IntroductionLate-onset Alzheimer's disease (LOAD, onset age > 60 years) is the most prevalent dementia in the elderly 1 , and risk is partially driven by genetics 2 . Many of the loci responsible for this genetic risk were identified by genome-wide association studies (GWAS) [3][4][5][6][7][8] . To identify additional LOAD risk loci, the we performed the largest GWAS to date (89,769 individuals), analyzing both common and rare variants. We confirm 20 previous LOAD risk loci and identify four new genome-wide loci (IQCK, ACE, ADAM10, and ADAMTS1). Pathway analysis of these data implicates the immune system and lipid metabolism, and for the first time tau binding proteins and APP metabolism. These findings show that genetic variants affecting APP and Aβ processing are not only associated with early-onset autosomal dominant AD but also with LOAD. Analysis of AD risk genes and pathways show enrichment for rare variants (P = 1.32 x 10 -7 ) indicating that additional rare variants remain to be identified. Main TextOur previous work identified 19 genome-wide significant common variant signals in addition to APOE 9 , that influence risk for LOAD. These signals, combined with 'subthreshold' common variant associations, account for ~31% of the genetic variance of LOAD 2 , leaving the majority of genetic risk uncharacterized 10 . To search for additional signals, we conducted a GWAS metaanalysis of non-Hispanic Whites (NHW) using a larger sample (17 new, 46 total datasets) from our group, the International Genomics of Alzheimer's Project (IGAP) (composed of four AD consortia: ADGC, CHARGE, EADI, and GERAD). This sample increases our previous discovery sample (Stage 1) by 29% for cases and 13% for controls (N=21,982 cases; 41,944 controls) ( Supplementary Table 1 and 2, and Supplementary Note). To sample both common and rare variants (minor allele frequency MAF ≥ 0.01, and MAF < 0.01, respectively), we imputed the discovery datasets using a 1000 Genomes reference panel consisting of . CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a 11 36,648,992 single-nucleotide variants, 1,380,736 insertions/deletions, and 13,805 structural variants. After quality control, 9,456,058 common variants and 2,024,574 rare variants were selected for analysis (a 63% increase from our previous common variant analysis in 2013).Genotype dosages were analyzed within each dataset, and then combined with meta-analysis ( Supplementary Figures 1 and 2 and Supplementary Table 3). The Stage 1 discovery metaanalysis was first followed by Stage 2 using the I-select chip we previously developed in Lambert et al (including 11,632 variants, N=18,845) and finally stage 3A (N=6,998). The final sample was 33,692 clinical AD cases and 56,077 controls.Meta-analysis of Stages 1 and 2 produced 21 associations with P ≤ 5x10 -8 (Table 1 and Figure 1). Of these, 18 were previously reported as genome-wide significant and three of them are signals not initially described in Lambert et al: the rare R47H TREM2 coding va...

This Clinical Practice Guideline document is based upon systematic literature searches last conducted in June 2011, supplemented with additional evidence through November 2012. It is designed to provide information and assist decision making. It is not intended to define a standard of care, and should not be construed as one, nor should it be interpreted as prescribing an exclusive course of management. Variations in practice will inevitably and appropriately occur when clinicians take into account the needs of individual patients, available resources, and limitations unique to an institution or type of practice. Every health-care professional making use of these recommendations is responsible for evaluating the appropriateness of applying them in any particular clinical situation. The recommendations for research contained within this document are general and do not imply a specific protocol. SECTION II: DISCLOSUREKidney Disease: Improving Global Outcomes (KDIGO) makes every effort to avoid any actual or reasonably perceived conflicts of interest that may arise as a result of an outside relationship or a personal, professional, or business interest of a member of the Work Group. All members of the Work Group are required to complete, sign, and submit a disclosure and attestation form showing all such relationships that might be perceived as or are actual conflicts of interest. This document is updated annually and information is adjusted accordingly. All reported information is published in its entirety at the end of this document in the Work Group members' Biographic and Disclosure Information section, and is kept on file at the National Kidney Foundation (NKF), former Managing Agent for KDIGO.http://www.kidney-international.org

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Acute and chronic kidney diseases affect pharmacokinetics and pharmacodynamics. There has been substantial progress in the past 20 years in the use of glomerular filtration rate (GFR) estimating equations. In principle, use of a single equation for each filtration marker (creatinine, cystatin C, or the combination) for detection, evaluation, and management of kidney disease and for drug development and dosing would facilitate clinical practice. We review the principles for assessment of GFR, provide historical perspectives and updates regarding use of GFR estimating equations, including assay methods for filtration markers, performance of estimating equations, and recommendations by clinical practice guideline groups and regulatory agencies. We conclude that it is time to change from rigid adherence to the use of the Cockcroft‐Gault equation for use in drug development and drug dosing to the more accurate and more widely used Modification of Diet in Renal Disease (MDRD) study and the Chronic Kidney Disease Epidemiology Collaboration (CKD‐EPI) equations.

Considerable variation in grading systems used to rate the strength of guideline recommendations and the quality of the supporting evidence in Nephrology highlights the need for a uniform, internationally accepted, rigorous system. In 2004, Kidney Disease: Improving Global Outcomes (KDIGO) commissioned a methods expert group to recommend an approach for grading in future nephrology guidelines. This position statement by KDIGO recommends adopting the Grades of Recommendation Assessment, Development, and Evaluation (GRADE) approach for the grading of evidence and guidelines on interventions. The GRADE approach appraises systematic reviews of the benefits and harms of an intervention to determine its net health benefit. The system considers the design, quality, and quantity of studies as well as the consistency and directness of findings when grading the quality of evidence. The strength of the recommendation builds on the quality of the evidence and additional considerations including costs. Adaptations of the GRADE approach are presented to address some issues pertinent to the field of nephrology, including (1) the need to extrapolate from studies performed predominantly in patients without kidney disease, and (2) the need to use qualitative summaries of effects when it is not feasible to quantitatively summarize them. Further refinement of the system will be required for grading of evidence on questions other than those related to intervention effects, such as diagnostic accuracy and prognosis.