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.

APOE4 is the strongest genetic risk factor for late-onset Alzheimer’s disease (AD). ApoE4 increases brain amyloid-β (Aβ) pathology relative to other ApoE isoforms1. However, whether APOE independently influences tau pathology, the other major proteinopathy of AD and other tauopathies, or tau-mediated neurodegeneration, is not clear. By generating P301S tau transgenic mice on either a human ApoE knockin (KI) or ApoE knockout (KO) background, we show that P301S/E4 mice have significantly higher tau levels in the brain and a greater extent of somatodendritic tau redistribution by 3 months of age compared to P301S/E2, P301S/E3 and P301S/EKO mice. By 9 months of age, P301S mice with different ApoE genotypes display distinct p-tau staining patterns. P301S/E4 mice develop markedly more brain atrophy and neuroinflammation than P301S/E2 and P301S/E3 mice, whereas P301S/EKO mice are largely protected from these changes. In vitro, E4-expressing microglia exhibit higher innate immune reactivity following LPS treatment. Co-culturing P301S tau-expressing neurons with E4-expressing mixed glia results in a significantly higher level of TNFα secretion and markedly reduced neuronal viability compared to neuron/E2 and neuron/E3 co-cultures. Neurons co-cultured with EKO glia showed the greatest viability with the lowest level of secreted TNFα. Treatment of P301S neurons with recombinant ApoE (E2, E3, E4) also leads to some neuronal damage and death compared to the absence of ApoE, with ApoE4 exacerbating the effect. In individuals with a sporadic primary tauopathy, the presence of an ε4 allele is associated with more severe regional neurodegeneration. In Aβ-pathology positive individuals with symptomatic AD who usually have tau pathology, ε4-carriers demonstrate greater rates of disease progression. Our results demonstrate that ApoE affects tau pathogenesis, neuroinflammation, and tau-mediated neurodegeneration independent of Aβ pathology. ApoE4 exerts a “toxic” gain of function whereas the absence of ApoE is protective.

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.

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Frontotemporal dementia is an umbrella clinical term that encompasses a group of neurodegenerative diseases characterised by progressive deficits in behaviour, executive function, or language. Frontotemporal dementia is a common type of dementia, particularly in patients younger than 65 years. The disease can mimic many psychiatric disorders because of the prominent behavioural features. Various underlying neuropathological entities lead to the frontotemporal dementia clinical phenotype, all of which are characterised by the selective degeneration of the frontal and temporal cortices. Genetics is an important risk factor for frontotemporal dementia. Advances in clinical, imaging, and molecular characterisation have increased the accuracy of frontotemporal dementia diagnosis, thus allowing for the accurate differentiation of these syndromes from psychiatric disorders. As the understanding of the molecular basis for frontotemporal dementia improves, rational therapies are beginning to emerge.

With the potential development of new disease-modifying Alzheimer’s Disease (AD) therapies, simple, widely available screening tests are needed to identify which individuals who are experiencing symptoms of cognitive or behavioral decline should be further evaluated for initiation of treatment. A blood-based test for AD would be a less invasive and less expensive screening tool than the currently approved CSF or amyloid β-PET diagnostic tests. We examined whether plasma phosphorylated tau at residue 181 (pTau181) could differentiate between clinically diagnosed or autopsy confirmed AD and Frontotemporal Lobar Degeneration (FTLD). Plasma pTau181 concentrations were increased by 3.5 fold in AD compared to controls and differentiated AD from both clinically diagnosed (Receiver Operating Characteristic Area Under the Curve [AUC]=0.894) and autopsy confirmed FTLD (AUC=0.878). Plasma pTau181 identified amyloid β-PET positive individuals regardless of clinical diagnosis and correlated with cortical tau protein deposition measured by 18 F-Flortaucipir PET. Plasma pTau181 may be useful to screen for tau pathology associated with AD.

Progressive supranuclear palsy (PSP) is a movement disorder with prominent tau neuropathology. Brain diseases with abnormal tau deposits are called tauopathies, the most common being Alzheimer’s disease. Environmental causes of tauopathies include repetitive head trauma associated with some sports. To identify common genetic variation contributing to risk for tauopathies, we carried out a genome-wide association study of 1,114 PSP cases and 3,247 controls (Stage 1) followed up by a second stage where 1,051 cases and 3,560 controls were genotyped for Stage 1 SNPs that yielded P ≤ 10−3. We found significant novel signals (P < 5 × 10−8) associated with PSP risk at STX6, EIF2AK3, and MOBP. We confirmed two independent variants in MAPT affecting risk for PSP, one of which influences MAPT brain expression. The genes implicated encode proteins for vesicle-membrane fusion at the Golgi-endosomal interface, for the endoplasmic reticulum unfolded protein response, and for a myelin structural component.