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3.
Kidney Int Rep ; 9(9): 2667-2676, 2024 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-39291188

RESUMO

Introduction: Among individuals with high-risk APOL1 genotypes, the lifetime risk of developing kidney failure is ∼15%, indicating that other genetic variants or nongenetic modifiers likely contribute substantially to an individual patient's risk of progressive kidney disease. Here, we estimate the prevalence and distribution of Mendelian kidney diseases among patients with high-risk APOL1 genotypes undergoing commercial genetic testing in the United States. Methods: We analyzed clinical exome sequencing data from 15,181 individuals undergoing commercial genetic testing for Mendelian kidney disease in the United States from 2020 to 2021. We identified patients with high-risk APOL1 genotypes by the presence of G1/G1, G1/G2, or G2/G2 alleles. Patients carrying single risk APOL1 alleles were identified as G1/G0, G2/G0; the remainder of patients were G0/G0. We estimated the prevalence and distribution of Mendelian kidney disease stratified by APOL1 genotype and genetically predicted ancestry. Results: Of 15,181 patients, 3119 had genetic testing results consistent with a molecular diagnosis of Mendelian kidney disease (20.5%). Of 15,181 patients, 1035 (6.8%) had high-risk APOL1 genotypes. Among patients with recent genomic African ancestry, the prevalence of Mendelian kidney diseases was lower in those with high-risk APOL1 genotypes (9.6%; n = 91/944) compared with single risk APOL1 allele carriers (13.6%; n = 198/1453) and those with G0/G0 APOL1 genotypes (16.6%; n = 213/1281). Among patients with Mendelian kidney disease and recent genomic African ancestry, we observed differences in the prevalence of pathogenic/likely pathogenic variants in PKD1 (19.8% in high-risk vs. 30.2% in low-risk genotypes), and COL4A4 (24.2% in high-risk vs. 10.5% in low-risk genotypes). Conclusion: In this selected population of patients undergoing clinical genetic testing, we found evidence of Mendelian kidney disease in ∼10% patients with high-risk APOL1 genotypes.

4.
Virus Evol ; 7(2): veab078, 2021 Sep 29.
Artigo em Inglês | MEDLINE | ID: mdl-34642605

RESUMO

Long-term infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a challenge to virus dispersion and the control of coronavirus disease 2019 (COVID-19) pandemic. The reason why some people have prolonged infection and how the virus persists for so long are still not fully understood. Recent studies suggested that the accumulation of intra-host single nucleotide variants (iSNVs) over the course of the infection might play an important role in persistence as well as emergence of mutations of concern. For this reason, we aimed to investigate the intra-host evolution of SARS-CoV-2 during prolonged infection. Thirty-three patients who remained reverse transcription polymerase chain reaction (RT-PCR) positive in the nasopharynx for on average 18 days from the symptoms onset were included in this study. Whole-genome sequences were obtained for each patient at two different time points. Phylogenetic, populational, and computational analyses of viral sequences were consistent with prolonged infection without evidence of coinfection in our cohort. We observed an elevated within-host genomic diversity at the second time point samples positively correlated with cycle threshold (Ct) values (lower viral load). Direct transmission was also confirmed in a small cluster of healthcare professionals that shared the same workplace by the presence of common iSNVs. A differential accumulation of missense variants between the time points was detected targeting crucial structural and non-structural proteins such as Spike and helicase. Interestingly, longitudinal acquisition of iSNVs in Spike protein coincided in many cases with SARS-CoV-2 reactive and predicted T cell epitopes. We observed a distinguishing pattern of mutations over the course of the infection mainly driven by increasing A→U and decreasing G→A signatures. G→A mutations may be associated with RNA-editing enzyme activities; therefore, the mutational profiles observed in our analysis were suggestive of innate immune mechanisms of the host cell defense. Therefore, we unveiled a dynamic and complex landscape of host and pathogen interaction during prolonged infection of SARS-CoV-2, suggesting that the host's innate immunity shapes the increase of intra-host diversity. Our findings may also shed light on possible mechanisms underlying the emergence and spread of new variants resistant to the host immune response as recently observed in COVID-19 pandemic.

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