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      Rare Variants in APP, PSEN1 and PSEN2 Increase Risk for AD in Late-Onset Alzheimer's Disease Families

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          Abstract

          Pathogenic mutations in APP, PSEN1, PSEN2, MAPT and GRN have previously been linked to familial early onset forms of dementia. Mutation screening in these genes has been performed in either very small series or in single families with late onset AD (LOAD). Similarly, studies in single families have reported mutations in MAPT and GRN associated with clinical AD but no systematic screen of a large dataset has been performed to determine how frequently this occurs. We report sequence data for 439 probands from late-onset AD families with a history of four or more affected individuals. Sixty sequenced individuals (13.7%) carried a novel or pathogenic mutation. Eight pathogenic variants, (one each in APP and MAPT, two in PSEN1 and four in GRN) three of which are novel, were found in 14 samples. Thirteen additional variants, present in 23 families, did not segregate with disease, but the frequency of these variants is higher in AD cases than controls, indicating that these variants may also modify risk for disease. The frequency of rare variants in these genes in this series is significantly higher than in the 1,000 genome project (p = 5.09×10 −5; OR = 2.21; 95%CI = 1.49–3.28) or an unselected population of 12,481 samples (p = 6.82×10 −5; OR = 2.19; 95%CI = 1.347–3.26). Rare coding variants in APP, PSEN1 and PSEN2, increase risk for or cause late onset AD. The presence of variants in these genes in LOAD and early-onset AD demonstrates that factors other than the mutation can impact the age at onset and penetrance of at least some variants associated with AD. MAPT and GRN mutations can be found in clinical series of AD most likely due to misdiagnosis. This study clearly demonstrates that rare variants in these genes could explain an important proportion of genetic heritability of AD, which is not detected by GWAS.

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          Most cited references54

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          Prediction of human mRNA donor and acceptor sites from the DNA sequence.

          Artificial neural networks have been applied to the prediction of splice site location in human pre-mRNA. A joint prediction scheme where prediction of transition regions between introns and exons regulates a cutoff level for splice site assignment was able to predict splice site locations with confidence levels far better than previously reported in the literature. The problem of predicting donor and acceptor sites in human genes is hampered by the presence of numerous amounts of false positives: here, the distribution of these false splice sites is examined and linked to a possible scenario for the splicing mechanism in vivo. When the presented method detects 95% of the true donor and acceptor sites, it makes less than 0.1% false donor site assignments and less than 0.4% false acceptor site assignments. For the large data set used in this study, this means that on average there are one and a half false donor sites per true donor site and six false acceptor sites per true acceptor site. With the joint assignment method, more than a fifth of the true donor sites and around one fourth of the true acceptor sites could be detected without accompaniment of any false positive predictions. Highly confident splice sites could not be isolated with a widely used weight matrix method or by separate splice site networks. A complementary relation between the confidence levels of the coding/non-coding and the separate splice site networks was observed, with many weak splice sites having sharp transitions in the coding/non-coding signal and many stronger splice sites having more ill-defined transitions between coding and non-coding.
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            FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer's disease.

            Distinguishing Alzheimer's disease (AD) and frontotemporal dementia (FTD) currently relies on a clinical history and examination, but positron emission tomography with [(18)F] fluorodeoxyglucose (FDG-PET) shows different patterns of hypometabolism in these disorders that might aid differential diagnosis. Six dementia experts with variable FDG-PET experience made independent, forced choice, diagnostic decisions in 45 patients with pathologically confirmed AD (n = 31) or FTD (n = 14) using five separate methods: (1) review of clinical summaries, (2) a diagnostic checklist alone, (3) summary and checklist, (4) transaxial FDG-PET scans and (5) FDG-PET stereotactic surface projection (SSP) metabolic and statistical maps. In addition, we evaluated the effect of the sequential review of a clinical summary followed by SSP. Visual interpretation of SSP images was superior to clinical assessment and had the best inter-rater reliability (mean kappa = 0.78) and diagnostic accuracy (89.6%). It also had the highest specificity (97.6%) and sensitivity (86%), and positive likelihood ratio for FTD (36.5). The addition of FDG-PET to clinical summaries increased diagnostic accuracy and confidence for both AD and FTD. It was particularly helpful when raters were uncertain in their clinical diagnosis. Visual interpretation of FDG-PET after brief training is more reliable and accurate in distinguishing FTD from AD than clinical methods alone. FDG-PET adds important information that appropriately increases diagnostic confidence, even among experienced dementia specialists.
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              APOE and Alzheimer disease: a major gene with semi-dominant inheritance.

              Apolipoprotein E (APOE) dependent lifetime risks (LTRs) for Alzheimer Disease (AD) are currently not accurately known and odds ratios alone are insufficient to assess these risks. We calculated AD LTR in 7351 cases and 10 132 controls from Caucasian ancestry using Rochester (USA) incidence data. At the age of 85 the LTR of AD without reference to APOE genotype was 11% in males and 14% in females. At the same age, this risk ranged from 51% for APOE44 male carriers to 60% for APOE44 female carriers, and from 23% for APOE34 male carriers to 30% for APOE34 female carriers, consistent with semi-dominant inheritance of a moderately penetrant gene. Using PAQUID (France) incidence data, estimates were globally similar except that at age 85 the LTRs reached 68 and 35% for APOE 44 and APOE 34 female carriers, respectively. These risks are more similar to those of major genes in Mendelian diseases, such as BRCA1 in breast cancer, than those of low-risk common alleles identified by recent GWAS in complex diseases. In addition, stratification of our data by age groups clearly demonstrates that APOE4 is a risk factor not only for late-onset but for early-onset AD as well. Together, these results urge a reappraisal of the impact of APOE in Alzheimer disease.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                1 February 2012
                : 7
                : 2
                : e31039
                Affiliations
                [1 ]Department of Psychiatry and Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University, St. Louis, Missouri, United States of America
                [2 ]Department of Genetics, Washington University, St. Louis, Missouri, United States of America
                [3 ]Department of Medical and Molecular Genetics, Indiana University, Indianapolis, United States of America
                [4 ]Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University College of Physicians and Surgeons, New York, New York, United States of America
                [5 ]VA Medical Center and Departments of Neurology and Medicine, University of Washington, Seattle, Washington, United States of America
                [6 ]Department of Neurology, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
                [7 ]Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America
                [8 ]Department of Neurology, Mayo Clinic, Jacksonville, Florida, United States of America
                [9 ]Genetics, GlaxoSmithKline, Research Triangle Park, North Carolina, United States of America
                Oslo University Hospital, Norway
                Author notes

                Conceived and designed the experiments: CC R. Mayeux AG. Performed the experiments: CC SC KM. Analyzed the data: CC SC KM FV Robi Mitra. Contributed reagents/materials/analysis tools: KF JW TB RD TF BB NG PST ML ME R. Mayeux. Wrote the paper: CC AG.

                ¤ For a list of the members of the NIA-LOAD/NCRAD Family Study Consortium please see the Acknowledgments section.

                Article
                PONE-D-11-25311
                10.1371/journal.pone.0031039
                3270040
                22312439
                8cbb806a-174e-461f-a988-47c72b423de0
                Cruchaga et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 28 November 2011
                : 30 December 2011
                Page count
                Pages: 10
                Categories
                Research Article
                Biology
                Computational Biology
                Population Genetics
                Genetics
                Human Genetics
                Population Genetics
                Medicine
                Clinical Genetics
                Neurology
                Dementia

                Uncategorized
                Uncategorized

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