A Method for Bridging Population-Specific Genotypes to Detect Gene Modules Associated with Alzheimer’s Disease
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data
2.2. Enriched Gene Pipeline
2.3. Imputed Gene Expression Data
2.4. Identify Differentially Expressed Modules through Dense Gene Module Computations
2.5. Gene Set Variation Analysis of the Imputed Expression
3. Results
3.1. Key Gene Modules Are Shared across Populations
3.2. Shared Genes Overlap with Previously Detected AD-Associated Genes
3.3. Shared Genes Are Enriched with Biological Processes Associated with AD
3.4. Comparison to GSVA
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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White | African | Hispanic | |
---|---|---|---|
# of samples | 2545 | 1221 | 3102 |
# of cases | 1266 | 85 | 1425 |
# of controls | 1279 | 1136 | 1677 |
Average age cases | 72.9 | 80.8 | 79 |
Average age controls | NA | 78.3 | 73 |
# of significant modules | 317 | 342 | 779 |
Afr + Hisp | Afr + White | Hisp + White |
---|---|---|
AGPAT4, CYB5A, DRG2, HSPA14 | C4orf27, KCNJ6, TMEM218 | ACP6, DHX36, SUCLG2 |
ANO5, GADD45GIP1, NUP50, RNGTT | AGPS, CBS, NIPSNAP1, TRAP1 | |
ARPC5L, DYRK1A, S100A10, TTLL13 | AGPS, CDK5RAP2, NIPSNAP1, NME7 | |
BDKRB1, CERS1, HHATL | AGPS, MCUR1, NDUFAF4, NIPSNAP1 | |
BTN2A2, HLA-DRB1, HLA-DRB5 | AIMP1, CEP135, GCSH, SFI1 | |
C4orf27, IFNGR2, KCNJ6, TMEM218 | ALDH5A1, HSCB, MRPL35, NFXL1, VEZT | |
C4orf27, KCNJ6, TMEM218 | ALDH5A1, HSCB, NFXL1, VEZT | |
CCDC146, HIP1R, VPS28 | ATP6V0A1, CYTH2, SMPD3 | |
DCDC2, FAM118A, NMU | B3GAT3, CSGALNACT2, GOSR1, GPR35, NRAS, SNAP47 | |
ENAH, FYCO1, PRMT6, SMG7 | BMP7, GNB2, GRB7, SERINC1, TDGF1 | |
HEATR1, HLA-B, HLA-H | BTN2A1, HMGCR, TYW1 | |
HLA-B, HLA-H, UXS1 | C4orf27, KCNJ6, TMEM218 | |
NDUFAF6, OTX1, RGS20 | CAPZA2, HIP1R, KRI1, MYO6, RIN3 | |
CBL, RIPK1, TAB2, YWHAE | ||
COMMD2, COMMD4, TP53RK | ||
CPSF3L, GIGYF1, HSD17B14, SNRPC | ||
CSNK1E, CUL7, DDX42, MAPK9, RCC1 | ||
CSNK1E, KIAA0101, LTBR, NBR1, TMEM259, TRIM4 | ||
DERL1, RMDN3, SLC13A3, SRPR | ||
GPC1, ITGA3, RABIF, RPS25, ZDHHC18 | ||
HLA-B, HLA-H, PSMA4, WDR11 | ||
MRPL20, MTRF1L, NDUFAF4, PDPR | ||
NRAS, SLC4A7, SNAP47, UNC5B | ||
RIPK1, TAB2, TICAM1 |
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Dai, Y.; Jia, P.; Zhao, Z.; Gottlieb, A. A Method for Bridging Population-Specific Genotypes to Detect Gene Modules Associated with Alzheimer’s Disease. Cells 2022, 11, 2219. https://doi.org/10.3390/cells11142219
Dai Y, Jia P, Zhao Z, Gottlieb A. A Method for Bridging Population-Specific Genotypes to Detect Gene Modules Associated with Alzheimer’s Disease. Cells. 2022; 11(14):2219. https://doi.org/10.3390/cells11142219
Chicago/Turabian StyleDai, Yulin, Peilin Jia, Zhongming Zhao, and Assaf Gottlieb. 2022. "A Method for Bridging Population-Specific Genotypes to Detect Gene Modules Associated with Alzheimer’s Disease" Cells 11, no. 14: 2219. https://doi.org/10.3390/cells11142219
APA StyleDai, Y., Jia, P., Zhao, Z., & Gottlieb, A. (2022). A Method for Bridging Population-Specific Genotypes to Detect Gene Modules Associated with Alzheimer’s Disease. Cells, 11(14), 2219. https://doi.org/10.3390/cells11142219