Valerio Caputo
@uniroma2.it
Department of Biomedicine and Prevention
Tor Vergata University of Roma
RESEARCH INTERESTS
Medical Genetics, Human Genetics, Molecular Genetics, Epigenomics, Molecular Biology
Scopus Publications
Scopus Publications
Valerio Caputo, Giovanni Tarantino, Silvano Junior Santini, Giovanna Fracassi, and Clara Balsano
MDPI AG
Metabolic dysfunction-associated steatotic fatty liver disease (MASLD), a novel definition for NAFLD, represents one of the most common causes of liver disease, and its incidence is increasing worldwide. It is characterized by a complex etiopathogenesis in which mitochondrial dysfunction exerts a pivotal role together with alteration of lipid metabolism, inflammation, and oxidative stress. Nutrients and bioactive compounds can influence such mechanisms so that changes in diet and lifestyle are regarded as important treatment strategies. Notably, natural compounds can exert their influence through changes of the epigenetic landscape, overall resulting in rewiring of molecular networks involved in cell and tissue homeostasis. Considering such information, the present review aims at providing evidence of epigenetic modifications occurring at mitochondria in response to natural and bioactive compounds in the context of liver (dys)function. For this purpose, recent studies reporting effects of compounds on mitochondria in the context of NAFLD/MASLD, as well as research showing alteration of DNA methylation and non-coding RNAs-related circuits occurring at liver mitochondria, will be illustrated. Overall, the present review will highlight the importance of understanding the bioactive compounds-dependent epigenetic modulation of mitochondria for improving the knowledge of MASLD and identifying biomarkers to be employed for effective preventative strategies or treatment protocols.
Domenica Megalizzi, Giulia Trastulli, Valerio Caputo, Luca Colantoni, Carlo Caltagirone, Claudia Strafella, Raffaella Cascella, and Emiliano Giardina
Wiley
AbstractThe alteration of epigenetic modifications, including DNA methylation, can contribute to the etiopathogenesis and progression of many diseases. Among them, facioscapulohumeral dystrophy (FSHD) is a muscular disorder characterized by the loss of repressive epigenetic features affecting the D4Z4 locus (4q35). As a consequence, these alterations are responsible for DNA hypomethylation and a transcriptional‐active chromatin conformation change that, in turn, lead to the aberrant expression of DUX4 in muscle cells. In the present study, methylation levels of 29 CpG sites of the DR1 region (within each repeat unit of the D4Z4 macrosatellite) were assessed on 335 subjects by employing primers designed for enhancing the performance of the assay. First, the DR1 original primers were optimized by adding M13 oligonucleotide tails. Moreover, the DR1 reverse primer was replaced with a degenerate one. As a result, the protocol optimization allowed a better sequencing resolution and a more accurate evaluation of DR1 methylation levels. Moreover, the assessment of the repeatability of measurements proved the reliability and robustness of the assay. The optimized protocol emerges as an excellent method to detect methylation levels compatible with FSHD.
Claudia Strafella, Valerio Caputo, Sara Bortolani, Eleonora Torchia, Domenica Megalizzi, Giulia Trastulli, Mauro Monforte, Luca Colantoni, Carlo Caltagirone, Enzo Ricci,et al.
Frontiers Media SA
Introduction: Despite the progress made in the study of Facioscapulohumeral Dystrophy (FSHD), the wide heterogeneity of disease complicates its diagnosis and the genotype-phenotype correlation among patients and within families. In this context, the present work employed Whole Exome Sequencing (WES) to investigate known and unknown genetic contributors that may be involved in FSHD and may represent potential disease modifiers, even in presence of a D4Z4 Reduced Allele (DRA).Methods: A cohort of 126 patients with clinical signs of FSHD were included in the study, which were characterized by D4Z4 sizing, methylation analysis and WES. Specific protocols were employed for D4Z4 sizing and methylation analysis, whereas the Illumina® Next-Seq 550 system was utilized for WES. The study included both patients with a DRA compatible with FSHD diagnosis and patients with longer D4Z4 alleles. In case of patients harboring relevant variants from WES, the molecular analysis was extended to the family members.Results: The WES data analysis highlighted 20 relevant variants, among which 14 were located in known genetic modifiers (SMCHD1, DNMT3B and LRIF1) and 6 in candidate genes (CTCF, DNMT1, DNMT3A, EZH2 and SUV39H1). Most of them were found together with a permissive short (4–7 RU) or borderline/long DRA (8–20 RU), supporting the possibility that different genes can contribute to disease heterogeneity in presence of a FSHD permissive background. The segregation and methylation analysis among family members, together with clinical findings, provided a more comprehensive picture of patients.Discussion: Our results support FSHD pathomechanism being complex with a multigenic contribution by several known (SMCHD1, DNMT3B, LRIF1) and possibly other candidate genes (CTCF, DNMT1, DNMT3A, EZH2, SUV39H1) to disease penetrance and expressivity. Our results further emphasize the importance of extending the analysis of molecular findings within the proband’s family, with the purpose of providing a broader framework for understanding single cases and allowing finer genotype-phenotype correlations in FSHD-affected families.
Valerio Caputo, Domenica Megalizzi, Carlo Fabrizio, Andrea Termine, Luca Colantoni, Cristina Bax, Juliette Gimenez, Mauro Monforte, Giorgio Tasca, Enzo Ricci,et al.
MDPI AG
The study describes a protocol for methylation analysis integrated with Machine Learning (ML) algorithms developed to classify Facio-Scapulo-Humeral Dystrophy (FSHD) subjects. The DNA methylation levels of two D4Z4 regions (DR1 and DUX4-PAS) were assessed by an in-house protocol based on bisulfite sequencing and capillary electrophoresis, followed by statistical and ML analyses. The study involved two independent cohorts, namely a training group of 133 patients with clinical signs of FSHD and 150 healthy controls (CTRL) and a testing set of 27 FSHD patients and 25 CTRL. As expected, FSHD patients showed significantly reduced methylation levels compared to CTRL. We utilized single CpG sites to develop a ML pipeline able to discriminate FSHD subjects. The model identified four CpGs sites as the most relevant for the discrimination of FSHD subjects and showed high metrics values (accuracy: 0.94, sensitivity: 0.93, specificity: 0.96). Two additional models were developed to differentiate patients with lower D4Z4 size and patients who might carry pathogenic variants in FSHD genes, respectively. Overall, the present model enables an accurate classification of FSHD patients, providing additional evidence for DNA methylation as a powerful disease biomarker that could be employed for prioritizing subjects to be tested for FSHD.
Carlo Fabrizio, Andrea Termine, Valerio Caputo, Domenica Megalizzi, Giulia Calvino, Giulia Trastulli, Arcangela Ingrascì, Simona Ferrante, Cristina Peconi, Angelo Rossini,et al.
MDPI AG
The clinical spectrum of SARS-CoV-2 infection ranges from asymptomatic status to mild infections, to severe disease and death. In this context, the identification of specific susceptibility factors is crucial to detect people at the higher risk of severe disease and improve the outcome of COVID-19 treatment. Several studies identified genetic variants conferring higher risk of SARS-CoV-2 infection and COVID-19 severity. The present study explored their genetic distribution among different populations (AFR, EAS, EUR and SAS). As a result, the obtained data support the existence of a genetic basis for the observed variability among populations, in terms of SARS-CoV-2 infection and disease outcomes. The comparison of ORs distribution for genetic risk of infection as well as for disease outcome shows that each population presents its own characteristics. These data suggest that each country could benefit from a population-wide risk assessment, aimed to personalize the national vaccine programs and the preventative measures as well as the allocation of resources and the access to proper therapeutic interventions. Moreover, the host genetics should be further investigated in order to realize personalized medicine protocols tailored to improve the management of patients suffering from COVID-19.
Valerio Caputo, Domenica Megalizzi, Carlo Fabrizio, Andrea Termine, Luca Colantoni, Carlo Caltagirone, Emiliano Giardina, Raffaella Cascella, and Claudia Strafella
MDPI AG
Despite the knowledge of the main mechanisms involved in facioscapulohumeral muscular dystrophy (FSHD), the high heterogeneity and variable penetrance of the disease complicate the diagnosis, characterization and genotype–phenotype correlation of patients and families, raising the need for further research and data. Thus, the present review provides an update of the main molecular aspects underlying the complex architecture of FSHD, including the genetic factors (related to D4Z4 repeated units and FSHD-associated genes), epigenetic elements (D4Z4 methylation status, non-coding RNAs and high-order chromatin interactions) and gene expression profiles (FSHD transcriptome signatures both at bulk tissue and single-cell level). In addition, the review will also describe the methods currently available for investigating the above-mentioned features and how the resulting data may be combined with artificial-intelligence-based pipelines, with the purpose of developing a multifunctional tool tailored to enhancing the knowledge of disease pathophysiology and progression and fostering the research for novel treatment strategies, as well as clinically useful biomarkers. In conclusion, the present review highlights how FSHD should be regarded as a disease characterized by a molecular spectrum of genetic and epigenetic factors, whose alteration plays a differential role in DUX4 repression and, subsequently, contributes to determining the FSHD phenotype.
Shila Barati, Carlo Fabrizio, Claudia Strafella, Raffaella Cascella, Valerio Caputo, Domenica Megalizzi, Cristina Peconi, Julia Mela, Luca Colantoni, Carlo Caltagirone,et al.
MDPI AG
In the present review, the main features involved in the susceptibility and progression of neurodegenerative disorders (NDDs) have been discussed, with the purpose of highlighting their potential application for promoting the management and treatment of patients with NDDs. In particular, the impact of genetic and epigenetic factors, nutrients, and lifestyle will be presented, with particular emphasis on Alzheimer’s disease (AD) and Parkinson’s disease (PD). Metabolism, dietary habits, physical exercise and microbiota are part of a complex network that is crucial for brain function and preservation. This complex equilibrium can be disrupted by genetic, epigenetic, and environmental factors causing perturbations in central nervous system homeostasis, contributing thereby to neuroinflammation and neurodegeneration. Diet and physical activity can directly act on epigenetic modifications, which, in turn, alter the expression of specific genes involved in NDDs onset and progression. On this subject, the introduction of nutrigenomics shed light on the main molecular players involved in the modulation of health and disease status. In particular, the review presents data concerning the impact of ADH1B, CYP1A2, and MTHFR on the susceptibility and progression of NDDs (especially AD and PD) and how they may be exploited for developing precision medicine strategies for the disease treatment and management.
Carlo Fabrizio, Andrea Termine, Valerio Caputo, Domenica Megalizzi, Stefania Zampatti, Benedetto Falsini, Andrea Cusumano, Chiara Maria Eandi, Federico Ricci, Emiliano Giardina,et al.
MDPI AG
Given the multifactorial features characterizing age-related macular degeneration (AMD), the availability of a tool able to provide the individual risk profile is extremely helpful for personalizing the follow-up and treatment protocols of patients. To this purpose, we developed an open-source computational tool named WARE (Wet AMD Risk Evaluation), able to assess the individual risk profile for wet AMD based on genetic and non-genetic factors. In particular, the tool uses genetic risk measures normalized for their relative frequencies in the general population and disease prevalence. WARE is characterized by a user-friendly web page interface that is intended to assist clinicians in reporting risk assessment upon patient evaluation. When using the tool, plots of population risk distribution highlight a “low-risk zone” and a “high-risk zone” into which subjects can fall depending on their risk-assessment result. WARE represents a reliable population-specific computational system for wet AMD risk evaluation that can be exploited to promote preventive actions and personalized medicine approach for affected patients or at-risk individuals. This tool can be suitable to compute the disease risk adjusted to different populations considering their specific genetic factors and related frequencies, non-genetic factors, and the disease prevalence.
Andrea Termine, Carlo Fabrizio, Claudia Strafella, Valerio Caputo, Laura Petrosini, Carlo Caltagirone, Raffaella Cascella, and Emiliano Giardina
MDPI AG
Precision medicine emphasizes fine-grained diagnostics, taking individual variability into account to enhance treatment effectiveness. Parkinson’s disease (PD) heterogeneity among individuals proves the existence of disease subtypes, so subgrouping patients is vital for better understanding disease mechanisms and designing precise treatment. The purpose of this study was to identify PD subtypes using RNA-Seq data in a combined pipeline including unsupervised machine learning, bioinformatics, and network analysis. Two hundred and ten post mortem brain RNA-Seq samples from PD (n = 115) and normal controls (NCs, n = 95) were obtained with systematic data retrieval following PRISMA statements and a fully data-driven clustering pipeline was performed to identify PD subtypes. Bioinformatics and network analyses were performed to characterize the disease mechanisms of the identified PD subtypes and to identify target genes for drug repurposing. Two PD clusters were identified and 42 DEGs were found (p adjusted ≤ 0.01). PD clusters had significantly different gene network structures (p < 0.0001) and phenotype-specific disease mechanisms, highlighting the differential involvement of the Wnt/β-catenin pathway regulating adult neurogenesis. NEUROD1 was identified as a key regulator of gene networks and ISX9 and PD98059 were identified as NEUROD1-interacting compounds with disease-modifying potential, reducing the effects of dopaminergic neurodegeneration. This hybrid data analysis approach could enable precision medicine applications by providing insights for the identification and characterization of pathological subtypes. This workflow has proven useful on PD brain RNA-Seq, but its application to other neurodegenerative diseases is encouraged.
Claudia Strafella, Valerio Caputo, Andrea Termine, Carlo Fabrizio, Giulia Calvino, Domenica Megalizzi, Paola Ruffo, Elisa Toppi, Nerisa Banaj, Andrea Bassi,et al.
Frontiers Media SA
Amnestic mild cognitive impairment (aMCI) and sporadic Alzheimer’s disease (AD) are multifactorial conditions resulting from a complex crosstalk among multiple molecular and biological processes. The present study investigates the association of variants localized in genes and miRNAs with aMCI and AD, which may represent susceptibility, prognostic biomarkers or multi-target treatment options for such conditions. We included 371 patients (217 aMCI and 154 AD) and 503 healthy controls, which were genotyped for a panel of 120 single nucleotide polymorphisms (SNPs) and, subsequently, analyzed by statistical, bioinformatics and machine-learning approaches. As a result, 21 SNPs were associated with aMCI and 13 SNPs with sporadic AD. Interestingly, a set of variants shared between aMCI and AD displayed slightly higher Odd Ratios in AD with respect to aMCI, highlighting a specific risk trajectory linking aMCI to AD. Some of the associated genes and miRNAs were shown to interact within the signaling pathways of APP (Amyloid Precursor Protein), ACE2 (Angiotensin Converting Enzyme 2), miR-155 and PPARG (Peroxisome Proliferator Activated Receptor Gamma), which are known to contribute to neuroinflammation and neurodegeneration. Overall, results of this study increase insights concerning the genetic factors contributing to the neuroinflammatory and neurodegenerative mechanisms underlying aMCI and sporadic AD. They have to be exploited to develop personalized approaches based on the individual genetic make-up and multi-target treatments.
Valerio Caputo, Giulia Calvino, Claudia Strafella, Andrea Termine, Carlo Fabrizio, Giulia Trastulli, Arcangela Ingrascì, Cristina Peconi, Silvia Bardini, Angelo Rossini,et al.
MDPI AG
The emergence of the Omicron SARS-CoV-2 variant caused public health concerns worldwide, raising the need for the improvement of rapid monitoring strategies. The present manuscript aimed at providing evidence of the utility of a diagnostic kit for the routine testing of SARS-CoV-2 infection as a cost-effective method for tracking the Omicron variant in Italy. The study was conducted on patients’ naso-oropharyngeal-swab-derived RNA samples. These samples were subjected to RT-PCR using the TaqPath COVID-19 RT PCR CE IVD kit. Nonparametric testing and polynomial models fitting were used to compare the spreading of Alpha, Delta and Omicron variants. The samples of interest were correctly amplified and displayed the presence of S gene-target failure, suggesting that these patients carry the Omicron variant. The trend of diffusion was found to be significantly different and more rapid compared with that of the Alpha and Delta variants in our cohorts. Overall, these results highlight that the S gene target failure was a very useful tool for the immediate and inexpensive tracking of Omicron variant in the three weeks from the first detection. Thus, our approach could be used as a first-line screening to reduce the time and costs of monitoring strategies, facilitating the management of preventive and counteracting measures against COVID-19.
Paola Ruffo, Claudia Strafella, Raffaella Cascella, Valerio Caputo, Francesca Luisa Conforti, Sebastiano Andò, and Emiliano Giardina
Frontiers Media SA
Parallel and massive sequencing of total RNA samples derived from different samples are possible thanks to the use of NGS (Next Generation Sequencing) technologies. This allowed characterizing the transcriptomic profile of both cell and tissue populations, increasing the knowledge of the molecular pathological processes of complex diseases, such as neurodegenerative diseases (NDs). Among the NDs, Amyotrophic Lateral Sclerosis (ALS) is caused by the progressive loss of motor neurons (MNs), and, to date, the diagnosis is often made by exclusion because there is no specific symptomatologic picture. For this reason, it is important to search for biomarkers that are clinically useful for carrying out a fast and accurate diagnosis of ALS. Thanks to various studies, it has been possible to propose several molecular mechanisms associated with the disease, some of which include the action of non-coding RNA, including circRNAs, miRNAs, and lncRNAs which will be discussed in the present review. The evidence analyzed in this review highlights the importance of conducting studies to better characterize the different ncRNAs in the disease to use them as possible diagnostic, prognostic, and/or predictive biomarkers of ALS and other NDs.
Valerio Caputo, Claudia Strafella, Andrea Termine, Carlo Fabrizio, Paola Ruffo, Andrea Cusumano, Emiliano Giardina, Federico Ricci, and Raffaella Cascella
SAGE Publications
Epigenetics is characterized by molecular modifications able to shape gene expression profiles in response to inner and external stimuli. Therefore, epigenetic elements are able to provide intriguing and useful information for the comprehension and management of different human conditions, including aging process, and diseases. On this subject, Age-related Macular Degeneration (AMD) represents one of the most frequent age-related disorders, dramatically affecting the quality of life of older adults worldwide. The etiopathogenesis is characterized by an interplay among multiple genetic and non-genetic factors, which have been extensively studied. Nevertheless, a deeper dissection of molecular machinery associated with risk, onset, progression and effectiveness of therapies is still missing. In this regard, epigenetic signals may be further explored to disentangle disease etiopathogenesis, the possible therapeutic avenues and the differential response to AMD treatment. This review will discuss the epigenomic signatures mostly investigated in AMD, which could be applied to improve the knowledge of disease mechanisms and to set-up novel or modified treatment options.
Valerio Caputo, Claudia Strafella, Terenzio Cosio, Caterina Lanna, Elena Campione, Giuseppe Novelli, Emiliano Giardina, and Raffaella Cascella
MDPI AG
Pharmacogenomic studies allowed the reasons behind the different responses to treatments to be understood. Its clinical utility, in fact, is demonstrated by the reduction in adverse drug reaction incidence and the improvement of drug efficacy. Pharmacogenomics is an important tool that is able to improve the drug therapy of different disorders. In particular, this review will highlight the current pharmacogenomics knowledge about biologics and small-molecule treatments for psoriasis. To date, studies performed on genes involved in the metabolism of biological drugs (tumor necrosis factor inhibitors and cytokines inhibitors) and small molecules (apremilast, dimethyl fumarate, and tofacitinib) have provided conflicting results, and further investigations are necessary in order to establish a set of biomarkers to be introduced into clinical practice.
Valerio Caputo, Andrea Termine, Carlo Fabrizio, Giulia Calvino, Laura Luzzi, Claudia Fusco, Arcangela Ingrascì, Cristina Peconi, Rebecca D'Alessio, Serena Mihali,et al.
MDPI AG
The COVID-19 pandemic caused by SARS-CoV-2 represents a public health emergency, which became even more challenging since the detection of highly transmissible variants and strategies against COVID-19 were indistinctly established. We characterized the temporal viral load kinetics in individuals infected by original and variant strains. Naso-oropharyngeal swabs from 33,000 individuals (admitted to the IRCCS Santa Lucia Foundation Drive-in, healthcare professionals and hospitalized patients who underwent routinary screening) from November 2020 to June 2021 were analyzed. Of them, 1735 subjects were selected and grouped according to the viral strain. Diagnostic analyses were performed by CE-IVD RT-PCR-based kits. The subgenomic-RNA component was assessed in 36 subjects using digital PCR. Infection duration, viral load decay speed, effects of age and sex were assessed and compared by extensive statistical analyses. Overall, infection duration and viral load differed between the groups (p < 0.05). Male sex was more present among both original and variant carriers affected with high viral load and showing fast decay speed, whereas original strain carriers with slow decay speed resulted in older (p < 0.05). Subgenomic-RNA was detected in the positive samples, including those with low viral load. This study provides a picture of the viral load kinetics, identifying individuals with similar patterns and showing differential effects of age and sex, thus providing potentially useful information for personalized management of infected subjects.
Stefania Zampatti, Carlo Fabrizio, Michele Ragazzo, Giulia Campoli, Valerio Caputo, Claudia Strafella, Clelia Pellicano, Raffaella Cascella, Gianfranco Spalletta, Laura Petrosini,et al.
MDPI AG
The management of neuropsychiatric disorders involves different pharmacological treatments. In order to perform efficacious drug treatments, the metabolism of CYP genes can help to foresee potential drug–drug interactions. The NeuroPGx software is an open-source web-based tool for genotype/diplotype/phenotype interpretation for neuropharmacogenomic purposes. The software provides information about: (i) the genotypes of evaluated SNPs (single nucleotide polymorphisms); (ii) the main diplotypes in CYP genes and corresponding metabolization phenotypes; (iii) the list of neuropsychiatric drugs with recommended dosage adjustment (according to CPIC and DPWG guidelines); (iv) the list of possible (rare) diplotypes and corresponding metabolization phenotypes. The combined application of NeuroPGx software to the OpenArray technology results in an easy, quick, and highly automated device ready to be used in routine clinical practice.
Anthea Di Rita, Daniela F. Angelini, Teresa Maiorino, Valerio Caputo, Raffaella Cascella, Mukesh Kumar, Matteo Tiberti, Matteo Lambrughi, Nicole Wesch, Frank Löhr,et al.
Springer Science and Business Media LLC
The role of mitophagy, a process that allows the removal of damaged mitochondria from cells, remains unknown in multiple sclerosis (MS), a disease that is found associated with dysfunctional mitochondria. Here we have qualitatively and quantitatively studied the main players in PINK1-mediated mitophagy in peripheral blood mononuclear cells (PBMCs) of patients with relapsing-remitting MS. We found the variant c.491G>A (rs550510, p.G140E) of NDP52, one of the major mitophagy receptor genes, associated with a MS cohort. Through the characterization of this variant, we discovered that the residue 140 of human NDP52 is a crucial modulator of NDP52/LC3C binding, promoting the formation of autophagosomes in order to drive efficient mitophagy. In addition, we found that in the PBMC population, NDP52 is mainly expressed in B cells and by ensuring efficient mitophagy, it is able to limit the production of the proinflammatory cytokine TNF-α following cell stimulation. In sum, our results contribute to a better understanding of the role of NDP52 in mitophagy and underline, for the first time, a possible role of NDP52 in MS.
Valerio Caputo, Cristina Bax, Luca Colantoni, Cristina Peconi, Andrea Termine, Carlo Fabrizio, Giulia Calvino, Laura Luzzi, Giorgia Gaia Panunzi, Claudia Fusco,et al.
Elsevier BV
Objectives
The present study compared the performance of Lumipulse G Sars-CoV-2 Ag kit with TaqPath COVID-19 RT-PCR CE IVD kit.
Methods
The study was conducted on 4266 naso-oropharyngeal swabs. Samples were subjected to antigen RT-PCR tests for detection of Sars-CoV-2 and related variants. Statistical analyses were conducted in R software.
Results
We found 503 positives (including 138 H69-V70 deletion carriers) and 3763 negatives by RT-PCR, whereas 538 positives and 3728 negatives were obtained by antigen testing. We achieved empirical and binormal AU-ROCs of 0.920 and 0.990, accuracy of 0.960, sensitivity of 0.866, specificity of 0.973, positive and negative predictive values of 0.810 and 0.980. We obtained a positive correlation between viral loads and antigen levels (R2 = 0.81), founding a complete concordance for high viral loads (log10copies/mL>5.4). Antigen levels >222 pg/mL were found to be reliable in assigning positive samples (p < 0.01). Concerning variant carriers, antigen test detected them with the same accuracy of other positive samples.
Conclusions
Molecular and antigen tests should be evaluated regarding the prevalence of the area. In case of low prevalence, antigen testing can be employed as a first-line screening for the timely identification of affected individuals with high viral load, also if carriers of Sars-CoV-2 variants.
C. Strafella, Valerio Caputo, Gisella Guerrera, Andrea Termine, Carlo Fabrizio, R. Cascella, M. Picozza, C. Caltagirone, A. Rossini, M. Balice,et al.
During the COVID19 pandemic, a range of vaccines displayed high efficacy in preventing disease, severe outcomes of infection, and mortality. However, the immunological correlates of protection, the duration of immune response, the transmission risk over time from vaccinated individuals are currently under active investigation. In this brief report, we describe the case of a vaccinated Healthcare Professional infected with a variant of Sars-CoV-2, who has been extensively investigated in order to draw a complete trajectory of infection. The patient has been monitored for the whole length of infection, assessing the temporal viral load decay, the quantification of viral RNA and subgenomic mRNA, antibodies (anti Sars-CoV-2, IgA, IgG, IgM) and cell-mediated (cytokine, B- and T-cell profiles) responses. Overall, this brief report highlights the efficacy of vaccine in preventing COVID19 disease, accelerating the recovery from infection, reducing the transmission risk, although the use of precautionary measures against Sars-CoV-2 spreading still remain critical.
Claudia Strafella, Valerio Caputo, Andrea Termine, Francesca Assogna, Clelia Pellicano, Francesco E. Pontieri, Lucia Macchiusi, Giulietta Minozzi, Stefano Gambardella, Diego Centonze,et al.
Frontiers Media SA
The present study investigated the association of SNPs involved in the regulation of immune response, cellular degenerative and neuroinflammatory pathways with the susceptibility and progression of idiopathic Parkinson’s Disease (PD). In particular, 342 PD patients were subjected to a genotyping analysis of a panel of 120 SNPs by Open Array Technology. As control group, 503 samples representative of the European general population were utilized. The genetic analysis identified 26 SNPs associated with PD susceptibility. Of them, 12 SNPs were described as significant expression Quantitative Loci (eQTL) variants in different brain regions associated with motor and non-motor PD phenomenology. Moreover, the study highlighted 11 novel susceptibility genes for PD, which may alter multiple signaling pathways critically involved in peripheral immune response, neuroinflammation, neurodegeneration and dopaminergic neurons wiring. The study of miRNA-target genes highlighted a possible role of miR-499a, miR-196a2, and miR-29a in the modulation of multiple neuroinflammatory and neurodegenerative mechanisms underlying PD physiopathology. The study described a network of interconnected genes (APOE, CLU, IL6, IL7R, IL12B, INPP5D, MAPK1, MEF2C, MIF, and TNFSF14), which may act as upstream regulators in the modulation of biological pathways relevant to PD. Intriguingly, IL6 stands out as a master gene regulator since it may indirectly regulate the network of interconnected genes. The study highlighted different genes and miRNAs interactions potentially involved in PD physiopathology, which are worth to be further explored to improve the knowledge of disease and the research of novel treatments strategies.
Stefania Zampatti, Michele Ragazzo, Cristina Peconi, Serena Luciano, Stefano Gambardella, Valerio Caputo, Claudia Strafella, Raffaella Cascella, Carlo Caltagirone, and Emiliano Giardina
MDPI AG
Dementing disorders are a complex group of neurodegenerative diseases characterised by different, but often overlapping, pathological pathways. Genetics have been largely associated with the development or the risk to develop dementing diseases. Recent advances in molecular technologies permit analyzing of several genes in a small time, but the interpretation analysis is complicated by several factors: the clinical complexity of neurodegenerative disorders, the frequency of co-morbidities, and the high phenotypic heterogeneity of genetic diseases. Genetic counselling supports the diagnostic path, providing an accurate familial and phenotypic characterisation of patients. In this review, we summarise neurodegenerative dementing disorders and their genetic determinants. Genetic variants and associated phenotypes will be divided into high and low impact, in order to reflect the pathologic continuum between multifactorial and mendelian genetic factors. Moreover, we report a molecular characterisation of genes associated with neurodegenerative disorders with cognitive impairment. In particular, the high frequency of rare coding genetic variants in dementing genes strongly supports the role of geneticists in both, clinical phenotype characterisation and interpretation of genotypic data. The smart application of exome analysis to dementia patients, with a pre-analytical selection on familial, clinical, and instrumental features, improves the diagnostic yield of genetic test, reduces time for diagnosis, and allows a rapid and personalised management of disease.
Claudia Strafella, Valerio Caputo, Andrea Termine, Carlo Fabrizio, Paola Ruffo, Saverio Potenza, Andrea Cusumano, Federico Ricci, Carlo Caltagirone, Emiliano Giardina,et al.
Frontiers Media SA
Age-related macular degeneration (AMD) showed several processes and risk factors in common with neurodegenerative disorders (NDDs). The present work explored the existence of genetic determinants associated with AMD, which may provide insightful clues concerning its relationship with NDDs and their possible application into the clinical practice. In this study, 400 AMD patients were subjected to the genotyping analysis of 120 genetic variants by OpenArray technology. As the reference group, 503 samples representative of the European general population were utilized. Statistical analysis revealed the association of 23 single-nucleotide polymorphisms (SNPs) with AMD risk. The analysis of epistatic effects revealed that ARMS2, IL6, APOE, and IL2RA could contribute to AMD and neurodegenerative processes by synergistic modulation of the expression of disease-relevant genes. In addition, the bioinformatic analysis of the associated miRNA variants highlighted miR-196a, miR-6796, miR-6499, miR-6810, miR-499, and miR-7854 as potential candidates for counteracting AMD and neurodegenerative processes. Finally, this work highlighted the existence of shared disease mechanisms (oxidative stress, immune-inflammatory response, mitochondrial dysfunction, axonal guidance pathway, and synaptogenesis) between AMD and NDDs and described the associated SNPs as candidate biomarkers for developing novel strategies for early diagnosis, monitoring, and treatment of such disorders in a progressive aging population.
Stefania Zampatti, Michele Ragazzo, Carlo Fabrizio, Andrea Termine, Giulia Campoli, Valerio Caputo, Claudia Strafella, Raffaella Cascella, Carlo Caltagirone, and Emiliano Giardina
MDPI AG
Human behaviour is determined by a complex interaction of genetic and environmental factors. Several studies have demonstrated different associations between human behaviour and numerous genetic variants. In particular, allelic variants in SLC6A4, MAOA, DRD4, and DRD2 showed statistical associations with major depressive disorder, antisocial behaviour, schizophrenia, and bipolar disorder; BDNF polymorphic variants were associated with depressive, bipolar, and schizophrenia diseases, and TPH2 variants were found both in people with unipolar depression and in children with attention deficit-hyperactivity disorder (ADHD). Independent studies have failed to confirm polymorphic variants associated with criminal and aggressive behaviour. In the present study, a set of genetic variants involved in serotoninergic, dopaminergic, and neurobiological pathways were selected from those previously associated with criminal behaviour. The distribution of these genetic variants was compared across worldwide populations. While data on single polymorphic variants showed differential distribution across populations, these differences failed to be significant when a comprehensive analysis was conducted on the total number of published variants. The lack of reproducibility of the genetic association data published to date, the weakness of statistical associations, the heterogeneity of the phenotype, and the massive influence of the environment on human behaviour do not allow us to consider these genetic variants as undoubtedly associated with antisocial behaviour. Moreover, these data confirm the absence of ethnic predisposition to aggressive and criminal behaviour.
Michele Ragazzo, Giulio Puleri, Valeria Errichiello, Laura Manzo, Laura Luzzi, Saverio Potenza, Claudia Strafella, Cristina Peconi, Fabio Nicastro, Valerio Caputo,et al.
MDPI AG
A custom plate of OpenArray™ technology was evaluated to test 60 single-nucleotide polymorphisms (SNPs) validated for the prediction of eye color, hair color, and skin pigmentation, and for personal identification. The SNPs were selected from already validated subsets (Hirisplex-s, Precision ID Identity SNP Panel, and ForenSeq DNA Signature Prep Kit). The concordance rate and call rate for every SNP were calculated by analyzing 314 sequenced DNA samples. The sensitivity of the assay was assessed by preparing a dilution series of 10.0, 5.0, 1.0, and 0.5 ng. The OpenArray™ platform obtained an average call rate of 96.9% and a concordance rate near 99.8%. Sensitivity testing performed on serial dilutions demonstrated that a sample with 0.5 ng of total input DNA can be correctly typed. The profiles of the 19 SNPs selected for human identification reached a random match probability (RMP) of, on average, 10−8. An analysis of 21 examples of biological evidence from 8 individuals, that generated single short tandem repeat profiles during the routine workflow, demonstrated the applicability of this technology in real cases. Seventeen samples were correctly typed, revealing a call rate higher than 90%. Accordingly, the phenotype prediction revealed the same accuracy described in the corresponding validation data. Despite the reduced discrimination power of this system compared to STR based kits, the OpenArray™ System can be used to exclude suspects and prioritize samples for downstream analyses, providing well-established information about the prediction of eye color, hair color, and skin pigmentation. More studies will be needed for further validation of this technology and to consider the opportunity to implement this custom array with more SNPs to obtain a lower RMP and to include markers for studies of ancestry and lineage.
Andrea Termine, Carlo Fabrizio, Claudia Strafella, Valerio Caputo, Laura Petrosini, Carlo Caltagirone, Emiliano Giardina, and Raffaella Cascella
MDPI AG
In the big data era, artificial intelligence techniques have been applied to tackle traditional issues in the study of neurodegenerative diseases. Despite the progress made in understanding the complex (epi)genetics signatures underlying neurodegenerative disorders, performing early diagnosis and developing drug repurposing strategies remain serious challenges for such conditions. In this context, the integration of multi-omics, neuroimaging, and electronic health records data can be exploited using deep learning methods to provide the most accurate representation of patients possible. Deep learning allows researchers to find multi-modal biomarkers to develop more effective and personalized treatments, early diagnosis tools, as well as useful information for drug discovering and repurposing in neurodegenerative pathologies. In this review, we will describe how relevant studies have been able to demonstrate the potential of deep learning to enhance the knowledge of neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases through the integration of all sources of biomedical data.