In the second example, EFA was applied to the LDSC-derived genetic correlation matrix for nine anthropometric traits from the EGG and GIANT consortia (Supplementary Table 4). EFA results indicated that two factors explained 61% of the total genetic variance. Moreover, a heatmap of the genetic correlation matrix suggests two primary factors that index overweight and early life-growth phenotypes (Supplementary Figure 5). A follow-up CFA (Supplementary Figure 6) within Genomic SEM was specified based on the EFA parameter estimates (standardized loadings > .25 were retained). The CFA showed good fit to the data (χ2[25] = 12994.71, AIC = 13034.71, CFI = .962, SRMR = .092). Results indicated highly significant loadings, and a small correlation between the two factors (rg = .10, SE = .03, p < .001). This indicates that early life physical growth is modestly associated with later life obesity traits via genetic pathways.
