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Building evidence and measuring clinical outcomes for genomic medicine.
Peterson JF, Roden DM, Orlando LA, Ramirez AH, Mensah GA, Williams MS
(2019) Lancet 394: 604-610
MeSH Terms: Diagnostic Tests, Routine, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing, Humans, Patient Outcome Assessment, Precision Medicine, Standard of Care
Show Abstract · Added March 24, 2020
Human genomic sequencing has potential diagnostic, prognostic, and therapeutic value across a wide breadth of clinical disciplines. One barrier to widespread adoption is the paucity of evidence for improved outcomes in patients who do not already have an indication for more focused testing. In this Series paper, we review clinical outcome studies in genomic medicine and discuss the important features and key challenges to building evidence for next generation sequencing in the context of routine patient care.
Copyright © 2019 Elsevier Ltd. All rights reserved.
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Genomic medicine for undiagnosed diseases.
Wise AL, Manolio TA, Mensah GA, Peterson JF, Roden DM, Tamburro C, Williams MS, Green ED
(2019) Lancet 394: 533-540
MeSH Terms: Adult, Child, Early Diagnosis, Genomics, Humans, Phenotype, Prenatal Diagnosis, Rare Diseases, Sequence Analysis, DNA, Whole Exome Sequencing, Whole Genome Sequencing
Show Abstract · Added March 24, 2020
One of the primary goals of genomic medicine is to improve diagnosis through identification of genomic conditions, which could improve clinical management, prevent complications, and promote health. We explore how genomic medicine is being used to obtain molecular diagnoses for patients with previously undiagnosed diseases in prenatal, paediatric, and adult clinical settings. We focus on the role of clinical genomic sequencing (exome and genome) in aiding patients with conditions that are undiagnosed even after extensive clinical evaluation and testing. In particular, we explore the impact of combining genomic and phenotypic data and integrating multiple data types to improve diagnoses for patients with undiagnosed diseases, and we discuss how these genomic sequencing diagnoses could change clinical management.
Copyright © 2019 Elsevier Ltd. All rights reserved.
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Genome-wide enhancer annotations differ significantly in genomic distribution, evolution, and function.
Benton ML, Talipineni SC, Kostka D, Capra JA
(2019) BMC Genomics 20: 511
MeSH Terms: Cell Line, Databases, Genetic, Enhancer Elements, Genetic, Evolution, Molecular, Gene Expression Regulation, Genomics, Humans, Liver, Molecular Sequence Annotation, Myocardium
Show Abstract · Added March 3, 2020
BACKGROUND - Non-coding gene regulatory enhancers are essential to transcription in mammalian cells. As a result, a large variety of experimental and computational strategies have been developed to identify cis-regulatory enhancer sequences. Given the differences in the biological signals assayed, some variation in the enhancers identified by different methods is expected; however, the concordance of enhancers identified by different methods has not been comprehensively evaluated. This is critically needed, since in practice, most studies consider enhancers identified by only a single method. Here, we compare enhancer sets from eleven representative strategies in four biological contexts.
RESULTS - All sets we evaluated overlap significantly more than expected by chance; however, there is significant dissimilarity in their genomic, evolutionary, and functional characteristics, both at the element and base-pair level, within each context. The disagreement is sufficient to influence interpretation of candidate SNPs from GWAS studies, and to lead to disparate conclusions about enhancer and disease mechanisms. Most regions identified as enhancers are supported by only one method, and we find limited evidence that regions identified by multiple methods are better candidates than those identified by a single method. As a result, we cannot recommend the use of any single enhancer identification strategy in all settings.
CONCLUSIONS - Our results highlight the inherent complexity of enhancer biology and identify an important challenge to mapping the genetic architecture of complex disease. Greater appreciation of how the diverse enhancer identification strategies in use today relate to the dynamic activity of gene regulatory regions is needed to enable robust and reproducible results.
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Signatures of Recent Positive Selection in Enhancers Across 41 Human Tissues.
Moon JM, Capra JA, Abbot P, Rokas A
(2019) G3 (Bethesda) 9: 2761-2774
MeSH Terms: DNA Transposable Elements, Databases, Genetic, Enhancer Elements, Genetic, Evolution, Molecular, Genome-Wide Association Study, Genomics, Humans, Immunity, Organ Specificity, Quantitative Trait, Heritable, Selection, Genetic
Show Abstract · Added March 3, 2020
Evolutionary changes in enhancers are widely associated with variation in human traits and diseases. However, studies comprehensively quantifying levels of selection on enhancers at multiple evolutionary periods during recent human evolution and how enhancer evolution varies across human tissues are lacking. To address these questions, we integrated a dataset of 41,561 transcribed enhancers active in 41 different human tissues (FANTOM Consortium) with whole genome sequences of 1,668 individuals from the African, Asian, and European populations (1000 Genomes Project). Our analyses based on four different metrics (Tajima's , , H12, ) showed that ∼5.90% of enhancers showed evidence of recent positive selection and that genes associated with enhancers under very recent positive selection are enriched for diverse immune-related functions. The distributions of these metrics for brain and testis enhancers were often statistically significantly different and in the direction suggestive of less positive selection compared to those of other tissues; the same was true for brain and testis enhancers that are tissue-specific compared to those that are tissue-broad and for testis enhancers associated with tissue-enriched and non-tissue-enriched genes. These differences varied considerably across metrics and tissues and were generally in the form of changes in distributions' shapes rather than shifts in their values. Collectively, these results suggest that many human enhancers experienced recent positive selection throughout multiple time periods in human evolutionary history, that this selection occurred in a tissue-dependent and immune-related functional context, and that much like the evolution of their protein-coding gene counterparts, the evolution of brain and testis enhancers has been markedly different from that of enhancers in other tissues.
Copyright © 2019 Moon et al.
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My Cousin Also Has Atrial Fibrillation: Family Relationships in a Genomic Era.
Roden DM, Below JE
(2019) JACC Clin Electrophysiol 5: 501-503
MeSH Terms: Atrial Fibrillation, Family Relations, Fibrosis, Genomics, Humans
Added March 24, 2020
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Zinc intoxication induces ferroptosis in A549 human lung cells.
Palmer LD, Jordan AT, Maloney KN, Farrow MA, Gutierrez DB, Gant-Branum R, Burns WJ, Romer CE, Tsui T, Allen JL, Beavers WN, Nei YW, Sherrod SD, Lacy DB, Norris JL, McLean JA, Caprioli RM, Skaar EP
(2019) Metallomics 11: 982-993
MeSH Terms: A549 Cells, Apoptosis, Cell Survival, Ferroptosis, Genomics, Humans, Lung, NAD, Necrosis, Protein Binding, Time Factors, Zinc
Show Abstract · Added August 7, 2019
Zinc (Zn) is an essential trace metal required for all forms of life, but is toxic at high concentrations. While the toxic effects of high levels of Zn are well documented, the mechanism of cell death appears to vary based on the study and concentration of Zn. Zn has been proposed as an anti-cancer treatment against non-small cell lung cancer (NSCLC). The goal of this analysis was to determine the effects of Zn on metabolism and cell death in A549 cells. Here, high throughput multi-omics analysis identified the molecular effects of Zn intoxication on the proteome, metabolome, and transcriptome of A549 human NSCLC cells after 5 min to 24 h of Zn exposure. Multi-omics analysis combined with additional experimental evidence suggests Zn intoxication induces ferroptosis, an iron and lipid peroxidation-dependent programmed cell death, demonstrating the utility of multi-omics analysis to identify cellular response to intoxicants.
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Genome-wide maps of distal gene regulatory enhancers active in the human placenta.
Zhang J, Simonti CN, Capra JA
(2018) PLoS One 13: e0209611
MeSH Terms: Chromosome Mapping, Computational Biology, Enhancer Elements, Genetic, Female, Genes, Regulator, Genome-Wide Association Study, Genomics, Humans, Machine Learning, Molecular Sequence Annotation, Placenta, Pregnancy, ROC Curve
Show Abstract · Added March 3, 2020
Placental dysfunction is implicated in many pregnancy complications, including preeclampsia and preterm birth (PTB). While both these syndromes are influenced by environmental risk factors, they also have a substantial genetic component that is not well understood. Precisely controlled gene expression during development is crucial to proper placental function and often mediated through gene regulatory enhancers. However, we lack accurate maps of placental enhancer activity due to the challenges of assaying the placenta and the difficulty of comprehensively identifying enhancers. To address the gap in our knowledge of gene regulatory elements in the placenta, we used a two-step machine learning pipeline to synthesize existing functional genomics studies, transcription factor (TF) binding patterns, and evolutionary information to predict placental enhancers. The trained classifiers accurately distinguish enhancers from the genomic background and placental enhancers from enhancers active in other tissues. Genomic features collected from tissues and cell lines involved in pregnancy are the most predictive of placental regulatory activity. Applying the classifiers genome-wide enabled us to create a map of 33,010 predicted placental enhancers, including 4,562 high-confidence enhancer predictions. The genome-wide placental enhancers are significantly enriched nearby genes associated with placental development and birth disorders and for SNPs associated with gestational age. These genome-wide predicted placental enhancers provide candidate regions for further testing in vitro, will assist in guiding future studies of genetic associations with pregnancy phenotypes, and aid interpretation of potential mechanisms of action for variants found through genetic studies.
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integRATE: a desirability-based data integration framework for the prioritization of candidate genes across heterogeneous omics and its application to preterm birth.
Eidem HR, Steenwyk JL, Wisecaver JH, Capra JA, Abbot P, Rokas A
(2018) BMC Med Genomics 11: 107
MeSH Terms: Genome-Wide Association Study, Genomics, Humans, Polymorphism, Single Nucleotide, Premature Birth, Proteomics, Trans-Activators, User-Computer Interface
Show Abstract · Added March 3, 2020
BACKGROUND - The integration of high-quality, genome-wide analyses offers a robust approach to elucidating genetic factors involved in complex human diseases. Even though several methods exist to integrate heterogeneous omics data, most biologists still manually select candidate genes by examining the intersection of lists of candidates stemming from analyses of different types of omics data that have been generated by imposing hard (strict) thresholds on quantitative variables, such as P-values and fold changes, increasing the chance of missing potentially important candidates.
METHODS - To better facilitate the unbiased integration of heterogeneous omics data collected from diverse platforms and samples, we propose a desirability function framework for identifying candidate genes with strong evidence across data types as targets for follow-up functional analysis. Our approach is targeted towards disease systems with sparse, heterogeneous omics data, so we tested it on one such pathology: spontaneous preterm birth (sPTB).
RESULTS - We developed the software integRATE, which uses desirability functions to rank genes both within and across studies, identifying well-supported candidate genes according to the cumulative weight of biological evidence rather than based on imposition of hard thresholds of key variables. Integrating 10 sPTB omics studies identified both genes in pathways previously suspected to be involved in sPTB as well as novel genes never before linked to this syndrome. integRATE is available as an R package on GitHub ( https://github.com/haleyeidem/integRATE ).
CONCLUSIONS - Desirability-based data integration is a solution most applicable in biological research areas where omics data is especially heterogeneous and sparse, allowing for the prioritization of candidate genes that can be used to inform more targeted downstream functional analyses.
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Prediction of gene regulatory enhancers across species reveals evolutionarily conserved sequence properties.
Chen L, Fish AE, Capra JA
(2018) PLoS Comput Biol 14: e1006484
MeSH Terms: Animals, Conserved Sequence, Enhancer Elements, Genetic, Evolution, Molecular, Genomics, Humans, Machine Learning, Mammals, Neural Networks, Computer, Sequence Alignment, Sequence Analysis, DNA, Support Vector Machine
Show Abstract · Added March 3, 2020
Genomic regions with gene regulatory enhancer activity turnover rapidly across mammals. In contrast, gene expression patterns and transcription factor binding preferences are largely conserved between mammalian species. Based on this conservation, we hypothesized that enhancers active in different mammals would exhibit conserved sequence patterns in spite of their different genomic locations. To investigate this hypothesis, we evaluated the extent to which sequence patterns that are predictive of enhancers in one species are predictive of enhancers in other mammalian species by training and testing two types of machine learning models. We trained support vector machine (SVM) and convolutional neural network (CNN) classifiers to distinguish enhancers defined by histone marks from the genomic background based on DNA sequence patterns in human, macaque, mouse, dog, cow, and opossum. The classifiers accurately identified many adult liver, developing limb, and developing brain enhancers, and the CNNs outperformed the SVMs. Furthermore, classifiers trained in one species and tested in another performed nearly as well as classifiers trained and tested on the same species. We observed similar cross-species conservation when applying the models to human and mouse enhancers validated in transgenic assays. This indicates that many short sequence patterns predictive of enhancers are largely conserved. The sequence patterns most predictive of enhancers in each species matched the binding motifs for a common set of TFs enriched for expression in relevant tissues, supporting the biological relevance of the learned features. Thus, despite the rapid change of active enhancer locations between mammals, cross-species enhancer prediction is often possible. Our results suggest that short sequence patterns encoding enhancer activity have been maintained across more than 180 million years of mammalian evolution.
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Bid maintains mitochondrial cristae structure and function and protects against cardiac disease in an integrative genomics study.
Salisbury-Ruf CT, Bertram CC, Vergeade A, Lark DS, Shi Q, Heberling ML, Fortune NL, Okoye GD, Jerome WG, Wells QS, Fessel J, Moslehi J, Chen H, Roberts LJ, Boutaud O, Gamazon ER, Zinkel SS
(2018) Elife 7:
MeSH Terms: Animals, Apoptosis, BH3 Interacting Domain Death Agonist Protein, Beclin-1, Cell Respiration, Fibrosis, Gene Expression Regulation, Genome-Wide Association Study, Genomics, Heart Diseases, Heart Ventricles, Humans, Mice, Inbred C57BL, Mitochondria, Mitochondrial Proton-Translocating ATPases, Mutation, Myeloid Progenitor Cells, Myocardial Infarction, Myocytes, Cardiac, Polymorphism, Single Nucleotide, Protein Multimerization, Protein Structure, Secondary, Protein Subunits, Reactive Oxygen Species, Reproducibility of Results, Up-Regulation
Show Abstract · Added December 11, 2018
Bcl-2 family proteins reorganize mitochondrial membranes during apoptosis, to form pores and rearrange cristae. In vitro and in vivo analysis integrated with human genetics reveals a novel homeostatic mitochondrial function for Bcl-2 family protein Bid. Loss of full-length Bid results in apoptosis-independent, irregular cristae with decreased respiration. mice display stress-induced myocardial dysfunction and damage. A gene-based approach applied to a biobank, validated in two independent GWAS studies, reveals that decreased genetically determined BID expression associates with myocardial infarction (MI) susceptibility. Patients in the bottom 5% of the expression distribution exhibit >4 fold increased MI risk. Carrier status with nonsynonymous variation in Bid's membrane binding domain, Bid, associates with MI predisposition. Furthermore, Bid but not Bid associates with Mcl-1, previously implicated in cristae stability; decreased MCL-1 expression associates with MI. Our results identify a role for Bid in homeostatic mitochondrial cristae reorganization, that we link to human cardiac disease.
© 2018, Salisbury-Ruf et al.
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26 MeSH Terms