Development of Risk Prediction Equations for Incident Chronic Kidney Disease

IMPORTANCE Early identification of individuals at elevated risk of developing chronic kidney disease (CKD) could improve clinical care through enhanced surveillance and better management of underlying health conditions.OBJECTIVE To develop assessment tools to identify individuals at increased risk of CKD, defined by reduced estimated glomerular filtration rate (eGFR).DESIGN, SETTING, AND PARTICIPANTS Individual-level data analysis of 34 multinational cohorts from the CKD Prognosis Consortium including 5 222 711 individuals from 28 countries. Data were collected from April 1970 through January 2017. A 2-stage analysis was performed, with each study first analyzed individually and summarized overall using a weighted average. Because clinical variables were often differentially available by diabetes status, models were developed separately for participants with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external cohorts (n = 2 253 540).EXPOSURES Demographic and clinical factors.MAIN OUTCOMES AND MEASURES Incident eGFR of less than 60 mL/min/1.73 m(2).RESULTS Among 4 441 084 participants without diabetes (mean age, 54 years, 38% women), 660 856 incident cases (14.9%) of reduced eGFR occurred during a mean follow-up of 4.2 years. Of 781 627 participants with diabetes (mean age, 62 years, 13% women), 313 646 incident cases (40%) occurred during a mean follow-up of 3.9 years. Equations for the 5-year risk of reduced eGFR included age, sex, race/ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, body mass index, and albuminuria concentration. For participants with diabetes, the models also included diabetes medications, hemoglobin A(1c), and the interaction between the 2. The risk equations had a median C statistic for the 5-year predicted probability of 0.845 (interquartile range [IQR], 0.789-0.890) in the cohorts without diabetes and 0.801 (IQR, 0.750-0.819) in the cohorts with diabetes. Calibration analysis showed that 9 of 13 study populations (69%) had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25.CONCLUSIONS AND RELEVANCE Equations for predicting risk of incident chronic kidney disease developed from more than 5 million individuals from 34 multinational cohorts demonstrated high discrimination and variable calibration in diverse populations. Further study is needed to determine whether use of these equations to identify individuals at risk of developing chronic kidney disease will improve clinical care and patient outcomes.</p

Development of Risk Prediction Equations for Incident Chronic Kidney Disease

IMPORTANCE ‐ Early identification of individuals at elevated risk of developing chronic kidney disease  could improve clinical care through enhanced surveillance and better management of underlying health  conditions.  OBJECTIVE – To develop assessment tools to identify individuals at increased risk of chronic kidney  disease, defined by reduced estimated glomerular filtration rate (eGFR).  DESIGN, SETTING, AND PARTICIPANTS – Individual level data analysis of 34 multinational cohorts from  the CKD Prognosis Consortium including 5,222,711 individuals from 28 countries. Data were collected  from April, 1970 through January, 2017. A two‐stage analysis was performed, with each study first  analyzed individually and summarized overall using a weighted average. Since clinical variables were  often differentially available by diabetes status, models were developed separately within participants  with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external  cohorts (N=2,253,540). EXPOSURE Demographic and clinical factors.  MAIN OUTCOMES AND MEASURES – Incident eGFR <60 ml/min/1.73 m2.  RESULTS – In 4,441,084 participants without diabetes (mean age, 54 years, 38% female), there were  660,856 incident cases of reduced eGFR during a mean follow‐up of 4.2 years. In 781,627 participants  with diabetes (mean age, 62 years, 13% female), there were 313,646 incident cases during a mean follow‐up of 3.9 years. Equations for the 5‐year risk of reduced eGFR included age, sex, ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, BMI, and albuminuria. For participants  with diabetes, the models also included diabetes medications, hemoglobin A1c, and the interaction  between the two. The risk equations had a median C statistic for the 5‐year predicted probability of  0.845 (25th – 75th percentile, 0.789‐0.890) in the cohorts without diabetes and 0.801 (25th – 75th percentile, 0.750‐0.819) in the cohorts with diabetes. Calibration analysis showed that 9 out of 13 (69%) study populations had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was  similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 out of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25. CONCLUSIONS AND RELEVANCE – Equations for predicting risk of incident chronic kidney disease developed in over 5 million people from 34 multinational cohorts demonstrated high discrimination and  variable calibration in diverse populations

1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function

HapMap imputed genome-wide association studies (GWAS) have revealed &gt;50 loci at which common variants with minor allele frequency &gt;5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value &lt; 5 × 10(-8) previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR &lt; 0.05) genes and 127 significantly (FDR &lt; 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples

Polycystic kidney disease with hyperinsulinemic hypoglycemia caused by a promoter mutation in PMM2

Hyperinsulinemic hypoglycemia (HI) and congenital polycystic kidney disease (PKD) are rare, genetically heterogeneous disorders. The co-occurrence of these disorders (HIPKD) in 17 children from 11 unrelated families suggested an unrecognized genetic disorder. Whole-genome linkage analysis in five informative families identified a single significant locus on chromosome 16p13.2 (logarithm of odds score 6.5). Sequencing of the coding regions of all linked genes failed to identify biallelic mutations. Instead, we found in all patients a promoter mutation (c.-167G>T) in the phosphomannomutase 2 gene (PMM2), either homozygous or in trans with PMM2 coding mutations. PMM2 encodes a key enzyme in N-glycosylation. Abnormal glycosylation has been associated with PKD, and we found that deglycosylation in cultured pancreatic β cells altered insulin secretion. Recessive coding mutations in PMM2 cause congenital disorder of glycosylation type 1a (CDG1A), a devastating multisystem disorder with prominent neurologic involvement. Yet our patients did not exhibit the typical clinical or diagnostic features of CDG1A. In vitro, the PMM2 promoter mutation associated with decreased transcriptional activity in patient kidney cells and impaired binding of the transcription factor ZNF143. In silico analysis suggested an important role of ZNF143 for the formation of a chromatin loop including PMM2. We propose that the PMM2 promoter mutation alters tissue-specific chromatin loop formation, with consequent organ-specific deficiency of PMM2 leading to the restricted phenotype of HIPKD. Our findings extend the spectrum of genetic causes for both HI and PKD and provide insights into gene regulation and PMM2 pleiotropy

Mild-to-Moderate Kidney Dysfunction and Cardiovascular Disease: Observational and Mendelian Randomization Analyses

BACKGROUND: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. METHODS: Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million personyears of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. RESULTS: There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eG FR values 105 mL.min(-1).1.73 m(-2), compared with those with eG FR between 60 and 105 mL.min(-1).1.73 m(-2). Mendelian randomization analyses for CHD showed an association among participants with eGFR 105 mL.min(-1).1.73 m(-2). Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin Alc, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. CONCLUSIONS: In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive approaches that preserve and modulate kidney function

Activation of AP-1 through reactive oxygen species by angiotensin II in rat cardiomyocytes

Cardiovascular pathogenesis induced by angiotensin II (Ang-II) is a complex process often connected to oxidative stress. In the present study we show that, 4 h after addition, Ang-II induces a four- to fivefold increase in AP-1 activity in cultured neonatal rat cardiomyocytes and that the intracellular level of reactive oxygen species (ROS) correlates with the extent of AP-1 binding activity. Ang-II stimulated ROS generation in rat cardiomyocytes in a dose- and time-dependent manner. These effects of Ang-II were suppressed by the Ang-II receptor type I (AT 1) inhibitor CV-11974 as well as by the antioxidants diphenylene iodonium (DPI) and N-acetyl-l-cysteine (NAC), but not by AT 2 antagonist PD 122319. Furthermore, Ang-II induced a two- to threefold increase in protein synthesis and cell size during 12-24 h, which could be inhibited by CV-11974 as well as by DPI and NAC. Because the rat cardiomyocytes strongly expressed gp91 phox, this suggests that ROS generated in a gp91-containing NADPH oxidase are involved in signal transduction leading to AP-1 activation. Together, these findings indicate that Ang-II elicits the activation of the redox-sensitive AP-1 via ROS through AT 1, resulting in effects on cardiomyocyte function such as hypertroph

Polycystic kidney disease with hyperinsulinemic hypoglycemia caused by a promoter mutation in phosphomannomutase 2.

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Hyperinsulinemic hypoglycemia (HI) and congenital polycystic kidney disease (PKD) are rare, genetically heterogeneous disorders. The co-occurrence of these disorders (HIPKD) in 17 children from 11 unrelated families suggested an unrecognized genetic disorder. Whole-genome linkage analysis in five informative families identified a single significant locus on chromosome 16p13.2 (logarithm of odds score 6.5). Sequencing of the coding regions of all linked genes failed to identify biallelic mutations. Instead, we found in all patients a promoter mutation (c.-167G>T) in the phosphomannomutase 2 gene (PMM2), either homozygous or in trans with PMM2 coding mutations. PMM2 encodes a key enzyme in N-glycosylation. Abnormal glycosylation has been associated with PKD, and we found that deglycosylation in cultured pancreatic β cells altered insulin secretion. Recessive coding mutations in PMM2 cause congenital disorder of glycosylation type 1a (CDG1A), a devastating multisystem disorder with prominent neurologic involvement. Yet our patients did not exhibit the typical clinical or diagnostic features of CDG1A. In vitro, the PMM2 promoter mutation associated with decreased transcriptional activity in patient kidney cells and impaired binding of the transcription factor ZNF143. In silico analysis suggested an important role of ZNF143 for the formation of a chromatin loop including PMM2 We propose that the PMM2 promoter mutation alters tissue-specific chromatin loop formation, with consequent organ-specific deficiency of PMM2 leading to the restricted phenotype of HIPKD. Our findings extend the spectrum of genetic causes for both HI and PKD and provide insights into gene regulation and PMM2 pleiotropy.This work was supported by the Medical Research Council (Grant Number 98144), the Great Ormond Street Hospital Children’s Charity, Kids Kidney Research, St Peter’s Trust for Kidney, Bladder and Prostate Research, The David and Elaine Potter Foundation and the European Union, FP7 (grant agreement 2012-305608 “European Consortium for High-Throughput Research in Rare Kidney Diseases (EURenOmics”). SEF has a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant Number: 105636/Z/14/Z). SE is a Wellcome Trust Senior Investigator