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F4‐02‐01: Neurosin Levels in CSF as Potential Marker for Clinical Differentiation Between Alzheimer's Disease and Dementia With Lewy Bodies
Author(s) -
Nielsen Henrietta M.,
Wennström Malin,
Hansson Oskar H.,
Londos Elisabet,
Minthon Lennart
Publication year - 2010
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2010.08.004
Subject(s) - dementia with lewy bodies , pathogenesis , senile plaques , parkinson's disease , dementia , medicine , alzheimer's disease , cerebrospinal fluid , pathology , disease , lewy body , endocrinology
The primary focus for identifying Alzheimer’s disease (AD) risk genes over the five years has tested the common disease, common variant (CDCV) hypothesis, in part, because the tools to do so (e.g., dbSNP, the hapmap, largescale SNP chips) were available. These tools permit genome-wide association studies (GWAS), which have been applied to increasingly larger datasets and are currently being further exploited by large AD consortia in an effort to cull the maximum information from the CDCV hypothesis. While common variation clearly plays a role in AD (e.g. APOE, CR1, PICALM, CLU); there is a growing realization that the CDCV hypothesis does not explain all the AD genetic effect. One alternative hypothesis invokes multiple rare variants (RVs), in one or more genes, each with stronger individual risk effects than CDCV loci. Only recently have new platforms of next-generation sequencing (NGS) become available to efficiently test for the existence of RV genes. The RV hypothesis is an important approach to dissecting the etiology of AD, has not been explored in detail, and is timely given the growing concern over the missing heritability associated with GWAS. Family data is the ideal substrate for identifying rare but strong AD risk effects. However, in the field’s excitement to harvest the most from the GWAS approaches, many abandoned the ascertainment of family data in favor of large data sets of cases and controls. With the advent of these new technologies, family data is once again highly desirable and useful. Families that have been studied over multiple generations are the perfect medium for these new approaches. High density SNP genotyping on extended late onset AD families can be used to extract segregation information identifying the minimum shared genomic space among relatives that likely contains the AD gene(s) of interest in each family. If one or more rare variants are acting in a family, they will lie within these regions and may be identified using NGS. This approach represents the next step in the quest to identify the remaining AD genes.