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      Genome-wide association meta-analysis of neuropathologic features of Alzheimer's disease and related dementias.

      Author(s): 1 , 1 , 2 , 1 , 3 , 4 , 3 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 14 , 1 , 15 , 16 , 17 , 7 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 1 , 25 , 26 , 27 , 26 , 28
      Publication date (Electronic):
      Journal: PLoS genetics
      Publisher: Public Library of Science (PLoS)

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          Abstract

          Alzheimer's disease (AD) and related dementias are a major public health challenge and present a therapeutic imperative for which we need additional insight into molecular pathogenesis. We performed a genome-wide association study and analysis of known genetic risk loci for AD dementia using neuropathologic data from 4,914 brain autopsies. Neuropathologic data were used to define clinico-pathologic AD dementia or controls, assess core neuropathologic features of AD (neuritic plaques, NPs; neurofibrillary tangles, NFTs), and evaluate commonly co-morbid neuropathologic changes: cerebral amyloid angiopathy (CAA), Lewy body disease (LBD), hippocampal sclerosis of the elderly (HS), and vascular brain injury (VBI). Genome-wide significance was observed for clinico-pathologic AD dementia, NPs, NFTs, CAA, and LBD with a number of variants in and around the apolipoprotein E gene (APOE). GalNAc transferase 7 (GALNT7), ATP-Binding Cassette, Sub-Family G (WHITE), Member 1 (ABCG1), and an intergenic region on chromosome 9 were associated with NP score; and Potassium Large Conductance Calcium-Activated Channel, Subfamily M, Beta Member 2 (KCNMB2) was strongly associated with HS. Twelve of the 21 non-APOE genetic risk loci for clinically-defined AD dementia were confirmed in our clinico-pathologic sample: CR1, BIN1, CLU, MS4A6A, PICALM, ABCA7, CD33, PTK2B, SORL1, MEF2C, ZCWPW1, and CASS4 with 9 of these 12 loci showing larger odds ratio in the clinico-pathologic sample. Correlation of effect sizes for risk of AD dementia with effect size for NFTs or NPs showed positive correlation, while those for risk of VBI showed a moderate negative correlation. The other co-morbid neuropathologic features showed only nominal association with the known AD loci. Our results discovered new genetic associations with specific neuropathologic features and aligned known genetic risk for AD dementia with specific neuropathologic changes in the largest brain autopsy study of AD and related dementias.

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          Most cited references29

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          PLINK: a tool set for whole-genome association and population-based linkage analyses.

          Shaun Purcell, Benjamin M. Neale, Kathe Todd-Brown … (2007)
          Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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            Neuropathological stageing of Alzheimer-related changes

            H Braak, E Braak (1991)
            Eighty-three brains obtained at autopsy from nondemented and demented individuals were examined for extracellular amyloid deposits and intraneuronal neurofibrillary changes. The distribution pattern and packing density of amyloid deposits turned out to be of limited significance for differentiation of neuropathological stages. Neurofibrillary changes occurred in the form of neuritic plaques, neurofibrillary tangles and neuropil threads. The distribution of neuritic plaques varied widely not only within architectonic units but also from one individual to another. Neurofibrillary tangles and neuropil threads, in contrast, exhibited a characteristic distribution pattern permitting the differentiation of six stages. The first two stages were characterized by an either mild or severe alteration of the transentorhinal layer Pre-alpha (transentorhinal stages I-II). The two forms of limbic stages (stages III-IV) were marked by a conspicuous affection of layer Pre-alpha in both transentorhinal region and proper entorhinal cortex. In addition, there was mild involvement of the first Ammon's horn sector. The hallmark of the two isocortical stages (stages V-VI) was the destruction of virtually all isocortical association areas. The investigation showed that recognition of the six stages required qualitative evaluation of only a few key preparations.
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              Principal components analysis corrects for stratification in genome-wide association studies.

              Alkes L. Price, Nick Patterson, Robert Plenge … (2006)
              Population stratification--allele frequency differences between cases and controls due to systematic ancestry differences-can cause spurious associations in disease studies. We describe a method that enables explicit detection and correction of population stratification on a genome-wide scale. Our method uses principal components analysis to explicitly model ancestry differences between cases and controls. The resulting correction is specific to a candidate marker's variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. Our simple, efficient approach can easily be applied to disease studies with hundreds of thousands of markers.
              Article 0 comments Cited 1283 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (iso-abbrev): PLoS Genet.
                Title: PLoS genetics
                Publisher: Public Library of Science (PLoS)
                ISSN (Electronic): 1553-7404
                ISSN (Print): 1553-7390
                Publication date (Electronic): Sep 2014
                Volume: 10
                Issue: 9
                Affiliations
                [1 ] John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, United States of America.
                [2 ] Division of Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
                [3 ] Neurogenomics Division, Translational Genomics Research Institute, Phoenix, Arizona, United States of America.
                [4 ] Department of Psychiatry & Behavioral Sciences, University of Miami, Miami, Florida, United States of America.
                [5 ] Department of Molecular Neuroscience, University College London, London, United Kingdom.
                [6 ] New York Brain Bank, Columbia University, New York, New York, United States of America.
                [7 ] Department of Neuroscience, Mayo Clinic College of Medicine, Jacksonville, Florida, United States of America.
                [8 ] Department of Neurological Sciences, Rush University, Chicago, Illinois, United States of America.
                [9 ] Department of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Harvard Medical School, Boston, Massachusetts, United States of America.
                [10 ] Group Health Research Institute, Seattle, Washington, United States of America.
                [11 ] Department of Medicine, University of Washington, Seattle, Washington, United States of America.
                [12 ] Department of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania, United States of America.
                [13 ] Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America.
                [14 ] Department of Neurology, University of Miami, Miami, Florida, United States of America.
                [15 ] Department of Psychiatry, Vanderbilt University, Nashville, Tennessee, United States of America.
                [16 ] Department of Psychiatry, Mount Sinai Hospital, New York, New York, United States of America.
                [17 ] Department of Neurology, Oregon Health & Science University, Portland, Oregon, United States of America.
                [18 ] Biomedical Genetics, Boston University School of Public Health, Boston, Massachusetts, United States of America.
                [19 ] C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America.
                [20 ] Department of Pathology and Laboratory Medicine, Indiana University, Indianapolis, Indiana, United States of America.
                [21 ] Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America.
                [22 ] Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
                [23 ] Department of Epidemiology, National Alzheimer's Coordinating Center, University of Washington, Seattle, Washington, United States of America.
                [24 ] Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, United States of America.
                [25 ] Department of Neurological Sciences, Rush University, Chicago, Illinois, United States of America; Department of Pathology (Neuropathology), Rush University Medical Center, Chicago, Illinois, United States of America.
                [26 ] Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
                [27 ] Arizona Alzheimer's Consortium, Banner Alzheimer's Institute, Phoenix, Arizona, United States of America; Department of Psychiatry, University of Arizona, Phoenix, Arizona, United States of America.
                [28 ] Department of Pathology, University of Washington, Seattle, Washington, United States of America.
                Article
                Publisher Item ID: PGENETICS-D-14-00298
                DOI: 10.1371/journal.pgen.1004606
                PMC ID: 4154667
                PubMed ID: 25188341
                SO-VID: 0895397a-ed0f-469e-9c4b-f7b0edea6aed
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