We applied SAIGE-GENE to the high-density lipoprotein (HDL) levels in 69,500 Norwegian samples from a population-based HUNT study15 (link),16 (link). About 70,000 HUNT participants were genotyped using Illumina HumanCoreExome v1.0 and 1.1 and imputed using Minimac338 with a merged reference panel of Haplotype Reference Consortium (HRC)39 and whole genome sequencing data (WGS) for 2,201 HUNT samples. Variants with imputation r2 < 0.8 were excluded from further analysis. Participation in the HUNT Study is based on informed consent, and the study has been approved by the Data Inspectorate and the Regional Ethics Committee for Medical Research in Norway. Total 13,416 genes with at least two rare (MAF ≤ 1%) missense and/or stop-gain variants with imputation r2 ≥ 0.8 were tested. Variants were annotated using Seattle Seq Annotations (http://snp.gs.washington.edu/SeattleSeqAnnotation138/). We used 249,749 pruned genotyped markers to estimate relatedness coefficients in the full GRM for Step 1 and used the relative coefficient cutoff ≥ 0.125 for the sparse GRM.
We have also analyzed 53 quantitative traits and 10 binary traits using SAIGE-GENE in the UK Biobank for 408,910 participants with White British ancestry2 (link). UK Biobank protocols were approved by the National Research Ethics Service Committee and participants signed written informed consent. Markers that were imputed by the HRC39 panel with imputation info score ≥ 0.8 were used in the analysis. Total 15,342 genes with at least two rare (MAF ≤ 1%) missense and stop-gain variants that were directly genotyped or successfully imputed from HRC (imputation score ≥ 0.8) were tested. We used 340,447 pruned markers, which were pruned from the directly genotyped markers using the following parameters, were used to construct GRM: window size of 500 base pairs (bp), step-size of 50 bp, and pairwise r2 < 0.2. We used the relative coefficient cutoff ≥ 0.125 for the sparse GRM.