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

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.

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...

Deep brain stimulation of the subthalamic nucleus represents the most important innovation for treatment of advanced Parkinson's disease. Prospective studies have shown that although the beneficial effects of this procedure are maintained at 5 years, axial motor features and cognitive decline may occur in the long term after the implants. In order to address some unsolved questions raised by previous studies, we evaluated a series of 20 consecutive patients who received continuous stimulation for 8 years. The overall motor improvement reported at 5 years (55.5% at Unified Parkinson's Disease Rating Scale-motor part, P < 0.001 compared with baseline) was only partly retained 3 years later (39%, P < 0.001, compared with baseline; -16.5%, P < 0.01, compared with 5 years), with differential effects on motor features: speech did not improve and postural stability worsened (P < 0.05). The preoperative levodopa equivalent daily dose was reduced by 58.2% at 5 years and by 60.3% at 8 years. In spite of subtle worsening of motor features, a dramatic impairment in functional state (-56.6% at Unified Parkinson's Disease Rating Scale-Activities of Daily Living, P < 0.01) emerged after the fifth year of stimulation. The present study did not reveal a predictive value of preoperative levodopa response, whereas few single features at baseline (such as gait and postural stability motor scores and the preoperative levodopa equivalent daily dose) could predict long-term motor outcome. A decline in verbal fluency (slightly more pronounced than after 5 years) was detected after 8 years. A significant but slight decline in tasks of abstract reasoning, episodic memory and executive function was also found. One patient had developed dementia at 5 years with further progression at 8 years. Executive dysfunction correlated significantly with postural stability, suggesting interplay between axial motor deterioration and cognition. Eight years after surgery, no significant change was observed on scales assessing depression or anxiety when compared with baseline. At 8 years, there was no significant increase of side-effects when compared with 5-year follow-up. In conclusion, deep brain stimulation of the subthalamic nucleus is a safe procedure with regard to cognitive and behavioural morbidity over long-term follow-up. However, the global benefit partly decreases later in the course of the disease, due to progression of Parkinson's disease and the appearance of medication- and stimulation-resistant symptoms.

Frailty, a critical intermediate status of the aging process that is at increased risk for negative health-related events, includes physical, cognitive, and psychosocial domains or phenotypes. Cognitive frailty is a condition recently defined by operationalized criteria describing coexisting physical frailty and mild cognitive impairment (MCI), with two proposed subtypes: potentially reversible cognitive frailty (physical frailty/MCI) and reversible cognitive frailty (physical frailty/pre-MCI subjective cognitive decline). In the present article, we reviewed the framework for the definition, different models, and the current epidemiology of cognitive frailty, also describing neurobiological mechanisms, and exploring the possible prevention of the cognitive frailty progression. Several studies suggested a relevant heterogeneity with prevalence estimates ranging 1.0–22.0% (10.7–22.0% in clinical-based settings and 1.0–4.4% in population-based settings). Cross-sectional and longitudinal population-based studies showed that different cognitive frailty models may be associated with increased risk of functional disability, worsened quality of life, hospitalization, mortality, incidence of dementia, vascular dementia, and neurocognitive disorders. The operationalization of clinical constructs based on cognitive impairment related to physical causes (physical frailty, motor function decline, or other physical factors) appears to be interesting for dementia secondary prevention given the increased risk for progression to dementia of these clinical entities. Multidomain interventions have the potential to be effective in preventing cognitive frailty. In the near future, we need to establish more reliable clinical and research criteria, using different operational definitions for frailty and cognitive impairment, and useful clinical, biological, and imaging markers to implement intervention programs targeted to improve frailty, so preventing also late-life cognitive disorders.

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The findings suggest that this method can be used as a noninvasive test of cholinergic pathways in AD. Future studies are required to evaluate whether short latency afferent inhibition measurements have any consistent clinical correlates.