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Pulmonology 2020Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous and multisystemic disease with progressive increasing morbidity and mortality. COPD is now widely... (Review)
Review
Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous and multisystemic disease with progressive increasing morbidity and mortality. COPD is now widely accepted as a heterogeneous condition with multiple phenotypes and endotypes. This review will discuss the old and new concepts for the different types of COPD phenotypes, as well as the inclusion of them in current guidelines. Phenotypical approach to COPD is having huge impact on everyday practice and changed nonpharmacological and pharmacological management of COPD in last decade. However, phenotypical approach is small step to precision medicine in COPD management in the absence of big, specific and well-designed COPD trials with exact identification of phenotypes for more personalization of the treatment of COPD.
Topics: Humans; Phenotype; Practice Guidelines as Topic; Precision Medicine; Pulmonary Disease, Chronic Obstructive
PubMed: 31740261
DOI: 10.1016/j.pulmoe.2019.10.006 -
Circulation Research Apr 2018Precision medicine is an integrative approach to cardiovascular disease prevention and treatment that considers an individual's genetics, lifestyle, and exposures as... (Review)
Review
Precision medicine is an integrative approach to cardiovascular disease prevention and treatment that considers an individual's genetics, lifestyle, and exposures as determinants of their cardiovascular health and disease phenotypes. This focus overcomes the limitations of reductionism in medicine, which presumes that all patients with the same signs of disease share a common pathophenotype and, therefore, should be treated similarly. Precision medicine incorporates standard clinical and health record data with advanced panomics (ie, transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics) for deep phenotyping. These phenotypic data can then be analyzed within the framework of molecular interaction (interactome) networks to uncover previously unrecognized disease phenotypes and relationships between diseases, and to select pharmacotherapeutics or identify potential protein-drug or drug-drug interactions. In this review, we discuss the current spectrum of cardiovascular health and disease, population averages and the response of extreme phenotypes to interventions, and population-based versus high-risk treatment strategies as a pretext to understanding a precision medicine approach to cardiovascular disease prevention and therapeutic interventions. We also consider the search for resilience and Mendelian disease genes and argue against the theory of a single causal gene/gene product as a mediator of the cardiovascular disease phenotype, as well as an Erlichian magic bullet to solve cardiovascular disease. Finally, we detail the importance of deep phenotyping and interactome networks and the use of this information for rational polypharmacy. These topics highlight the urgent need for precise phenotyping to advance precision medicine as a strategy to improve cardiovascular health and prevent disease.
Topics: Cardiovascular Agents; Cardiovascular Diseases; Computational Biology; Demography; Drug Discovery; Forecasting; Gene-Environment Interaction; Genetic Association Studies; Genetic Diseases, Inborn; Genetic Variation; Humans; Mutation; Pharmacogenetics; Phenotype; Precision Medicine
PubMed: 29700074
DOI: 10.1161/CIRCRESAHA.117.310782 -
Journal of Clinical Immunology Jan 2020Since 2013, the International Union of Immunological Societies (IUIS) expert committee (EC) on Inborn Errors of Immunity (IEI) has published an updated phenotypic...
Since 2013, the International Union of Immunological Societies (IUIS) expert committee (EC) on Inborn Errors of Immunity (IEI) has published an updated phenotypic classification of IEI, which accompanies and complements their genotypic classification into ten tables. This phenotypic classification is user-friendly and serves as a resource for clinicians at the bedside. There are now 430 single-gene IEI underlying phenotypes as diverse as infection, malignancy, allergy, autoimmunity, and autoinflammation. We herein report the 2019 phenotypic classification, including the 65 new conditions. The diagnostic algorithms are based on clinical and laboratory phenotypes for each of the ten broad categories of IEI.
Topics: Autoimmunity; Genotype; Hereditary Autoinflammatory Diseases; Humans; Hypersensitivity; Immunity; Immunologic Deficiency Syndromes; Phenotype
PubMed: 32048120
DOI: 10.1007/s10875-020-00758-x -
Sleep Medicine Reviews Oct 2017Obstructive sleep apnea (OSA) is a complex and heterogeneous disorder and the apnea hypopnea index alone can not capture the diverse spectrum of the condition. Enhanced... (Review)
Review
Obstructive sleep apnea (OSA) is a complex and heterogeneous disorder and the apnea hypopnea index alone can not capture the diverse spectrum of the condition. Enhanced phenotyping can improve prognostication, patient selection for clinical trials, understanding of mechanisms, and personalized treatments. In OSA, multiple condition characteristics have been termed "phenotypes." To help classify patients into relevant prognostic and therapeutic categories, an OSA phenotype can be operationally defined as: "A category of patients with OSA distinguished from others by a single or combination of disease features, in relation to clinically meaningful attributes (symptoms, response to therapy, health outcomes, quality of life)." We review approaches to clinical phenotyping in OSA, citing examples of increasing analytic complexity. Although clinical feature based OSA phenotypes with significant prognostic and treatment implications have been identified (e.g., excessive daytime sleepiness OSA), many current categorizations lack association with meaningful outcomes. Recent work focused on pathophysiologic risk factors for OSA (e.g., arousal threshold, craniofacial morphology, chemoreflex sensitivity) appears to capture heterogeneity in OSA, but requires clinical validation. Lastly, we discuss the use of machine learning as a promising phenotyping strategy that can integrate multiple types of data (genomic, molecular, cellular, clinical) to identify unique, meaningful OSA phenotypes.
Topics: Humans; Phenotype; Sleep Apnea, Obstructive; Sleep, REM
PubMed: 27815038
DOI: 10.1016/j.smrv.2016.10.002 -
Nucleic Acids Research Jan 2018ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease,...
ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease, maintained at the National Institutes of Health. Interpretations of the clinical significance of variants are submitted by clinical testing laboratories, research laboratories, expert panels and other groups. ClinVar aggregates data by variant-disease pairs, and by variant (or set of variants). Data aggregated by variant are accessible on the website, in an improved set of variant call format files and as a new comprehensive XML report. ClinVar recently started accepting submissions that are focused primarily on providing phenotypic information for individuals who have had genetic testing. Submissions may come from clinical providers providing their own interpretation of the variant ('provider interpretation') or from groups such as patient registries that primarily provide phenotypic information from patients ('phenotyping only'). ClinVar continues to make improvements to its search and retrieval functions. Several new fields are now indexed for more precise searching, and filters allow the user to narrow down a large set of search results.
Topics: Databases, Nucleic Acid; Disease; Genetic Variation; Humans; Phenotype
PubMed: 29165669
DOI: 10.1093/nar/gkx1153 -
Journal of Clinical Immunology Jan 2018Since the 1990s, the International Union of Immunological Societies (IUIS) PID expert committee (EC), now called Inborn Errors of Immunity Committee, has published every...
Since the 1990s, the International Union of Immunological Societies (IUIS) PID expert committee (EC), now called Inborn Errors of Immunity Committee, has published every other year a classification of the inborn errors of immunity. This complete catalog serves as a reference for immunologists and researchers worldwide. However, it was unadapted for clinicians at the bedside. For those, the IUIS PID EC is now publishing a phenotypical classification since 2013, which proved to be more user-friendly. There are now 320 single-gene inborn errors of immunity underlying phenotypes as diverse as infection, malignancy, allergy, auto-immunity, and auto-inflammation. We herein propose the revised 2017 phenotypic classification, based on the accompanying 2017 IUIS Inborn Errors of Immunity Committee classification.
Topics: Allergy and Immunology; Humans; Immunity; Immunologic Deficiency Syndromes; International Cooperation; Phenotype
PubMed: 29226301
DOI: 10.1007/s10875-017-0465-8 -
Handbook of Clinical Neurology 2018Essential tremor (ET) is one of the most common neurologic disorders, and genetic factors are thought to contribute significantly to disease etiology. There has been a... (Review)
Review
Essential tremor (ET) is one of the most common neurologic disorders, and genetic factors are thought to contribute significantly to disease etiology. There has been a relative lack of progress in understanding the genetic etiology of ET. This could reflect a number of factors, including the presence of substantial phenotypic and genotypic heterogeneity. Thus, a meticulous approach to phenotyping is important for genetic research. A lack of standardized phenotyping across studies and patient centers likely has contributed to the relative lack of success of genomewide association studies in ET. To dissect the genetic architecture of ET, whole-genome sequencing will likely be of value. This will allow specific hypotheses about the mode of inheritance and genetic architecture to be tested. A number of approaches still remain unexplored in ET genetics, including the contribution of copy number variants, uncommon moderate-effect alleles, rare variant large-effect alleles (including Mendelian and complex/polygenic modes of inheritance), de novo and gonadal mosaicism, epigenetic changes, and noncoding variation.
Topics: Essential Tremor; Gene-Environment Interaction; Genetic Predisposition to Disease; Genotype; Humans; Phenotype
PubMed: 29325613
DOI: 10.1016/B978-0-444-63233-3.00015-4 -
Plant Biotechnology Journal Jul 2020Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are... (Review)
Review
Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.
Topics: Breeding; Genome-Wide Association Study; Genomics; Genotype; Phenotype; Polymorphism, Single Nucleotide
PubMed: 32163658
DOI: 10.1111/pbi.13372 -
Trends in Ecology & Evolution Jan 2020Genetically identical individuals can be phenotypically variable, even in constant environmental conditions. The ubiquity of this phenomenon, known as 'intra-genotypic... (Review)
Review
Genetically identical individuals can be phenotypically variable, even in constant environmental conditions. The ubiquity of this phenomenon, known as 'intra-genotypic variability', is increasingly evident and the relevant mechanistic underpinnings are beginning to be understood. In parallel, theory has delineated a number of formal expectations for contexts in which such a feature would be adaptive. Here, we review empirical evidence across biological systems and theoretical expectations, including nonlinear averaging and bet hedging. We synthesize existing results to illustrate the dependence of selection outcomes both on trait characteristics, features of environmental variability, and species' demographic context. We conclude by discussing ways to bridge the gap between empirical evidence of intra-genotypic variability, studies demonstrating its genetic component, and evidence that it is adaptive.
Topics: Biological Evolution; Genotype; Humans; Phenotype; Selection, Genetic
PubMed: 31519463
DOI: 10.1016/j.tree.2019.08.005 -
Journal of Experimental Botany May 2022Gas exchange techniques revolutionized plant research and advanced understanding, including associated fluxes and efficiencies, of photosynthesis, photorespiration, and... (Review)
Review
Gas exchange techniques revolutionized plant research and advanced understanding, including associated fluxes and efficiencies, of photosynthesis, photorespiration, and respiration of plants from cellular to ecosystem scales. These techniques remain the gold standard for inferring photosynthetic rates and underlying physiology/biochemistry, although their utility for high-throughput phenotyping (HTP) of photosynthesis is limited both by the number of gas exchange systems available and the number of personnel available to operate the equipment. Remote sensing techniques have long been used to assess ecosystem productivity at coarse spatial and temporal resolutions, and advances in sensor technology coupled with advanced statistical techniques are expanding remote sensing tools to finer spatial scales and increasing the number and complexity of phenotypes that can be extracted. In this review, we outline the photosynthetic phenotypes of interest to the plant science community and describe the advances in high-throughput techniques to characterize photosynthesis at spatial scales useful to infer treatment or genotypic variation in field-based experiments or breeding trials. We will accomplish this objective by presenting six lessons learned thus far through the development and application of proximal/remote sensing-based measurements and the accompanying statistical analyses. We will conclude by outlining what we perceive as the current limitations, bottlenecks, and opportunities facing HTP of photosynthesis.
Topics: Ecosystem; Genotype; Phenotype; Photosynthesis
PubMed: 35218184
DOI: 10.1093/jxb/erac077