RESUMO
Alzheimer's disease (AD) is a common neurodegenerative disease with high morbidity among elderly people. A genetic attribution has been extensively proved. Here, we propose to further prioritize genes that harbor single nucleotide variation (SNV) or structural variation (SV) for AD and explore the underlying potential mechanisms through exploiting their expression and methylation spectra. A high-confidence AD-associated candidate gene list was obtained from the ClinVar and Human Gene Mutation Database (HGMD). Genome-wide methylation and expression profiles of AD and normal subjects were downloaded from the Gene Expression Omnibus (GEO). Through comprehensive comparison of expression and methylation levels between AD and normal samples, as well as different stages of AD samples, SORL1 was identified as the most plausible gene for AD incidence and progression. Gene Set Enrichment Analysis (GSEA) revealed significant activation of the ABC (ATP binding cassette) transporter with the aberrant up-regulation of SORL1 within AD samples. This study unfolds the expression and methylation spectra of previously probed genes with SNV or SV in AD for the first time, and reports an aberrant activation of the ABC transporter pathway that might contribute to AD progression. This should shed some light on AD diagnosis and precision treatment.
Assuntos
Transportadores de Cassetes de Ligação de ATP/metabolismo , Doença de Alzheimer/patologia , Proteínas Relacionadas a Receptor de LDL/metabolismo , Proteínas de Membrana Transportadoras/metabolismo , Transportadores de Cassetes de Ligação de ATP/genética , Doença de Alzheimer/genética , Doença de Alzheimer/metabolismo , Metilação de DNA , Bases de Dados Genéticas , Regulação para Baixo , Humanos , Proteínas Relacionadas a Receptor de LDL/genética , Proteínas de Membrana Transportadoras/genética , Polimorfismo de Nucleotídeo ÚnicoRESUMO
PURPOSE: The present study aimed to investigate the comprehensive differential expression profile of microRNAs (miRNAs) by screening for miRNA expression in ischemic stroke and normal samples. METHODS: Differentially expressed miRNA (DEM) analysis was conducted using limma R Bioconductor package. Target genes of DEMs were identified from TargetScanHuman and miRTarBase databases. Functional enrichment analysis of the target genes was performed using clusterProfiler R Bioconductor package. The miRNA-based ischemic stroke diagnostic signature was constructed via logistic regression analysis. RESULTS: Compared with the normal cohort, a total of 14 DEMs, including 5 up-regulated miRNAs and 9 down-regulated miRNAs, were identified in ischemic stroke patients. These DEMs have 1600 regulatory targets. Using a logistic regression model, the top five miRNAs were screened for constructing an miRNA-based ischemic stroke diagnostic signature. Using the miRNA-mRNA interaction pairs, two target genes (specificity protein 1 (SP1) and Argonaute 1 (AGO1)) were speculated to be the primary genes of ischemic stroke. DISCUSSION AND CONCLUSION: Here, several potential miRNAs biomarkers were identified and an miRNA-based diagnostic signature for ischemic stroke was established, which can be a valuable reference for future clinical researches.
Assuntos
Biologia Computacional , Perfilação da Expressão Gênica , AVC Isquêmico/diagnóstico , MicroRNAs/genética , Transcriptoma , Proteínas Argonautas/genética , Estudos de Casos e Controles , Bases de Dados Genéticas , Fatores de Iniciação em Eucariotos/genética , Redes Reguladoras de Genes , Humanos , AVC Isquêmico/genética , Modelos Logísticos , Aprendizado de Máquina , Valor Preditivo dos Testes , Medição de Risco , Fatores de Risco , Fator de Transcrição Sp1/genéticaRESUMO
BACKGROUND: This study aims to present the trends of incidence and mortality of kidney cancer from 1990 to 2016 by age, gender, geographical region, regional, and sociodemographic index (SDI), and then forecast the future trends to 2030. METHODS: Data of this study were gathered from the Global Burden of Disease Study (GBD), including 195 countries and territories, accounting for 21 regions. Over-time trends from 1990 to 2016 were analyzed by gender, geographical region, age range and SDI. Based on the big data, we forecasted the future trends to 2030 by ARIMA model. All the data were analyzed by R software (x64 version 3.5.1), SAS (version 9.3) and SPSS (version 22.0). RESULTS: Globally, in 2016, there were 342,100 [95% uncertainty interval (UI), 330,759-349,934] incident cases of kidney cancer and the number of deaths were 131,800 (127,335-136,185). The age-standardized incidence rate (ASIR) and death rate (ASDR) were 4.97 (4.81-5.09) per 100,000 and 2.00 (1.93-2.06) per 100,000, respectively. Globally, the estimated risk of kidney cancer for male within the age of 30 and 70 is around 0.79% compared to 0.41% for female. In other words, the probability of developing kidney cancer was generally higher in male than in female. By 2030, incidence of kidney cancer in both sexes are projected to increase substantially in high SDI, followed by middle SDI, low-middle SDI, and low SDI countries. High SDI and low SDI countries will also have increased mortality rates of kidney cancers. Globally, the trends in deaths due to kidney cancer will remain stable. CONCLUSIONS: The incidence and death rate of kidney cancer are highly variable among SDI countries and regions but have increased uniformly from 1990 to 2016. By 2030, the future incidence of kidney cancer will grow continuously especially in high SDI countries, middle SDI, low-middle SDI, and low SDI countries.