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The cerebral deposition of Aβ42, a neurotoxic proteolytic derivate of amyloid precursor protein (APP), is a central event in Alzheimer's disease (AD)(Amyloid hypothesis). Given the key role of APP-Aβ metabolism in AD pathogenesis, we selected 29 genes involved in APP processing, Aβ degradation and clearance. We then used exome and genome sequencing to investigate the single independent (single-variant association test) and cumulative (gene-based association test) effect of coding variants in these genes as potential susceptibility factors for AD, in a cohort composed of 332 sporadic and mainly late-onset AD cases and 676 elderly controls from North America and the UK. Our study shows that common coding variability in these genes does not play a major role for the disease development. In the single-variant association analysis, the main hits, none of which statistically significant after multiple testing correction (1.9e-4

BackgroundPotentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR).Methods and findingsWe used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, NSNPs = 49), fasting glucose (NSNPs = 36), insulin resistance (NSNPs = 10), body mass index (BMI, NSNPs = 32), total cholesterol (NSNPs = 73), HDL-cholesterol (NSNPs = 71), LDL-cholesterol (NSNPs = 57), triglycerides (NSNPs = 39), systolic blood pressure (SBP, NSNPs = 24), smoking initiation (NSNPs = 1), smoking quantity (NSNPs = 3), university completion (NSNPs = 2), and years of education (NSNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP-AD associations from the International Genomics of Alzheimer's Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62-0.91]; p = 3.4 × 10(-3)). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10(-8)). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51-0.89]; p = 6.5 × 10(-3)), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses.ConclusionsInherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure--or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications--may reduce AD risk.

BackgroundAlthough altered lipid metabolism has been extensively implicated in the pathogenesis of Alzheimer disease (AD) through cell biological, epidemiological, and genetic studies, the molecular mechanisms linking cholesterol and AD pathology are still not well understood and contradictory results have been reported. We have used a Mendelian randomization approach to dissect the causal nature of the association between circulating lipid levels and late onset AD (LOAD) and test the hypothesis that genetically raised lipid levels increase the risk of LOAD.Methods and findingsWe included 3,914 patients with LOAD, 1,675 older individuals without LOAD, and 4,989 individuals from the general population from six genome wide studies drawn from a white population (total n=10,578). We constructed weighted genotype risk scores (GRSs) for four blood lipid phenotypes (high-density lipoprotein cholesterol [HDL-c], low-density lipoprotein cholesterol [LDL-c], triglycerides, and total cholesterol) using well-established SNPs in 157 loci for blood lipids reported by Willer and colleagues (2013). Both full GRSs using all SNPs associated with each trait at pConclusionsGenetic predisposition to increased blood cholesterol and triglyceride lipid levels is not associated with elevated LOAD risk. The observed epidemiological associations between abnormal lipid levels and LOAD risk could therefore be attributed to the result of biological pleiotropy or could be secondary to LOAD. Limitations of this study include the small proportion of lipid variance explained by the GRS, biases in case-control ascertainment, and the limitations implicit to Mendelian randomization studies. Future studies should focus on larger LOAD datasets with longitudinal sampled peripheral lipid measures and other markers of lipid metabolism, which have been shown to be altered in LOAD. Please see later in the article for the Editors' Summary.

BACKGROUND:Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. PRINCIPAL FINDINGS:In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10-6) and 14 (IGHV1-67 p = 7.9×10-8) which indexed novel susceptibility loci. SIGNIFICANCE:The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.

BACKGROUND: Genetic studies are challenging in many complex diseases, particularly those with limited diagnostic certainty, low prevalence or of old age. The result is that genes may be reported as disease-causing with varying levels of evidence, and in some cases, the data may be so limited as to be indistinguishable from chance findings. When there are large numbers of such genes, an objective method for ranking the evidence is useful. Using the neurodegenerative and complex disease amyotrophic lateral sclerosis (ALS) as a model, and the disease-specific database ALSoD, the objective is to develop a method using publicly available data to generate a credibility score for putative disease-causing genes. METHODS: Genes with at least one publication suggesting involvement in adult onset familial ALS were collated following an exhaustive literature search. SQL was used to generate a score by extracting information from the publications and combined with a pathogenicity analysis using bioinformatics tools. The resulting score allowed us to rank genes in order of credibility. To validate the method, we compared the objective ranking with a rank generated by ALS genetics experts. Spearman's Rho was used to compare rankings generated by the different methods. RESULTS: The automated method ranked ALS genes in the following order: TARDBP, FUS, ANG, SPG11, NEFH, OPTN, ALS2, SETX, FIG4, VAPB, DCTN1, TAF15, VCP, DAO. This compared very well to the ranking of ALS genetics experts, with Spearman's Rho of 0.69 (P = 0.009). CONCLUSION: We have presented an automated method for scoring the level of evidence for a gene being disease-causing. In developing the method we have used the model disease ALS, but it could equally be applied to any disease in which there is genotypic uncertainty.

Nicastrin is an obligatory component of the γ-secretase; the enzyme complex that leads to the production of Aβ fragments critically central to the pathogenesis of Alzheimer's disease (AD). Analyses of the effects of common variation in this gene on risk for late onset AD have been inconclusive. We investigated the effect of rare variation in the coding regions of the Nicastrin gene in a cohort of AD patients and matched controls using an innovative pooling approach and next generation sequencing. Five SNPs were identified and validated by individual genotyping from 311 cases and 360 controls. Association analysis identified a non-synonymous rare SNP (N417Y) with a statistically higher frequency in cases compared to controls in the Greek population (OR 3.994, CI 1.105-14.439, p = 0.035). This finding warrants further investigation in a larger cohort and adds weight to the hypothesis that rare variation explains some of genetic heritability still to be identified in Alzheimer's disease.

Transmissible Spongiform Encephalopathies (TSEs) are a group of progressive fatal neurodegenerative disorders, triggered by abnormal folding of the endogenous prion protein molecule. The encoding gene is a major biological factor influencing the length of the asymptomatic period after infection. It remains unclear the extent to which the variation between quantitative trait loci (QTLs) reported in mouse models is due to methodological differences between approaches or genuine differences between traits. With this in mind, our approach to identifying genetic factors has sought to extend the linkage mapping approach traditionally applied, to a series of additional traits, while minimising methodological variability between them. Our approach allows estimations of heritability to be derived, as well as predictions to be made about possible existence of genetic overlap between the various traits.Our data indicate a surprising degree of heritability (up to 60%). Correlations between traits are also identified. A series of QTLs on chromosomes 1, 2, 3, 4, 6, 11 and 18 accompany our heritability estimates. However, only a locus on chromosome 11 has a general effect across all 4 models explored.We have achieved some success in detecting novel and pre-existing QTLs associated with incubation time. However, aside from the general effects described, the model-specific nature of the broader host genetic architecture has also been brought into clearer focus. This suggests that genetic overlap can only partially account for the general heritability of incubation time when factors, such as the nature of the TSE agent and the route of administration are considered. This point is highly relevant to vCJD (a potential threat to public health) where the route of primary importance is oral, while the QTLs being sought derive exclusively from studies of the ic route. Our results highlight the limitations of a single-model approach to QTL-mapping of TSEs.