Comprehensively characterizing genotype-phenotype correlations (GPCs) in Mendelian disease would create new opportunities for improving clinical management and understanding disease biology. However, heterogeneous approaches to data sharing, reuse, and analysis have hindered progress in the field. We developed Genotype Phenotype Evaluation of Statistical Association (GPSEA), a software package that leverages the Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema to represent case-level clinical and genetic data about individuals. GPSEA applies an independent filtering strategy to boost statistical power to detect categorical GPCs represented by Human Phenotype Ontology terms. GPSEA additionally enables visualization and analysis of continuous phenotypes, clinical severity scores, and survival data such as age of onset of disease or clinical manifestations. We applied GPSEA to 85 cohorts with 6613 previously published individuals with variants in one of 80 genes associated with 122 Mendelian diseases and identified 225 significant GPCs, with 48 cohorts having at least one statistically significant GPC. These results highlight the power of standardized representations of clinical data for scalable discovery of GPCs in Mendelian disease.

• Publikační typ
• časopisecké články MeSH
• preprinty MeSH

The subset of ovarian cancer (OC) diagnosed ≤ 30yo represents a distinct subgroup exhibiting disparities from late-onset OC in many aspects, including indefinite germline cancer predisposition. We performed DNA/RNA-WES with HLA-typing, PRS assessment and survival analysis in 123 early-onset OC-patients compared to histology/stage-matched late-onset and unselected OC-patients, and population-matched controls. Only 6/123(4.9%) early-onset OC-patients carried a germline pathogenic variant (GPV) in high-penetrance OC-predisposition genes. Nevertheless, our comprehensive germline analysis of early-onset OC-patients revealed two divergent trajectories of potential germline susceptibility. Firstly, overrepresentation analysis highlighted a connection to breast cancer (BC) that was supported by the CHEK2 GPV enrichment in early-onset OC(p = 1.2 × 10-4), and the presumably BC-specific PRS313, which successfully stratified early-onset OC-patients from controls(p = 0.03). The second avenue pointed towards the impaired immune response, indicated by LY75-CD302 GPV(p = 8.3 × 10-4) and diminished HLA diversity compared with controls(p = 3 × 10-7). Furthermore, we found a significantly higher overall GPV burden in early-onset OC-patients compared to controls(p = 3.8 × 10-4). The genetic predisposition to early-onset OC appears to be a heterogeneous and complex process that goes beyond the traditional Mendelian monogenic understanding of hereditary cancer predisposition, with a significant role of the immune system. We speculate that rather a cumulative overall GPV burden than specific GPV may potentially increase OC risk, concomitantly with reduced HLA diversity.

• Klíčová slova
• Early-onset, Germline whole exome sequencing, HLA, Mutation burden, Ovarian cancer, Polygenic risk score,
• MeSH
• checkpoint kinasa 2 genetika   MeSH
• dospělí MeSH
• genetická predispozice k nemoci * MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• nádory vaječníků * genetika   MeSH
• studie případů a kontrol MeSH
• věk při počátku nemoci * MeSH
• zárodečné mutace * MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• checkpoint kinasa 2 MeSH

BACKGROUND: Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS). METHODS: We analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan. RESULTS: Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that TP53 3'-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10-9). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62). CONCLUSIONS: This study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.

• Publikační typ
• časopisecké články MeSH
• preprinty MeSH

Ovarian cancer (OC) is one of the leading causes of cancer-related deaths in women. Most patients are diagnosed with advanced epithelial OC in their late 60s, and early-onset adult OC diagnosed ≤30 years is rare, accounting for less than 5% of all OC cases. The most significant risk factor for OC development are germline pathogenic/likely pathogenic variants (GPVs) in OC predisposition genes (including BRCA1, BRCA2, BRIP1, RAD51C, RAD51D, Lynch syndrome genes, or BRIP1), which contribute to the development of over 20% of all OC cases. GPVs in BRCA1/BRCA2 are the most prevalent. The presence of a GPV directs tailored cancer risk-reducing strategies for OC patients and their relatives. Identification of OC patients with GPVs can also have therapeutic consequences. Despite the general assumption that early cancer onset indicates higher involvement of hereditary cancer predisposition, the presence of GPVs in early-onset OC is rare (<10% of patients), and their heritability is uncertain. This review summarizes the current knowledge on the genetic predisposition to early-onset OC, with a special focus on epithelial OC, and suggests other alternative genetic factors (digenic, oligogenic, polygenic heritability, genetic mosaicism, imprinting, etc.) that may influence the development of early-onset OC in adult women lacking GPVs in known OC predisposition genes.

• Klíčová slova
• early-onset, genetic predisposition, germline pathogenic variant, ovarian cancer,
• MeSH
• dospělí MeSH
• epiteliální ovariální karcinom genetika   MeSH
• genetická predispozice k nemoci * MeSH
• geny BRCA2 MeSH
• lidé MeSH
• nádory vaječníků * patologie   MeSH
• protein BRCA1 genetika   MeSH
• protein BRCA2 genetika   MeSH
• rizikové faktory MeSH
• zárodečné mutace MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH
• Názvy látek
• protein BRCA1 MeSH
• protein BRCA2 MeSH