CF_MetS_results_adapt.txt.gz contain the results of the common factor GWAS conducted and described in 'Disentangling Genetic Risks for Metabolic Syndrome' by Eva S van Walree et al. published in Diabetes in November 2022. 
CF_MetS_code_description.txt contains the code used to generate the results described in the paper.
This GWAS was conducted using genomicSEM, see https://github.com/GenomicSEM/GenomicSEM/wiki/4.-Common-Factor-GWAS
Input summary statistics on phenotypes fasting glucose, HDL cholesterol, systolic blood pressure, triglycerides and waist circumference were publicly available, see supplement. Included samples were all of European ancestry. Estimated sample size of this common factor GWAS was 
The effective population size was 461,920 (as estimated by genomicSEM).

Human genome reference build is GRCh37.
chromosome = chromosome number
base_pair_location = base pair position in chromosome
effect_allele = effect allele
other_allele = non-effect allele
beta = effect size of variant
standard_error = sandwich corrected standard error of effect size
minor_allele_frequency = allele frequency of the minor allele
p_value = p-value of effect estimate
rsid = rs ID number of the SNP
i = an ordered list of the runs
Z_Estimate = ratio of beta/standard_error
Q = heterogeneity estimate for that SNP, see https://github.com/GenomicSEM/GenomicSEM/wiki/4.-Common-Factor-GWAS
Q_df = the degrees of freedom for Q
Q_pval = the p-value associated with the Q statistic. 
fail = the fail column indicates whether a particular run did not converge. 
warning = the warning column will list whether a particular run raised any warnings in lavaan. This may include specific runs where the residual variance of an indicator is negative.
The "lhs", "op", and "rhs" column lists the outcome, operator, and predictor. In this case "F1 ~ SNP", indicates the common factor regressed on the SNP. 

For comparative purposes, the columns have been renamed from the output given by genomicSEM.