Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele.

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...

Glaucoma is the leading cause of irreversible blindness globally.1 Despite its gravity, the disease is frequently undiagnosed in the community.2 Raised intraocular pressure (IOP) is the most important risk factor for primary open-angle glaucoma (POAG).3,4 Here we present a meta-analysis of 139,555 European participants that identified 112 genomic loci associated with IOP, 68 of which are novel. These loci suggest a strong role for angiopoietin-receptor tyrosine kinase signaling, lipid metabolism, mitochondrial function and developmental processes underlying risk for elevated IOP. In addition, 48 of these loci were associated with glaucoma in an independent cohort, 14 of which at a Bonferroni-corrected threshold. Regression-based glaucoma prediction models had an area under Receiving Operator Characteristic curve (AUROC) of 0.76 in USA NEIGHBORHOOD study participants and 0.74 in independent glaucoma cases from UK Biobank. Genetic prediction models for POAG offer an opportunity to target screening and timely therapy to individuals most at risk.

Primary open angle glaucoma (POAG) is a leading cause of blindness world-wide. To identify new susceptibility loci, we meta-analyzed GWAS results from 8 independent studies from the United States (3,853 cases and 33,480 controls) and investigated the most significant SNPs in two Australian studies (1,252 cases and 2,592 controls), 3 European studies (875 cases and 4,107 controls) and a Singaporean Chinese study (1,037 cases and 2,543 controls). A meta-analysis of top SNPs identified three novel loci: rs35934224[T] within TXNRD2 (odds ratio (OR) = 0.78, P = 4.05×10−11 encoding a mitochondrial protein required for redox homeostasis; rs7137828[T] within ATXN2 (OR = 1.17, P = 8.73×10−10), and rs2745572[A] upstream of FOXC1 (OR = 1.17, P = 1.76×10−10). Using RT-PCR and immunohistochemistry, we show TXNRD2 and ATXN2 expression in retinal ganglion cells and the optic nerve head. These results identify new pathways underlying POAG susceptibility and suggest novel targets for preventative therapies.

PurposeNoncoding microRNAs (miRNAs) have been implicated in the pathogenesis of glaucoma. We aimed to identify common variants in miRNA coding genes (MIR) associated with primary open-angle glaucoma (POAG).MethodsUsing the NEIGHBORHOOD data set (3853 cases/33,480 controls with European ancestry), we first assessed the relation between 85 variants in 76 MIR genes and overall POAG. Subtype-specific analyses were performed in high-tension glaucoma (HTG) and normal-tension glaucoma subsets. Second, we examined the expression of miR-182, which was associated with POAG, in postmortem human ocular tissues (ciliary body, cornea, retina, and trabecular meshwork [TM]), using miRNA sequencing (miRNA-Seq) and droplet digital PCR (ddPCR). Third, miR-182 expression was also examined in human aqueous humor (AH) by using miRNA-Seq. Fourth, exosomes secreted from primary human TM cells were examined for miR-182 expression by using miRNA-Seq. Fifth, using ddPCR we compared miR-182 expression in AH between five HTG cases and five controls.ResultsOnly rs76481776 in MIR182 gene was associated with POAG after adjustment for multiple comparisons (odds ratio [OR] = 1.23, 95% confidence interval [CI]: 1.11–1.42, P = 0.0002). Subtype analysis indicated that the association was primarily in the HTG subset (OR = 1.26, 95% CI: 1.08–1.47, P = 0.004). The risk allele T has been associated with elevated miR-182 expression in vitro. Data from ddPCR and miRNA-Seq confirmed miR-182 expression in all examined ocular tissues and TM-derived exosomes. Interestingly, miR-182 expression in AH was 2-fold higher in HTG patients than nonglaucoma controls (P = 0.03) without controlling for medication treatment.ConclusionsOur integrative study is the first to associate rs76481776 with POAG via elevated miR-182 expression.