Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (<60 years) cases with no reported clinical risk factors (n = 378), compared to 0.24% of controls (odds ratio [OR] = 12.3, p = 1.27 × 10-10). Incorporation of the results of either functional assays or protein modeling led to a pronounced increase in effect size (ORmax = 46.5, p = 1.74 × 10-15). Association signals for the X-chromosomal gene TLR7 were also detected in the female-only subgroup, suggesting the existence of additional mechanisms beyond X-linked recessive inheritance in males. Additionally, supporting evidence was generated for a contribution to severe COVID-19 of the previously implicated genes IFNAR2, IFIH1, and TBK1. Our results refine the genetic contribution of rare TLR7 variants to severe COVID-19 and strengthen evidence for the etiological relevance of genes in the interferon signaling pathway.

This chapter aims to explore the usefulness of the latest advances in genetic studies in the field of the circadian system in the future development of individualised strategies for health improvement based on lifestyle intervention. Due to the multifactorial and complex nature of the circadian system, we focus on the highly prevalent phenotypes in the population that are key to understanding its biology from an evolutionary perspective and that can be modulated by lifestyle. Therefore, we leave in the background those phenotypes that constitute infrequent pathologies or in which the current level of scientific evidence does not favour the implementation of practical approaches of this type. Therefore, from an evolutionary paradigm, this chapter addresses phenotypes such as morning chronotypes, evening chronotypes, extreme chronotypes, and other key concepts such as circadian rhythm amplitude, resilience to changes in circadian rhythm, and their relationships with pathologies associated with circadian rhythm imbalances.

The impact of common and rare variants in COVID-19 host genetics has been widely studied. In particular, in Fallerini et al. (Human genetics, 2022, 141, 147-173), common and rare variants were used to define an interpretable machine learning model for predicting COVID-19 severity. First, variants were converted into sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. After that, the Boolean features, selected by these logistic models, were combined into an Integrated PolyGenic Score (IPGS), which offers a very simple description of the contribution of host genetics in COVID-19 severity.. IPGS leads to an accuracy of 55%-60% on different cohorts, and, after a logistic regression with both IPGS and age as inputs, it leads to an accuracy of 75%. The goal of this paper is to improve the previous results, using not only the most informative Boolean features with respect to the genetic bases of severity but also the information on host organs involved in the disease. In this study, we generalize the IPGS adding a statistical weight for each organ, through the transformation of Boolean features into \"Boolean quantum features,\" inspired by quantum mechanics. The organ coefficients were set via the application of the genetic algorithm PyGAD, and, after that, we defined two new integrated polygenic scores (IPGSph1 and IPGSph2). By applying a logistic regression with both IPGS, (IPGSph2 (or indifferently IPGSph1) and age as inputs, we reached an accuracy of 84%-86%, thus improving the results previously shown in Fallerini et al. (Human genetics, 2022, 141, 147-173) by a factor of 10%.

Aim: Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell non-Hodgkin lymphoma (NHL). Despite the availability of clinical and molecular algorithms applied for the prediction of prognosis, in up to 30%-40% of patients, intrinsic or acquired drug resistance occurs. Constitutional genetics may help to predict R-CHOP resistance. This study aimed to validate previously identified single nucleotide polymorphisms (SNPs) in the literature as potential predictors of R-CHOP resistance in DLBCL patients, SNPs. Methods: Twenty SNPs, involved in R-CHOP pharmacokinetics/pharmacodynamics or other pathobiological processes, were investigated in 185 stage I-IV DLBCL patients included in a multi-institution pharmacogenetic study to validate their previously identified correlations with resistance to R-CHOP. Results: Correlations between rs2010963 (VEGFA gene) and sex (P = 0.046), and rs1625895 (TP53 gene) and stage (P = 0.003) were shown. After multivariate analyses, a concordant effect (i.e., increased risk of disease progression and death) was observed for rs1883112 (NCF4 gene) and rs1800871 (IL10 gene). When patients were grouped according to the revised International Prognostic Index (R-IPI), both these SNPs further discriminated progression-free survival (PFS) and overall survival (OS) of the R-IPI-1-2 subgroup. Overall, patients harboring the rare allele showed shorter PFS and OS compared with wild-type patients. Conclusions: Two out of the 20 study SNPs were validated. Thus, these results support the role of previously identified rs1883112 and rs1800871 in predicting DLBCL resistance to R-CHOP and highlight their ability to further discriminate the prognosis of R-IPI-1-2 patients. These data point to the need to also focus on host genetics for a more comprehensive assessment of DLBCL patient outcomes in future prospective trials.

OBJECTIVE: This study aimed to explore the potential correlation between specific single nucleotide polymorphisms (TYK2, IFITM3, IFNAR2, and OAS3 variants) and the severity of COVID-19 in Moroccan patients.
METHODS: A genetic analysis was conducted on 109 patients with PCR-confirmed SARS-CoV-2 infection in Morocco. Among these patients, 46% were hospitalized in the intensive care unit, while 59% were not hospitalized. Importantly, all patients lacked known risk factors associated with COVID-19 severity. Genotyping was performed to identify variations in TYK2 rs74956615, IFITM3 rs12252, IFNAR2 rs2236757, and OAS3 rs10735079. Statistical analysis was applied using codominant, dominant and recessive logistic regression models to assess correlations with COVID-19 severity.
RESULTS: Our findings revealed no significant correlation between TYK2 rs74956615, IFITM3 rs12252, IFNAR2 rs2236757, and OAS3 rs10735079 with COVID-19 severity in Moroccan patients, as indicated in logistic regression models (p > .05). Interestingly, these results may offer insights into the mitigated impact of the COVID-19 pandemic and the reduced severity observed in SARS-CoV-2 infected patients in Morocco. Age, however, exhibited a significant correlation with severity (p < .001), with a trend towards increased likelihood of ICU admission with advancing age. Additionally, In the severe group, a higher proportion of patients were females (54%), indicating a statistically significant correlation with disease severity (p = .04). Nevertheless, female ICU patients aged above 60 years accounted for 37%, compared to 17% for males.
CONCLUSIONS: This study underscores the absence of a genetic association between the selected polymorphisms and COVID-19 severity in Moroccan patients. Advanced age emerges as the primary factor influencing the severity of COVID-19 patients without comorbidities. We recommend setting the threshold for advanced age at 60 years as a risk factor for severe forms of COVID-19.

Human genetic contribution to HIV progression remains inadequately explained. The type 1 interferon (IFN) pathway is important for host control of HIV and variation in type 1 IFN genes may contribute to disease progression. This study assessed the impact of variations at the gene and pathway level of type 1 IFN on HIV-1 viral load (VL).
Two cohorts of antiretroviral (ART) naïve participants living with HIV (PLWH) with either early (START) or advanced infection (FIRST) were analysed separately. Type 1 IFN genes (n = 17) and receptor subunits (IFNAR1, IFNAR2) were examined for both cumulated type 1 IFN pathway analysis and individual gene analysis. SKAT-O was applied to detect associations between the genotype and HIV-1 study entry viral load (log10 transformed) as a proxy for set point VL; P-values were corrected using Bonferroni (P < 0.0025).
The analyses among those with early infection included 2429 individuals from five continents. The median study entry HIV VL was 14,623 (IQR 3460-45100) copies/mL. Across 673 SNPs within 19 type 1 IFN genes, no significant association with study entry VL was detected. Conversely, examining individual genes in START showed a borderline significant association between IFNW1, and study entry VL (P = 0.0025). This significance remained after separate adjustments for age, CD4+ T-cell count, CD4+/CD8+ T-cell ratio and recent infection. When controlling for population structure using linear mixed effects models (LME), in addition to principal components used in the main model, this was no longer significant (p = 0.0244). In subgroup analyses stratified by geographical region, the association between IFNW1 and study entry VL was only observed among African participants, although, the association was not significant when controlling for population structure using LME. Of the 17 SNPs within the IFNW1 region, only rs79876898 (A > G) was associated with study entry VL (p = 0.0020, beta = 0.32; G associated with higher study entry VL than A) in single SNP association analyses. The findings were not reproduced in FIRST participants.
Across 19 type 1 IFN genes, only IFNW1 was associated with HIV-1 study entry VL in a cohort of ART-naïve individuals in early stages of their infection, however, this was no longer significant in sensitivity analyses that controlled for population structures using LME.

Objectives: This study combines two innovative mouse models in a major gene discovery project to assess the influence of host genetics on asbestos related disease (ARD). Conventional genetics studies provided evidence that some susceptibility to mesothelioma is genetic. However, the identification of host modifier genes, the roles they may play, and whether they contribute to disease susceptibility remain unknown. Here we report a study designed to rapidly identify genes associated with mesothelioma susceptibility by combining the Collaborative Cross (CC) resource with the well-characterised MexTAg mesothelioma mouse model. Methods: The CC is a powerful mouse resource that harnesses over 90% of common genetic variation in the mouse species, allowing rapid identification of genes mediating complex traits. MexTAg mice rapidly, uniformly, and predictably develop mesothelioma, but only after asbestos exposure. To assess the influence of host genetics on ARD, we crossed 72 genetically distinct CC mouse strains with MexTAg mice and exposed the resulting CC-MexTAg (CCMT) progeny to asbestos and monitored them for traits including overall survival, the time to ARD onset (latency), the time between ARD onset and euthanasia (disease progression) and ascites volume. We identified phenotype-specific modifier genes associated with these traits and we validated the role of human orthologues in asbestos-induced carcinogenesis using human mesothelioma datasets. Results: We generated 72 genetically distinct CCMT strains and exposed their progeny (2,562 in total) to asbestos. Reflecting the genetic diversity of the CC, there was considerable variation in overall survival and disease latency. Surprisingly, however, there was no variation in disease progression, demonstrating that host genetic factors do have a significant influence during disease latency but have a limited role once disease is established. Quantitative trait loci (QTL) affecting ARD survival/latency were identified on chromosomes 6, 12 and X. Of the 97-protein coding candidate modifier genes that spanned these QTL, eight genes (CPED1, ORS1, NDUFA1, HS1BP3, IL13RA1, LSM8, TES and TSPAN12) were found to significantly affect outcome in both CCMT and human mesothelioma datasets. Conclusion: Host genetic factors affect susceptibility to development of asbestos associated disease. However, following mesothelioma establishment, genetic variation in molecular or immunological mechanisms did not affect disease progression. Identification of multiple candidate modifier genes and their human homologues with known associations in other advanced stage or metastatic cancers highlights the complexity of ARD and may provide a pathway to identify novel therapeutic targets.

Tumor necrosis factor (TNF) and interferon-gamma (IFNγ) are important inflammatory mediators in the development of cytokine storm syndrome (CSS). Single nucleotide polymorphisms (SNPs) regulate the expression of these cytokines, making host genetics a key factor in the prognosis of COVID-19. In this study, we investigated the associations of the TNF -308G/A and IFNG +874T/A polymorphisms with COVID-19. We analyzed the frequencies of the two polymorphisms in the control groups (CG: TNF -308G/A, n = 497; IFNG +874T/A, n = 397), a group of patients with COVID-19 (CoV, n = 222) and among the subgroups of patients with nonsevere (n = 150) and severe (n = 72) COVID-19. We found no significant difference between the genotypic and allelic frequencies of TNF -308G/A in the groups analyzed; however, both the frequencies of the high expression genotype (TT) (CoV: 13.51% vs. CG: 6.30%; p = 0.003) and the *T allele (CoV: 33.56% vs. CG: 24. 81%; p = 0.001) of the IFNG +874T/A polymorphism were higher in the COVID-19 group than in the control group, with no differences between the subgroups of patients with nonsevere and severe COVID-19. The *T allele of IFNG +874T/A (rs2430561) is associated with susceptibility to symptomatic COVID-19. These SNPs provided valuables clues about the potential mechanism involved in the susceptibility to developing symptomatic COVID-19.

The coronavirus disease 2019 (COVID-19) has left a devasting effect on various regions globally. Africa has exceptionally high rates of other infectious diseases, such as tuberculosis (TB), human immunodeficiency virus (HIV), and malaria, and was not impacted by COVID-19 to the extent of other continents Globally, COVID-19 has caused approximately 7 million deaths and 700 million infections thus far. COVID-19 disease severity and susceptibility vary among individuals and populations, which could be attributed to various factors, including the viral strain, host genetics, environment, lifespan, and co-existing conditions. Host genetics play a substantial part in COVID-19 disease severity among individuals. Human leukocyte antigen (HLA) was previously been shown to be very important across host immune responses against viruses. HLA has been a widely studied gene region for various disease associations that have been identified. HLA proteins present peptides to the cytotoxic lymphocytes, which causes an immune response to kill infected cells. The HLA molecule serves as the central region for infectious disease association; therefore, we expect HLA disease association with COVID-19. Therefore, in this narrative review, we look at the HLA gene region, particularly, HLA class I, to understand its role in COVID-19 disease.

Invasive pulmonary aspergillosis is a severe fungal infection primarily affecting immunocompromised patients. Individuals with severe viral infections have recently been identified as vulnerable to developing invasive fungal infections. Both influenza-associated pulmonary aspergillosis (IAPA) and COVID-19-associated pulmonary aspergillosis (CAPA) are linked to high mortality rates, emphasizing the urgent need for an improved understanding of disease pathogenesis to unveil new molecular targets with diagnostic and therapeutic potential. The recent establishment of animal models replicating the co-infection context has offered crucial insights into the mechanisms that underlie susceptibility to disease. However, the development and progression of human viral-fungal co-infections exhibit a significant degree of interindividual variability, even among patients with similar clinical conditions. This observation implies a significant role for host genetics, but information regarding the genetic basis for viral-fungal co-infections is currently limited. In this review, we discuss how genetic factors known to affect either antiviral or antifungal immunity could potentially reveal pathogenetic mechanisms that predispose to IAPA or CAPA and influence the overall disease course. These insights are anticipated to foster further research in both pre-clinical models and human patients, aiming to elucidate the complex pathophysiology of viral-associated pulmonary aspergillosis and contributing to the identification of new diagnostic and therapeutic targets to improve the management of these co-infections.