Allele-specific quantification of HLA-DQB1 gene expression by real-time reverse transcriptase-polymerase chain reaction

Ferstl, Barbara; Zacher, Thorsten; Lauer, B.; Blagitko-Dorfs, Nadya; Carl, A.; Waßmuth, Ralf

doi:10.1038/sj.gene.6364108

Cited by 18 publications

(18 citation statements)

References 32 publications

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“…A quantitative hierarchy of DRB1 mRNA in healthy individuals has been observed for different alleles ( DRB1*03>DRB1*04>DRB1*01>DRB1*08 ) [20]. Similar quantitative hierarchy has been observed for DQA1 ( DQA1*0301>DQA1*0101>DQA1*0501 ) [21] and DQB1 genes ( DQB1*0301>DQB*0501>DQB1*0602 ) [22]. Over 90% of Caucasian diabetic subjects possess one of susceptibility haplotypes HLA-DR4-DQA1*0301-DQB1*0302 or HLA-DR3-DQA1*0501-DQB1*0201 or both [23], [24], [25].…”

Section: Introductionsupporting

confidence: 53%

Interaction between Treg Apoptosis Pathways, Treg Function and HLA Risk Evolves during Type 1 Diabetes Pathogenesis

Glišić

Jailwala

2012

PLoS ONE

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We have previously reported increased apoptosis of regulatory T cells (Tregs) in recent-onset Type 1 Diabetes subjects (RO T1D) in the honeymoon phase and in multiple autoantibody-positive (Ab+) subjects, some of which are developing T1D. We have also reported that increased Treg apoptosis was associated with High HLA risk and that it subsided with cessation of honeymoon period. In this report, we present results generated using genetics, genomics, functional cell-based assays and flow cytometry to assess cellular changes at the T-cell level during T1D pathogenesis. We measured ex vivo Treg apoptosis and Treg function, surface markers expression, expression of HLA class II genes, the influence of HLA risk on Treg apoptosis and function, and evaluated contribution of genes reported to be involved in the apoptosis process. This integrated comprehensive approach uncovered important information that can serve as a basis for future studies aimed to modulate Treg cell responsiveness to apoptotic signals in autoimmunity. For example, T1D will progress in those subjects where increased Treg apoptosis is accompanied with decreased Treg function. Furthermore, Tregs from High HLA risk healthy controls had increased Treg apoptosis levels and overexpressed FADD but not Fas/FasL. Tregs from RO T1D subjects in the honeymoon phase were primarily dying through withdrawal of growth hormones with contribution of oxidative stress, mitochondrial apoptotic pathways, and employment of TNF-receptor family members. Ab+ subjects, however, expressed high inflammation level, which probably contributed to Treg apoptosis, although other apoptotic pathways were also activated: withdrawal of growth hormones, oxidative stress, mitochondrial apoptosis and Fas/FasL apoptotic pathways. The value of these results lie in potentially different preventive treatment subjects would receive depending on disease progression stage when treated.

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Section: Introductionsupporting

confidence: 53%

Interaction between Treg Apoptosis Pathways, Treg Function and HLA Risk Evolves during Type 1 Diabetes Pathogenesis

Glišić

Jailwala

2012

PLoS ONE

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“…In the DQ locus, Nepon et al [30] also found differential expression of DQB1*02 and DQB1*04 in an heterozygous cell line that was not obviously explained by differential promoter methylation or direct DNA-protein interactions in the X box region, suggesting the involvement of other regulatory proteins that could have low abundance and regulate differentially both promoters. In other cases where DQ allele specific expression has been looked at, focus has been directed at differential allelic expression in correlation with promoter differences not differential expression of the same allele, but it is clear from these studies as well that interindividual variation is not likely solely explain by DQ promoter variation [31, 32]. …”

Section: Discussionmentioning

confidence: 99%

“…The DQB1 promoter is polymorphic and has been postulated to regulate allelic specific expression of various alleles differentially in cellular subtypes, although no definitive allelic hierarchy has been published [30-31]. Interestingly, Ferstl, et al were studying cytokine driven maturation of monocytes into dendritic cells, a process known to involve increased HLA class II expression, and they found increased DQB1*03:01 expression in comparison to other alleles such as DQB1*06:02 and DQB1*05:01 in DQB1*03:01/DQB1*06:02 and DQB1*03:01/DQB1*05:01 heterozygotes [32], extending on a finding in primary human skin fibroblasts also showing increased expression of DQB1*03:01 versus other alleles [31],…”

Section: Discussionmentioning

confidence: 99%

DQB1*06:02 allele-specific expression varies by allelic dosage, not narcolepsy status

Lachmi¹,

Li²,

Kornum³

et al. 2012

Human Immunology

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The association of narcolepsy-cataplexy, a sleep disorder caused by the loss of hypocretin/orexin neurons in the hypothalamus, with DQA1*01:02-DQB1*06:02 is one of the tightest known single allele HLA associations. In this study, we explored genome wide expression in peripheral white blood cells of 50 narcolepsy versus 47 controls (half of whom were DQB1*06:02 positive) and found the largest differences between the groups to be in the signal from HLA probes. Further studies of HLA-DQ expression (mRNA and protein in a subset) in 125 controls and 147 narcolepsy cases did not reveal any difference, a result we explain by the lack of proper control of allelic diversity in Affymetrix HLA probes. Rather, a clear effect of DQB1*06:02 allelic dosage on DQB1*06:02 mRNA levels (1.65 fold) and protein (1.59 fold) could be demonstrated independent of the disease status. These results indicate that allelic dosage is transmitted into changes in heterodimer availability, a phenomenon that may explain increased risk for narcolepsy in DQB1*06:02 homozygotes versus heterozygotes.

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“…Previously, Ferstl et al (2004) indicated that RT-PCR is an accurate method to study the expression of desired genes in in vivo experiments [22]. The spleen and muscle (immunization site) samples of the chickens immunized with different DNA vaccine constructs were extracted and used as templates for PCR and RT-PCR amplifications.…”

Section: Discussionmentioning

confidence: 99%

Development of avian influenza virus H5 DNA vaccine and MDP-1 gene of Mycobacterium bovisas genetic adjuvant

Jalilian

Omar

Bejo

et al. 2010

Genet Vaccines Ther

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BackgroundStudies have shown that DNA vaccines can induce protective immunity, which demonstrated the high potential of DNA vaccines as an alternative to inactivated vaccines. Vaccines are frequently formulated with adjuvants to improve their release, delivery and presentation to the host immune system.MethodsThe H5 gene of H5N1 virus (A/Ck/Malaysia/5858/04) was cloned separately into pcDNA3.1 + vector. The immunogenicity of the cloned H5 DNA vaccine was tested on SPF chickens using two different approaches. First approach was using H5 DNA vaccine (pcDNA3.1/H5) and the second was using H5 DNA vaccine in addition to the pcDNA3.1/MDP1 vaccine. Ten days old chickens inoculated three times with two weeks intervals. The spleen and muscle samples from chickens immunized with H5 (pcDNA3.1/H5) and H5 + MDP1 (pcDNA3.1/H5 + pcDNA3.1/MDP1) vaccines were collected after sacrificing the chickens and successfully expressed H5 and MDP1 RNA transcripts. The sera of immunized chickens were collected prior to first immunization and every week after immunization; and analyzed using enzyme-linked immunosorbent assay (ELISA) and hemagglutination inhibition (HI) test.ResultsResults of competitive ELISA showed successful antibody responses two weeks post immunization. The HI test showed an increased in antibody titers during the course of experiment in group immunized with H5 and H5 + MDP1 vaccines. The result showed that the constructed DNA vaccines were able to produce detectable antibody titer in which the group immunized with H5 + MDP1 vaccine produced higher antibody comparing to H5 vaccine alone.ConclusionsThis study shows for the first time the usefulness of MDP1 as a genetic adjuvant for H5 DNA vaccine.

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Allele-specific quantification of HLA-DQB1 gene expression by real-time reverse transcriptase-polymerase chain reaction

Cited by 18 publications

References 32 publications

Interaction between Treg Apoptosis Pathways, Treg Function and HLA Risk Evolves during Type 1 Diabetes Pathogenesis

Interaction between Treg Apoptosis Pathways, Treg Function and HLA Risk Evolves during Type 1 Diabetes Pathogenesis

DQB1*06:02 allele-specific expression varies by allelic dosage, not narcolepsy status

Development of avian influenza virus H5 DNA vaccine and MDP-1 gene of Mycobacterium bovisas genetic adjuvant

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