GENOME-WIDE ANALYSIS OF LATE-ONSET ALZHEIMER'S DISEASE USING INTERGENERATIONAL, MULTI-TRAIT, AND CROSS-ANCE…

Assistance award details

Assistance award identifier

ASST_NON_R00AG062787_075

FAIN

R00AG062787

Recipient

UNIVERSITY OF SOUTHERN CALIFORNIA

Awarding agency

Department of Health and Human Services

Funding agency

Department of Health and Human Services

Assistance listing (CFDA)

93.866

Total obligated

$810,138

Period

Jul 1, 2019 – Mar 31, 2024

Fiscal year

2021

Place of performance state

CA

Source file

FY2021_All_Assistance_Full_20261006.zip

Description

GENOME-WIDE ANALYSIS OF LATE-ONSET ALZHEIMER'S DISEASE USING INTERGENERATIONAL, MULTI-TRAIT, AND CROSS-ANCESTRY DATA - PROJECT SUMMARY/ABSTRACT LATE-ONSET ALZHEIMER’S DISEASE (LOAD) AFFECTS A LARGE PORTION OF THE HUMAN POPULATION AND IS HIGHLY HERITABLE, THOUGH DUE TO THE DIFFICULTY OF ACQUIRING WELL-PHENTOYPED DATA, GENOME-WIDE ASSOCIATION STUDIES (GWASS) OF LOAD HAVE HAD LIMITED SUCCESS IN IDENTIFYING ASSOCIATED GENES. ADDITIONAL STATISTICAL POWER WOULD LIKELY PRODUCE MANY DISCOVERIES RELATED TO THE BIOLOGY OF LOAD, AS IT HAS FOR OTHER COMPLEX PHENOTYPES. THIS RESEARCH PLAN PROPOSES ALTERNATE DATA SOURCES AND NEW METHODS TO INCREASE THE STATISTICAL POWER IN GENETIC STUDIES OF LOAD. FIRST, BECAUSE LOAD IS DIAGNOSED LATE IN LIFE, LARGE, CROSS-SECTIONAL STUDIES CANNOT EASILY CLASSIFY INDIVIDUALS AS CASES OR CONTROLS. THIS LIMITATION CAN BE SOMEWHAT ATTENUATED USING PEDIGREE INFORMATION, AS IS DONE IN THE EXISTING METHOD, GWAX. DR. TURLEY WILL EXTEND GWAX TO ACCOUNT FOR CASE-STATUS, AGE, AND OTHER CHARACTERISTICS OF BOTH PARENTS. THESE RESULTS WILL BE META-ANALYZED WITH AVAILABLE CASE-CONTROL- BASED RESULTS USING MULTI-TRAIT ANALYSIS OF GWAS (MTAG), LEADING TO SUBSTANTIAL GAINS IN POWER AND REDUCED RISK OF BIAS DUE TO MISCLASSIFICATION OF CASES. SECOND, LOAD AND EDUCATIONAL ATTAINMENT (EA) HAVE A GENETIC CORRELATION OF -0.3, SUGGESTING THAT THEY MAY BE ASSOCIATED WITH BOTH COMMON AND UNIQUE BIOLOGICAL PATHWAYS. DR. TURLEY WILL SEEK TO BETTER UNDERSTAND LOAD BY CLASSIFYING AND ANALYZING SNPS THAT ARE EITHER JOINTLY OR UNIQUELY ASSOCIATED WITH LOAD USING BAYES-MTAG, AN EXTENSION OF MTAG THAT HE IS DEVELOPING. THIRD, A LACK OF NON-EUROPEAN GWAS COHORTS HAVE RESULTED IN POLYGENIC SCORES THAT PERFORM POORLY IN THOSE POPULATIONS. DR. TURLEY WILL DEVELOP MULTI-ANCESTRY META-ANALYSIS (MAMA), A TRANS-ETHNIC META-ANALYSIS EXTENSION OF MTAG THAT ACCOUNTS FOR DIFFERENCES IN LINKAGE DISEQUILIBRIUM AND GENETIC ARCHITECTURE ACROSS ANCESTRIES, TO IMPROVE PREDICTION OF LOAD IN NON