American Journal of Medical Genetics Part C: Seminars in Medical Genetics最新文献

{"title":"Computational facial analysis for rare Mendelian disorders","authors":"Tzung-Chien Hsieh,&nbsp;Peter M. Krawitz","doi":"10.1002/ajmg.c.32061","DOIUrl":"10.1002/ajmg.c.32061","url":null,"abstract":"<p>With the advances in computer vision, computational facial analysis has become a powerful and effective tool for diagnosing rare disorders. This technology, also called next-generation phenotyping (NGP), has progressed significantly over the last decade. This review paper will introduce three key NGP approaches. In 2014, Ferry et al. first presented Clinical Face Phenotype Space (CFPS) trained on eight syndromes. After 5 years, Gurovich et al. proposed DeepGestalt, a deep convolutional neural network trained on more than 21,000 patient images with 216 disorders. It was considered a state-of-the-art disorder classification framework. In 2022, Hsieh et al. developed GestaltMatcher to support the ultra-rare and novel disorders not supported in DeepGestalt. It further enabled the analysis of facial similarity presented in a given cohort or multiple disorders. Moreover, this article will present the usage of NGP for variant prioritization and facial gestalt delineation. Although NGP approaches have proven their capability in assisting the diagnosis of many disorders, many limitations remain. This article will introduce two future directions to address two main limitations: enabling the global collaboration for a medical imaging database that fulfills the FAIR principles and synthesizing patient images to protect patient privacy. In the end, with more and more NGP approaches emerging, we envision that the NGP technology can assist clinicians and researchers in diagnosing patients and analyzing disorders in multiple directions in the near future.</p>","PeriodicalId":7445,"journal":{"name":"American Journal of Medical Genetics Part C: Seminars in Medical Genetics","volume":"193 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.c.32061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9997772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence and the impact on medical genetics","authors":"Benjamin D. Solomon,&nbsp;Wendy K. Chung","doi":"10.1002/ajmg.c.32060","DOIUrl":"10.1002/ajmg.c.32060","url":null,"abstract":"<p>Virtually all areas of biomedicine will be increasingly affected by applications of artificial intelligence (AI). We discuss how AI may affect fields of medical genetics, including both clinicians and laboratorians. In addition to reviewing the anticipated impact, we provide recommendations for ways in which these groups may want to evolve in light of the influence of AI. We also briefly discuss how educational and training programs can play a key role in preparing the future workforce given these anticipated changes.</p>","PeriodicalId":7445,"journal":{"name":"American Journal of Medical Genetics Part C: Seminars in Medical Genetics","volume":"193 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.c.32060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9974406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of facial analysis Technology in Clinical Genetics: Considerations for diverse populations","authors":"Paul Kruszka,&nbsp;Cedrik Tekendo-Ngongang","doi":"10.1002/ajmg.c.32059","DOIUrl":"10.1002/ajmg.c.32059","url":null,"abstract":"<p>Facial analysis technology in rare diseases has the potential to shorten the diagnostic odyssey by providing physicians with a valuable diagnostic tool. Given that most clinical genetic resources focus on populations of European descent, we compare craniofacial features in genetic syndromes across different populations and review how machine learning algorithms perform on diagnosing genetic syndromes in geographically and ethnically diverse populations. We also discuss the value of populations from ancestrally diverse backgrounds in the training set of machine learning algorithms. Finally, this review demonstrates that across diverse population groups, machine learning models have outstanding accuracy as supported by the area under the curve values greater than 0.9. Artificial intelligence is only in its infancy in the diagnosis of rare disease in diverse populations and will become more accurate as larger and more diverse training sets, including a wider spectrum of ages, particularly infants, are studied.</p>","PeriodicalId":7445,"journal":{"name":"American Journal of Medical Genetics Part C: Seminars in Medical Genetics","volume":"193 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.c.32059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9927786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of webcam-collected and artificial-intelligence-derived social and cognitive performance measures for neurodevelopmental genetic syndromes","authors":"Thomas W. Frazier,&nbsp;Robyn M. Busch,&nbsp;Patricia Klaas,&nbsp;Katherine Lachlan,&nbsp;Shafali Jeste,&nbsp;Alexander Kolevzon,&nbsp;Eva Loth,&nbsp;Jacqueline Harris,&nbsp;Leslie Speer,&nbsp;Tom Pepper,&nbsp;Kristin Anthony,&nbsp;J. Michael Graglia,&nbsp;Christal G. Delagrammatikas,&nbsp;Sandra Bedrosian-Sermone,&nbsp;Constance Smith-Hicks,&nbsp;Katie Huba,&nbsp;Robert Longyear,&nbsp;LeeAnne Green-Snyder,&nbsp;Frederick Shic,&nbsp;Mustafa Sahin,&nbsp;Charis Eng,&nbsp;Antonio Y. Hardan,&nbsp;Mirko Uljarević","doi":"10.1002/ajmg.c.32058","DOIUrl":"10.1002/ajmg.c.32058","url":null,"abstract":"<p>This study focused on the development and initial psychometric evaluation of a set of online, webcam-collected, and artificial intelligence-derived patient performance measures for neurodevelopmental genetic syndromes (NDGS). Initial testing and qualitative input was used to develop four stimulus paradigms capturing social and cognitive processes, including social attention, receptive vocabulary, processing speed, and single-word reading. The paradigms were administered to a sample of 375 participants, including 163 with NDGS, 56 with idiopathic neurodevelopmental disability (NDD), and 156 neurotypical controls. Twelve measures were created from the four stimulus paradigms. Valid completion rates varied from 87 to 100% across measures, with lower but adequate completion rates in participants with intellectual disability. Adequate to excellent internal consistency reliability (<i>α</i> = 0.67 to 0.95) was observed across measures. Test–retest reproducibility at 1-month follow-up and stability at 4-month follow-up was fair to good (<i>r</i> = 0.40–0.73) for 8 of the 12 measures. All gaze-based measures showed evidence of convergent and discriminant validity with parent-report measures of other cognitive and behavioral constructs. Comparisons across NDGS groups revealed distinct patterns of social and cognitive functioning, including people with <i>PTEN</i> mutations showing a less impaired overall pattern and people with <i>SYNGAP1</i> mutations showing more attentional, processing speed, and social processing difficulties relative to people with <i>NFIX</i> mutations. Webcam-collected performance measures appear to be a reliable and potentially useful method for objective characterization and monitoring of social and cognitive processes in NDGS and idiopathic NDD. Additional validation work, including more detailed convergent and discriminant validity analyses and examination of sensitivity to change, is needed to replicate and extend these observations.</p>","PeriodicalId":7445,"journal":{"name":"American Journal of Medical Genetics Part C: Seminars in Medical Genetics","volume":"193 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.c.32058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10016091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applications of artificial intelligence in clinical laboratory genomics","authors":"Swaroop Aradhya,&nbsp;Flavia M. Facio,&nbsp;Hillery Metz,&nbsp;Toby Manders,&nbsp;Alexandre Colavin,&nbsp;Yuya Kobayashi,&nbsp;Keith Nykamp,&nbsp;Britt Johnson,&nbsp;Robert L. Nussbaum","doi":"10.1002/ajmg.c.32057","DOIUrl":"10.1002/ajmg.c.32057","url":null,"abstract":"<p>The transition from analog to digital technologies in clinical laboratory genomics is ushering in an era of “big data” in ways that will exceed human capacity to rapidly and reproducibly analyze those data using conventional approaches. Accurately evaluating complex molecular data to facilitate timely diagnosis and management of genomic disorders will require supportive artificial intelligence methods. These are already being introduced into clinical laboratory genomics to identify variants in DNA sequencing data, predict the effects of DNA variants on protein structure and function to inform clinical interpretation of pathogenicity, link phenotype ontologies to genetic variants identified through exome or genome sequencing to help clinicians reach diagnostic answers faster, correlate genomic data with tumor staging and treatment approaches, utilize natural language processing to identify critical published medical literature during analysis of genomic data, and use interactive chatbots to identify individuals who qualify for genetic testing or to provide pre-test and post-test education. With careful and ethical development and validation of artificial intelligence for clinical laboratory genomics, these advances are expected to significantly enhance the abilities of geneticists to translate complex data into clearly synthesized information for clinicians to use in managing the care of their patients at scale.</p>","PeriodicalId":7445,"journal":{"name":"American Journal of Medical Genetics Part C: Seminars in Medical Genetics","volume":"193 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.c.32057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9888181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Table of Contents, Volume 193, Number 2, June 2023","authors":"","doi":"10.1002/ajmg.c.31977","DOIUrl":"https://doi.org/10.1002/ajmg.c.31977","url":null,"abstract":"","PeriodicalId":7445,"journal":{"name":"American Journal of Medical Genetics Part C: Seminars in Medical Genetics","volume":"193 2","pages":"99-100"},"PeriodicalIF":3.1,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.c.31977","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50153074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Publication schedule for 2023","authors":"","doi":"10.1002/ajmg.c.31978","DOIUrl":"https://doi.org/10.1002/ajmg.c.31978","url":null,"abstract":"","PeriodicalId":7445,"journal":{"name":"American Journal of Medical Genetics Part C: Seminars in Medical Genetics","volume":"193 2","pages":"101"},"PeriodicalIF":3.1,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.c.31978","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50153075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cover Image, Volume 193, Number 2, June 2023","authors":"","doi":"10.1002/ajmg.c.31979","DOIUrl":"https://doi.org/10.1002/ajmg.c.31979","url":null,"abstract":"<p><b>Cover legend: Kabuki syndrome across the lifespan</b></p><p>Images depicting physical exam features of three adult patients with <i>KMT2D</i>-related Kabuki syndrome. For Patients 7 and 8, photographs illustrate the evolution of the facial phenotype over time.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":7445,"journal":{"name":"American Journal of Medical Genetics Part C: Seminars in Medical Genetics","volume":"193 2","pages":"i"},"PeriodicalIF":3.1,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.c.31979","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50153082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unmasking the challenges of Kabuki syndrome in adulthood: A case series","authors":"Jessica R. C. Priestley,&nbsp;Alyssa L. Rippert,&nbsp;Courtney Condit,&nbsp;Kosuke Izumi,&nbsp;Staci Kallish,&nbsp;Theodore G. Drivas","doi":"10.1002/ajmg.c.32054","DOIUrl":"10.1002/ajmg.c.32054","url":null,"abstract":"<p>Kabuki syndrome is a recognizable Mendelian disorder characterized by the clinical constellation of childhood hypotonia, developmental delay or intellectual impairment, and characteristic dysmorphism resulting from monoallelic pathogenic variants in <i>KMT2D</i> or <i>KDM6A</i>. In the medical literature, most reported patients are children, and data is lacking on the natural history of the condition across the lifespan, with little known about adult-specific presentations and symptoms. Here, we report the results of a retrospective chart review of eight adult patients with Kabuki syndrome, seven of whom are molecularly confirmed. We use their trajectories to highlight the diagnostic challenges unique to an adult population, expand on neurodevelopmental/psychiatric phenotypes across the lifespan, and describe adult-onset medical complications, including a potential cancer risk and unusual and striking premature/accelerated aging phenotype.</p>","PeriodicalId":7445,"journal":{"name":"American Journal of Medical Genetics Part C: Seminars in Medical Genetics","volume":"193 2","pages":"128-138"},"PeriodicalIF":3.1,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9670392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Autosomal dominant genodermatoses in adults being heralded by superimposed skin lesions in children","authors":"Rudolf Happle","doi":"10.1002/ajmg.c.32055","DOIUrl":"10.1002/ajmg.c.32055","url":null,"abstract":"<p>In autosomal dominant skin disorders, pronounced mosaic involvement may sometimes occur in the neonate, originating in a heterozygous embryo from early loss of heterozygosity, probably during the first week after fertilization. In biallelic phenotypes, such overlaying mosaic involvement may coexist with disseminated mosaicism, for example, in neurofibromatosis or tuberous sclerosis. In other phenotypes, however, classical nonsegmental involvement tends to appear much later, which is why the superimposed mosaic is a heralding feature. In Brooke–Spiegler syndrome (eccrine cylindromatosis), a large pedigree documented a 5-year-old boy with multiple, congenital small eccrine cylindromas along the lines of Blaschko. Disseminated cylindromas were absent because they usually appear in adulthood. ̶ In Hornstein–Knickenberg syndrome, an affected woman had an 8-year-old son with a nevus comedonicus-like lesion exemplifying a forerunner of the syndrome. (“Birt-Hogg-Dubé syndrome” represents a nonsyndromic type of hereditary perifollicular fibromas.) In glomangiomatosis, neonatal superimposed mosaicism is a heralding feature because disseminated lesions appear during puberty or adulthood. Linear porokeratosis is a harbinger of disseminated porokeratosis that develops 30 or 40 years later. ̶ Cases of superimposed linear Darier disease were forerunners of nonsegmental manifestation. ̶ In a case of Hailey–Hailey disease, neonatal mosaic lesions heralded nonsegmental involvement that began 22 years later.</p>","PeriodicalId":7445,"journal":{"name":"American Journal of Medical Genetics Part C: Seminars in Medical Genetics","volume":"193 2","pages":"109-115"},"PeriodicalIF":3.1,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.c.32055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9664062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}