Roberto Littera

Idiopathic Pulmonary Fibrosis (IPF) is a progressive and fatal lung disease with limited treatment options. Nintedanib and pirfenidone are the only antifibrotic drugs approved by both the USA and European medicinal agencies, but their efficacy and tolerability remain concerns. This exploratory study investigates the association between genetic variation in the Major Histocompatibility Complex (MHC) region and adverse effects (AEs) of these therapies. HLA genotyping has been previously performed in a discovery cohort of 124 IPF Italian patients, with recorded drug‐related AEs. Logistic regression analysis using an additive model identified HLA‐C*06:02 as a significant risk factor, increasing the likelihood of AEs sixfold in nintedanib ‐treated patients ( p = 0.0043, OR = 6.54, 95% C.I. 1.80–23.75). Notably, gastrointestinal toxicity—the most common AE—was strongly associated with this allele ( p = 0.0005, OR = 11.85, 95% C.I. 2.94–47.71). These findings suggest a potential immune‐mediated mechanism involving IL‐23‐driven inflammation and underscore the importance of pharmacogenetic tools in tailoring antifibrotic therapy. Implementing genetic screening could help minimize AEs and improve patient outcomes. Larger studies are warranted to validate these associations and guide personalized treatment strategies.

Introduction: Primary biliary cholangitis (PBC) is a rare autoimmune liver disease involving bile duct damage and fibrosis. This study explores the role of HLA-G, an immunomodulatory molecule crucial for immune tolerance, in PBC pathogenesis and treatment.Methods: A cohort of 166 PBC patients from Sardinia was compared to 180 healthy controls and 205 autoimmune hepatitis type 1 (AIH-1) patients. Plasma soluble HLA-G (sHLA-G) levels, HLA-G alleles, and 3’UTR haplotypes were analyzed alongside clinical data, including therapy response to ursodeoxycholic acid.Results: The UTR-1 haplotype was significantly more frequent in PBC patients than in controls (48.2% vs 34.3%, Pc= 0.0018). The extended haplotype HLA-G*01:01:01:08/UTR-1 was also strongly associated with PBC (23.2% vs 12.5% in controls, Pc = 0.008; 23.2% vs 6.6% in AIH-1, Pc= 2.6×10_-9). PBC patients exhibited lower sHLA-G levels compared to controls and AIH-1 (9.1 U/mL vs 24.03 U/mL and 13.9 U/mL, respectively). Among UTR-1 carriers, sHLA-G levels were particularly reduced in PBC patients. The HLA-G*01:01:01:08/UTR-1 haplotype correlated with the lowest sHLA-G levels and poorer therapy response (60% vs 24.1%, P = 0.0001).Discussion: These findings suggest HLA-G variants, especially HLA-G*01:01:01:08/UTR-1, as potential biomarkers for PBC prognosis and treatment outcomes.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease characterized by the disruption of the alveolar and interstitial architecture due to extracellular matrix deposition. Emerging evidence suggests that genetic susceptibility plays a crucial role in IPF development. This study explores the role of human leukocyte antigen (HLA) alleles and haplotypes in IPF susceptibility and progression within the genetically distinct Sardinian population. Genotypic data were analyzed for associations with disease onset and progression, focusing on allele and haplotype frequencies in patients exhibiting slow (S) or rapid (R) progression. While no significant differences in HLA allele frequencies were observed between IPF patients and controls, the HLA-DRB1*04:05 allele and the extended haplotype (HLA-A*30:02, B*18:01, C*05:01, DQA1*05:01, DQB1*02:01, DRB1*03:01) were associated with a slower disease progression and improved survival (log-rank = 0.032 and 0.01, respectively). At 36 months, carriers of these variants demonstrated significantly better pulmonary function, measured with single-breath carbon monoxide diffusing capacity (DLCO%p) (p = 0.005 and 0.02, respectively). Multivariate analysis confirmed these findings as being independent of confounding factors. These results highlight the impact of HLA alleles and haplotypes on IPF outcomes and underscore the potential of the Sardinian genetic landscape to illuminate immunological mechanisms, paving the way for predictive biomarkers and personalized therapies.

Background: Antibody-mediated rejection is a significant cause of kidney transplant failure. Recent studies have shown that the MHC class I MICA gene influences the transplantation outcome. However, the role of the primary MICA receptor, NKG2D, has yet to be explored.Aim: We aimed to investigate the correlation between recipient/donor MICA allele matching and NKG2D genotype with the risk of antibody-mediated rejection and their potential clinical effects and implications for organ maintenance therapy.Methods: Of the 524 patients who underwent transplantation, 387 were eligible for the study. Complete MICA allele and two functional polymorphisms of NKG2D (rs1049174C>G and rs2255336G>A) were analyzed in 148 transplanted patients and 146 controls.Results: Increased recipient/donor MICA allele mismatches correlate with an elevated risk of antibody-mediated rejection (X² = 6.95; Log-rank=0.031). Notably, the rs1049174[GG] genotype contributes to a significantly increased risk of antibody-mediated rejection (X² = 13.44; Log-rank=0.001 and X² = 0.34; Log-rank=0.84). The combined effect of two MICA allele mismatches and rs1049174[GG] genotype shows the highest risk (X² = 23.21; Log-rankrs1049174[GG] and rs2255336[AA] genotypes may respond less to mTOR inhibitor immunosuppressive therapy than Calcineurin inhibitors (rs1049174[GG]; P=0.035; and rs2255336[AA]; P=0.002).Conclusion: Recipient/donor MICA allele mismatches and specific NKG2D variants, as well as their combinations, influence kidney transplant outcomes, providing insights for personalized treatment and enhancing graft survival.

Background: The disruption of social rhythms was found to be associated with depressive disorders during the COVID-19 pandemic; lower rates of these disorders were surprisingly found in old adults. The present study aims to verify the stability of social rhythms during lockdown in a sample of elderly people. Methods: Controlled cohort study (secondary analyses) of a previous randomized-controlled trial with the first evaluation in April 2019 (T0) and then 48 weeks later (T1) during the lockdown. The regulation of social and behavioral rhythms was measured through the Brief Social Rhythms Scale (BSRS); the Patient Health Questionnaire-9 (PHQ9) was adopted to detect relevant depressive symptoms. Results: 93 elderlies (73.36 ± 4.97 years old, 50.5% females) were evaluated at T0 and T1. Neither the total score of BSRS nor any of the 10 items showed a statistically significant difference comparing the two survey periods. The frequency of relevant depressive symptoms was 5.3% at T0 and 6.4% at T1 (OR = 0.8, CI95% 0.2–24). Conclusions: Among elderlies who did not show an increased risk of depression during the lockdown, social and behavioral rhythms remained exceptionally stable during the same period. Considering previous evidence about rhythms dysregulation preceding depression, their stability may be considered a factor of resilience.

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.

This review aimed to compare the different responses of countries to the pandemic, their National Health Systems, and their impact on citizens' health. This work aimed to create a narrative plot that connects different discussion points and suggests organizational solutions and strategic choices in the face of the pandemic. In particular, this work focused on public health organizations, specifically the European Union and vaccination politics. It is also based on a case report series (about the United States, Germany, Vietnam, New Zealand, Cuba, and Italy), where each country has responded differently to the pandemic in terms of political decisions such as vaccination type, information to citizens, dealings with independent experts, and other specific country factors. In comparing the various models of care systems response to the pandemic, it emerges that: we have found some (few) good practices, but without global coordination, and this is obviously not enough. It is now quite clear that there cannot be a "good answer" in a single nation. Uncoordinated local responses cannot counter a global phenomenon. The second point is that the general context must be considered from a strategic point of view. With the threat of new pandemics (but also of health disasters linked to climate change, pollution, and wars), humanity finds itself at the crossroads between investing in a "democratic" management of international bodies but without power (and at the mercy of the need for funds with consequent conflicts) or in some new leadership proposals that advocate efficiency and problem-solving (and that would probably be able to implement it) but that would place processes totally outside of the public's control.

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 β-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 [OR_M = 0.4 (95% CI 0.2 – 0.7), P_M = 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.

Vaccine hesitancy and conspiracy beliefs among healthcare workers (HCWs) represent operational priorities that require urgent attention. Identifying and classifying specific subpopulation of hesitancy is crucial to customize educational and intervention strategies to enhance the acceptance and uptake rate of vaccination. Thus, the main purpose of our study was to empirically identify latent profiles of vaccine hesitancy among Italian HCWs adopting a person-centered approach and investigating their relationships with antecedents and intention to get a fourth dose of COVID-19 vaccine. We conducted latent profile analyses (LPA) to identify different configurations of vaccine hesitancy based on five antecedents of vaccination: confidence, complacency, constraints, calculation, and collective responsibility among a sample of Italian HCWs (n = 573). LPA revealed four distinct profiles: believer (61.5%), middler (24.7%), hesitant (9.00%), and rejecter (4.7%). Having conspiracy beliefs was associated with a greater likelihood of membership in all but believer. Finally, the likelihood of intention to get a fourth dose of COVID-19 vaccine was lowest in the rejector and hesitant profiles. Theoretical contributions and implications for practice are discussed.

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.