A talented giant: a tribute to the memory of John M. Opitz.

BACKGROUND: John M. Opitz, a towering figure in both stature and scientific achievement, left an indelible mark on the fields of genetics, pediatrics, and embryology. Born in 1935 in Hamburg to a Jewish family, Opitz's early life was marked by adversities. Despite these challenges, he pursued a remarkable career, immigrating to the United States at 15 years and becoming a renowned scientist in institutions like Iowa State University and the University of Wisconsin, where he made groundbreaking contributions to clinical genetics. MAIN BODY: A testament to his compassionate nature, Opitz dedicated himself to understanding and treating rare genetic disorders, earning him eponymous recognition in several medical conditions. His impact extended beyond academia, as evidenced by his collaborative efforts with Sicilian universities to advance clinical genetics in Italy. Opitz's teaching style emphasized simplicity, empathy, and meticulous clinical examination, leaving an indelible mark on students and colleagues. CONCLUSION: John M. Opitz's towering intellect, compassionate demeanor, and profound impact on medicine and genetics made him a figure of enduring significance. His legacy lives on through the countless lives he touched, the knowledge he transmitted, and the enduring friendships he forged. In remembering John Opitz, we honor not only a man, but also a myth-a symbol of resilience, humanity, and scientific excellence.

The impact and future of artificial intelligence in medical genetics and molecular medicine: an ongoing revolution.

Artificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, availability of greater sets of omics data, and the need to continuously analyse them have led to the development of new AI platforms. AI continues to weave its way into the fabric of genetics with the potential to unlock new discoveries and enhance patient care. This technology is setting the stage for breakthroughs across various domains, including dysmorphology, rare hereditary diseases, cancers, clinical microbiomics, the investigation of zoonotic diseases, omics studies in all medical disciplines. AI's role in facilitating a deeper understanding of these areas heralds a new era of personalised medicine, where treatments and diagnoses are tailored to the individual's molecular features, offering a more precise approach to combating genetic or acquired disorders. The significance of these AI platforms is growing as they assist healthcare professionals in the diagnostic and treatment processes, marking a pivotal shift towards more informed, efficient, and effective medical practice. In this review, we will explore the range of AI tools available and show how they have become vital in various sectors of genomic research supporting clinical decisions.

Victor McKusick: Father of Medical Genetics and his Impact on Orthopaedics.

Victor McKusick, an iconic figure in medicine and considered the founding father of medical genetics, lived an exemplary life bound to inspire others. As a geneticist, McKusick was heavily involved in the Human Genome Project and the development of the widely used Online Mendelian Inheritance in Man. As a researcher and prolific writer, he published more than 700 research articles, reviews, and books. McKusick educated and inspired thousands of students, doctors, and scientists while performing landmark studies in hereditary disorders and skeletal dysplasias. This brief history describes the life of Dr. Victor McKusick and his tremendous impact on orthopaedic surgery. (Journal of Surgical Orthopaedic Advances 33(2):068-071, 2024).

Eugenics and the misuse of Mendel.

Highlighting the Distinguished Speakers Symposium on "The Future of Human Genetics and Genomics," this collection of articles is based on presentations at the ASHG 2023 Annual Meeting in Washington, DC, in celebration of all our field has accomplished in the past 75 years, since the founding of ASHG in 1948.

Identifying knowledge deficiencies in genetics education among medical students and interns in Saudi Arabia- A cross-sectional study.

BACKGROUND: Understanding genetics is crucial for medical students, particularly in Saudi Arabia, where genetic disorders are prevalent owing to high rates of consanguineous marriages. This knowledge is essential for the early detection, prevention, and management of genetic disorders, and for incorporating medical genetics and genomics into patient care. This study aimed to assess the current state of genetics knowledge among medical students and interns across Saudi Arabia and to identify knowledge gaps in genetics. METHOD: A cross-sectional study was conducted between August and September 2023 involving 732 medical students from all regions of Saudi Arabia. The participants completed a validated questionnaire assessing their knowledge of basic genetics, genetic inheritance, genetic testing, and clinical genetics. RESULT: Over 60% of medical students and interns reported that they considered themselves to have only slight knowledge in all areas of genetics. The results revealed a general lack of medical genetic understanding among students and interns, particularly regarding genetic inheritance and testing. For genetic inheritance, slight knowledge was found in 65.2% of pre-clinical, 60.1% of clinical, and 53.2% of interns, with significant differences between groups (p < 0.001). In genetic testing, 75.4% of pre-clinical, 83.9% of clinical, and 90.6% of interns showed slight knowledge, with significant differences across stages (p = 0.021). This study also found that lectures, genetics laboratories, and problem-solving sessions were the preferred resources for learning genetics. CONCLUSION: The current study revealed a notable deficiency in the understanding of medical genetics among medical students and interns in Saudi Arabia, particularly regarding genetic inheritance and testing. This is consistent with previous research highlighting the widespread lack of genetics knowledge among medical students. Integrating more comprehensive genetics education, especially during the clinical years, could improve students' preparedness and confidence in managing genetic disorders. These findings highlight the critical need for curriculum development to equip future physicians with the essential skills for managing genetic disorders.

Myotonic dystrophy type 1 testing, 2024 revision: A technical standard of the American College of Medical Genetics and Genomics (ACMG).

Myotonic dystrophy type 1 (DM1) is a form of muscular dystrophy causing progressive muscle loss and weakness. Although clinical features can manifest at any age, it is the most common form of muscular dystrophy with onset in adulthood. DM1 is an autosomal dominant condition, resulting from an unstable CTG expansion in the 3'-untranslated region of the myotonic dystrophy protein kinase (DMPK) gene. The age of onset and the severity of the phenotype are roughly correlated with the size of the CTG expansion. Multiple methodologies can be used to diagnose affected individuals with DM1, including polymerase chain reaction, Southern blot, and triplet repeat-primed polymerase chain reaction. Recently, triplet repeat interruptions have been described, which may affect clinical outcomes of a fully-variable allele in DMPK. This document supersedes the Technical Standards and Guidelines for Myotonic Dystrophy originally published in 2009 and reaffirmed in 2015. It is designed for genetic testing professionals who are already familiar with the disease and the methods of analysis.

Approximating facial expression effects on diagnostic accuracy via generative AI in medical genetics.

Artificial intelligence (AI) is increasingly used in genomics research and practice, and generative AI has garnered significant recent attention. In clinical applications of generative AI, aspects of the underlying datasets can impact results, and confounders should be studied and mitigated. One example involves the facial expressions of people with genetic conditions. Stereotypically, Williams (WS) and Angelman (AS) syndromes are associated with a "happy" demeanor, including a smiling expression. Clinical geneticists may be more likely to identify these conditions in images of smiling individuals. To study the impact of facial expression, we analyzed publicly available facial images of approximately 3500 individuals with genetic conditions. Using a deep learning (DL) image classifier, we found that WS and AS images with non-smiling expressions had significantly lower prediction probabilities for the correct syndrome labels than those with smiling expressions. This was not seen for 22q11.2 deletion and Noonan syndromes, which are not associated with a smiling expression. To further explore the effect of facial expressions, we computationally altered the facial expressions for these images. We trained HyperStyle, a GAN-inversion technique compatible with StyleGAN2, to determine the vector representations of our images. Then, following the concept of InterfaceGAN, we edited these vectors to recreate the original images in a phenotypically accurate way but with a different facial expression. Through online surveys and an eye-tracking experiment, we examined how altered facial expressions affect the performance of human experts. We overall found that facial expression is associated with diagnostic accuracy variably in different genetic conditions.

Application of Genomic Medicine in Africa: 14th Conference of the African Society of Human Genetics and the 2nd International Congress of the Moroccan Society of Genomics and Human Genetics, Rabat, Morocco 2022.

The 14th African Society of Human Genetics (AfSHG) Morocco Meeting and 2nd International Congress of the Moroccan Society of Genomics and Human Genetics (SM2GH), held in Rabat, Morocco, from December 12 through 17, 2022, brought together 298 attendees from 23 countries, organized by the AfSHG in collaboration with the SM2GH. The conference's overarching theme was "Applications of Genomics Medicine in Africa," covering a wide range of topics, including population genetics, genetics of infectious diseases, hereditary disorders, cancer genetics, and translational genetics. The conference aimed to address the lag in the field of genetics in Africa and highlight the potential for genetic research and personalized medicine on the continent. The goal was to improve the health of African populations and global communities while nurturing the careers of young African scientists in the field. Distinguished scientists from around the world shared their recent findings in genetics, immunogenetics, genomics, genome editing, immunotherapy, and ethics genomics. Precongress activities included a 2-day bioinformatics workshop, "NGS Analysis for Monogenic Disease in African Populations," and a Young Investigators Forum, providing opportunities for young African researchers to showcase their work. The vast genetic diversity of the African continent poses a significant challenge in investigating and characterizing public health issues at the genetic and functional levels. Training, research, and the development of expertise in genetics, immunology, genomics, and bioinformatics are vital for addressing these challenges and advancing genetics in Africa. The AfSHG is committed to leading efforts to enhance genetic research, coordinate training, and foster research collaborations on the continent.

Laboratory testing for preconception/prenatal carrier screening: A technical standard of the American College of Medical Genetics and Genomics (ACMG).

Carrier screening has historically assessed a relatively small number of autosomal recessive and X-linked conditions selected based on frequency in a specific subpopulation and association with severe morbidity or mortality. Advances in genomic technologies enable simultaneous screening of individuals for several conditions. The American College of Medical Genetics and Genomics recently published a clinical practice resource that presents a framework when offering screening for autosomal recessive and X-linked conditions during pregnancy and preconception and recommends a tier-based approach when considering the number of conditions to screen for and their frequency within the US population in general. This laboratory technical standard aims to complement the practice resource and to put forth considerations for clinical laboratories and clinicians who offer preconception/prenatal carrier screening.

"Why did I choose genetics?": A survey of current and recent medical genetics and genomics residents provides insight into recruitment efforts.

There is a shortage of clinical geneticists, even with concerted recruitment efforts. Previously, no data had been collected about why young career geneticists chose this specialty. To investigate this question, we carried out a survey of current and recent medical genetics and genomics residents. The goal of this survey was to understand their reasons for pursuing medical genetics and genomics as a specialty. Results demonstrate that, for most, interest in genetics begins in medical school and was largely influenced by mentorship. This suggests that placing greater focus on introducing medical genetics as a clinical specialty and fostering robust mentorship of students in preclinical years may increase recruitment into medical genetics residencies.

Genebe.net: Implementation and validation of an automatic ACMG variant pathogenicity criteria assignment.

We present GeneBe, an online platform streamlining the automated application of American College of Medical Genetics and Genomics (ACMG), Association for Molecular Pathology (AMP), and the College of American Pathologists (CAP) criteria for assessment of pathogenicity of genetic variants. GeneBe utilizes automated algorithms that evaluate 17 criteria from 28, closely aligning with current guidelines and leveraging data from diverse sources, including ClinVar. The user-friendly web interface enables manual refinement of assignments for specific criteria based on site-collected data. Our algorithm demonstrates a high correlation (r = 0.90) of assigned pathogenicity scores compared to expert assessments from the ClinGen Evidence Repository and substantial concordance with ClinVar verdict assignments (κ = 0.69). Comparative analysis with other published tools reveals that GeneBe performs similarly to VarSome while being superior over TAPES and InterVar. In contrast to some other tools, GeneBe's web implementation is tracker-free and third-party request-free, safeguarding user privacy. Additionally, GeneBe offers an Application Programming Interface (API) for enhanced flexibility and integration into existing workflows and is provided free of charge for research purposes. GeneBe is available at https://genebe.net.

Genetics providers' perspectives on the use of digital tools in clinical practice.

PURPOSE: Digital tools are increasingly incorporated into genetics practice to address challenges with the current model of care. Yet, genetics providers' perspectives on digital tool use are not well characterized. METHODS: Genetics providers across Canada were recruited. Semistructured interviews were conducted to ascertain their perspectives on digital tool use and the clinical practice factors that might inform digital tool integration. A qualitative interpretive description approach was used for analysis. RESULTS: Thirty-three genetics providers across 5 provinces were interviewed. Participants had favorable attitudes toward digital tool use. They were open to using digital tools in the pretest phase of the genetic testing pathway and for some posttest tasks or in a hybrid model of care. Participants expressed that digital tools could enhance efficiency and allow providers to spend more time practicing at the top of scope. Providers also described the need for careful consideration of the potential impact of digitalization on the clinician-patient dynamic, access to and equity of care, and unintended digital burden on providers. CONCLUSION: Genetics providers considered digital tools to represent a viable solution for improving access, efficiency, and quality of care in genetics practice. Successful use of digital tools in practice will require careful consideration of their potential unintended impacts.

Genomic data in the All of Us Research Program.

Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics1-4. The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health5,6. Here we describe the programme's genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all.

Section E6.7-6.12 of the American College of Medical Genetics and Genomics (ACMG) Technical Laboratory Standards: Cytogenomic studies of acquired chromosomal abnormalities in solid tumors.

Clinical cytogenomic studies of solid tumor samples are critical to the diagnosis, prognostication, and treatment selection for cancer patients. An overview of current cytogenomic techniques for solid tumor analysis is provided, including standards for sample preparation, clinical and technical considerations, and documentation of results. With the evolving technologies and their application in solid tumor analysis, these standards now include sequencing technology and optical genome mapping, in addition to the conventional cytogenomic methods, such as G-banded chromosome analysis, fluorescence in situ hybridization, and chromosomal microarray analysis. This updated Section E6.7-6.12 supersedes the previous Section E6.5-6.8 in Section E: Clinical Cytogenetics of the American College of Medical Genetics and Genomics Standards for Clinical Genetics Laboratories.