Antivirals and monoclonal antibody combination therapy in haematological patients in the omicron era

Abstract: Im We describe here a single-center case series of 27 IC COVID-19 inpatients (mostly with haematological disorders) treated with a combined therapy based on tixagevimab/cilgavimab (T/C) plus small-molecule antivirals (AV), between April 1 2022 and November 30 2022.  Keywords: immunocompromised; SARS-CoV-2 infection; monoclonal antibodies; antivirals; persistent infection; viral evolutio

Investigation of cartlilage aging by means of MRI, DTI and DS techniques

Articular cartilage (AC) is an aneural and avascular tissue that covers the ends of articulating bones in diarthrodial joints, and its main functions are to distribute joint loading and to provide nearly frictionless movement of the articulating bones. The mechanical properties of AC can be attribute to the complex structure of its extracellular matrix (ECM), mainly composed by collagen fibres, proteoglycan (PG) aggregates and interstitial water [1, 2]. Nowadays, the progression of mean expectation of life has highlighted the importance of a correct diagnosis for many age-related diseases. In AC, aging process occur in older age with cellular senescence [3, 4] and ECM modifications [5, 6], frequently involving in Osteoarthritic diseases [7–9]. Osteoarthritis (OA) is the most common degenerative joint disease and represent one of the most common disabilities cause (6,6% of Italian population, actually), posing a high economical burden to society. OA is characterized by the proceeding destruction of AC by uncontrolled proteolysis of ECM and typically leads to a remodeling of affected joints. No treatment neither early diagnosis method currently exist for OA pathologies, and the detection of differences and relations between early OA and aging is still an open field in clinical research [3, 8, 10]. To understand the progression of the disease, the comprehension of mechanisms involving on to ECM components during AC degradation is essential. The reduction of PGs concentration is recognized as the first symptom of degeneration in OA [11–14], while collagen fibers result more resistant from degradation. Using different experimental techniques, it is possible to observe the contribution of degradation of a specific macromolecule to the AC disease progression. Dielectric Spectroscopy (DS) resulted as an indirect indicator of collagen fibrils integrity through observation of intermolecular hydrogen bounds formation between water molecules [15]. Moreover, some water molecules result oriented along collagen fibers and that orientation is well recognized by Magnetic Resonance T2 -weighted imaging (T2w-MRI) contrast variations through intra-molecular dipole interactions of water hydrogen nuclei[16-18]. The study of the dynamic of water molecules in cartilage resulted to provide information on cartilage structure [19-21]. Diffusion Tensor Imaging (DTI) [22-26] is a widely used Magnetic Resonance technique to investigate fiber microstructures in human brain, like in skeletal muscle tissue [27]. Moreover, some authors [20, 28, 29] have demonstrated that DTI technique can recognise collagen fibril orientation and other authors [20, 30, 31] have shown how the reduction of proteoglycan content in cartilage affect water Apparent Diffusion Coefficient (ADC). For all the cartilage futures listed so far, and taking into account the potentiality provided by DTI investigations, here we monitored cartilage aging by means of DTI and T2 -weighted imaging techniques. Specifically, starting to the observation that in cartilage is generally observed a reduction in water content during aging [32], we investigate in vitro cartilage samples during natural dehydration process. Moreover, we combined NMR with DS measurements to deeply investigate structural variation in cartilage matrix. [1] Zernia, G. 2006. Collagen dynamics in articular cartilage under osmotic pressure. NMR Biomed. 19:1010-1019. [2] Newman, A.P. 1998. Articular cartilage repair. Am. J. Sports. Med. 26:309-324. [3] R. F. Loeser. Aging and osteoarthritis. Curr. Op. Rheum.,(23), 492 (2011). [4] H. Muir. The chondrocyte, architect of cartilage. biomechanics,structure, function and molecular biology of cartilage matrix macromolecules. Bioessays, (17), 1039 (1995). [5] E. Wachtel, A. Maroudas and R. Schneiderman. Age-related changes in collagen packing of human articular cartilage. Bioch. Bioph. Acta, (1243), 239 (1995). [6] J. Dudhia. Aggrecan, aging and assembly in articular cartilage.Cellular and Molecular Life Sciences, (62), 2241 (2005). [7] M. B. Goldring and S. R. Goldring. Osteoarthritis. J. Cell. Physiol., (213), 626 (2007). [8] D. Umlauf, S. Frank, T. Pap and J. Bertrand. Cartilage biology, pathology, and repair. Cellular and Molecular Life Sciences,(67), 41974211 (2010). [9] F. Eckstein, M. Kunzy, M. Schutzery, M. Hudelmaier, R. D.Jackson, J. Yu, C. B. Eaton and E. Schneider. Two year longitudinal change and teste-retest-precision of knee cartilage morphology in a pilot study for the osteoarthritis initiative. OsteoArthritis and Cartilage, (15), 1326 (2007). [10] M. Beekhuizen, Y. M. Bastiaansen-Jenniskens, W. Koevoet,D. B. F. Saris, W. J. A. Dhert, L. B. Creemers and G. J. V. M.van Osch. Osteoarthritic synovial tissue inhibition of proteoglycan production in human osteoarthritic knee cartilage. Arth.& Rheum., (63), 1918 (2011). [11] H. J. Mankin, H. Dorfman, L. Lippiello and L. Zarins. Biochemical and metabolic abnormalities in articular cartilage from osteoarthritic human hips. ii: Correlation of morphology with biochemical and metabolic data. J. Bone Joint. Surg. Am., (53), 523 (1971). [12] A. A. V. de Loo, O. Arntz, I. Otterness and W. V. den Berg. Proteoglycan loss and subsequent replenishment in articularcartilage after a mild arthritic insult by il-1 in mice: impaired proteoglycan turnover in the recovery phase. Ag. Act., (41), 200 (1994). [13] G. Grushko, R. Schneiderman and A. Maroudas. Some bichemical and biophysical parameters for the study of the pathogenesis of osteoarthritis: comparison between the processes of aging and degeneration in human hip cartilage. Conn. Tiss. Res., (19), 149 (1989). [14] J. Degroot, N. Verzijl, R. Bank, F. P. J. Lafeber, J. W. J. Bijlsma and J. Tekoppele. Age-related decrease in proteoglycan syntesis of human articular chondrocytes. Arth. Reum., (42), 1003 (1999). [15] J. R. Grigera, F. Vericat, K. Hallenga and H. Berendsen. Dielectric properties of hydrated collagen. Biopol., (18), 35 (1979). [16] Akella, S.V.S., R.R. Regatte, A.J. Wheaton, A. Borthakur, and R. Reddy. 2004. Reduction of Residual Dipolar Interaction in Cartilage by Spin-Lock Technique. Magn. Res. Med. 52:1103-1109. [17] Migchelsen, C. and H.J.C. Berendsen. 1973. Proton exchange and molecular orientation of water in hydrated collagen fibers. J.Chem.Phys. 59(1):296-305. [18] Shinar, H., and G. Navon. 2006. Multinuclear NMR and Microscopic MRI studies of articular cartilage nanostructure. NMR Biomed.19:877-893. [19] Filidoro, L., O. Dietrich, J. Weber, E. Rauch, T. Oerther, M. Wick, M.F. Reiser, and C. Glaser. 2005. High-Resolution DTI of human patellar cartilage: feasibility and preliminary findings. Magn. Res. Med. 53:993-998. [20] Raya, J.G., Melkus, G., Adam-Neumair, S., Dietrich, O., Mutzel, E., Kahr, B., Reiser, M.F., Jakob, P.M., Putz, R. and C. Glaser. 2011. Change of diffusion tensor imaging parameters in articular cartilage with progressive proteoglycan extraction. Invest. Radiol. 46:401-409. [21] Azuma, T., Nakai, R., Takizawa O. and S. Tsutsumi. 2009. In vivo structural analysis of articular cartilage using diffusion tensor magnetic resonance imaging. Magn. Res. Im. 27:1242-1248. [22] Basser, P.J., and C. Pierpaoli. 1996. Microstructural and Physiological Features of Tissues elucidated by Quantitative-Diffusion-Tensor MRI. J.Magn.Res. 111:209-219. [23] Pierpaoli, C., P. Jezzard, P.J. Basser, J. Barnett , and G. Di Chiro. 1996. Diffusion tensor MR imaging of the human brain. Radiol. 201:637-648. [24] Basser, P.J., J. Mattiello, and D. LeBihan. 1994. MR Diffusion Tensor Spectroscopy and Imaging. Bioph. J. 66:259-267. [25] Le Bihan, D. 1991. Molecular diffusion nuclear magnetic resonance imaging. Magn. Res. Quart. 7:1-30. [26] Basser, P.J., and D.K. Jones. 2002. Diffusion-Tensor MRI. NMR Biomed. 15:456 -467. [27] Napadow, V.J., V. Q. Chen, V. Mai, P.T.C. So, and R. J. Gilbert. 2001. Quantitative Analysis of Three-Dimensional-Resolved Fiber Architecture in Heterogeneous Skeletal Muscle Tissue Using NMR and Optical Imaging Methods. Bioph. J. 80:2968-2975. [28] De Visser, S.K., J. C. Bowden, E. Wentrup-Byrne, L. Rintoul, T. Bostrom, J. M. Pope D and K. I. Momot. 2008. Anisotropy of collagen fibre alignment in bovine cartilage: comparison of polarised light microscopy and spatially resolved diffusion-tensor measurements. Ost. and Cart.16: 689-697. [29] Pierce, D.M., Trobin W., Raya J.G., Trattnig S., Bishof H., Glaser C. and G.A. Holzapfeli. 2010. DT-MRI based computation of collagen fiber deformation in human articular cartilage: a feasibility study. Ann. Biom. Eng. 38:2447–2463. [30] Meder, R., S. K. de Visser, J. C. Bowden, T. Bostrom, and J. M. Pope. 2006. Diffusion tensor imaging of articular cartilage as a measure of tissue microstructure Ost. and Cart. 14, 875-881. [31] Othman, S.F., Williams, J.M., Sumner, D.R. and R.L. Magin. 2004. MRI heterogeneity of articular cartilage in strong magnetic field: dependence on proteoglycan content. Magn. Res. Eng. 23B(1):33-43. [32] Venn, M. F. 1978. Variation of chemical composition with age in human femoral head cartilage. Ann. Rheum. Dis. 37:168-174

SARS-CoV-2 Variants Identification: Overview of Molecular Existing Methods

Since the beginning of COVID-19 pandemic the Real Time sharing of genome sequences of circulating virus supported the diagnostics and surveillance of SARS-CoV-2 and its transmission dynamics. SARS-CoV-2 straightaway showed its tendency to mutate and adapt to the host, culminating in the emergence of variants; so it immediately became of crucial importance to be able to detect them quickly but also to be able to monitor in depth the changes on the whole genome to early identify the new possibly emerging variants. In this scenario, this manuscript aims to provide an overview of the existing methods for the identification of SARS-CoV-2 variants (from rapid method based on identification of one or more specific mutations to Whole Genome sequencing approach-WGS), taking into account limitations, advantages and applications of them in the field of diagnosis and surveillance of SARS-CoV-2

Compartmentalized Replication of SARS-Cov-2 in Upper vs. Lower Respiratory Tract Assessed by Whole Genome Quasispecies Analysis

We report whole-genome and intra-host variability of SARS-Cov-2 assessed by next generation sequencing (NGS) in upper (URT) and lower respiratory tract (LRT) from COVID-19 patients. The aim was to identify possible tissue-specific patterns and signatures of variant selection for each respiratory compartment. Six patients, admitted to the Intensive Care Unit, were included in the study. Thirteen URT and LRT were analyzed by NGS amplicon-based approach on Ion Torrent Platform. Bioinformatic analysis was performed using both realized in-house and supplied by ThermoFisher programs. Phylogenesis showed clade V clustering of the first patients diagnosed in Italy, and clade G for later strains. The presence of quasispecies was observed, with variants uniformly distributed along the genome and frequency of minority variants spanning from 1% to ~30%. For each patient, the patterns of variants in URT and LRT were profoundly different, indicating compartmentalized virus replication. No clear variant signature and no significant difference in nucleotide diversity between LRT and URT were observed. SARS-CoV-2 presents genetic heterogeneity and quasispecies compartmentalization in URT and LRT. Intra-patient diversity was low. The pattern of minority variants was highly heterogeneous and no specific district signature could be identified, nevertheless, analysis of samples, longitudinally collected in patients, supported quasispecies evolution

Molecular Genotyping of Circulating Enterovirus in the Lazio Region from 2012 to 2023

Enteroviruses (EVs) are ubiquitous viruses that circulate worldwide, causing sporadic or epidemic infections, typically during the summer and fall. They cause a broad spectrum of illnesses, ranging from an unspecified febrile clinical presentation to a severe illness. EVs are recognized to be the most frequent etiological agents of aseptic meningitis in children. However, as the infection is usually mild and self-limiting, it remains underestimated, and the epidemiology of EVs is poorly understood. To date, no vaccine or effective therapy for all types of enteroviruses is available, and EVs constitute a public health concern. Here, we investigated the molecular epidemiology of EV strains circulating in the Lazio region over a 10-year time span (2012–2023) by using a sequence-typing approach and phylogenetic analysis. The epidemiological trend of EV infection has undergone changes during the SARS-CoV-2 pandemic (2020–2021), which resulted in a modification in terms of the number of diagnosed cases and seasonality. From 2022, the circulation of EVs showed a behavior typical of the pre-pandemic period, although changes in predominantly circulating strains have been noted. Both epidemic and sporadic circulation events have been characterized in the Lazio region. Further analyses are needed to better characterize any strain with higher potential pathogenic power and to identify possible recombinant strains

Detection of SARS-CoV-2 Variants via Different Diagnostics Assays Based on Single-Nucleotide Polymorphism Analysis

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is characterized by fast evolution with the appearance of several variants. Next-Generation Sequencing (NGS) technology is considered the gold standard for monitoring known and new SARS-CoV-2 variants. However, the complexity of this technology renders this approach impracticable in laboratories located in areas with limited resources. We analyzed the capability of the ThermoFisher TaqPath COVID-19 RT-PCR (TaqPath) and the Seegene Novaplex SARS-CoV-2 Variant assay (Novaplex) to detect Omicron variants; the Allplex VariantII (Allplex) was also evaluated for Delta variants. Sanger sequencing (SaS) was the reference method. The results obtained with n = 355 nasopharyngeal samples were: negative with TaqPath, although positive with other qualitative molecular assays (n = 35); undetermined (n = 40) with both the assays; negative for the ∆69/70 mutation and confirmed as the Delta variant via SaS (n = 100); positive for ∆69/70 and confirmed as Omicron BA.1 via SaS (n = 80); negative for ∆69/70 and typed as Omicron BA.2 via SaS (n = 80). Novaplex typed 27.5% of samples as undetermined with TaqPath, 11.4% of samples as negative with TaqPath, and confirmed 100% of samples were Omicron subtypes. In total, 99/100 samples were confirmed as the Delta variant with Allplex with a positive per cent agreement (PPA) of 98% compared to SaS. As undermined samples with Novaplex showed RdRp median Ct values (Ct = 35.4) statistically higher than those of typed samples (median Ct value = 22.0; p < 0.0001, Mann–Whitney test), the inability to establish SARS-CoV-2 variants was probably linked to the low viral load. No amplification was obtained with SaS among all 35 negative TaqPath samples. Overall, 20% of samples which were typed as negative or undetermined with TaqPath, and among them, twelve were not typed even by SaS, but they were instead correctly identified with Novaplex. Although full-genome sequencing remains the elected method to characterize new strains, our data show the high ability of a SNP-based assay to identify VOCs, also resolving samples typed as undetermined with TaqPath

The Spike Mutants Website: A Worldwide Used Resource against SARS-CoV-2

A large number of SARS-CoV-2 mutations in a short period of time has driven scientific research related to vaccines, new drugs, and antibodies to combat the new variants of the virus. Herein, we present a web portal containing the structural information, the tridimensional coordinates, and the molecular dynamics trajectories of the SARS-CoV-2 spike protein and its main variants. The Spike Mutants website can serve as a rapid online tool for investigating the impact of novel mutations on virus fitness. Taking into account the high variability of SARS-CoV-2, this application can help the scientific community when prioritizing molecules for experimental assays, thus, accelerating the identification of promising drug candidates for COVID-19 treatment. Below we describe the main features of the platform and illustrate the possible applications for speeding up the drug discovery process and hypothesize new effective strategies to overcome the recurrent mutations in SARS-CoV-2 genome

16S rRNA gene sequencing of rectal swab in patients affected by COVID-19.

COronaVIrus Disease-2019 (COVID-19) is a pandemic respiratory infection caused by a new betacoronavirus, the Severe Acute Respiratory Syndrome-CoronaVirus-2 (SARS-CoV-2). Few data are reported on the gut microbiota in COVID-19 patients. 16S rRNA gene sequencing was performed to reveal an altered composition of the gut microbiota in patients with COVID-19 pneumonia admitted in intensive care unit (ICU) (i-COVID19), or in infectious disease wards (w-COVID19) as compared to controls (CTRL). i-COVID19 patients showed a decrease of Chao1 index as compared to CTRL and w-COVID19 patients indicating that patients in ICU displayed a lower microbial richness while no change was observed as for Shannon Index. At the phylum level, an increase of Proteobacteria was detected in w-COVID19 patients as compared to CTRL. A decrease of Fusobacteria and Spirochetes has been found, with the latter decreased in i-COVID19 patients as compared to CTRL. Significant changes in gut microbial communities in patients with COVID-19 pneumonia with different disease severity compared to CTRL have been identified. Our preliminary data may provide valuable information and promising biomarkers for the diagnosis of the disease and, when validated in larger cohort, it could facilitate the stratification of patients based on the microbial signature

Genomic and Epidemiologic Surveillance of SARS-CoV-2 in the Pandemic Period: Sequencing Network of the Lazio Region, Italy

Since the beginning of the COVID-19 pandemic, large-scale genomic sequencing has immediately pointed out that SARS-CoV-2 has rapidly mutated during the course of the pandemic, resulting in the emergence of variants with a public health impact. In this context, strictly monitoring the circulating strains via NGS has proven to be crucial for the early identification of new emerging variants and the study of the genomic evolution and transmission of SARS-CoV-2. Following national and international guidelines, the Lazio region has created a sequencing laboratory network (WGSnet-Lazio) that works in synergy with the reference center for epidemiological surveillance (SERESMI) to monitor the circulation of SARS-CoV-2. Sequencing was carried out with the aims of characterizing outbreak transmission dynamics, performing the genomic analysis of viruses infecting specific categories of patients (i.e., immune-depressed, travelers, and people with severe symptoms) and randomly monitoring variant circulation. Here we report data emerging from sequencing activities carried out by WGSnet-Lazio (from February 2020 to October 2022) linked with epidemiological data to correlate the circulation of variants with the clinical and demographic characteristics of patients. The model of the sequencing network developed in the Lazio region proved to be a useful tool for SARS-CoV-2 surveillance and to support public health measures for epidemic containment