Largest GWAS (N=1,126,563) of Alzheimer's Disease Implicates Microglia and Immune Cells
Wightman, D. P.; Jansen, I. E.; Savage, J. E.; Shadrin, A. A.; Bahrami, S.; Rongve, A.; Borte, S.; Winsvold, B. S.; Drange, O. K.; Martinsen, A. E.; Skogholt, A. H.; Willer, C.; Brathen, G.; Bosnes, I.; Nielsen, J. B.; Fritsche, L.; Thomas, L. F.; Pedersen, L. M.; Gabrielsen, M. E.; Johnsen, M. B.; Meisingset, T. W.; Zhou, W.; Proitsi, P.; Hodges, A.; Dobson, R.; Velayudhan, L.; 23andMe Research Team, ; Sealock, J. M.; Davis, L. K.; Pedersen, N. L.; Reynolds, C. A.; Karlsson, I. K.; Magnusson, S.; Stefansson, H.; Thordardottir, S.; Jonsson, P. V.; Snaedal, J.; Zettergren, A.; Skoog, I.; Kern,
Show abstract
Late-onset Alzheimers disease is a prevalent age-related polygenic disease that accounts for 50-70% of dementia cases1. Late-onset Alzheimers disease is caused by a combination of many genetic variants with small effect sizes and environmental influences. Currently, only a fraction of the genetic variants underlying Alzheimers disease have been identified2,3. Here we show that increased sample sizes allowed for identification of seven novel genetic loci contributing to Alzheimers disease. We highlighted eight potentially causal genes where gene expression changes are likely to explain the association. Human microglia were found as the only cell type where the gene expression pattern was significantly associated with the Alzheimers disease association signal. Gene set analysis identified four independent pathways for associated variants to influence disease pathology. Our results support the importance of microglia, amyloid and tau aggregation, and immune response in Alzheimers disease. We anticipate that through collaboration the results from this study can be included in larger meta-analyses of Alzheimers disease to identify further genetic variants which contribute to Alzheimers pathology. Furthermore, the increased understanding of the mechanisms that mediate the effect of genetic variants on disease progression will help identify potential pathways and gene-sets as targets for drug development.
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