Eleven susceptibility loci for late-onset Alzheimer’s disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer’s disease cases and 37,154 controls. In stage 2,11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer’s disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer’s disease.

Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. We thank Drs. D. Stephen Snyder and Marilyn Miller from NIA who are ex-officio ADGC members. EADI. This work has been developed and supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant (Development of Innovative Strategies for a Transdisciplinary approach to ALZheimer's disease) including funding from MEL (Metropole européenne de Lille), ERDF (European Regional Development Fund) and Conseil Régional Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. The generation and management of GWAS genotype data for the Rotterdam Study (RS-I, RS-II, RS-III) was executed by the Human Genotyping Facility of the Genetic Laboratory of the

We sought to identify new susceptibility loci for Alzheimer’s disease (AD) through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer’s Disease Genetic Consortium (ADGC). First, we undertook a combined analysis of four genome-wide association datasets (Stage 1) and identified 10 novel variants with P≤1×10−5. These were tested for association in an independent sample (Stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (Stage 3). Meta-analyses of all data provide compelling evidence that ABCA7 (meta-P 4.5×10−17; including ADGC meta-P=5.0×10−21) and the MS4A gene cluster (rs610932, meta-P=1.8×10−14; including ADGC meta-P=1.2×10−16; rs670139, meta-P=1.4×10−9; including ADGC meta-P=1.1×10−10) are novel susceptibility loci for AD. Second, we observed independent evidence for association for three suggestive loci reported by the ADGC GWAS, which when combined shows genome-wide significance: CD2AP (GERAD+ P=8.0×10−4; including ADGC meta-P=8.6×10−9), CD33 (GERAD+ P=2.2×10−4; including ADGC meta-P=1.6×10−9) and EPHA1 (GERAD+ P=3.4×10−4; including ADGC meta-P=6.0×10−10). These findings support five novel susceptibility genes for AD.

Introduction We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development.

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...

Individuals who are at risk for autosomal dominant polycystic kidney disease are often screened by ultrasound using diagnostic criteria derived from individuals with mutations in PKD1. Families with mutations in PKD2 typically have less severe disease, suggesting a potential need for different diagnostic criteria. In this study, 577 and 371 at-risk individuals from 58 PKD1 and 39 PKD2 families, respectively, were assessed by renal ultrasound and molecular genotyping. Using sensitivity data derived from genetically affected individuals and specificity data derived from genetically unaffected individuals, various diagnostic criteria were compared. In addition, data sets were created to simulate the PKD1 and PKD2 case mix expected in practice to evaluate the performance of diagnostic criteria for families of unknown genotype. The diagnostic criteria currently in use performed suboptimally for individuals with mutations in PKD2 as a result of reduced test sensitivity. In families of unknown genotype, the presence of three or more (unilateral or bilateral) renal cysts is sufficient for establishing the diagnosis in individuals aged 15 to 39 y, two or more cysts in each kidney is sufficient for individuals aged 40 to 59 y, and four or more cysts in each kidney is required for individuals Ն60 yr. Conversely, fewer than two renal cysts in at-risk individuals aged Ն40 yr is sufficient to exclude the disease. These unified diagnostic criteria will be useful for testing individuals who are at risk for autosomal dominant polycystic kidney disease in the usual clinical setting in which molecular genotyping is seldom performed.

Apolipoprotein E (APOE) dependent lifetime risks (LTRs) for Alzheimer Disease (AD) are currently not accurately known and odds ratios (ORs) alone are insufficient to assess these risks. We calculated AD lifetime risk in 7,351 cases and 10,132 controls from Caucasian ancestry using Rochester (USA) incidence data. At the age of 85 the LTR of AD without reference to APOE genotype was 11% in males and 14% in females. At the same age, this risk ranged from 51% for APOE44 male carriers to 60% for APOE44 female carriers, and from 23% for APOE34 male carriers to 30% for APOE34 female carriers, consistent with semi-dominant inheritance of a moderately penetrant gene. Using PAQUID (France) incidence data, estimates were globally similar except that at age 85 the LTRs reached 68% and 35 % for APOE 44 and APOE 34 female carriers, respectively. These risks are more similar to those of major genes in Mendelian diseases, such as BRCA1 in breast cancer, than those of low-risk common alleles identified by recent GWAS in complex diseases. In addition, stratification of our data by age- groups clearly demonstrates that APOE4 is a risk factor not only for late- onset but for early- onset AD as well. Together, these results urge a reappraisal of the impact of APOE in Alzheimer disease.

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