We undertook a two-stage genome-wide association study of Alzheimer's disease involving over 16,000 individuals. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the APOE locus (most significant SNP: rs2075650, p= 1.8×10−157) and observed genome-wide significant association with SNPs at two novel loci: rs11136000 in the CLU or APOJ gene (p= 1.4×10−9) and rs3851179, a SNP 5′ to the PICALM gene (p= 1.9×10−8). Both novel associations were supported in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with AD in the combined dataset (rs11136000: p= 8.5×10−10, odds ratio= 0.86; rs3851179: p= 1.3×10−9, odds ratio= 0.86). We also observed more variants associated at p< 1×10−5 than expected by chance (p=7.5×10−6), including polymorphisms at the BIN1, DAB1 and CR1 loci.

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.

IMPORTANCE Epidemiologic research on the possible link between age-related hearing loss (ARHL) and cognitive decline and dementia has produced inconsistent results. Clarifying this association is of interest because ARHL may be a risk factor for outcomes of clinical dementia. OBJECTIVES To examine and estimate the association between ARHL and cognitive function, cognitive impairment, and dementia through a systematic review and meta-analysis. DATA SOURCES AND STUDY SELECTION A search of PubMed, the Cochrane Library, EMBASE, and SCOPUS from inception to April 15, 2016, with cross-referencing of retrieved studies and personal files for potentially eligible studies was performed. Keywords included hearing, cognition, dementia, and Alzheimer disease. Cohort and cross-sectional studies published in peer-reviewed literature and using objective outcome measures were included. Case-control studies were excluded. DATA EXTRACTION AND SYNTHESIS One reviewer extracted and another verified data. Both reviewers independently assessed study quality. Estimates were pooled using random-effects meta-analysis. Subgroup and meta-regression analyses of study-level characteristics were performed. MAIN OUTCOMES AND MEASURES Hearing loss measured by pure-tone audiometry only and objective assessment measures of cognitive function, cognitive impairment, and dementia. Cognitive function outcomes were converted to correlation coefficients (r value); cognitive impairment and dementia outcomes, to odds ratios (ORs). RESULTS Forty studies from 12 countries met our inclusion criteria. Of these, 36 unique studies with an estimated 20 264 unique participants were included in the meta-analyses. Based on the pooled maximally adjusted effect sizes using random-effects models, a small but significant association was found for ARHL within all domains of cognitive function. Among cross-sectional studies, a significant association was found for cognitive impairment (OR, 2.00; 95% CI, 1.39–2.89) and dementia (OR, 2.42; 95% CI, 1.24–4.72). Among prospective cohort studies, a significant association was found for cognitive impairment (OR, 1.22; 95% CI, 1.09–1.36) and dementia (OR, 1.28; 95% CI, 1.02–1.59) but not for Alzheimer disease (OR, 1.69; 95% CI, 0.72–4.00). In further analyses, study, demographic, audiometric, and analyses factors were associated with cognitive function. Vascular dysfunction and impaired verbal communication may contribute to the association between hearing loss and cognitive decline. CONCLUSIONS AND RELEVANCE Age-related hearing loss is a possible biomarker and modifiable risk factor for cognitive decline, cognitive impairment, and dementia. Additional research and randomized clinical trials are warranted to examine implications of treatment for cognition and to explore possible causal mechanisms underlying this relationship.

The EURO-D scale should permit valid comparison of risk-factor associations between centres, even if between-centre variation remains difficult to attribute.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Loneliness is common in older people an is associated with adverse health consequences both from a mental and physical health point of view. There needs to be an increased focus on initiating intervention strategies targeting loneliness to determine if decreasing loneliness can improve quality of life and functioning in the elderly.