeletal features (joint hypermobility, mild scoliosis, and easy fractures)., Conclusion: This work provides an improved characterization of the phenotypic spectrum of RNU4-2 syndrome across different age groups and demonstrates that thorough clinical assessment of patients with an NDD can be enhanced significantly for this novel syndrome., Competing Interests: Conflict of Interest The enclosed manuscript has been revised and approved by all the authors and they have taken care to ensure the integrity of the work. The authors have no conflicts of interest or financial disclosures to report., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Children with autism spectrum disorder (ASD) often face challenges in early social communication skills, prompting the need for a detailed exploration of specific behaviors and their impact on cognitive and adaptive functioning. This study aims to address this gap by examining the developmental trajectories of early social communication skills in preschoolers with ASD aged 18-60 months, comparing them to age-matched typically developing (TD) children. Utilizing the early social communication scales (ESCS), the research employs a longitudinal design to capture changes over time. We apply a principal component analysis (PCA) to ESCS variables to identify underlying components, and cluster analysis to identify subgroups based on preverbal communication profiles. The results reveal consistent differences in early social communication skills between ASD and TD children, with ASD children exhibiting reduced skills. PCA identifies two components, distinguishing objects-directed behaviors and social interaction-directed behaviors. Cluster analysis identifies three subgroups of autistic children, each displaying specific communication profiles associated with distinct cognitive and adaptive functioning trajectories. In conclusion, this study provides a nuanced understanding of early social communication development in ASD, emphasizing the importance of low-level behaviors. The identification of subgroups and their unique trajectories contributes to a more comprehensive understanding of ASD heterogeneity. These findings underscore the significance of early diagnosis, focusing on specific behaviors predicting cognitive and adaptive functioning outcomes. The study encourages further research to explore the sequential development of these skills, offering valuable insights for interventions and support strategies., (© 2024 The Author(s). Autism Research published by International Society for Autism Research and Wiley Periodicals LLC.)

Chronic Lymphocytic Leukemia (CLL) is characterized by the progressive accumulation of monoclonal mature B lymphocytes. Autoimmune complications are common in CLL occurring in up to a quarter of all patients during the course of the illness. Etiology of autoimmunity in CLL is unknown but it is widely admitted that the pathogenic auto-Abs do not originate from the tumoral clone but from the non-malignant B cell pool. This indicates that the developmental scheme of non-malignant B cells could also be perturbed in CLL patients. To address this question, we have designed a B cell-centered antibody panel and used time-of-flight mass cytometry to compare the residual non-malignant B cell pool of CLL patients with the peripheral B cell pool of age-matched healthy donors. We show that the non-malignant B cell compartment of the patients is characterized by profound attrition of naïve B cells and of a population of anergized autoreactive B cells, suggesting impaired B cell lymphopoeisis as well as perturbations of the B cell tolerance checkpoints.

In the last few years, trio-Whole Exome Sequencing (WES) analysis has revolutionized the diagnostic process for patients with rare genetic syndromes, demonstrating its potential even in non-specific clinical pictures and in atypical presentations of known diseases. Multiple disorders in a single patient have been estimated to occur in approximately 2–7.5% of diagnosed cases, with higher frequency in consanguineous families. Here, we report the clinical and molecular characterisation of eight illustrative patients for whom trio-WES allowed for identifing more than one genetic condition. Double homozygosity represented the causal mechanism in only half of them, whereas the other half showed peculiar multilocus combinations. The paper takes into consideration difficulties and learned lessons from our experience and therefore supports the powerful role of wide analyses for ascertaining multiple genetic diseases in complex patients, especially when a clinical suspicion could account for the majority of clinical signs. It finally makes clear how a patient's "deep phenotyping" might not be sufficient to suggest the presence of multiple genetic diagnoses but remains essential to validate an unexpected multilocus result from genetic tests. [ABSTRACT FROM AUTHOR]

The Pulmonary Vascular Research Institute GoDeep meta‐registry is a collaboration of pulmonary hypertension (PH) reference centers across the globe. Merging worldwide PH data in a central meta‐registry to allow advanced analysis of the heterogeneity of PH and its groups/subgroups on a worldwide geographical, ethnical, and etiological landscape (ClinTrial. gov NCT05329714). Retrospective and prospective PH patient data (diagnosis based on catheterization; individuals with exclusion of PH are included as a comparator group) are mapped to a common clinical parameter set of more than 350 items, anonymized and electronically exported to a central server. Use and access is decided by the GoDeep steering board, where each center has one vote. As of April 2022, GoDeep comprised 15,742 individuals with 1.9 million data points from eight PH centers. Geographic distribution comprises 3990 enrollees (25%) from America and 11,752 (75%) from Europe. Eighty‐nine perecent were diagnosed with PH and 11% were classified as not PH and provided a comparator group. The retrospective observation period is an average of 3.5 years (standard error of the mean 0.04), with 1159 PH patients followed for over 10 years. Pulmonary arterial hypertension represents the largest PH group (42.6%), followed by Group 2 (21.7%), Group 3 (17.3%), Group 4 (15.2%), and Group 5 (3.3%). The age distribution spans several decades, with patients 60 years or older comprising 60%. The majority of patients met an intermediate risk profile upon diagnosis. Data entry from a further six centers is ongoing, and negotiations with >10 centers worldwide have commenced. Using electronic interface‐based automated retrospective and prospective data transfer, GoDeep aims to provide in‐depth epidemiological and etiological understanding of PH and its various groups/subgroups on a global scale, offering insights for improved management. [ABSTRACT FROM AUTHOR]

Background: Malan syndrome (MALNS) is a recently described ultrarare syndrome lacking guidelines for diagnosis, management and monitoring of evolutive complications. Less than 90 patients are reported in the literature and limited clinical information are available to assure a proper health surveillance.Results: A multidisciplinary team with high expertise in MALNS has been launched at the "Ospedale Pediatrico Bambino Gesù", Rome, Italy. Sixteen Italian MALNS individuals with molecular confirmed clinical diagnosis of MALNS were enrolled in the program. For all patients, 1-year surveillance in a dedicated outpatient Clinic was attained. The expert panel group enrolled 16 patients and performed a deep phenotyping analysis directed to clinically profiling the disorder and performing critical revision of previously reported individuals. Some evolutive complications were also assessed. Previously unappreciated features (e.g., high risk of bone fractures in childhood, neurological/neurovegetative symptoms, noise sensitivity and Chiari malformation type 1) requiring active surveillance were identified. A second case of neoplasm was recorded. No major cardiovascular anomalies were noticed. An accurate clinical description of 9 new MALNS cases was provided.Conclusions: Deep phenotyping has provided a more accurate characterization of the main clinical features of MALNS and allows broadening the spectrum of disease. A minimal dataset of clinical evaluations and follow-up timeline has been proposed for proper management of patients affected by this ultrarare disorder. [ABSTRACT FROM AUTHOR]

Despite recent progress in the understanding of the genetic etiologies of rare diseases (RDs), a significant number remain intractable to diagnostic and discovery efforts. Broad data collection and sharing of information among RD researchers is therefore critical. In 2018, the Care4Rare Canada Consortium launched the project C4R‐SOLVE, a subaim of which was to collect, harmonize, and share both retrospective and prospective Canadian clinical and multiomic data. Here, we introduce Genomics4RD, an integrated web‐accessible platform to share Canadian phenotypic and multiomic data between researchers, both within Canada and internationally, for the purpose of discovering the mechanisms that cause RDs. Genomics4RD has been designed to standardize data collection and processing, and to help users systematically collect, prioritize, and visualize participant information. Data storage, authorization, and access procedures have been developed in collaboration with policy experts and stakeholders to ensure the trusted and secure access of data by external researchers. The breadth and standardization of data offered by Genomics4RD allows researchers to compare candidate disease genes and variants between participants (i.e., matchmaking) for discovery purposes, while facilitating the development of computational approaches for multiomic data analyses and enabling clinical translation efforts for new genetic technologies in the future. [ABSTRACT FROM AUTHOR]

Abstract The Pulmonary Vascular Research Institute GoDeep meta‐registry is a collaboration of pulmonary hypertension (PH) reference centers across the globe. Merging worldwide PH data in a central meta‐registry to allow advanced analysis of the heterogeneity of PH and its groups/subgroups on a worldwide geographical, ethnical, and etiological landscape (ClinTrial. gov NCT05329714). Retrospective and prospective PH patient data (diagnosis based on catheterization; individuals with exclusion of PH are included as a comparator group) are mapped to a common clinical parameter set of more than 350 items, anonymized and electronically exported to a central server. Use and access is decided by the GoDeep steering board, where each center has one vote. As of April 2022, GoDeep comprised 15,742 individuals with 1.9 million data points from eight PH centers. Geographic distribution comprises 3990 enrollees (25%) from America and 11,752 (75%) from Europe. Eighty‐nine perecent were diagnosed with PH and 11% were classified as not PH and provided a comparator group. The retrospective observation period is an average of 3.5 years (standard error of the mean 0.04), with 1159 PH patients followed for over 10 years. Pulmonary arterial hypertension represents the largest PH group (42.6%), followed by Group 2 (21.7%), Group 3 (17.3%), Group 4 (15.2%), and Group 5 (3.3%). The age distribution spans several decades, with patients 60 years or older comprising 60%. The majority of patients met an intermediate risk profile upon diagnosis. Data entry from a further six centers is ongoing, and negotiations with >10 centers worldwide have commenced. Using electronic interface‐based automated retrospective and prospective data transfer, GoDeep aims to provide in‐depth epidemiological and etiological understanding of PH and its various groups/subgroups on a global scale, offering insights for improved management.

Febrile-associated epileptic encephalopathy is a large genetically heterogeneous group that is associated with pathogenic variants in SCN1A , PCDH19 , SCN2A , SCN8A , and other genes. The disease onset ranges from neonatal or early-onset epileptic encephalopathy to late-onset epilepsy after 18 months. Some etiology-specific epileptic encephalopathies have target therapy which can serve as a clue for the correct genetic diagnosis. We present genetic, clinical, electroencephalographic, and behavioral features of a 4-year-old girl with epileptic encephalopathy related to a de novo intronic variant in the SCN2A gene. Initial NGS analysis revealed a frameshift variant in the KDM6A gene and a previously reported missense variant in SCN1A. Due to lack of typical clinical signs of Kabuki syndrome, we performed X-chromosome inactivation that revealed nearly complete skewed inactivation. Segregation analysis showed that the SCN1A variant was inherited from a healthy father. The proband had resistance to multiple antiseizure medications but responded well to sodium channel inhibitor Carbamazepine. Reanalysis of NGS data by a neurogeneticist revealed a previously uncharacterized heterozygous variant c.1035–7A>G in the SCN2A gene. Minigene assay showed that the c.1035–7A>G variant activates a cryptic intronic acceptor site which leads to 6-nucleotide extension of exon 9 (NP_066287.2:p.(Gly345_Gln346insTyrSer). SCN2A encephalopathy is a recognizable severe phenotype. Its electro-clinical and treatment response features can serve as a hallmark. In such a patient, reanalysis of genetic data is strongly recommended in case of negative or conflicting results of DNA analysis. [ABSTRACT FROM AUTHOR]

Background: Neurodevelopmental disorders, a group of early‐onset neurological disorders with significant clinical and genetic heterogeneity, remain a diagnostic challenge for clinical genetic evaluation. Therefore, we assessed the diagnostic yield by combining standard phenotypes and whole‐exome sequencing in families with these disorders that were "not yet diagnosed" by the traditional testing methods. Methods: Using a standardized vocabulary of phenotypic abnormalities from human phenotype ontology (HPO), we performed deep phenotyping for 45 "not yet diagnosed" pedigrees to characterize multiple clinical features extracted from Chinese electronic medical records (EMRs). By matching HPO terms with known human diseases and phenotypes from model organisms, together with whole‐exome sequencing data, we prioritized candidate mutations/genes. We made probable genetic diagnoses for the families. Results: We obtained a diagnostic yield of 29% (13 out of 45) with probably genetic diagnosis, of which compound heterozygosity and de novo mutations accounted for 77% (10/13) of the diagnosis. Of note, these pedigrees are accompanied by a more significant number of non‐neurological features. Conclusions: Deep phenotyping and whole‐exome sequencing improve the etiological evaluation for neurodevelopmental disorders in the clinical setting. [ABSTRACT FROM AUTHOR]