Project description:Background: Age-dependent renal impairment contributes to renal dysfunction in both the general population and young and middle-aged patients with renal diseases. Pathological changes in age-dependent renal impairment include glomerulosclerosis and tubulointerstitial fibrosis. The molecules involved in age-dependent renal impairment are not fully elucidated. MicroRNA (miRNA) species were reported to modulate various renal diseases, but the miRNA species involved in age-dependent renal impairment are unclear. Here, we investigated miRNAs in age-dependent renal impairment, and we evaluated their potential as biomarkers and therapeutic targets. Methods: We conducted an initial microarray profiling analysis to screen miRNAs whose expression levels changed in kidneys of senescence-accelerated resistant (SAMR1)-10-week-old (wk) mice and SAMR1-50wk mice and senescence-accelerated prone (SAMP1)-10wk mice and SAMP1-50wk mice. We then evaluated the expressions of differentially expressed miRNAs in serum from 13 older patients (>65 years old) with age-dependent renal impairment (estimated glomerular filtration ratio <60 mL/min/1.73 m2) by a quantitative real-time polymerase chain reaction (qRT-PCR) and compared the expressions with those of age-matched subjects with normal renal function. We also administered miRNA mimics or inhibitors (5 nmol) with a nonviral vector (polyethylenimine nanoparticles: PEI-NPs) to SAMP1-20wk mice to investigate the therapeutic effects. Results: The qRT-PCR revealed a specific miRNA (miRNA-503-5p) whose level was significantly changed in SAMP1-50wk mouse kidneys in comparison to the controls. The expression level of miRNA-503-5p was upregulated in the serum of the 13 patients with age-dependent renal impairment compared to the age-matched subjects with normal renal function. The administration of a miRNA-503-5p-inhibitor with PEI-NPs decreased the miRNA-503-5p expression levels, resulting in the inhibition of renal fibrosis in mice via an inhibition of a pro-fibrotic signaling pathway and a suppression of glomerulosclerosis in mice by inhibiting intrinsic signaling pathways. Conclusion: miRNA-503-5p may represent a biomarker for age-dependent renal impairment, and the inhibition of miRNA-503-5p had no effect on age-dependent renal impairment. However, the inhibition of miRNA-503-5p had therapeutic effects on renal fibrosis and glomerulosclerosis.

Project description:The mechanisms underlying age-associated memory impairment are not well understood. We have shown that the onset of memory disturbances in the aging brain is associated with altered hippocampal chromatin plasticity. During learning, aged mice display a specific deregulation of histone H4 lysine 12 (H4K12) acetylation. To analyze if deregulated H4K12 acetylation impacts on learning-induced gene-expression required for memory consolidation we performed a high-density oligonucleotide microarray to compare the entire hippocampal gene-expression profile of 3 and 16-month-old mice during memory consolidation. In order to identify genes differentially regulated between 3- and 16-month old mice upon fear conditioning we subjected 3- and 16-month old mice to fear conditioning (4 mice each group, total 8 mice) . Mice of the same age that were handled but not subjected to any of the employed behavior paradigms served as control (4 mice 3-month old and 4 mice 16-month old, total 8 mice). During fear conditioning mice are subjected to a novel context followed by a mild electric foot-shock (context-shock exposure). In order to identify genes that are differentially regulated upon fear conditioning and are specific to associative learning we also tested the hippocampal gene-expression profile of 3-month old mice subjected to the same context-exposure that is not followed by a foot-shock (Context-exposure) (4 mice) or receive an immediate foot shock once they are placed in the context and only afterwards are allowed to explore the context (shock-context exposure) (4 mice). In order to identify genes that are regulated upon fear conditioning and are specific to associative learning we compared the hippocampal gene-expression profile of mice subjected to fear conditioning (context-shock), context or shock-context exposure regarding to their age-matched control mice (3 month old) mentioned above (control). Hippocampi from each mice were tested resulting to 24 samples which were separately hybridized (OneColor Array Design).

Project description:Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining “molecular Banff” signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set here comprises a small validation batch of renal allograft biopsies for clinical indications plus control normal kidney samples from patients at Hôpital Tenon, Paris (second batch) that complements the first batch of 60 samples. We used microarrays to identify different gene expression signatures of renal allograft biopsies that can classify them according to different types of allograft rejection or CAN. Keywords: disease state analysis 4 renal allograft core biopsies for clinical indications with different histopathological diagnoses according to Banff'97 criteria and 2 normal kidney samples.

Project description:Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining âmolecular Banffâ signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set comprises all renal allograft biopsies for clinical indications from patients at HÃ´pital Tenon, Paris (February 2003 until September 2004) and few respective patients from HÃ´pital BicÃªtre, Paris, HÃ´pital Pellegrin, Bordeaux, and HÃ´pital Dupuytren, Limoges, plus control normal kidney samples from HÃ´pital Tenon, Paris, France (first batch). We used microarrays to identify different gene expression signatures of renal allograft biopsies that can classify them according to different types of allograft rejection or CAN. Experiment Overall Design: 47 renal allograft core biopsies for clinical indications with different histopathological diagnoses according to BANFF'97 criteria, and 13 normal kidney samples as controls.

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Identification of Messenger RNA Signatures in Age-Dependent Renal Impairment

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