ArticleJAMA oncology2022
Association of Pathogenic Variants in Hereditary Cancer Genes With Multiple Diseases.
Article in JAMA oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- DNA damage repair mutations in pancreatic cancer- prognostic or predictive?Frontiers in oncology · 2023Pooled it
- 'How Did That Make You Feel?' Latinas' Use of Genetic Counseling and Testing for Hereditary Cancer Risk After Watching a Culturally Targeted Video and Receiving Patient Navigation.Psycho-oncology · 2025Trial
- Phenotype-Specific Recalibration of MAVE Data Enables Repurposing ofmedRxiv : the preprint server for health sciences · 2026Article
- Genetic background shapes AI-predicted variant effects.bioRxiv : the preprint server for biology · 2026Article
- Genetic Predisposition to Pancreatic Cancer: A Systematic Review of Hereditary Syndromes and Familial Aggregation.Cancers · 2026Review
- The global cancer crisis: a review of growing burden, deepening inequality and initiatives for prevention and early detection.Ecancermedicalscience · 2026Review
- Construction and evaluation of machine learning models for postoperative prognosis prediction of biliary tract malignancies.Frontiers in oncology · 2026Article
- Genomic Ascertainment of CHEK2-Related Cancer Predisposition.JAMA network open · 2025Article
- The landscape of germline variants in breast and colorectal cancer susceptibility genes in patients with pituitary tumours.Journal of neuro-oncology · 2025Article
- Established Cancer Predisposition Genes in Single and Multiple Cancer Diagnoses.JAMA oncology · 2025Article
- Saturation mapping of MUTYH variant effects using DNA repair reporters.American journal of human genetics · 2025Article
- Germline variants in CDKN2A wild-type melanoma prone families.Molecular oncology · 2025Article
- Risk of lymphoid malignancy associated with cancer predisposition genes.Blood cancer journal · 2025Article
- Risk of Subsequent Primary Cancers Among Adult-Onset 5-Year Cancer Survivors in South Korea: Retrospective Cohort Study.JMIR public health and surveillance · 2024Article
- Cancer genetic mutation prevalence in sub-Saharan Africa: A review of existing data.Seminars in oncology · 2023Review
- Next-generation phenotyping: introducing phecodeX for enhanced discovery research in medical phenomics.Bioinformatics (Oxford, England) · 2023Article
- Construction and validation of a metabolism-associated gene signature for predicting the prognosis, immune landscape, and drug sensitivity in bladder cancer.BMC medical genomics · 2023Article
- Article
- Global trends in the epidemiology of bladder cancer: challenges for public health and clinical practice.Nature reviews. Clinical oncology · 2023Review
- Bacterial-Mediated Tumor Therapy: Old Treatment in a New Context.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Review
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33 authors at 19 institutions in 2 countries.
Funding
Abstract
Importance: Knowledge about the spectrum of diseases associated with hereditary cancer syndromes may improve disease diagnosis and management for patients and help to identify high-risk individuals. Objective: To identify phenotypes associated with hereditary cancer genes through a phenome-wide association study. Design, Setting, and Participants: This phenome-wide association study used health data from participants in 3 cohorts. The Electronic Medical Records and Genomics Sequencing (eMERGEseq) data set recruited predominantly healthy individuals from 10 US medical centers from July 16, 2016, through February 18, 2018, with a mean follow-up through electronic health records (EHRs) of 12.7 (7.4) years. The UK Biobank (UKB) cohort recruited participants from March 15, 2006, through August 1, 2010, with a mean (SD) follow-up of 12.4 (1.0) years. The Hereditary Cancer Registry (HCR) recruited patients undergoing clinical genetic testing at Vanderbilt University Medical Center from May 1, 2012, through December 31, 2019, with a mean (SD) follow-up through EHRs of 8.8 (6.5) years. Exposures: Germline variants in 23 hereditary cancer genes. Pathogenic and likely pathogenic variants for each gene were aggregated for association analyses. Main Outcomes and Measures: Phenotypes in the eMERGEseq and HCR cohorts were derived from the linked EHRs. Phenotypes in UKB were from multiple sources of health-related data. Results: A total of 214 020 participants were identified, including 23 544 in eMERGEseq cohort (mean [SD] age, 47.8 [23.7] years; 12 611 women [53.6%]), 187 234 in the UKB cohort (mean [SD] age, 56.7 [8.1] years; 104 055 [55.6%] women), and 3242 in the HCR cohort (mean [SD] age, 52.5 [15.5] years; 2851 [87.9%] women). All 38 established gene-cancer associations were replicated, and 19 new associations were identified. These included the following 7 associations with neoplasms: CHEK2 with leukemia (odds ratio [OR], 3.81 [95% CI, 2.64-5.48]) and plasma cell neoplasms (OR, 3.12 [95% CI, 1.84-5.28]), ATM with gastric cancer (OR, 4.27 [95% CI, 2.35-7.44]) and pancreatic cancer (OR, 4.44 [95% CI, 2.66-7.40]), MUTYH (biallelic) with kidney cancer (OR, 32.28 [95% CI, 6.40-162.73]), MSH6 with bladder cancer (OR, 5.63 [95% CI, 2.75-11.49]), and APC with benign liver/intrahepatic bile duct tumors (OR, 52.01 [95% CI, 14.29-189.29]). The remaining 12 associations with nonneoplastic diseases included BRCA1/2 with ovarian cysts (OR, 3.15 [95% CI, 2.22-4.46] and 3.12 [95% CI, 2.36-4.12], respectively), MEN1 with acute pancreatitis (OR, 33.45 [95% CI, 9.25-121.02]), APC with gastritis and duodenitis (OR, 4.66 [95% CI, 2.61-8.33]), and PTEN with chronic gastritis (OR, 15.68 [95% CI, 6.01-40.92]). Conclusions and Relevance: The findings of this genetic association study analyzing the EHRs of 3 large cohorts suggest that these new phenotypes associated with hereditary cancer genes may facilitate early detection and better management of cancers. This study highlights the potential benefits of using EHR data in genomic medicine.
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