The effect of KIR and HLA polymorphisms on dengue infection and disease severity in northeastern Thais

Identification of HLA ligands in dengue patients by multiplex PCR-SSP method

BACKGROUND

High-throughput DNA sequencing technologies have revolutionized genetic studies of populations and diseases. These methods provide deeper insights into gene structure and variation, offering more comprehensive immunogenetic data with stronger relevance to protein function and biological impact. However, the widespread adoption of high-resolution sequencing is hindered by factors such as cost and limited accessibility. Furthermore, successful implementation requires high-quality and sufficient quantities of genomic DNA.

METHODS AND RESULTS

This study addresses the challenges of limited DNA yields, a common issue in clinical samples, by employing whole-genome amplification (WGA) with isothermal multiple displacement amplification (IMDA). We investigated HLA ligands in 253 dengue samples with low DNA quantity. A multiplex PCR-SSP method was developed to determine HLA ligands in population, including HLA-C1, HLA-C2, HLA-A (Bw4), HLA-Bw4 (I80), HLA-Bw4 (T80), and HLA-A*11. The study successfully demonstrates the applicability of a multiplex PCR-SSP method for HLA genotyping in a large cohort of dengue patients. Our findings highlight the high prevalence of HLA-C1 (92.1%) and HLA-A*11:03 (78.3%) in dengue patients, providing valuable data for further investigations into the role of HLA polymorphisms in diseases.

CONCLUSIONS

This study demonstrates the utility of our approach for investigating HLA ligands in clinical samples with limited DNA. WGA-IMDA effectively overcomes the challenge of low DNA availability, making this approach suitable for resource-constrained settings. The multiplex PCR-SSP method provides a simple and cost-effective solution for immunogenetic studies.

Influence of killer immunoglobulin-like receptors genes on the recurrence rate of ocular toxoplasmosis in Brazil

BACKGROUND

Recurrence is a hallmark of ocular toxoplasmosis (OT), and conditions that influence its occurrence remain a challenge. Natural killer cells (NK) are effectors cells whose primary is cytotoxic function against many parasites, including Toxoplasma gondii. Among the NK cell receptors, immunoglobulin-like receptors (KIR) deserve attention due to their high polymorphism.

OBJECTIVES

This study aimed to analyse the influence of KIR gene polymorphism in the course of OT infection and its association with recurrences after an active episode.

METHODS

Ninety-six patients from the Ophthalmologic Clinic of the National Institute of Infectology Evandro Chagas were followed for up to five years. After DNA extraction, genotyping of the patients was performed by polymerase chain reaction sequence-specific oligonucleotide (PCR-SSO) utilising Luminex equipment for reading. During follow-up, 60.4% had a recurrence.

FINDINGS

We identified 25 KIR genotypes and found a higher frequency of genotype 1 (31.7%) with worldwide distribution. We note that the KIR2DL2 inhibitor gene and the gene activator KIR2DS2 were more frequent in patients without recurrence. Additionally, we observed that individuals who carry these genes progressed recurrence episodes slowly compared to individuals who do not carry these genes.

MAIN CONCLUSIONS

The KIR2DL2 and KIR2DS2 are associated as possible protection markers against ocular toxoplasmosis recurrence (OTR).

Lack of association of the KIR and HLA class I ligands with ZIKV infection in south and southeast of Brazil

BACKGROUND

Zika virus (ZIKV) is an emerging arbovirus associated with foetal malformations and neurological complications. The infection is usually associated with mild symptoms. The comparison between the allelic frequency of polymorphic genes in symptomatic infected individuals in the population can clarify the pathogenic mechanisms of ZIKV. During ZIKV infection, cytokines are produced and natural killer (NK) cells are recruited, whose activation depends on signaling pathways activated by specific receptors, such as killer cell immunoglobulin-like receptors (KIR). These molecules interact with human leukocyte antigen (HLA) class I ligands and are encoded by polymorphic genes.

OBJECTIVES

This study aimed to evaluate the frequency of allelic variants of the genes encoding the KIR receptors and their HLA class I ligands in 139 symptomatic ZIKV-patients and 170 controls negative for the virus, and to evaluate the role of these variants for ZIKV susceptibility.

METHODS

KIR and HLA class I genes were genotyped using the polymerase chain reaction-sequence specific oligonucleotide (PCR-SSO) technique.

FINDINGS

No significant differences in the frequency distribution of KIRs and KIR-HLA in patients compared to controls were observed.

MAIN CONCLUSIONS

KIR and its HLA ligands might play a minor role in ZIKV infection in the south and southeast Brazilian individuals.

Current HLA Investigations on SARS-CoV-2 and Perspectives

The rapid, global spread of the SARS-CoV-2 virus during the current pandemic has triggered numerous efforts in clinical and research settings to better understand the host genetics' interactions and the severity of COVID-19. Due to the established major role played by MHC/HLA polymorphism in infectious disease course and susceptibility, immunologists and geneticists have teamed up to investigate its contribution to the SARS-CoV-2 infection and COVID-19 progression. A major goal of the Covid-19|HLA & Immunogenetics Consortium is to support and unify these efforts. Here, we present a review of HLA immunogenomics studies in the SARS-CoV-2 pandemic and reflect on the role of various HLA data, their limitation and future perspectives.

A model integrating Killer Immunoglobulin-like Receptor (KIR) haplotypes for risk prediction of COVID-19 clinical disease severity

Associations between inherited Killer Immunoglobulin-like Receptor (KIR) genotypes and the severity of multiple RNA virus infections have been reported. This prospective study was initiated to investigate if such an association exists for COVID-19. In this cohort study performed at Ankara University, 132 COVID-19 patients (56 asymptomatic, 51 mild-intermediate, and 25 patients with severe disease) were genotyped for KIR and ligands. Ankara University Donor Registry (n:449) KIR data was used for comparison. Clinical parameters (age, gender, comorbidities, blood group antigens, inflammation biomarkers) and KIR genotypes across cohorts of asymptomatic, mild-intermediate, or severe disease were compared to construct a risk prediction model based on multivariate binary logistic regression analysis with backward elimination method. Age, blood group, number of comorbidities, CRP, D-dimer, and telomeric and centromeric KIR genotypes (tAA, tAB1, and cAB1) along with their cognate ligands were found to differ between cohorts. Two prediction models were constructed; both included age, number of comorbidities, and blood group. Inclusion of the KIR genotypes in the second prediction model exp (-3.52 + 1.56 age group - 2.74 blood group (type A vs others) + 1.26 number of comorbidities - 2.46 tAB1 with ligand + 3.17 tAA with ligand) increased the predictive performance with a 92.9% correct classification for asymptomatic and 76% for severe cases (AUC: 0.93; P < 0.0001, 95% CI 0.88, 0.99). This novel risk model, consisting of KIR genotypes with their cognate ligands, and clinical parameters but excluding earlier published inflammation-related biomarkers allow for the prediction of the severity of COVID-19 infection prior to the onset of infection. This study is listed in the National COVID-19 clinical research studies database.