Indeed, there was a highly significant overlap between the proteins that increased during the 3 rd trimester and decreased post-partum (13/33 proteins, odds ratio (OR): 98.9, p=4.85e-09, Fisher’s exact test, Figure 4B ) and, conversely, between the downregulated proteins during the 3 rd trimester and the ones upregulated post-partum (13/44 proteins, OR: 29.9 , p=1.73e-05, Figure 4C ).
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This analysis revealed that 25 genes were up-regulated 1.5-fold or greater in both Tsc1 LOF and FOXO GOF expression profiles, which represents a highly significant degree of overlap (P = 4.9 × 10 e−009 ) as determined by calculation of the hypergeometric distribution.
A highly significant 20% of the genes targeted by PLZF/RARA have altered expression patterns ( P = 4.99×10 −9 , Fisher exact ) with 11% becoming down regulated and 9% being up regulated upon PLZF/RARA binding ( Figure 2a ).
All these reported associations remain highly significant even after accounting for multiple testing using Bonferroni correction and a stringent GWAS P -value threshold (nominally P = 5 × 10 −9 adjusted to 1 × 10 −9 for five individual GWAS).
KEGG analysis of this 372-gene set revealed highly significant NFIB-dependent pathways (focal adhesion p = 5*10 −9 , extracellular matrix-receptor interaction p = 5*10 −8 , axon guidance, p = 5*10 −8 and pathways in cancer p = 5*10 −4 ) shown in Figure 4B .
A number of highly significant associations ( P < 5 × 10 −9 ) were identified in regulatory sequences which are good candidates for causing susceptibility to AS, possibly by regulating ERAP1 expression. pmc-status-qastatus 0 pmc-status-live yes pmc-status-embargo no pmc-status-released yes pmc-prop-open-access yes pmc-prop-olf n
The association was highly significant in “OncoArray” population ( p = 5.05 × 10 –9 ) and was replicated in “HumanCore” population ( p = 3.73 × 10 –3 ).
This difference was highly significant (p = 5.1×10 −9 Student's t-test) and was confirmed by bisulphite sequencing ( Fig. 3 ).
We could not test whether this effect was significant using the GLM framework, but a one-sided two-sample Wilcoxon test showed that the difference in estimated selection coefficients for G→A mutations and non-CpG-forming A→G mutations was highly significant ( p = 5 ⋅ 10 −9 ).
The C3 K155Q (position 133 excluding the signal peptide) variant demonstrated compelling evidence of association in replication ( p =3.5×10 −5 , OR =2.8) and was highly significant with a large effect size in joint analysis with discovery samples ( p =5.2×10 −9 , OR =3.8; Table 1 ).
One-way ANOVA revealed a highly significant effect of year on median IgG concentrations ( p = 5.3 × 10 −9 ).
Interestingly, while no clear correlation was identified between temperature, or salinity and diversity levels of Aminicenantes at OTU 0.03 , a positive highly significant correlation existed between the dataset diversity rank and the environment’s oxygen tension (Spearman rank correlation coefficient = 0.4, p-value = 5.3E-9).
Among the predictions, we observed a striking enrichment for α 2‐6 linked Neu5Ac‐containing motifs, which was highly significant based on a Wilcoxon signed‐rank test ( p = 5.38 × 10 −9 ).
The test statistic (t = 8.15, df = 29) yielded a highly significant p -value ( p ≈ 5.4 × 10 −9 ), and the 95% confidence interval (0.68–0.92) confirmed the robustness of this association ( Figure 1 A).
The second gene set with highly significant overlap (EMBRYONIC STEM CELL UP; p < 5.53E-09) was derived from a study of gene expression profiles in mouse embryonic stem cells compared to differentiated brain and bone marrow cells [ 73 ].
This revealed a large overlap; that is, 29% of the genes that were differentially expressed in control and coInsm1 mutant islets were also differentially expressed in mature and immature β-cells; a hypergeometric probability test demonstrated that this overlap was highly significant ( P < 5.6 × 10 −9 ; Fig 4 C).
For the 374 sex-DE genes (FD≥1.2, P ≤0.05) that were also tested in the ASD-DE analysis, we observe a highly significant positive correlation between the sex-differential and ASD-differential FDs ( r =0.30, P =5.7e-09, Fig. 2c ), as well as for the subset of genes differentially expressed at FD≥1.2 and P ≤0.05 in both comparisons ( r =0.29, P =5.7e-04, N =90 genes).
The association peak between 110 and 144 Mbp on the same chromosome for the same trait contained three highly significant SNPs, namely S8_111289041 ( P -value = 5.82E−09); S8_124434722 ( P -value = 3.97E−10), and S8_138938949/S8_138938983 ( P -value = 9.81E−12) that were in strong LD to one another, with R 2 value ranging from 0.31 to 0.67 ( Figure 4 ).
This variant in TMEM9 (rs6667912) was also highly significant in the European subgroup analysis (odds ratio [95% CI], 1.39 [1.24–1.55]; P =6.01×10 −9 ; Figure S2 ) and was significantly associated with a skeletal muscle splicing quantitative trait loci in TMEM9 23 ( P =1.1×10 −8 ; Table S2 ).
Specifically, we observed clusters of highly significant Single Nucleotide Polymorphisms (SNPs) proximal to S04_3657761 in Chr04 associated with the DW ( − log 10 P = 8.22) (Fig. 6c ; see the quantile-quantile plots in Fig.
Interestingly, in the top-ten ranking splice sites, we see a highly significant enrichment of splice sites associated to COSMIC genes (p=6.1 × 10 −9 , Fisher’s exact test).
Following the MLM and applying a Bonferroni LOD-threshold of 4.96 ( P = 1.08E-05), we identified two highly significant SNPs, Lalb_Chr05_2957601 and Lalb_Chr05_2957940, for both sAUDPC ( P = 6.11E-09 and 2.41E-07, respectively) and LS rel ( P = 1.55E-06 and 2.13E-06, respectively; Fig. 3 and Table 1 ).
There is a highly significant ( p < 6.18e‐09) overlap of piRNAs up‐regulated by cocaine and down‐regulated by MET with target genes in opposite direction, and also highly significant ( p < 6.34e‐06) overlap piRNAs down‐regulated by cocaine and up‐regulated by MET with target genes in opposite direction.
Among probe sets exhibiting negative fold changes of ≥1.5, this analysis identified highly significant associations with STAT3 (p-value of overlap with reference set = 2.5×10 −13 ), OSM (p = 6.2×10 −9 ), IL6 (p = 1.2×10 −7 ) and other components of STAT3-dependent signaling pathways including cytokines (e.g., leukemia inhibitory factor [LIF], p = 8.2×10 −8 , and granulocyte colony-stimulating factor [GCSF], p = 8.4×10 −7 ), growth factors (e.g., hepatocyte growth factor, p = 2.2×10 −5 , and epidermal growth factor, p = 2.6×10 −4 ) and receptors (e.g., IL10 receptor α, p = 1.2×10 −6 , and IL6ST, p = 1.2×10 −4 ).
The 56 genes showed no significant set-level association with word reading ability, but a highly significant association with dyslexia ( P = 6.22 × 10 −9 ) ( SI Appendix , Table S5 ).