Fig. 4: LongGWAS is viable with GMMAT/MAGEE and identifies five loci with genome-wide significance for eGFR-decline. | Nature Communications

Fig. 4: LongGWAS is viable with GMMAT/MAGEE and identifies five loci with genome-wide significance for eGFR-decline.

From: Analyzing longitudinal trait trajectories using GWAS identifies genetic variants for kidney function decline

Fig. 4

We conducted a genome-wide search for genetic variant association with eGFR-decline (Pdecline, GC-corrected, lambda = 1.06) using the LMM age model RI&RS 350K implemented in GMMAT/MAGEE34,35 (UKB 350K; n = 348,275, m = 1,520,382; testing 11 million SNPs with MAF ≥ 0.5%, imputation quality INFO ≥ 0.6). a Shown are association P values versus chromosomal position. We identified five loci at genome-wide significance (Pdecline < 5 × 10−8; red dashed horizontal line). Coloring highlights the overall 11 loci identified for eGFR-decline: 10 loci around the 12 variants identified by 595-search (Pdecline < 0.05/595 = 8.4 × 10−5, brown dashed horizontal line; 4 novel and 6 known for eGFR-decline in blue or green, respectively), and one novel locus for eGFR-decline now identified by longGWAS (cyan; lead variant rs2075570 in the 424 loci, but not among the 595 variants). Loci were derived by clumping based on variant position (d > 500kB between loci, “Methods” section). b Shown is the Quantile–Quantile (QQ) plot comparing the distribution of observed Pdecline with the distribution of Pdecline expected under the null hypothesis of “no association with eGFR-decline” (green: all variants; cyan: excluding the 10 loci around the 12 decline-associated variants; black: excluding the 424 loci around the 595 variants).

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