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Best Practice & Research. Clinical... Jan 2022Pathogenic variants have been found in all genes involved in the classic pathways of human adrenal and gonadal steroidogenesis. Depending on their function and severity,... (Review)
Review
Pathogenic variants have been found in all genes involved in the classic pathways of human adrenal and gonadal steroidogenesis. Depending on their function and severity, they cause characteristic disorders of corticosteroid and/or sex hormone deficiency, may result in atypical sex development at birth and/or puberty, and mostly lead to sexual dysfunction and infertility. Genetic disorders of steroidogenesis are all inherited in an autosomal recessive fashion. Loss of function mutations lead to typical phenotypes, while variants with partial activity may manifest with milder, non-classic, late-onset disorders that share similar phenotypes. Thus, these disorders of steroidogenesis are diagnosed by comprehensive phenotyping, steroid profiling and genetic testing using next generation sequencing techniques. Treatment comprises of steroid replacement therapies, but these are insufficient in many aspects. Therefore, studies are currently ongoing towards newer approaches such as lentiviral transmitted enzyme replacement therapy and reprogrammed stem cell-based gene therapy.
Topics: Adrenal Glands; Gonads; Humans; Phenotype; Sexual Development; Steroids
PubMed: 34711511
DOI: 10.1016/j.beem.2021.101593 -
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 -
AMIA ... Annual Symposium Proceedings.... 2022Acute kidney injury (AKI) is a life-threatening and heterogeneous syndrome. Timely and etiology-based personalized treatment is crucial. AKI sub-phenotyping can lead to...
Acute kidney injury (AKI) is a life-threatening and heterogeneous syndrome. Timely and etiology-based personalized treatment is crucial. AKI sub-phenotyping can lead to better understanding of the pathophysiology of AKI and help developing more targeted intervention. Current dimensionality reduction and similarity-based clustering for AKI sub-phenotyping suffer from limited interpretability and specificity. To address these limitations, we propose a pattern mining approach with multiobjective evolutionary algorithm (MOEA) for AKI sub-phenotyping. AKI sub-phenotypes are presented as explicit rules, so no post-hoc explanation is needed. Also, our method can search feature subspace efficiently for minor and highly specific sub-phenotypes. We aimed to discover sub-phenotypes for AKI patients against non-AKI patients (AKI vs non-AKI) and moderate-to-severe AKI patients against mild AKI patients (AKI-2/3 vs AKI-1). We identified 174(178) significant sub-phenotypes with average confidence of 0.33(0.33). Our method can assign patients to a sub-phenotype with higher confidence than k-means clustering, with average improvement of 0.20(0.23).
Topics: Humans; Phenotype; Acute Kidney Injury
PubMed: 37128400
DOI: No ID Found -
HGG Advances Oct 2023Inherited metabolic disorders (IMDs) are variably expressive, complicating identification of affected individuals. A genotype-first approach can identify individuals at...
Inherited metabolic disorders (IMDs) are variably expressive, complicating identification of affected individuals. A genotype-first approach can identify individuals at risk for morbidity and mortality from undiagnosed IMDs and can lead to protocols that improve clinical detection, counseling, and management. Using data from 57,340 participants in two hospital biobanks, we assessed the frequency and phenotypes of individuals with pathogenic/likely pathogenic variants (PLPVs) in two IMD genes: , associated with Fabry disease, and , associated with ornithine transcarbamylase deficiency. Approximately 1 in 19,100 participants harbored an undiagnosed PLPV in or . We identified three individuals (2 male, 1 female) with PLPVs in , all of whom were undiagnosed, and three individuals (3 female) with PLPVs in , two of whom were undiagnosed. All three individuals with PLPVs in (100%) had symptoms suggestive of mild Fabry disease, and one individual (14.2%) had an ischemic stroke at age 33, likely indicating the presence of classic disease. No individuals with PLPVs in had documented hyperammonemia despite exposure to catabolic states, but all (100%) had chronic symptoms suggestive of attenuated disease, including mood disorders and migraines. Our findings suggest that and variants identified via a genotype-first approach are of high penetrance and that population screening of these genes can be used to facilitate stepwise phenotyping and appropriate care.
Topics: Female; Male; Humans; Fabry Disease; Phenotype; Genotype; Penetrance; Hospitals
PubMed: 37593415
DOI: 10.1016/j.xhgg.2023.100226 -
Bioinformatics (Oxford, England) May 2024Whole-exome and genome sequencing have become common tools in diagnosing patients with rare diseases. Despite their success, this approach leaves many patients...
MOTIVATION
Whole-exome and genome sequencing have become common tools in diagnosing patients with rare diseases. Despite their success, this approach leaves many patients undiagnosed. A common argument is that more disease variants still await discovery, or the novelty of disease phenotypes results from a combination of variants in multiple disease-related genes. Interpreting the phenotypic consequences of genomic variants relies on information about gene functions, gene expression, physiology, and other genomic features. Phenotype-based methods to identify variants involved in genetic diseases combine molecular features with prior knowledge about the phenotypic consequences of altering gene functions. While phenotype-based methods have been successfully applied to prioritizing variants, such methods are based on known gene-disease or gene-phenotype associations as training data and are applicable to genes that have phenotypes associated, thereby limiting their scope. In addition, phenotypes are not assigned uniformly by different clinicians, and phenotype-based methods need to account for this variability.
RESULTS
We developed an Embedding-based Phenotype Variant Predictor (EmbedPVP), a computational method to prioritize variants involved in genetic diseases by combining genomic information and clinical phenotypes. EmbedPVP leverages a large amount of background knowledge from human and model organisms about molecular mechanisms through which abnormal phenotypes may arise. Specifically, EmbedPVP incorporates phenotypes linked to genes, functions of gene products, and the anatomical site of gene expression, and systematically relates them to their phenotypic effects through neuro-symbolic, knowledge-enhanced machine learning. We demonstrate EmbedPVP's efficacy on a large set of synthetic genomes and genomes matched with clinical information.
AVAILABILITY AND IMPLEMENTATION
EmbedPVP and all evaluation experiments are freely available at https://github.com/bio-ontology-research-group/EmbedPVP.
Topics: Humans; Genomics; Phenotype; Genetic Variation; Computational Biology; Machine Learning
PubMed: 38696757
DOI: 10.1093/bioinformatics/btae301 -
Postepy Biochemii Jun 2020Diet is an important modifiable lifestyle factor affecting the risk of developing of most non-communicable diseases. A properly selected diet protects against the... (Review)
Review
Diet is an important modifiable lifestyle factor affecting the risk of developing of most non-communicable diseases. A properly selected diet protects against the development of many diseases or supports their treatment. Randomized clinical trials have shown that personalized nutrition is more effective than general nutritional advice in terms of changing eating habits and treating obesity. Depending on the degree of diversification of dietary recommendations and their adaptation to the individuals’ needs, one can differentiate: stratified, personalized and precise nutrition. Metabolic phenotyping – grouping people based on their metabolic characteristics – is a relatively new research field which may have a great value in the development of personalized nutrition. Many studies have shown that people with different metabotypes react differently to a diet or specific nutritional interventions. This article reviews current studies regarding the possibility of using the metabolic phenotyping in stratified and personalized nutrition. The article presents methods for creating metabolic phenotypes, diagnostic and prognostic research involving metabotyping and research that use metabotyping for the delivery of targeted dietary advice conducted so far.
Topics: Diet, Healthy; Humans; Individuality; Nutritional Status; Obesity; Phenotype
PubMed: 32700505
DOI: 10.18388/pb.2020_329 -
American Journal of Human Genetics Jan 2023Although genomic research has predominantly relied on phenotypic ascertainment of individuals affected with heritable disease, the falling costs of sequencing allow... (Review)
Review
Although genomic research has predominantly relied on phenotypic ascertainment of individuals affected with heritable disease, the falling costs of sequencing allow consideration of genomic ascertainment and reverse phenotyping (the ascertainment of individuals with specific genomic variants and subsequent evaluation of physical characteristics). In this research modality, the scientific question is inverted: investigators gather individuals with a genomic variant and test the hypothesis that there is an associated phenotype via targeted phenotypic evaluations. Genomic ascertainment research is thus a model of predictive genomic medicine and genomic screening. Here, we provide our experience implementing this research method. We describe the infrastructure we developed to perform reverse phenotyping studies, including aggregating a super-cohort of sequenced individuals who consented to recontact for genomic ascertainment research. We assessed 13 studies completed at the National Institutes of Health (NIH) that piloted our reverse phenotyping approach. The studies can be broadly categorized as (1) facilitating novel genotype-disease associations, (2) expanding the phenotypic spectra, or (3) demonstrating ex vivo functional mechanisms of disease. We highlight three examples of reverse phenotyping studies in detail and describe how using a targeted reverse phenotyping approach (as opposed to phenotypic ascertainment or clinical informatics approaches) was crucial to the conclusions reached. Finally, we propose a framework and address challenges to building collaborative genomic ascertainment research programs at other institutions. Our goal is for more researchers to take advantage of this approach, which will expand our understanding of the predictive capability of genomic medicine and increase the opportunity to mitigate genomic disease.
Topics: Phenotype; Genotype; Genome; Genomics; Medical Informatics
PubMed: 36608682
DOI: 10.1016/j.ajhg.2022.12.004 -
Molecular Plant Feb 2020Since whole-genome sequencing of many crops has been achieved, crop functional genomics studies have stepped into the big-data and high-throughput era. However,... (Review)
Review
Since whole-genome sequencing of many crops has been achieved, crop functional genomics studies have stepped into the big-data and high-throughput era. However, acquisition of large-scale phenotypic data has become one of the major bottlenecks hindering crop breeding and functional genomics studies. Nevertheless, recent technological advances provide us potential solutions to relieve this bottleneck and to explore advanced methods for large-scale phenotyping data acquisition and processing in the coming years. In this article, we review the major progress on high-throughput phenotyping in controlled environments and field conditions as well as its use for post-harvest yield and quality assessment in the past decades. We then discuss the latest multi-omics research combining high-throughput phenotyping with genetic studies. Finally, we propose some conceptual challenges and provide our perspectives on how to bridge the phenotype-genotype gap. It is no doubt that accurate high-throughput phenotyping will accelerate plant genetic improvements and promote the next green revolution in crop breeding.
Topics: Crops, Agricultural; Genome, Plant; Genomics; Genotype; Phenomics; Phenotype; Plant Breeding
PubMed: 31981735
DOI: 10.1016/j.molp.2020.01.008 -
Journal of Neurodevelopmental Disorders Feb 2023Recurrent gene dosage disorders impart substantial risk for psychopathology. Yet, understanding that risk is hampered by complex presentations that challenge classical...
BACKGROUND
Recurrent gene dosage disorders impart substantial risk for psychopathology. Yet, understanding that risk is hampered by complex presentations that challenge classical diagnostic systems. Here, we present a suite of generalizable analytic approaches for parsing this clinical complexity, which we illustrate through application to XYY syndrome.
METHOD
We gathered high-dimensional measures of psychopathology in 64 XYY individuals and 60 XY controls, plus additional interviewer-based diagnostic data in the XYY group. We provide the first comprehensive diagnostic description of psychiatric morbidity in XYY syndrome and show how diagnostic morbidity relates to functioning, subthreshold symptoms, and ascertainment bias. We then map behavioral vulnerabilities and resilience across 67 behavioral dimensions before borrowing techniques from network science to resolve the mesoscale architecture of these dimensions and links to observable functional outcomes.
RESULTS
Carriage of an extra Y-chromosome increases risk for diverse psychiatric diagnoses, with clinically impactful subthreshold symptomatology. Highest rates are seen for neurodevelopmental and affective disorders. A lower bound of < 25% of carriers are free of any diagnosis. Dimensional analysis of 67 scales details the profile of psychopathology in XYY, which survives control for ascertainment bias, specifies attentional and social domains as the most impacted, and refutes stigmatizing historical associations between XYY and violence. Network modeling compresses all measured symptom scales into 8 modules with dissociable links to cognitive ability, adaptive function, and caregiver strain. Hub modules offer efficient proxies for the full symptom network.
CONCLUSIONS
This study parses the complex behavioral phenotype of XYY syndrome by applying new and generalizable analytic approaches for analysis of deep-phenotypic psychiatric data in neurogenetic disorders.
Topics: Humans; Male; XYY Karyotype; Sex Chromosome Disorders; Cognition; Phenotype
PubMed: 36803654
DOI: 10.1186/s11689-023-09476-y -
PLoS Computational Biology Jan 2020Functional annotation of genes remains a challenge in fundamental biology and is a limiting factor for translational medicine. Computational approaches have been...
Functional annotation of genes remains a challenge in fundamental biology and is a limiting factor for translational medicine. Computational approaches have been developed to process heterogeneous data into meaningful metrics, but often do not address how findings might be updated when new evidence comes to light. To address this challenge, we describe requirements for a framework for incremental data integration and propose an implementation based on phenotype ontologies and Bayesian probability updates. We apply the framework to quantify similarities between gene annotations and disease profiles. Within this scope, we categorize human diseases according to how well they can be recapitulated by animal models and quantify similarities between human diseases and mouse models produced by the International Mouse Phenotyping Consortium. The flexibility of the approach allows us to incorporate negative phenotypic data to better prioritize candidate genes, and to stratify disease mapping using sex-dependent phenotypes. All our association scores can be updated and we exploit this feature to showcase integration with curated annotations from high-precision assays. Incremental integration is thus a suitable framework for tracking functional annotations and linking to complex human pathology.
Topics: Animals; Computational Biology; Disease Models, Animal; Genetic Predisposition to Disease; Genotype; Humans; Mice; Molecular Sequence Annotation; Phenotype
PubMed: 31986132
DOI: 10.1371/journal.pcbi.1007586