Dikilitas, Ozan

AbstractObjective Familial hypercholesterolemia (FH), a prevalent genomic disorder that increases risk of coronary heart disease, remains significantly underdiagnosed. Clinical decision support (CDS) tools have the potential to increase FH detection. We describe our experience in the development and implementation of a genomic CDS for FH at a large academic medical center.Methods CDS development and implementation were conducted in four phases: (1) development and validation of an algorithm to identify “possible FH”; (2) obtaining approvals from institutional committees to develop the CDS; (3) development of the initial prototype; and (4) use of an implementation science framework to evaluate the CDS.Results The timeline for this work was approximately 4 years; algorithm development and validation occurred from August 2018 to February 2020. During this 4-year period, we engaged with 15 stakeholder groups to build and integrate the CDS, including health care providers who gave feedback at each stage of development. During CDS implementation six main challenges were identified: (1) need for multiple institutional committee approvals; (2) need to align the CDS with institutional knowledge resources; (3) need to adapt the CDS to differing workflows; (4) lack of institutional guidelines for CDS implementation; (5) transition to a new institutional electronic health record (EHR) system; and (6) limitations of the EHR related to genomic medicine.Conclusion We identified multiple challenges in different domains while developing CDS for FH and integrating it with the EHR. The lessons learned herein may be helpful in streamlining the development and deployment of CDS to facilitate genomic medicine implementation.

Background Atherosclerosis in >1 vascular bed (ie, polyvascular disease), often a feature of peripheral artery disease (PAD), is associated with high morbidity and mortality. We sought to identify risk factors for polyvascular involvement in patients with PAD. Methods and Results We performed 2‐sample Mendelian randomization using an inverse‐variance‐weighted approach, to assess 60 exposures including size and lipid content of atherogenic lipoproteins, blood pressure, glycated hemoglobin, and smoking as causal mediators for polyvascular disease in patients with PAD. Genetic instruments for these exposures were obtained from prior genome‐wide association studies. Patients with PAD were from the Mayo Vascular Disease Biorepository, and polyvascular disease (ie, concomitant coronary heart disease, cerebrovascular disease, and/or abdominal aortic aneurysm) was ascertained by validated phenotyping algorithms. Of 3279 patients with PAD, 61% had polyvascular disease. Genetically predicted levels of the lipid content and/or particle measures of very small and small size very low‐density lipoprotein, intermediate‐density lipoprotein, and large low‐density lipoprotein were associated with polyvascular disease: odds ratios (OR) of 1.80 (95% CI, 1.23–2.61), 1.70 (95% CI, 1.17–2.61), and 1.40 (95% CI, 1.09–1.80) per 1 SD increase in genetically determined levels, respectively. Both genetically predicted diastolic and systolic blood pressure were associated with polyvascular disease; OR per 10 mm Hg genetic increase in diastolic and systolic blood pressure were 1.66 (95% CI, 1.19–2.33) and 1.31 (95% CI, 1.07–1.60), respectively. Conclusions Lifetime exposure to increased lipid content and levels of very small and small very low‐density lipoprotein, intermediate‐density lipoprotein, and large low‐density lipoprotein particles as well as elevated blood pressure are associated with polyvascular involvement in patients with PAD. Reduction in levels of such exposures may limit progression of atherosclerosis in patients with PAD.

Background: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality; however, its genetic determinants remain incompletely defined. In total, 10 previously identified risk loci explain a small fraction of AAA heritability. Methods: We performed a genome-wide association study in the Million Veteran Program testing ≈18 million DNA sequence variants with AAA (7642 cases and 172 172 controls) in veterans of European ancestry with independent replication in up to 4972 cases and 99 858 controls. We then used mendelian randomization to examine the causal effects of blood pressure on AAA. We examined the association of AAA risk variants with aneurysms in the lower extremity, cerebral, and iliac arterial beds, and derived a genome-wide polygenic risk score (PRS) to identify a subset of the population at greater risk for disease. Results: Through a genome-wide association study, we identified 14 novel loci, bringing the total number of known significant AAA loci to 24. In our mendelian randomization analysis, we demonstrate that a genetic increase of 10 mm Hg in diastolic blood pressure (odds ratio, 1.43 [95% CI, 1.24–1.66]; P =1.6×10 −6 ), as opposed to systolic blood pressure (odds ratio, 1.06 [95% CI, 0.97–1.15]; P =0.2), likely has a causal relationship with AAA development. We observed that 19 of 24 AAA risk variants associate with aneurysms in at least 1 other vascular territory. A 29-variant PRS was strongly associated with AAA (odds ratio PRS , 1.26 [95% CI, 1.18–1.36]; P PRS =2.7×10 −11 per SD increase in PRS), independent of family history and smoking risk factors (odds ratio PRS+family history+smoking , 1.24 [95% CI, 1.14–1.35]; P PRS =1.27×10 −6 ). Using this PRS, we identified a subset of the population with AAA prevalence greater than that observed in screening trials informing current guidelines. Conclusions: We identify novel AAA genetic associations with therapeutic implications and identify a subset of the population at significantly increased genetic risk of AAA independent of family history. Our data suggest that extending current screening guidelines to include testing to identify those with high polygenic AAA risk, once the cost of genotyping becomes comparable with that of screening ultrasound, would significantly increase the yield of current screening at reasonable cost.

Electronic health record (EHR)-based clinical decision support (CDS) can address the low awareness and undertreatment of familial hypercholesterolemia (FH), a disorder associated with a markedly increased risk of coronary heart disease. We aimed to incorporate provider perspectives into the development and implementation of a CDS tool for FH. An implementation science framework and a user-centered design process were used to create a CDS tool for FH. Primary care physicians and specialist physicians participated in qualitative interviews, usability testing and an implementation survey. The CDS was configured in two formats—a best practice alert (BPA) and an in-basket message and subsequently deployed in the EHR in silent mode. The key themes that emerged from the analysis of interview transcripts included understanding and awareness of FH, clinical workflow, physician preferences and value of CDS tools, perspectives on patient needs and values and dissemination and implementation. Recommendations related to usability included preferred CDS format and placement, content, timing and frequency, and level of alert urgency/prioritization. In response to the survey, 84.6% of physicians agreed that the CDS would improve early FH diagnosis and 92.3% agreed that it would help them identify and manage FH patients. Physician feedback led to iterative CDS refinement. In summary, we developed a CDS tool for FH using an implementation science framework and physician feedback. Initial deployment revealed a significant burden of FH and the potential for the CDS tool to have a large impact.