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1.
Viruses ; 11(7)2019 07 02.
Article in English | MEDLINE | ID: mdl-31269734

ABSTRACT

Hemorrhagic fever with renal syndrome (HFRS) is endemic in Tatarstan, where thousands of cases are registered annually. Puumalaorthohantavirus is commonly detected in human case samples as well as in captured bank voles, the rodent hosts. The pathogenesis of HFRS is still not well described, although the cytokine storm hypothesis is largely accepted. In this study, we present a comprehensive analysis of a fatal HFRS case compared with twenty four non-fatal cases where activation of the humoral and cellular immune responses, pro-inflammatory cytokines and disturbed blood coagulation were detected using immunological, histological, genetic and clinical approaches. Multiple organ failure combined with disseminated intravascular coagulation syndrome and acute renal failure was the cause of death. Decreased Interleukin (IL)-7 and increased IL-18, chemokine (C-C motif) ligand (CCL)-5, stem cell growth factor (SCGF)-b and tumor necrosis factor-beta (TNF-ß) serum levels were found, supporting the cytokine storm hypothesis of hantavirus pathogenesis.


Subject(s)
Cytokines/immunology , Hemorrhagic Fever with Renal Syndrome/immunology , Immunity, Humoral/immunology , Adult , Animals , Chlorocebus aethiops , Female , HEK293 Cells , Orthohantavirus/immunology , Hemorrhagic Fever with Renal Syndrome/pathology , Hemorrhagic Fever with Renal Syndrome/virology , Humans , Interleukin-17/metabolism , Interleukin-18/metabolism , Kidney/immunology , Kidney/pathology , Lung/diagnostic imaging , Lung/pathology , Male , Middle Aged , Phylogeny , Puumala virus/classification , Puumala virus/genetics , Rodentia , Tatarstan , Vero Cells
2.
Kidney Int ; 66(1): 428-32, 2004 Jul.
Article in English | MEDLINE | ID: mdl-15200452

ABSTRACT

BACKGROUND: While the influence of cytokine gene polymorphisms on immunologic complications after organ transplantation is widely evaluated, little is known about predictive value of cytokine genotype for the development of nonimmunologic post-transplant complications: hypertension, dyslipoproteinemia, diabetes mellitus, hyperuricemia. METHODS: The -1082IL-10, -308TNF-alpha, transforming growth factor-beta1 (TGF-beta1) (codon 10, 25), -174IL-6, +874IFN-gamma gene single nucleotide polymorphisms (SNP) were studied in 278 long-term renal transplants by polymerase chain reaction-sequence specific primer (PCR-SSP) with respect to nonimmunologic post-transplant complications. RESULTS: Significant association of the TGF-beta (codon 25) GG genotype with hyperuricemia (P= 0.0013) and dyslipoproteinemia (P= 0.0171) was found. The TGF-beta1 (codon 25) CG genotype was detected more frequently in patients with normal uric acid levels. The +874IFN-gamma AA genotype was associated with type 2/steroid-induced diabetes (P= 0.0127). Frequency of the -1082IL-10 AG genotype was significantly higher in hyperuricemic patients versus controls (P= 0.0022). No associations of polymorphisms in the tumor necrosis factor-alpha (TNF-alpha), interleukin-6 (IL-6), TGF-beta codon 10 genes with hyperuricemia, dyslipoproteinemia, or diabetes were detected. We failed to observe significant differences in cytokine genotype distribution between hypertensive and normotensive patients. CONCLUSION: We established an association of particular cytokine genotypes with nonimmunologic post-transplant complications. This supports an idea that assessment of cytokine SNPs may allow more accurate prediction of nonimmunologic complications and appropriate adjustment of pre-emptive treatments in long-term transplant patients.


Subject(s)
Cytokines/genetics , Immunologic Factors/genetics , Kidney Transplantation/adverse effects , Polymorphism, Genetic , Adult , Cohort Studies , Diabetes Mellitus/etiology , Diabetes Mellitus/genetics , Female , Genetic Predisposition to Disease , Genotype , Humans , Hyperlipidemias/blood , Hyperlipidemias/etiology , Hyperlipidemias/genetics , Hypertension/etiology , Hypertension/genetics , Hyperuricemia/etiology , Hyperuricemia/genetics , Lipoproteins/blood , Male , Middle Aged , Predictive Value of Tests , Time Factors
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