-
Molecular Aspects of Medicine Jun 2022Although there is still no consensus on the definition of Asthma-COPD Overlap (ACO), it is generally accepted that some patients with airway disease have features of... (Review)
Review
Although there is still no consensus on the definition of Asthma-COPD Overlap (ACO), it is generally accepted that some patients with airway disease have features of both asthma and COPD. Just as its constituents, ACO consists of different phenotypes, possibly depending on the predominance of the underlying asthma or COPD-associated pathophysiological mechanisms. The clinical picture is influenced by the development of airway inflammatory processes either eosinophilic, neutrophilic or mixed, in addition to glandular changes leading to mucus hypersecretion and a variety of other airway structural changes. Although animal models have exposed how smoking-related changes can interact with those observed in asthma, much remains to be known about their interactions in humans and the additional modulating effects of environmental exposures. There is currently no solid evidence to establish the optimal treatment of ACO but it should understandably include an avoidance of environmental triggers such as smoking and relevant allergens. The recognition and targeting of "treatable traits" following phenotyping is a pragmatic approach to select the optimal pharmacological treatment for ACO, although an association of inhaled corticosteroids and bronchodilators is always required in these patients. This association acts both as an anti-inflammatory treatment for the asthma component and as a functional antagonist for the airway remodeling features. Research should be promoted on well phenotyped subgroups of ACO patients to determine their optimal management.
Topics: Asthma; Bronchodilator Agents; Humans; Phenotype; Pulmonary Disease, Chronic Obstructive
PubMed: 34521557
DOI: 10.1016/j.mam.2021.101021 -
Journal of the Royal Society, Interface Aug 2023Selection and variation are both key aspects in the evolutionary process. Previous research on the mapping between molecular sequence (genotype) and molecular fold...
Selection and variation are both key aspects in the evolutionary process. Previous research on the mapping between molecular sequence (genotype) and molecular fold (phenotype) has shown the presence of several structural properties in different biological contexts, implying that these might be universal in evolutionary spaces. The deterministic genotype-phenotype (GP) map that links short RNA sequences to minimum free energy secondary structures has been studied extensively because of its computational tractability and biologically realistic nature. However, this mapping ignores the phenotypic plasticity of RNA. We define a GP map that incorporates non-deterministic (ND) phenotypes, and take RNA as a case study; we use the Boltzmann probability distribution of folded structures and examine the structural properties of ND GP maps for RNA sequences of length 12 and coarse-grained RNA structures of length 30 (RNAshapes30). A framework is presented to study robustness, evolvability and neutral spaces in the ND map. This framework is validated by demonstrating close correspondence between the ND quantities and sample averages of their deterministic counterparts. When using the ND framework we observe the same structural properties as in the deterministic GP map, such as bias, negative correlation between genotypic robustness and evolvability, and positive correlation between phenotypic robustness and evolvability.
Topics: Adaptation, Physiological; Biological Evolution; Genotype; Phenotype; RNA
PubMed: 37608711
DOI: 10.1098/rsif.2023.0132 -
Journal of Microbiology (Seoul, Korea) Mar 2021Raman spectroscopy is a promising tool for identifying microbial phenotypes based on single cell Raman spectra reflecting cellular biochemical biomolecules. Recent... (Review)
Review
Raman spectroscopy is a promising tool for identifying microbial phenotypes based on single cell Raman spectra reflecting cellular biochemical biomolecules. Recent studies using Raman spectroscopy have mainly analyzed phenotypic changes caused by microbial interactions or stress responses (e.g., antibiotics) and evaluated the microbial activity or substrate specificity under a given experimental condition using stable isotopes. Lack of labelling and the nondestructive pretreatment and measurement process of Raman spectroscopy have also aided in the sorting of microbial cells with interesting phenotypes for subsequently conducting physiology experiments through cultivation or genome analysis. In this review, we provide an overview of the principles, advantages, and status of utilization of Raman spectroscopy for studies linking microbial phenotypes and functions. We expect Raman spectroscopy to become a next-generation phenotyping tool that will greatly contribute in enhancing our understanding of microbial functions in natural and engineered systems.
Topics: Bacteria; Bacterial Physiological Phenomena; Phenomics; Phenotype; Spectrum Analysis, Raman
PubMed: 33496936
DOI: 10.1007/s12275-021-0590-1 -
Journal of the American Dental... Nov 2019A significant amount of clinical information captured as free-text narratives could be better used for several applications, such as clinical decision support, ontology...
BACKGROUND
A significant amount of clinical information captured as free-text narratives could be better used for several applications, such as clinical decision support, ontology development, evidence-based practice, and research. The Human Phenotype Ontology (HPO) is specifically used for semantic comparisons for diagnostic purposes. All these functions require quality coverage of the domain of interest. The authors used natural language processing to capture craniofacial and oral phenotype signatures from electronic health records and then used these signatures for evaluation of existing oral phenotype ontology coverage.
METHODS
The authors applied a text-processing pipeline based on the clinical Text Analysis and Knowledge Extraction System to annotate the clinical notes with Unified Medical Language System codes. The authors extracted the disease or disorder phenotype terms, which were then compared with HPO terms and their synonyms.
RESULTS
The authors retrieved 2,153 deidentified clinical notes from 558 patients. Finally, 2,416 unique diseases or disorders phenotype terms were extracted, which included 210 craniofacial or oral phenotype terms. Twenty-six of these phenotypes were not found in the HPO.
CONCLUSIONS
The authors demonstrated that natural language processing tools could extract relevant phenotype terms from clinical narratives, which could help identify gaps in existing ontologies and enhance craniofacial and dental phenotyping vocabularies.
PRACTICAL IMPLICATIONS
The expansion of terms in the dental, oral, and craniofacial domains in the HPO is particularly important as the dental community moves toward electronic health records.
Topics: Electronic Health Records; Humans; Narration; Natural Language Processing; Phenotype; Vocabulary
PubMed: 31668172
DOI: 10.1016/j.adaj.2019.05.029 -
Annual Review of Biomedical Data Science Jul 2021Electronic health records (EHRs) are a rich source of data for researchers, but extracting meaningful information out of this highly complex data source is challenging.... (Review)
Review
Electronic health records (EHRs) are a rich source of data for researchers, but extracting meaningful information out of this highly complex data source is challenging. Phecodes represent one strategy for defining phenotypes for research using EHR data. They are a high-throughput phenotyping tool based on ICD (International Classification of Diseases) codes that can be used to rapidly define the case/control status of thousands of clinically meaningful diseases and conditions. Phecodes were originally developed to conduct phenome-wide association studies to scan for phenotypic associations with common genetic variants. Since then, phecodes have been used to support a wide range of EHR-based phenotyping methods, including the phenotype risk score. This review aims to comprehensively describe the development, validation, and applications of phecodes and suggest some future directions for phecodes and high-throughput phenotyping.
Topics: Electronic Health Records; Genome-Wide Association Study; International Classification of Diseases; Phenomics; Phenotype
PubMed: 34465180
DOI: 10.1146/annurev-biodatasci-122320-112352 -
Forensic Science International. Genetics Nov 2023Over a decade after the publication of the first forensic DNA phenotyping (FDP) studies, DNA-based appearance predictions are now becoming a reality in routine crime...
Over a decade after the publication of the first forensic DNA phenotyping (FDP) studies, DNA-based appearance predictions are now becoming a reality in routine crime scene investigations. The significant number of publications dedicated to the subject of FDP clearly demonstrates a sustained interest and a strong need for further method development. However, the implementation of FDP in routine work still encounters obstacles, and one of these challenges is making phenotype predictions from DNA mixtures. In this study, we examined single-cell sequencing as a potential tool to enable reliable phenotyping of contributors within mixtures. Two mock mixtures, each containing two contributors with similar and different physical appearances, were analyzed using two different workflows. In the first workflow, the mixtures were sequenced using the Ion AmpliSeq™ PhenoTrivium Panel, which includes 41 HIrisPlex-S (HPS) markers. Subsequently, the genotypes were analyzed using the HPS Deconvolution Tool to predict the phenotypes of both contributors. The second workflow involved the introduction of single-cell separation and collection using the DEPArray™ PLUS System. Two different PhenoTrivium amplification protocols were tested, and the phenotype predictions from single cells were compared with the results obtained using the HPS Tool. Our results suggest that the approach presented here allows for the obtainment of nearly complete HIrisPlex-S profiles with accurate genotypes and reliable phenotype predictions from single cells. This method proves successful in deconvoluting mixtures submitted to forensic DNA phenotyping.
Topics: Humans; Polymorphism, Single Nucleotide; Phenotype; DNA Fingerprinting; DNA; High-Throughput Nucleotide Sequencing; Sequence Analysis, DNA; Single-Cell Analysis
PubMed: 37832204
DOI: 10.1016/j.fsigen.2023.102938 -
Journal of Theoretical Biology Dec 2021We develop new equations for the eco-evolutionary dynamics of populations and their traits. These equations resolve the change in the phenotypic differentiation within a...
We develop new equations for the eco-evolutionary dynamics of populations and their traits. These equations resolve the change in the phenotypic differentiation within a population, which better estimates how the variance of the trait distribution changes. We note that traits may be bounded, assume they may be described by beta distributions with small variances, and develop a coupled ordinary differential equation system to describe the dynamics of the total population, the mean trait value, and a measure of phenotype differentiation. The variance of the trait in the population is calculated from its mean and the population's phenotype differentiation. We consider an example of two competing plant populations to demonstrate the efficacy of the new approach. Each population may trade-off its growth rate against its susceptibility to direct competition from the other population. We create two models of this system: a population model based on our new eco-evolutionary equations; and a phenotype model, in which the growth or demise of each fraction of each population with a defined phenotype is simulated as it interacts with a shared limiting resource and its competing phenotypes and populations. Comparison of four simulation scenarios reveals excellent agreement between the predicted quantities from both models: total populations, the average trait values, the trait variances, and the degree of phenotypic differentiation within each population. In each of the four scenarios simulated, three of which are initially subject to competitive exclusion in the absence of evolution, the populations adapt to coexist. One population maximises growth and dominates, while the other minimises competitive losses. These simulations suggest that our new eco-evolutionary equations may provide an excellent approximation to phenotype changes in populations.
Topics: Adaptation, Physiological; Biological Evolution; Computer Simulation; Phenotype; Population Dynamics
PubMed: 34481861
DOI: 10.1016/j.jtbi.2021.110893 -
Mammalian Genome : Official Journal of... Jun 2020Thought to be directly and uniquely dependent from genotypes, the ontogeny of individual phenotypes is much more complicated. Individual genetics, environmental... (Review)
Review
Thought to be directly and uniquely dependent from genotypes, the ontogeny of individual phenotypes is much more complicated. Individual genetics, environmental exposures, and their interaction are the three main determinants of individual's phenotype. This picture has been further complicated a decade ago when the Lamarckian theory of acquired inheritance has been rekindled with the discovery of epigenetic inheritance, according to which acquired phenotypes can be transmitted through fertilization and affect phenotypes across generations. The results of Genome-Wide Association Studies have also highlighted a big degree of missing heritability in genetics and have provided hints that not only acquired phenotypes, but also individual's genotypes affect phenotypes intergenerationally through indirect genetic effects. Here, we review available examples of indirect genetic effects in mammals, what is known of the underlying molecular mechanisms and their potential impact for our understanding of missing heritability, phenotypic variation. and individual disease risk.
Topics: Animals; DNA Methylation; Epigenesis, Genetic; Gene-Environment Interaction; Genetic Variation; Genome-Wide Association Study; Genotype; Histone Code; Humans; Mammals; Multifactorial Inheritance; Phenotype
PubMed: 32529318
DOI: 10.1007/s00335-020-09841-5 -
TAG. Theoretical and Applied Genetics.... Jan 2022Rising temperatures and changing precipitation patterns will affect agricultural production substantially, exposing crops to extended and more intense periods of stress.... (Review)
Review
Rising temperatures and changing precipitation patterns will affect agricultural production substantially, exposing crops to extended and more intense periods of stress. Therefore, breeding of varieties adapted to the constantly changing conditions is pivotal to enable a quantitatively and qualitatively adequate crop production despite the negative effects of climate change. As it is not yet possible to select for adaptation to future climate scenarios in the field, simulations of future conditions in controlled-environment (CE) phenotyping facilities contribute to the understanding of the plant response to special stress conditions and help breeders to select ideal genotypes which cope with future conditions. CE phenotyping facilities enable the collection of traits that are not easy to measure under field conditions and the assessment of a plant's phenotype under repeatable, clearly defined environmental conditions using automated, non-invasive, high-throughput methods. However, extrapolation and translation of results obtained under controlled environments to field environments is ambiguous. This review outlines the opportunities and challenges of phenotyping approaches under controlled environments complementary to conventional field trials. It gives an overview on general principles and introduces existing phenotyping facilities that take up the challenge of obtaining reliable and robust phenotypic data on climate response traits to support breeding of climate-adapted crops.
Topics: Adaptation, Physiological; Climate Change; Droughts; Environment, Controlled; Phenotype; Plant Breeding; Plant Transpiration; Salt Stress
PubMed: 34302493
DOI: 10.1007/s00122-021-03892-1 -
The Behavioral and Brain Sciences Sep 2022We need better understanding of functional differences of behavioral phenotypes across cultures because cultural evolution (e.g., temporal changes in innovation within...
We need better understanding of functional differences of behavioral phenotypes across cultures because cultural evolution (e.g., temporal changes in innovation within populations) is less important than culturally molded phenotypes (e.g., differences across populations) for understanding gene effects. Furthermore, changes in one behavioral domain likely have complex downstream effects in other domains, requiring careful parsing of phenotypic variability and functions.
Topics: Cultural Evolution; Phenotype
PubMed: 36098442
DOI: 10.1017/S0140525X21001746