Phenotype: Diagnoses - main ICD10: M51 Other intervertebral disk disorders

This phenotype can be found as part of the ICD code listings on the UK Biobank Showcase for code 41202. Neale Lab GWAS results are available for 361,194 unrelated individuals of European ancestry. This is a binary phenotype with 4,690 cases and 356,504 controls.


Warning: Low confidence

Our confidence rating for this phenotype is low. Estimates are likely unstable. For that reason, we do not report enrichment results from partitioning (though they remain available in the full results file download) and we recommend you avoid making any strong inferences from these results. Read more about our confidence criteria here.


Primary Results

Estimated SNP heritability: 0.0768 (se=0.0257, p=0.00141)

Significance level: none (insufficient confidence)

Confidence rating: low

Our confidence in the LD Score regression result for this phenotype is reduced due to:

  • Potentially biased estimates at low effective sample size

Note: SNP heritability for this binary outcome is reported on the liability scale, assuming that the population prevalence matches the prevalence in the UK Biobank analysis set (0.013). This may be unreliable if the outcome was limited to a subset of individuals, or if the UK Biobank study population is not representative for this phenotype (which is likely in many cases). The estimated observed-scale heritability is: 0.0067 (se=0.00224).


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: 1.0158 (se=0.00839, p=0.0299)
  • Mean \(\chi^2\): 1.0591
  • Ratio: 0.2670 (se=0.1419)
  • \(\lambda_{GC}\): 1.0469

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.


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.