Whole genome and exome sequence data is currently being generated for population- and family-based studiestoelucidatetheinvolvementofrarevariantsintheetiologyofcomplextraitsincludingonAlzheimer?s Disease(AD).Althoughmanyrarevariantpopulation-basedassociationmethodshavebeendevelopedthere are extremely few methods to study families. Analyzing families to detect complex trait associations can be advantageousbecausesusceptibilityvariantsthatsegregateinfamiliescanhavelargereffectsizesthanthose found in sporadic cases, thereby increasing the power for detection, while avoiding spurious findings due to populationsubstructureandadmixture,thatcanplaguerarevariantpopulation-basedstudies.Forrarevariant complextraitanalysis,wewilldevelopfamily-basedassociationandlinkagemethods.Rarevariantmixedmodel association methods will also be developed for analysis of related and unrelated individuals. All developed methodswillbeusedtostudylate-onsetAD;?analyzingwholegenomeandexomesequencedatageneratedon families,casesandcontrolstodiscovernovelgenesandelucidatemechanismsunderlyingAD.ADstatus,as wellasquantitativetraitsageofonset,memoryandmemorydeclinewillbeanalyzed.Thedevelopedmethods willbeimplementedinourSEQSparksoftwaretoallowforrapidanalysisthroughparallelprocessing.Completion ofthisstudywilldevelopmethodsandsoftwaretoelucidatecomplextraitetiology.Applicationofthesemethods, analyzingexistingADsequencedatafromtheAlzheimer?sDiseaseSequencingProject(ADSP)andtheNational InstituteofAgingLate-onsetAlzheimer?sDisease(NIALOAD)study,willelucidateabetterunderstandingoflate- onsetADetiologyandriskfactors.IdentifyingsusceptibilityvariantsforADisthefirststepinriskpredictionand developmentoftreatmentswithhighefficacy.Thisstudyhashighpublichealthsignificance,sincelate-onsetAD causesconsiderablemorbiditywithintheelderlyandADprevalenceisincreasingduetoanagingpopulation.

Public Health Relevance

Novel methods will be developed to perform rare variant linkage and association analyses of binary and quantitative traits for families and population data. The developed methods will be used to analyze late-onset Alzheimer?s Disease families, cases and controls from the Alzheimer?sDiseaseSequencingProject(ADSP)andtheNationalInstituteofAgingLate-onset Alzheimer?s Disease (NIALOAD) study. This study will bring about a deeper understanding of thegeneticetiologyoflate-onsetAlzheimer?sDisease.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
1R01AG058131-01
Application #
9434732
Study Section
Biomedical Computing and Health Informatics Study Section (BCHI)
Program Officer
Miller, Marilyn
Project Start
2018-04-01
Project End
2023-01-31
Budget Start
2018-04-01
Budget End
2019-01-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Baylor College of Medicine
Department
Genetics
Type
Schools of Medicine
DUNS #
051113330
City
Houston
State
TX
Country
United States
Zip Code
77030