Kruisselbrink, Teresa M

PURPOSE The autosomal dominant cancer predisposition disorders hereditary breast and ovarian cancer (HBOC) and Lynch syndrome (LS) are genetic conditions for which early identification and intervention have a positive effect on the individual and public health. The goals of this study were to determine whether germline genetic screening using exome sequencing could be used to efficiently identify carriers of HBOC and LS. METHODS Participants were recruited from three geographically and racially diverse sites in the United States (Rochester, MN; Phoenix, AZ; Jacksonville, FL). Participants underwent Exome+ sequencing (Helix Inc, San Mateo, CA) and return of results for specific genetic findings: HBOC ( BRCA1 and BRCA1) and LS ( MLH1, MSH2, MSH6, PMS2, and EPCAM). Chart review was performed to collect demographics and personal and family cancer history. RESULTS To date, 44,306 participants have enrolled in Tapestry. Annotation and interpretation of all variants in genes for HBOC and LS resulted in the identification of 550 carriers (prevalence, 1.24%), which included 387 with HBOC (27.2% BRCA1, 42.8% BRCA2) and 163 with LS (12.3% MSH6, 8.8% PMS2, 4.5% MLH1, 3.8% MSH2, and 0.2% EPCAM). More than half of these participants (52.1%) were newly diagnosed carriers with HBOC and LS. In all, 39.2% of HBOC/LS carriers did not satisfy National Comprehensive Cancer Network (NCCN) criteria for genetic evaluation. NCCN criteria were less commonly met in underrepresented minority populations versus self-reported White race (51.5% v 37.5%, P = .028). CONCLUSION Our results emphasize the need for wider utilization of germline genetic sequencing for enhanced screening and detection of individuals who have LS and HBOC cancer predisposition syndromes.

AbstractBackgroundWe characterized the pharmacogenomics (PGx) results received by diagnostic odyssey patients as secondary findings during clinical whole exome sequencing (WES) testing as a part of their care in Mayo Clinic's Individualized Medicine Clinic to determine the potential benefits and limitations to this cohort.MethodsWES results on 94 patients included a subset of PGx variants in CYP2C19, CYP2C9, and VKORC1 if identified in the patient. Demographic, phenotypic, and medication usage information was abstracted from patient medical data. A pharmacist interpreted the PGx results in the context of the patients’ current medication use and made therapeutic recommendations.ResultsThe majority was young with a median age of 10 years old, had neurological involvement in the disease presentation (71%), and was currently taking medications (90%). Of the 94 PGx‐evaluated patients, 91% had at least one variant allele reported and 20% had potential immediate implications on current medication use.ConclusionDue to the disease complexity and medication needs of diagnostic odyssey patients, there may be immediate benefit obtained from early life PGx testing for many and most will likely find benefit in the future. These results require conscientious interpretation and management to be actionable for all prescribing physicians throughout the lifetime of the patient.

Whether disclosure of genetic risk for coronary heart disease (CHD) influences shared decision-making (SDM) regarding use of statins to reduce CHD risk is unknown. We randomized 207 patients, age 45–65 years, at intermediate CHD risk, and not on statins, to receive the 10-year risk of CHD based on conventional risk factors alone (n=103) or in combination with a genetic risk score (n=104). A genetic counselor disclosed this information followed by a physician visit for SDM regarding statin therapy. A novel decision aid was used in both encounters to disclose the CHD risk estimates and facilitate SDM regarding statin use. Patients reported their decision quality and physician visit satisfaction using validated surveys. There were no statistically significant differences between the two groups in the SDM score, satisfaction with the clinical encounter, perception of the quality of the discussion or of participation in decision-making and physician visit satisfaction scores. Quantitative analyses of a random subset of 80 video-recorded encounters using the OPTION5 scale also showed no significant difference in SDM between the two groups. Disclosure of CHD genetic risk using an electronic health record-linked decision aid did not adversely affect SDM or patients’ satisfaction with the clinical encounter. Trial registration number NCT01936675; Results.

Background— Whether knowledge of genetic risk for coronary heart disease (CHD) affects health-related outcomes is unknown. We investigated whether incorporating a genetic risk score (GRS) in CHD risk estimates lowers low-density lipoprotein cholesterol (LDL-C) levels. Methods and Results— Participants (n=203, 45–65 years of age, at intermediate risk for CHD, and not on statins) were randomly assigned to receive their 10-year probability of CHD based either on a conventional risk score (CRS) or CRS + GRS ( + GRS). Participants in the + GRS group were stratified as having high or average/low GRS. Risk was disclosed by a genetic counselor followed by shared decision making regarding statin therapy with a physician. We compared the primary end point of LDL-C levels at 6 months and assessed whether any differences were attributable to changes in dietary fat intake, physical activity levels, or statin use. Participants (mean age, 59.4±5 years; 48% men; mean 10-year CHD risk, 8.5±4.1%) were allocated to receive either CRS (n=100) or + GRS (n=103). At the end of the study period, the + GRS group had a lower LDL-C than the CRS group (96.5±32.7 versus 105.9±33.3 mg/dL; P =0.04). Participants with high GRS had lower LDL-C levels (92.3±32.9 mg/dL) than CRS participants ( P =0.02) but not participants with low GRS (100.9±32.2 mg/dL; P =0.18). Statins were initiated more often in the + GRS group than in the CRS group (39% versus 22%, P <0.01). No significant differences in dietary fat intake and physical activity levels were noted. Conclusions— Disclosure of CHD risk estimates that incorporated genetic risk information led to lower LDL-C levels than disclosure of CHD risk based on conventional risk factors alone. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT01936675.