Recall by genotype and cascade screening for familial hypercholesterolemia in a population-based biobank from Estonia.

PURPOSE: Large-scale, population-based biobanks integrating health records and genomic profiles may provide a platform to identify individuals with disease-predisposing genetic variants. Here, we recall probands carrying familial hypercholesterolemia (FH)-associated variants, perform cascade screening of family members, and describe health outcomes affected by such a strategy. METHODS: The Estonian Biobank of Estonian Genome Center, University of Tartu, comprises 52,274 individuals. Among 4776 participants with exome or genome sequences, we identified 27 individuals who carried FH-associated variants in the LDLR, APOB, or PCSK9 genes. Cascade screening of 64 family members identified an additional 20 carriers of FH-associated variants. RESULTS: Via genetic counseling and clinical management of carriers, we were able to reclassify 51% of the study participants from having previously established nonspecific hypercholesterolemia to having FH and identify 32% who were completely unaware of harboring a high-risk disease-associated genetic variant. Imaging-based risk stratification targeted 86% of the variant carriers for statin treatment recommendations. CONCLUSION: Genotype-guided recall of probands and subsequent cascade screening for familial hypercholesterolemia is feasible within a population-based biobank and may facilitate more appropriate clinical management.

Polygenic prediction of breast cancer: comparison of genetic predictors and implications for risk stratification.

BACKGROUND: Published genetic risk scores for breast cancer (BC) so far have been based on a relatively small number of markers and are not necessarily using the full potential of large-scale Genome-Wide Association Studies. This study aimed to identify an efficient polygenic predictor for BC based on best available evidence and to assess its potential for personalized risk prediction and screening strategies. METHODS: Four different genetic risk scores (two already published and two newly developed) and their combinations (metaGRS) were compared in the subsets of two population-based biobank cohorts: the UK Biobank (UKBB, 3157 BC cases, 43,827 controls) and Estonian Biobank (EstBB, 317 prevalent and 308 incident BC cases in 32,557 women). In addition, correlations between different genetic risk scores and their associations with BC risk factors were studied in both cohorts. RESULTS: The metaGRS that combines two genetic risk scores (metaGRS2 - based on 75 and 898 Single Nucleotide Polymorphisms, respectively) had the strongest association with prevalent BC status in both cohorts. One standard deviation difference in the metaGRS2 corresponded to an Odds Ratio = 1.6 (95% CI 1.54 to 1.66, p = 9.7*10- 135) in the UK Biobank and accounting for family history marginally attenuated the effect (Odds Ratio = 1.58, 95% CI 1.53 to 1.64, p = 7.8*10- 129). In the EstBB cohort, the hazard ratio of incident BC for the women in the top 5% of the metaGRS2 compared to women in the lowest 50% was 4.2 (95% CI 2.8 to 6.2, p = 8.1*10- 13). The different GRSs were only moderately correlated with each other and were associated with different known predictors of BC. The classification of genetic risk for the same individual varied considerably depending on the chosen GRS. CONCLUSIONS: We have shown that metaGRS2, that combined on the effects of more than 900 SNPs, provided best predictive ability for breast cancer in two different population-based cohorts. The strength of the effect of metaGRS2 indicates that the GRS could potentially be used to develop more efficient strategies for breast cancer screening for genotyped women.

Lessons learned during the process of reporting individual genomic results to participants of a population-based biobank.

The return of individual genomic results (ROR) to research participants is still in its early phase, and insight on how individuals respond to ROR is scarce. Studies contributing to the evidence base for best practices are crucial before these can be established. Here, we describe a ROR procedure conducted at a population-based biobank, followed by surveying the responses of almost 3000 participants to a range of results, and discuss lessons learned from the process, with the aim of facilitating large-scale expansion. Overall, participants perceived the information that they received with counseling as valuable, even when the reporting of high risks initially caused worry. The face-to-face delivery of results limited the number of participants who received results. Although the participants highly valued this type of communication, additional means of communication need to be considered to improve the feasibility of large-scale ROR. The feedback collected sheds light on the value judgements of the participants and on potential responses to the receipt of genetic risk information. Biobanks in other countries are planning or conducting similar projects, and the sharing of lessons learned may provide valuable insight and aid such endeavors.

Do Biobank Recall Studies Matter? Long-Term Follow-Up of Research Participants With Familial Hypercholesterolemia.

Recall-by-genotype (RbG) studies conducted with population-based biobank data remain urgently needed, and follow-up RbG studies, which add substance to this research approach, remain solitary. In such studies, potentially disease-related genotypes are identified and individuals with those genotypes are recalled for consultation to gather more detailed clinical phenotypic information and explain to them the meaning of their genetic findings. Familial hypercholesterolemia (FH) is among the most common autosomal-dominant single-gene disorders, with a global prevalence of 1 in 500 (Nordestgaard et al., Eur. Heart J., 2013, 34 (45), 3478-3490). Untreated FH leads to lifelong elevated LDL cholesterol levels, which can cause ischemic heart disease, with potentially fatal consequences at a relatively early age. In most cases, the pathogenesis of FH is based on a defect in one of three LDL receptor-related genes-APOB, LDLR, and PCSK9. We present our first long-term follow-up RbG study of FH, conducted within the Estonian Biobank (34 recalled participants from a pilot RbG study and 291 controls harboring the same APOB, LDLR, and PCSK9 variants that were included in the pilot study). The participants' electronic health record data (FH-related diagnoses, lipid-lowering treatment prescriptions) and pharmacogenomic risk of developing statin-induced myopathy were assessed. A survey was administered to recalled participants to discern the impact of the knowledge of their genetic findings on their lives 4-6 years later. Significant differences in FH diagnoses and lipid-lowering treatment prescriptions were found between the recalled participants and controls (34 and 291 participants respectively). Our study highlights the need for more consistent lipid-lowering treatment adherence checkups and encourage more follow-up RbG studies to be performed.

Spectrum and frequency of CHEK2 variants in breast cancer affected and general population in the Baltic states region, initial results and literature review.

BACKGROUND: While BRCA1/2 gene mutational spectrum and clinical features are widely studied, there is limited data on breast cancer-predisposing non-BRCA pathogenic/likely pathogenic variants (PV/LPVs) in the Baltic states region. According to previous studies, CHEK2 is the most frequent moderate-risk breast cancer predisposition gene. The study aimed to analyse the frequency and mutational spectrum of CHEK2 PV/LPVs in the Baltic states region and perform a literature review on the subject. METHODS: The study includes two cohorts - population-based Estonian biobank (EstBB) (N-152 349) and breast cancer affected cases from Latvia (N-105). In the cohort from Latvia, CHEK2, BRCA1, BRCA2, PALB2 testing with next-generation sequencing (NGS) was carried out in selected breast cancer cases. In the EstBB, the full SNP genotyped dataset Global Screening Array (GSA) (N-152 349) was used to screen CHEK2 PV/LPVs and variants c.319+2T > A (p.(?)), c.444+1G>A (p.(?)), c.433C > T (p.Arg145Trp), c.283C > T (p.Arg95*) in CHEK2 are reported from this dataset. In addition, a subset of the EstBB (N-4776) underwent whole-genome sequencing (WGS, N-2420) and whole-exome sequencing (WES, N-2356) and founder variants c.470T > C (p.Ile157Thr), c.444+1G>A (p.(?)), c.1100delC (p.Thr367Metfs*15) in CHEK2 were reported from this dataset. Moreover, a literature overview was performed on April 1, 2021, using the PubMed search of keywords 'CHEK2', 'breast cancer', 'Estonia', 'Lithuania', 'Latvia', 'Poland', 'Belarus' and 'Russia'. RESULTS: In the breast cancer affected cohort from Latvia 6 CHEK2 variants, classified as PV/LPVs, were observed (6/105; 5.7%), including recurrent ones c.470T > C (p.Ile157Thr) (1.9%) and del5395(ex9-10del; (p.Met304Leufs*16)) (1.9%), as well as single ones - c.1100delC (p.Thr367Metfs*15) (1%) and c.444+1G>A (p.(?)) (1%). From EstBB NGS data (N-4776) CHEK2 variant c.470T > C (p.Ile157Thr) was detected in 8.6% of cases, c.1100delC (p.Thr367Metfs*15) in 0.6% and c.444+1G>A (p.(?)) in 0.2% of cases. In the EstBB full cohort of SNP array data (N-152 349) CHEK2 variant c.444+1G>A (p.(?)) was detected in 0.02% of cases, c.319+2T > A (p.(?)) in 0.09% of cases, c.433C > T (p.Arg145Trp) in 0.02% of cases and c.283C > T (p.Arg95*) in <0.001% of cases. For the literature review altogether, 49 PubMed articles were found, 23 of which were relevant, representing CHEK2 PV/LPVs in the population of interest. Ten publications are from Poland, eight from Russia, three from Latvia and two from Belarus. CONCLUSIONS: This study is the first combined report on complete CHEK2 PV/LPVs screening in selected breast cancer affected cases in Latvia and large-scale population screening in Estonia, providing insight into the CHEK2 mutational spectrum in the Baltic states region. The initial results are in line with other studies that CHEK2 PV/LPVs frequency is around 5-6% of selected breast cancer cases. Here we report three CHEK2 PV/LPV - c.319+2T > A (p.(?)), c.433C > T (p.Arg145Trp), c.283C > T (p.Arg95*), that are novel for the Baltic states region. This is also the first report on c.1100delC (p.Thr367Metfs*15) and c.444+1G>A (p.(?)) from the Baltic states. High population frequency of c.470T > C (p. Ile157Thr) (8.6%) continues to question the variant's pathogenicity in particular populations. Other findings are concordant with previous reports from Latvia and neighbouring populations.

Precise, Genotype-First Breast Cancer Prevention: Experience With Transferring Monogenic Findings From a Population Biobank to the Clinical Setting.

Although hereditary breast cancer screening and management are well accepted and established in clinical settings, these efforts result in the detection of only a fraction of genetic predisposition at the population level. Here, we describe our experience from a national pilot study (2018-2021) in which 180 female participants of Estonian biobank (of >150,000 participants in total) were re-contacted to discuss personalized clinical prevention measures based on their genetic predisposition defined by 11 breast cancer-related genes. Our results show that genetic risk variants are relatively common in the average-risk Estonian population. Seventy-five percent of breast cancer cases in at-risk subjects occurred before the age of 50 years. Only one-third of subjects would have been eligible for clinical screening according to the current criteria. The participants perceived the receipt of genetic risk information as valuable. Fluent cooperation of project teams supported by state-of-art data management, quality control, and secure transfer can enable the integration of research results to everyday medical practice in a highly efficient, timely, and well-accepted manner. The positive experience in this genotype-first breast cancer study confirms the value of using existing basic genomic data from population biobanks for precise prevention.

Genotype-first approach to the detection of hereditary breast and ovarian cancer risk, and effects of risk disclosure to biobank participants.

Genotype-first approach allows to systematically identify carriers of pathogenic variants in BRCA1/2 genes conferring a high risk of familial breast and ovarian cancer. Participants of the Estonian biobank have expressed support for the disclosure of clinically significant findings. With an Estonian biobank cohort, we applied a genotype-first approach, contacted carriers, and offered return of results with genetic counseling. We evaluated participants' responses to and the clinical utility of the reporting of actionable genetic findings. Twenty-two of 40 contacted carriers of 17 pathogenic BRCA1/2 variants responded and chose to receive results. Eight of these 22 participants qualified for high-risk assessment based on National Comprehensive Cancer Network criteria. Twenty of 21 counseled participants appreciated being contacted. Relatives of 10 participants underwent cascade screening. Five of 16 eligible female BRCA1/2 variant carriers chose to undergo risk-reducing surgery, and 10 adhered to surveillance recommendations over the 30-month follow-up period. We recommend the return of results to population-based biobank participants; this approach could be viewed as a model for population-wide genetic testing. The genotype-first approach permits the identification of individuals at high risk who would not be identified by application of an approach based on personal and family histories only.

Disclosing genetic information to family members without consent: Five Australian case studies.

Genetic risk information is relevant to individual patients and also their blood relatives. Health practitioners (HPs) routinely advise patients of the importance of sharing genetic information with family members, especially for clinically actionable conditions where prevention is possible. However, some patients refuse to share genetic results with at-risk relatives, and HPs must choose whether to use or disclose genetic information without consent. This requires an understanding of their legal and ethical obligations, which research shows many HPs do not have. A recent UK case held that HPs have a duty to a patient's relatives where there is a proximate relationship, to conduct a balancing exercise of the benefit of disclosure of the genetic risk information to the relative against the interest of the patient in maintaining confidentiality. In Australia, there is currently no legal duty to disclose genetic information to a patient's at-risk relatives, but there are laws and guidelines governing unconsented use/disclosure of genetic information. These laws are inconsistent across different Australian states and health contexts, requiring greater harmonisation. Here we provide an up-to-date and clinically accessible resource summarising the laws applying to HPs across Australia, and outline five Australian case studies which have arisen in clinical genetics services, regarding the disclosure of genetic results to relatives without consent. The issues addressed here are relevant to any Australian HP with access to genetic information, as well as HPs and policy-makers in other jurisdictions considering these issues.