Abstract Details
Activity Number:
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139
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Type:
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Contributed
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Date/Time:
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Monday, August 4, 2014 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract #313141
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View Presentation
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Title:
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Pleiotropic Approach Identifies Genetic Regions Missed in Single Phenotype Analyses: Example in Alzheimer's Disease (AD) Pathology
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Author(s):
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Lori B. Chibnik*+ and Charles C. White and Towfique Raj and David A. Bennett and Philip L. De Jager
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Companies:
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Brigham & Women's Hospital/Harvard Medical School and Brigham & Women's Hospital and Brigham & Women's Hospital and Rush Alzheimer's Disease Center and Brigham & Women's Hospital
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Keywords:
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pleiotropy ;
Genetics ;
Alzheimer's ;
pathology ;
ordinal regression ;
neurology
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Abstract:
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The standard univariate GWAS lacks power to identify genetic variants with small effects. By applying a pleiotropic approach, we leveraged the shared genetic architecture of pathologically driven cognitive decline to increase power to find associated variants. Using Multiphen, we simultaneously analyzed 7 pathology traits with an inverted ordinal logistic regression model genome wide, where alleles are the outcome and traits are the independent variables. Variants with p-values < 5x10-6 were further investigated in univariate analyses to elucidate traits driving the effect. The top variant is located at APOE (rs429358, p=6x10-29) driven by 5 of 7 traits. Five novel loci were identified driven by 2 to 6 traits. Two SNPs near or in genes are: rs324540 (p=1x10-7, PTPRD), driven by neurofibrillary tangles (p=4x10-6), neuritic plaque (p< 0.04), and macro strokes (p=0.07); and rs12597858 (p=2x10-6, HS3ST4), driven by 6 of 7 traits (3x10-4< p< 0.05). In sum, we discovered several genetic regions that show evidence of pleiotropic association with the pathological traits, which otherwise would have been missed with a univariate approach.
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