Structure-guided approach to identify a novel class of anti-leishmaniasis diaryl sulfide compounds targeting the trypanothione metabolism.

Leishmania protozoans are the causative agent of leishmaniasis, a neglected tropical disease consisting of three major clinical forms: visceral leishmaniasis (VL), cutaneous leishmaniasis, and mucocutaneous leishmaniasis. VL is caused by Leishmania donovani in East Africa and the Indian subcontinent and by Leishmania infantum in Europe, North Africa, and Latin America, and causes an estimated 60,000 deaths per year. Trypanothione reductase (TR) is considered to be one of the best targets to find new drugs against leishmaniasis. This enzyme is fundamental for parasite survival in the human host since it reduces trypanothione, a molecule used by the tryparedoxin/tryparedoxin peroxidase system of Leishmania to neutralize the hydrogen peroxide produced by host macrophages during infection. Recently, we solved the X-ray structure of TR in complex with the diaryl sulfide compound RDS 777 (6-(sec-butoxy)-2-((3-chlorophenyl)thio)pyrimidin-4-amine), which impairs the parasite defense against the reactive oxygen species by inhibiting TR with high efficiency. The compound binds to the catalytic site and engages in hydrogen bonds the residues more involved in the catalysis, namely Glu466', Cys57 and Cys52, thereby inhibiting the trypanothione binding. On the basis of the RDS 777-TR complex, we synthesized structurally related diaryl sulfide analogs as TR inhibitors able to compete for trypanothione binding to the enzyme and to kill the promastigote in the micromolar range. One of the most active among these compounds (RDS 562) was able to reduce the trypanothione concentration in cell of about 33% via TR inhibition. RDS 562 inhibits selectively Leishmania TR, while it does not inhibit the human homolog glutathione reductase.

Decision trees for early prediction of inadequate immune response to coronavirus infections: a pilot study on COVID-19.

Introduction: Few artificial intelligence models exist to predict severe forms of COVID-19. Most rely on post-infection laboratory data, hindering early treatment for high-risk individuals. Methods: This study developed a machine learning model to predict inherent risk of severe symptoms after contracting SARS-CoV-2. Using a Decision Tree trained on 153 Alpha variant patients, demographic, clinical and immunogenetic markers were considered. Model performance was assessed on Alpha and Delta variant datasets. Key risk factors included age, gender, absence of KIR2DS2 gene (alone or with HLA-C C1 group alleles), presence of 14-bp polymorphism in HLA-G gene, presence of KIR2DS5 gene, and presence of KIR telomeric region A/A. Results: The model achieved 83.01% accuracy for Alpha variant and 78.57% for Delta variant, with True Positive Rates of 80.82 and 77.78%, and True Negative Rates of 85.00% and 79.17%, respectively. The model showed high sensitivity in identifying individuals at risk. Discussion: The present study demonstrates the potential of AI algorithms, combined with demographic, epidemiologic, and immunogenetic data, in identifying individuals at high risk of severe COVID-19 and facilitating early treatment. Further studies are required for routine clinical integration.

Decision trees to evaluate the risk of developing multiple sclerosis.

Introduction: Multiple sclerosis (MS) is a persistent neurological condition impacting the central nervous system (CNS). The precise cause of multiple sclerosis is still uncertain; however, it is thought to arise from a blend of genetic and environmental factors. MS diagnosis includes assessing medical history, conducting neurological exams, performing magnetic resonance imaging (MRI) scans, and analyzing cerebrospinal fluid. While there is currently no cure for MS, numerous treatments exist to address symptoms, decelerate disease progression, and enhance the quality of life for individuals with MS. Methods: This paper introduces a novel machine learning (ML) algorithm utilizing decision trees to address a key objective: creating a predictive tool for assessing the likelihood of MS development. It achieves this by combining prevalent demographic risk factors, specifically gender, with crucial immunogenetic risk markers, such as the alleles responsible for human leukocyte antigen (HLA) class I molecules and the killer immunoglobulin-like receptors (KIR) genes responsible for natural killer lymphocyte receptors. Results: The study included 619 healthy controls and 299 patients affected by MS, all of whom originated from Sardinia. The gender feature has been disregarded due to its substantial bias in influencing the classification outcomes. By solely considering immunogenetic risk markers, the algorithm demonstrates an ability to accurately identify 73.24% of MS patients and 66.07% of individuals without the disease. Discussion: Given its notable performance, this system has the potential to support clinicians in monitoring the relatives of MS patients and identifying individuals who are at an increased risk of developing the disease.

A review of the main genetic factors influencing the course of COVID-19 in Sardinia: the role of human leukocyte antigen-G.

Introduction: A large number of risk and protective factors have been identified during the SARS-CoV-2 pandemic which may influence the outcome of COVID-19. Among these, recent studies have explored the role of HLA-G molecules and their immunomodulatory effects in COVID-19, but there are very few reports exploring the genetic basis of these manifestations. The present study aims to investigate how host genetic factors, including HLA-G gene polymorphisms and sHLA-G, can affect SARS-CoV-2 infection. Materials and Methods: We compared the immune-genetic and phenotypic characteristics between COVID-19 patients (n = 381) with varying degrees of severity of the disease and 420 healthy controls from Sardinia (Italy). Results: HLA-G locus analysis showed that the extended haplotype HLA-G*01:01:01:01/UTR-1 was more prevalent in both COVID-19 patients and controls. In particular, this extended haplotype was more common among patients with mild symptoms than those with severe symptoms [22.7% vs 15.7%, OR = 0.634 (95% CI 0.440 - 0.913); P = 0.016]. Furthermore, the most significant HLA-G 3'UTR polymorphism (rs371194629) shows that the HLA-G 3'UTR Del/Del genotype frequency decreases gradually from 27.6% in paucisymptomatic patients to 15.9% in patients with severe symptoms (X2 = 7.095, P = 0.029), reaching the lowest frequency (7.0%) in ICU patients (X2 = 11.257, P = 0.004). However, no significant differences were observed for the soluble HLA-G levels in patients and controls. Finally, we showed that SARS-CoV-2 infection in the Sardinian population is also influenced by other genetic factors such as ß-thalassemia trait (rs11549407C>T in the HBB gene), KIR2DS2/HLA-C C1+ group combination and the HLA-B*58:01, C*07:01, DRB1*03:01 haplotype which exert a protective effect [P = 0.005, P = 0.001 and P = 0.026 respectively]. Conversely, the Neanderthal LZTFL1 gene variant (rs35044562A>G) shows a detrimental consequence on the disease course [P = 0.001]. However, by using a logistic regression model, HLA-G 3'UTR Del/Del genotype was independent from the other significant variables [ORM = 0.4 (95% CI 0.2 - 0.7), PM = 6.5 x 10-4]. Conclusion: Our results reveal novel genetic variants which could potentially serve as biomarkers for disease prognosis and treatment, highlighting the importance of considering genetic factors in the management of COVID-19 patients.

A Protective HLA Extended Haplotype Outweighs the Major COVID-19 Risk Factor Inherited From Neanderthals in the Sardinian Population.

Sardinia has one of the lowest incidences of hospitalization and related mortality in Europe and yet a very high frequency of the Neanderthal risk locus variant on chromosome 3 (rs35044562), considered to be a major risk factor for a severe SARS-CoV-2 disease course. We evaluated 358 SARS-CoV-2 patients and 314 healthy Sardinian controls. One hundred and twenty patients were asymptomatic, 90 were pauci-symptomatic, 108 presented a moderate disease course and 40 were severely ill. All patients were analyzed for the Neanderthal-derived genetic variants reported as being protective (rs1156361) or causative (rs35044562) for severe illness. The ß°39 C>T Thalassemia variant (rs11549407), HLA haplotypes, KIR genes, KIRs and their HLA class I ligand combinations were also investigated. Our findings revealed an increased risk for severe disease in Sardinian patients carrying the rs35044562 high risk variant [OR 5.32 (95% CI 2.53 - 12.01), p = 0.000]. Conversely, the protective effect of the HLA-A*02:01, B*18:01, DRB*03:01 three-loci extended haplotype in the Sardinian population was shown to efficiently contrast the high risk of a severe and devastating outcome of the infection predicted for carriers of the Neanderthal locus [OR 15.47 (95% CI 5.8 - 41.0), p < 0.0001]. This result suggests that the balance between risk and protective immunogenetic factors plays an important role in the evolution of COVID-19. A better understanding of these mechanisms may well turn out to be the biggest advantage in the race for the development of more efficient drugs and vaccines.

The double-sided of human leukocyte antigen-G molecules in type 1 autoimmune hepatitis.

The immunomodulatory effects of HLA-G expression and its role in cancers, human liver infections and liver transplantation are well documented, but so far, there are only a few reports addressing autoimmune liver diseases, particularly autoimmune hepatitis (AIH). Method and materials: We analyzed the genetic and phenotypic characteristics of HLA-G in 205 type 1 AIH patients (AIH-1) and a population of 210 healthy controls from Sardinia (Italy). Results: Analysis of the HLA-G locus showed no substantial differences in allele frequencies between patients and the healthy control population. The HLA-G UTR-1 haplotype was the most prevalent in both AIH-1 patients and controls (40.24% and 34.29%). Strong linkage was found between the HLA-G UTR-1 haplotype and HLA-DRB1*03:01 in AIH-1 patients but not controls (D' = 0.92 vs D' = 0.50 respectively; P = 1.3x10-8). Soluble HLA-G (sHLA-G) levels were significantly lower in AIH-1 patients compared to controls [13.9 (11.6 - 17.4) U/mL vs 21.3 (16.5 - 27.8) U/mL; P = 0.011]. Twenty-four patients with mild or moderate inflammatory involvement, as assessed from liver biopsy, showed much higher sHLA-G levels compared to the 28 patients with severe liver inflammation [33.5 (23.6 - 44.8) U/mL vs 8.8 (6.1 - 14.5) U/mL; P = 0.003]. Finally, immunohistochemistry analysis of 52 liver biopsies from AIH-1 patients did not show expression of HLA-G molecules in the liver parenchyma. However, a percentage of 69.2% (36/52) revealed widespread expression of HLA-G both in the cytoplasm and the membrane of plasma cells labeled with anti-HLA-G monoclonal antibodies. Conclusion: This study highlights the positive immunomodulatory effect of HLA-G molecules on the clinical course of AIH-1 and how this improvement closely correlates with plasma levels of sHLA-G. However, our results open the debate on the ambiguous role of HLA-G molecules expressed by plasma cells, which are pathognomonic features of AIH-1.