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Biometrics Dec 2023Gene-environment (G-E) interactions have important implications for cancer outcomes and phenotypes beyond the main G and E effects. Compared to main-effect-only...
Gene-environment (G-E) interactions have important implications for cancer outcomes and phenotypes beyond the main G and E effects. Compared to main-effect-only analysis, G-E interaction analysis more seriously suffers from a lack of information caused by higher dimensionality, weaker signals, and other factors. It is also uniquely challenged by the "main effects, interactions" variable selection hierarchy. Effort has been made to bring in additional information to assist cancer G-E interaction analysis. In this study, we take a strategy different from the existing literature and borrow information from pathological imaging data. Such data are a "byproduct" of biopsy, enjoys broad availability and low cost, and has been shown as informative for modeling prognosis and other cancer outcomes/phenotypes in recent studies. Building on penalization, we develop an assisted estimation and variable selection approach for G-E interaction analysis. The approach is intuitive, can be effectively realized, and has competitive performance in simulation. We further analyze The Cancer Genome Atlas (TCGA) data on lung adenocarcinoma (LUAD). The outcome of interest is overall survival, and for G variables, we analyze gene expressions. Assisted by pathological imaging data, our G-E interaction analysis leads to different findings with competitive prediction performance and stability.
Topics: Humans; Gene-Environment Interaction; Neoplasms; Computer Simulation; Phenotype; Models, Genetic
PubMed: 37132273
DOI: 10.1111/biom.13873 -
Theoretical Population Biology Feb 2024Natural selection acts on phenotypes constructed over development, which raises the question of how development affects evolution. Classic evolutionary theory indicates...
Natural selection acts on phenotypes constructed over development, which raises the question of how development affects evolution. Classic evolutionary theory indicates that development affects evolution by modulating the genetic covariation upon which selection acts, thus affecting genetic constraints. However, whether genetic constraints are relative, thus diverting adaptation from the direction of steepest fitness ascent, or absolute, thus blocking adaptation in certain directions, remains uncertain. This limits understanding of long-term evolution of developmentally constructed phenotypes. Here we formulate a general, tractable mathematical framework that integrates age progression, explicit development (i.e., the construction of the phenotype across life subject to developmental constraints), and evolutionary dynamics, thus describing the evolutionary and developmental (evo-devo) dynamics. The framework yields simple equations that can be arranged in a layered structure that we call the evo-devo process, whereby five core elementary components generate all equations including those mechanistically describing genetic covariation and the evo-devo dynamics. The framework recovers evolutionary dynamic equations in gradient form and describes the evolution of genetic covariation from the evolution of genotype, phenotype, environment, and mutational covariation. This shows that genotypic and phenotypic evolution must be followed simultaneously to yield a dynamically sufficient description of long-term phenotypic evolution in gradient form, such that evolution described as the climbing of a fitness landscape occurs in "geno-phenotype" space. Genetic constraints in geno-phenotype space are necessarily absolute because the phenotype is related to the genotype by development. Thus, the long-term evolutionary dynamics of developed phenotypes is strongly non-standard: (1) evolutionary equilibria are either absent or infinite in number and depend on genetic covariation and hence on development; (2) developmental constraints determine the admissible evolutionary path and hence which evolutionary equilibria are admissible; and (3) evolutionary outcomes occur at admissible evolutionary equilibria, which do not generally occur at fitness landscape peaks in geno-phenotype space, but at peaks in the admissible evolutionary path where "total genotypic selection" vanishes if exogenous plastic response vanishes and mutational variation exists in all directions of genotype space. Hence, selection and development jointly define the evolutionary outcomes if absolute mutational constraints and exogenous plastic response are absent, rather than the outcomes being defined only by selection. Moreover, our framework provides formulas for the sensitivities of a recurrence and an alternative method to dynamic optimization (i.e., dynamic programming or optimal control) to identify evolutionary outcomes in models with developmentally dynamic traits. These results show that development has major evolutionary effects.
Topics: Biological Evolution; Phenotype; Genotype; Selection, Genetic; Mutation
PubMed: 38043588
DOI: 10.1016/j.tpb.2023.11.003 -
Bioinformatics (Oxford, England) Nov 2023Phecodes are widely used and easily adapted phenotypes based on International Classification of Diseases codes. The current version of phecodes (v1.2) was designed...
MOTIVATION
Phecodes are widely used and easily adapted phenotypes based on International Classification of Diseases codes. The current version of phecodes (v1.2) was designed primarily to study common/complex diseases diagnosed in adults; however, there are numerous limitations in the codes and their structure.
RESULTS
Here, we present phecodeX, an expanded version of phecodes with a revised structure and 1,761 new codes. PhecodeX adds granularity to phenotypes in key disease domains that are under-represented in the current phecode structure-including infectious disease, pregnancy, congenital anomalies, and neonatology-and is a more robust representation of the medical phenome for global use in discovery research.
AVAILABILITY AND IMPLEMENTATION
phecodeX is available at https://github.com/PheWAS/phecodeX.
Topics: Phenomics; Genome-Wide Association Study; Polymorphism, Single Nucleotide; Phenotype
PubMed: 37930895
DOI: 10.1093/bioinformatics/btad655 -
Clinical Science (London, England :... Aug 2023Macrophages represent heterogeneous cell population with important roles in defence mechanisms and in homoeostasis. Tissue macrophages from diverse anatomical locations...
Macrophages represent heterogeneous cell population with important roles in defence mechanisms and in homoeostasis. Tissue macrophages from diverse anatomical locations adopt distinct activation states. M1 and M2 macrophages are two polarized forms of mononuclear phagocyte in vitro differentiation with distinct phenotypic patterns and functional properties, but in vivo, there is a wide range of different macrophage phenotypes in between depending on the microenvironment and natural signals they receive. In human infections, pathogens use different strategies to combat macrophages and these strategies include shaping the macrophage polarization towards one or another phenotype. Macrophages infiltrating the tumours can affect the patient's prognosis. M2 macrophages have been shown to promote tumour growth, while M1 macrophages provide both tumour-promoting and anti-tumour properties. In autoimmune diseases, both prolonged M1 activation, as well as altered M2 function can contribute to their onset and activity. In human atherosclerotic lesions, macrophages expressing both M1 and M2 profiles have been detected as one of the potential factors affecting occurrence of cardiovascular diseases. In allergic inflammation, T2 cytokines drive macrophage polarization towards M2 profiles, which promote airway inflammation and remodelling. M1 macrophages in transplantations seem to contribute to acute rejection, while M2 macrophages promote the fibrosis of the graft. The view of pro-inflammatory M1 macrophages and M2 macrophages suppressing inflammation seems to be an oversimplification because these cells exploit very high level of plasticity and represent a large scale of different immunophenotypes with overlapping properties. In this respect, it would be more precise to describe macrophages as M1-like and M2-like.
Topics: Humans; Macrophages; Cytokines; Phenotype; Inflammation; Cell Differentiation
PubMed: 37530555
DOI: 10.1042/CS20220531 -
Trends in Cell Biology Jun 2024Non-genetic alterations can produce changes in a cell's phenotype. In cancer, these phenomena can influence a cell's fitness by conferring access to heritable,... (Review)
Review
Non-genetic alterations can produce changes in a cell's phenotype. In cancer, these phenomena can influence a cell's fitness by conferring access to heritable, beneficial phenotypes. Herein, we argue that current discussions of 'phenotypic plasticity' in cancer evolution ignore a salient feature of the original definition: namely, that it occurs in response to an environmental change. We suggest 'phenotypic noise' be used to distinguish non-genetic changes in phenotype that occur independently from the environment. We discuss the conceptual and methodological techniques used to identify these phenomena during cancer evolution. We propose that the distinction will guide efforts to define mechanisms of phenotype change, accelerate translational work to manipulate phenotypes through treatment, and, ultimately, improve patient outcomes.
Topics: Animals; Humans; Cell Plasticity; Neoplasms; Phenotype; Evolution, Molecular
PubMed: 37968225
DOI: 10.1016/j.tcb.2023.10.002 -
Annual Review of Pharmacology and... Jan 2024Pharmacogenomics (PGx) enables personalized treatment for the prediction of drug response and to avoid adverse drug reactions. Currently, PGx mainly relies on the... (Review)
Review
Pharmacogenomics (PGx) enables personalized treatment for the prediction of drug response and to avoid adverse drug reactions. Currently, PGx mainly relies on the genetic information of absorption, distribution, metabolism, and excretion (ADME) targets such as drug-metabolizing enzymes or transporters to predict differences in the patient's phenotype. However, there is evidence that the phenotype-genotype concordance is limited. Thus, we discuss different phenotyping strategies using exogenous xenobiotics (e.g., drug cocktails) or endogenous compounds for phenotype prediction. In particular, minimally invasive approaches focusing on liquid biopsies offer great potential to preemptively determine metabolic and transport capacities. Early studies indicate that ADME phenotyping using exosomes released from the liver is reliable. In addition, pharmacometric modeling and artificial intelligence improve phenotype prediction. However, further prospective studies are needed to demonstrate the clinical utility of individualized treatment based on phenotyping strategies, not only relying on genetics. The present review summarizes current knowledge and limitations.
Topics: Humans; Artificial Intelligence; Genotype; Biomarkers; Phenotype; Drug-Related Side Effects and Adverse Reactions
PubMed: 37585662
DOI: 10.1146/annurev-pharmtox-032023-121106 -
Biophysical Journal Nov 2023Phenotypic adaptation is a universal feature of biological systems navigating highly variable environments. Recent empirical data support the role of memory-driven...
Phenotypic adaptation is a universal feature of biological systems navigating highly variable environments. Recent empirical data support the role of memory-driven decision making in cellular systems navigating uncertain future nutrient landscapes, wherein a distinct growth phenotype emerges in fluctuating conditions. We develop a simple stochastic mathematical model to describe memory-driven cellular adaptation required for systems to optimally navigate such uncertainty. In this framework, adaptive populations traverse dynamic environments by inferring future variation from a memory of prior states, and memory capacity imposes a fundamental trade-off between the speed and accuracy of adaptation to new fluctuating environments. Our results suggest that the observed growth reductions that occur in fluctuating environments are a direct consequence of optimal decision making and result from bet hedging and occasional phenotypic-environmental mismatch. We anticipate that this modeling framework will be useful for studying the role of memory in phenotypic adaptation, including in the design of temporally varying therapies against adaptive systems.
Topics: Environment; Adaptation, Physiological; Selection, Genetic; Biological Evolution; Phenotype
PubMed: 37876159
DOI: 10.1016/j.bpj.2023.10.019 -
Genes Sep 2023Cardiomyopathies (CMPs) represent a significant healthcare burden and are a major cause of heart failure leading to premature death. Several CMPs are now recognized to... (Review)
Review
Cardiomyopathies (CMPs) represent a significant healthcare burden and are a major cause of heart failure leading to premature death. Several CMPs are now recognized to have a strong genetic basis, including arrhythmogenic cardiomyopathy (ACM), which predisposes patients to arrhythmic episodes. Variants in one of the five genes ( and ) encoding proteins of the desmosome are known to cause a subset of ACM, which we classify as desmosome-related ACM (dACM). Phenotypically, this disease may lead to sudden cardiac death in young athletes and, during late stages, is often accompanied by myocardial fibrofatty infiltrates. While the pathogenicity of the desmosome genes has been well established through animal studies and limited supplies of primary human cells, these systems have drawbacks that limit their utility and relevance to understanding human disease. Human induced pluripotent stem cells (hiPSCs) have emerged as a powerful tool for modeling ACM in vitro that can overcome these challenges, as they represent a reproducible and scalable source of cardiomyocytes (CMs) that recapitulate patient phenotypes. In this review, we provide an overview of dACM, summarize findings in other model systems linking desmosome proteins with this disease, and provide an up-to-date summary of the work that has been conducted in hiPSC-cardiomyocyte (hiPSC-CM) models of dACM. In the context of the hiPSC-CM model system, we highlight novel findings that have contributed to our understanding of disease and enumerate the limitations, prospects, and directions for research to consider towards future progress.
Topics: Humans; Induced Pluripotent Stem Cells; Myocytes, Cardiac; Cardiomyopathies; Phenotype
PubMed: 37895213
DOI: 10.3390/genes14101864 -
Current Opinion in Microbiology Aug 2023How microbes interact with their environment and how the complex interplay of their genes enables them to survive and thrive under stress is a fundamental question in... (Review)
Review
How microbes interact with their environment and how the complex interplay of their genes enables them to survive and thrive under stress is a fundamental question in microbial system biology, which is also important from a public health perspective. Large-scale studies of gene-gene, gene-drug, and drug-drug interactions have proven to be powerful tools for elucidating gene function and functional modules in the cell. Approaches that systematically quantify phenotypes in libraries of microbial strains with genome-wide genetic perturbations are crucial for progress in this area. Here, we review recent advances in this field, and point out applications to the study of gene-drug interactions. We highlight newly developed techniques for the rapid generation of genome-wide mutant libraries and the high-throughput measurement of more complex phenotypes and other observables, such as cell morphology or thermal stability of the proteome.
Topics: Phenotype; Genome
PubMed: 37276805
DOI: 10.1016/j.mib.2023.102333 -
Revista Alergia Mexico (Tecamachalco,... Dec 2023Food allergy is a common event, especially in the pediatric population, affecting between 3-6% of children. There are various challenges in the care of patients with...
Food allergy is a common event, especially in the pediatric population, affecting between 3-6% of children. There are various challenges in the care of patients with food allergy, but certainly the diversity of symptoms and the outcome of the disease are important aspects in the treatment of patients, in the development of care guidelines and in the knowledge of the Natural history of disease. The classification into phenotypes allows a better understanding of the evolution of food allergy. The endotype is a subtype of a phenotype defined by its pathophysiological characteristic. Genetic, epigenetic, and environmental characteristics interfere with the construction of the phenotype and its possible endotypes. Understanding the phenotypes and endotypes of food allergies brings with it two fundamental aspects: 1) the need to understand that the analysis of phenotypes and endotypes in food allergies will allow establishing prognoses and helping in intervention with specific therapies, and 2) the importance of understanding The characterization of local endotypes and phenotypes, and the dietary diversity of the different countries that make up Latin America brings with it a varied menu of foods that may pose a risk of allergy that needs to be studied.
Topics: Child; Humans; Food Hypersensitivity; Food; Phenotype
PubMed: 38506862
DOI: 10.29262/ram.v70i4.1331