S1 Data -

Table A. Continuous Q-risk outcome regression results for LDL-C polygenic deviators, for all methods. Table B. Binary outcome regression results for LDL-C polygenic deviators, for all methods. Analyses where the logistic regression model did not converge are labelled with “NA”. Table C. SNP weights used to calculate the polygenic score for height (GIANT meta-analysis excluding UKB and 23&Me). (XLSX)</p

Fig 4 -

Scatter plots showing the distribution of individuals who deviate (red) and do not deviate (black) deviate their genetic predictor for LDL cholesterol, based on a) Mahalanobis distances with P 0.001 and b) P 0.05/n, c) regression residuals at the 2SD and d) 3SD threshold, e) GRS centiles with a Q3 + 1.5 IQR and f) Q3 + 3 IQR threshold, and finally g) GRS rank with P 0.001 and (h) P (1/10000).</p

Odds ratios for an individual having either type two diabetes (T2D) or coronary artery disease if they classified as misaligned to their LDL-C polygenic score, adjusted for BMI, age and LDL-C.

Odds ratios for an individual having either type two diabetes (T2D) or coronary artery disease if they classified as misaligned to their LDL-C polygenic score, adjusted for BMI, age and LDL-C.</p

Odds ratio per standard deviation increase in Q-Risk exposure phenotypes with respect to being classified as a deviating for a polygenic score for LDL cholesterol.

Odds ratio per standard deviation increase in Q-Risk exposure phenotypes with respect to being classified as a deviating for a polygenic score for LDL cholesterol.</p

A density plot of standardized polygenic scores for height plotted against standardized height for 158,951 unrelated individuals from the UK Biobank.

A density plot of standardized polygenic scores for height plotted against standardized height for 158,951 unrelated individuals from the UK Biobank.</p

Fig 2 -

a) Observed (red) and simulated (black) polygenic scores and standardized height adjusted for age, sex and assessment centre. b) Individuals aligned (black) and misaligned (red) to genetically predicted height defined using Mahalanobis distance P 0.001 and being more than 2 standard deviations away from the mean of the residual distribution generated by regressing the polygenic score against height. Individuals who were neither classified as aligned or misaligned were removed from 2)b).</p

Fig 3 -

Scatter plots showing the distribution of individuals who deviate (red) and do not deviate (black) from their genetic predictor for height, based on a) Mahalanobis distances with P 0.001 and b) P 0.05/n, c) regression residuals at the 2SD and d) 3SD threshold, e) GRS centiles with a Q3 + 1.5 IQR and f) Q3 + 3 IQR threshold, and finally g) GRS rank with P 0.001 and (h) P (1/10000).</p

Odds ratio of an individual being a carrier of a loss-of-function variant in one of three genes known to affect LDL-C levels: (<i>LDLR</i>, <i>APOB</i> and <i>PCSK9</i>) if they were classified as misaligned to their LDL-C polygenic score.

Odds ratio of an individual being a carrier of a loss-of-function variant in one of three genes known to affect LDL-C levels: (LDLR, APOB and PCSK9) if they were classified as misaligned to their LDL-C polygenic score.</p

SDS_UK10K_n3195_release_Sep_19_2016.tab

Singleton Density Score (SDS) computed for autosomal SNPs with let least 5% minor allele frequency over a set of 3,195 individuals from the UK10K project. This is a gzipped tab-delimited file and the first row is a column header. Columns correspond to: (1) chromosome; (2) genomic position (hg19); (3) SNP id (rsid); (4) ancestral allele; (5) derived allele; (6) derived allele frequency; (7) SDS. See our manuscript for further description of the SDS method as well as the data quality control and SNP filtering

Phenotypic criteria for filtering genes catalogued in OMIM and described as causal for syndromes associated with stature.

Table A. List of 238 genes with prior evidence for a causal association with syndromes associated with stature, filtered on those with evidence of a dominant inheritance relationship. Table B. The number of individuals who are defined as deviating from their polygenic score for height using different methodologies, split by those relatively tall and relatively short for their polygenic score (total n = 158,951). Table C. Percentage overlap of individuals classified as shorter than expected for their polygenic score for height across derivation methods Table D. Percentage overlap of individuals classified as taller than expected for their polygenic score for height across derivation methods. Note, no individuals were classified as being relatively tall when using a Mahalanobis-based P-value threshold = 0.05/n. Table E. Empirical P-values for enrichment in individuals who are short relative to their genetically predicted height across all deviator definitions. Table F. Empirical P-values for enrichment in individuals who are tall relative to their genetically predicted height across all deviator definitions. No individuals were classified as being relatively tall when using a Mahalanbobis-based P-value threshold = 0.05/n. Table G. Number of individuals, and percentage of population, identified as deviating from their polygenic score for measured LDL using different methodologies. Table H. UKB Fields used to derive Q-risk measures. (PDF)</p