A simplified method for segregation analysis (SISA) to determine penetrance and expression of a genetic variant in a family

Møller, Pål; Clark, Neal; Mæhle, Lovise

doi:10.1002/humu.21441

Cited by 17 publications

(12 citation statements)

References 9 publications

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“…The statistical alpha level was 0.05. The Bonferroni adjustment for multiple testing was performed using SISA [25] to control for a family-wise error rate of 0.05, for which a significance level was considered as 0.05/42 = 0.00114. The P-values in the tables are reported in scientific notation if too many digits were needed for the evaluation and to address the issue of et al [14] (Model 2: 7 genes) and Han et al [15] (Model 3: 5 genes) and performed the multivariate logistic regression analysis using the pooled 12 public microarray data sets, in addition to external validation.…”

Section: Discussionmentioning

confidence: 99%

A Gene Expression Profile of Peripheral Blood in Colorectal Cancer

Huang¹,

Terng²

2014

JMBT

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AIM: Optimal molecular markers for detecting colorectal cancer (CRC) in a blood-based assay were evaluated. METHODS:A matched (by variables of age and sex) case-control design (111 CRC and 227 non-cancer samples) was applied. Total RNAs isolated from the 338 blood samples were reverse-transcribed, and the relative transcript levels of candidate genes were analyzed. The training set was made of 162 random samples of the total 338 samples. A logistic regression analysis was performed, and odds ratios for each gene were determined between CRC and non-cancer. The samples (n = 176) in the testing set were used to validate the logistic model, and an inferred performance (generality) was verified. By pooling 12 public microarray datasets (GSE 4107, 4183, 8671, 9348, 10961, 13067, 13294, 13471, 14333, 15960, 17538, and 18105), which included 519 cases of adenocarcinoma and 88 controls of normal mucosa, we were able to verify the selected genes from logistic models and estimate their external generality. RESULTS:The logistic regression analysis resulted in the selection of five significant genes (P < 0.05; MDM2 , DUSP6 , CPEB4 , MMD , and EIF2S3 ), with odds ratios of 2.978, 6.029, 3.776, 0.538 and 0.138, respectively. The five-gene model performed stably for the discrimination of CRC cases from controls in the training set, with accuracies ranging from 73.9% to 87.0%, a sensitivity of 95% and a specificity of 95%. In addition, a good performance in the test set was obtained using the discrimination model, providing 83.5% ac- = 0.853, AUC = 0.978, accuracy = 0.949, specificity = 0.818 and sensitivity = 0.971). RETROSPECTIVE STUDY

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Section: Discussionmentioning

confidence: 99%

A Gene Expression Profile of Peripheral Blood in Colorectal Cancer

Huang¹,

Terng²

2014

JMBT

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“…As previously described, demonstrated and obligate mutation carriers were included in segregation analysis to determine probability for co-segregation of the mutation and disease by chance [13]. …”

Section: Methodsmentioning

confidence: 99%

The Norwegian PMS2 founder mutation c.989-1G > T shows high penetrance of microsatellite instable cancers with normal immunohistochemistry

Grindedal

Aarset

Bjørnevoll

et al. 2014

Hered Cancer Clin Pract

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BackgroundUsing immunohistochemistry (IHC) to select cases for mismatch repair (MMR) genetic testing, we failed to identify a large kindred with the deleterious PMS2 mutation c.989-1G > T. The purpose of the study was to examine the sensitivity of IHC and microsatellite instability-analysis (MSI) to identify carriers of the mutation, and to estimate its penetrance and expressions.MethodsAll carriers and obligate carriers of the mutation were identified. All cancer diagnoses were confirmed. IHC and MSI-analysis were performed on available tumours. Penetrances of cancers included in the Amsterdam and the Bethesda Criteria, for MSI-high tumours and MSI-high and low tumours were calculated by the Kaplan-Meier algorithm.ResultsProbability for co-segregation of the mutation and cancers by chance was 0.000004. Fifty-six carriers or obligate carriers were identified. There was normal staining for PMS2 in 15/18 (83.3%) of tumours included in the AMS1/AMS2/Bethesda criteria. MSI-analysis showed that 15/21 (71.4%) of tumours were MSI-high and 4/21 (19.0%) were MSI-low. Penetrance at 70 years was 30.6% for AMS1 cancers (colorectal cancers), 42.8% for AMS2 cancers, 47.2% for Bethesda cancers, 55.6% for MSI-high and MSI-low cancers and 52.2% for MSI-high cancers.ConclusionsThe mutation met class 5 criteria for pathogenicity. IHC was insensitive in detecting tumours caused by the mutation. Penetrance of cancers that displayed MSI was 56% at 70 years. Besides colorectal cancers, the most frequent expressions were carcinoma of the endometrium and breast in females and stomach and prostate in males.

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“…The number of informative meioses for all families carrying a single variant were summed before calculating the probability that the variant is not disease causing according to Møller and colleagues. 15 British/Dutch guidelines 16 have suggested that the presence of genotypephenotype discordance (affected non-carrier or non-affected carrier) precludes the use of the SISA method of predicting disease association. When we encountered cases of discordance, we reviewed the IVCT records (phenotype) and calculated the probability that the IVCT responses represented an abnormal response.…”

Section: Segregation Analysesmentioning

confidence: 99%

“…The requirement for a specialized invasive procedure (muscle biopsy and IVCT) for accurate phenotyping and the lack of validity in combining families for linkage in a heterogeneous disorder has meant this is not a realistic option. Møller and colleagues, 15 however, proposed a simplified method for segregation analysis (SISA), where combining the number of informative meioses from more than one family carrying the same variant, can legitimately be used to generate a probability of association between genotype and phenotype. Use of the SISA method has been proposed as a tool to identify likely pathogenic variants in generic guidelines for classification of genetic variants.…”

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confidence: 99%