Bucket Fuser: Statistical Signal Extraction for 1D 1H NMR Metabolomic Data

Untargeted metabolomics is a promising tool for identifying novel disease biomarkers and unraveling underlying pathomechanisms. Nuclear magnetic resonance (NMR) spectroscopy is particularly suited for large-scale untargeted metabolomics studies due to its high reproducibility and cost effectiveness. Here, one-dimensional (1D) 1H NMR experiments offer good sensitivity at reasonable measurement times. Their subsequent data analysis requires sophisticated data preprocessing steps, including the extraction of NMR features corresponding to specific metabolites. We developed a novel 1D NMR feature extraction procedure, called Bucket Fuser (BF), which is based on a regularized regression framework with fused group LASSO terms. The performance of the BF procedure was demonstrated using three independent NMR datasets and was benchmarked against existing state-of-the-art NMR feature extraction methods. BF dynamically constructs NMR metabolite features, the widths of which can be adjusted via a regularization parameter. BF consistently improved metabolite signal extraction, as demonstrated by our correlation analyses with absolutely quantified metabolites. It also yielded a higher proportion of statistically significant metabolite features in our differential metabolite analyses. The BF algorithm is computationally efficient and it can deal with small sample sizes. In summary, the Bucket Fuser algorithm, which is available as a supplementary python code, facilitates the fast and dynamic extraction of 1D NMR signals for the improved detection of metabolic biomarker

Genetic studies of paired metabolomes reveal enzymatic and transport processes at the interface of plasma and urine.

The kidneys operate at the interface of plasma and urine by clearing molecular waste products while retaining valuable solutes. Genetic studies of paired plasma and urine metabolomes may identify underlying processes. We conducted genome-wide studies of 1,916 plasma and urine metabolites and detected 1,299 significant associations. Associations with 40% of implicated metabolites would have been missed by studying plasma alone. We detected urine-specific findings that provide information about metabolite reabsorption in the kidney, such as aquaporin (AQP)-7-mediated glycerol transport, and different metabolomic footprints of kidney-expressed proteins in plasma and urine that are consistent with their localization and function, including the transporters NaDC3 (SLC13A3) and ASBT (SLC10A2). Shared genetic determinants of 7,073 metabolite-disease combinations represent a resource to better understand metabolic diseases and revealed connections of dipeptidase 1 with circulating digestive enzymes and with hypertension. Extending genetic studies of the metabolome beyond plasma yields unique insights into processes at the interface of body compartments

Blood pressure control in chronic kidney disease: A cross-sectional analysis from the German Chronic Kidney Disease (GCKD) study

We assessed the prevalence, awareness, treatment and control of hypertension in patients with moderate chronic kidney disease (CKD) under nephrological care in Germany. In the German Chronic Kidney Disease (GCKD) study, 5217 patients under nephrology specialist care were enrolled from 2010 to 2012 in a prospective observational cohort study. Inclusion criteria were an estimated glomerular filtration rate (eGFR) of 30 +/- 60 mL/min/1.73 m 2 or overt proteinuria in the presence of an eGFR> 60 mL/min/1.73 m 2. Office blood pressure was measured by trained study personnel in a standardized way and hypertension awareness and medication were assessed during standardized interviews. Blood pressure was considered as controlled if systolic 90%. However, only 2456 (49.3%) of the hypertensive patients had controlled blood pressure. About half (51.0%) of the patients with uncontrolled blood pressure met criteria for resistant hypertension. Factors associated with better odds for controlled blood pressure in multivariate analyses included younger age, female sex, higher income, low or absent proteinuria, and use of certain classes of antihypertensive medication. We conclude that blood pressure control of CKD patients remains challenging even in the setting of nephrology specialist care, despite high rates of awareness and medication use

Heart Failure in a Cohort of Patients with Chronic Kidney Disease: The GCKD Study

Background and Aims Chronic kidney disease (CKD) is a risk factor for development and progression of heart failure (HF). CKD and HF share common risk factors, but few data exist on the prevalence, signs and symptoms as well as correlates of HF in populations with CKD of moderate severity. We therefore aimed to examine the prevalence and correlates of HF in the German Chronic Kidney Disease (GCKD) study, a large observational prospective study. Methods and Results We analyzed data from 5,015 GCKD patients aged 18-74 years with an estimated glomerular filtration rate (eGFR) of = 60 and overt proteinuria (>500 mg/d). We evaluated a definition of HF based on the Gothenburg score, a clinical HF score used in epidemiological studies (Gothenburg HF), and self-reported HF. Factors associated with HF were identified using multivariable adjusted logistic regression. The prevalence of Gothenburg HF was 43% (ranging from 24% in those with eGFR >90 to 59% in those with eGFR<30 ml/min/1.73m2). The corresponding estimate for self-reported HF was 18% (range 5%-24%). Lower eGFR was significantly and independently associated with the Gothenburg definition of HF (p-trend <0.001). Additional significantly associated correlates included older age, female gender, higher BMI, hypertension, diabetes mellitus, valvular heart disease, anemia, sleep apnea, and lower educational status. Conclusions The burden of self-reported and Gothenburg HF among patients with CKD is high. The proportion of patients who meet the criteria for Gothenburg HF in a European cohort of patients with moderate CKD is more than twice as high as the prevalence of self-reported HF. However, because of the shared signs, symptoms and medications of HF and CKD, the Gothenburg score cannot be used to reliably define HF in CKD patients. Our results emphasize the need for early screening for HF in patients with CKD

Apolipoprotein A-IV concentrations and cancer in a large cohort of chronic kidney disease patients: results from the GCKD study

Abstract Background Chronic kidney disease (CKD) is highly connected to inflammation and oxidative stress. Both favour the development of cancer in CKD patients. Serum apolipoprotein A-IV (apoA-IV) concentrations are influenced by kidney function and are an early marker of kidney impairment. Besides others, it has antioxidant and anti-inflammatory properties. Proteomic studies and small case–control studies identified low apoA-IV as a biomarker for various forms of cancer; however, prospective studies are lacking. We therefore investigated whether serum apoA-IV is associated with cancer in the German Chronic Kidney Disease (GCKD) study. Methods These analyses include 5039 Caucasian patients from the prospective GCKD cohort study followed for 6.5 years. Main inclusion criteria were an eGFR of 30–60 mL/min/1.73m2 or an eGFR > 60 mL/min/1.73m2 in the presence of overt proteinuria. Results Mean apoA-IV concentrations of the entire cohort were 28.9 ± 9.8 mg/dL (median 27.6 mg/dL). 615 patients had a history of cancer before the enrolment into the study. ApoA-IV concentrations above the median were associated with a lower odds for a history of cancer (OR = 0.79, p = 0.02 when adjusted age, sex, smoking, diabetes, BMI, albuminuria, statin intake, and eGFRcreatinine). During follow-up 368 patients developed an incident cancer event and those with apoA-IV above the median had a lower risk (HR = 0.72, 95%CI 0.57–0.90, P = 0.004). Finally, 62 patients died from such an incident cancer event and each 10 mg/dL higher apoA-IV concentrations were associated with a lower risk for fatal cancer (HR = 0.62, 95%CI 0.44–0.88, P = 0.007). Conclusions Our data indicate an association of high apoA-IV concentrations with reduced frequencies of a history of cancer as well as incident fatal and non-fatal cancer events in a large cohort of patients with CKD. Graphical Abstrac

Uromodulin and its association with urinary metabolites: the German Chronic Kidney Disease Study

BACKGROUND: The progression of chronic kidney disease (CKD), a global public health burden, is accompanied by a declining number of functional nephrons. Estimation of remaining nephron mass may improve assessment of CKD progression. Uromodulin has been suggested as a marker of tubular mass. We aimed to identify metabolites associated with uromodulin concentrations in urine and serum to characterize pathophysiologic alterations of metabolic pathways to generate new hypotheses regarding CKD pathophysiology. METHODS: We measured urinary and serum uromodulin levels (uUMOD, sUMOD) and 607 urinary metabolites and performed cross-sectional analyses within the German Chronic Kidney Disease study (N = 4628), a prospective observational study. Urinary metabolites significantly associated with urine and serum uromodulin were used to build weighted metabolite scores for urine (uMS) and serum uromodulin (sMS) and evaluated for time to adverse kidney events over 6.5 years. RESULTS: Metabolites cross-sectionally associated with uromodulin included amino acids of the tryptophan metabolism, lipids, and nucleotides. Higher levels of the sMS (HR = 0.73 [95% CI 0.64; 0.82], p = 7.45e-07) and sUMOD (HR = 0.74 [95% CI 0.63; 0.87], p = 2.32e-04) were associated with a lower risk of adverse kidney events over time, whereas uUMOD and uMS showed the same direction of association but were not significant. CONCLUSIONS: We identified urinary metabolites associated with urinary and serum uromodulin. sUMOD and the sMS were associated with lower risk of adverse kidney events among CKD patients. Higher levels of sUMOD and sMS may reflect a higher number of functional nephrons and therefore a reduced risk of adverse kidney outcomes