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BackgroundDelaying the transition from minimal cognitive impairment to Alzheimer’s dementia is a major concern in Alzheimer’s disease (AD) therapeutics.Pathological signs of AD occur years before the onset of clinical dementia. Thus, long-term therapeutic approaches, with safe, minimally invasive, and yet effective substances are recommended. There is a need to develop new drugs to delay Alzheimer’s dementia. We have taken a nutritional supplement approach with genistein, a chemically defined polyphenol that acts by multimodal specific mechanisms. Our group previously showed that genistein supplementation is effective to treat the double transgenic (APP/PS1) AD animal model.MethodsIn this double-blind, placebo-controlled, bicentric clinical trial we evaluated the effect of daily oral supplementation with 120 mg of genistein for 12 months on 24 early symptomatic Alzheimer’s patients. We used a battery of validated neurocognitive tests: Mini-Mental State Exam (MMSE), Memory Alteration Test (M@T) Clock-drawing test, Complutense Verbal Learning Test (TAVEC), Barcelona Test-Revised (TBR), and Rey Complex Figure Test.ResultsWe report that genistein treatment results in a significant improvement in two of the tests used (dichotomized direct TAVEC, p=0.031; dichotomized delayed centil REY copy p=0.002 and a tendency to improve in all the rest of them.The amyloid-beta deposition was analyzed using 18F-flutemetamol uptake which showed that genistein-treated patients did not increase their uptake in the anterior cingulate gyrus after treatment (p = 0.878) while placebo-treated did increase it (p=0.036) We did not observe significant changes in other brain areas studiedConclusionsThis study shows that genistein may have a role in therapeutics to delay the onset of Alzheimer’s dementia in patients with mild cognitive impairment. These encouraging results indicate that this should be followed up by a new study with more patients to further validate the conclusion that arises from this study.Trial registrationNCT01982578

[Introduction] Limited information is available on people’s experiences of living with Alzheimer’s disease (AD) at earlier stages. This study assessed awareness of diagnosis among people with early-stage AD and its impact on different person-centered outcome measures., [Methods] We conducted an observational, cross-sectional study in 21 memory clinics in Spain. Persons aged 50–90 years, diagnosed with prodromal or mild AD (NIA/AA criteria), a Mini Mental State Examination (MMSE) score ≥ 22, and a Clinical Dementia Rating-Global score (CDR-GS) of 0.5 or 1.0 were recruited. The Representations and Adjustment to Dementia Index (RADIX) was used to assess participants’ beliefs about their condition and its consequences., [Results] A total of 149 persons with early-stage AD were studied. Mean (SD) age was 72.3 (7.0) years and 50.3% were female. Mean duration of AD was 1.4 (1.8) years. Mean MMSE score was 24.6 (2.1) and 87.2% had a CDR-GS score of 0.5. Most participants (n = 84, 57.5%) used a descriptive term related to specific AD symptoms (e.g., memory difficulties) when asked what they called their condition. Participants aware of their diagnosis using the term AD (n = 66, 45.2%) were younger, had more depressive symptoms, and poorer life satisfaction and quality of life compared to those without awareness of their specific diagnosis. Practical and emotional consequences RADIX scores showed a significant negative correlation with Quality of Life in Alzheimer’s Disease score (rho = − 0.389 and − 0.413, respectively; p, [Conclusions] Awareness of diagnosis was a common phenomenon in persons with early-stage AD negatively impacting their quality of life. Understanding illness representations in earlier stages may facilitate implementing optimized care that supports improved quality of life and well-being., This study was funded by the Medical Department of Roche Farma Spain (ML42346); funding sources with Life Molecular Imaging, Bioiberica, and Schwabe; and grants from CIBERNED, EU/EFPIA, Instituto de Salud Carlos III (ISCIII), Fundación La Caixa, and Grífols.

[Background] There is a need to better understand the experience of patients living with Alzheimer's disease (AD) in the early stages., [Objective] The aim of the study was to evaluate the perception of quality of life in patients with early-stage AD., [Methods] A multicenter, non-interventional study was conducted including patients of 50–90 years of age with prodromal or mild AD, a Mini-Mental State Examination (MMSE) score ≥22, and a Clinical Dementia Rating-Global score (CDR-GS) of 0.5.–1.0. The Quality of Life in Alzheimer ’s Disease (QoL-AD) questionnaire was used to assess health-related quality of life. A battery of self-report instruments was used to evaluate different psychological and behavioral domains. Associations between the QoL-AD and other outcome measures were analyzed using Spearman’s rank correlations., [Results] A total of 149 patients were included. Mean age (SD) was 72.3 (7.0) years and mean disease duration was 1.4 (1.8) years. Mean MMSE score was 24.6 (2.1). The mean QoL-AD score was 37.9 (4.5). Eighty-three percent (n = 124) of patients had moderate-to-severe hopelessness, 22.1% (n = 33) had depressive symptoms, and 36.9% (n = 55) felt stigmatized. The quality of life showed a significant positive correlation with self-efficacy and negative correlations with depression, emotional and practical consequences, stigma, and hopelessness., [Conclusion] Stigma, depressive symptoms, and hopelessness are frequent scenarios in AD negatively impacting quality of life, even in a population with short disease duration and minimal cognitive impairment., This study was funded by the Medical Department of Roche Farma Spain (ML42346).

Purpose The purpose of this project is to develop and externally validate a Deep Learning (DL) FDG PET imaging algorithm able to identify patients with Alzheimer's Disease (AD), Frontotemporal Degeneration (FTD) and Dementia with Lewy Bodies (DLB) among a group of patients with Mild Cognitive Impairment (MCI). Methods A 3D Convolutional neural network, trained using images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, was implemented. The ADNI dataset used for training and testing the model consisted of 822 subjects (472 AD and 350 MCI). The external validation was performed on an independent dataset from our hospital. The hospital real world dataset contains 90 subjects with MCI: 71 patients that developed a neurodegenerative disease (64 AD, 4 FTD and 3 DLB) and 19 subjects without associated neurodegenerative disease. Results The ADNI model had 79% accuracy, 88% sensitivity and 71% specificity in the identification of patients with neurodegenerative diseases tested on the 10% ADNI dataset, achieving an area under the receiver operating characteristic curve (AUC) of 0.897. When used for the external validation, the model preserved 77% accuracy, 75% sensitivity, 84% specificity and 0.860 area under the ROC curve. Conclusion This model based on FDG PET images can help the early non-invasive prediction of neurodegenerative diseases in MCI patients in standard clinical settings with an overall 77% classification accuracy.

BACKGROUNDDisentangling the genetic constellation underlying Alzheimer’s disease (AD) is important. Doing so allows us to identify biological pathways underlying AD, point towards novel drug targets and use the variants for individualised risk predictions in disease modifying or prevention trials. In the present work we report on the largest genome-wide association study (GWAS) for AD risk to date and show the combined utility of proven AD loci for precision medicine using polygenic risk scores (PRS).METHODSThree sets of summary statistics were included in our meta-GWAS of AD: an Spanish case-control study (GR@ACE/DEGESCO study, n = 12,386), the case-control study of International Genomics of Alzheimer project (IGAP, n = 82,771) and the UK Biobank (UKB) AD-by-proxy case-control study (n=314,278). Using these resources, we performed a fixed-effects inverse-variance-weighted meta-analysis. Detected loci were confirmed in a replication study of 19,089 AD cases and 39,101 controls from 16 European-ancestry cohorts not previously used. We constructed a weighted PRS based on the 39 AD variants. PRS were generated by multiplying the genotype dosage of each risk allele for each variant by its respective weight, and then summing across all variants. We first validated it for AD in independent data (assessing effects of sub-threshold signal, diagnostic certainty, age at onset and sex) and tested its effect on risk (odds for disease) and age at onset in the GR@ACE/DEGESCO study.FINDINGSUsing our meta-GWAS approach and follow-up analysis, we identified novel genome-wide significant associations of six genetic variants with AD risk (rs72835061-CHRNE, rs2154481-APP, rs876461-PRKD3/NDUFAF7, rs3935877-PLCG2 and two missense variants: rs34173062/rs34674752 in SHARPIN gene) and confirmed a stop codon mutation in the IL34 gene increasing the risk of AD (IL34-Tyr213Ter), and two other variants in PLCG2 and HS3ST1 regions. This brings the total number of genetic variants associated with AD to 39 (excluding APOE). The PRS based on these variants was associated with AD in an independent clinical AD-case control dataset (OR=1.30, per 1-SD increase in the PRS, 95%CI 1.18-1.44, p = 1.1×10−7), a similar effect to that in the GR@ACE/DEGESCO (OR=1.27, 95%CI 1.23-1.32, p = 7.4×10−39). We then explored the combined effects of these 39 variants in a PRS for AD risk and age-at-onset stratification in GR@ACE/DEGESCO. Excluding APOE, we observed a gradual risk increase over the 2% tiles; when comparing the extremes, those with the 2% highest risk had a 2.98-fold (95% CI 2.12–4.18, p = 3.2×10−10) increased risk compared to those with the 2% lowest risk (p = 5.9×10−10). Using the PRS we identified APOE ε33 carriers with a similar risk as APOE ε4 heterozygotes carriers, as well as APOE ε4 heterozygote carriers with a similar risk as APOE ε4 homozygote. Considering age at onset; there was a 9-year difference between median onset of AD the lowest risk group and the highest risk group (82 vs 73 years; p = 1.6×10−6); a 4-year median onset difference (81 vs 77 years; p = 6.9×10−5) within APOE ε4 heterozygotes and a 5.5-year median onset difference (78.5 vs 73 years; p = 4.6×10−5) within APOE ε4 carriers.INTERPRETATIONWe identified six novel genetic variants associated with AD-risk, among which one common APP variant. A PRS of all genetic loci reported to date could be a robust tool to predict the risk and age at onset of AD, beyond APOE alone. These properties make PRS instrumental in selecting individuals at risk in order to apply preventative strategies and might have potential use in diagnostic work-up.

Introduction: Large variability among Alzheimer's disease (AD) cases might impact genetic discoveries and complicate dissection of underlying biological pathways. Methods: Genome Research at Fundacio ACE (GR@ACE) is a genome-wide study of dementia and its clinical endophenotypes, defined based on AD's clinical certainty and vascular burden. We assessed the impact of known AD loci across endophenotypes to generate loci categories. We incorporated gene coexpression data and conducted pathway analysis per category. Finally, to evaluate the effect of heterogeneity in genetic studies, GR@ACE series were meta-analyzed with additional genome-wide association study data sets. Results: We classified known AD loci into three categories, which might reflect the disease clinical heterogeneity. Vascular processes were only detected as a causal mechanism in probable AD. The meta-analysis strategy revealed the ANKRD31-rs4704171 and NDUFAF6-rs10098778 and confirmed SCIMP-rs7225151 and CD33-rs3865444. Discussion: The regulation of vasculature is a prominent causal component of probable AD. GR@ACE meta-analysis revealed novel AD genetic signals, strongly driven by the presence of clinical heterogeneity in the AD series., The authors would like to thank patients and controls who participated in this project. The Genome Research @ Fundacio ACE project (GR@ACE) is supported by Fundacion bancaria La Caixa, Grifols SA, Fundacio ACE, and ISCIII (Ministry of Health, Spain). They also want to thank the private sponsors who support the basic and clinical projects of our institution (Piramal AG, Laboratorios Echevarne, Araclon Biotech S.A., and Fundacio ACE). They are indebted to the Trinitat Port-Carbo legacy and her family for their support of Fundacio ACE research programs. Fundacio ACE is a participating center in the Dementia Genetics Spanish Consortium (DEGESCO). A.R. and M.B. receive support from the European Union/EFPIA Innovative Medicines Initiative Joint undertaking ADAPTED and MOPEAD projects (grant numbers 115975 and 115985, respectively). M.B. and A.R. are also supported by national grants PI13/02434, PI16/01861, and PI17/01474. Accion Estrategica en Salud is integrated into the Spanish National R + D + I Plan and funded by ISCIII (Instituto de Salud Carlos III)-Subdireccion General de Evaluacion and the Fondo Europeo de Desarrollo Regional (FEDER-Una manera de Hacer Europa). L.M.R. is supported by Consejeria de Salud de la Junta de Andalucia (grant PI-0001/2017). Control samples and data from patients included in this study were provided in part by the National DNA Bank Carlos III (www.bancoadn.org, University of Salamanca, Spain) and Hospital Universitario Virgen de Valme (Sevilla, Spain); they were processed after standard operating procedures with the appropriate approval of the Ethical and Scientific Committee. The present work was performed as part of the Biochemistry, Molecular Biology, and Biomedicine doctoral program of S. MorenoGrau at Universitat Autonoma de Barcelona (Barcelona, Spain).r Data collection and sharing for this project was partially funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). The ADNI is funded by the National Institute on Aging and the National Institute of Biomedical Imaging and Bioengineering, as well as through generous contributions from the following: AbbVie; the Alzheimer's Association; the Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research provides funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study was coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for NeuroImaging at the University of Southern California.; r The AddNeuroMed data are from a public-private partnership supported by EFPIA companies and SMEs as part of InnoMed (Innovative Medicines in Europe), an integrated project funded by the European Union of the Sixth Framework program priority FP6-2004-LIFESCIHEALTH-5. Clinical leads responsible for data collection are Iwona K1oszewska (Lodz), Simon Lovestone (London), Patrizia Mecocci (Perugia), Hilkka Soininen (Kuopio), Magda Tsolaki (Thessaloniki), and Bruno Vellas (Toulouse). Imaging leads are Andy Simmons (London), Lars-Olad Wahlund (Stockholm), and Christian Spenger (Zurich). Bioinformatics leads are Richard Dobson (London) and Stephen Newhouse (London).r Funding support for the Alzheimer's Disease Genetics Consortium (ADGC) was provided through the NIA Division of Neuroscience (U01-AG032984).r The Mayo Clinic Alzheimer's Disease Genetic Studies, led by Dr. Nilufer Ertekin-Taner and Dr. Steven G. Younkin at the Mayo Clinic in Jacksonville, FL, used samples from the Mayo Clinic Study of Aging, the Mayo Clinic Alzheimer's Disease Research Center, and the Mayo Clinic Brain Bank. Data collection was supported through funding by NIA grants P50 AG016574, R01 AG032990, U01 AG046139, R01 AG018023, U01 AG006576, U01 AG006786, R01 AG025711, R01 AG017216, and R01 AG003949, NINDS grant R01 NS080820, the CurePSP Foundation, and support from the Mayo Foundation.r The Neocodex-Murcia study was funded by the Fundacion Alzheimur (Murcia), the Ministerio de Educacion y Ciencia (Gobierno de Espana), Corporacion Tecnologica de Andalucia, Agencia IDEA (Consejeria de Innovacion, Junta de Andalucia), the Diabetes Research Laboratory, and the Biomedical Research Foundation. University Hospital Clinico San Carlos has been supported by CIBER de Diabetes y Enfermedades Metabolicas Asociadas (CIBERDEM); CIBERDEM is an ISCIII Project.r The ROS/MAP study data were provided by the Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago. Data collection was supported through funding by NIA grants P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG36836, U01AG32984 and U01AG46152, the Illinois Department of Public Health, and the Translational Genomics Research Institute.r The TGEN study was supported by Kronos Life Science Laboratories, the National Institute on Aging (Arizona Alzheimer's Disease Center grants P30 AG19610 and RO1 AG023193, the Mayo Clinic Alzheimer's Disease Center grant P50 AG16574, and the Intramural Research Program), the National Alzheimer's Coordinating Center (U01 AG016976), and the state of Arizona.r The authors thank the International Genomics of Alzheimer's Project (IGAP) for providing summary result data for these analyses. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients, and their families. The i-Select chip was funded by the French National Foundation on Alzheimer's disease and related disorders. European Alzheimer's Disease Initiative (EADI) was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Universite de Lille 2, and the Lille University Hospital. GERAD was supported by the Medical Research Council (grant no. 503480), Alzheimer's Research UK (grant no. 503176), the Wellcome Trust (grant no. 082604/2/07/Z), and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant no.; 01GI0102, 01GI0711, 01GI0420. CHARGE was partly supported by the NIH/NIA grant R01 AG033193 and the NIA AG081220 and AGES contract N01-AG12100, the NHLBI grant R01 HL105756, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer's Association grant ADGC-10-196728.

Dols-Icardo, O. et al. Assessing the role of TUBA4A gene in frontotemporal degeneration. Neurobiology of Aging 38:215.e13-4 (2016). Artículo: 2 páginas y 1 tabla como material suplementario, The tubulin alpha 4a (TUBA4A) gene has been recently associated with amyotrophic lateral sclerosis. Interestingly, some of the mutation carriers were also diagnosed with frontotemporal degeneration (FTD) or mild cognitive impairment. With the aim to investigate the role of TUBA4A in FTD, we screened TUBA4A in a series of 814 FTD patients from Spain. Our data did not disclose any nonsense or missense variant in the cohort, thus suggesting that TUBA4A mutations are not associated with FTD., This work was supported in part by grants from CIBERNED and Ministerio de Economía y Competitividad, Spain (SAF2014-59469-R to JPT), grants from the Department of Health of the Government of Navarra, Spain (refs.13085 and 3/2008), from the UTE project FIMA, Spain, from the Instituto de Salud Carlos III (PI12/01311 to JC) and Fundació La Marató de TV3 (project nº 20143810 to RSV

Depressive symptoms are very common in chronic conditions. This is true so for neurodegenerative diseases. A number of patients with cognitive decline and dementia due to Alzheimer's disease and related conditions like Parkinson's disease, Lewy body disease, vascular dementia, frontotemporal degeneration amongst other entities, experience depressive symptoms in greater or lesser grade at some point during the course of the illness. Depressive symptoms have a particular significance in neurological disorders, specially in neurodegenerative diseases, because brain, mind, behavior and mood relationship. A number of patients may develop depressive symptoms in early stages of the neurologic disease, occurring without clear presence of cognitive decline with only mild cognitive deterioration. Classically, depression constitutes a reliable diagnostic challenge in this setting. However, actually we can recognize and evaluate depressive, cognitive or motor symptoms of neurodegenerative disease in order to establish their clinical significance and to plan some therapeutic strategies. Depressive symptoms can appear also lately, when the neurodegenerative disease is fully developed. The presence of depression and other neuropsychiatric symptoms have a negative impact on the quality-of-life of patients and caregivers. Besides, patients with depressive symptoms also tend to further decrease function and reduce cognitive abilities and also uses to present more affected clinical status, compared with patients without depression. Depressive symptoms are treatable. Early detection of depressive symptoms is very important in patients with neurodegenerative disorders, in order to initiate the most adequate treatment. We review in this paper the main neurodegenerative diseases, focusing in depressive symptoms of each other entities and current recommendations of management and treatment.

4 páginas, 1 figura, a tabla. Los autores pertenecen a The dementia genetic Spanish consortium (DEGESCO)., A non-synonymous genetic rare variant, rs75932628-T (p.R47H), in the TREM2 gene has recently been reported to be a strong genetic risk factor for Alzheimer's disease (AD). Also, rare recessive mutations have been associated with frontotemporal dementia (FTD). We aimed to investigate the role of p.R47H variant in AD and FTD through a multi-center study comprising 3,172 AD and 682 FTD patients and 2,169 healthy controls from Spain. We found that 0.6% of AD cases carried this variant compared to 0.1% of controls (odds ratio [OR]=4.12, 95% confidence interval [CI]: 1.21-14.00, P=0.014). A meta-analysis comprising 32,598 subjects from four previous studies demonstrated the large effect of the p.R47H variant in AD risk (OR=4.11, 95% CI: 2.99-5.68, P=5.27x10-18). We did not find an association between p.R47H and age of onset of AD or family history of dementia. Finally, none of the FTD patients harbored this genetic variant. These data strongly support the important role of p.R47H in AD risk and suggest that this rare genetic variant is not related to FTD., This study was supported by grants from Instituto de Salud Carlos III (PI12/01311 and 12/00013), grants from the Ministry of Science (SAF2010-15558, SAF2009-10434), Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED, Spain), Consolider (CSD2010-00045), and the Department of Health of the Government of Navarra (refs. 13085 and 3/2008). CR held during the period 2009-2013 a “Torres Quevedo” fellowship from the Spanish Ministry of Science and Technology, co-financed by the European Social Fund. Fundació ACE researchers are indebted to Trinitat Port-Carbó and her family who are supporting Fundació ACE scientific programs.

Mutations in three genes (PSEN1, PSEN2, and APP) have been identified in patients with early-onset (