838 resultados para Non-genetic factors


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To collect information about the genetic diversity of the plankton community and to study how plankton respond to environmental conditions, plankton samples were collected from five stations representing different trophic levels in a shallow, eutrophic lake (Lake Donghu), and investigated by PCR-DGGE fingerprinting. A total of 100 bands (61 of 16S rDNA bands and 39 of 18S rDNA bands) were detected. The DGGE bands unique to any single station accounted for 38% of the total bands, whereas common bands detected at all five stations accounted for only 11%. Using UPGMA clustering and MDS ordination of DGGE fingerprints, stations I and II were found to initially group together into one cluster, which was later joined by station V. Stations III and IV were isolated into two separate groups of one station each. Some differences in grouping relationships were found when analysis was completed on the basis of chemical characteristics and morphological composition, with zooplankton composition showing the greatest variability. However, the most similar stations (I and II) were always initially grouped into one cluster. Moreover, stations that exhibited the same or similar trophic level (stations III and IV), but different concentrations of heavy metals, were further differentiated by the DGGE method. Results of the present study indicated that PCR-DGGE fingerprinting was more sensitive than the traditional methods, as other studies suggested. Additionally, PCR-DGGE appears to be more appropriate for diversity characterization of the plankton community, as it is more canonical, systematic, and effective. Most importantly, fingerprinting results are more convenient for the comparative analyses between different studies. Therefore, the use of the described fingerprinting analysis may provide an operable and sensitive biomonitoring approach to identify critical, and potentially negative, stress within an aquatic ecosystem.

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The genetic structure of populations of the fish cestode, Bothriocephalus acheilognathi collected from Bailianhe Reservoir (BLH), Changshou (CSH) and Liangzi (LZH) Lakes was investigated by using 8 microsatellite loci. A total of 108 adult worms were genotyped at each of the 8 loci. For the 3 populations, the mean number of alleles per locus ranged from 2.38 to 5.5, and the mean expected heterozygosity ranged from 0.432 to 0.559. The average polymorphic information content (PIC) was from 0.384 to 0.492. The significant F-is values indicated non-random mating within LZH and BLH populations. On the other hand, when samples were further classified into subpopulations at the level of host fish species, no or little heterozygote deficiency was detected at most loci, showing that cross-fertilization, predominantly, but not exclusively, must have occurred within the subpopulations. Microsatellite markers also revealed an unexpected high level of genetic differentiation, as measured by R-st and N-m values or by deltau(2) genetic distance among subpopulations from different hosts. Factors influencing the population genetic structure and the parasite host specificity are discussed.

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Transient overexpression of defined combinations of master regulator genes can effectively induce cellular reprogramming: the acquisition of an alternative predicted phenotype from a differentiated cell lineage. This can be of particular importance in cardiac regenerative medicine wherein the heart lacks the capacity to heal itself, but simultaneously contains a large pool of fibroblasts. In this study we determined the cardio-inducing capacity of ten transcription factors to actuate cellular reprogramming of mouse embryonic fibroblasts into cardiomyocyte-like cells. Overexpression of transcription factors MYOCD and SRF alone or in conjunction with Mesp1 and SMARCD3 enhanced the basal but necessary cardio-inducing effect of the previously reported GATA4, TBX5, and MEF2C. In particular, combinations of five or seven transcription factors enhanced the activation of cardiac reporter vectors, and induced an upregulation of cardiac-specific genes. Global gene expression analysis also demonstrated a significantly greater cardio-inducing effect when the transcription factors MYOCD and SRF were used. Detection of cross-striated cells was highly dependent on the cell culture conditions and was enhanced by the addition of valproic acid and JAK inhibitor. Although we detected Ca(2+) transient oscillations in the reprogrammed cells, we did not detect significant changes in resting membrane potential or spontaneously contracting cells. This study further elucidates the cardio-inducing effect of the transcriptional networks involved in cardiac cellular reprogramming, contributing to the ongoing rational design of a robust protocol required for cardiac regenerative therapies.

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Aims/hypothesis: Diabetic nephropathy, characterised by persistent proteinuria, hypertension and progressive kidney failure, affects a subset of susceptible individuals with diabetes. It is also a leading cause of end-stage renal disease (ESRD). Non-synonymous (ns) single nucleotide polymorphisms (SNPs) have been reported to contribute to genetic susceptibility in both monogenic disorders and common complex diseases. The objective of this study was to investigate whether nsSNPs are involved in susceptibility to diabetic nephropathy using a case-control design.

Methods: White type 1 diabetic patients with (cases) and without (controls) nephropathy from eight centres in the UK and Ireland were genotyped for a selected subset of nsSNPs using Illumina's GoldenGate BeadArray assay. A ? 2 test for trend, stratified by centre, was used to assess differences in genotype distribution between cases and controls. Genomic control was used to adjust for possible inflation of test statistics, and the False Discovery Rate method was used to account for multiple testing.

Results: We assessed 1,111 nsSNPs for association with diabetic nephropathy in 1,711 individuals with type 1 diabetes (894 cases, 817 controls). A number of SNPs demonstrated a significant difference in genotype distribution between groups before but not after correction for multiple testing. Furthermore, neither subgroup analysis (diabetic nephropathy with ESRD or diabetic nephropathy without ESRD) nor stratification by duration of diabetes revealed any significant differences between groups.

Conclusions/interpretation: The nsSNPs investigated in this study do not appear to contribute significantly to the development of diabetic nephropathy in patients with type 1 diabetes.

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BRCA1/2 test decliners/deferrers have received almost no attention in the literature and this is the first study of this population in the United Kingdom. The aim of this multicenter study is to examine the attributes of a group of individuals offered predictive genetic testing for breast/ovarian cancer predisposition who did not wish to proceed with testing at the time of entry into this study. This forms part of a larger study involving 9 U.K. centers investigating the psychosocial impact of predictive genetic testing for BRCA1/2. Cancer worry and reasons for declining or deferring BRCA1/2 predictive genetic testing were evaluated by questionnaire following genetic counseling. A total of 34 individuals declined the offer of predictive genetic testing. Compared to the national cohort of test acceptors, test decliners are significantly younger. Female test decliners have lower levels of cancer worry than female test acceptors. Barriers to testing include apprehension about the result, traveling to the genetics clinic, and taking time away from work/family. Women are more likely than men to worry about receiving less screening if found not to be a carrier. The findings do not indicate that healthy BRCA1/2 test decliners are a more vulnerable group in terms of cancer worry. However, barriers to testing need to be discussed in genetic counseling.

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BACKGROUND: The genetic basis for developing asthma has been extensively studied. However, association studies to date have mostly focused on mild to moderate disease and genetic risk factors for severe asthma remain unclear. OBJECTIVE: To identify common genetic variants affecting susceptibility to severe asthma. METHODS: A genome-wide association study was undertaken in 933 European ancestry individuals with severe asthma based on Global Initiative for Asthma (GINA) criteria 3 or above and 3346 clean controls. After standard quality control measures, the association of 480?889 genotyped single nucleotide polymorphisms (SNPs) was tested. To improve the resolution of the association signals identified, non-genotyped SNPs were imputed in these regions using a dense reference panel of SNP genotypes from the 1000 Genomes Project. Then replication of SNPs of interest was undertaken in a further 231 cases and 1345 controls and a meta-analysis was performed to combine the results across studies. RESULTS: An association was confirmed in subjects with severe asthma of loci previously identified for association with mild to moderate asthma. The strongest evidence was seen for the ORMDL3/GSDMB locus on chromosome 17q12-21 (rs4794820, p=1.03×10((-8)) following meta-analysis) meeting genome-wide significance. Strong evidence was also found for the IL1RL1/IL18R1 locus on 2q12 (rs9807989, p=5.59×10((-8)) following meta-analysis) just below this threshold. No novel loci for susceptibility to severe asthma met strict criteria for genome-wide significance. CONCLUSIONS: The largest genome-wide association study of severe asthma to date was carried out and strong evidence found for the association of two previously identified asthma susceptibility loci in patients with severe disease. A number of novel regions with suggestive evidence were also identified warranting further study.

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Diabetes is increasing at daunting rates worldwide, and approximately 40% of affected individuals will develop kidney complications. Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease, and there are significant healthcare costs providing appropriate renal replacement therapies to affected individuals. For several decades, investigators have sought to discover inherited risk factors and biomarkers for DKD. In recent years, advances in high-throughput laboratory techniques and computational analyses, coupled with the establishment of multicenter consortia, have helped to identify genetic loci that are replicated across multiple populations. Several genome-wide association studies (GWAS) have been conducted for DKD with further meta-analysis of GWAS and comprehensive ”single gene” meta-analyses now published. Despite these efforts, much of the inherited predisposition to DKD remains unexplained. Meta-analyses and integrated–omics pathway studies are being used to help elucidate underlying genetic risks. Epigenetic phenomena are increasingly recognized as important drivers of disease risk, and several epigenome-wide association studies have now been completed. This review describes key findings and ongoing genetic and epigenetic initiatives for DKD.

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Background: More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.

Methods: Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5-18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.

Results: Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50-59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.

Conclusions: Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.

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Chronic kidney disease (CKD) has become a serious public health problem because of its associated morbidity, premature mortality and attendant healthcare costs. The rising number of persons with CKD is linked with ageing population structure and an increased prevalence of diabetes, hypertension and obesity. There is an inherited risk associated with developing CKD as evidenced by familial clustering and differing prevalence rates across ethnic groups. Earlier studies to determine the inherited risk factors for CKD rarely identified genetic variants that were robustly replicated. However, improvements in genotyping technologies and analytical methods are now helping to identify promising genetic loci aided by international collaboration and multi-consortia efforts. More recently, epigenetic modifications have been proposed to play a role in both the inherited susceptibility to CKD and, importantly, to explain how the environment dynamically interacts with the genome to alter an individual's disease risk. Genome-wide, epigenome-wide and whole transcriptome studies have been performed and optimal approaches for integrative analysis are being developed. This review summarises recent research and the current status of genetic and epigenetic risk factors influencing CKD using population-based information.