“highly significant”

Using these analytic approaches, we found that each of the eight groups of sex-specific genes listed in SM- Table 3 a-3b are jointly and significantly associated with longevity in one sex ( P = 8.7 × 10 −165 ∼1.5 × 10 −37 ), but not jointly significant in the other sex ( P > 0.05), while PRS-sex interaction effects are highly significant ( P = 5.2 × 10 −106 ∼4.4 × 10 −15 ) (SM- Table 5 ).

Next, based on the z score in the latent factor mixed models (LFMMs), we detected 155 CNVs with |z| scores ≥ 10 ( Supplementary Table S11 ) that were highly significant (3.63 × 10 −6 ≥ p values ≥ 1.34 × 10 −103 ), associated with environmental parameters in 47 old sheep populations.

Other highly significant proteins for AD included GFAP ( β = 0.676; FDR-adjusted p = 5.02 × 10 −102 ), p-tau231 ( β = 0.700; FDR-adjusted p = 4.42 × 10 −94 ), NEFL ( β = 0.417; FDR-adjusted p = 1.52 × 10 −48 ) and p-tau181 ( β = 0.483; FDR-adjusted p = 9.25 × 10 −46 ; Supplementary Table 1 ).

This comparison yielded a highly significant overlap ( P < 1e−100) in 2419 of 3802 DEGs, validating our adopted strategy ( supplemental Figure 1 D).

Likelihood ratio tests indicated a highly significant genetic effect (LRT = 197.9, df = 1, P < 10 -100 ), suggesting that approximately 70% of the phenotypic variation is attributable to genetic factors.

All these variables have a statistically highly significant correlation (P~10 −100 ).

Similarly, when surveying combined protein expression and SV data across 328 cell lines 38 , 54 , 55 , we observed a highly significant overlap ( p < 1E−100 chi-square test) of events involving CRISPR knockout effect in genes with events involving SV-associated protein over-expression (Fig. 8b ), involving 2682 genes, 178 with combined breakpoint and protein over-expression involving at least 5% of cell lines examined (Supplementary Dataset 10 ).

The SNP-based heritability estimated on the observed scale was 0.78% (SE = 0.04%), which was highly significant (Z = 21.09, P-value = 9.41 × 10−99), further supporting a polygenic basis for ovarian cancer.

TH interneuron density increased steeply toward ventral caudoputamen ( β = 519.7, p = 5.6 × 10 −85 , N (hemispheres) = 13, N (sections) = 299), while SST interneurons showed a more moderate but highly significant ventral increase ( β = 253.9, p = 3.9 × 10 −98 , N (hemispheres) = 12, N (sections) = 276).

Additionally, the chi-square test for taxonomic distribution differences was highly significant ( χ 2 = 549.60, p < 7.64E-97), indicating that microbial composition varies between conditions.

We did not find a significant sex difference in overall PRS effects (OR male = 4.70 (4.16–5.31), OR female = 5.28 (4.80–5.80), P difference = 0.141, two-sample two-sided Z -test), even though the effect of sex was highly significant (OR = 2.54 (2.33–2.78), P = 1.93 × 10 −94 , one-sample two-sided Z -test).

Two highly significant loci associated with idiopathic MN were discovered: the human leukocyte antigen (HLA)-DQ alpha chain 1 ( HLA-DQA1 ) locus (rs 2187668; odds ratio, 4.32; P = 8.0 × 10 −93 ) and the PLA2R1 locus (rs 4664308; odds ratio, 2.28; P = 8.6 × 10 −29 ).

One-way ANOVA revealed highly significant differences in abundance, with 10 metabolites showing strong accumulation patterns (F-values 1.38 × 1031−7.84 × 1032; p < 1.03 × 10−92, FDR-corrected).

On the other hand, there were 180 genes differentially regulated by both dfoxo and Xbp1 s overexpression in the fat body ( Figure 4 C) and this overlap was highly significant ( p < 10 −90 ).

LD score regression analysis revealed a genetic correlation coefficient of rg = 0.23 (95% confidence interval [CI]: 0.203 to 0.249; se = 1.15 × 10 − 02 ), which was highly significant ( P = 2.65 × 10 − 85 ).

For viscosity–transparency relationships, ANOVA demonstrated a highly significant association (F = 244.94, p < 1 × 10 −84 , R 2 = 0.98), where viscosity nearly fully explained transparency differences—likely linked to enhanced molecular alignment or suppressed phase separation in high-viscosity systems—with a negligible C.V.

Genome size remained a highly significant predictor of the number of metabolites in the microbial genomes per species ( β = 6.99 × 10 −5 , p = 6.97 × 10 −83 ), indicating that genome completeness does not confound the observed relationship.

When comparing IBD genes to non-IBD genes within each tissue group, we observed highly significant differences across all categories: brain tissues ( p = 9.39 × 10 −82 ), GIT tissues ( p = 2.65 × 10 −97 ), and other tissues ( p = 1.17 × 10 −90 ), indicating that IBD-associated genes have distinct expression profiles compared to background genes.

The division of the San and Damara forager groups was in line with ADMIXTURE clustering, with highly significant correlations of admixture fractions between methods (Pearson correlation; R = 0.76 and 1.00, P -value = 1.21 × 10 −81 and 3.59 × 10 −13 ; Supplementary Fig. 5a, b ).

Remarkably, we observed a highly significant overlap (hypergeometric test, P = 2.44e-81) between the AS genes in smad1 -cKO (121/512) and smad1 -KD (121/660) PGCs (Fig. 7b ), such as ccdc187 (coiled-coil domain containing 187) that is involved in microtubule anchoring and located in the centrosome 51 , mak ( male germ cell associated kinase ) that encodes a serine/threonine protein kinase related to cell cycle regulation 52 , tinf2 ( TERF1-interacting nuclear factor 2 0) that encodes one subunit of shelterin complex involved in distinguishing between telomeres and DNA damage 53 , among others (Supplementary Fig. 7a ).

Results Monocyte responsiveness to LPS showed a highly significant, negative correlation with blood pressure levels (ρ< -0.4; P<10 -80 ).

Statistical Significance of Circuit Category Effects One-way ANOVA on proof generation times across the seven non-ECDSA circuits reveals highly significant differences ( F = 355.0 , p < 10 − 79 ), with circuit type explaining 94.1% of variance ( η 2 = 0.941 ).

Furthermore, the overlap in hits between cell lines was highly significant ( p < 1e-78, hypergeometric test; Figure 3G ).

As additional validation supporting the role of myeloid-derived cells, and specifically monocytes, as a dominant contributor to plasma CyC levels, we found a significant positive correlation between blood monocyte counts and CyC residual in the UKB cohort ( Figure S4 B; multivariate regression), and two-sample Mendelian randomization using blood-derived CST3 eQTLs (eQTLGen 58 ) as exposure identified a highly significant positive association with CyC production (p = 6.13e−77; Figure 4 E).

Results for the theta band showed a highly significant association between the mean relevance of each brain region, and how their centrality changes in association with p-tau231 levels (rho = 0.499; p = 9.2 × 10 –77 ).