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...

Objectives-i) to assess the diagnostic specificity of MRI-defined hippocampal atrophy for Alzheimer's disease (AD) among individuals with a variety of pathologically confirmed conditions associated with dementia as well as changes attributable to typical aging, and, ii) to measure correlations among pre-mortem MRI measurements of hippocampal atrophy, mental status exam performance, and the pathologic stage of AD. Methods-An un-selected series of 67 individuals participating in the Mayo Alzheimer's DiseaseResearch Center/Alzheimer's Disease Patient Registry were identified who had undergone a standardized antemortem MRI study and also post-mortem examination. Hippocampal volumes were measured from antemortem MRI. Each post-mortem specimen was assigned a pathologic diagnosis, and in addition, the severity of AD pathology was staged using the method of Braak and Braak.Results-Individuals with an isolated pathologic diagnosis of AD, hippocampal sclerosis, frontotemporal degeneration, and neurofibrillary tangle-only degeneration usually had substantial hippocampal atrophy while those with changes of typical aging did not. Among all 67 subjects, correlations (all p<0.001) were observed between hippocampal volume and Braak stage (r = −0.39), between hippocampal volume and MMSE score (r = 0.60), and between MMSE score and Braak stage (r = −0.41).Conclusions-Hippocampal atrophy, while not specific for AD, was a fairly sensitive marker of the pathologic AD stage [particularly among subjects with isolated AD pathology (r = −0.63, p = 0.001)] and consequent cognitive status.

Background: Neurofibrillary tangles (NFTs), composed of hyperphosphorylated tau proteins, are one

No abstract

In chronic liver failure, manganese accumulation is responsible for the pallidal MRI T1 hyperintensity. Pallidal copper was also elevated in affected cases, but copper does not have the paramagnetic properties to generate isolated T1 hyperintensity. Basal ganglia manganese or copper accumulation may be responsible for the parkinsonism sometimes seen in chronic liver failure. Pallidal MRI T1 hyperintensity is a biomarker of manganese overload.