127 research outputs found
Host genetic basis of COVID-19: from methodologies to genes
No full textThe COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is having a massive impact on public health, societies, and economies worldwide. Despite the ongoing vaccination program, treating COVID-19 remains a high priority; thus, a better understanding of the disease is urgently needed. Initially, susceptibility was associated with age, sex, and other prior existing comorbidities. However, as these conditions alone could not explain the highly variable clinical manifestations of SARS-CoV-2 infection, the attention was shifted toward the identification of the genetic basis of COVID-19. Thanks to international collaborations like The COVID-19 Host Genetics Initiative, it became possible the elucidation of numerous genetic markers that are not only likely to help in explaining the varied clinical outcomes of COVID-19 patients but can also guide the development of novel diagnostics and therapeutics. Within this framework, this review delineates GWAS and Burden test as traditional methodologies employed so far for the discovery of the human genetic basis of COVID-19, with particular attention to recently emerged predictive models such as the post-Mendelian model. A summary table with the main genome-wide significant genomic loci is provided. Besides, various common and rare variants identified in genes like TLR7, CFTR, ACE2, TMPRSS2, TLR3, and SELP are further described in detail to illustrate their association with disease severity
Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features
No full textThe 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 ( IPGS p h 1 and IPGS p h 2 ). By applying a logistic regression with both IPGS, ( IPGS p h 2 (or indifferently IPGS p h 1 ) 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%
Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity
No full textThe combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate 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. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.</p
Potentially treatable disorder diagnosed post Mortem by exome analysis in a boy with respiratory distress
No full textWe highlight the importance of exome sequencing in solving a clinical case of a child who died at 14 months after a series of respiratory crises. He was the half-brother of a girl diagnosed a7 years with the early-onset seizure variant of Rett syndrome due to CDKL5 mutation. We performed a test for CDKL5 in the boy, which came back negative. Driven by the mother’s compelling need for a diagnosis, we moved forward performing whole exome sequencing analysis. Surprisingly, two missense mutations in compound heterozygosity were identified in the RAPSN gene encoding a receptor-associated protein with a key role in clustering and anchoring nicotinic acetylcholine receptors at synaptic sites. This gene is responsible for a congenital form of myasthenic syndrome, a disease potentially treatable with cholinesterase inhibitors. Therefore, an earlier diagnosis in this boy would have led to a better clinical management and prognosis. Our study supports the key role of exome sequencing in achieving a definite diagnosis in severe perinatal diseases, an essential step especially when a specific therapy is available
Nosological and Theranostic Approach to Vascular Malformation through cfDNA NGS Liquid Biopsy
No full textSeveral 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
Autism Spectrum Disorders: Analysis of Mobile Elements at 7q11.23 Williams–Beuren Region by Comparative Genomics
No full textAutism spectrum disorders (ASD) are a group of complex neurodevelopmental disorders, characterized by a deficit in social interaction and communication. Many genetic variants are associated with ASD, including duplication of 7q11.23 encompassing 26–28 genes. Symmetrically, the hemizygous deletion of 7q11.23 causes Williams–Beuren syndrome (WBS), a multisystem disorder characterized by “hyper-sociability” and communication skills. Interestingly, deletion of four non-exonic mobile elements (MEs) in the “canine WBS locus” were associated with the behavioral divergence between the wolf and the dog and dog sociability and domestication. We hypothesized that indel of these MEs could be involved in ASD, associated with its different phenotypes and useful as biomarkers for patient stratification and therapeutic design. Since these MEs are non-exonic they have never been discovered before. We searched the corresponding MEs and loci in humans by comparative genomics. Interestingly, they mapped on different but ASD related genes. The loci in individuals with phenotypically different autism and neurotypical controls were amplified by PCR. A sub-set of each amplicon was sequenced by Sanger. No variant resulted associated with ASD and neither specific phenotypes were found but novel small-scale insertions and SNPs were discovered. Since MEs are hyper-methylated and epigenetically modulate gene expression, further investigation in ASD is necessary
X-Linked Alport Syndrome in Women: Genotype and Clinical Course in 24 Cases
No full textObjectives: X-linked Alport syndrome (XLAS) females are at risk of developing proteinuria and chronic kidney damage (CKD). The aim of this study is to evaluate the genotype-phenotype correlation in this rare population.Materials and Methods: This is a prospective, observational study of XLAS females, confirmed by a pathogenic mutation in COL4A5 and renal ultrastructural evaluation. Proteinuria, renal function and extrarenal involvement were monitored during follow-up. Patients were divided in 2 groups, according to mutations in COL4A5: missense (Group 1) and non-missense variants (Group 2).Results: Twenty-four XLAS females, aged 10.6 +/- 10.4 years at clinical onset (mean follow-up: 13.1 +/- 12.6 years) were recruited between 2000 and 2017 at a single center. In group 1 there were 10 patients and in group 2, 14 (mean age at the end of follow-up: 24.9 +/- 13.6 and 23.2 +/- 13.8 years, respectively). One patient in Group 1 and 9 in Group 2 (p = 0.013) developed proteinuria during follow-up. Mean eGFR at last follow-up was lower in Group 2 (p = 0.027), where two patients developed CKD. No differences in hearing loss were documented among the two groups. Two patients in Group 2 carried one mutation in both COL4A5 and COL4A3 (digenic inheritance) and were proteinuric. In one family, the mother presented only hematuria while the daughter was proteinuric and presented a greater inactivation of the X chromosome carrying the wild-type allele.Conclusions: The appearance of proteinuria and CKD is more frequent in patients with severe variants. Carrying digenic inheritance and skewed XCI seem to be additional risk factors for proteinuria in XLAS females
Prognostic Value of Glomerular Collagen IV Immunofluorescence Studies in Male Patients with X-Linked Alport Syndrome
No full textBackground and objectives X-linked Alport syndrome (X-AS) is caused by mutations of the COL4A5 gene, which encodes for the collagen IV a5 chain (a5[COLIV]), resulting in structural and functional abnormalities of the glomerular basement membrane (GBM) and leading to CKD. The aim of the present study was to evaluate the prognostic value of residual collagen IV chain expression in the GBM of patients with X-AS. Design, setting, participants, & measurements The medical records of 22 patients with X-AS from 21 unrelated families collected between 1987 and 2009 were reviewed (median age at last follow-up, 19.9 years; range, 5.4-35.1 years); GBM expression of a1, a3, and a5(COLIV) chains was assessed by immunofluorescence microscopy. Results GBM distribution of the a5(COLIV) chain was diffuse in 1 and segmental or absent in 21 of the 22 patients; the expression of the a3(COLIV) chain was diffuse in 5 of 22 patients and segmental or absent in 17 of 22 patients. Patients with diffuse staining for the a3(COLIV) chain presented with proteinuria significantly later (median age, 16.9 versus 6.1 years; P=0.02) and reached an estimated GFR < 90 ml/min per 1.73 m2 at an older age (median age, 27.0 versus 14.9 years; P=0.01) compared with patients with segmental or absent staining. Two thirds of patients with abnormal a3(COLIV) expression by immunofluorescence studies had null or truncating COL4A5 mutations, as opposed to none of the 4 tested patients with diffuse a3(COLIV) chain glomerular distribution. © 2013 by the American Society of Nephrology
Gain- and Loss-of-Function <i>CFTR</i> Alleles Are Associated with COVID-19 Clinical Outcomes
No full textCarriers 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
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