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Not all SNPs identified by genome-wide association studies (GWAS) are functional in disease pathogenesis.
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SUPPORTED
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Is it true that not all SNPs identified by genome-wide association studies (GWAS) are functional in disease pathogenesis?
Yes. Genome-wide association studies (GWAS) routinely identify statistical risk variants, but many reside in non-coding regions or act as markers rather than causal elements, requiring downstream functional annotation and multi-omics analysis to confirm their biological roles.
Verdict: SUPPORTED · 4 sources for, 0 against · Last checked
Evidence for · 4
Identifies specific functional polymorphisms within Alzheimer's disease GWAS loci that impact miRNA-mediated gene expression.
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Delay, C., Grenier-Boley, B., Amouyel, P., Dumont, J., & Lambert, J. (2016). miRNA-dependent target regulation: functional characterization of single-nucleotide polymorphisms identified in genome-wide association studies of Alzheimer’s disease. doi.org. https://doi.org/10.1186/s13195-016-0186-x
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Notes that many GWAS loci reside in non-coding regions and require integrative computational frameworks to identify true effector genes.
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H, L., Z, W., X, L., & X, S. (2026). Functional Annotation of Alzheimer's Disease-Associated SNPs Based on Three-Dimensional Chromatin Structure.. doi.org. https://doi.org/10.3390/ijms27188396
Highlights the challenge of translating polygenic GWAS signals into functionally validated candidate genes and regulatory mechanisms in SLE.
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V, M., M, K., N, P., SL, S., P, L., & A, S. (2026). Integrative post-GWAS analysis prioritizes immune regulatory pathways and candidate effector signals in systemic lupus erythematosus.. doi.org. https://doi.org/10.1016/j.jtauto.2026.100399
Explains that most primary open-angle glaucoma risk loci from GWAS reside in non-coding regions with unclear function, requiring multi-omics mapping.
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J, G., Y, Y., H, L., Y, N., X, L., J, L., S, L., Y, Q., M, B., X, S., Z, Z., D, P., H, W., AP, K., M, H., Y, H., & H, Z. (2026). Decoding Primary Open-Angle Glaucoma: A Multi-Omics Approach to Identify Druggable Effector Genes.. doi.org. https://doi.org/10.1167/iovs.67.11.19
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