family history assessment
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2021 ◽  
Author(s):  
Daniele Guadagnolo ◽  
Gioia Mastromoro ◽  
Enrica Marchionni ◽  
Aldo Germani ◽  
Fabio Libi ◽  
...  

Abstract We describe the unusual presentation of familial early-onset gastric cancer due to a heterozygous pathogenic variant in the ATM gene. The proband had gastric cancer (age 45), and reported a sister deceased for diffuse gastric cancer (age 30) and another sister who developed diffuse gastric cancer (age 52) and ovarian serous cancer. Next Generation Sequencing for cancer susceptibility genes (APC, ATM, BRD1, BRIP1, CDH1, CDK4, CDKN2A, CHEK2, EPCAM, MLH1, MRE11, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, PTEN, RAD50, RAD51C, RAD51D, RECQL1, SMAD4, STK11, TP53) identified the truncating c.5944C>T, p.(Gln1982*) variant in ATM (NM_000051.3; NP_000042.3) in the proband. The variant segregated in the living affected sister and in the unaffected daughter of the deceased sister. Heterozygous ATM variants appear to significantly increase the risk for pancreatic, breast, gastric and prostatic cancer and, to a reduced extent, ovarian and colon cancer and melanoma, with moderate penetrance and variable expressivity. Familial gastric cancer is an unusual presentation for ATM. The occurrence of gastric cancer in this family suggests that individual variants may result in different, specific risks. Genotype-phenotype correlations are challenging, given the low penetrance and variable expressivity for ATM variants. Careful family history assessment is pivotal for prevention planning, strengthened by the availability of molecular diagnoses.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Yasmin Bylstra ◽  
Weng Khong Lim ◽  
Sylvia Kam ◽  
Koei Wan Tham ◽  
R. Ryanne Wu ◽  
...  

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Yasmin Bylstra ◽  
Weng Khong Lim ◽  
Sylvia Kam ◽  
Koei Wan Tham ◽  
R. Ryanne Wu ◽  
...  

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.


2020 ◽  
Author(s):  
Yasmin Bylstra ◽  
Weng Khong Lim ◽  
Sylvia Kam ◽  
Koei Wan Tham ◽  
R. Ryanne Wu ◽  
...  

AbstractBackgroundFamily 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, with less emphasis on family history assessment. We evaluated the utility of family history for genomic sequencing selection.MethodsWe analysed whole genome sequences of 1750 healthy research participants, with and without preselection based on standardised family history collection, screening 95 cancer genes.ResultsThe frequency of likely pathogenic/ pathogenic (LP/P) variants in 884 participants with no family history available (FH not available group) (2%) versus 866 participants with family history available (FH available group) (3.1%) was not significant (p=0.158). However, within the FH available group, amongst 73 participants with an increased family history cancer risk (increased FH risk), 1 in 7 participants carried a LP/P variant inferring a six-fold increase compared with 1 in 47 participants assessed at average family history cancer risk (average FH risk) and a seven-fold increase compared to the FH not available group. The enrichment was further pronounced (up to 18-fold) when assessing the 25 cancer genes in the ACMG 59-gene panel. Furthermore, 63 participants had an increased family history cancer risk in absence of an apparent LP/P variant.ConclusionOur findings show that systematic family history collection remains critical for health risk assessment, providing important actionable data and augmenting the yield from genomic data. Family history also highlights the potential impact of additional hereditary, environmental and behavioural influences not reflected by genomic sequencing.


2018 ◽  
Vol 21 (5) ◽  
pp. 1100-1110 ◽  
Author(s):  
M. Ragan Hart ◽  
Barbara B. Biesecker ◽  
Carrie L. Blout ◽  
Kurt D. Christensen ◽  
Laura M. Amendola ◽  
...  

2015 ◽  
Vol 148 (4) ◽  
pp. S-209
Author(s):  
Tannaz Guivatchian ◽  
Erika S. Koeppe ◽  
Jason Baker ◽  
Cristina Moisa ◽  
Matthew Demerath ◽  
...  

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