Unleashing the power of precision medicine: Precision medicine promises the ability to identify risks and treat patients on the basis of pathogenic genetic variation. Two studies combined exome sequencing results for over 50,000 people with their electronic health records. Dewey et al. found that ∼3.5% of individuals in their cohort had clinically actionable genetic variants. Many of these variants affected blood lipid levels that could influence cardiovascular health. Abul-Husn et al. extended these findings to investigate the genetics and treatment of familial hypercholesterolemia, a risk factor for cardiovascular disease, within their patient pool. Genetic screening helped identify at-risk patients who could benefit from increased treatment. Science , this issue p. 10.1126/science.aaf6814 , p. 10.1126/science.aaf7000

Statin-associated muscle symptoms (SAMS) are the most common form of statin intolerance and are associated with increased risk of cardiovascular events that manifest from statin underutilization and discontinuation. The reported frequencies of SAMS are divergent in the literature. The writing group estimates the prevalence of SAMS, namely all muscle symptoms temporally related to statin use but without regard to causality, to be about 10% (range 5% to 25%), and the prevalence of pharmacological SAMS, specifically muscle symptoms resulting from pharmacological properties of the statin, to be about 1-2% (range 0.5% to 4%). In clinical practice, SAMS are likely to result from a combination of pharmacological and nonpharmacological effects, however this does not make the symptoms any less clinically relevant. Regardless of the etiology, SAMS need to be addressed in accordance with patients' preferences and experiences. This clinical perspective reviews the epidemiology and underlying pathophysiology of SAMS, and the cardiovascular consequences resulting from statin discontinuation. We present patient-centered clinical and communication strategies to mitigate SAMS and improve medication adherence and outcomes among statin users. Treatment strategies include 1) optimizing lifestyle interventions, 2) modulating risk factors that may contribute to muscle symptoms, 3) optimizing statin tolerability by dose reduction, decreased dosing frequency, or use of an alternate statin with more favorable pharmacokinetic properties, and 4) use of non-statins, emphasizing those with evidence for atherosclerotic risk reduction, either in combination with or in place of statin therapy depending on the patient's circumstances. The focus of this clinical perspective is sustainable lipoprotein goal achievement, which is important for cardiovascular risk reduction.

The cost-effectiveness of screening the U.S. population for Centers for Disease Control and Prevention (CDC) Tier 1 genomic conditions is unknown. To estimate the cost-effectiveness of simultaneous genomic screening for Lynch syndrome (LS), hereditary breast and ovarian cancer syndrome (HBOC), and familial hypercholesterolemia (FH). Decision analytic Markov model. Published literature. Separate age-based cohorts (ages 20 to 60 years at time of screening) of racially and ethnically representative U.S. adults. Lifetime. U.S. health care payer. Population genomic screening using clinical sequencing with a restricted panel of high-evidence genes, cascade testing of first-degree relatives, and recommended preventive interventions for identified probands. Incident breast, ovarian, and colorectal cancer cases; incident cardiovascular events; quality-adjusted survival; and costs. Screening 100 000 unselected 30-year-olds resulted in 101 (95% uncertainty interval [UI], 77 to 127) fewer overall cancer cases and 15 (95% UI, 4 to 28) fewer cardiovascular events and an increase of 495 quality-adjusted life-years (QALYs) (95% UI, 401 to 757) at an incremental cost of $33.9 million (95% UI, $27.0 million to $41.1 million). The incremental cost-effectiveness ratio was $68 600 per QALY gained (95% UI, $41 800 to $88 900). Screening 30-, 40-, and 50-year-old cohorts was cost-effective in 99%, 88%, and 19% of probabilistic simulations, respectively, at a $100 000-per-QALY threshold. The test costs at which screening 30-, 40-, and 50-year-olds reached the $100 000-per-QALY threshold were $413, $290, and $166, respectively. Variant prevalence and adherence to preventive interventions were also highly influential parameters. Population averages for model inputs, which were derived predominantly from European populations, vary across ancestries and health care environments. Population genomic screening with a restricted panel of high-evidence genes associated with 3 CDC Tier 1 conditions is likely to be cost-effective in U.S. adults younger than 40 years if the testing cost is relatively low and probands have access to preventive interventions. National Human Genome Research Institute.

Background: Familial hypercholesterolemia (FH) is the most common cardiovascular genetic disorder and, if left untreated, is associated with increased risk of premature atherosclerotic cardiovascular disease, the leading cause of preventable death in the United States. Although FH is common, fatal, and treatable, it is underdiagnosed and undertreated due to a lack of systematic methods to identify individuals with FH and limited uptake of cascade testing. Methods and Results: This mixed-method, multi-stage study will optimize, test, and implement innovative approaches for both FH identification and cascade testing in 3 aims. To improve identification of individuals with FH, in Aim 1, we will compare and refine automated phenotype-based and genomic approaches to identify individuals likely to have FH. To improve cascade testing uptake for at-risk individuals, in Aim 2, we will use a patient-centered design thinking process to optimize and develop novel, active family communication methods. Using a prospective, observational pragmatic trial, we will assess uptake and effectiveness of each family communication method on cascade testing. Guided by an implementation science framework, in Aim 3, we will develop a comprehensive guide to identify individuals with FH. Using the Conceptual Model for Implementation Research, we will evaluate implementation outcomes including feasibility, acceptability, and perceived sustainability as well as health outcomes related to the optimized methods and tools developed in Aims 1 and 2. Conclusions: Data generated from this study will address barriers and gaps in care related to underdiagnosis of FH by developing and optimizing tools to improve FH identification and cascade testing.