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Mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed Alzheimer’s disease GWAS and self-report proxy phenotype GWAX

BACKGROUND: Until now, Mendelian randomization (MR) studies have investigated the causal association of risk factors with Alzheimer’s disease (AD) using large-scale AD genome-wide association studies (GWAS), GWAS by proxy (GWAX), and meta-analyses of GWAS and GWAX (GWAS+GWAX) datasets. However, it c...

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Autores principales: Liu, Haijie, Hu, Yang, Zhang, Yan, Zhang, Haihua, Gao, Shan, Wang, Longcai, Wang, Tao, Han, Zhifa, Sun, Bao-liang, Liu, Guiyou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8800228/
https://www.ncbi.nlm.nih.gov/pubmed/35090530
http://dx.doi.org/10.1186/s13195-022-00963-3
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author Liu, Haijie
Hu, Yang
Zhang, Yan
Zhang, Haihua
Gao, Shan
Wang, Longcai
Wang, Tao
Han, Zhifa
Sun, Bao-liang
Liu, Guiyou
author_facet Liu, Haijie
Hu, Yang
Zhang, Yan
Zhang, Haihua
Gao, Shan
Wang, Longcai
Wang, Tao
Han, Zhifa
Sun, Bao-liang
Liu, Guiyou
author_sort Liu, Haijie
collection PubMed
description BACKGROUND: Until now, Mendelian randomization (MR) studies have investigated the causal association of risk factors with Alzheimer’s disease (AD) using large-scale AD genome-wide association studies (GWAS), GWAS by proxy (GWAX), and meta-analyses of GWAS and GWAX (GWAS+GWAX) datasets. However, it currently remains unclear about the consistency of MR estimates across these GWAS, GWAX, and GWAS+GWAX datasets. METHODS: Here, we first selected 162 independent educational attainment genetic variants as the potential instrumental variables (N = 405,072). We then selected one AD GWAS dataset (N = 63,926), two AD GWAX datasets (N = 314,278 and 408,942), and three GWAS+GWAX datasets (N = 388,324, 455,258, and 472,868). Finally, we conducted a MR analysis to evaluate the impact of educational attainment on AD risk across these datasets. Meanwhile, we tested the genetic heterogeneity of educational attainment genetic variants across these datasets. RESULTS: In AD GWAS dataset, MR analysis showed that each SD increase in years of schooling (about 3.6 years) was significantly associated with 29% reduced AD risk (OR=0.71, 95% CI: 0.60–0.84, and P=1.02E−04). In AD GWAX dataset, MR analysis highlighted that each SD increase in years of schooling significantly increased 84% AD risk (OR=1.84, 95% CI: 1.59–2.13, and P=4.66E−16). Meanwhile, MR analysis suggested the ambiguous findings in AD GWAS+GWAX datasets. Heterogeneity test indicated evidence of genetic heterogeneity in AD GWAS and GWAX datasets. CONCLUSIONS: We highlighted significant difference and genetic heterogeneity in clinically diagnosed AD GWAS and self-report proxy phenotype GWAX. Our MR findings are consistent with recent findings in AD genetic variants. Hence, the GWAX and GWAS+GWAX findings and MR findings from GWAX and GWAS+GWAX should be carefully interpreted and warrant further investigation using the AD GWAS dataset. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13195-022-00963-3.
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spelling pubmed-88002282022-02-02 Mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed Alzheimer’s disease GWAS and self-report proxy phenotype GWAX Liu, Haijie Hu, Yang Zhang, Yan Zhang, Haihua Gao, Shan Wang, Longcai Wang, Tao Han, Zhifa Sun, Bao-liang Liu, Guiyou Alzheimers Res Ther Research BACKGROUND: Until now, Mendelian randomization (MR) studies have investigated the causal association of risk factors with Alzheimer’s disease (AD) using large-scale AD genome-wide association studies (GWAS), GWAS by proxy (GWAX), and meta-analyses of GWAS and GWAX (GWAS+GWAX) datasets. However, it currently remains unclear about the consistency of MR estimates across these GWAS, GWAX, and GWAS+GWAX datasets. METHODS: Here, we first selected 162 independent educational attainment genetic variants as the potential instrumental variables (N = 405,072). We then selected one AD GWAS dataset (N = 63,926), two AD GWAX datasets (N = 314,278 and 408,942), and three GWAS+GWAX datasets (N = 388,324, 455,258, and 472,868). Finally, we conducted a MR analysis to evaluate the impact of educational attainment on AD risk across these datasets. Meanwhile, we tested the genetic heterogeneity of educational attainment genetic variants across these datasets. RESULTS: In AD GWAS dataset, MR analysis showed that each SD increase in years of schooling (about 3.6 years) was significantly associated with 29% reduced AD risk (OR=0.71, 95% CI: 0.60–0.84, and P=1.02E−04). In AD GWAX dataset, MR analysis highlighted that each SD increase in years of schooling significantly increased 84% AD risk (OR=1.84, 95% CI: 1.59–2.13, and P=4.66E−16). Meanwhile, MR analysis suggested the ambiguous findings in AD GWAS+GWAX datasets. Heterogeneity test indicated evidence of genetic heterogeneity in AD GWAS and GWAX datasets. CONCLUSIONS: We highlighted significant difference and genetic heterogeneity in clinically diagnosed AD GWAS and self-report proxy phenotype GWAX. Our MR findings are consistent with recent findings in AD genetic variants. Hence, the GWAX and GWAS+GWAX findings and MR findings from GWAX and GWAS+GWAX should be carefully interpreted and warrant further investigation using the AD GWAS dataset. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13195-022-00963-3. BioMed Central 2022-01-28 /pmc/articles/PMC8800228/ /pubmed/35090530 http://dx.doi.org/10.1186/s13195-022-00963-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Liu, Haijie
Hu, Yang
Zhang, Yan
Zhang, Haihua
Gao, Shan
Wang, Longcai
Wang, Tao
Han, Zhifa
Sun, Bao-liang
Liu, Guiyou
Mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed Alzheimer’s disease GWAS and self-report proxy phenotype GWAX
title Mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed Alzheimer’s disease GWAS and self-report proxy phenotype GWAX
title_full Mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed Alzheimer’s disease GWAS and self-report proxy phenotype GWAX
title_fullStr Mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed Alzheimer’s disease GWAS and self-report proxy phenotype GWAX
title_full_unstemmed Mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed Alzheimer’s disease GWAS and self-report proxy phenotype GWAX
title_short Mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed Alzheimer’s disease GWAS and self-report proxy phenotype GWAX
title_sort mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed alzheimer’s disease gwas and self-report proxy phenotype gwax
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8800228/
https://www.ncbi.nlm.nih.gov/pubmed/35090530
http://dx.doi.org/10.1186/s13195-022-00963-3
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