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

• Published in: Alzheimer's research & therapy 2022-01, Vol.14 (1), p.17-17, Article 17
• Main Authors: Liu, Haijie, Hu, Yang, Zhang, Yan, Zhang, Haihua, Gao, Shan, Wang, Longcai, Wang, Tao, Han, Zhifa, Sun, Bao-Liang, Liu, Guiyou
• Format: Article
• Language: English
• Subjects: Alzheimer Disease - diagnosis; Alzheimer Disease - genetics; Alzheimer's disease; Biobanks; Consortia; Datasets; Dementia; Diagnosis; Educational attainment; Epidemiologic methods; Genetic aspects; Genetic Heterogeneity; Genetic research; Genetic variation; Genome-wide association studies; Genome-Wide Association Study; Genomes; Genotype & phenotype; GWAS; GWAX; Health risk assessment; Humans; Medical diagnosis; Mendelian randomization; Mendelian Randomization Analysis; Meta-analysis; Phenotype; Polymorphism, Single Nucleotide - genetics; Risk factors; Self Report; Variables; Variance analysis
• ISSN: 1758-9193; 1758-9193
• DOI: 10.1186/s13195-022-00963-3

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. 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. 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. 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.