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Reproductive Sciences (Thousand Oaks,... Nov 2023This cross-sectional study examines the Doi-Alshoumer PCOS clinical phenotype classification in relation to measured clinical and biochemical characteristics of women...
This cross-sectional study examines the Doi-Alshoumer PCOS clinical phenotype classification in relation to measured clinical and biochemical characteristics of women with polycystic ovary syndrome (PCOS). Two cohorts of women (Kuwait and Rotterdam) diagnosed with PCOS (FAI > 4.5%) were examined. These phenotypes were created using neuroendocrine dysfunction (IRMA LH/FSH ratio > 1 or LH > 6 IU/L) and menstrual cycle status (oligo/amenorrhea) to create three phenotypes: (A) neuroendocrine dysfunction and oligo/amenorrhea, (B) without neuroendocrine dysfunction but with oligo/amenorrhea, and (C) without neuroendocrine dysfunction and with regular cycles. These phenotypes were compared in terms of hormonal, biochemical, and anthropometric measures. The three suggested phenotypes (A, B, and C) were shown to be sufficiently distinct in terms of hormonal, biochemical, and anthropometric measures. Patients who were classified as phenotype A had neuroendocrine dysfunction, excess LH (and LH/FSH ratio), irregular cycles, excess A4, infertility, excess T, highest FAI and E2, and excess 17αOHPG when compared to the other phenotypes. Patients classified as phenotype B had irregular cycles, no neuroendocrine dysfunction, obesity, acanthosis nigricans, and insulin resistance. Lastly, patients classified as phenotype C had regular cycles, acne, hirsutism, excess P4, and the highest P4 to E2 molar ratio. The differences across phenotypes suggested distinct phenotypic expression of this syndrome, and the biochemical and clinical correlates of each phenotype are likely to be useful in the management of women with PCOS. These phenotypic criteria are distinct from criteria used for diagnosis.
Topics: Female; Humans; Polycystic Ovary Syndrome; Cross-Sectional Studies; Amenorrhea; Phenotype; Follicle Stimulating Hormone
PubMed: 37217826
DOI: 10.1007/s43032-023-01262-4 -
Cancer Biology & Therapy Dec 2024Neuroblastoma is the most frequent extracranial pediatric tumor and leads to 15% of all cancer-related deaths in children. Tumor relapse and therapy resistance in...
Neuroblastoma is the most frequent extracranial pediatric tumor and leads to 15% of all cancer-related deaths in children. Tumor relapse and therapy resistance in neuroblastoma are driven by phenotypic plasticity and heterogeneity between noradrenergic (NOR) and mesenchymal (MES) cell states. Despite the importance of this phenotypic plasticity, the dynamics and molecular patterns associated with these bidirectional cell-state transitions remain relatively poorly understood. Here, we analyze multiple RNA-seq datasets at both bulk and single-cell resolution, to understand the association between NOR- and MES-specific factors. We observed that NOR-specific and MES-specific expression patterns are largely mutually exclusive, exhibiting a "teams-like" behavior among the genes involved, reminiscent of our earlier observations in lung cancer and melanoma. This antagonism between NOR and MES phenotypes was also associated with metabolic reprogramming and with immunotherapy targets PD-L1 and GD2 as well as with experimental perturbations driving the NOR-MES and/or MES-NOR transition. Further, these "teams-like" patterns were seen only among the NOR- and MES-specific genes, but not in housekeeping genes, possibly highlighting a hallmark of network topology enabling cancer cell plasticity.
Topics: Child; Humans; Neoplasm Recurrence, Local; Neuroblastoma; Gene Expression Regulation, Neoplastic; Phenotype
PubMed: 38230570
DOI: 10.1080/15384047.2024.2301802 -
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 -
STAR Protocols Mar 2024DNA G-quadruplex (G4) is a non-canonical four-stranded secondary structure that has been shown to play a role in epigenetic modulation of gene expression. Here, we... (Review)
Review
DNA G-quadruplex (G4) is a non-canonical four-stranded secondary structure that has been shown to play a role in epigenetic modulation of gene expression. Here, we present a primer on phenotype-specific profiling of DNA G-quadruplex-regulated genes. We provide guidance on in silico exploration of G4-related genes and phenotypes, and in vitro and in vivo validation of the relationship between G4 and phenotype. We describe commonly utilized techniques and detail critical steps involved in determining the phenotype-specific G4-regulated genes for subsequent investigations.
Topics: DNA; G-Quadruplexes; Phenotype
PubMed: 38198280
DOI: 10.1016/j.xpro.2023.102820 -
Journal of Endocrinological... Jan 2024To evaluate the genotypic and phenotypic relationship in a large cohort of OI patients and to compare the differences between eastern and western OI cohorts.
PURPOSE
To evaluate the genotypic and phenotypic relationship in a large cohort of OI patients and to compare the differences between eastern and western OI cohorts.
METHODS
A total of 671 OI patients were included. Pathogenic mutations were identified, phenotypic information was collected, and relationships between genotypes and phenotypes were analyzed. Literature about western OI cohorts was searched, and differences were compared between eastern and western OI cohorts.
RESULTS
A total of 560 OI patients were identified as carrying OI pathogenic mutations, and the positive detection rate of disease-causing gene mutations was 83.5%. Mutations in 15 OI candidate genes were identified, with COL1A1 (n = 308, 55%) and COL1A2 (n = 164, 29%) being the most common mutations, and SERPINF1 and WNT1 being the most common biallelic variants. Of the 414 probands, 48.8, 16.9, 29.2 and 5.1% had OI types I, III, IV and V, respectively. Peripheral fracture was the most common phenotype (96.6%), and femurs (34.7%) were most commonly affected. Vertebral compression fracture was observed in 43.5% of OI patients. Biallelic or COL1A2 mutation led to more bone deformities and poorer mobility than COL1A1 mutation (all P < 0.05). Glycine substitution of COL1A1 or COL1A2 or biallelic variants led to more severe phenotypes than haploinsufficiency of collagen type I α chains, which induced the mildest phenotypes. Although the gene mutation spectrum varied among countries, the fracture incidence was similar between eastern and western OI cohorts.
CONCLUSION
The findings are valuable for accurate diagnosis and treatment of OI, mechanism exploration and prognosis judgment. Genetic profiles of OI may vary among races, but the mechanism needs to be explored.
Topics: Humans; Osteogenesis Imperfecta; Collagen Type I, alpha 1 Chain; Fractures, Compression; Spinal Fractures; Collagen Type I; Genotype; Phenotype; Mutation; Bone Diseases, Metabolic
PubMed: 37270749
DOI: 10.1007/s40618-023-02123-2 -
Genome Biology May 2024Numerous algorithms have been proposed to identify cell types in single-cell RNA sequencing data, yet a fundamental problem remains: determining associations between...
Numerous algorithms have been proposed to identify cell types in single-cell RNA sequencing data, yet a fundamental problem remains: determining associations between cells and phenotypes such as cancer. We develop SCIPAC, the first algorithm that quantitatively estimates the association between each cell in single-cell data and a phenotype. SCIPAC also provides a p-value for each association and applies to data with virtually any type of phenotype. We demonstrate SCIPAC's accuracy in simulated data. On four real cancerous or noncancerous datasets, insights from SCIPAC help interpret the data and generate new hypotheses. SCIPAC requires minimum tuning and is computationally very fast.
Topics: Single-Cell Analysis; Phenotype; Algorithms; Humans; Neoplasms; Sequence Analysis, RNA
PubMed: 38741183
DOI: 10.1186/s13059-024-03263-1 -
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 -
Lab on a Chip Jul 2023Modelling proximal tubule physiology and pharmacology is essential to understand tubular biology and guide drug discovery. To date, multiple models have been developed;...
Modelling proximal tubule physiology and pharmacology is essential to understand tubular biology and guide drug discovery. To date, multiple models have been developed; however, their relevance to human disease has yet to be evaluated. Here, we report a 3D vascularized proximal tubule-on-a-multiplexed chip (3DvasPT-MC) device composed of co-localized cylindrical conduits lined with confluent epithelium and endothelium, embedded within a permeable matrix, and independently addressed by a closed-loop perfusion system. Each multiplexed chip contains six 3DvasPT models. We performed RNA-seq and compared the transcriptomic profile of proximal tubule epithelial cells (PTECs) and human glomerular endothelial cells (HGECs) seeded in our 3D vasPT-MCs and on 2D transwell controls with and without a gelatin-fibrin coating. Our results reveal that the transcriptional profile of PTECs is highly dependent on both the matrix and flow, while HGECs exhibit greater phenotypic plasticity and are affected by the matrix, PTECs, and flow. PTECs grown on non-coated Transwells display an enrichment of inflammatory markers, including TNF-a, IL-6, and CXCL6, resembling damaged tubules. However, this inflammatory response is not observed for 3D proximal tubules, which exhibit expression of kidney signature genes, including drug and solute transporters, akin to native tubular tissue. Likewise, the transcriptome of HGEC vessels resembled that of sc-RNAseq from glomerular endothelium when seeded on this matrix and subjected to flow. Our 3D vascularized tubule on chip model has utility for both renal physiology and pharmacology.
Topics: Humans; Endothelial Cells; Kidney Tubules, Proximal; Epithelium; Kidney; Epithelial Cells; Phenotype
PubMed: 37341452
DOI: 10.1039/d2lc00723a -
Journal of Plant Physiology Nov 2023A plant's genome encodes enzymes, transporters and many other proteins which constitute metabolism. Interactions of plants with their environment shape their growth,... (Review)
Review
A plant's genome encodes enzymes, transporters and many other proteins which constitute metabolism. Interactions of plants with their environment shape their growth, development and resilience towards adverse conditions. Although genome sequencing technologies and applications have experienced triumphantly rapid development during the last decades, enabling nowadays a fast and cheap sequencing of full genomes, prediction of metabolic phenotypes from genotype × environment interactions remains, at best, very incomplete. The main reasons are a lack of understanding of how different levels of molecular organisation depend on each other, and how they are constituted and expressed within a setup of growth conditions. Phenotypic plasticity, e.g., of the genetic model plant Arabidopsis thaliana, has provided important insights into plant-environment interactions and the resulting genotype x phenotype relationships. Here, we summarize previous and current findings about plant development in a changing environment and how this might be shaped and reflected in metabolism and its regulation. We identify current challenges in the study of plant development and metabolic regulation and provide an outlook of how methodological workflows might support the application of findings made in model systems to crops and their cultivation.
Topics: Gene-Environment Interaction; Genotype; Phenotype; Crops, Agricultural; Arabidopsis
PubMed: 37839392
DOI: 10.1016/j.jplph.2023.154116