Family history assessment significantly enhances delivery of precision medicine in the genomics era Article Swipe
Yasmin Bylstra
,
Weng Khong Lim
,
Sylvia Kam
,
Koei Wan Tham
,
R. Ryanne Wu
,
Jing Xian Teo
,
Sonia Dávila
,
Jyn Ling Kuan
,
Sock Hoai Chan
,
Nicolas Bertin
,
Cheng Yang
,
Steve Rozen
,
Bin Tean Teh
,
Khung Keong Yeo
,
Stuart A. Cook
,
Saumya Shekhar Jamuar
,
Geoffrey S. Ginsburg
,
Lori A. Orlando
,
Patrick Tan
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1186/s13073-020-00819-1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1186/s13073-020-00819-1
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.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1186/s13073-020-00819-1
- https://genomemedicine.biomedcentral.com/track/pdf/10.1186/s13073-020-00819-1
- OA Status
- gold
- Cited By
- 37
- References
- 62
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3119812814
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3119812814Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1186/s13073-020-00819-1Digital Object Identifier
- Title
-
Family history assessment significantly enhances delivery of precision medicine in the genomics eraWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-01-07Full publication date if available
- Authors
-
Yasmin Bylstra, Weng Khong Lim, Sylvia Kam, Koei Wan Tham, R. Ryanne Wu, Jing Xian Teo, Sonia Dávila, Jyn Ling Kuan, Sock Hoai Chan, Nicolas Bertin, Cheng Yang, Steve Rozen, Bin Tean Teh, Khung Keong Yeo, Stuart A. Cook, Saumya Shekhar Jamuar, Geoffrey S. Ginsburg, Lori A. Orlando, Patrick TanList of authors in order
- Landing page
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https://doi.org/10.1186/s13073-020-00819-1Publisher landing page
- PDF URL
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https://genomemedicine.biomedcentral.com/track/pdf/10.1186/s13073-020-00819-1Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://genomemedicine.biomedcentral.com/track/pdf/10.1186/s13073-020-00819-1Direct OA link when available
- Concepts
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Human genetics, Genomics, Precision medicine, Genome Biology, Reproductive medicine, Medicine, Systems biology, Genomic medicine, Computational biology, Bioinformatics, Biology, Genetics, Genome, Pathology, Gene, PregnancyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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37Total citation count in OpenAlex
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2025: 6, 2024: 11, 2023: 9, 2022: 5, 2021: 6Per-year citation counts (last 5 years)
- References (count)
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62Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.(8.4%) | 113 |
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| abstract_inverted_index.17/884) | 183 |
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| abstract_inverted_index.0.00001) | 169 |
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| abstract_inverted_index.NCT02791152 | 295 |
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| cited_by_percentile_year.max | 99 |
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| corresponding_author_ids | https://openalex.org/A5003742732 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 19 |
| corresponding_institution_ids | https://openalex.org/I115228651, https://openalex.org/I66068411 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.5799999833106995 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.95866974 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |