A novel age-informed approach for genetic association analysis in Alzheimer’s disease

Abstract Background Many Alzheimer’s disease (AD) genetic association studies disregard age or incorrectly account for it, hampering variant discovery. Methods Using simulated data, we compared the statistical power of several models: logistic regression on AD diagnosis adjusted and not adjusted for age; linear regression on a score integrating case-control status and age; and multivariate Cox regression on age-at-onset. We applied these models to real exome-wide data of 11,127 sequenced individuals (54% cases) and replicated suggestive associations in 21,631 genotype-imputed individuals (51% cases). Results Modeling variable AD risk across age results in 5–10% statistical power gain compared to logistic regression without age adjustment, while incorrect age adjustment leads to critical power loss. Applying our novel AD-age score and/or Cox regression, we discovered and replicated novel variants associated with AD on KIF21B, USH2A, RAB10, RIN3, and TAOK2 genes. Conclusion Our AD-age score provides a simple means for statistical power gain and is recommended for future AD studies.

Download Full-text

A novel age-informed approach for genetic association analysis in Alzheimer’s disease

10.1101/2021.01.05.21249292 ◽

2021 ◽

Author(s):

Yann Le Guen ◽

Michael E. Belloy ◽

Valerio Napolioni ◽

Sarah J. Eger ◽

Gabriel Kennedy ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Logistic Regression ◽

Genetic Association ◽

Statistical Power ◽

Cox Regression ◽

Association Studies ◽

Age At Onset ◽

Simulated Data ◽

Power Gain

ABSTRACTIntroductionMany Alzheimer’s disease (AD) genetic association studies disregard age or incorrectly account for it, hampering variant discovery.MethodUsing simulated data, we compared the statistical power of several models: logistic regression on AD diagnosis adjusted and not adjusted for age; linear regression on a score integrating case-control status and age; and multivariate Cox regression on age-at-onset. We applied these models to real exome-wide data of 11,127 sequenced individuals (54% cases) and replicated suggestive associations in 21,631 genotype-imputed individuals (51% cases).ResultsModelling variable AD risk across age results in 10-20% statistical power gain compared to logistic regression without age adjustment, while incorrect age adjustment leads to critical power loss. Applying our novel AD-age score and/or Cox regression, we discovered and replicated novel variants associated with AD on KIF21B, USH2A, RAB10, RIN3 and TAOK2 genes.DiscussionOur AD-age score provides a simple means for statistical power gain and is recommended for future AD studies.

Download Full-text

Fast Algorithms for Conducting Large-Scale GWAS of Age-at-Onset Traits Using Cox Mixed-Effects Models

Genetics ◽

10.1534/genetics.119.302940 ◽

2020 ◽

Vol 215 (1) ◽

pp. 41-58 ◽

Cited By ~ 4

Author(s):

Liang He ◽

Alexander M. Kulminski

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Statistical Power ◽

Large Scale ◽

Cox Model ◽

Association Studies ◽

Age At Onset ◽

Mixed Effects ◽

Mixed Effects Models ◽

Genome Wide Association Studies

Age-at-onset is one of the critical traits in cohort studies of age-related diseases. Large-scale genome-wide association studies (GWAS) of age-at-onset traits can provide more insights into genetic effects on disease progression and transitions between stages. Moreover, proportional hazards (or Cox) regression models can achieve higher statistical power in a cohort study than a case-control trait using logistic regression. Although mixed-effects models are widely used in GWAS to correct for sample dependence, application of Cox mixed-effects models (CMEMs) to large-scale GWAS is so far hindered by intractable computational cost. In this work, we propose COXMEG, an efficient R package for conducting GWAS of age-at-onset traits using CMEMs. COXMEG introduces fast estimation algorithms for general sparse relatedness matrices including, but not limited to, block-diagonal pedigree-based matrices. COXMEG also introduces a fast and powerful score test for dense relatedness matrices, accounting for both population stratification and family structure. In addition, COXMEG generalizes existing algorithms to support positive semidefinite relatedness matrices, which are common in twin and family studies. Our simulation studies suggest that COXMEG, depending on the structure of the relatedness matrix, is orders of magnitude computationally more efficient than coxme and coxph with frailty for GWAS. We found that using sparse approximation of relatedness matrices yielded highly comparable results in controlling false-positive rate and retaining statistical power for an ethnically homogeneous family-based sample. By applying COXMEG to a study of Alzheimer’s disease (AD) with a Late-Onset Alzheimer’s Disease Family Study from the National Institute on Aging sample comprising 3456 non-Hispanic whites and 287 African Americans, we identified the APOE ε4 variant with strong statistical power (P = 1e−101), far more significant than that reported in a previous study using a transformed variable and a marginal Cox model. Furthermore, we identified novel SNP rs36051450 (P = 2e−9) near GRAMD1B, the minor allele of which significantly reduced the hazards of AD in both genders. These results demonstrated that COXMEG greatly facilitates the application of CMEMs in GWAS of age-at-onset traits.

Download Full-text

Impact of home visit capacity on genetic association studies of late-onset Alzheimer's disease

Alzheimer s & Dementia ◽

10.1016/j.jalz.2017.01.012 ◽

2017 ◽

Vol 13 (8) ◽

pp. 933-939 ◽

Cited By ~ 2

Author(s):

David W. Fardo ◽

Laura E. Gibbons ◽

Shubhabrata Mukherjee ◽

M. Maria Glymour ◽

Wayne McCormick ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Genetic Association ◽

Home Visit ◽

Late Onset ◽

Association Studies ◽

Genetic Association Studies

Download Full-text

Genetic association studies in Alzheimer's disease research: challenges and opportunities

Statistics in Medicine ◽

10.1002/sim.1706 ◽

2004 ◽

Vol 23 (2) ◽

pp. 169-178 ◽

Cited By ~ 11

Author(s):

Steven D. Edland ◽

Susan Slager ◽

Matthew Farrer

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Genetic Association ◽

Association Studies ◽

Genetic Association Studies ◽

Disease Research ◽

Research Challenges ◽

Challenges And Opportunities

Download Full-text

Hidden heterogeneity in Alzheimer's disease: Insights from genetic association studies and other analyses

Experimental Gerontology ◽

10.1016/j.exger.2017.10.020 ◽

2018 ◽

Vol 107 ◽

pp. 148-160 ◽

Cited By ~ 18

Author(s):

Anatoliy I. Yashin ◽

Fang Fang ◽

Mikhail Kovtun ◽

Deqing Wu ◽

Matt Duan ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Genetic Association ◽

Association Studies ◽

Genetic Association Studies

Download Full-text

P2-089: Impact of Home Visit Capacity on Genetic Association Studies of Late-Onset Alzheimer’s Disease

Alzheimer s & Dementia ◽

10.1016/j.jalz.2016.06.1294 ◽

2016 ◽

Vol 12 ◽

pp. P643-P644

Author(s):

David W. Fardo ◽

Laura E. Gibbons ◽

Shubhabrata Mukherjee ◽

M. Maria Glymour ◽

Wayne McCormick ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Genetic Association ◽

Home Visit ◽

Late Onset ◽

Association Studies ◽

Genetic Association Studies

Download Full-text

Genomics and Functional Genomics of Alzheimer’s Disease

Neurotherapeutics ◽

10.1007/s13311-021-01152-0 ◽

2021 ◽

Author(s):

M. Ilyas Kamboh

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Functional Genomics ◽

Early Onset ◽

Late Onset ◽

Association Studies ◽

Age At Onset ◽

Significant Risk ◽

Major Public Health Problem ◽

Genome Wide Association Studies

AbstractAlzheimer’s disease (AD) is a complex and multifactorial neurodegenerative disease. Due to its long clinical course and lack of an effective treatment, AD has become a major public health problem in the USA and worldwide. Due to variation in age-at-onset, AD is classified into early-onset (< 60 years) and late-onset (≥ 60 years) forms with early-onset accounting for only 5–10% of all cases. With the exception of a small number of early-onset cases that are afflicted because of high penetrant single gene mutations in APP, PSEN1, and PSEN2 genes, AD is genetically heterogeneous, especially the late-onset form having a polygenic or oligogenic risk inheritance. Since the identification of APOE as the most significant risk factor for late-onset AD in 1993, the path to the discovery of additional AD risk genes had been arduous until 2009 when the use of large genome-wide association studies opened up the discovery gateways that led the identification of ~ 95 additional risk loci from 2009 to early 2022. This article reviews the history of AD genetics followed by the potential molecular pathways and recent application of functional genomics methods to identify the causal AD gene(s) among the many genes that reside within a single locus. The ultimate goal of integrating genomics and functional genomics is to discover novel pathways underlying the AD pathobiology in order to identify drug targets for the therapeutic treatment of this heterogeneous disorder.

Download Full-text

Sex differences in the genetic predictors of Alzheimer’s pathology

Brain ◽

10.1093/brain/awz206 ◽

2019 ◽

Vol 142 (9) ◽

pp. 2581-2589 ◽

Cited By ~ 13

Author(s):

Logan Dumitrescu ◽

Lisa L Barnes ◽

Madhav Thambisetty ◽

Gary Beecham ◽

Brian Kunkle ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Sex Differences ◽

Disease Risk ◽

Association Studies ◽

Age At Onset ◽

Genome Wide Association Studies ◽

Genetic Associations ◽

Data Repositories ◽

Genome Wide

Abstract Autopsy measures of Alzheimer’s disease neuropathology have been leveraged as endophenotypes in previous genome-wide association studies (GWAS). However, despite evidence of sex differences in Alzheimer’s disease risk, sex-stratified models have not been incorporated into previous GWAS analyses. We looked for sex-specific genetic associations with Alzheimer’s disease endophenotypes from six brain bank data repositories. The pooled dataset included 2701 males and 3275 females, the majority of whom were diagnosed with Alzheimer’s disease at autopsy (70%). Sex-stratified GWAS were performed within each dataset and then meta-analysed. Loci that reached genome-wide significance (P < 5 × 10−8) in stratified models were further assessed for sex interactions. Additional analyses were performed in independent datasets leveraging cognitive, neuroimaging and CSF endophenotypes, along with age-at-onset data. Outside of the APOE region, one locus on chromosome 7 (rs34331204) showed a sex-specific association with neurofibrillary tangles among males (P = 2.5 × 10−8) but not females (P = 0.85, sex-interaction P = 2.9 × 10−4). In follow-up analyses, rs34331204 was also associated with hippocampal volume, executive function, and age-at-onset only among males. These results implicate a novel locus that confers male-specific protection from tau pathology and highlight the value of assessing genetic associations in a sex-specific manner.

Download Full-text