Prostate cancer genetic risk and associated aggressive disease in men of African ancestry

Supplementary Table 1. Summary of clinical information for 113 South African men with prostate cancer where deep sequence data was available (Jaratlerdsiri et al., 2022).

Supplementary Table 2. Summary of clinical information for the exome study population. PSA, prostate-specific antigen; ISUP, International Society of Urological Pathology.

Supplementary Table 3. Number of SNPs and proportion (out of 247,780 assayed variants) per minor allele frequency (MAF) interval for 780 samples genotyped on the Illumina HumanExome BeadChip v1.0 array, prior to and post-processing of rare variants (MAF£0.01) with zCall v3.4 (Goldstein et al., 2012).

Supplementary Table 4. Risk allele frequency (RAF) in our South African population (sequence data and exome array data where available) compared to previously reported RAF in African ancestry controls (N=61,620) (Chen et al., 2023).

Supplementary Table 5. Risk allele frequency (RAF) in our South African population (N=113) for the top 136 associated variants from the Uganda prostate cancer GWAS study (UGPCS) (Du et al., 2018) and for the African Ancestry prostate cancer study (AAPC) which were reported by Du et al., 2018. None of these variants were genotyped in the exome array.

Supplementary Table 6. Risk allele frequencies (RAF) for the top 30 associated variants from the Ghana GWAS study (Cook et al., 2014) in South African PCa sequenced cases, and for the samples genotyped on the exomic array, where available.

Supplementary Table 7. Risk allele frequencies, odds ratios (OR), and P-values for 397 known cancer variants out out of 2477 previously summarised (Harlemon et al., 2020) that were available on the exomic array.

Supplementary Table 8. Genes significantly associated to PCa in the rare variant gene-based analysis, and the frequencies of each set of genotypes in cases compared to controls, as well as predicted consequences of each variant.

Supplementary Table 9. Genes significantly associated to PCa in the gene-based analysis including common and rare variants, and the frequencies of each set of genotypes in cases compared to controls, as well as predicted consequences of each variant.

Supplementary Table 10. Genes significantly associated to HRPCa in the gene-based analysis including common and rare variants, and the frequencies of each set of genotypes in cases compared to controls, as well as predicted consequences of each variant.

补充表1：113名携带深度测序数据的南非前列腺癌男性患者的临床信息汇总（Jaratlerdsiri等人，2022）。
补充表2：外显子组研究队列的临床信息汇总。PSA：前列腺特异性抗原(Prostate-specific antigen)；ISUP：国际泌尿病理学会(International Society of Urological Pathology)。
补充表3：基于Illumina HumanExome BeadChip v1.0芯片对780份样本进行基因分型后，在使用zCall v3.4工具（Goldstein等人，2012）对低频变异（次要等位基因频率(Minor Allele Frequency, MAF)≤0.01）进行预处理前后，各次要等位基因频率区间内的单核苷酸多态性(Single Nucleotide Polymorphism, SNP)数量及其占所检测247,780个变异位点的比例。
补充表4：本研究南非人群（含已获取的测序数据及外显子组芯片数据）的风险等位基因频率(Risk Allele Frequency, RAF)，与既往报道的非洲血统对照人群（N=61,620）的风险等位基因频率对比（Chen等人，2023）。
补充表5：本研究南非人群（N=113）的风险等位基因频率(RAF)，涵盖来自乌干达前列腺癌全基因组关联研究(UGPCS, Uganda Prostate Cancer GWAS Study)（Du等人，2018）筛选出的前136个关联变异，以及Du等人2018年报道的非洲血统前列腺癌研究(AAPC, African Ancestry Prostate Cancer Study)的关联变异。上述变异均未在外显子组芯片中进行基因分型。
补充表6：加纳全基因组关联研究（Cook等人，2014）筛选出的前30个关联变异在南非前列腺癌(PCa, Prostate Cancer)测序样本中的风险等位基因频率(RAF)，以及已获取的外显子组芯片分型样本的对应频率。
补充表7：本研究外显子组芯片包含的397个已知癌症变异的风险等位基因频率、比值比(Odds Ratio, OR)与P值，该397个变异来自此前汇总的2,477个变异（Harlemon等人，2020）。
补充表8：基于罕见变异的基因水平分析中与前列腺癌(PCa)显著关联的基因，以及病例组与对照组各基因型组合的频率，同时包含各变异的预测功能后果。
补充表9：纳入常见与罕见变异的基因水平分析中与前列腺癌(PCa)显著关联的基因，以及病例组与对照组各基因型组合的频率，同时包含各变异的预测功能后果。
补充表10：纳入常见与罕见变异的基因水平分析中与去势抵抗性前列腺癌(HRPCa, Hormone-Refractory Prostate Cancer)显著关联的基因，以及病例组与对照组各基因型组合的频率，同时包含各变异的预测功能后果。