Yasmin Bylstra1, Weng Khong Lim1,2,3, Sylvia Kam1,4, Koei Wan Tham1,5, R Ryanne Wu6, Jing Xian Teo1, Sonia Davila1,3,7, Jyn Ling Kuan1, Sock Hoai Chan8, Nicolas Bertin9, Cheng Xi Yang10, Steve Rozen1,2, Bin Tean Teh1,11, Khung Keong Yeo7,12, Stuart Alexander Cook1,7,12, Saumya Shekhar Jamuar1,3,4,13, Geoffrey S Ginsburg6, Lori A Orlando14, Patrick Tan15,16,17. 1. SingHealth Duke-NUS Institute of Precision Medicine, Singapore Health Services, Singapore, Singapore. 2. Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore. 3. SingHealth Duke-NUS Genomic Medicine Center, Singapore Health Services, Singapore, Singapore. 4. Department of Paediatrics, KK Women's and Children's Hospital, Singapore, Singapore. 5. Department of Physiology, National University of Singapore, Singapore, Singapore. 6. Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA. 7. Cardiovascular and Metabolic Disorders, Duke-NUS Medical School, Singapore, Singapore. 8. Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore. 9. Centre for Big Data and Integrative Genomics, Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore. 10. National Heart Research Institute Singapore, National Heart Centre Singapore, Singapore, Singapore. 11. National Cancer Centre Singapore, Singapore, Singapore. 12. Department of Cardiology, National Heart Centre Singapore, Singapore, Singapore. 13. Paediatric Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore. 14. Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA. orlan002@duke.edu. 15. SingHealth Duke-NUS Institute of Precision Medicine, Singapore Health Services, Singapore, Singapore. gmstanp@duke-nus.edu.sg. 16. Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore. gmstanp@duke-nus.edu.sg. 17. Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore. gmstanp@duke-nus.edu.sg.
Abstract
BACKGROUND: Family history has traditionally been an essential part of clinical care to assess health risks. However, declining sequencing costs have precipitated a shift towards genomics-first approaches in population screening programs rendering the value of family history unknown. We evaluated the utility of incorporating family history information for genomic sequencing selection. METHODS: To ascertain the relationship between family histories on such population-level initiatives, we analysed whole genome sequences of 1750 research participants with no known pre-existing conditions, of which half received comprehensive family history assessment of up to four generations, focusing on 95 cancer genes. RESULTS: Amongst the 1750 participants, 866 (49.5%) had high-quality standardised family history available. Within this group, 73 (8.4%) participants had an increased family history risk of cancer (increased FH risk cohort) and 1 in 7 participants (n = 10/73) carried a clinically actionable variant inferring a sixfold increase compared with 1 in 47 participants (n = 17/793) assessed at average family history cancer risk (average FH risk cohort) (p = 0.00001) and a sevenfold increase compared to 1 in 52 participants (n = 17/884) where family history was not available (FH not available cohort) (p = 0.00001). The enrichment was further pronounced (up to 18-fold) when assessing only the 25 cancer genes in the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes. Furthermore, 63 (7.3%) participants had an increased family history cancer risk in the absence of an apparent clinically actionable variant. CONCLUSIONS: These findings demonstrate that the collection and analysis of comprehensive family history and genomic data are complementary and in combination can prioritise individuals for genomic analysis. Thus, family history remains a critical component of health risk assessment, providing important actionable data when implementing genomics screening programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT02791152 . Retrospectively registered on May 31, 2016.
BACKGROUND: Family history has traditionally been an essential part of clinical care to assess health risks. However, declining sequencing costs have precipitated a shift towards genomics-first approaches in population screening programs rendering the value of family history unknown. We evaluated the utility of incorporating family history information for genomic sequencing selection. METHODS: To ascertain the relationship between family histories on such population-level initiatives, we analysed whole genome sequences of 1750 research participants with no known pre-existing conditions, of which half received comprehensive family history assessment of up to four generations, focusing on 95 cancer genes. RESULTS: Amongst the 1750 participants, 866 (49.5%) had high-quality standardised family history available. Within this group, 73 (8.4%) participants had an increased family history risk of cancer (increased FH risk cohort) and 1 in 7 participants (n = 10/73) carried a clinically actionable variant inferring a sixfold increase compared with 1 in 47 participants (n = 17/793) assessed at average family history cancer risk (average FH risk cohort) (p = 0.00001) and a sevenfold increase compared to 1 in 52 participants (n = 17/884) where family history was not available (FH not available cohort) (p = 0.00001). The enrichment was further pronounced (up to 18-fold) when assessing only the 25 cancer genes in the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes. Furthermore, 63 (7.3%) participants had an increased family history cancer risk in the absence of an apparent clinically actionable variant. CONCLUSIONS: These findings demonstrate that the collection and analysis of comprehensive family history and genomic data are complementary and in combination can prioritise individuals for genomic analysis. Thus, family history remains a critical component of health risk assessment, providing important actionable data when implementing genomics screening programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT02791152 . Retrospectively registered on May 31, 2016.
Entities:
Keywords:
Cancer; Clinically actionable variants; Family history; Population genomics screening
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