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[Preprint]. 2023 Aug 29:2023.08.28.23294631.

doi: 10.1101/2023.08.28.23294631.

Key variants via Alzheimer's Disease Sequencing Project whole genome sequence data

Yanbing Wang¹, Chloé Sarnowski^{1

2}, Honghuang Lin³, Achilleas N Pitsillides¹, Nancy L Heard-Costa^{1

4}, Seung Hoan Choi¹, Dongyu Wang¹, Joshua C Bis⁵, Elizabeth E Blue^{6

7}; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Eric Boerwinkle², Philip L De Jager^{8

9}, Myriam Fornage^{2

10}, Ellen M Wijsman¹¹, Sudha Seshadri^{4

12

13}, Josée Dupuis^{1

14}, Gina M Peloso¹, Anita L DeStefano^{1

4}; Alzheimer’s Disease Sequencing Project (ADSP)

Affiliations

¹ Department of Biostatistics, Boston University, School of Public Health, Boston, MA, USA.
² Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
³ Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA.
⁴ The Framingham Heart Study, Framingham, MA, USA.
⁵ Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
⁶ Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA, USA.
⁷ Brotman Baty Institute, Seattle, WA, USA.
⁸ Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.
⁹ Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA.
¹⁰ Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA.
¹¹ Div. of Medical Genetics and Dept. Biostatistics Statistical Genetics Lab, University of Washington, Seattle, WA, USA.
¹² Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
¹³ Boston University School of Medicine, Department of Neurology, Boston, MA, USA.
¹⁴ Department of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill University, Montreal, Canada.

PMID: 37693453
PMCID: PMC10491364
DOI: 10.1101/2023.08.28.23294631

Key variants via Alzheimer's Disease Sequencing Project whole genome sequence data

Yanbing Wang et al. medRxiv. 2023.

[Preprint]. 2023 Aug 29:2023.08.28.23294631.

doi: 10.1101/2023.08.28.23294631.

Authors

Affiliations

¹ Department of Biostatistics, Boston University, School of Public Health, Boston, MA, USA.
² Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
³ Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA.
⁴ The Framingham Heart Study, Framingham, MA, USA.
⁵ Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
⁶ Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA, USA.
⁷ Brotman Baty Institute, Seattle, WA, USA.
⁸ Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.
⁹ Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA.
¹⁰ Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA.
¹¹ Div. of Medical Genetics and Dept. Biostatistics Statistical Genetics Lab, University of Washington, Seattle, WA, USA.
¹² Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
¹³ Boston University School of Medicine, Department of Neurology, Boston, MA, USA.
¹⁴ Department of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill University, Montreal, Canada.

PMID: 37693453
PMCID: PMC10491364
DOI: 10.1101/2023.08.28.23294631

Update in

Key variants via the Alzheimer's Disease Sequencing Project whole genome sequence data.
Wang Y, Sarnowski C, Lin H, Pitsillides AN, Heard-Costa NL, Choi SH, Wang D, Bis JC, Blue EE; Alzheimer's Disease Neuroimaging Initiative (ADNI); Boerwinkle E, De Jager PL, Fornage M, Wijsman EM, Seshadri S, Dupuis J, Peloso GM, DeStefano AL; Alzheimer's Disease Sequencing Project (ADSP). Wang Y, et al. Alzheimers Dement. 2024 May;20(5):3290-3304. doi: 10.1002/alz.13705. Epub 2024 Mar 21. Alzheimers Dement. 2024. PMID: 38511601 Free PMC article.

Abstract

Introduction: Genome-wide association studies (GWAS) have identified loci associated with Alzheimer's disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci.

Methods: We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases=2,184, N controls=2,383) and targeted analyses in sub-populations using WGS data from the Alzheimer's Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants.

Results: Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses.

Discussion: This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS.

Keywords: Alzheimer’s disease; Association Analyses; Diverse Populations; Genome Wide Association Study; Single Nucleotide Variations; Whole Genome Sequencing.

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Conflict of interest statement

Disclosures The authors do not have declarations of interest to report. The funding sources of this study had no role in the study design, the collection, the analysis or the interpretation of data, in the writing of the report, or in the decision to submit the article for publication.

Figures

**Figure 1.**
Schematic of the ADSP 5K analysis

**Figure 2.**
Top variants identified from single variant association analysis in the pooled sample within 100kb of the 83 lead GWAS variants Variant ID is in the form of chromosome:position (effect allele). Positions provided are on build 38. EAF is the effect allele frequency, Meta-RE is the multi-population meta-analysis using a random effect model, Meta-FE is the multi-population meta-analysis using a fixed effect model. The p-value for Meta-RE is calculated using Han and Eskin’s random effects model. The effect size and its 95% CI is not shown for variants with a minor allele count (MAC) < 10 in population specific analysis.

See this image and copyright information in PMC

References

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This is a preprint.

Key variants via Alzheimer's Disease Sequencing Project whole genome sequence data

Affiliations

Key variants via Alzheimer's Disease Sequencing Project whole genome sequence data

Authors

Affiliations

Update in

Abstract

Conflict of interest statement

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References

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