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

The Alzheimer Disease Genetics Consortium (ADGC) performed a genome-wide association study (GWAS) of late-onset Alzheimer disease (LOAD) using a 3 stage design consisting of a discovery stage (Stage 1) and two replication stages (Stages 2 and 3). Both joint and meta-analysis analysis approaches were used. We obtained genome-wide significant results at MS4A4A [rs4938933; Stages 1+2, meta-analysis (PM) = 1.7 × 10−9, joint analysis (PJ) = 1.7 × 10−9; Stages 1–3, PM = 8.2 × 10−12], CD2AP (rs9349407; Stages 1–3, PM = 8.6 × 10−9), EPHA1 (rs11767557; Stages 1–3 PM = 6.0 × 10−10), and CD33 (rs3865444; Stages 1–3, PM = 1.6 × 10−9). We confirmed that CR1 (rs6701713; PM = 4.6×10−10, PJ = 5.2×10−11), CLU (rs1532278; PM = 8.3 × 10−8, PJ = 1.9×10−8), BIN1 (rs7561528; PM = 4.0×10−14; PJ = 5.2×10−14), and PICALM (rs561655; PM = 7.0 × 10−11, PJ = 1.0×10−10) but not EXOC3L2 are LOAD risk loci1–3.

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.

These results suggest that regular exercise is associated with a delay in onset of dementia and Alzheimer disease, further supporting its value for elderly persons.

Our dementia and AD incidence rates are consistent with recent US and European cohort studies, providing clinicians and researchers new information concerning the reproducibility of incidence estimates across settings. Increased risk was associated with age and the apolipoprotein E genotype; also with a low baseline cognitive screening test score. Educational level was inversely associated with the risk of dementia and positively associated with the baseline cognitive test score; thus, detection of AD by the screening test could also be influenced by educational level.

BACKGROUND Diabetes is a risk factor for dementia. It is unknown whether higher glucose levels increase the risk of dementia in people without diabetes. METHODS We used 35,264 clinical measurements of glucose levels and 10,208 measurements of glycated hemoglobin levels from 2067 participants without dementia to examine the relationship between glucose levels and the risk of dementia. Participants were from the Adult Changes in Thought study and included 839 men and 1228 women whose mean age at baseline was 76 years; 232 participants had diabetes, and 1835 did not. We fit Cox regression models, stratified according to diabetes status and adjusted for age, sex, study cohort, educational level, level of exercise, blood pressure, and status with respect to coronary and cerebrovascular diseases, atrial fibrillation, smoking, and treatment for hypertension. RESULTS During a median follow-up of 6.8 years, dementia developed in 524 participants (74 with diabetes and 450 without). Among participants without diabetes, higher average glucose levels within the preceding 5 years were related to an increased risk of dementia (P = 0.01); with a glucose level of 115 mg per deciliter (6.4 mmol per liter) as compared with 100 mg per deciliter (5.5 mmol per liter), the adjusted hazard ratio for dementia was 1.18 (95% confidence interval [CI], 1.04 to 1.33). Among participants with diabetes, higher average glucose levels were also related to an increased risk of dementia (P = 0.002); with a glucose level of 190 mg per deciliter (10.5 mmol per liter) as compared with 160 mg per deciliter (8.9 mmol per liter), the adjusted hazard ratio was 1.40 (95% CI, 1.12 to 1.76). CONCLUSIONS Our results suggest that higher glucose levels may be a risk factor for dementia, even among persons without diabetes. (Funded by the National Institutes of Health.)

In this sample of community-dwelling elderly persons who received a diagnosis of Alzheimer disease, survival duration was shorter than predicted on the basis of U.S. population data, especially for persons with onset at relatively younger ages. Features significantly associated with reduced survival at diagnosis were increased severity of cognitive impairment, decreased functional level, history of falls, physical examination findings of frontal release signs, and abnormal gait. The variables most strongly associated with survival were measures of disease severity at the time of diagnosis. These results should be useful to patients and families experiencing Alzheimer disease, other caregivers, clinicians, and policymakers when planning for future care needs.

In this large community sample, the severity of multiple sclerosis was more strongly associated with depressive symptoms than was pattern of illness. Clinicians should evaluate depression in patients with recent diagnoses of multiple sclerosis, major changes in functioning, or limited social support.