Uncovering genetic mechanisms of kidney aging through transcriptomics, genomics, and epigenomics
- Rowland, Joshua, Akbarov, Artur, Eales, James, Xu, Xiaoguang, Dormer, John, Guo, Hui, Denniff, Matthew, Jiang, Xiao, Ranjzad, Parisa, Nazgiewicz, Alicja, Prestes, Priscilla, Antczak, Andrzej, Szulinska, Monika, Wise, Ingrid, Zukowska-Szczechowska, Ewa, Bogdanski, Pawel, Woolf, Adrian, Samani, Nilesh, Charchar, Fadi, Tomaszewski, Maciej
- Authors: Rowland, Joshua , Akbarov, Artur , Eales, James , Xu, Xiaoguang , Dormer, John , Guo, Hui , Denniff, Matthew , Jiang, Xiao , Ranjzad, Parisa , Nazgiewicz, Alicja , Prestes, Priscilla , Antczak, Andrzej , Szulinska, Monika , Wise, Ingrid , Zukowska-Szczechowska, Ewa , Bogdanski, Pawel , Woolf, Adrian , Samani, Nilesh , Charchar, Fadi , Tomaszewski, Maciej
- Date: 2019
- Type: Text , Journal article
- Relation: Kidney International Vol. 95, no. 3 (2019), p. 624-635
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- Description: Nephrons scar and involute during aging, increasing the risk of chronic kidney disease. Little is known, however, about genetic mechanisms of kidney aging. We sought to define the signatures of age on the renal transcriptome using 563 human kidneys. The initial discovery analysis of 260 kidney transcriptomes from the TRANScriptome of renaL humAn TissuE Study (TRANSLATE) and the Cancer Genome Atlas identified 37 age-associated genes. For 19 of those genes, the association with age was replicated in 303 kidney transcriptomes from the Nephroseq resource. Surveying 42 nonrenal tissues from the Genotype–Tissue Expression project revealed that, for approximately a fifth of the replicated genes, the association with age was kidney-specific. Seventy-three percent of the replicated genes were associated with functional or histological parameters of age-related decline in kidney health, including glomerular filtration rate, glomerulosclerosis, interstitial fibrosis, tubular atrophy, and arterial narrowing. Common genetic variants in four of the age-related genes, namely LYG1, PPP1R3C, LTF and TSPYL5, correlated with the trajectory of age-related changes in their renal expression. Integrative analysis of genomic, epigenomic, and transcriptomic information revealed that the observed age-related decline in renal TSPYL5 expression was determined both genetically and epigenetically. Thus, this study revealed robust molecular signatures of the aging kidney and new regulatory mechanisms of age-related change in the kidney transcriptome.
- Authors: Rowland, Joshua , Akbarov, Artur , Eales, James , Xu, Xiaoguang , Dormer, John , Guo, Hui , Denniff, Matthew , Jiang, Xiao , Ranjzad, Parisa , Nazgiewicz, Alicja , Prestes, Priscilla , Antczak, Andrzej , Szulinska, Monika , Wise, Ingrid , Zukowska-Szczechowska, Ewa , Bogdanski, Pawel , Woolf, Adrian , Samani, Nilesh , Charchar, Fadi , Tomaszewski, Maciej
- Date: 2019
- Type: Text , Journal article
- Relation: Kidney International Vol. 95, no. 3 (2019), p. 624-635
- Full Text:
- Reviewed:
- Description: Nephrons scar and involute during aging, increasing the risk of chronic kidney disease. Little is known, however, about genetic mechanisms of kidney aging. We sought to define the signatures of age on the renal transcriptome using 563 human kidneys. The initial discovery analysis of 260 kidney transcriptomes from the TRANScriptome of renaL humAn TissuE Study (TRANSLATE) and the Cancer Genome Atlas identified 37 age-associated genes. For 19 of those genes, the association with age was replicated in 303 kidney transcriptomes from the Nephroseq resource. Surveying 42 nonrenal tissues from the Genotype–Tissue Expression project revealed that, for approximately a fifth of the replicated genes, the association with age was kidney-specific. Seventy-three percent of the replicated genes were associated with functional or histological parameters of age-related decline in kidney health, including glomerular filtration rate, glomerulosclerosis, interstitial fibrosis, tubular atrophy, and arterial narrowing. Common genetic variants in four of the age-related genes, namely LYG1, PPP1R3C, LTF and TSPYL5, correlated with the trajectory of age-related changes in their renal expression. Integrative analysis of genomic, epigenomic, and transcriptomic information revealed that the observed age-related decline in renal TSPYL5 expression was determined both genetically and epigenetically. Thus, this study revealed robust molecular signatures of the aging kidney and new regulatory mechanisms of age-related change in the kidney transcriptome.
Molecular insights into genome-wide association studies of chronic kidney disease-defining traits
- Xu, Xiaoguang, Eales, James, Akbarov, Artur, Guo, Hui, Becker, Lorenz, Talavera, David, Ashraf, Fehzan, Nawaz, Jabran, Pramanik, Sanjeev, Bowes, John, Jiang, Xiao, Dormer, John, Denniff, Matthew, Antczak, Andrzej, Szulinska, Monika, Wise, Ingrid, Prestes, Priscilla, Glyda, Maciej, Bogdanski, Pawel, Zukowska-Szczechowska, Ewa, Berzuini, Carlo, Woolf, Adrian, Samani, Nilesh, Charchar, Fadi, Tomaszewski, Maciej
- Authors: Xu, Xiaoguang , Eales, James , Akbarov, Artur , Guo, Hui , Becker, Lorenz , Talavera, David , Ashraf, Fehzan , Nawaz, Jabran , Pramanik, Sanjeev , Bowes, John , Jiang, Xiao , Dormer, John , Denniff, Matthew , Antczak, Andrzej , Szulinska, Monika , Wise, Ingrid , Prestes, Priscilla , Glyda, Maciej , Bogdanski, Pawel , Zukowska-Szczechowska, Ewa , Berzuini, Carlo , Woolf, Adrian , Samani, Nilesh , Charchar, Fadi , Tomaszewski, Maciej
- Date: 2018
- Type: Text , Journal article
- Relation: Nature communications Vol. 9, no. 1 (2018), p. 1-12
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- Description: Genome-wide association studies (GWAS) have identified >100 loci of chronic kidney disease-defining traits (CKD-dt). Molecular mechanisms underlying these associations remain elusive. Using 280 kidney transcriptomes and 9958 gene expression profiles from 44 non-renal tissues we uncover gene expression partners (eGenes) for 88.9% of CKD-dt GWAS loci. Through epigenomic chromatin segmentation analysis and variant effect prediction we annotate functional consequences to 74% of these loci. Our colocalisation analysis and Mendelian randomisation in >130,000 subjects demonstrate causal effects of three eGenes (NAT8B, CASP9 and MUC1) on estimated glomerular filtration rate. We identify a common alternative splice variant in MUC1 (a gene responsible for rare Mendelian form of kidney disease) and observe increased renal expression of a specific MUC1 mRNA isoform as a plausible molecular mechanism of the GWAS association signal. These data highlight the variants and genes underpinning the associations uncovered in GWAS of CKD-dt.
- Authors: Xu, Xiaoguang , Eales, James , Akbarov, Artur , Guo, Hui , Becker, Lorenz , Talavera, David , Ashraf, Fehzan , Nawaz, Jabran , Pramanik, Sanjeev , Bowes, John , Jiang, Xiao , Dormer, John , Denniff, Matthew , Antczak, Andrzej , Szulinska, Monika , Wise, Ingrid , Prestes, Priscilla , Glyda, Maciej , Bogdanski, Pawel , Zukowska-Szczechowska, Ewa , Berzuini, Carlo , Woolf, Adrian , Samani, Nilesh , Charchar, Fadi , Tomaszewski, Maciej
- Date: 2018
- Type: Text , Journal article
- Relation: Nature communications Vol. 9, no. 1 (2018), p. 1-12
- Full Text:
- Reviewed:
- Description: Genome-wide association studies (GWAS) have identified >100 loci of chronic kidney disease-defining traits (CKD-dt). Molecular mechanisms underlying these associations remain elusive. Using 280 kidney transcriptomes and 9958 gene expression profiles from 44 non-renal tissues we uncover gene expression partners (eGenes) for 88.9% of CKD-dt GWAS loci. Through epigenomic chromatin segmentation analysis and variant effect prediction we annotate functional consequences to 74% of these loci. Our colocalisation analysis and Mendelian randomisation in >130,000 subjects demonstrate causal effects of three eGenes (NAT8B, CASP9 and MUC1) on estimated glomerular filtration rate. We identify a common alternative splice variant in MUC1 (a gene responsible for rare Mendelian form of kidney disease) and observe increased renal expression of a specific MUC1 mRNA isoform as a plausible molecular mechanism of the GWAS association signal. These data highlight the variants and genes underpinning the associations uncovered in GWAS of CKD-dt.
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