Genome-wide association study of Alzheimer’s disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

AbstractAlzheimer’s disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case–control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer’s Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (Aβ) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to Aβ42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-Aβ38 and CSF-Aβ40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case–control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-Aβ and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.

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Genome-wide association study of Alzheimer’s disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

10.1101/774554 ◽

2019 ◽

Cited By ~ 2

Author(s):

Shengjun Hong ◽

Dmitry Prokopenko ◽

Valerija Dobricic ◽

Fabian Kilpert ◽

Isabelle Bos ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Association Study ◽

Genome Wide Association Study ◽

Biomarker Discovery ◽

Case Control ◽

Genome Wide Association ◽

Great Promise ◽

Phenotypic Traits ◽

Genome Wide

AbstractAlzheimer’s disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer’s Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures of amyloid-beta (Aβ) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to Aβ42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-Aβ38 and CSF-Aβ40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-Aβ and -tau related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.

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P2-146: APOE 4-STRATIFIED GENOME-WIDE ASSOCIATION STUDY OF LATE-ONSET ALZHEIMER'S DISEASE IN NORTHWESTERN EUROPEANS REVEALS NOVEL SUGGESTIVE PROTECTIVE LOCI

Alzheimer s & Dementia ◽

10.1016/j.jalz.2019.06.2553 ◽

2019 ◽

Vol 15 ◽

pp. P629-P631

Author(s):

Michael E. Belloy ◽

Valerio Napolioni ◽

Yann Le Guen ◽

Yongha Kim ◽

Michael D. Greicius

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Association Study ◽

Genome Wide Association Study ◽

Late Onset ◽

Genome Wide Association ◽

Genome Wide

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Genome-Wide Association Study of CSF Levels of 59 Alzheimer's Disease Candidate Proteins: Significant Associations with Proteins Involved in Amyloid Processing and Inflammation

PLoS Genetics ◽

10.1371/journal.pgen.1004758 ◽

2014 ◽

Vol 10 (10) ◽

pp. e1004758 ◽

Cited By ~ 61

Author(s):

John S. K. Kauwe ◽

Matthew H. Bailey ◽

Perry G. Ridge ◽

Rachel Perry ◽

Mark E. Wadsworth ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Association Study ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Genome Wide ◽

Csf Levels

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Prediction of Alzheimer's disease using multi-variants from a Chinese genome-wide association study

Brain ◽

10.1093/brain/awaa364 ◽

2020 ◽

Cited By ~ 1

Author(s):

Longfei Jia ◽

Fangyu Li ◽

Cuibai Wei ◽

Min Zhu ◽

Qiumin Qu ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Association Study ◽

Predictive Models ◽

Genome Wide Association Study ◽

Disease Onset ◽

Genome Wide Association ◽

Nucleotide Polymorphisms ◽

Risk Variants ◽

Genome Wide

Abstract Previous genome-wide association studies have identified dozens of susceptibility loci for sporadic Alzheimer’s disease, but few of these loci have been validated in longitudinal cohorts. Establishing predictive models of Alzheimer’s disease based on these novel variants is clinically important for verifying whether they have pathological functions and provide a useful tool for screening of disease risk. In the current study, we performed a two-stage genome-wide association study of 3913 patients with Alzheimer’s disease and 7593 controls and identified four novel variants (rs3777215, rs6859823, rs234434, and rs2255835; Pcombined = 3.07 × 10−19, 2.49 × 10−23, 1.35 × 10−67, and 4.81 × 10−9, respectively) as well as nine variants in the apolipoprotein E region with genome-wide significance (P < 5.0 × 10−8). Literature mining suggested that these novel single nucleotide polymorphisms are related to amyloid precursor protein transport and metabolism, antioxidation, and neurogenesis. Based on their possible roles in the development of Alzheimer’s disease, we used different combinations of these variants and the apolipoprotein E status and successively built 11 predictive models. The predictive models include relatively few single nucleotide polymorphisms useful for clinical practice, in which the maximum number was 13 and the minimum was only four. These predictive models were all significant and their peak of area under the curve reached 0.73 both in the first and second stages. Finally, these models were validated using a separate longitudinal cohort of 5474 individuals. The results showed that individuals carrying risk variants included in the models had a shorter latency and higher incidence of Alzheimer’s disease, suggesting that our models can predict Alzheimer’s disease onset in a population with genetic susceptibility. The effectiveness of the models for predicting Alzheimer’s disease onset confirmed the contributions of these identified variants to disease pathogenesis. In conclusion, this is the first study to validate genome-wide association study-based predictive models for evaluating the risk of Alzheimer’s disease onset in a large Chinese population. The clinical application of these models will be beneficial for individuals harbouring these risk variants, and particularly for young individuals seeking genetic consultation.

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Genome-Wide Association Study of Brain Alzheimer’s Disease-Related Metabolic Decline as Measured by [18F] FDG-PET Imaging

Journal of Alzheimer s Disease ◽

10.3233/jad-200415 ◽

2020 ◽

Vol 77 (1) ◽

pp. 401-409

Author(s):

Rong-Ze Wang ◽

Yu-Xiang Yang ◽

Hong-Qi Li ◽

Xue-Ning Shen ◽

Shi-Dong Chen ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Association Study ◽

Fdg Pet ◽

Genome Wide Association Study ◽

Genetic Model ◽

Genome Wide Association ◽

Angular Gyrus ◽

Genome Wide ◽

18F Fdg

Background: Hypometabolism detected by fluorodeoxyglucose F18 positron emission tomography ([18F] FDG PET) is an early neuropathologic changes in Alzheimer’s disease (AD) and provides important pathologic staging information. Objective: This study aimed to discover genetic interactions that regulate longitudinal glucose metabolic decline in AD-related brain regions. Methods: A total of 586 non-Hispanic white individuals from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) 1/GO/2 cohorts that met all quality control criteria were included in this study. Genome-wide association study of glucose metabolic decline in regions of interest (ROIs) was performed with linear regression under the additive genetic model. Results: We identified two novel variants that had a strong association with longitudinal metabolic decline in different ROI. Rs4819351-A in gene 1-acylglycerol-3-phosphate O-acyltransferase 3 (AGPAT3) demonstrated reduced metabolic decline in right temporal gyrus (p = 3.97×10–8, β= –0.016), while rs13387360-T in gene LOC101928196 demonstrated reduced metabolic decline in left angular gyrus (p = 1.69×10–8, β= –0.027). Conclusion: Our results suggest two genome-wide significant SNPs (rs4819351, rs13387360) in AGPAT3 and LOC101928196 as protective loci that modulate glucose metabolic decline. These two genes should be further investigated as potential therapeutic target for neurodegeneration diseases.

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