2023 ASHG Lifetime Achievement Award: Neil Risch.

This article is based on the address given by the author for the 2023 meeting of The American Society of Human Genetics (ASHG) in Washington, D.C. A video of the original address can be found at the ASHG website.

2023 ASHG Leadership Award: Nancy Cox.

This article is based on the address given by the author at the 2023 meeting of the American Society of Human Genetics (ASHG) in Washington, D.C. The video of the original address can be found at the ASHG website.

2023 ASHG Leadership Award.

This article is based on the address given by the author at the 2023 meeting of The American Society of Human Genetics (ASHG). A video of the original address can be found at the ASHG website.

2023 ASHG presidential address-Reflecting on our 75 years: Acknowledging our past, embracing our present, and dreaming about our future.

This article is based on the address given by the author at the 2023 meeting of The American Society of Human Genetics (ASHG). A video of the original address can be found at the ASHG website.

2023 ASHG Scientific Achievement Award: Molly Przeworski.

This article is based on the address given by the author at the 2023 meeting of The American Society of Human Genetics (ASHG) in Washington, D.C. The video of the original address can be found at the ASHG website.

2023 ASHG Scientific Achievement Award.

This article is based on the address given by the author at the 2023 meeting of The American Society of Human Genetics (ASHG) in Washington, D.C. A video of the original address can be found at the ASHG website.

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.

Section E6.1-6.6 of the American College of Medical Genetics and Genomics (ACMG) Technical Laboratory Standards: Cytogenomic studies of acquired chromosomal abnormalities in neoplastic blood, bone marrow, and lymph nodes.

Cytogenomic analyses of acquired clonal chromosomal abnormalities in neoplastic blood, bone marrow, and/or lymph nodes are instrumental in the clinical management of patients with hematologic neoplasms. Cytogenetic analyses assist in the diagnosis of such disorders and can provide important prognostic information. Furthermore, cytogenetic studies can provide crucial information regarding specific genetically defined subtypes of these neoplasms that may have targeted therapies. At time of relapse, cytogenetic analysis can confirm recurrence of the original neoplasm, detect clonal disease evolution, or uncover a new unrelated neoplastic process. This section deals specifically with the technical standards applicable to cytogenomic studies of acquired clonal chromosomal abnormalities in neoplastic blood, bone marrow, and/or lymph nodes. This updated Section E6.1-6.6 supersedes the previous Section E6 in Section E: Clinical Cytogenetics of the American College of Medical Genetics and Genomics Technical Standards for Clinical Genetics Laboratories.

Elevated genetic risk for multiple sclerosis emerged in steppe pastoralist populations.

Multiple sclerosis (MS) is a neuro-inflammatory and neurodegenerative disease that is most prevalent in Northern Europe. Although it is known that inherited risk for MS is located within or in close proximity to immune-related genes, it is unknown when, where and how this genetic risk originated1. Here, by using a large ancient genome dataset from the Mesolithic period to the Bronze Age2, along with new Medieval and post-Medieval genomes, we show that the genetic risk for MS rose among pastoralists from the Pontic steppe and was brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the steppe population and later in Europe, probably driven by pathogenic challenges coinciding with changes in diet, lifestyle and population density. This study highlights the critical importance of the Neolithic period and Bronze Age as determinants of modern immune responses and their subsequent effect on the risk of developing MS in a changing environment.

Investigation on the construction of teaching case base in medical genetics.

Medical genetics is a basic medical course that discusses the diagnosis, prevention and treatment of diseases in relation with genetic factors. This course requires students who have abilities of strong logical thinking, independent thinking, problem analyzing and solving. Single "cramming" teaching is difficult to mobilize students' autonomous learning, and hardly achieves teaching effect of medical genetics. Teaching of case-based discussion breaks passive teaching mode in traditional class. The teacher throws out typically clinical cases. The students prepare materials around relevant problems of cases, and carry out class discussion. Then, key and difficult points of the course are integrated in teaching and learning interaction, which reaches a remarkable effect of teaching. Since 2013, the teaching and research group has carried out teaching of case-based discussion in undergraduates majoring in clinical medicine. In this paper, we screen and sort clinical cases on the basis of course teaching plan and case-based discussion in the teaching of medical genetics. The cases are summarized into 8 chapters in teaching case base, which basically cover the teaching of disease genetics and clinical genetics.The construction of teaching case base in medical genetics has realized the deep integration of clinical cases and teaching. Students can understand and master important and difficult points of teaching in a more intuitive way, which is helpful to stimulate students' innovative thinking, improve students' learning interest and class participation.

The landscape of genomic structural variation in Indigenous Australians.

Indigenous Australians harbour rich and unique genomic diversity. However, Aboriginal and Torres Strait Islander ancestries are historically under-represented in genomics research and almost completely missing from reference datasets1-3. Addressing this representation gap is critical, both to advance our understanding of global human genomic diversity and as a prerequisite for ensuring equitable outcomes in genomic medicine. Here we apply population-scale whole-genome long-read sequencing4 to profile genomic structural variation across four remote Indigenous communities. We uncover an abundance of large insertion-deletion variants (20-49 bp; n = 136,797), structural variants (50 b-50 kb; n = 159,912) and regions of variable copy number (>50 kb; n = 156). The majority of variants are composed of tandem repeat or interspersed mobile element sequences (up to 90%) and have not been previously annotated (up to 62%). A large fraction of structural variants appear to be exclusive to Indigenous Australians (12% lower-bound estimate) and most of these are found in only a single community, underscoring the need for broad and deep sampling to achieve a comprehensive catalogue of genomic structural variation across the Australian continent. Finally, we explore short tandem repeats throughout the genome to characterize allelic diversity at 50 known disease loci5, uncover hundreds of novel repeat expansion sites within protein-coding genes, and identify unique patterns of diversity and constraint among short tandem repeat sequences. Our study sheds new light on the dimensions and dynamics of genomic structural variation within and beyond Australia.

Indigenous Australian genomes show deep structure and rich novel variation.

The Indigenous peoples of Australia have a rich linguistic and cultural history. How this relates to genetic diversity remains largely unknown because of their limited engagement with genomic studies. Here we analyse the genomes of 159 individuals from four remote Indigenous communities, including people who speak a language (Tiwi) not from the most widespread family (Pama-Nyungan). This large collection of Indigenous Australian genomes was made possible by careful community engagement and consultation. We observe exceptionally strong population structure across Australia, driven by divergence times between communities of 26,000-35,000 years ago and long-term low but stable effective population sizes. This demographic history, including early divergence from Papua New Guinean (47,000 years ago) and Eurasian groups1, has generated the highest proportion of previously undescribed genetic variation seen outside Africa and the most extended homozygosity compared with global samples. A substantial proportion of this variation is not observed in global reference panels or clinical datasets, and variation with predicted functional consequence is more likely to be homozygous than in other populations, with consequent implications for medical genomics2. Our results show that Indigenous Australians are not a single homogeneous genetic group and their genetic relationship with the peoples of New Guinea is not uniform. These patterns imply that the full breadth of Indigenous Australian genetic diversity remains uncharacterized, potentially limiting genomic medicine and equitable healthcare for Indigenous Australians.

[The secrets of variants]. / Les secrets des variants - Chroniques génomiques.

Most sequence variants encountered in medical genetics are of unknown significance, and their interpretation is a major stumbling block. Building on the successful AlphaFold system, the DeepMind group at Google has built a tool that predicts the pathogenic potential of any substitution in the human proteome. This is a major achievement and will be an important asset in clinical genetics.

Mexican Biobank advances population and medical genomics of diverse ancestries.

Latin America continues to be severely underrepresented in genomics research, and fine-scale genetic histories and complex trait architectures remain hidden owing to insufficient data1. To fill this gap, the Mexican Biobank project genotyped 6,057 individuals from 898 rural and urban localities across all 32 states in Mexico at a resolution of 1.8 million genome-wide markers with linked complex trait and disease information creating a valuable nationwide genotype-phenotype database. Here, using ancestry deconvolution and inference of identity-by-descent segments, we inferred ancestral population sizes across Mesoamerican regions over time, unravelling Indigenous, colonial and postcolonial demographic dynamics2-6. We observed variation in runs of homozygosity among genomic regions with different ancestries reflecting distinct demographic histories and, in turn, different distributions of rare deleterious variants. We conducted genome-wide association studies (GWAS) for 22 complex traits and found that several traits are better predicted using the Mexican Biobank GWAS compared to the UK Biobank GWAS7,8. We identified genetic and environmental factors associating with trait variation, such as the length of the genome in runs of homozygosity as a predictor for body mass index, triglycerides, glucose and height. This study provides insights into the genetic histories of individuals in Mexico and dissects their complex trait architectures, both crucial for making precision and preventive medicine initiatives accessible worldwide.

Causal complexity in human research: On the shared challenges of behavior genetics, medical genetics, and environmentally oriented social science.

We received 23 spirited commentaries on our target article from across the disciplines of philosophy, economics, evolutionary genetics, molecular biology, criminology, epidemiology, and law. We organize our reply around three overarching questions: (1) What is a cause? (2) How are randomized controlled trials (RCTs) and within-family genome-wide association studies (GWASs) alike and unalike? (3) Is behavior genetics a qualitatively different enterprise? Throughout our discussion of these questions, we advocate for the idea that behavior genetics shares many of the same pitfalls and promises as environmentally oriented research, medical genetics, and other arenas of the social and behavioral sciences.

Artificial intelligence and the impact on medical genetics.

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.