Phenotype: Number in household

This phenotype can be found on the UK Biobank Showcase for code 709. Neale Lab GWAS results are available for 358,963 unrelated individuals of European ancestry. This is a ordinal phenotype.


Primary Results

Estimated SNP heritability: 0.0139 (se=0.00239, p=2.63e-09)

Significance level: significant after multiple testing correction

Confidence rating: high

Confounding and model misspecification

In addition to SNP heritability, LD score regression also estimates an intercept term that indexes population stratification, other counfounding, and potential misspecification in the partitioned LD score model for the distribution of genetic effects genome-wide.

  • Intercept: 1.0171 (se=0.00856, p=0.0229)
  • Mean \(\chi^2\): 1.1034
  • Ratio: 0.1653 (se=0.0828)
  • \(\lambda_{GC}\): 1.0927

Intercept values near 1 indicate little or no confounding. The reported LDSR ratio compares the intercept estimate and the mean \(\chi^2\) statistic to provide a rough index for how much of the polygenic signal in the GWAS may be due to confounding rather than genetic effects (assuming the LD score model is well specified). Note that the intercept, mean \(\chi^2\), and genomic control \(\lambda_{GC}\) are all expected to scale with sample size, making the ratio better suited for comparisons between different GWAS.

Correlations

Genetic correlations and phenotypic correlations comparing this phenotype to other significantly heritable phenotypes from the Neale Lab UK Biobank GWAS can be found at: ukbb-rg.hail.is



Insufficient power for partitioning

We omit results for enrichment of specific annotations in the partitioned heritability model here when the overall SNP heritability is not strongly significant (\(z < 7\)) as recommended by Finucane et al. 2015. Partitioned results for this phenotype are available in the full results file download, but we caution that the analysis is likely to be underpowered and unstable.


Methods

All results are from partitioned heritability analysis of this phenotype using LD score regression (Bulik-Sullivan et al. 2015, github repo) with 75 annotations as described by Gazal et al. 2017 (also on biorxiv). See Methods for more information on the underlying GWAS and LDSR analysis. You can also read more about the confidence criteria and the significance thresholds.

Downloads

See the full manifest of LDSR sumstats files for sumstats for other GWAS of this phenotype, where applicable.

See the Downloads page for more information.

Credits

See the full team behind these results here.