Dataset Information

KIR2DL4 expression rather than its single nucleotide polymorphisms correlates with pre-eclampsia.

ABSTRACT:

Objective

To evaluate the single nucleotide polymorphisms and expression of KIR2DL4 (killer cell immunoglobulin-like receptors) gene in pre-eclampsia patients.

Methods

KIR2DL4 gene polymorphisms were detected in 100 patients with pre-eclampsia and 100 healthy pregnant women, respectively, by using PCR-SS. Then, the expression of KIR2DL4 was measured in 5 cases of placentas tissues with pre-eclampsia and normal pregnancies by using qRT-PCR.

Results

Compared with healthy controls, 16 loci of single nucleotide polymorphisms (SNP) were identified in pre-eclampsia patients, including 7 new polymorphisms loci. But, no significant difference was found in genotype distributions and allele frequencies in pre-eclampsia and controls (P>0.05). However, qRT-PCR results showed that KIR2DL4 mRNA in placenta tissues with pre-eclampsia was significantly lower than those with normal pregnancy, and the difference was statistically significant.

Conclusion

Decreased level of KIR2DL4 rather than its SNP is correlated with the susceptibility of pre-eclampsia.

SUBMITTER: Wang D

PROVIDER: S-EPMC4713560 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

KIR2DL4 expression rather than its single nucleotide polymorphisms correlates with pre-eclampsia.

Wang Dandan D Tian Yuan Y Zhao Yanhui Y Liu Lianlian L Liu Xianying X Wu Fuju F

International journal of clinical and experimental pathology 20151101 11

<h4>Objective</h4>To evaluate the single nucleotide polymorphisms and expression of KIR2DL4 (killer cell immunoglobulin-like receptors) gene in pre-eclampsia patients.<h4>Methods</h4>KIR2DL4 gene polymorphisms were detected in 100 patients with pre-eclampsia and 100 healthy pregnant women, respectively, by using PCR-SS. Then, the expression of KIR2DL4 was measured in 5 cases of placentas tissues with pre-eclampsia and normal pregnancies by using qRT-PCR.<h4>Results</h4>Compared with healthy cont ...[more]

PMID: 26823774

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Project description:Single-nucleotide polymorphisms (SNPs) provide an abundant source of DNA polymorphisms in a number of eukaryotic species. Information on the frequency, nature, and distribution of SNPs in plant genomes is limited. Thus, our objectives were (1) to determine SNP frequency in coding and noncoding soybean (Glycine max L. Merr.) DNA sequence amplified from genomic DNA using PCR primers designed to complete genes, cDNAs, and random genomic sequence; (2) to characterize haplotype variation in these sequences; and (3) to provide initial estimates of linkage disequilibrium (LD) in soybean. Approximately 28.7 kbp of coding sequence, 37.9 kbp of noncoding perigenic DNA, and 9.7 kbp of random noncoding genomic DNA were sequenced in each of 25 diverse soybean genotypes. Over the >76 kbp, mean nucleotide diversity expressed as Watterson's theta was 0.00097. Nucleotide diversity was 0.00053 and 0.00111 in coding and in noncoding perigenic DNA, respectively, lower than estimates in the autogamous model species Arabidopsis thaliana. Haplotype analysis of SNP-containing fragments revealed a deficiency of haplotypes vs. the number that would be anticipated at linkage equilibrium. In 49 fragments with three or more SNPs, five haplotypes were present in one fragment while four or less were present in the remaining 48, thereby supporting the suggestion of relatively limited genetic variation in cultivated soybean. Squared allele-frequency correlations (r(2)) among haplotypes at 54 loci with two or more SNPs indicated low genome-wide LD. The low level of LD and the limited haplotype diversity suggested that the genome of any given soybean accession is a mosaic of three or four haplotypes. To facilitate SNP discovery and the development of a transcript map, subsets of four to six diverse genotypes, whose sequence analysis would permit the discovery of at least 75% of all SNPs present in the 25 genotypes as well as 90% of the common (frequency >0.10) SNPs, were identified.

Project description:BackgroundPre-eclampsia is the most common complication occurring during pregnancy. In the majority of cases, it is concurrent with other pathologies in a comorbid manner (frequent co-occurrences in patients), such as diabetes mellitus, gestational diabetes and obesity. Providing bronchial asthma, pulmonary tuberculosis, certain neurodegenerative diseases and cancers as examples, we have shown previously that pairs of inversely comorbid pathologies (rare co-occurrences in patients) are more closely related to each other at the molecular genetic level compared with randomly generated pairs of diseases. Data in the literature concerning the causes of pre-eclampsia are abundant. However, the key mechanisms triggering this disease that are initiated by other pathological processes are thus far unknown. The aim of this work was to analyse the characteristic features of genetic networks that describe interactions between comorbid diseases, using pre-eclampsia as a case in point.ResultsThe use of ANDSystem, Pathway Studio and STRING computer tools based on text-mining and database-mining approaches allowed us to reconstruct associative networks, representing molecular genetic interactions between genes, associated concurrently with comorbid disease pairs, including pre-eclampsia, diabetes mellitus, gestational diabetes and obesity. It was found that these associative networks statistically differed in the number of genes and interactions between them from those built for randomly chosen pairs of diseases. The associative network connecting all four diseases was composed of 16 genes (PLAT, ADIPOQ, ADRB3, LEPR, HP, TGFB1, TNFA, INS, CRP, CSRP1, IGFBP1, MBL2, ACE, ESR1, SHBG, ADA). Such an analysis allowed us to reveal differential gene risk factors for these diseases, and to propose certain, most probable, theoretical mechanisms of pre-eclampsia development in pregnant women. The mechanisms may include the following pathways: [TGFB1 or TNFA]-[IL1B]-[pre-eclampsia]; [TNFA or INS]-[NOS3]-[pre-eclampsia]; [INS]-[HSPA4 or CLU]-[pre-eclampsia]; [ACE]-[MTHFR]-[pre-eclampsia].ConclusionsFor pre-eclampsia, diabetes mellitus, gestational diabetes and obesity, we showed that the size and connectivity of the associative molecular genetic networks, which describe interactions between comorbid diseases, statistically exceeded the size and connectivity of those built for randomly chosen pairs of diseases. Recently, we have shown a similar result for inversely comorbid diseases. This suggests that comorbid and inversely comorbid diseases have common features concerning structural organization of associative molecular genetic networks.

Dataset Information

KIR2DL4 expression rather than its single nucleotide polymorphisms correlates with pre-eclampsia.

Objective

Methods

Results

Conclusion

Publications

KIR2DL4 expression rather than its single nucleotide polymorphisms correlates with pre-eclampsia.

Similar Datasets

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