RESUMO
We investigated the effects of 35 inflammatory cytokines on respiratory outcomes, including COVID-19, asthma (atopic and non-atopic), chronic obstructive pulmonary disease (COPD), and pulmonary function indices, using Mendelian randomization and colocalization analyses. The emerging associations were further explored using observational analyses in the UK Biobank. We found an inverse association between genetically predicted macrophage colony stimulating factor (MCSF), soluble intercellular adhesion molecule-1 (sICAM), and soluble vascular cell adhesion molecule-1 with risk of COVID-19 outcomes. sICAM was positively associated with atopic asthma risk, whereas tumor necrosis factor-alfa showed an inverse association. A positive association was shown between interleukin-18 and COPD risk (replicated in observational analysis), whereas an inverse association was shown for interleukin-1 receptor antagonist (IL-1ra). IL-1ra and monocyte chemotactic protein-3 were positively associated with lung function indices, whereas inverse associations were shown for MCSF and interleukin-18 (replicated in observational analysis). Our results point to these cytokines as potential pharmacological targets for respiratory traits.
RESUMO
Thyroid hormones play a critical role in regulation of multiple physiological functions and thyroid dysfunction is associated with substantial morbidity. Here, we use electronic health records to undertake a genome-wide association study of thyroid-stimulating hormone (TSH) levels, with a total sample size of 247,107. We identify 158 novel genetic associations, more than doubling the number of known associations with TSH, and implicate 112 putative causal genes, of which 76 are not previously implicated. A polygenic score for TSH is associated with TSH levels in African, South Asian, East Asian, Middle Eastern and admixed American ancestries, and associated with hypothyroidism and other thyroid disease in South Asians. In Europeans, the TSH polygenic score is associated with thyroid disease, including thyroid cancer and age-of-onset of hypothyroidism and hyperthyroidism. We develop pathway-specific genetic risk scores for TSH levels and use these in phenome-wide association studies to identify potential consequences of pathway perturbation. Together, these findings demonstrate the potential utility of genetic associations to inform future therapeutics and risk prediction for thyroid diseases.
Assuntos
Hipertireoidismo , Hipotireoidismo , Doenças da Glândula Tireoide , Humanos , Tireotropina/genética , Estudo de Associação Genômica Ampla , Doenças da Glândula Tireoide/genética , Hipotireoidismo/genética , Hipertireoidismo/genética , TiroxinaRESUMO
Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.
Assuntos
Pulmão , Doença Pulmonar Obstrutiva Crônica , Humanos , Estudo de Associação Genômica Ampla , Predisposição Genética para Doença/genética , Doença Pulmonar Obstrutiva Crônica/genética , Fumar/efeitos adversos , Fumar/genética , Polimorfismo de Nucleotídeo Único/genéticaRESUMO
Modifications in gene expression determine many of the phenotypic differentiations between closely related species. This is particularly evident in reproductive tissues, where evolution of genes is more rapid, facilitating the appearance of distinct reproductive characteristics which may lead to species isolation and phenotypic variation. Large-scale, comparative analyses of transcript expression levels have been limited until recently by lack of inter-species data mining solutions. Here, by combining expression normalisation across lineages, multivariate statistical analysis, evolutionary rate, and protein-protein interaction analysis, we investigate ortholog transcripts in the male accessory glands and testes across five closely related species in the Anopheles gambiae complex. We first demonstrate that the differentiation by transcript expression is consistent with the known Anopheles phylogeny. Then, through clustering, we discover groups of transcripts with tissue-dependent expression patterns conserved across lineages, or lineage-dependent patterns conserved across tissues. The strongest associations with reproductive function, transcriptional regulatory networks, protein-protein subnetworks, and evolutionary rate are found for the groups of transcripts featuring large expression differences in lineage or tissue-conserved patterns.
Assuntos
Anopheles/genética , Evolução Molecular , Expressão Gênica/genética , Genitália Masculina , Transcriptoma/genética , Animais , Genoma de Inseto/genética , Masculino , Análise Multivariada , Fenótipo , Filogenia , Mapas de Interação de Proteínas/genética , Elementos Reguladores de Transcrição/genéticaRESUMO
The proteome of human brain synapses is highly complex and is mutated in over 130 diseases. This complexity arose from two whole-genome duplications early in the vertebrate lineage. Zebrafish are used in modelling human diseases; however, its synapse proteome is uncharacterized, and whether the teleost-specific genome duplication (TSGD) influenced complexity is unknown. We report the characterization of the proteomes and ultrastructure of central synapses in zebrafish and analyse the importance of the TSGD. While the TSGD increases overall synapse proteome complexity, the postsynaptic density (PSD) proteome of zebrafish has lower complexity than mammals. A highly conserved set of â¼1,000 proteins is shared across vertebrates. PSD ultrastructural features are also conserved. Lineage-specific proteome differences indicate that vertebrate species evolved distinct synapse types and functions. The data sets are a resource for a wide range of studies and have important implications for the use of zebrafish in modelling human synaptic diseases.
Assuntos
Encéfalo/metabolismo , Proteínas do Tecido Nervoso/metabolismo , Proteoma/metabolismo , Proteoma/ultraestrutura , Sinapses/metabolismo , Proteínas de Peixe-Zebra/metabolismo , Animais , Encéfalo/ultraestrutura , Feminino , Duplicação Gênica , Genoma , Masculino , Camundongos , Microscopia Eletrônica de Transmissão , Modelos Biológicos , Proteínas do Tecido Nervoso/genética , Densidade Pós-Sináptica/metabolismo , Proteoma/genética , Especificidade da Espécie , Sinapses/ultraestrutura , Sinaptossomos/metabolismo , Peixe-Zebra , Proteínas de Peixe-Zebra/genéticaRESUMO
De novo assembly of a complete transcriptome without the need for a guiding reference genome is attractive, particularly where the cost and complexity of generating a eukaryote genome is prohibitive. The transcriptome should not however be seen as just a quick and cheap alternative to building a complete genome. Transcriptomics allows the understanding and comparison of spatial and temporal samples within an organism, and allows surveying of multiple individuals or closely related species. De novo assembly in theory allows the building of a complete transcriptome without any prior knowledge of the genome. It also allows the discovery of alternate splice forms of coding RNAs and also non-coding RNAs, which are often missed by proteomic approaches, or are incompletely annotated in genome studies. The limitations of the method are that the generation of a truly complete assembly is unlikely, and so we require some methods for the assessment of the quality and appropriateness of a generated transcriptome. Whilst no single consensus pipeline or tool is agreed as optimal, various algorithms, and easy to use software do exist making transcriptome generation a more common approach. With this expansion of data, questions still exist relating to how do we make these datasets fully discoverable, comparable and most useful to understand complex biological systems?