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.

Background Frontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72. Methods In this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried. Findings Data were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49•5 years (SD 10•0; onset) and 58•5 years (11•3; death) in the MAPT group, 58•2 years (9•8; onset) and 65•3 years (10•9; death) in the C9orf72 group, and 61•3 years (8•8; onset) and 68•8 years (9•7; death) in the GRN group. Mean disease duration was 6•4 years (SD 4•9) in the C9orf72 group, 7•1 years (3•9) in the GRN group, and 9•3 years (6•4) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0•45 between individual and parental age at onset, r=0•63 between individual and mean family age at onset, r=0•58 between individual and parental age at death, and r=0•69 between individual and mean family age at death) than in either the C9orf72 group (r=0•32 individual and parental age at onset, r=0•36 individual and mean family age at onset, r=0•38 individual and parental age at death, and r=0•40 individual and mean family age at death) or the GRN group (r=0•22 individual and parental age at onset, r=0•18 individual and mean family age at onset, r=0•22 individual and parental age at death, and r=0•32 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35-62, for age at onset; 61%, 47-73, for age at death), and even mor...

Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease.

ObjectiveTo assess the diagnostic and prognostic value of serum neurofilament light (NfL) and serum phospho-Tau181 (p-Tau181) in a large cohort of patients with frontotemporal lobar degeneration (FTLD).MethodsIn this retrospective study, performed on 417 participants, we analysed serum NfL and p-Tau181 concentrations with an ultrasensitive single molecule array (Simoa) approach. We assessed the diagnostic values of serum biomarkers in the differential diagnosis between FTLD, Alzheimer’s disease (AD) and healthy ageing; their role as markers of disease severity assessing the correlation with clinical variables, cross-sectional brain imaging and neurophysiological data; their role as prognostic markers, considering their ability to predict survival probability in FTLD.ResultsWe observed significantly higher levels of serum NfL in patients with FTLD syndromes, compared with healthy controls, and lower levels of p-Tau181 compared with patients with AD. Serum NfL concentrations showed a high accuracy in discriminating between FTLD and healthy controls (area under the curve (AUC): 0.86, p<0.001), while serum p-Tau181 showed high accuracy in differentiating FTLD from patients with AD (AUC: 0.93, p<0.001). In FTLD, serum NfL levels correlated with measures of cognitive function, disease severity and behavioural disturbances and were associated with frontotemporal atrophy and indirect measures of GABAergic deficit. Moreover, serum NfL concentrations were identified as the best predictors of survival probability.ConclusionsThe assessment of serum NfL and p-Tau181 may provide a comprehensive view of FTLD, aiding in the differential diagnosis, in staging disease severity and in defining survival probability.

Deciphering the genetic landscape of Alzheimer disease (AD) is essential to define the pathophysiological pathways involved and to successfully translate genomics to potential tailored medical care. To generate the most complete knowledge of the AD genetics, we developed through the European Alzheimer Disease BioBank (EADB) consortium a discovery meta-analysis of genome-wide association studies (GWAS) based on a new large case-control study and previous GWAS (in total 39,106 clinically diagnosed cases, 46,828 proxy-AD cases and 401,577 controls) with the most promising signals followed-up in independent samples (18,063 cases and 23,207 controls). In addition to 34 known AD loci, we report here the genome-wide significant association of 31 new loci with the risk of AD. Pathway-enrichment analyses strongly indicated the involvement of gene sets related to amyloid and Tau, but also highlighted microglia, in which increased gene expression corresponds to more significant AD risk. In addition, we successfully prioritized candidate genes in the majority of our new loci, with nine being primarily expressed in microglia. Finally, we observed that a polygenic risk score generated from this new genetic landscape was strongly associated with the risk of progression from mild cognitive impairment (MCI) to dementia (4,609 MCI cases of whom 1,532 converted to dementia), independently of age and the APOE e4 allele.