4 research outputs found

    Whole-exome identifies germline variants in families with obstructive sleep apnea syndrome

    Get PDF
    Background: Obstructive sleep apnea syndrome (OSAS) (OMIM #107650) is characterized by complete or partial obstruction of the upper airways, resulting in periods of sleep associated apnea. OSAS increases morbidity and mortality risk from cardiovascular and cerebrovascular diseases. While heritability of OSAS is estimated at ∼40%, the precise underlying genes remain elusive. Brazilian families with OSAS that follows as seemingly autosomal dominant inheritance pattern were recruited.Methods: The study included nine individuals from two Brazilian families displaying a seemingly autosomal dominant inheritance pattern of OSAS. Whole exome sequencing of germline DNA were analyzed using Mendel, MD software. Variants selected were analyzed using Varstation® with subsequent analyses that included validation by Sanger sequencing, pathogenic score assessment by ACMG criteria, co-segregation analyses (when possible) allele frequency, tissue expression patterns, pathway analyses, effect on protein folding modeling using Swiss-Model and RaptorX.Results: Two families (six affected patients and three unaffected controls) were analyzed. A comprehensive multistep analysis yielded variants in COX20 (rs946982087) (family A), PTPDC1 (rs61743388) and TMOD4 (rs141507115) (family B) that seemed to be strong candidate genes for being OSAS associated genes in these families.Conclusion: Sequence variants in COX20, PTPDC1 and TMOD4 seemingly are associated with OSAS phenotype in these families. Further studies in more, ethnically diverse families and non-familial OSAS cases are needed to better define the role of these variants as contributors to OSAS phenotype

    Identification of driver genes for critical forms of COVID-19 in a deeply phenotyped young patient cohort

    No full text
    International audienceThe etiopathogenesis of critical COVID-19 remains unknown. Indeed given major confounding factors (age and comorbidities), true drivers of this condition have remained elusive. Here, we employ an unprecedented multi-omics analysis, combined with artificial intelligence, in a young patient cohort where major comorbidities have been excluded at the onset. Here, we established a three-tier cohort of individuals younger than 50 years without major comorbidities. These included 47 “critical” (in the ICU under mechanical ventilation) and 25 “non-critical” (in a non-critical care ward) COVID-19 patients as well as 22 healthy individuals. The analyses included whole-genome sequencing, whole-blood RNA sequencing, plasma and blood mononuclear cells proteomics, cytokine profiling and high-throughput immunophenotyping. An ensemble of machine learning, deep learning, quantum annealing and structural causal modeling led to key findings. Critical patients were characterized by exacerbated inflammation, perturbed lymphoid/myeloid compartments, coagulation and viral cell biology. Within a unique gene signature that differentiated critical from non-critical patients, several driver genes promoted critical COVID-19 among which the upregulated metalloprotease ADAM9 was key. This gene signature was supported in a second independent cohort of 81 critical and 73 recovered COVID-19 patients, as were ADAM9 transcripts, soluble form and proteolytic activity. Ex vivo ADAM9 inhibition affected SARS-CoV-2 uptake and replication in human lung epithelial cells. In conclusion, within a young, otherwise healthy, COVID-19 cohort, we provide the landscape of biological perturbations in vivo where a unique gene signature differentiated critical from non-critical patients. The key driver, ADAM9, interfered with SARS-CoV-2 biology. A repositioning strategy for anti-ADAM9 therapeutic is feasible

    NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

    No full text
    Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data

    NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

    No full text
    Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data
    corecore