Torque Teno Virus (TTV) in Renal Transplant Recipients: Species Diversity and Variability.

Torque Teno Virus (TTV) is a nonpathogenic and ubiquitous ssDNA virus, a member of the Anelloviridae family. TTV has been postulated as a biomarker in transplant patients. This study aimed to determine the TTV species diversity and variability in renal transplant recipients and to associate species diversity with the corresponding TTV viral load. From 27 recipients, 30 plasma samples were selected. Viral load was determined using two real-time PCR assays, followed by RCA-NGS and ORF1 phylogenetic analysis. The TTV diversity was determined in all samples. Variability was determined in three patients with two sequential samples (pre- and post-transplantation). Most of the samples presented multiple TTV species, up to 15 different species were detected. In the pre-transplant samples (n = 12), the most prevalent species were TTV3 (75%) and TTV13 (75%), and the median number of species per sample was 5 (IQR: 4-7.5). TTV3 was also the most prevalent (56%) in the post-transplant samples (n = 18), and the median number of species was 2 (IQR: 1.8-5.5). No significant correlation between the number of species and viral load was found. The number and type of TTV species showed total variability over time. We report high TTV species diversity in Argentinian recipients, especially in pre-transplant period, with total intra-host variability. However, we found no significant correlation between this high diversity and TTV viral load.

CFTR chloride channel activity modulates the mitochondrial morphology in cultured epithelial cells.

The impairment of the CFTR channel activity, a cAMP-activated chloride (Cl-) channel responsible for cystic fibrosis (CF), has been associated with a variety of mitochondrial alterations such as modified gene expression, impairment in oxidative phosphorylation, increased reactive oxygen species (ROS), and a disbalance in calcium homeostasis. The mechanisms by which these processes occur in CF are not fully understood. Previously, we demonstrated a reduced MTND4 expression and a failure in the mitochondrial complex I (mCx-I) activity in CF cells. Here we hypothesized that the activity of CFTR might modulate the mitochondrial fission/fusion balance, explaining the decreased mCx-I. The mitochondrial morphology and the levels of mitochondrial dynamic proteins MFN1 and DRP1 were analysed in IB3-1 CF cells, and S9 (IB3-1 expressing wt-CFTR), and C38 (IB3-1 expressing a truncated functional CFTR) cells. The mitochondrial morphology of IB3-1 cells compared to S9 and C38 cells showed that the impaired CFTR activity induced a fragmented mitochondrial network with increased rounded mitochondria and shorter branches. Similar results were obtained by using the CFTR pharmacological inhibitors CFTR(inh)-172 and GlyH101 on C38 cells. These morphological changes were accompanied by modifications in the levels of the mitochondrial dynamic proteins MFN1, DRP1, and p(616)-DRP1. IB3-1 CF cells treated with Mdivi-1, an inhibitor of mitochondrial fission, restored the mCx-I activity to values similar to those seen in S9 and C38 cells. These results suggest that the mitochondrial fission/fusion balance is regulated by the CFTR activity and might be a potential target to treat the impaired mCx-I activity in CF.

Glomerular filtration rate estimation in people older than 85: Comparison between CKD-EPI, MDRD-IDMS and BIS1 equations. / Estimación del filtrado glomerular en personas mayores de 85 años: comparación de las ecuaciones CKD-EPI, MDRD-IDMS y BIS1.

BACKGROUND: The evidence of glomerular filtration rate (GFR) estimating with serum creatinine based formulae in the elderly population is scarce. The purpose of this study is to compare CKD-EPI, MRD4-IDMS and BIS1 equations to analyse correlation and concordance in a population older than 85 years old. PATIENTS AND METHODS: We designed a retrospective cross-sectional study, which included data from 600 patients older than 85 years. GFR was estimated by the following equations: CKD-EPI, MDR4-IDMS and BIS1, using as variables sex, age and serum creatinine concentration. Statistics analysis included Wilcoxon test, Bland-Altman plot, non-parametric Passing-Bablok method and kappa statistic (simple and weighted). RESULTS: The patients' median (range) age was 87 (interval 85-98). The median GFR (range) was 42.4 (5.2-127.4) mL/min/1.73 m2, when it was estimated with MDRD-IDMS, 40.0 (4.5-93.1) for CKD-EPI and 36.9 (7.6-83.7) for BIS1. The comparison of BIS1 and CKD-EPI and MDRD-IDMS using the Wilcoxon test was significant (P<.001). The regression analysis yielded the following equations: MDRD-IDMS= 1,025×CKD-EPI+1.360; BIS1= 0.688×CKD-EPI+9.074 and BIS1= 0.666×MDRD-IDMS+8.401. The weighted coefficient was 0.958 for the concordance between MDRD-IDMS and CKD-EPI, 0.812 for the concordance between MDRD-IDMS and BIS1 and 0.846 for CKD-EPI and BIS1. CONCLUSIONS: The GFR estimations obtained with BS1 equation are not interchangeable with MDRD-IDMS or CKD-EPI equations. BIS1 estimates lower GFR values than MDRD-IDMS and CKD-EPI and tends to classify the patients in a more advanced chronic kidney disease stage, especially for estimated GFR higher than 29mL/min/1.73 m2.

Estimación del filtrado glomerular en personas mayores de 85 años: comparación de las ecuaciones CKD-EPI, MDRD-IDMS y BIS1 / Glomerular filtration rate estimation in people older than 85: Comparison between CKD-EPI, MDRD-IDMS and BIS1 equations

Antecedentes: La estimación del filtrado glomerular (FG) en el anciano con las fórmulas basadas en la creatinina es limitada. El objetivo del estudio es comparar las ecuaciones CKD-EPI, MDRD-IDMS y BIS1 y analizar la correlación y la concordancia en una población mayor de 85 años. Pacientes y métodos: Realizamos un estudio transversal retrospectivo y se recogieron datos de 600 pacientes mayores de 85 años. Se estimó el FG por las ecuaciones CKD-EPI, MDRD-IDMS y BIS1 a partir de datos de sexo, edad y creatinina. El estudio estadístico incluyó el test de Wilcoxon, análisis de Bland-Altman, rectas de regresión de Passing-Bablok, concordancia bruta e índice ponderado. Resultados: La mediana (intervalo) de edad de los pacientes fue 87 (85-98). Las medianas del filtrado glomerular estimado por MDRD-IDMS fueron 42,4 (5,2-127,4) mL/min/1,73 m2, según CKD-EPI 40,0 (4,5-93,1) mL/min/1,73 m2 y por BIS1 36,9 (7,6-83,7) mL/min/1,73 m2. La comparación mediante test de Wilcoxon de BIS1 con CKD-EPI y MDRD-IDMS fue significativa (p<0,001). El análisis de regresión dio lugar a las siguientes ecuaciones: MDRD-IDMS = 1,025×CKD-EPI+1,36; BIS1=0,688×CKD-EPI+9,074 y BIS1=0,666×MDRD-IDMS+8,401. La concordancia ponderada entre MDRD-IDMS y CKD-EPI fue κ=0,598; entre MDRD-IDMS y BIS1: κ=0,812 y entre CKD-EPI y BIS1: κ=0,846. Conclusiones: Las estimaciones de FG obtenidas con la ecuación BIS1 no son intercambiables ni con MDRD-IDMS ni con CKD-EPI. La ecuación BIS1 presenta valores más bajos que MDRD-IDMS y CKD-EPI, y tiende a clasificar en un estadio mayor de ERC a los pacientes, sobre todo a partir de un FG estimado de 29mL/min/1,73 m2 (AU)

Background: The evidence of glomerular filtration rate (GFR) estimating with serum creatinine based formulae in the elderly population is scarce. The purpose of this study is to compare CKD-EPI, MRD4-IDMS and BIS1 equations to analyse correlation and concordance in a population older than 85 years old. Patients and methods: We designed a retrospective cross-sectional study, which included data from 600 patients older than 85 years. GFR was estimated by the following equations: CKD-EPI, MDR4-IDMS and BIS1, using as variables sex, age and serum creatinine concentration. Statistics analysis included Wilcoxon test, Bland-Altman plot, non-parametric Passing-Bablok method and kappa statistic (simple and weighted). Results: The patients’ median (range) age was 87 (interval 85-98). The median GFR (range) was 42.4 (5.2-127.4) mL/min/1.73 m2, when it was estimated with MDRD-IDMS, 40.0 (4.5-93.1) for CKD-EPI and 36.9 (7.6-83.7) for BIS1. The comparison of BIS1 and CKD-EPI and MDRD-IDMS using the Wilcoxon test was significant (P<.001). The regression analysis yielded the following equations: MDRD-IDMS= 1,025×CKD-EPI+1.360; BIS1= 0.688×CKD-EPI+9.074 and BIS1= 0.666×MDRD-IDMS+8.401. The weighted coefficient was 0.958 for the concordance between MDRD-IDMS and CKD-EPI, 0.812 for the concordance between MDRD-IDMS and BIS1 and 0.846 for CKD-EPI and BIS1. Conclusions: The GFR estimations obtained with BS1 equation are not interchangeable with MDRD-IDMS or CKD-EPI equations. BIS1 estimates lower GFR values than MDRD-IDMS and CKD-EPI and tends to classify the patients in a more advanced chronic kidney disease stage, especially for estimated GFR higher than 29mL/min/1.73 m2 (AU)