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1.
Soins ; 65(843-844): 37-39, 2020.
Artigo em Francês | MEDLINE | ID: mdl-32563506

RESUMO

When the body fails a person's foundations are damaged. The wait for a diagnosis, the physical pain, the chronic disease weaken the patient who may be overwhelmed by fears and anxiety. For patients from another country, this distressing experience adds to their vulnerability inherent to the separation from the home country the effects of which are intensified when illness strikes.


Assuntos
Doença/psicologia , Migrantes/psicologia , Ansiedade , Características Culturais , Medo , Humanos , Angústia Psicológica
2.
Stud Health Technol Inform ; 270: 267-271, 2020 Jun 16.
Artigo em Inglês | MEDLINE | ID: mdl-32570388

RESUMO

Information relevant to pharmacogenomics studies is available in several open databases, which makes it difficult to synthetize the available data. Within the PractikPharma project, several databases were integrated to PGxLOD, a resource dedicated to the generation and verification of pharmacogenomic influence on drug responses. The Comparative Toxicogenomic Database (CTD) describes the toxic effects of many chemicals on living species based on the literature. Since drugs are peculiar chemicals and side effects are peculiar toxic effects, we aimed at extracting information from CTD that matches drug side effects in the human specie.


Assuntos
Doença/etiologia , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Substâncias Perigosas/toxicidade , Farmacogenética , Toxicogenética , Bases de Dados Factuais , Doença/genética , Humanos , Pesquisa , Integração de Sistemas
3.
PLoS Comput Biol ; 16(5): e1007775, 2020 05.
Artigo em Inglês | MEDLINE | ID: mdl-32413045

RESUMO

The human genome harbors a variety of genetic variations. Single-nucleotide changes that alter amino acids in protein-coding regions are one of the major causes of human phenotypic variation and diseases. These single-amino acid variations (SAVs) are routinely found in whole genome and exome sequencing. Evaluating the functional impact of such genomic alterations is crucial for diagnosis of genetic disorders. We developed DeepSAV, a deep-learning convolutional neural network to differentiate disease-causing and benign SAVs based on a variety of protein sequence, structural and functional properties. Our method outperforms most stand-alone programs, and the version incorporating population and gene-level information (DeepSAV+PG) has similar predictive power as some of the best available. We transformed DeepSAV scores of rare SAVs in the human population into a quantity termed "mutation severity measure" for each human protein-coding gene. It reflects a gene's tolerance to deleterious missense mutations and serves as a useful tool to study gene-disease associations. Genes implicated in cancer, autism, and viral interaction are found by this measure as intolerant to mutations, while genes associated with a number of other diseases are scored as tolerant. Among known disease-associated genes, those that are mutation-intolerant are likely to function in development and signal transduction pathways, while those that are mutation-tolerant tend to encode metabolic and mitochondrial proteins.


Assuntos
Doença/genética , Previsões/métodos , Genoma Humano/genética , Alelos , Sequência de Aminoácidos/genética , Biologia Computacional/métodos , Aprendizado Profundo , Redes Reguladoras de Genes/genética , Humanos , Mutação/genética , Mutação de Sentido Incorreto/genética , Rede Nervosa , Fases de Leitura Aberta/genética , Análise de Sequência/métodos , Sequenciamento Completo do Exoma/métodos
4.
Nat Commun ; 11(1): 2073, 2020 04 29.
Artigo em Inglês | MEDLINE | ID: mdl-32350270

RESUMO

Functional variomics provides the foundation for personalized medicine by linking genetic variation to disease expression, outcome and treatment, yet its utility is dependent on appropriate assays to evaluate mutation impact on protein function. To fully assess the effects of 106 missense and nonsense variants of PTEN associated with autism spectrum disorder, somatic cancer and PTEN hamartoma syndrome (PHTS), we take a deep phenotypic profiling approach using 18 assays in 5 model systems spanning diverse cellular environments ranging from molecular function to neuronal morphogenesis and behavior. Variants inducing instability occur across the protein, resulting in partial-to-complete loss-of-function (LoF), which is well correlated across models. However, assays are selectively sensitive to variants located in substrate binding and catalytic domains, which exhibit complete LoF or dominant negativity independent of effects on stability. Our results indicate that full characterization of variant impact requires assays sensitive to instability and a range of protein functions.


Assuntos
Doença/genética , Modelos Genéticos , Mutação de Sentido Incorreto/genética , PTEN Fosfo-Hidrolase/genética , Animais , Comportamento Animal , Caenorhabditis elegans/fisiologia , Células Cultivadas , Dendritos/fisiologia , Drosophila/genética , Drosophila/crescimento & desenvolvimento , Ensaios Enzimáticos , Células HEK293 , Humanos , Neoplasias/genética , Sistema Nervoso/crescimento & desenvolvimento , Fosforilação , Estabilidade Proteica , Proteínas Proto-Oncogênicas c-akt/metabolismo , Células Piramidais/metabolismo , Ratos Sprague-Dawley , Saccharomyces cerevisiae/metabolismo
5.
BMC Bioinformatics ; 21(1): 180, 2020 May 11.
Artigo em Inglês | MEDLINE | ID: mdl-32393162

RESUMO

BACKGROUND: In recent years, increasing evidences have indicated that long non-coding RNAs (lncRNAs) are deeply involved in a wide range of human biological pathways. The mutations and disorders of lncRNAs are closely associated with many human diseases. Therefore, it is of great importance to predict potential associations between lncRNAs and complex diseases for the diagnosis and cure of complex diseases. However, the functional mechanisms of the majority of lncRNAs are still remain unclear. As a result, it remains a great challenge to predict potential associations between lncRNAs and diseases. RESULTS: Here, we proposed a new method to predict potential lncRNA-disease associations. First, we constructed a bipartite network based on known associations between diseases and lncRNAs/protein coding genes. Then the cluster association scores were calculated to evaluate the strength of the inner relationships between disease clusters and gene clusters. Finally, the gene-disease association scores are defined based on disease-gene cluster association scores and used to measure the strength for potential gene-disease associations. CONCLUSIONS: Leave-One Out Cross Validation (LOOCV) and 5-fold cross validation tests were implemented to evaluate the performance of our method. As a result, our method achieved reliable performance in the LOOCV (AUCs of 0.8169 and 0.8410 based on Yang's dataset and Lnc2cancer 2.0 database, respectively), and 5-fold cross validation (AUCs of 0.7573 and 0.8198 based on Yang's dataset and Lnc2cancer 2.0 database, respectively), which were significantly higher than the other three comparative methods. Furthermore, our method is simple and efficient. Only the known gene-disease associations are exploited in a graph manner and further new gene-disease associations can be easily incorporated in our model. The results for melanoma and ovarian cancer have been verified by other researches. The case studies indicated that our method can provide informative clues for further investigation.


Assuntos
Biologia Computacional/métodos , Doença/genética , Predisposição Genética para Doença , RNA Longo não Codificante/genética , Algoritmos , Área Sob a Curva , Análise por Conglomerados , Humanos , Neoplasias/genética
6.
Adv Exp Med Biol ; 1253: 3-55, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32445090

RESUMO

Epigenetic mechanisms, which include DNA methylation, histone modification, and microRNA (miRNA), can produce heritable phenotypic changes without a change in DNA sequence. Disruption of gene expression patterns which are governed by epigenetics can result in autoimmune diseases, cancers, and various other maladies. Mechanisms of epigenetics include DNA methylation (and demethylation), histone modifications, and non-coding RNAs such as microRNAs. Compared to numerous studies that have focused on the field of genetics, research on epigenetics is fairly recent. In contrast to genetic changes, which are difficult to reverse, epigenetic aberrations can be pharmaceutically reversible. The emerging tools of epigenetics can be used as preventive, diagnostic, and therapeutic markers. With the development of drugs that target the specific epigenetic mechanisms involved in the regulation of gene expression, development and utilization of epigenetic tools are an appropriate and effective approach that can be clinically applied to the treatment of various diseases.


Assuntos
Doença/genética , Epigênese Genética , Saúde , Animais , Metilação de DNA , Epigenômica , Código das Histonas , Humanos , MicroRNAs
7.
Adv Exp Med Biol ; 1253: 57-94, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32445091

RESUMO

The study of epigenetics has its roots in the study of organism change over time and response to environmental change, although over the past several decades the definition has been formalized to include heritable alterations in gene expression that are not a result of alterations in underlying DNA sequence. In this chapter, we discuss first the history and milestones in the 100+ years of epigenetic study, including early discoveries of DNA methylation, histone posttranslational modification, and noncoding RNA. We then discuss how epigenetics has changed the way that we think of both health and disease, offering as examples studies examining the epigenetic contributions to aging, including the recent development of an epigenetic "clock", and explore how antiaging therapies may work through epigenetic modifications. We then discuss a nonpathogenic role for epigenetics in the clinic: epigenetic biomarkers. We conclude by offering two examples of modern state-of-the-art integrated multi-omics studies of epigenetics in disease pathogenesis, one which sought to capture shared mechanisms among multiple diseases, and another which used epigenetic big data to better understand the pathogenesis of a single tissue from one disease.


Assuntos
Doença/genética , Epigênese Genética , Epigenômica , Animais , Metilação de DNA , Código das Histonas , Humanos , RNA não Traduzido
8.
BMC Bioinformatics ; 21(1): 176, 2020 May 04.
Artigo em Inglês | MEDLINE | ID: mdl-32366225

RESUMO

BACKGROUND: As regulators of gene expression, microRNAs (miRNAs) are increasingly recognized as critical biomarkers of human diseases. Till now, a series of computational methods have been proposed to predict new miRNA-disease associations based on similarity measurements. Different categories of features in miRNAs are applied in these methods for miRNA-miRNA similarity calculation. Benchmarking tests on these miRNA similarity measures are warranted to assess their effectiveness and robustness. RESULTS: In this study, 5 categories of features, i.e. miRNA sequences, miRNA expression profiles in cell-lines, miRNA expression profiles in tissues, gene ontology (GO) annotations of miRNA target genes and Medical Subject Heading (MeSH) terms of miRNA-associated diseases, are collected and similarity values between miRNAs are quantified based on these feature spaces, respectively. We systematically compare the 5 similarities from multi-statistical views. Furthermore, we adopt a rule-based inference method to test their performance on miRNA-disease association predictions with the similarity measurements. Comprehensive comparison is made based on leave-one-out cross-validations and a case study. Experimental results demonstrate that the similarity measurement using MeSH terms performs best among the 5 measurements. It should be noted that the other 4 measurements can also achieve reliable prediction performance. The best-performed similarity measurement is used for new miRNA-disease association predictions and the inferred results are released for further biomedical screening. CONCLUSIONS: Our study suggests that all the 5 features, even though some are restricted by data availability, are useful information for inferring novel miRNA-disease associations. However, biased prediction results might be produced in GO- and MeSH-based similarity measurements due to incomplete feature spaces. Similarity fusion may help produce more reliable prediction results. We expect that future studies will provide more detailed information into the 5 feature spaces and widen our understanding about disease pathogenesis.


Assuntos
Doença/genética , MicroRNAs/genética , Algoritmos , Biomarcadores/análise , Biologia Computacional/métodos , Ontologia Genética , Humanos , MicroRNAs/metabolismo , Prognóstico
10.
Chiropr Man Therap ; 28(1): 24, 2020 05 11.
Artigo em Inglês | MEDLINE | ID: mdl-32393394

RESUMO

BACKGROUND: Internet analytics are increasingly being integrated into public health regulation. One specific application is to monitor compliance of website and social media activity with respect to jurisdictional regulations. These data may then identify breaches of compliance and inform disciplinary actions. Our study aimed to evaluate the novel use of internet analytics by a Canadian chiropractic regulator to determine their registrants compliance with three regulations related to specific health conditions, pregnancy conditions and most recently, claims of improved immunity during the COVID-19 crisis. METHODS: A customized internet search tool (Market Review Tool, MRT) was used by the College of Chiropractors of British Columbia (CCBC), Canada to audit registrants websites and social media activity. The audits extracted words whose use within specific contexts is not permitted under CCBC guidelines. The MRT was first used in October of 2018 to identify words related to specific health conditions. The MRT was again used in December 2019 for words related to pregnancy and most recently in March 2020 for words related to COVID-19. In these three MRT applications, potential cases of word misuse were evaluated by the regulator who then notified the practitioner to comply with existing regulations by a specific date. The MRT was then used on that date to determine compliance. Those found to be non-compliant were referred to the regulator's inquiry committee. We mapped this process and reported the outcomes with permission of the regulator. RESULTS: In September 2018, 250 inappropriate mentions of specific health conditions were detected from approximately 1250 registrants with 2 failing to comply. The second scan for pregnancy related terms of approximately1350 practitioners revealed 83 inappropriate mentions. Following notification, all 83 cases were compliant within the specified timeframe. Regarding COVID-19 related words, 97 inappropriate mentions of the word "immune" were detected from 1350 registrants with 7 cases of non-compliance. CONCLUSION: Internet analytics are an effective way for regulators to monitor internet activity to protect the public from misleading statements. The processes described were effective at bringing about rapid practitioner compliance. Given the increasing volume of internet activity by healthcare professionals, internet analytics are an important addition for health care regulators to protect the public they serve.


Assuntos
Quiroprática/legislação & jurisprudência , Comunicação , Internet , Saúde Pública/legislação & jurisprudência , Canadá/epidemiologia , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/imunologia , Doença , Feminino , Humanos , Pandemias , Pneumonia Viral/epidemiologia , Pneumonia Viral/imunologia , Gravidez
11.
Adv Exp Med Biol ; 1254: 87-103, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32323272

RESUMO

B cells are typically characterized by their ability to produce antibodies, function as secondary antigen-present cells, and produce various immunoregulatory cytokines. The regulatory B (Breg)-cell population is now widely accepted as an important modulatory component of the immune system that suppresses inflammation. Recent studies indicate that Breg-cell populations are small under physiological conditions but expand substantially in both human patients and murine models of chronic inflammatory diseases, autoimmune diseases, infection, transplantation, and cancer. Almost all B-cell subsets can be induced to form Breg cells. In addition, there are unique Breg-cell subsets such as B10 and Tim-1+ B cells. Immunoregulatory function may be mediated by production of cytokines such as IL-10 and TGF-ß and ensuing suppression of T cells, by direct cell-cell interactions, and (or) by altering the immune microenvironment. In this chapter, we describe in detail the discovery of Breg cells, their phenotypes, differentiation, function, contributions to disease, and therapeutic potential.


Assuntos
Linfócitos B Reguladores , Animais , Doença , Humanos , Interleucina-10 , Linfócitos T , Fator de Crescimento Transformador beta
12.
Nat Commun ; 11(1): 1738, 2020 04 08.
Artigo em Inglês | MEDLINE | ID: mdl-32269218

RESUMO

A complex interplay of metabolic and immunological mechanisms underlies many diseases that represent a substantial unmet medical need. There is an increasing appreciation of the role microbes play in human health and disease, and evidence is accumulating that a new class of live biotherapeutics comprised of engineered microbes could address specific mechanisms of disease. Using the tools of synthetic biology, nonpathogenic bacteria can be designed to sense and respond to environmental signals in order to consume harmful compounds and deliver therapeutic effectors. In this perspective, we describe considerations for the design and development of engineered live biotherapeutics to achieve regulatory and patient acceptance.


Assuntos
Bactérias/genética , Doença , Engenharia Genética , Biomarcadores/metabolismo , Trato Gastrointestinal/microbiologia , Humanos , Neoplasias/terapia
13.
Am J Hum Genet ; 106(5): 611-622, 2020 05 07.
Artigo em Inglês | MEDLINE | ID: mdl-32275883

RESUMO

Population-scale biobanks that combine genetic data and high-dimensional phenotyping for a large number of participants provide an exciting opportunity to perform genome-wide association studies (GWAS) to identify genetic variants associated with diverse quantitative traits and diseases. A major challenge for GWAS in population biobanks is ascertaining disease cases from heterogeneous data sources such as hospital records, digital questionnaire responses, or interviews. In this study, we use genetic parameters, including genetic correlation, to evaluate whether GWAS performed using cases in the UK Biobank ascertained from hospital records, questionnaire responses, and family history of disease implicate similar disease genetics across a range of effect sizes. We find that hospital record and questionnaire GWAS largely identify similar genetic effects for many complex phenotypes and that combining together both phenotyping methods improves power to detect genetic associations. We also show that family history GWAS using cases ascertained on family history of disease agrees with combined hospital record and questionnaire GWAS and that family history GWAS has better power to detect genetic associations for some phenotypes. Overall, this work demonstrates that digital phenotyping and unstructured phenotype data can be combined with structured data such as hospital records to identify cases for GWAS in biobanks and improve the ability of such studies to identify genetic associations.


Assuntos
Doença/genética , Estudo de Associação Genômica Ampla , Fenótipo , Asma/genética , Bases de Dados Factuais , Feminino , Genética Médica , Genótipo , Humanos , Masculino , Neoplasias/genética , Reino Unido
14.
Sheng Li Xue Bao ; 72(2): 227-234, 2020 Apr 25.
Artigo em Chinês | MEDLINE | ID: mdl-32328616

RESUMO

Adrenergic receptor (AR), one of the key receptors for nervous system, plays an important role in the immune microenvironment and the progression of many diseases. In recent years, the regulation of ARs and its signal on macrophages has become a research hotspot. Researchers found that ARs could exert different regulatory functions on macrophages in different microenvironments, which in turn affects occurrence and development of diseases such as tumor, heart failure, obesity, acute injury, infection and pregnancy-related diseases. This review summarizes the expression and functional regulation of ARs on macrophages, and the role of ARs in microenvironment of related diseases, which might provide new ideas for the treatments.


Assuntos
Doença , Macrófagos/fisiologia , Receptores Adrenérgicos/fisiologia , Transdução de Sinais , Humanos
15.
PLoS One ; 15(4): e0231333, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32320422

RESUMO

There is a strong and continuously growing interest in using large electronic healthcare databases to study health outcomes and the effects of pharmaceutical products. However, concerns regarding disease misclassification (i.e. classification errors of the disease status) and its impact on the study results are legitimate. Validation is therefore increasingly recognized as an essential component of database research. In this work, we elucidate the interrelations between the true prevalence of a disease in a database population (i.e. prevalence assuming no disease misclassification), the observed prevalence subject to disease misclassification, and the most common validity indices: sensitivity, specificity, positive and negative predictive value. Based on this, we obtained analytical expressions to derive all the validity indices and true prevalence from the observed prevalence and any combination of two other parameters. The analytical expressions can be used for various purposes. Most notably, they can be used to obtain an estimate of the observed prevalence adjusted for outcome misclassification from any combination of two validity indices and to derive validity indices from each other which would otherwise be difficult to obtain. To allow researchers to easily use the analytical expressions, we additionally developed a user-friendly and freely available web-application.


Assuntos
Bases de Dados Factuais , Doença/classificação , Algoritmos , Registros Eletrônicos de Saúde , Humanos , Interface Usuário-Computador
16.
PLoS One ; 15(4): e0231059, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32251458

RESUMO

Diseases involve complex modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disease. Hence, new biological knowledge about a disease can be extracted from these profiles, improving our ability to diagnose and assess disease risks. This knowledge can be used for drug re-purposing, or by physicians to evaluate a patient's condition and co-morbidity risk. Here, we consider differential gene expressions obtained by microarray technology for patients diagnosed with various diseases. Based on these data and cellular multi-scale organization, we aim at uncovering disease-disease, disease-gene and disease-pathway associations. We propose a neural network with structure based on the multi-scale organization of proteins in a cell into biological pathways. We show that this model is able to correctly predict the diagnosis for the majority of patients. Through the analysis of the trained model, we predict disease-disease, disease-pathway, and disease-gene associations and validate the predictions by comparisons to known interactions and literature search, proposing putative explanations for the predictions.


Assuntos
Biologia Computacional/métodos , Doença/genética , Redes Reguladoras de Genes , Redes Neurais de Computação , Transcriptoma , Comorbidade , Humanos , Modelos Biológicos , Prognóstico , Curva ROC , Transdução de Sinais/genética
17.
BMC Bioinformatics ; 21(1): 135, 2020 Apr 07.
Artigo em Inglês | MEDLINE | ID: mdl-32264950

RESUMO

BACKGROUND: Microarray technology provides the expression level of many genes. Nowadays, an important issue is to select a small number of informative differentially expressed genes that provide biological knowledge and may be key elements for a disease. With the increasing volume of data generated by modern biomedical studies, software is required for effective identification of differentially expressed genes. Here, we describe an R package, called ORdensity, that implements a recent methodology (Irigoien and Arenas, 2018) developed in order to identify differentially expressed genes. The benefits of parallel implementation are discussed. RESULTS: ORdensity gives the user the list of genes identified as differentially expressed genes in an easy and comprehensible way. The experimentation carried out in an off-the-self computer with the parallel execution enabled shows an improvement in run-time. This implementation may also lead to an important use of memory load. Results previously obtained with simulated and real data indicated that the procedure implemented in the package is robust and suitable for differentially expressed genes identification. CONCLUSIONS: The new package, ORdensity, offers a friendly and easy way to identify differentially expressed genes, which is very useful for users not familiar with programming. AVAILABILITY: https://github.com/rsait/ORdensity.


Assuntos
Interface Usuário-Computador , Doença/genética , Regulação da Expressão Gênica , Humanos , Análise de Sequência com Séries de Oligonucleotídeos/métodos , RNA-Seq/métodos
18.
N Engl J Med ; 382(18): 1721-1731, 2020 04 30.
Artigo em Inglês | MEDLINE | ID: mdl-32348643

RESUMO

BACKGROUND: Persons with mental disorders are at a higher risk than the general population for the subsequent development of certain medical conditions. METHODS: We used a population-based cohort from Danish national registries that included data on more than 5.9 million persons born in Denmark from 1900 through 2015 and followed them from 2000 through 2016, for a total of 83.9 million person-years. We assessed 10 broad types of mental disorders and 9 broad categories of medical conditions (which encompassed 31 specific conditions). We used Cox regression models to calculate overall hazard ratios and time-dependent hazard ratios for pairs of mental disorders and medical conditions, after adjustment for age, sex, calendar time, and previous mental disorders. Absolute risks were estimated with the use of competing-risks survival analyses. RESULTS: A total of 698,874 of 5,940,299 persons (11.8%) were identified as having a mental disorder. The median age of the total population was 32.1 years at entry into the cohort and 48.7 years at the time of the last follow-up. Persons with a mental disorder had a higher risk than those without such disorders with respect to 76 of 90 pairs of mental disorders and medical conditions. The median hazard ratio for an association between a mental disorder and a medical condition was 1.37. The lowest hazard ratio was 0.82 for organic mental disorders and the broad category of cancer (95% confidence interval [CI], 0.80 to 0.84), and the highest was 3.62 for eating disorders and urogenital conditions (95% CI, 3.11 to 4.22). Several specific pairs showed a reduced risk (e.g., schizophrenia and musculoskeletal conditions). Risks varied according to the time since the diagnosis of a mental disorder. The absolute risk of a medical condition within 15 years after a mental disorder was diagnosed varied from 0.6% for a urogenital condition among persons with a developmental disorder to 54.1% for a circulatory disorder among those with an organic mental disorder. CONCLUSIONS: Most mental disorders were associated with an increased risk of a subsequent medical condition; hazard ratios ranged from 0.82 to 3.62 and varied according to the time since the diagnosis of the mental disorder. (Funded by the Danish National Research Foundation and others; COMO-GMC ClinicalTrials.gov number, NCT03847753.).


Assuntos
Doença/etiologia , Transtornos Mentais/complicações , Adulto , Doenças Cardiovasculares/etiologia , Estudos de Coortes , Dinamarca/epidemiologia , Feminino , Doenças Urogenitais Femininas/etiologia , Humanos , Masculino , Doenças Urogenitais Masculinas/etiologia , Pessoa de Meia-Idade , Doenças Musculoesqueléticas/etiologia , Neoplasias/etiologia , Risco , Esquizofrenia/complicações , Fatores Sexuais
19.
PLoS Genet ; 16(4): e1008663, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-32243438

RESUMO

Previous studies have surveyed the potential impact of loss-of-function (LoF) variants and identified LoF-tolerant protein-coding genes. However, the tolerance of human genomes to losing enhancers has not yet been evaluated. Here we present the catalog of LoF-tolerant enhancers using structural variants from whole-genome sequences. Using a conservative approach, we estimate that individual human genomes possess at least 28 LoF-tolerant enhancers on average. We assessed the properties of LoF-tolerant enhancers in a unified regulatory network constructed by integrating tissue-specific enhancers and gene-gene interactions. We find that LoF-tolerant enhancers tend to be more tissue-specific and regulate fewer and more dispensable genes relative to other enhancers. They are enriched in immune-related cells while enhancers with low LoF-tolerance are enriched in kidney and brain/neuronal stem cells. We developed a supervised learning approach to predict the LoF-tolerance of all enhancers, which achieved an area under the receiver operating characteristics curve (AUROC) of 98%. We predict 3,519 more enhancers would be likely tolerant to LoF and 129 enhancers that would have low LoF-tolerance. Our predictions are supported by a known set of disease enhancers and novel deletions from PacBio sequencing. The LoF-tolerance scores provided here will serve as an important reference for disease studies.


Assuntos
Elementos Facilitadores Genéticos/genética , Genoma Humano/genética , Mutação com Perda de Função , Sequência Conservada , Doença/genética , Regulação da Expressão Gênica , Predisposição Genética para Doença , Humanos , Especificidade de Órgãos/genética , Curva ROC , Reprodutibilidade dos Testes , Aprendizado de Máquina Supervisionado
20.
PLoS One ; 15(4): e0230684, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32240183

RESUMO

BACKGROUND: This study aimed to characterize trends in absolute and relative socioeconomic inequalities in adult premature mortality between 1992 and 2017, in the context of declining population-wide mortality rates. We conducted a population-based cohort study of all adult premature deaths in Ontario, Canada using provincial vital statistics data linked to census-based, area-level deprivation indices for socioeconomic status. METHODS: The cohort included all individuals eligible for Ontario's single-payer health insurance system at any time between January 1, 1992 and December 31, 2017 with a recorded Ontario place of residence and valid socioeconomic status information (N = 820,370). Deaths between ages 18 and 74 were used to calculate adult premature mortality rates per 1000, stratified by provincial quintile of material deprivation. Relative inequalities were measured using Relative Index of Inequality (RII) measures. Absolute inequalities were estimated using Slope Index of Inequality (SII) measures. All outcome measures were calculated as sex-specific, annual measures for each year from 1992 to 2017. RESULTS: Premature mortality rates declined in all socioeconomic groups between 1992 and 2017. Relative inequalities in premature mortality increased over the same period. Absolute inequalities were mostly stable between 1992 and 2007, but increased dramatically between 2008 and 2017, with larger increases to absolute inequalities seen in females than in males. CONCLUSIONS: As in other developed countries, long-term downward trends in all-cause premature mortality in Ontario, Canada have shifted to a plateau pattern in recent years, especially in lower- socioeconomic status subpopulations. Determinants of this may differ by setting. Regular monitoring of mortality by socioeconomic status is the only way that this phenomenon can be detected sensitively and early, for public health attention and possible corrective action.


Assuntos
Doença/economia , Disparidades nos Níveis de Saúde , Mortalidade Prematura/tendências , Classe Social , Fatores Socioeconômicos , Adolescente , Adulto , Idoso , Causas de Morte , Estudos de Coortes , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Ontário/epidemiologia , Adulto Jovem
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