Dataset Information

High-Resolution Genetic and Phenotypic Analysis of KIR2DL1 Alleles and Their Association with Pre-Eclampsia.

ABSTRACT: Killer-cell Ig-like receptor (KIR) genes are inherited as haplotypes. They are expressed by NK cells and linked to outcomes of infectious diseases and pregnancy in humans. Understanding how genotype relates to phenotype is difficult because of the extensive diversity of the KIR family. Indeed, high-resolution KIR genotyping and phenotyping in single NK cells in the context of disease association is lacking. In this article, we describe a new method to separate NK cells expressing allotypes of the KIR2DL1 gene carried by the KIR A haplotype (KIR2DL1A) from those expressing KIR2DL1 alleles carried by the KIR B haplotype (KIR2DL1B). We find that in KIR AB heterozygous individuals, different KIR2DL1 allotypes can be detected in both peripheral blood and uterine NK cells. Using this new method, we demonstrate that both blood and uterine NK cells codominantly express KIR2DL1A and KIR2DL1B allotypes but with a predominance of KIR2DL1A variants, which associate with enhanced NK cell function. In a case-control study of pre-eclampsia, we show that KIR2DL1A, not KIR2DL1B, associates with increased disease risk. This method will facilitate our understanding of how individual KIR2DL1 allelic variants affect NK cell function and contribute to disease risk.

SUBMITTER: Huhn O

PROVIDER: S-EPMC6258046 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

High-Resolution Genetic and Phenotypic Analysis of KIR2DL1 Alleles and Their Association with Pre-Eclampsia.

Huhn Oisín O Chazara Olympe O Ivarsson Martin A MA Retière Christelle C Venkatesan Timothy C TC Norman Paul J PJ Hilton Hugo G HG Jayaraman Jyothi J Traherne James A JA Trowsdale John J Ito Mitsutero M Kling Christiane C Parham Peter P Ghadially Hormas H Moffett Ashley A Sharkey Andrew M AM Colucci Francesco F

Journal of immunology (Baltimore, Md. : 1950) 20180924 9

Killer-cell Ig-like receptor (KIR) genes are inherited as haplotypes. They are expressed by NK cells and linked to outcomes of infectious diseases and pregnancy in humans. Understanding how genotype relates to phenotype is difficult because of the extensive diversity of the KIR family. Indeed, high-resolution KIR genotyping and phenotyping in single NK cells in the context of disease association is lacking. In this article, we describe a new method to separate NK cells expressing allotypes of th ...[more]

PMID: 30249807

Similar Datasets

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

High-Resolution Genetic and Phenotypic Analysis of KIR2DL1 Alleles and Their Association with Pre-Eclampsia.

Publications

High-Resolution Genetic and Phenotypic Analysis of KIR2DL1 Alleles and Their Association with Pre-Eclampsia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets