Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification.

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification.

Evaluating the performance of the breast cancer genetic risk models BOADICEA, IBIS, BRCAPRO and Claus for predicting BRCA1/2 mutation carrier probabilities: a study based on 7352 families from the German Hereditary Breast and Ovarian Cancer Consortium.

BACKGROUND: Risk prediction models are widely used in clinical genetic counselling. Despite their frequent use, the genetic risk models BOADICEA, BRCAPRO, IBIS and extended Claus model (eCLAUS), used to estimate BRCA1/2 mutation carrier probabilities, have never been comparatively evaluated in a large sample from central Europe. Additionally, a novel version of BOADICEA that incorporates tumour pathology information has not yet been validated. PATIENTS AND METHODS: Using data from 7352 German families we estimated BRCA1/2 carrier probabilities under each model and compared their discrimination and calibration. The incremental value of using pathology information in BOADICEA was assessed in a subsample of 4928 pedigrees with available data on breast tumour molecular markers oestrogen receptor, progesterone receptor and human epidermal growth factor 2. RESULTS: BRCAPRO (area under receiver operating characteristic curve (AUC)=0.80 (95% CI 0.78 to 0.81)) and BOADICEA (AUC=0.79 (0.78-0.80)), had significantly higher diagnostic accuracy than IBIS and eCLAUS (p<0.001). The AUC increased when pathology information was used in BOADICEA: AUC=0.81 (95% CI 0.80 to 0.83, p<0.001). At carrier thresholds of 10% and 15%, the net reclassification index was +3.9% and +5.4%, respectively, when pathology was included in the model. Overall, calibration was best for BOADICEA and worst for eCLAUS. With eCLAUS, twice as many mutation carriers were predicted than observed. CONCLUSIONS: Our results support the use of BRCAPRO and BOADICEA for decision making regarding genetic testing for BRCA1/2 mutations. However, model calibration has to be improved for this population. eCLAUS should not be used for estimating mutation carrier probabilities in clinical settings. Whenever possible, breast tumour molecular marker information should be taken into account.

Aberrant splicing is a common mutational mechanism in MKS1, a key player in Meckel-Gruber syndrome.

Meckel-Gruber syndrome (MKS) is an autosomal recessive, usually lethal multisystemic disorder characterized by early developmental anomalies of the central nervous system, cystic kidney dysplasia, hepatobiliary ductal plate malformation, and postaxial polydactyly. Three MKS loci have been mapped and recently, two genes were identified: MKS1 on 17q22 in Caucasian kindreds and MKS3 on 8q22 in Omani and Pakistani families, putting MKS on the growing list of ciliary disorders ("ciliopathies"). We performed linkage analysis for MKS1-3 in 14 consanguineous and/or multiplex families of different ethnic origins with histologic diagnosis and at least three classic MKS manifestations in each kindred. Unexpectedly, only five families were linked to any of the known MKS loci, clearly indicating further locus heterogeneity. All five families showed homozygosity for MKS1 and, intriguingly, were of non-Caucasian origin. MKS1 sequencing revealed no mutation in two of these pedigrees, whereas different, novel splicing defects were identified in the three other families and an additional sporadic German patient. Given that all of our mutations and two of the in total four known MKS1 changes cause aberrant splicing (while the other two known mutations were frameshift mutations), we hypothesize that splicing defects are a crucial mutational mechanism in MKS1 which apparently is one of the main loci and key players in MKS. Our results indicate that MKS1 mutations are not restricted to the Caucasian gene pool and suggest further genetic heterogeneity for MKS. Overall, our data have immediate implications for genetic counselling and testing approaches in MKS.