Variations in discovery-based preeclampsia candidate genes.
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ABSTRACT:
SUBMITTER: Founds SA
PROVIDER: S-EPMC3419489 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Biochemical and biophysical processes that take place in muscle under relaxed and stressed conditions depend on the abundance and activity of gene products of metabolic and structural pathways. In livestock at post-mortem, these muscle properties determine aspects of meat quality and are measurable. The conversion of muscle to meat mimics pathological processes associated with muscle ischemia, injury or damage in humans and it is an economic factor in pork production. Linkage, association, and expression analyses independently contributed to the identification of trait-associated molecular pathways and genes. We aim at providing multiple evidences for the role of specific genes in meat quality by integrating a genome-wide association study (GWAS) for meat quality traits and the detection of eQTL based on trait-correlated expressed genes and trait-associated markers. The GWAS revealed 51 and 200 SNPs significantly associated with meat quality in a crossbred Pietrain×(German Landrace×Large White) (Pi×(GL×LW)) and a purebred German Landrace (GL) population, respectively. Most significant SNPs in Pi×(GL×LW) were located on chromosomes (SSC) 4 and 6. The data of 47,836 eQTLs at a significance level of p<10(-5) were used to scale down the number candidate genes located in these regions. These SNPs on SSC4 showed association with expression levels of ZNF704, IMPA1, and OXSR1; SSC6 SNPs were associated with expression of SIGLEC10 and PIH1D1. Most significant SNPs in GL were located on SSC6 and associated with expression levels of PIH1D1, SIGLEC10, TBCB, LOC100518735, KIF1B, LOC100514845, and two unknown genes. The abundance of transcripts of these genes in muscle, in turn, is significantly correlated with meat quality traits. We identified several genes with evidence for their candidacy for meat quality arising from the integrative approach of a genome-wide association study and eQTL analysis.
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Project description:: Preeclampsia is a pregnancy-specific disorder characterized by the presence of hypertension with the onset of either proteinuria, maternal organ or uteroplacental dysfunction. Preeclampsia is one of the leading causes of maternal and fetal mortality and morbidity worldwide. However, the etiopathologies of preeclampsia are not fully understood. Many studies have indicated that genes are differentially expressed between normal and in the disease state. Hence, this study systematically searched the literature on human gene expression that was differentially expressed in preeclampsia. An electronic search was performed through 2019 through PubMed, Scopus, Ovid-Medline, and Gene Expression Omnibus where the following MeSH (Medical Subject Heading) terms were used and they had been specified as the primary focus of the articles: Gene, placenta, preeclampsia, and pregnancy in the title or abstract. We also found additional MeSH terms through Cochrane Library: Transcript, sequencing, and profiling. From 687 studies retrieved from the search, only original publications that had performed high throughput sequencing of human placental tissues that reported on differentially expressed genes in pregnancies with preeclampsia were included. Two reviewers independently scrutinized the titles and abstracts before examining the eligibility of studies that met the inclusion criteria. For each study, study design, sample size, sampling type, and method for gene analysis and gene were identified. The genes listed were further analyzed with the DAVID, STRING and Cytoscape MCODE. Three original research articles involving preeclampsia comprising the datasets in gene expression were included. By combining three studies together, 250 differentially expressed genes were produced at a significance setting of p < 0.05. We identified candidate genes: LEP, NRIP1, SASH1, and ZADHHC8P1. Through GO analysis, we found extracellular matrix organization as the highly significant enriched ontology in a group of upregulated genes and immune process in downregulated genes. Studies on a genetic level have the potential to provide new insights into the regulation and to widen the basis for identification of changes in the mechanism of preeclampsia. Integrated bioinformatics could identify differentially expressed genes which could be candidate genes and potential pathways in preeclampsia that may improve our understanding of the cause and underlying molecular mechanisms that could be used as potential biomarkers for risk stratification and treatment.
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Project description:Valenzuela and colleagues have recently reviewed some polymorphisms in important candidate genes involved in different pathogenic mechanisms related to preeclampsia (PE) and concluded that various studies in different populations have identified maternal polymorphisms associated with PE. However, we would like to contribute to some studies regarding candidate genes related to angiogenesis and endothelial dysfunction in PE performed in the Brazilian population. Specifically, genotypes and haplotypes formed by polymorphisms of VEGF, eNOS and MMP-9, along with an example of the interaction among these genes in the prediction of PE. Our suggestions may provide additional information with clinical relevance to PE susceptibility.
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Project description:Genetic variations in olfactory receptors likely contribute to the diversity of odorant-specific sensitivity phenotypes. Our working hypothesis is that genetic variations in auxiliary olfactory genes, including those mediating transduction and sensory neuronal development, may constitute the genetic basis for general olfactory sensitivity (GOS) and congenital general anosmia (CGA). We thus performed a systematic exploration for auxiliary olfactory genes and their documented variation. This included a literature survey, seeking relevant functional in vitro studies, mouse gene knockouts and human disorders with olfactory phenotypes, as well as data mining in published transcriptome and proteome data for genes expressed in olfactory tissues. In addition, we performed next-generation transcriptome sequencing (RNA-seq) of human olfactory epithelium and mouse olfactory epithelium and bulb, so as to identify sensory-enriched transcripts. Employing a global score system based on attributes of the 11 data sources utilized, we identified a list of 1,680 candidate auxiliary olfactory genes, of which 450 are shortlisted as having higher probability of a functional role. For the top-scoring 136 genes, we identified genomic variants (probably damaging single nucleotide polymorphisms, indels, and copy number deletions) gleaned from public variation repositories. This database of genes and their variants should assist in rationalizing the great interindividual variation in human overall olfactory sensitivity (http://genome.weizmann.ac.il/GOSdb).
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Project description:BackgroundRegions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is reduced by matching functional annotation to knowledge of the disease or phenotype in question. However, here we show that disease genes share patterns of sequence-based features that can provide a good basis for automatic prioritization of candidates by machine learning.ResultsWe examined a variety of sequence-based features and found that for many of them there are significant differences between the sets of genes known to be involved in human hereditary disease and those not known to be involved in disease. We have created an automatic classifier called PROSPECTR based on those features using the alternating decision tree algorithm which ranks genes in the order of likelihood of involvement in disease. On average, PROSPECTR enriches lists for disease genes two-fold 77% of the time, five-fold 37% of the time and twenty-fold 11% of the time.ConclusionPROSPECTR is a simple and effective way to identify genes involved in Mendelian and oligogenic disorders. It performs markedly better than the single existing sequence-based classifier on novel data. PROSPECTR could save investigators looking at large regions of interest time and effort by prioritizing positional candidate genes for mutation detection and case-control association studies.
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Project description:Medical resequencing of candidate genes in individual patient samples is becoming increasingly important in the clinic and in clinical research. Medical resequencing requires the amplification and sequencing of many candidate genes in many patient samples. Here we introduce Nested Patch PCR, a novel method for highly multiplexed PCR that is very specific, can sensitively detect SNPs and mutations, and is easy to implement. This is the first method that couples multiplex PCR with sample-specific DNA barcodes and next-generation sequencing to enable highly multiplex mutation discovery in candidate genes for multiple samples in parallel. In our pilot study, we amplified exons from colon cancer and matched normal human genomic DNA. From each sample, we successfully amplified 96% (90 of 94) targeted exons from across the genome, totaling 21.6 kbp of sequence. Ninety percent of all sequencing reads were from targeted exons, demonstrating that Nested Patch PCR is highly specific. We found that the abundance of reads per exon was reproducible across samples. We reliably detected germline SNPs and discovered a colon tumor specific nonsense mutation in APC, a gene causally implicated in colorectal cancer. With Nested Patch PCR, candidate gene mutation discovery across multiple individual patient samples can now utilize the power of second-generation sequencing.
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Project description:Preeclampsia is a hypertensive, multi-system pregnancy disorder whose pathophysiology remains unclear. Elevations in circulating soluble endoglin (sENG) and placental/blood ENG mRNA expression antedate the clinical onset of preeclampsia. This study investigated if endoglin (ENG) pathway genetic variation was also associated with the development of preeclampsia.We used a case-control candidate gene association design. Data from 355 white (181 preeclampsia cases/174 controls) and 60 black (30 preeclampsia cases/30 controls) women matched on ancestry, age, and parity were analyzed. Tagging single nucleotide polymorphisms (tSNPs) and potentially functional SNPs in ENG, TGF?1, TGF?R1, ALK1, and TGF?R2 were genotyped with iPLEX® and TaqMan®. Chi-square or Fisher's exact tests were used to conduct allele/genotype/haplotype tests in white/black subgroups separately. Odds ratios were computed with binary logistic regression for tSNPs with significant genotype tests.Of the 49 SNPs evaluated, variation in two ENG tSNPs (rs11792480, rs10121110) and one TGF?R2 tSNP (rs6550005) was associated with preeclampsia in white women (P <0.05, each). In black women, variation in two TGF?1 tSNPs (rs4803455, rs4803457), one TGF?R1 tSNP (rs10739778), and three TGF?R2 tSNPs (rs6550005, rs1346907, rs877572) was associated with preeclampsia (P <0.05, each). Further evaluation of ENG tSNP rs10121110 revealed that white women inheriting the AA genotype were 2.29 times more likely to develop preeclampsia compared to the GG genotype (P?=?0.008, [99% CI: 1.02 to 5.13]). For black women, similar evaluation of TGF?1 tSNP rs4803457 revealed women inheriting the CT genotype were 7.44 times more likely to develop preeclampsia than those with the CC genotype (P?=?0.005, [99% CI: 1.19 to 46.41]).ENG pathway genetic variation is associated with preeclampsia. Different ENG pathway genes may be involved in preeclampsia development among white and black women. Additional studies are needed to validate these findings and to determine if genetic variation in ENG pathway genes impacts ENG and sENG levels in preeclampsia.
| S-EPMC3651360 | biostudies-literature
Project description:Unbalanced inflammatory reactions and oxidative stress are inseparably interconnected, and both may play crucial roles in the pathophysiological mechanisms of preeclampsia (PE). In the published previous studies, we have genotyped for SNPs that related to inflammation (rs2227485, rs153109, rs17855750, rs2027432, rs2275913, rs763780, rs4819554, and rs13015714) and oxidative stress (rs1695, rs4680, rs1800566, rs4807542, rs713041, rs7579, rs230813, rs1004467, rs3824755, and rs9932581) to investigate whether these polymorphisms were associated with susceptibility to PE in a Chinese Han population. In this present study, we collected these data of experimental and clinical from above studies for haplotype analysis of inflammation-related SNPs in 631 PE patients and 720 normal pregnancy and oxidative stress-related SNPs in 342 PE patients and 457 normal pregnancies for susceptibility to PE. The data of genotype distribution and allele frequency comparisons after correction for multiple comparisons (P/8 or P/10) showed 2 among the 8 candidate inflammation-related SNPs have significant differences (rs2027432 genotype χ 2 = 407.377, p < 0.001, p < 0.00625). Moreover, the minor alleles of rs2027432 T (minor allele χ 2 = 450.923, p < 0.001, p < 0.00625; OR = 21.439, 95%CI = 15.181-30.278) and rs4819554 G (minor allele χ 2 = 163.465, p < 0.001, p < 0.00625; OR = 5.814, 95%CI = 4.380-7.719) were confirmed as risk allele of PE, respectively. Our analysis revealed rs2027432 (TT) of NLRP3 and rs4819554 (GG) of IL-17RA are risk factors for PE. However, no significant difference was found at the oxidative stress-related SNPs. In the candidate loci for oxidative stress, we also identified 3 SNP matches (rs4807542 and rs713041, rs230813 and rs75799, rs1004467 and rs3824755) that had high linkage disequilibrium (LD) with each other and were selected as a block (r 2 = 0.98, r 2 = 0.97, r 2 = 0.97, r 2 > 0.9), and the GT and GC haplotypes of rs4807542 and rs713041 in GPX4 showed significant differences between the PE and control groups (χ 2 = 5.143, p = 0.0233, p < 0.05; χ 2 = 6.373, p = 0.0116, p < 0.05). So, we inferred that polymorphisms of NLRP3 rs2027432 and IL-17RA rs4819554, which are related to inflammation, and the rs713041 variant of GPX4, which is related to oxidative stress, were associated with susceptibility to PE. The GT and GC haplotypes of rs4807542 and rs713041 in GPX4 may increase the risk of PE in the Chinese Han population.
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Project description:It is well established that embryonic chromosomal abnormalities (both in the number of chromosomes and the structure) account for 50% of early pregnancy losses. However, little is known regarding the potential differences in the incidence and distribution of chromosomal abnormalities between patients with sporadic abortion (SA) and recurrent pregnancy loss (RPL), let alone the role of submicroscopic copy-number variations (CNVs) in these cases. The aim of the present study was to systematically evaluate the role of embryonic chromosomal abnormalities and CNVs in the etiology of RPL compared with SA. Over a 3-year period, 1556 fresh products of conception (POCs) from miscarriage specimens were investigated using single nucleotide polymorphism array (SNP-array) and CNV sequencing (CNV-seq) in this study, along with further functional enrichment analysis. Chromosomal abnormalities were identified in 57.52% (895/1556) of all cases. Comparisons of the incidence and distributions of chromosomal abnormalities within the SA group and RPL group and within the different age groups were performed. Moreover, 346 CNVs in 173 cases were identified, including 272 duplications, 2 deletions and 72 duplications along with deletions. Duplications in 16q24.3 and 16p13.3 were significantly more frequent in RPL cases, and thereby considered to be associated with RPL. There were 213 genes and 131 signaling pathways identified as potential RPL candidate genes and signaling pathways, respectively, which were centered primarily on six functional categories. The results of the present study may improve our understanding of the etiologies of RPL and assist in the establishment of a population-based diagnostic panel of genetic markers for screening RPL amongst Chinese women.
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Project description:BackgroundThere are two US Food and Drug Administration (FDA)-approved drugs, pirfenidone and nintedanib, for treatment of patients with idiopathic pulmonary fibrosis (IPF). However, neither of these drugs provide a cure. In addition, both are associated with several drug-related adverse events. Hence, the pursuit for newer IPF therapeutics continues. Recent studies show that joint analysis of systems-biology-level information with drug-disease connectivity are effective in discovery of biologically relevant candidate therapeutics.MethodsPublicly available gene expression signatures from patients with IPF were used to query a large-scale perturbagen signature library to discover compounds that can potentially reverse dysregulated gene expression in IPF. Two methods were used to calculate IPF-compound connectivity: gene expression-based connectivity and feature-based connectivity. Identified compounds were further prioritized if their shared mechanism(s) of action were IPF-related.ResultsWe found 77 compounds as potential candidate therapeutics for IPF. Of these, 39 compounds are either FDA-approved for other diseases or are currently in phase II/III clinical trials suggesting their repurposing potential for IPF. Among these compounds are multiple receptor kinase inhibitors (e.g. nintedanib, currently approved for IPF, and sunitinib), aurora kinase inhibitor (barasertib), epidermal growth factor receptor inhibitors (erlotinib, gefitinib), calcium channel blocker (verapamil), phosphodiesterase inhibitors (roflumilast, sildenafil), PPAR agonists (pioglitazone), histone deacetylase inhibitors (entinostat), and opioid receptor antagonists (nalbuphine). As a proof of concept, we performed in vitro validations with verapamil using lung fibroblasts from IPF and show its potential benefits in pulmonary fibrosis.ConclusionsAs about half of the candidates discovered in this study are either FDA-approved or are currently in clinical trials for other diseases, rapid translation of these compounds as potential IPF therapeutics is possible. Further, the integrative connectivity analysis framework in this study can be adapted in early phase drug discovery for other common and rare diseases with transcriptomic profiles.The reviews of this paper are available via the supplemental material section.
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