Phenome-wide profiling identifies genotype-phenotype associations in Phelan-McDermid syndrome using family-sourced data from an international registry / Rui YIN in Molecular Autism, 15 (2024)  

Public ISBD [article]  inMolecular Autism > 15 (2024) . - 40p. Titre : Phenome-wide profiling identifies genotype-phenotype associations in Phelan-McDermid syndrome using family-sourced data from an international registry Type de document : texte imprimé Auteurs : Rui YIN, Auteur ; Maxime WACK, Auteur ; Claire HASSEN-KHODJA, Auteur ; Michael T. MCDUFFIE, Auteur ; Geraldine BLISS, Auteur ; Elizabeth J. HORN, Auteur ; Cartik KOTHARI, Auteur ; Brittany MCLARNEY, Auteur ; Rebecca DAVIS, Auteur ; Kristen HANSON, Auteur ; Megan O'BOYLE, Auteur ; Catalina BETANCUR, Auteur ; Paul AVILLACH, Auteur Article en page(s) : 40p. Langues : Anglais (eng) Mots-clés : Humans  Registries  Chromosome Deletion  Chromosomes, Human, Pair 22/genetics  Male  Chromosome Disorders/genetics  Female  Phenotype  Genetic Association Studies  Child  Child, Preschool  Nerve Tissue Proteins/genetics  Adolescent  Adult  Young Adult  Family  Infant  Shank3  22q13.3 deletion  Phelan-McDermid syndrome  Phenome-wide association study  competing interests. Index. décimale : PER Périodiques Résumé : BACKGROUND: Phelan-McDermid syndrome (PMS) is a rare neurodevelopmental disorder caused by 22q13 deletions that include the SHANK3 gene or pathogenic sequence variants in SHANK3. It is characterized by global developmental delay, intellectual disability, speech impairment, autism spectrum disorder, and hypotonia; other variable features include epilepsy, brain and renal malformations, and mild dysmorphic features. Here, we conducted genotype-phenotype correlation analyses using the PMS International Registry, a family-driven registry that compiles clinical data in the form of family-reported outcomes and family-sourced genetic test results. METHODS: Data from the registry were harmonized and integrated into the i2b2/tranSMART clinical and genomics data warehouse. We gathered information from 401 individuals with 22q13 deletions including SHANK3 (n = 350, ranging in size from 10 kb to 9.1 Mb) or pathogenic or likely pathogenic SHANK3 sequence variants (n = 51), and used regression models with deletion size as a potential predictor of clinical outcomes for 328 phenotypes. RESULTS: Our results showed that increased deletion size was significantly associated with delay in gross and fine motor acquisitions, a spectrum of conditions related to poor muscle tone, renal malformations, mild dysmorphic features (e.g., large fleshy hands, sacral dimple, dysplastic toenails, supernumerary teeth), lymphedema, congenital heart defects, and more frequent neuroimaging abnormalities and infections. These findings indicate that genes upstream of SHANK3 also contribute to some of the manifestations of PMS in individuals with larger deletions. We also showed that self-help skills, verbal ability and a range of psychiatric diagnoses (e.g., autism, ADHD, anxiety disorder) were more common among individuals with smaller deletions and SHANK3 variants. LIMITATIONS: Some participants were tested with targeted 22q microarrays rather than genome-wide arrays, and karyotypes were unavailable in many cases, thus precluding the analysis of the effect of other copy number variants or chromosomal rearrangements on the phenotype. CONCLUSIONS: This is the largest reported case series of individuals with PMS. Overall, we demonstrate the feasibility of using data from a family-sourced registry to conduct genotype-phenotype analyses in rare genetic disorders. We replicate and strengthen previous findings, and reveal novel associations between larger 22q13 deletions and congenital heart defects, neuroimaging abnormalities and recurrent infections. En ligne : https://dx.doi.org/10.1186/s13229-024-00619-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=538 [article] Phenome-wide profiling identifies genotype-phenotype associations in Phelan-McDermid syndrome using family-sourced data from an international registry [texte imprimé] / Rui YIN, Auteur ; Maxime WACK, Auteur ; Claire HASSEN-KHODJA, Auteur ; Michael T. MCDUFFIE, Auteur ; Geraldine BLISS, Auteur ; Elizabeth J. HORN, Auteur ; Cartik KOTHARI, Auteur ; Brittany MCLARNEY, Auteur ; Rebecca DAVIS, Auteur ; Kristen HANSON, Auteur ; Megan O'BOYLE, Auteur ; Catalina BETANCUR, Auteur ; Paul AVILLACH, Auteur . - 40p. Langues : Anglais (eng) in Molecular Autism > 15 (2024) . - 40p. Mots-clés : Humans  Registries  Chromosome Deletion  Chromosomes, Human, Pair 22/genetics  Male  Chromosome Disorders/genetics  Female  Phenotype  Genetic Association Studies  Child  Child, Preschool  Nerve Tissue Proteins/genetics  Adolescent  Adult  Young Adult  Family  Infant  Shank3  22q13.3 deletion  Phelan-McDermid syndrome  Phenome-wide association study  competing interests. Index. décimale : PER Périodiques Résumé : BACKGROUND: Phelan-McDermid syndrome (PMS) is a rare neurodevelopmental disorder caused by 22q13 deletions that include the SHANK3 gene or pathogenic sequence variants in SHANK3. It is characterized by global developmental delay, intellectual disability, speech impairment, autism spectrum disorder, and hypotonia; other variable features include epilepsy, brain and renal malformations, and mild dysmorphic features. Here, we conducted genotype-phenotype correlation analyses using the PMS International Registry, a family-driven registry that compiles clinical data in the form of family-reported outcomes and family-sourced genetic test results. METHODS: Data from the registry were harmonized and integrated into the i2b2/tranSMART clinical and genomics data warehouse. We gathered information from 401 individuals with 22q13 deletions including SHANK3 (n = 350, ranging in size from 10 kb to 9.1 Mb) or pathogenic or likely pathogenic SHANK3 sequence variants (n = 51), and used regression models with deletion size as a potential predictor of clinical outcomes for 328 phenotypes. RESULTS: Our results showed that increased deletion size was significantly associated with delay in gross and fine motor acquisitions, a spectrum of conditions related to poor muscle tone, renal malformations, mild dysmorphic features (e.g., large fleshy hands, sacral dimple, dysplastic toenails, supernumerary teeth), lymphedema, congenital heart defects, and more frequent neuroimaging abnormalities and infections. These findings indicate that genes upstream of SHANK3 also contribute to some of the manifestations of PMS in individuals with larger deletions. We also showed that self-help skills, verbal ability and a range of psychiatric diagnoses (e.g., autism, ADHD, anxiety disorder) were more common among individuals with smaller deletions and SHANK3 variants. LIMITATIONS: Some participants were tested with targeted 22q microarrays rather than genome-wide arrays, and karyotypes were unavailable in many cases, thus precluding the analysis of the effect of other copy number variants or chromosomal rearrangements on the phenotype. CONCLUSIONS: This is the largest reported case series of individuals with PMS. Overall, we demonstrate the feasibility of using data from a family-sourced registry to conduct genotype-phenotype analyses in rare genetic disorders. We replicate and strengthen previous findings, and reveal novel associations between larger 22q13 deletions and congenital heart defects, neuroimaging abnormalities and recurrent infections. En ligne : https://dx.doi.org/10.1186/s13229-024-00619-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=538

Validation of a computational phenotype for finding patients eligible for genetic testing for pathogenic PTEN variants across three centers / Cartik KOTHARI in Journal of Neurodevelopmental Disorders, 14 (2022)  

Public ISBD [article]  inJournal of Neurodevelopmental Disorders > 14 (2022) Titre : Validation of a computational phenotype for finding patients eligible for genetic testing for pathogenic PTEN variants across three centers Type de document : texte imprimé Auteurs : Cartik KOTHARI, Auteur ; Siddharth SRIVASTAVA, Auteur ; Youssef KOUSA, Auteur ; Rima IZEM, Auteur ; Marcin GIERDALSKI, Auteur ; Dongkyu KIM, Auteur ; Amy GOOD, Auteur ; Kira A. DIES, Auteur ; Gregory GEISEL, Auteur ; Hiroki MORIZONO, Auteur ; Vittorio GALLO, Auteur ; Scott L. POMEROY, Auteur ; Gwenn A. GARDEN, Auteur ; Lisa GUAY-WOODFORD, Auteur ; Mustafa SAHIN, Auteur ; Paul AVILLACH, Auteur Langues : Anglais (eng) Mots-clés : Electronic Health Records  Genetic Testing  Hamartoma Syndrome, Multiple/diagnosis/genetics/pathology  Humans  PTEN Phosphohydrolase/genetics  Phenotype  Autism  Computational phenotype  Genetic disease  Rare disease  from GLG, Guidepoint (which connected to a client, Fortress Biotech), and  Novartis. 3. YK has no competing interests to declare. 4. RI has no competing  interests to declare. 5. MG has no competing interests to declare. 6. DK has no  competing interests to declare. 7. AG has no competing interests to declare. 8.  KAD has no competing interests to declare. 9. GG has no competing interests to  declare. 10. HM has no competing interests to declare. 11. VG has no competing  interests to declare. 12. SP has no competing interests to declare. 13. GAG has  no competing interests to declare. 14. LGW has no competing interests to declare.  15. MS reports grant support from Novartis, Roche, Biogen, Astellas, Aeovian,  Bridgebio, Aucta, and Quadrant Biosciences. He has served on Scientific Advisory  Boards for PTEN Research, Novartis, Roche, Celgene, Regenxbio, Alkermes, and  Takeda. 16. PA has no competing interests to declare Index. décimale : PER Périodiques Résumé : BACKGROUND: Computational phenotypes are most often combinations of patient billing codes that are highly predictive of disease using electronic health records (EHR). In the case of rare diseases that can only be diagnosed by genetic testing, computational phenotypes identify patient cohorts for genetic testing and possible diagnosis. This article details the validation of a computational phenotype for PTEN hamartoma tumor syndrome (PHTS) against the EHR of patients at three collaborating clinical research centers: Boston Children's Hospital, Children's National Hospital, and the University of Washington. METHODS: A combination of billing codes from the International Classification of Diseases versions 9 and 10 (ICD-9 and ICD-10) for diagnostic criteria postulated by a research team at Cleveland Clinic was used to identify patient cohorts for genetic testing from the clinical data warehouses at the three research centers. Subsequently, the EHR-including billing codes, clinical notes, and genetic reports-of these patients were reviewed by clinical experts to identify patients with PHTS. RESULTS: The PTEN genetic testing yield of the computational phenotype, the number of patients who needed to be genetically tested for incidence of pathogenic PTEN gene variants, ranged from 82 to 94% at the three centers. CONCLUSIONS: Computational phenotypes have the potential to enable the timely and accurate diagnosis of rare genetic diseases such as PHTS by identifying patient cohorts for genetic sequencing and testing. En ligne : https://dx.doi.org/10.1186/s11689-022-09434-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=574 [article] Validation of a computational phenotype for finding patients eligible for genetic testing for pathogenic PTEN variants across three centers [texte imprimé] / Cartik KOTHARI, Auteur ; Siddharth SRIVASTAVA, Auteur ; Youssef KOUSA, Auteur ; Rima IZEM, Auteur ; Marcin GIERDALSKI, Auteur ; Dongkyu KIM, Auteur ; Amy GOOD, Auteur ; Kira A. DIES, Auteur ; Gregory GEISEL, Auteur ; Hiroki MORIZONO, Auteur ; Vittorio GALLO, Auteur ; Scott L. POMEROY, Auteur ; Gwenn A. GARDEN, Auteur ; Lisa GUAY-WOODFORD, Auteur ; Mustafa SAHIN, Auteur ; Paul AVILLACH, Auteur. Langues : Anglais (eng) in Journal of Neurodevelopmental Disorders > 14 (2022) Mots-clés : Electronic Health Records  Genetic Testing  Hamartoma Syndrome, Multiple/diagnosis/genetics/pathology  Humans  PTEN Phosphohydrolase/genetics  Phenotype  Autism  Computational phenotype  Genetic disease  Rare disease  from GLG, Guidepoint (which connected to a client, Fortress Biotech), and  Novartis. 3. YK has no competing interests to declare. 4. RI has no competing  interests to declare. 5. MG has no competing interests to declare. 6. DK has no  competing interests to declare. 7. AG has no competing interests to declare. 8.  KAD has no competing interests to declare. 9. GG has no competing interests to  declare. 10. HM has no competing interests to declare. 11. VG has no competing  interests to declare. 12. SP has no competing interests to declare. 13. GAG has  no competing interests to declare. 14. LGW has no competing interests to declare.  15. MS reports grant support from Novartis, Roche, Biogen, Astellas, Aeovian,  Bridgebio, Aucta, and Quadrant Biosciences. He has served on Scientific Advisory  Boards for PTEN Research, Novartis, Roche, Celgene, Regenxbio, Alkermes, and  Takeda. 16. PA has no competing interests to declare Index. décimale : PER Périodiques Résumé : BACKGROUND: Computational phenotypes are most often combinations of patient billing codes that are highly predictive of disease using electronic health records (EHR). In the case of rare diseases that can only be diagnosed by genetic testing, computational phenotypes identify patient cohorts for genetic testing and possible diagnosis. This article details the validation of a computational phenotype for PTEN hamartoma tumor syndrome (PHTS) against the EHR of patients at three collaborating clinical research centers: Boston Children's Hospital, Children's National Hospital, and the University of Washington. METHODS: A combination of billing codes from the International Classification of Diseases versions 9 and 10 (ICD-9 and ICD-10) for diagnostic criteria postulated by a research team at Cleveland Clinic was used to identify patient cohorts for genetic testing from the clinical data warehouses at the three research centers. Subsequently, the EHR-including billing codes, clinical notes, and genetic reports-of these patients were reviewed by clinical experts to identify patients with PHTS. RESULTS: The PTEN genetic testing yield of the computational phenotype, the number of patients who needed to be genetically tested for incidence of pathogenic PTEN gene variants, ranged from 82 to 94% at the three centers. CONCLUSIONS: Computational phenotypes have the potential to enable the timely and accurate diagnosis of rare genetic diseases such as PHTS by identifying patient cohorts for genetic sequencing and testing. En ligne : https://dx.doi.org/10.1186/s11689-022-09434-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=574

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