AIMS:Ageing leads to a progressive loss in structural integrity and a functional decline of human organs, alongside telomere attrition and alterations in DNA methylation patterns. Their relationships in the human kidney in the context of ageing remain elusive. METHODS AND RESULTS:We analysed 200 participants from the human kidney tissue resource (HKTR) with matching information on kidney histology, renal function, blood leucocyte and kidney telomere length, as well as kidney genome-wide DNA methylation profiles. Additional 71 HKTR individuals without telomere data were used in validation analyses. Kidney telomere length showed a significant inverse association with age (β = -0.029, confidence interval = -0.043 to -0.016, P = 0.00003). Shorter kidney telomeres were strongly associated with both renal structure and function, independent of demographic and clinical confounders. Nephrosclerosis score showed a gradual increase with age categories, whilst kidney telomere length dropped simultaneously. Leucocyte telomere length was not related to the extent of age-related changes in kidney function or structure. Kidney DNA methylation analysis revealed that kidney CpGs, genes, pathways, and chromatin patterns associated with kidney telomere length are partly independent of these associated with chronological age. Consisted of 57 CpGs, epigenetic clock of kidney telomere length showed a predictive potential for nephrosclerosis, independent of clinical cofounders, chronological, and epigenetic age. CONCLUSION:Our study revealed that gradual age-related structural involution of human kidney and a decline in its filtration capacity are accompanied by shortening of telomeres in renal cells and that changes in the kidney epigenome (i.e. DNA methylation) may contribute to nephrosclerosis (at least in part) independently of chronological age.

Chronic Kidney Disease (CKD) affects 10% of the world's population and is the third fastest growing cause of death globally. Hyperuricemia and gout are frequent comorbidities of CKD and are associated with worse prognosis and increased mortality. We conducted a genome-wide association study (GWAS) of four CKD-defining traits (estimated glomerular filtration rate from creatinine—eGFRcr; eGFR from cystatin C—eGFRcys; blood urea nitrogen—BUN; and urinary albumin creatinine ratio—UACR) in the joint analysis of UK Biobank and CKDGen. We zoomed in on the novel candidate Carbonic Anhydrase 12 (CA12) given its role in renal acid-base and electrolyte balance, as well as treatment of several diseases through its inhibitor acetazolamide. Hypothesizing that CA12 is a causal contributor to kidney function, we aimed to characterise the effects of regulatory and loss-of-function CA12 alleles on CKD-defining traits and urate levels. We performed GWAS of four markers of kidney function in up to 327,689 UK biobank (UKB) participants, and meta-analysed the results with associations from CKDGen in up to 567,460 individuals. This identified a total of 508 unique independent genetic signals of associations with eGFRcr (424), eGFRcys (235), BUN (198) and UACR (51). A common CA12 variant rs1043256 showed strong consistent associations with eGFRcr, eGFRcys and BUN. We then tested rs1043256 association with its kidney mRNA (n = 645) and protein product (n = 83) in 2 collections of human kidney tissue. This was followed by Bayesian colocalization analyses to detect shared causal associations between gene/protein expression and kidney function biomarkers. To fully characterise the phenotypic effects, we tested a common CA12-reducing allele for association with 193 quantitative traits in 337,350 UKB participants by linear regression. A multi-trait colocalization analysis was performed to identify shared causal genetic associations. To investigate effects of CA12 loss-of-function, we tracked carriers of a rare allele causing the recessive monogenic disorder Hyperchloridhidrosis (HYCHL) in UKB (n = 1,038) and Million Veterans Program (MVP; n = 844). We tested this pathogenic variant for association with electrolytes, altered in HYCHL, and renal phenotypes. Associations were meta-analysed across the two cohorts when possible. The analyses were conducted in participants of European ancestry. The common CA12 rs1043256-C allele was associated with reduced kidney function (eGFRcr: P = 1.5 × 10−16, eGFRcys: P = 7.8 × 10−13, BUN: P = 1.1 × 10−9) and decreased expression of renal CA12 (mRNA: P = 1.2 × 10−5, protein: P = 1.5 × 10−3). The rs1043256-C allele was associated with increased serum urate in UKB (P = 4.5 × 10−6). Our multi-trait colocalization analysis confirmed a shared causal variant for indices of kidney function, urate and CA12 renal expression. In the fixed-effect meta-analysis conducted in UKB and MVP, we found that 1,882 heterozygote carriers of the CA12 loss-of-function allele (rs148438059-T) had decreased eGFRcr (P = 0.01), increased BUN (P = 0.03) and increased risk of gout (odds ratio = 1.5, P = 1.5 × 10−7). Serum urate was increased in UKB (P = 5.5 × 10−4). We demonstrate that genetically determined CA12 reduction is associated with decreased kidney function and increased serum urate. Our findings suggest that pharmacological CA12 inhibition by acetazolamide may mimic the renal effects of genetic CA12 reduction, including a drop in GFR and increase in serum urate (with the latter not a well-recognised side effect of this treatment).

The 2.7-Mb major pseudoautosomal region (PAR1) on the short arms of the human X and Y chromosomes plays a critical role in meiotic sex chromosome segregation and male fertility and has been regarded as evolutionarily stable. However, some European Y chromosomes belonging to Y haplogroups (Y-Hgs) R1b and I2a carry an ∼115-kb extension (ePAR [extended PAR]) arising from X-Y non-allelic homologous recombination (NAHR). To investigate the diversity, history, and dynamics of ePAR formation, we screened for its presence, and that of the predicted reciprocal X chromosome deletion, among ∼218,300 46,XY males of the UK Biobank (UKB), a cohort associated with longitudinal clinical data. The UKB incidence of ePAR is ∼0.77%, and that of the deletion is ∼0.02%. We found that Y-Hg I2a sub-lineages accounted for nearly 90% of ePAR cases but, by Y haplotyping and breakpoint sequencing, determined that, in total, there have been at least 18 independent ePAR origins, associated with nine different Y-Hgs. We found examples of ePAR linked to Y-Hg K among men of self-declared Pakistani ancestry and Y-Hg E1, typical of men with African ancestry, showing that ePAR is not restricted to Europeans. ePAR formation is likely random, with high frequencies in some Y-Hgs arising through drift and male-mediated expansions. Sequencing recombination junction fragments identified likely reciprocal events, and the heterogeneity of ePAR and X-deletion junctions highlighted the recurrent nature of the NAHR events. A phenome-wide association study revealed an association between ePAR and elevated levels of circulating IGF-1 as well as musculoskeletal phenotypes.

Hypertension is a major heritable risk factor for cardiovascular disease worldwide. The genetic underpinning of hypertension has expanded to encompass over 1000 common single-nucleotide polymorphisms (SNPs) associated with the blood pressure phenotype. However, these SNPs explain only approximately 27% of the 30–50% estimated heritability of blood pressure. This suggests that, although they may individually have a small impact, there are still unidentified SNPs that play a role in influencing this trait. Conventional Genome-Wide Association Studies (GWAS) have traditionally relied on cross-sectional data, overlooking the dynamic temporal dimension inherent in disease development. This study is distinctive for utilising whole-genome data and departing from cross-sectional GWAS studies with binary outcomes to identify SNPs associated with hypertension development through a time-to-event analysis. Disease outcome was determined based on data from various sources such as in-patient hospital records, self-reported data, primary care records, death registry data and time to event data collected in the UK Biobank. The timeframe for the survival analysis commenced from the enrolment of the final UK Biobank participant on October 1, 2010, and extended until the latest diagnosis of 'Essential hypertension' within the cohort on October 1, 2022, spanning approximately 12 years (4,383 days) of follow-up. For this analysis, samples containing whole-genome sequence (WGS) data were utilised. Employing the R package 'SPACox,' we conducted a genome-wide survival analysis utilising a saddlepoint approximation methodology rooted in a Cox Proportional Hazards (PH) regression model. SPACox facilitated genome-wide SNP association testing, with Age, Age2, Sex, BMI, and 10 principal components delineating population structure, included as covariates. Prior to the association analysis, stringent quality control (QC) measures were applied to the WGS data. SNPs exhibiting low call rates (<0.90), Hardy–Weinberg equilibrium exact test P-values below 1×10–15, or minor allele frequencies (MAFs) less than 0.01 were excluded from the analysis. The analysis included 21,248 hypertension cases and 123,038 controls, totalling 144,286 participants, with 58.0% women (average age - 55.3±0.0279 years). Post-genotyping QC, 6,319,822 million SNPs underwent analysis, revealing 31 variants at genome-wide significance (P-value<5×10–08), including 29 novel SNP associations—15 in Fibrillin-2 (FBN2) and 4 in Junctophilin-2 (JPH2) genes. Subsequently, Mendelian randomization analysis, employing a 2-sample strategy, and utilising two identified SNPs (rs17677724 and rs1014754), suggested a causal relationship. Specifically, a genetically induced decrease in heart FBN2 expression and an increase in adrenal gland JPH2 expression were implicated in the elevation of blood pressure (P-Value =1.66×10–06, 3.19×10–06). Phenome-wide association (PheWAS) analysis using the FinnGen dataset (r9.finngen.fi) reaffirmed rs17677724's (β = 0.492, P = 7.4×10–09) and rs1014754's (β = 0.0225, P = 4.8×10–05) positive association to hypertension, among 2,727 traits assessed in 377,277 individuals. Lastly, utilising a proteogenomic map sourced from 10,708 individuals of European descent and encompassing 4,775 measured plasma proteins, in the Fenland study, we conducted a targeted investigation into protein quantitative trait loci (pQTL) associations with Renin-Angiotensin-Aldosterone System (RAAS) component proteins. Our analysis unveiled that rs17677724 exhibited a negative association with renin (β = -0.036, SE = 0.018, P-value = 0.0435), while rs1014754 displayed a positive association with kallistatin (β = 0.031, SE = 0.013, P-Value= 0.0225). These findings suggest a potential counter-regulatory mechanism in response to the elevated blood pressure. In summary, our genome-wide time-to-event analysis unveils new genetic loci and potential therapeutic targets linked to hypertension. Conflict of Interest NA

Background and Objective: Chronic kidney disease (CKD) is a significant public health challenge, often progressing undetected until advanced stages. Early detection through biomarkers can enhance CKD management and improve patient outcomes. Previous studies suggested a link between telomeres and kidney health, but these results were inconsistent. This study aims to clarify the association between telomere length, kidney function and disease, and assess its causality using Mendelian randomisation (MR). Methods: Using the UK Biobank data, we examined the relationship between leukocyte telomere length (LTL) and kidney health. We performed multiple linear and logistic regression analyses using estimated glomerular filtration rate (eGFR) measures and reported kidney disease diagnoses, adjusting for age, sex, white blood cell count, body mass index, and hypertension. The causality of associations was tested using MR with established genetic instruments. Results: 338,143 participants were included in our analysis. The cohort had an average age of 56.52 years, with 54.41% being females. LTL was associated with eGFR from serum creatinine (eGFRcrea, beta = 0.001, p <0.01), serum cystatin C (eGFRcys, beta = 0.004, p <0.0001), and their combination (eGFRcreacys, beta = 0.003, p <0.0001). Additionally, longer LTL was associated with reduced odds of CKD (OR = 0.94 [95% CI 0.93-0.96], p <0.0001). Significant associations were also observed between LTL and acute renal failure (OR = 0.95 [95% CI 0.93-0.97], p <0.0001), and hypertensive kidney disease (OR = 0.91 [95% CI 0.86-0.96], p <0.001). MR analysis supported a causal effect of LTL on eGFRcrea (Effect size = 0.006, Bonferroni corrected p = 0.04). However, no causal effect was observed between LTL and CKD or other kidney diseases. Bi-directional MR analysis revealed that the relationship between LTL and kidney function is unidirectional. Conclusions: Longer LTL correlates with better kidney function and reduced kidney disease risk. MR findings suggest a potential causal relationship between LTL and kidney function, highlighting telomeres as promising biomarkers for early detection of CKD.

BackgroundUnderstanding the complex interactions between genes and their causal effects on diseases is crucial for developing targeted treatments and gaining insight into biological mechanisms. However, the analysis of molecular networks, especially in the context of high-dimensional data, presents significant challenges.MethodsThis study introduces MRdualPC, a computationally tractable algorithm based on the MRPC approach, to infer large-scale causal molecular networks. We apply MRdualPC to investigate the upstream causal transcriptomics influencing hypertension using a comprehensive dataset of kidney genome and transcriptome data.ResultsOur algorithm proves to be 100 times faster than MRPC on average in identifying transcriptomics drivers of hypertension. Through clustering, we identify 63 modules with causal driver genes, including 17 modules with extensive causal networks. Notably, we find that genes within one of the causal networks are associated with the electron transport chain and oxidative phosphorylation, previously linked to hypertension. Moreover, the identified causal ancestor genes show an over-representation of blood pressure-related genes.ConclusionsMRdualPC has the potential for broader applications beyond gene expression data, including multi-omics integration. While there are limitations, such as the need for clustering in large gene expression datasets, our study represents a significant advancement in building causal molecular networks, offering researchers a valuable tool for analyzing big data and investigating complex diseases.

Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes ( SLC5A11 , AGMAT , AGT , respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP ). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.

Objective: Telomeres shorten with each cell division and serve as markers of cell senescence. The rate of telomere attrition varies across tissues within the same individual. Telomere attrition and dysfunction has been associated with various disease states. Studies have shown that leukocyte telomere length (LTL) may be predictive of telomere length in other tissues of the body. Several histological changes occur in the kidney before functional impairment becomes evident. It is unclear if telomeres are associated with these early changes. We sought to (i) investigate whether LTL is a proxy of kidney telomere length (KTL), and (ii) estimate the extent to which both measures of biological ageing associate with histological markers of kidney damage. Design and Methods: Study group consisted of 200 participants (Female 38% and Male 62%) from the TRANScriptome of renaL humAn TissuE (TRANSLATE) study. Participants had no personal history of primary nephropathy and were eligible for unilateral elective nephrectomy because of sporadic non-invasive renal cancer. Kidney tissue samples were collected from the healthy (unaffected by cancer) pole immediately after nephrectomy and fixed in 10% formalin, then embedded in paraffin blocks. The extent of kidney histological damage was assessed using a semi-quantitative method of kidney slide evaluation. LTL and KTL were quantified using quantitative polymerase chain reaction. Results: There was a significant negative correlation between KTL and age (r = -0.287, P < 0.001). The correlation between LTL and age showed directionally consistent, but non-significant pattern (r = -0.135, P = 0.063). Unadjusted and adjusted analysis showed insignificant association between LTL and KTL (r = 0.042, P = 0.575). However, both KTL and LTL correlated with tubular atrophy (r = -0.28, -0.16; P < 0.001, 0.05, respectively). Each increased unit of both KTL and LTL also associated with a decrease of 61.3% and 47.4%, respectively in likelihood of developing tubular atrophy (Table 1). Shorter KTL was associated with increased odds of developing interstitial fibrosis, interstitial inflammation, and Bowmans capsule thickening (Table 1). KTL also associated with percentage of Bowmans capsule thickening (β = -0.214, P = 0.027), percentage of sclerosed glomeruli (β = -0.227, P = 0.017), and Remuzzi score (β = -0.280, P = 0.001). In contrast, LTL did not show an association with any other kidney histology variables, except with tubular atrophy in adjusted analysis. Conclusions: LTL shows only a weak association with tubular atrophy and KTL is a much more accurate measure of histologically confirmed structural kidney damage than LTL. LTL cannot be used as a proxy of KTL or the extent of kidney damage.

Objective: Essential hypertension is a major risk factor for incident chronic kidney disease (CKD). This is a main reason for preference of antihypertensive medications that provide some protection against hypertension induced renal damage. Furthermore, there is abundant evidence that hypertension and CKD comorbidity worsens cardiovascular disease prognosis with increased morbidity and mortality. Onset of CKD may not be noticeable until there is evident progressive decline in the estimated glomerular filtration rate (eGFR). For this, telomere attrition may provide some early indication. Telomeres are markers of biological aging, and telomere attrition is associated with oxidative stress and inflammation. Kidney interstitial inflammation is known to play a central role in loss of renal function progressing into CKD. This study investigated the association between telomere length and renal interstitial inflammation in hypertensive patients. Design and Methods: Our study group consisted of 200 participants from the TRANScriptome of renaL humAn TissuE (TRANSLATE) study. Interstitial inflammation in human kidney tissue samples was assessed by histology. eGFR was calculated from serum creatinine using Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) FORMULA. Leukocyte telomere length (LTL) was quantified using quantitative polymerase chain reaction. Results: Mean LTL was significantly shorter in hypertensive participants (2.776 ± 0.063) compared with non-hypertensive participants (3.007 ± 0.092; P = 0.041). In hypertensive participants without CKD, renal interstitial inflammation negatively associates with leukocyte telomere length (LTL) (r = -0.483, P = 0.048), and the association remained significant after adjustment for age (r = -0.479, P = 0.041). Similar results were observed after exclusion of patients with eGFR > = 60 ml/min/1.73m 2 . In patients with eGFR < 60 ml/min/1.73m 2 , the association remained significant after adjusting for age, sex, BMI, diabetes mellitus and smoking status (r = -1.429, P = 0.011). These results show that telomere length associates with interstitial inflammation in hypertensive patients with no apparent decrease in eGFR. Conclusions: Hypertensive participants have shorter LTL than non-hypertensive participants, and within the hypertensive group, participants with shorter telomeres are more likely to have CKD. Telomere length may provide suitable indication to help target hypertensive patients at increased risk of developing CKD.

Objective: To examine the effects of experimental reduction in the expression of circGRB10 in human kidney cells and identify its potential regulatory targets in human kidney cells. Design and method: Through use of small interfering RNA (siRNA), we knocked-down circGRB10 in human kidney cells (HEK293) and investigated potential downstream targets using RNA sequencing. Small RNA sequencing and total RNA sequencing were performed to investigate differentially expressed microRNAs (miRNAs) and mRNAs, respectively. Statistical significance was set as FDR < 0.01. Pathway analysis was performed using Kyoto Encyclopedia for Genes and Genomes (KEGG) on the Database Annotation Visualization Integrated Discovery (DAVID). Finally, we investigated enriched gene ontology terms. Results: We identified 1,483 genes showing differential expression between cells where circGRB10 was knocked down and the control cells. No miRNAs were differentially expressed between circGRB10 cells and the control. The differentially expressed genes mapped onto 66 KEGG pathways including those of relevance to protein and RNA binding. Conclusion: These results indicate that circGRB10 most likely operates as a direct regulator of mRNA expression in the kidney rather than through modulation of microRNAs.

Objective: Transcriptome-wide association study (TWAS) leverages information from reference panels of human tissues to predict the genetically determined component of expression in much larger datasets for thousands of genes and explore their association with a phenotype/disease of interest in thousands of individuals. Using TWAS, we sought to 1) define contributors to blood pressure (BP) regulation across a panel of 49 human cell-types/tissues 2) detect new kidney genes associated with BP in human kidney samples and 3) identify new pharmacological opportunities for hypertension through TWAS-informed drug repurposing. Design and method: We performed TWAS using PrediXcan across 49 human tissues/cell-types from The Genotype-Tissue Expression project and ranked the overall relevance of tissue of BP according to three independent metrics defining the strength of uncovered tissue-trait associations. We then trained predictors of gene expression from 478 samples from the Human Kidney Tissue Resource by applying a new predictive model which utilises epigenetic and three-dimensional genomic information to prioritise essential genetic variants. The subsequent BP kidney TWAS was conducted in up to ∼750k individuals from UK Biobank and International Consortium for Blood Pressure. Finally, we combined the input from BP kidney TWAS with Connectivity Map to identify drugs capable of inducing or reversing the identified gene expression signatures. Results: We found that fibroblasts, kidney cortex, lymphocytes, brain, thyroid, adrenal glands, aorta and spleen showed the overall strongest associations with BP across 49 human tissues/cell-types. Through TWAS of systolic blood pressure/diastolic blood pressure/pulse pressure we identified 997 kidney genes associated with at least one BP trait. Of these, 562 (56%) have not been reported before. Our computational druggability analysis re-affirmed the potential of several known BP inducers (glucocorticoid receptor agonists, calcineurin inhibitors) to increase BP and uncovered adenylate cyclase system activators to reverse the BP-related changes in the transcriptome. We also found purinergic receptor as a potential gene target for drug repurposing in hypertension. Finally, we found that use of topoisomerase inhibitors, cyclin-dependent kinase inhibitors, inosine monophosphate dehydrogenase inhibitors, and histone deacetylase inhibitors may be associated with hypotension. Conclusion: Our data provided evidence for the role of the kidney as an organ of the key relevance to hypertension and highlighted the importance of immune system in BP regulation. We also identified 997 kidney genes robustly associated with BP. Through TWAS-informed drug repurposing analysis, we uncovered novel targets for drug development in hypertension and highlighted BP drop as a potential side effect of several existing therapeutics.

Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p < 5 × 10-8), of which two have not been previously reported in any ancestry group. We integrated fine-mapped loci with epigenomic and transcriptomic resources to highlight potential effector genes relevant to kidney physiology and disease, and reveal key regulatory elements and pathways involved in renal function and development. We demonstrate the varying but increased predictive power offered by a multi-ancestry polygenic score for eGFR and highlight the importance of population diversity in GWASs and multi-omics resources to enhance opportunities for clinical translation for all.

Objective: Hypertension affects 35% of the global adult population and is the leading preventable risk factor for premature death globally. The kidney is the key organ of blood pressure regulation in the body. Here, we compare the gene expression profile from renal cells shed naturally into the urine and kidney tissue to determine if urine can provide a non-invasive readout of kidney gene expression and whether hypertension-associated genes can be quantified in urine. Design and Method: Urinary cell and kidney tissue samples were collected from 33 human participants and were both profiled by poly-A RNA-sequencing, generating an average of 30 million paired reads per sample. These were quantified using the standard Genotype Tissue Expression (GTEx) project pipeline and were compared against 43 different human tissues and other bodily fluids using transcriptomic correlation. RNA-sequencing quality metrics were calculated by RNA-SeQC software. Gene set overrepresentation analysis for Gene Ontology (GO) terms and Kyoto Encyclopaedia of Genes and Genomes (KEGG) employed Fishers exact test. Enriched and enhanced kidney genes were collected from the Human Protein Atlas (HPA). Results: Our RNA-sequencing metric analysis revealed that urinary cells can generate robust data of comparable or superior quality to that of saliva at similar read coverage. The top one hundred most highly expressed urinary cell genes show an enrichment for biological themes shared with the renal transcriptome, including immunity (P = 1.2x10–7), glucose metabolism (P = 1.3x10–5) and renal mineral reabsorption (P = 9.8x10–4). In an analysis all protein-coding genes across 43 human tissues/cell-types, urinary cells showed the highest level of transcriptomic correlation with kidney cortex (r2 = 0.65) and kidney medulla (r2 = 0.64). This correlation between urinary cells and kidney tissue was particularly strong (r2 = 0.72) in an analysis restricted to highly specific kidney genes (including uromodulin and the Na-K-Cl cotransporter NKCC2 [loop diuretic target]). 98% (176 out of 179) of kidney genes with a known causal association to blood pressure were expressed in urinary cells. Their urinary expression demonstrated strong correlation with their abundance in kidney cortex (r2 = 0.68) and medulla (r2 = 0.64). Conclusions: Standard poly-A RNA-sequencing of cells harvested from urinary sediments produces robust gene expression profiles. These profiles provide a non-invasive insight into transcriptome of the kidney and permit measuring expression of kidney genes of relevance to BP regulation and hypertension.

Objective: We systematically characterised the expression of all renin-angiotensin system (RAS) genes in the human kidney and searched in silico for new pharmacological therapeutic opportunities to modify RAS. Design and method: We compiled data from open access resources to characterise all components of the RAS pathway. We used transcriptomic profiles of 73 human kidney tissues from the Genotype-Tissue Expression Project, integrated genome-wide DNA genotypes and RNA-sequencing-derived transcriptome profiles of 478 human kidneys from Human Kidney Tissue Resource and, kidney tissue proteomics from 72 samples recruited by Clinical Proteomic Tumour Analysis Consortium. Additionally, we used an independent single-cell RNA sequencing data and gene expression datasets curated from the Kidney Precision Medicine Project (KPMP) and Enrichr (web-based enrichment analysis tool). Lastly, we integrated the Connectivity Map and Drug Gene Interaction Database to identify drug repurposing opportunities for treatment of hypertension targeting the RAS genes. Results: We identified 37 genes encoding components of the RAS pathway with measurable expression in human kidney tissue. 15% of these gene-pairs demonstrated a positive (r>0.5) correlation in kidney expression most consistent with a functionally integrated network of interacting molecules. Angiotensinogen (AGT), the key component of the pathway - showed the highest level of mRNA expression in the liver, and we demonstrated that its hepatic mRNA expression correlates most strongly with its mRNA expression in the kidney (r = 0.71, P = 2.60e-06). Expression levels of mRNA for 92% of RAS genes correlated positively with their protein abundance in the kidney, where renin had the strongest positive correlation (r = 0.64, P<0.01). Enrichr and KPMP revealed that RAS gene expression was enriched in mesangial and epithelial cell types. Existing genetic evidence for correlation between glutamyl aminopeptidase (ENPEP) and systolic blood pressure might relate to its capacity to generate angiotensin III acting on dilator angiotensin II type 2 receptors. This raises potential repurposing opportunities for ENPEP inhibitors like firibastat and tosedostat for the treatment of hypertension. Conclusions: Collectively, this study confirmed synchronized expression of RAS genes in the kidney at both mRNA and protein levels and identified new therapeutic opportunities for treatment of hypertension, through drug repurposing.

The majority of genes have a genetic component to their expression. Elastic nets have been shown effective at predicting tissue-specific, individual-level gene expression from genotype data. We apply principal component analysis (PCA), linkage disequilibrium pruning, or the combination of the two to reduce, or generate, a lower-dimensional representation of the genetic variants used as inputs to the elastic net models for the prediction of gene expression. Our results show that, in general, elastic nets attain their best performance when all genetic variants are included as inputs; however, a relatively low number of principal components can effectively summarize the majority of genetic variation while reducing the overall computation time. Specifically, 100 principal components reduce the computational time of the models by over 80% with only an 8% loss in R 2 . Finally, linkage disequilibrium pruning does not effectively reduce the genetic variants for predicting gene expression. As predictive models are commonly made for over 27,000 genes for more than 50 tissues, PCA may provide an effective method for reducing the computational burden of gene expression analysis.