Annual Review of Biomedical Data Science最新文献_第3页

Importance of Diversity in Precision Medicine: Generalizability of Genetic Associations Across Ancestry Groups Toward Better Identification of Disease Susceptibility Variants. 多样性在精准医学中的重要性:跨祖先群体遗传关联的普遍性，有助于更好地识别疾病易感性变异。

IF 6

Annual Review of Biomedical Data Science Pub Date : 2023-08-10 Epub Date: 2023-05-17 DOI: 10.1146/annurev-biodatasci-122220-113250

Lauren A Cruz, Jessica N Cooke Bailey, Dana C Crawford

{"title":"Importance of Diversity in Precision Medicine: Generalizability of Genetic Associations Across Ancestry Groups Toward Better Identification of Disease Susceptibility Variants.","authors":"Lauren A Cruz, Jessica N Cooke Bailey, Dana C Crawford","doi":"10.1146/annurev-biodatasci-122220-113250","DOIUrl":"10.1146/annurev-biodatasci-122220-113250","url":null,"abstract":"Genome-wide association studies (GWAS) revolutionized our understanding of common genetic variation and its impact on common human disease and traits. Developed and adopted in the mid-2000s, GWAS led to searchable genotype-phenotype catalogs and genome-wide datasets available for further data mining and analysis for the eventual development of translational applications. The GWAS revolution was swift and specific, including almost exclusively populations of European descent, to the neglect of the majority of the world's genetic diversity. In this narrative review, we recount the GWAS landscape of the early years that established a genotype-phenotype catalog that is now universally understood to be inadequate for a complete understanding of complex human genetics. We then describe approaches taken to augment the genotype-phenotype catalog, including the study populations, collaborative consortia, and study design approaches aimed to generalize and then ultimately discover genome-wide associations in non-European descent populations. The collaborations and data resources established in the efforts to diversify genomic findings undoubtedly provide the foundations of the next chapters of genetic association studies with the advent of budget-friendly whole-genome sequencing.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"6 ","pages":"339-356"},"PeriodicalIF":6.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10720270/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9960536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Human Microbiomes and Disease for the Biomedical Data Scientist. 生物医学数据科学家的人类微生物组和疾病。

IF 6

Annual Review of Biomedical Data Science Pub Date : 2023-08-10 DOI: 10.1146/annurev-biodatasci-020722-043017

Jonathan L Golob

引用次数: 0

Human Genomics of COVID-19 Pneumonia: Contributions of Rare and Common Variants. COVID-19 肺炎的人类基因组学：罕见和常见变异的贡献

IF 7

Annual Review of Biomedical Data Science Pub Date : 2023-08-10 Epub Date: 2023-05-17 DOI: 10.1146/annurev-biodatasci-020222-021705

Aurélie Cobat, Qian Zhang, Laurent Abel, Jean-Laurent Casanova, Jacques Fellay

{"title":"Human Genomics of COVID-19 Pneumonia: Contributions of Rare and Common Variants.","authors":"Aurélie Cobat, Qian Zhang, Laurent Abel, Jean-Laurent Casanova, Jacques Fellay","doi":"10.1146/annurev-biodatasci-020222-021705","DOIUrl":"10.1146/annurev-biodatasci-020222-021705","url":null,"abstract":"SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection is silent or benign in most infected individuals, but causes hypoxemic COVID-19 pneumonia in about 10% of cases. We review studies of the human genetics of life-threatening COVID-19 pneumonia, focusing on both rare and common variants. Large-scale genome-wide association studies have identified more than 20 common loci robustly associated with COVID-19 pneumonia with modest effect sizes, some implicating genes expressed in the lungs or leukocytes. The most robust association, on chromosome 3, concerns a haplotype inherited from Neanderthals. Sequencing studies focusing on rare variants with a strong effect have been particularly successful, identifying inborn errors of type I interferon (IFN) immunity in 1-5% of unvaccinated patients with critical pneumonia, and their autoimmune phenocopy, autoantibodies against type I IFN, in another 15-20% of cases. Our growing understanding of the impact of human genetic variation on immunity to SARS-CoV-2 is enabling health systems to improve protection for individuals and populations.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"6 ","pages":"465-486"},"PeriodicalIF":7.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10879986/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9960534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Single-Cell RNA Sequencing for Studying Human Cancers. 单细胞RNA测序用于研究人类癌症。

IF 6

Annual Review of Biomedical Data Science Pub Date : 2023-08-10 DOI: 10.1146/annurev-biodatasci-020722-091857

Dvir Aran

引用次数: 1

Challenges and Opportunities for Data Science in Women's Health. 妇女健康数据科学的挑战与机遇。

IF 7

Annual Review of Biomedical Data Science Pub Date : 2023-08-10 Epub Date: 2023-04-11 DOI: 10.1146/annurev-biodatasci-020722-105958

Todd L Edwards, Catherine A Greene, Jacqueline A Piekos, Jacklyn N Hellwege, Gabrielle Hampton, Elizabeth A Jasper, Digna R Velez Edwards

引用次数: 0

An Overview of Deep Generative Models in Functional and Evolutionary Genomics. 功能和进化基因组学中的深度生成模型概述。

IF 6

Annual Review of Biomedical Data Science Pub Date : 2023-08-10 Epub Date: 2023-05-03 DOI: 10.1146/annurev-biodatasci-020722-115651

Burak Yelmen, Flora Jay

引用次数: 0

Combining Molecular and Radiomic Features for Risk Assessment in Breast Cancer. 结合分子和放射学特征评估乳腺癌的风险。

IF 6

Annual Review of Biomedical Data Science Pub Date : 2023-08-10 DOI: 10.1146/annurev-biodatasci-020722-092748

Alex A Nguyen, Anne Marie McCarthy, Despina Kontos

{"title":"Combining Molecular and Radiomic Features for Risk Assessment in Breast Cancer.","authors":"Alex A Nguyen, Anne Marie McCarthy, Despina Kontos","doi":"10.1146/annurev-biodatasci-020722-092748","DOIUrl":"https://doi.org/10.1146/annurev-biodatasci-020722-092748","url":null,"abstract":"Breast cancer risk is highly variable within the population and current research is leading the shift toward personalized medicine. By accurately assessing an individual woman's risk, we can reduce the risk of over/undertreatment by preventing unnecessary procedures or by elevating screening procedures. Breast density measured from conventional mammography has been established as one of the most dominant risk factors for breast cancer; however, it is currently limited by its ability to characterize more complex breast parenchymal patterns that have been shown to provide additional information to strengthen cancer risk models. Molecular factors ranging from high penetrance, or high likelihood that a mutation will show signs and symptoms of the disease, to combinations of gene mutations with low penetrance have shown promise for augmenting risk assessment. Although imaging biomarkers and molecular biomarkers have both individually demonstrated improved performance in risk assessment, few studies have evaluated them together. This review aims to highlight the current state of the art in breast cancer risk assessment using imaging and genetic biomarkers.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"6 ","pages":"299-311"},"PeriodicalIF":6.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9967073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Challenges and Progress in Designing Broad-Spectrum Vaccines Against Rapidly Mutating Viruses. 针对快速变异病毒设计广谱疫苗的挑战与进展。

IF 6

Annual Review of Biomedical Data Science Pub Date : 2023-08-10 DOI: 10.1146/annurev-biodatasci-020722-041304

Rishi Bedi, Nicholas L Bayless, Jacob Glanville

{"title":"Challenges and Progress in Designing Broad-Spectrum Vaccines Against Rapidly Mutating Viruses.","authors":"Rishi Bedi, Nicholas L Bayless, Jacob Glanville","doi":"10.1146/annurev-biodatasci-020722-041304","DOIUrl":"https://doi.org/10.1146/annurev-biodatasci-020722-041304","url":null,"abstract":"Viruses evolve to evade prior immunity, causing significant disease burden. Vaccine effectiveness deteriorates as pathogens mutate, requiring redesign. This is a problem that has grown worse due to population increase, global travel, and farming practices. Thus, there is significant interest in developing broad-spectrum vaccines that mitigate disease severity and ideally inhibit disease transmission without requiring frequent updates. Even in cases where vaccines against rapidly mutating pathogens have been somewhat effective, such as seasonal influenza and SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), designing vaccines that provide broad-spectrum immunity against routinely observed viral variation remains a desirable but not yet achieved goal. This review highlights the key theoretical advances in understanding the interplay between polymorphism and vaccine efficacy, challenges in designing broad-spectrum vaccines, and technology advances and possible avenues forward. We also discuss data-driven approaches for monitoring vaccine efficacy and predicting viral escape from vaccine-induced protection. In each case, we consider illustrative examples in vaccine development from influenza, SARS-CoV-2, and HIV (human immunodeficiency virus)-three examples of highly prevalent rapidly mutating viruses with distinct phylogenetics and unique histories of vaccine technology development.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"6 ","pages":"419-441"},"PeriodicalIF":6.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9960533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toward Identification of Functional Sequences and Variants in Noncoding DNA. 非编码DNA功能序列和变异的鉴定。

IF 6

Annual Review of Biomedical Data Science Pub Date : 2023-08-10 DOI: 10.1146/annurev-biodatasci-122120-110102

Remo Monti, Uwe Ohler

引用次数: 0

A Review of and Roadmap for Data Science and Machine Learning for the Neuropsychiatric Phenotype of Autism. 自闭症神经精神表型的数据科学和机器学习综述和路线图。

IF 7

Annual Review of Biomedical Data Science Pub Date : 2023-08-10 Epub Date: 2023-05-03 DOI: 10.1146/annurev-biodatasci-020722-125454

Peter Washington, Dennis P Wall

{"title":"A Review of and Roadmap for Data Science and Machine Learning for the Neuropsychiatric Phenotype of Autism.","authors":"Peter Washington, Dennis P Wall","doi":"10.1146/annurev-biodatasci-020722-125454","DOIUrl":"10.1146/annurev-biodatasci-020722-125454","url":null,"abstract":"Autism spectrum disorder (autism) is a neurodevelopmental delay that affects at least 1 in 44 children. Like many neurological disorder phenotypes, the diagnostic features are observable, can be tracked over time, and can be managed or even eliminated through proper therapy and treatments. However, there are major bottlenecks in the diagnostic, therapeutic, and longitudinal tracking pipelines for autism and related neurodevelopmental delays, creating an opportunity for novel data science solutions to augment and transform existing workflows and provide increased access to services for affected families. Several efforts previously conducted by a multitude of research labs have spawned great progress toward improved digital diagnostics and digital therapies for children with autism. We review the literature on digital health methods for autism behavior quantification and beneficial therapies using data science. We describe both case-control studies and classification systems for digital phenotyping. We then discuss digital diagnostics and therapeutics that integrate machine learning models of autism-related behaviors, including the factors that must be addressed for translational use. Finally, we describe ongoing challenges and potential opportunities for the field of autism data science. Given the heterogeneous nature of autism and the complexities of the relevant behaviors, this review contains insights that are relevant to neurological behavior analysis and digital psychiatry more broadly.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":"6 ","pages":"211-228"},"PeriodicalIF":7.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11093217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9960498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0