Effect of large weight reductions on measured and estimated kidney function

BACKGROUND: When patients experience large weight loss, muscle mass may be affected followed by changes in plasma creatinine (pCr). The MDRD and CKD-EPI equations for estimated GFR (eGFR) include pCr. We hypothesised that a large weight loss reduces muscle mass and pCr causing increase in eGFR (creatinine-based equations), whereas measured GFR (mGFR) and cystatin C-based eGFR would be unaffected if adjusted for body surface area. METHODS: Prospective, intervention study including 19 patients. All attended a baseline visit before gastric bypass surgery followed by a visit six months post-surgery. mGFR was assessed during four hours plasma (51)Cr-EDTA clearance. GFR was estimated by four equations (MDRD, CKD-EPI-pCr, CKD-EPI-cysC and CKD-EPI-pCr-cysC). DXA-scans were performed at baseline and six months post-surgery to measure changes in lean limb mass, as a surrogate for muscle mass. RESULTS: Patients were (mean ± SD) 40.0 ± 9.3 years, 14 (74%) were female and 5 (26%) had type 2 diabetes, baseline weight was 128 ± 19 kg, body mass index 41 ± 6 kg/m2 and absolute mGFR 122 ± 24 ml/min. Six months post-surgery weight loss was 27 (95% CI: 23; 30) kg, mGFR decreased by 9 (−17; −2) from 122 ± 24 to 113 ± 21 ml/min (p = 0.024), but corrected for current body surface area (BSA) mGFR was unchanged by 2 (−5; 9) ml/min/1.73 m(2) (p = 0.52). CKD-EPI-pCr increased by 12 (6; 17) and MDRD by 13 (8; 18) (p < 0.001 for both), while CKD-EPI-cysC was unchanged by 2 (−8; 4) ml/min/1.73 m(2) (p = 0.51). Lean limb mass was reduced by 3.5 (−4.4;−2.6; p < 0.001) kg and change in lean limb mass correlated with change in plasma creatinine (R (2) = 0.28, p = 0.032). CONCLUSIONS: Major weight reductions are associated with a reduction in absolute mGFR, which may reflect resolution of glomerular hyperfiltration, while mGFR adjusted for body surface area was unchanged. Estimates of GFR based on creatinine overestimate renal function likely due to changes in muscle mass, whereas cystatin C based estimates are unaffected. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02138565. Date of registration: March 24, 2014

Plasma proteome analysis of patients with type 1 diabetes with diabetic nephropathy

<p>Abstract</p> <p>Background</p> <p>As part of a clinical proteomics program focused on diabetes and its complications we are looking for new and better protein biomarkers for diabetic nephropathy. The search for new and better biomarkers for diabetic nephropathy has, with a few exceptions, previously focused on either hypothesis-driven studies or urinary based investigations. To date only two studies have investigated the proteome of blood in search for new biomarkers, and these studies were conducted in sera from patients with type 2 diabetes. This is the first reported in depth proteomic study where plasma from type 1 diabetic patients was investigated with the goal of finding improved candidate biomarkers to predict diabetic nephropathy. In order to reach lower concentration proteins in plasma a pre-fractionation step, either hexapeptide bead-based libraries or anion exchange chromatography, was performed prior to surface enhanced laser desorption/ionization time-of-flight mass spectrometry analysis.</p> <p>Results</p> <p>Proteomic analysis of plasma from a cross-sectional cohort of 123 type 1 diabetic patients previously diagnosed as normoalbuminuric, microalbuminuric or macroalbuminuric, gave rise to 290 peaks clusters of which 16 were selected as the most promising biomarker candidates based on statistical performance, including independent component analysis. Four of the peaks that were discovered have been identified as transthyretin, apolipoprotein A1, apolipoprotein C1 and cystatin C. Several yet unidentified proteins discovered by this novel approach appear to have more potential as biomarkers for diabetic nephropathy.</p> <p>Conclusion</p> <p>These results demonstrate the capacity of proteomic analysis of plasma, by confirming the presence of known biomarkers as well as revealing new biomarkers for diabetic nephropathy in plasma in type 1 diabetic patients.</p

Using microarray-based subtyping methods for breast cancer in the era of high-throughput RNA sequencing

Breast cancer is a highly heterogeneous disease that can be classified into multiple subtypes based on the tumor transcriptome. Most of the subtyping schemes used in clinics today are derived from analyses of microarray data from thousands of different tumors together with clinical data for the patients from which the tumors were isolated. However, RNA sequencing (RNA‐Seq) is gradually replacing microarrays as the preferred transcriptomics platform, and although transcript abundances measured by the two different technologies are largely compatible, subtyping methods developed for probe‐based microarray data are incompatible with RNA‐Seq as input data. Here, we present an RNA‐Seq data processing pipeline, which relies on the mapping of sequencing reads to the probe set target sequences instead of the human reference genome, thereby enabling probe‐based subtyping of breast cancer tumor tissue using sequencing‐based transcriptomics. By analyzing 66 breast cancer tumors for which gene expression was measured using both microarrays and RNA‐Seq, we show that RNA‐Seq data can be directly compared to microarray data using our pipeline. Additionally, we demonstrate that the established subtyping method CITBCMST (Guedj et al., ), which relies on a 375 probe set‐signature to classify samples into the six subtypes basL, lumA, lumB, lumC, mApo, and normL, can be applied without further modifications. This pipeline enables a seamless transition to sequencing‐based transcriptomics for future clinical purposes

Efficacy and Safety of Dapagliflozin in Patients with Chronic Kidney Disease across the Spectrum of Frailty

BACKGROUND: A sizeable proportion of patients with chronic kidney disease (CKD) are reported to be frail. Here we examined the safety and efficacy of dapagliflozin in patients with CKD by frailty level. METHODS: Adults with CKD, with/without type 2 diabetes, with estimated glomerular filtration rate (eGFR) 25-75 mL/min/1.73m 2 and urinary albumin-to-creatinine ratio 200-5000 mg/g were randomized to dapagliflozin (10 mg/day) or placebo. The primary endpoint was composite of sustained ≥50% eGFR decline, end-stage kidney disease (ESKD) or death from kidney or cardiovascular (CV) causes. RESULTS: Frailty index (FI), assessed by Rockwood cumulative deficit approach, was calculable in 4303/4304 (99.9%) patients: 1162 (27.0%) in not-to-mildly frail(FI≤0.210), 1642 (38.2%) in moderately frail(FI 0.211-0.310), and 1499 (34.8%) in severely frail categories (FI>0.311). Dapagliflozin reduced the risk of the primary composite endpoint across all FI categories (hazard ratios [95% CI]: 0.50 [0.33-0.76], 0.62 [0.45-0.85], and 0.64 [0.49-0.83], respectively (P-interaction =0.67). Results were similar for secondary outcomes including kidney composite outcome (sustained ≥50% eGFR decline, ESKD or death from kidney cause; P-interaction=0.44), CV endpoint (heart failure hospitalization or CV death; P-interaction=0.63), and all-cause mortality (P-interaction p=0.42). Results were consistent when using FI as a continuous variable. Occurrence of serious adverse events was numerically lower in patients receiving dapagliflozin vs. placebo in all FI categories (16.9% vs. 20.1%, 26.3% vs. 30.7%, and 42.9% vs 47.8%, in not-to-mildly, moderately and severely frail categories, respectively). CONCLUSIONS: The relative benefit of dapagliflozin for all outcomes was consistent across all frailty categories, with no difference in associated safety