Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features.

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%.

Human leukocyte antigen variants associate with BNT162b2 mRNA vaccine response.

BACKGROUND: Since the beginning of the anti-COVID-19 vaccination campaign, it has become evident that vaccinated subjects exhibit considerable inter-individual variability in the response to the vaccine that could be partly explained by host genetic factors. A recent study reported that the immune response elicited by the Oxford-AstraZeneca vaccine in individuals from the United Kingdom was influenced by a specific allele of the human leukocyte antigen gene HLA-DQB1. METHODS: We carried out a genome-wide association study to investigate the genetic determinants of the antibody response to the Pfizer-BioNTech vaccine in an Italian cohort of 1351 subjects recruited in three centers. Linear regressions between normalized antibody levels and genotypes of more than 7 million variants was performed, using sex, age, centers, days between vaccination boost and serological test, and five principal components as covariates. We also analyzed the association between normalized antibody levels and 204 HLA alleles, with the same covariates as above. RESULTS: Our study confirms the involvement of the HLA locus and shows significant associations with variants in HLA-A, HLA-DQA1, and HLA-DQB1 genes. In particular, the HLA-A*03:01 allele is the most significantly associated with serum levels of anti-SARS-CoV-2 antibodies. Other alleles, from both major histocompatibility complex class I and II are significantly associated with antibody levels. CONCLUSIONS: These results support the hypothesis that HLA genes modulate the response to Pfizer-BioNTech vaccine and highlight the need for genetic studies in diverse populations and for functional studies aimed to elucidate the relationship between HLA-A*03:01 and CD8+ cell response upon Pfizer-BioNTech vaccination.

It is known that people respond differently to vaccines. It has been proposed that differences in their genes might play a role. We studied the individual genetic makeup of 1351 people from Italy to see if there was a link between their genes and how well they responded to the BNT162b2 mRNA COVID-19 vaccine. We discovered certain genetic differences linked to higher levels of protection in those who got the vaccine. Our findings suggest that individual's genetic characteristics play a role in vaccine response. A larger population involving diverse ethnic backgrounds will need to be studied to confirm the generalizability of these findings. Better understanding of this could facilitate improved vaccine designs against new SARS-CoV-2 variants.

FOXG1 variants can be associated with milder phenotypes than congenital Rett syndrome with unassisted walking and language development.

Since 2008, FOXG1 haploinsufficiency has been linked to a severe neurodevelopmental phenotype resembling Rett syndrome but with earlier onset. Most patients are unable to sit, walk, or speak. For years, FOXG1 sequencing was only prescribed in such severe cases, limiting insight into the full clinical spectrum associated with this gene. Next-generation sequencing (NGS) now enables unbiased diagnostics. Through the European Reference Network for Rare Malformation Syndromes, Intellectual and Other Neurodevelopmental Disorders, we gathered data from patients with heterozygous FOXG1 variants presenting a mild phenotype, defined as able to speak and walk independently. We also reviewed data from three previously reported patients meeting our criteria. We identified five new patients with pathogenic FOXG1 missense variants, primarily in the forkhead domain, showing varying nonspecific intellectual disability and developmental delay. These features are not typical of congenital Rett syndrome and were rarely associated with microcephaly and epilepsy. Our findings are consistent with a previous genotype-phenotype analysis by Mitter et al. suggesting the delineation of five different FOXG1 genotype groups. Milder phenotypes were associated with missense variants in the forkhead domain. This information may facilitate prognostic assessments in children carrying a FOXG1 variant and improve the interpretation of new variants identified with genomic sequencing.

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death.

The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10-8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10-8). A total of 113 variants were associated with survival at P-value < 1.0 × 10-5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways.

HLA-DPB1*13:01 associates with enhanced, and KIR2DS4*001 with diminished protection from developing severe COVID-19.

Extreme polymorphism of HLA and killer-cell immunoglobulin-like receptors (KIR) differentiates immune responses across individuals. Additional to T cell receptor interactions, subsets of HLA class I act as ligands for inhibitory and activating KIR, allowing natural killer (NK) cells to detect and kill infected cells. We investigated the impact of HLA and KIR polymorphism on the severity of COVID-19. High resolution HLA class I and II and KIR genotypes were determined from 403 non-hospitalized and 1575 hospitalized SARS-CoV-2 infected patients from Italy collected in 2020. We observed that possession of the activating KIR2DS4*001 allotype is associated with severe disease, requiring hospitalization (OR = 1.48, 95% CI 1.20-1.85, pc = 0.017), and this effect is greater in individuals homozygous for KIR2DS4*001 (OR = 3.74, 95% CI 1.75-9.29, pc = 0.003). We also observed the HLA class II allotype, HLA-DPB1*13:01 protects SARS-CoV-2 infected patients from severe disease (OR = 0.49, 95% CI 0.33-0.74, pc = 0.019). These association analyses were replicated using logistic regression with sex and age as covariates. Autoantibodies against IFN-α associated with COVID-19 severity were detected in 26% of 156 hospitalized patients tested. HLA-C*08:02 was more frequent in patients with IFN-α autoantibodies than those without, and KIR3DL1*01502 was only present in patients lacking IFN-α antibodies. These findings suggest that KIR and HLA polymorphism is integral in determining the clinical outcome following SARS-CoV-2 infection, by influencing the course both of innate and adaptive immunity.

Case report: PIK3CA somatic mutation leading to Klippel Trenaunay Syndrome and multiple tumors.

We report a case of Klippel Trenaunay Syndrome that was monitored both clinically and molecularly over a period of 9 years. A somatic mosaic mutation of PIK3CA (p(E545G)) was identified using both cfDNA NGS liquid biopsy and tissue biopsy. At the age of 56, due to intervening clonal mutations in PIK3CA background, she developed a squamous cell carcinoma in the right affected leg which was treated surgically. Nine years later, lung bilateral adenocarcinoma arose on PIK3CA mutated tissues supported by different clonal mutations. One year later, the patient died from metastases led by a new FGFR3 clone unresponsive to standard-of-care, immunotherapy-based. Our results highlight the presence of a molecular hallmark underlying neoplastic transformation that occurs upon an angiodysplastic process and support the view that PIK3CA mutated tissues must be treated as precancerous lesions. Importantly, they remark the effectiveness of combining cfDNA NGS liquid and tissue biopsies to monitor disease evolution as well as to identify aggressive clones targetable by tailored therapy, which is more efficient than conventional protocols.

CYP19A1 mediates severe SARS-CoV-2 disease outcome in males.

Male sex represents one of the major risk factors for severe COVID-19 outcome. However, underlying mechanisms that mediate sex-dependent disease outcome are as yet unknown. Here, we identify the CYP19A1 gene encoding for the testosterone-to-estradiol metabolizing enzyme CYP19A1 (also known as aromatase) as a host factor that contributes to worsened disease outcome in SARS-CoV-2-infected males. We analyzed exome sequencing data obtained from a human COVID-19 cohort (n = 2,866) using a machine-learning approach and identify a CYP19A1-activity-increasing mutation to be associated with the development of severe disease in men but not women. We further analyzed human autopsy-derived lungs (n = 86) and detect increased pulmonary CYP19A1 expression at the time point of death in men compared with women. In the golden hamster model, we show that SARS-CoV-2 infection causes increased CYP19A1 expression in the lung that is associated with dysregulated plasma sex hormone levels and reduced long-term pulmonary function in males but not females. Treatment of SARS-CoV-2-infected hamsters with a clinically approved CYP19A1 inhibitor (letrozole) improves impaired lung function and supports recovery of imbalanced sex hormones specifically in males. Our study identifies CYP19A1 as a contributor to sex-specific SARS-CoV-2 disease outcome in males. Furthermore, inhibition of CYP19A1 by the clinically approved drug letrozole may furnish a new therapeutic strategy for individualized patient management and treatment.

Ultra-rare RTEL1 gene variants associate with acute severity of COVID-19 and evolution to pulmonary fibrosis as a specific long COVID disorder.

BACKGROUND: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a novel coronavirus that caused an ongoing pandemic of a pathology termed Coronavirus Disease 19 (COVID-19). Several studies reported that both COVID-19 and RTEL1 variants are associated with shorter telomere length, but a direct association between the two is not generally acknowledged. Here we demonstrate that up to 8.6% of severe COVID-19 patients bear RTEL1 ultra-rare variants, and show how this subgroup can be recognized. METHODS: A cohort of 2246 SARS-CoV-2-positive subjects, collected within the GEN-COVID Multicenter study, was used in this work. Whole exome sequencing analysis was performed using the NovaSeq6000 System, and machine learning methods were used for candidate gene selection of severity. A nested study, comparing severely affected patients bearing or not variants in the selected gene, was used for the characterisation of specific clinical features connected to variants in both acute and post-acute phases. RESULTS: Our GEN-COVID cohort revealed a total of 151 patients carrying at least one RTEL1 ultra-rare variant, which was selected as a specific acute severity feature. From a clinical point of view, these patients showed higher liver function indices, as well as increased CRP and inflammatory markers, such as IL-6. Moreover, compared to control subjects, they present autoimmune disorders more frequently. Finally, their decreased diffusion lung capacity for carbon monoxide after six months of COVID-19 suggests that RTEL1 variants can contribute to the development of SARS-CoV-2-elicited lung fibrosis. CONCLUSION: RTEL1 ultra-rare variants can be considered as a predictive marker of COVID-19 severity, as well as a marker of pathological evolution in pulmonary fibrosis in the post-COVID phase. This notion can be used for a rapid screening in hospitalized infected people, for vaccine prioritization, and appropriate follow-up assessment for subjects at risk. Trial Registration NCT04549831 ( www. CLINICALTRIAL: org ).

Effects of the Rho GTPase-activating toxin CNF1 on fibroblasts derived from Rett syndrome patients: A pilot study.

The bacterial product CNF1, through its action on the Rho GTPases, is emerging as a modulator of crucial signalling pathways involved in selected neurological diseases characterized by mitochondrial dysfunctions. Mitochondrial impairment has been hypothesized to have a key role in paramount mechanisms underlying Rett syndrome (RTT), a severe neurologic rare disorder. CNF1 has been already reported to have beneficial effects in mouse models of RTT. Using human RTT fibroblasts from four patients carrying different mutations, as a reliable disease-in-a-dish model, we explored the cellular and molecular mechanisms, which can underlie the CNF1-induced amelioration of RTT deficits. We found that CNF1 treatment modulates the Rho GTPases activity of RTT fibroblasts and induces a considerable re-organization of the actin cytoskeleton, mainly in stress fibres. Mitochondria of RTT fibroblasts show a hyperfused morphology and CNF1 decreases the mitochondrial mass leaving substantially unaltered the mitochondrial dynamic. From a functional perspective, CNF1 induces mitochondrial membrane potential depolarization and activation of AKT in RTT fibroblasts. Given that mitochondrial quality control is altered in RTT, our results are suggestive of a reactivation of the damaged mitochondria removal via mitophagy restoration. These effects can be at the basis of the beneficial effects of CNF1 in RTT.

Corrigendum: Spondyloocular syndrome: A novel XYLT2 variant with description of the neonatal phenotype.

[This corrects the article DOI: 10.3389/fgene.2021.761264.].

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing.

PURPOSE: Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the "ClinVar low-hanging fruit" reanalysis, reasons for the failure of previous analyses, and lessons learned. METHODS: Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. RESULTS: We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). CONCLUSION: The "ClinVar low-hanging fruit" analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock.

Heterozygosity for neuronal ceroid lipofuscinosis predisposes to bipolar disorder

Objective: Bipolar disorder is a heritable chronic mental disorder that causes psychosocial impairment through depressive/manic episodes. Familial transmission of bipolar disorder does not follow simple Mendelian patterns of inheritance. The aim of this study was to describe a large family with 12 members affected by bipolar disorder. Whole-exome sequencing was performed for eight members, three of whom were diagnosed with bipolar disorder, and another reported as "borderline." Methods: Whole-exome sequencing data allowed us to select variants that the affected members had in common, including and excluding the "borderline" individual with moderate anxiety and obsessive-compulsive traits. Results: The results favored designating certain genes as predispositional to bipolar disorder: a heterozygous missense variant in CLN6 resulted in a "borderline" phenotype that, if combined with a heterozygous missense variant in ZNF92, is responsible for the more severe bipolar disorder phenotype. Both rare missense changes are predicted to disrupt protein function. Conclusions: Loss of both alleles in CLN6 causes neuronal ceroid lipofuscinosis, a severe progressive childhood neurological disorder. Our results indicate that heterozygous CLN6 carriers, previously reported as healthy, may be susceptible to bipolar disorder later in life if associated with additional variants in ZNF92.

Heterozygosity for neuronal ceroid lipofuscinosis predisposes to bipolar disorder.

OBJECTIVE: Bipolar disorder is a heritable chronic mental disorder that causes psychosocial impairment through depressive/manic episodes. Familial transmission of bipolar disorder does not follow simple Mendelian patterns of inheritance. The aim of this study was to describe a large family with 12 members affected by bipolar disorder. Whole-exome sequencing was performed for eight members, three of whom were diagnosed with bipolar disorder, and another reported as "borderline." METHODS: Whole-exome sequencing data allowed us to select variants that the affected members had in common, including and excluding the "borderline" individual with moderate anxiety and obsessive-compulsive traits. RESULTS: The results favored designating certain genes as predispositional to bipolar disorder: a heterozygous missense variant in CLN6 resulted in a "borderline" phenotype that, if combined with a heterozygous missense variant in ZNF92, is responsible for the more severe bipolar disorder phenotype. Both rare missense changes are predicted to disrupt protein function. CONCLUSIONS: Loss of both alleles in CLN6 causes neuronal ceroid lipofuscinosis, a severe progressive childhood neurological disorder. Our results indicate that heterozygous CLN6 carriers, previously reported as healthy, may be susceptible to bipolar disorder later in life if associated with additional variants in ZNF92.

Gain- and Loss-of-Function CFTR Alleles Are Associated with COVID-19 Clinical Outcomes.

Carriers of single pathogenic variants of the CFTR (cystic fibrosis transmembrane conductance regulator) gene have a higher risk of severe COVID-19 and 14-day death. The machine learning post-Mendelian model pinpointed CFTR as a bidirectional modulator of COVID-19 outcomes. Here, we demonstrate that the rare complex allele [G576V;R668C] is associated with a milder disease via a gain-of-function mechanism. Conversely, CFTR ultra-rare alleles with reduced function are associated with disease severity either alone (dominant disorder) or with another hypomorphic allele in the second chromosome (recessive disorder) with a global residual CFTR activity between 50 to 91%. Furthermore, we characterized novel CFTR complex alleles, including [A238V;F508del], [R74W;D1270N;V201M], [I1027T;F508del], [I506V;D1168G], and simple alleles, including R347C, F1052V, Y625N, I328V, K68E, A309D, A252T, G542*, V562I, R1066H, I506V, I807M, which lead to a reduced CFTR function and thus, to more severe COVID-19. In conclusion, CFTR genetic analysis is an important tool in identifying patients at risk of severe COVID-19.

An explainable model of host genetic interactions linked to COVID-19 severity.

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.

Rare coding variation provides insight into the genetic architecture and phenotypic context of autism.

Some individuals with autism spectrum disorder (ASD) carry functional mutations rarely observed in the general population. We explored the genes disrupted by these variants from joint analysis of protein-truncating variants (PTVs), missense variants and copy number variants (CNVs) in a cohort of 63,237 individuals. We discovered 72 genes associated with ASD at false discovery rate (FDR) ≤ 0.001 (185 at FDR ≤ 0.05). De novo PTVs, damaging missense variants and CNVs represented 57.5%, 21.1% and 8.44% of association evidence, while CNVs conferred greatest relative risk. Meta-analysis with cohorts ascertained for developmental delay (DD) (n = 91,605) yielded 373 genes associated with ASD/DD at FDR ≤ 0.001 (664 at FDR ≤ 0.05), some of which differed in relative frequency of mutation between ASD and DD cohorts. The DD-associated genes were enriched in transcriptomes of progenitor and immature neuronal cells, whereas genes showing stronger evidence in ASD were more enriched in maturing neurons and overlapped with schizophrenia-associated genes, emphasizing that these neuropsychiatric disorders may share common pathways to risk.

Nosological and Theranostic Approach to Vascular Malformation through cfDNA NGS Liquid Biopsy.

Several different nosological classifications have been used over time for vascular malformations (VMs) since clinical and pathological signs are largely overlapping. In a large proportion of cases, VMs are generated by somatic mosaicism in key genes, belonging to a few different molecular pathways. Therefore, molecular characterization may help in the understanding of the biological mechanisms related to the development of pathology. Tissue biopsy is not routinely included in the diagnostic path because of the need for fresh tissue specimens and the risk of bleeding. Bypassing the need for bioptic samples, we took advantage of the possibility of isolating cell-free DNA likely released by the affected tissues, to molecularly characterize 53 patients by cfDNA-NGS liquid biopsy. We found a good match between the identified variant and the clinical presentation. PIK3CA variants were found in 67% of Klippel Trenaunay Syndrome individuals; KRAS variants in 60% of arteriovenous malformations; MET was mutated in 75% of lymphovenous malformations. Our results demonstrate the power of cfDNA-NGS liquid biopsy in VMs clinical classification, diagnosis, and treatment. Indeed, tailored repurposing of pre-existing cancer drugs, such as PIK3CA, KRAS, and MET inhibitors, can be envisaged as adjuvant treatment, in addition to surgery and/or endovascular treatment, in the above-defined VMs categories, respectively.