Variants of Uncertain Significance (VUS) are genetic variants whose association with a disease phenotype has not been established. They are a common finding in sequencing-based genetic tests and pose a significant clinical challenge. The objective of this study was to assess the use of functional data to classify variants according to pathogenicity. We conduct functional analysis of a large set of BRCA1 VUS combining a validated functional assay with VarCall, a Bayesian hierarchical model to estimate the likelihood of pathogenicity given the functional data. The results from the functional assays were incorporated into a joint analysis of 214 BRCA1 VUS to predict their likelihood of pathogenicity (breast cancer). We show that applying the VarCall model (1.0 sensitivity; lower bound of 95% confidence interval (CI)=0.75 and 1.0 specificity; lower bound of 95% CI=0.83) to the current set of BRCA1 variants, use of the functional data would significantly reduce the number of VUS associated with the C-terminal region of the BRCA1 protein by ~87%. We extend this work developing yeast-based functional assays for two other genes coding for BRCT domain containing proteins, MCPH1 and MDC1. Analysis of missense variants in MCPH1 and MDC1 shows that structural inference based on the BRCA1 data set can aid in prioritising variants for further analysis. Taken together our results indicate that systematic functional assays can provide a robust tool to aid in clinical annotation of VUS. We propose that well-validated functional assays could be used for clinical annotation even in the absence of additional sources of evidence.

Hereditary cancer predisposition gene testing allows the identification of individuals at high risk of cancer that may benefit from increased surveillance, chemoprevention, and prophylactic surgery. In order to implement clinical genetic strategies adapted to each population’s needs and intrinsic genetic characteristic, this review aims to present the current status of knowledge about the spectrum of BRCA pathogenic variants in Latin American populations. We have conducted a comprehensive review of 33 studies published between 1994 and 2015 reporting the prevalence and/or spectrum of BRCA1 (OMIM 113705) and BRCA2 (OMIM 600185) variants. The combined sample size for these studies consisted of 4835 individuals from 13 countries in Latin America and the Caribbean, as well as in Hispanics in the United States. A total of 167 unique pathogenic variants have been reported in the existing literature. In unselected breast cancer cases, the prevalence ranged from 1.2 to 27.1 %. Some countries presented a few recurrent pathogenic variants, while others were characterized by diverse, non-recurrent variants. The proportion of BRCA pathogenic variants shared between Hispanics in the United States and Latin American populations was estimated at 10.4 %. Within Latin America and the Caribbean, 8.2 % of the BRCA variants reported were present in more than one country. Countries with high prevalence of BRCA pathogenic variants may benefit from more aggressive testing strategies, while testing of recurrent variant panels might present a cost-effective solution for improving genetic testing in some, but not all, countries.

Genetic testing for BRCA1, a DNA repair protein, can identify carriers of pathogenic variants associated with a substantially increased risk for breast and ovarian cancers. However, an association with increased risk is unclear for a large fraction of BRCA1 variants present in the human population. Most of these variants of uncertain clinical significance lead to amino acid changes in the BRCA1 protein. Functional assays are valuable tools to assess the potential pathogenicity of these variants. Here, we systematically probed the effects of substitutions in the C terminus of BRCA1: the N- and C-terminal borders of its tandem BRCT domain, the BRCT-[N-C] linker region, and the α1 and α′1 helices in BRCT-[N] and -[C]. Using a validated transcriptional assay based on a fusion of the GAL4 DNA-binding domain to the BRCA1 C terminus (amino acids 1396–1863), we assessed the functional impact of 99 missense variants of BRCA1. We include the data obtained for these 99 missense variants in a joint analysis to generate the likelihood of pathogenicity for 347 missense variants in BRCA1 using VarCall, a Bayesian integrative statistical model. The results from this analysis increase our understanding of BRCA1 regions less tolerant to changes, identify functional borders of structural domains, and predict the likelihood of pathogenicity for 98% of all BRCA1 missense variants in this region recorded in the population. This knowledge will be critical for improving risk assessment and clinical treatment of carriers of BRCA1 variants.

The Zika virus (ZIKV) is a mosquito-borne Flavivirus and can be transmitted through an infected mosquito bite or through human-to-human interaction by sexual activity, blood transfusion, breastfeeding, or perinatal exposure. After the 2015–2016 outbreak in Brazil, a strong link between ZIKV infection and microcephaly emerged. ZIKV specifically targets human neural progenitor cells, suggesting that proteins encoded by ZIKV bind and inactivate host cell proteins, leading to microcephaly. Here, we present a systematic annotation of interactions between human proteins and the seven non-structural ZIKV proteins corresponding to a Brazilian isolate. The interaction network was generated by combining tandem-affinity purification followed by mass spectrometry with yeast two-hybrid screens. We identified 150 human proteins, involved in distinct biological processes, as interactors to ZIKV non-structural proteins. Our interacting network is composed of proteins that have been previously associated with microcephaly in human genetic disorders and/or animal models. Further, we show that the protein inhibitor of activated STAT1 (PIAS1) interacts with NS5 and modulates its stability. This study builds on previously published interacting networks of ZIKV and genes related to autosomal recessive primary microcephaly to generate a catalog of human cellular targets of ZIKV proteins implicated in processes related to microcephaly in humans. Collectively, these data can be used as a resource for future characterization of ZIKV infection biology and help create a basis for the discovery of drugs that may disrupt the interaction and reduce the health damage to the fetus.

Genetic testing allows for the identification of germline DNA variations, which are associated with a significant increase in the risk of developing breast cancer (BC) and ovarian cancer (OC). Detection of a BRCA1 or BRCA2 pathogenic variant triggers several clinical management actions, which may include increased surveillance and prophylactic surgery for healthy carriers or treatment with the PARP inhibitor therapy for carriers diagnosed with cancer. Thus, standardized validated criteria for the annotation of BRCA1 and BRCA2 variants according to their pathogenicity are necessary to support clinical decision-making and ensure improved outcomes. Upon detection, variants whose pathogenicity can be inferred by the genetic code are typically classified as pathogenic, likely pathogenic, likely benign, or benign. Variants whose impact on function cannot be directly inferred by the genetic code are labeled as variants of uncertain clinical significance (VUS) and are evaluated by multifactorial likelihood models that use personal and family history of cancer, segregation data, prediction tools, and co-occurrence with a pathogenic BRCA variant. Missense variants, coding alterations that replace a single amino acid residue with another, are a class of variants for which determination of clinical relevance is particularly challenging. Here, we discuss current issues in the missense variant classification by following a typical life cycle of a BRCA1 missense variant through detection, annotation and information dissemination. Advances in massively parallel sequencing have led to a substantial increase in VUS findings. Although the comprehensive assessment and classification of missense variants according to their pathogenicity remains the bottleneck, new developments in functional analysis, high throughput assays, data sharing, and statistical models are rapidly changing this scenario.