Diseases of the kidney are difficult to diagnose and treat. This review summarises the definition, cause, epidemiology and treatment of some of these diseases including chronic kidney disease, diabetic nephropathy, acute kidney injury, kidney cancer, kidney transplantation and polycystic kidney diseases. Numerous studies have adopted a metabolomics approach to uncover new small molecule biomarkers of kidney diseases to improve specificity and sensitivity of diagnosis and to uncover biochemical mechanisms that may elucidate the cause and progression of these diseases. This work includes a description of mass spectrometry-based metabolomics approaches, including some of the currently available tools, and emphasises findings from metabolomics studies of kidney diseases. We have included a varied selection of studies (disease, model, sample number, analytical platform) and focused on metabolites which were commonly reported as discriminating features between kidney disease and a control. These metabolites are likely to be robust indicators of kidney disease processes, and therefore potential biomarkers, warranting further investigation.

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SummaryBackgroundExcess weight is associated with poor health and increased health-care costs. However, a detailed understanding of the effects of excess weight on total hospital costs and costs for different health conditions is needed.MethodsWomen in England aged 50–64 years were recruited into the prospective Million Women Study cohort in 1996–2001 through 60 NHS breast cancer screening centres. Participants were followed up and annual hospital costs and admission rates were estimated for April 1, 2006, to March 31, 2011, in relation to body-mass index (BMI) at recruitment, overall and for categories of health conditions defined by the International Classification of Diseases 10th revision chapter of the primary diagnosis at admission. Associations of BMI with hospital costs were projected to the 2013 population of women aged 55–79 years in England.Findings1 093 866 women who provided information on height and weight, had a BMI of at least 18·5 kg/m2, and had no previous cancer at recruitment, were followed up for an average of 4·9 years from April 1, 2006 (12·3 years from recruitment), during which time 1·84 million hospital admissions were recorded. Annual hospital costs were lowest for women with a BMI of 20·0 kg/m2 to less than 22·5 kg/m2 (£567 per woman per year, 99% CI 556–577). Every 2 kg/m2 increase in BMI above 20 kg/m2 was associated with a 7·4% (7·1–7·6) increase in annual hospital costs. Excess weight was associated with increased costs for all diagnostic categories, except respiratory conditions and fractures. £662 million (14·6%) of the estimated £4·5 billion of total annual hospital costs among all women aged 55–79 years in England was attributed to excess weight (BMI ≥25 kg/m2), of which £517 million (78%) arose from hospital admissions with procedures. £258 million (39%) of the costs attributed to excess weight were due to musculoskeletal admissions, mainly for knee replacement surgeries.InterpretationExcess body weight is associated with increased hospital costs for middle-aged and older women in England across a broad range of conditions, especially knee replacement surgery and diabetes. These results provide reliable up-to-date estimates of the health-care costs of excess weight and emphasise the need for investment to tackle this public health issue.FundingCancer Research UK; Medical Research Council; National Institute for Health Research.

Birth weight and height are correlated and likely to be markers of some aspect of growth that affects cancer risk in adulthood. However, birth weight adds little, if any, additional information to adult height as a predictor of cancer incidence in women.

Methods: Spot urine samples were collected from four male Lewis control and five male Lewis polycystic kidney rats aged 5 weeks, before kidney function was significantly impaired. Metabolites were extracted from urine and analysed using gas chromatography-mass spectrometry. Principal component analysis was used to determine key metabolites contributing to the variance observed between sample groups. Results:With the development of a metabolomics method to analyse Lewis and Lewis polycystic kidney rat urine, 2-ketoglutaric acid, allantoin, uric acid and hippuric acid were identified as potential biomarkers of cystic disease in the rat model. Conclusion:The findings of this study demonstrate the potential of metabolomics to further investigate kidney disease.Keywords: biomarker; gas chromatography; metabolite; polycystic kidney disease; urineThe advent of metabolomics, also termed metabolic profiling, has been in light of not only recent technological advancements in the separation and identification of low-molecular-weight molecules, but also in the software and hardware for processing the resultant large quantities of data.

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Polycystic kidney disease (PKD) encompasses a spectrum of inherited disorders that lead to end-stage renal disease (ESRD). There is no cure for PKD and current treatment options are limited to renal replacement therapy and transplantation. A better understanding of the pathobiology of PKD is needed for the development of new, less invasive treatments.The Lewis Polycystic Kidney (LPK) rat phenotype has been characterized and classified as a model of nephronophthisis (NPHP9, caused by mutation of the Nek8 gene) for which polycystic kidneys are one of the main pathologic features. The aim of this study was to use a GC-MS-based untargeted metabolomics approach to determine key biochemical changes in kidney and liver tissue of the LPK rat. Tissues from 16-week old LPK (n = 10) and Lewis age-and sex-matched control animals (n = 11) were used. Principal component analysis (PCA) distinguished signal corrected metabolite profiles from Lewis and LPK rats for kidney (PC-1 77%) and liver (PC-1 46%) tissue. There were marked differences in the metabolite profiles of the kidney tissues with 122 deconvoluted features significantly different between the LPK and Lewis strains. The metabolite profiles were less marked between strains for liver samples with 30 features significantly different. Five biochemical pathways showed three or more significantly altered metabolites: transcription/translation, arginine and proline metabolism, alpha-linolenic and linoleic acid metabolism, the citric acid cycle, and the urea cycle. The results of this study validate and complement the current literature and are consistent with the understood pathobiology of PKD.

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