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Background: Lp(a) (lipoprotein [a]) levels are higher in individuals of African ancestry (AA) than in individuals of European ancestry (EA). We examined associations of genetically predicted Lp(a) levels with (1) atherosclerotic cardiovascular disease subtypes: coronary heart disease, cerebrovascular disease, peripheral artery disease, and abdominal aortic aneurysm and (2) nonatherosclerotic cardiovascular disease phenotypes, stratified by ancestry. Methods: We performed (1) Mendelian randomization analyses for previously reported cardiovascular associations and (2) Mendelian randomization–phenome-wide association analyses for novel associations. Analyses were stratified by ancestry in electronic Medical Records and Genomics, United Kingdom Biobank, and Million Veteran Program cohorts separately and in a combined cohort of 804 507 EA and 103 580 AA participants. Results: In Mendelian randomization analyses using the combined cohort, a 1-SD genetic increase in Lp(a) level was associated with atherosclerotic cardiovascular disease subtypes in EA—odds ratio and 95% CI for coronary heart disease 1.28 (1.16–1.41); cerebrovascular disease 1.14 (1.07–1.21); peripheral artery disease 1.22 (1.11–1.34); abdominal aortic aneurysm 1.28 (1.17–1.40); in AA, the effect estimate was lower than in EA and nonsignificant for coronary heart disease 1.11 (0.99–1.24) and cerebrovascular disease 1.06 (0.99–1.14) but similar for peripheral artery disease 1.16 (1.01–1.33) and abdominal aortic aneurysm 1.34 (1.11–1.62). In EA, a 1-SD genetic increase in Lp(a) level was associated with aortic valve disorders 1.34 (1.10–1.62), mitral valve disorders 1.18 (1.09–1.27), congestive heart failure 1.12 (1.05–1.19), and chronic kidney disease 1.07 (1.01–1.14). In AA, no significant associations were noted for aortic valve disorders 1.08 (0.94–1.25), mitral valve disorders 1.02 (0.89–1.16), congestive heart failure 1.02 (0.95–1.10), or chronic kidney disease 1.05 (0.99–1.12). Mendelian randomization–phenome-wide association analyses identified novel associations in EA with arterial thromboembolic disease, nonaortic aneurysmal disease, atrial fibrillation, cardiac conduction disorders, and hypertension. Conclusions: Many cardiovascular associations of genetically increased Lp(a) that were significant in EA were not significant in AA. Lp(a) was associated with atherosclerotic cardiovascular disease in four major arterial beds in EA but only with peripheral artery disease and abdominal aortic aneurysm in AA. Additionally, novel cardiovascular associations were detected in EA.

Background: Perceived personal control (PPC) represents the belief that a person can alter his/her own situation or state. Higher PPC has been associated with increased health-related quality of life and helps facilitate healthy behavioral changes. We investigated whether disclosure of coronary heart disease (CHD) genetic risk influences PPC and genetic counseling satisfaction (GCS) in the myocardial infarction genes (MI-GENES) study, a randomized controlled trial of disclosing genetic risk of CHD. Methods: Participants (40-65 year-old, at intermediate 10-year CHD risk, and not on statins) were randomized to receive estimated 10-year risk of CHD based on their Framingham Risk Score (FRS) or FRS plus a 28 SNP genetic risk score (FRS*GRS). CHD risk was disclosed in each arm by a genetic counselor during a 30-minute scripted session that included a discussion of the impact of family history on CHD risk. For FRS*GRS participants, the genetic counselor also reviewed how their genetic risk score altered their FRS. Each participant then met with a physician to engage in shared-decision making regarding the need for statin therapy. Afterwards, study participants were asked to complete validated surveys to assess PPC and GCS. The 9-item PPC questionnaire was scored 0-9, with higher scores indicating greater control beliefs. The 5-item GCS questionnaire was scored 0-10, with greater scores indicating greater satisfaction with the disclosure session. Results: 207 patients (mean age 58.8±5 years, 46.7% males) were randomized to receive either FRS or FRS*GRS. Patients randomized to receive FRS*GRS had higher PPC compared to FRS although the absolute difference was small (8.85±0.77 vs. 8.54±1.31, P=0.016). Patients randomized to receive FRS*GRS also had a higher GCS score than FRS patients (9.08±2.67 vs. 8.3±3.67, P=0.050]. Conclusions: Disclosure of genetic risk for CHD did not adversely affect PPC or GCS. In fact, patients who received CHD genetic risk information had higher PPC and GCS. Our findings suggest that disclosure of CHD genetic risk is appreciated by patients and may empower them to improve health-related behaviors.

Background: Arterial stiffness is associated with increased risk for adverse cardiovascular outcome. Ankle-brachial index (ABI) is a measure reflective of systemic atherosclerosis. Whether it can predict central aortic stiffness and its progression is unknown. As such, we investigated the impact of ABI on carotid-femoral pulse wave velocity (cfPWV) and aortic characteristic impedance (Z c ) in apparently healthy adults from the community. Methods: Participants were from the GENOA study without cardiovascular disease at baseline (December 2000 to September 2006) and completed follow-up (September 2009 to December 2012) assessment (n=358, 63%women, 69% hypertensive). ABI was measured by standard protocol at baseline. cfPWV was measured by applanation tonometry. Difference in log-cfPWV between two visits ([[Unable to Display Character: &#8710;]]log-cfPWV) was used to estimate progression of aortic stiffness. Z c was ascertained at 2 nd visit using carotid tonometry followed by echocardiography (Cardiovascular Engineering Inc., Norwood). Results: After a mean follow-up of 8.5±0.9 years, cfPWV increased from 9.3±2.4m/s to 11.1±5.0m/s. After adjusted for age, sex and time-interval between two visits, lower ABI was associated with greater [[Unable to Display Character: &#8710;]]log-cfPWV (β±SE:-0.41±0.15), and increased risk for higher log-cfPWV (β±SE:-0.38±0.12) and higher log-Z c at 2 nd visit (β±SE:-0.38±0.18) (all P≤0.04). Diabetes and renal function at baseline were predictors for higher cfPWV and Z c ; hypertension and metabolic syndrome were only predictors of cfPWV; while age and male gender were major predictors for [[Unable to Display Character: &#8710;]]log-cfPWV (all P≤0.04). The association of ABI with cfPWV or Z c remained significant after adjustment for these covariates (both P<0.05). Greater [[Unable to Display Character: &#8710;]]log-cfPWV was associated with increased risk for higher log-Z c ; longer time-interval amplified this effect (both p for [[Unable to Display Character: &#8710;]]log-cfPWV and [[Unable to Display Character: &#8710;]]log-cfPWV x time-interval ≤0.03). Conclusions: Lower ABI predicts progression of aortic stiffness, leading to both increased aortic wall stiffness (PWV) and greater aortic area-flow mismatch (Z c ), suggesting the impact of subclinical atherosclerosis on proximal aortic stiffening.

Background: Familial hypercholesterolemia (FH) is an important public health burden as it is a relatively common Mendelian genetic disorder which is associated with dramatically increased lifetime risk for premature atherosclerotic cardiovascular disease (ASCVD) due to elevated plasma low-density lipoprotein cholesterol (LDL-C) levels. Little is known about prevalence and control of FH in the US. Objective: To develop an electronic phenotyping algorithm for rapid identification of FH in electronic health records (EHRs) and thereby address knowledge gaps in prevalence and control of FH. Methods: We identified patients in the Mayo Employee and Community Health (ECH) system who met the following inclusion criteria: 1) gave research authorization, 2) any LDL-C in EHR ≥190 mg/dL; 2) triglycerides <400 mg/dL; 3) absence of secondary causes of hyperlipidemia (hypothyroidism, cholestatic liver diseases, nephrotic syndrome, renal failure, and pregnancy). Next we applied the Dutch Lipid Clinic Network (DLCN) criteria to ascertain FH cases. ASCVD-related diagnosis codes, laboratory data, and medications were obtained from structured EHR datasets. We used the Mayo natural language processing (NLP) system to ascertain presence of family and personal history of premature ASCVD, xanthomas and corneal arcus from clinical text notes. Results: Of a total of 131,000 patients seen in ECH clinics between July 1993 and December 2014, 6018 met the inclusion criteria. Implementing the electronic phenotyping algorithm for FH in these patients identified 178 definite and 369 probable cases (DLCN score >8 and 6-8 points, respectively) with an overall FH prevalence of 0.4% (1:240). Blinded expert review of 160 randomly chosen patients showed positive and negative predictive values for electronic phenotyping algorithm at 85% and 90%, respectively. Only 40% of these patients achieved LDL-C ≤100 mg/dL on treatment. Conclusions: 1) An EHR-based phenotyping algorithm that included NLP had reasonable accuracy in ascertaining FH cases. 2) Implementing this algorithm revealed the prevalence of FH in the study cohort to be nearly twice the current estimate of 1:500 in the general population. 3) Less than half of the FH patients had optimal LDL-C levels on treatment.

Background: Whether disclosing genetic risk for coronary heart disease (CHD) to individuals influences information seeking and information sharing is not known. Methods: The myocardial infarction genes (MI-GENES) trial randomized participants aged 45-65 years who were at intermediate risk for CHD based on conventional risk factors and not on statins, to receive their conventional risk score (CRS) or their CRS plus a genetic risk score (GRS) based on 28 susceptibility variants. CHD risk was disclosed by a genetic counselor and then discussed with a physician. Surveys to assess information seeking (including internet use and accessing electronic health records (EHR)) were completed before and three and six months after risk disclosure. Information sharing parameters were assessed after risk disclosure. We assessed whether these behaviors differed by GRS disclosure, or by high (≥1.1) or low (<1.1) GRS. Adjustments were made for age, sex, family history of CHD, baseline CRS and GRS, and education. Results were reported as the mean difference (and standard error) in the score for each survey response between the GRS and CRS participants, with significance determined by regression analysis. Results: GRS participants accessed their EHR to obtain information related to their CHD risk more than CRS participants (0.14 ± 0.06, p=0.03). Overall internet use (0.61 ± 0.23, p=0.01), as well as internet use to seek information about heart disease (0.14 ± 0.06, p=0.02) and how genetic factors affect risk of having a heart attack (0.23 ± 0.07, p=0.002), was significantly higher in the GRS participants. GRS participants shared information about heart attack risk with others (0.35 ± 0.13, p=0.007), particularly family members (0.1 ± 0.04, p=0.02), (V4: 0.10 ± 0.05, p=0.05), and their primary care provider (V4: 0.15 ± 0.07, p=0.03) more than CRS participants. Internet use, EHR access, and information sharing did not differ significantly between the high and low GRS groups. Conclusions: Disclosure of GRS for CHD resulted in greater information seeking (including internet use and EHR access) and information sharing by study participants. Disclosure of genetic risk for CHD may help advance patient engagement in precision medicine.

Fibromuscular dysplasia (FMD) is a nonatherosclerotic vascular disease leading to arterial stenosis, aneurysm and dissection, mainly in renal and carotid arteries. FMD has higher prevalence in females (80-90%) and is associated with hypertension and stroke. The pathophysiology of FMD is unclear and a genetic origin is suspected. We performed a genetic association study in European ancestry individuals. The discovery included 249 cases and 689 controls, in which we analyzed ∼26K common variants (MAF>0.05) using an exome-chip array. We followed up 13 loci (P<10-4) in 393 cases and 2537 controls and replicated a signal on Chr6. Three additional studies (combined Ncases=512, Ncontrols=669) confirmed this association, with an overall OR of 1.39, (P=7.4х10e-10 , All Ncases=1154, All Ncontrols=3895). The FMD risk variant is intronic to the phosphatase and actin regulator 1 gene (PHACTR1), involved in angiogenesis and cell migration. PHACTR1 is a risk locus for coronary artery disease, migraine, and cervical artery dissection, which may occur in FMD. We found a significant association between the risk allele and higher central pulse pressure (P=0.0009), increased intima media thickness (P=0.001) and wall cross-sectional area (P=0.003) of carotids assessed by echotracking in 3800 population-based individuals. The correlation of genotypes with the expression of PHACTR1 in primary cultured human fibroblasts showed higher expression in FMD risk allele carriers, compared to non carriers (N=57, P=0.02). Finally, Phactr1 knockdown of zebrafish showed significantly dilated vessels (P=0.003) indicating impaired vascular development. In conclusion, we report the first risk locus for FMD with the largest genetic association study conducted so far. Our data reveal a common genetic variant at PHACTR1 providing indices of shared pathophysiology between FMD and other cardiovascular and neurovascular diseases.

Background: Compared to those with natural nocturnal blood pressure (BP) decreases, those lacking nocturnal BP decreases (“non-dippers”) are at greater risk of cardiovascular disease (CVD). Substantial evidence also supports a role of chronic systemic inflammation in the pathogenesis of CVD. The purpose of this study was to examine associations of markers of inflammation with two common definitions of BP dipping status using 24-hour ambulatory blood pressure (AMBP) readings. Methods: AMBP monitoring and assays of C-reactive protein (CRP), interleukin-6 (IL-6), e-selectin, tissue inhibitor of metalloproteinase-2 (TIMP-2), and a selection of thirteen other inflammatory-pathway biomarkers were performed in 722 participants (mean age 64 [range 42-83] years, 36% men, 39% black, 83% hypertensive) in the Genetic Epidemiology Network of Arteriopathy (GENOA) Study (2001-2004). Non-dippers were classified using two common definitions: (1) nocturnal systolic and diastolic BP both decreased by <10% compared to daytime values [“dual non-dippers”, n=161 (22%)], and (2) nocturnal SBP decreased by <10% [“systolic non-dippers”, n=380 (53%)]. Logistic regressions, fit with generalized estimating equations to account for sibship clustering, yielded odds ratios (OR) of dipping status for log-transformed inflammatory biomarkers, adjusted for age, race, and sex. Results: IL-6 (range 0-37 pg/ml) was associated with dual non-dipping status (OR=1.55 [95%CI: 1.03, 2.32] p=0.035), translating into a 55% increase in the likelihood of being a dual non-dipper for every approximate doubling of IL-6. IL-6 (OR=1.63 [1.13, 2.35] p=0.009) and CRP (OR=1.35 [1.08,1.68] p=0.008) overall, as well as e-selectin (OR=0.49 [0.28, 0.87] p=0.014) and TIMP-2 (OR=0.54 [0.30,0.98] p=0.041) in hypertensive subjects were associated with systolic non-dipping status. Conclusions: These results suggest that non-dipping classification should be approached with prudence, as the two different criteria may influence conclusions about predictive marker associations. In addition, markers involved in direct versus inhibitory inflammation pathways may operate differentially across patient subgroups. Our findings support the link between inflammation and non-dipping circadian BP patterns and provide novel information on markers and definitions which may be useful for early detection and subsequent prevention of CVD.

Background: Genome-wide association studies (GWAS) have identified several common variants associated with abdominal aortic aneurysm (AAA). We investigated whether a multi-locus genetic risk score (GRS) for AAA was associated with presence and progression of AAA in a case-control study. Methods: The study comprised of 1098 patients with AAA (74±8 years, 83% men) and 6538 controls (67±10 years, 58% men) enrolled in the Mayo Vascular Disease Biorepository. AAA was defined as a transverse diameter of abdominal aorta ≥ 3.0 cm or history of AAA repair. Controls were participants without known AAA. We found five single nucleotide polymorphisms (SNPs) previously shown to be associated with AAA at GWAS significance (P≤10^-8) in NHGRI GWAS catalog and PubMed. A GRS for AAA for each individual was calculated from four SNPs (rs2383107, rs7025486, rs599839, rs1466535) that were replicated in our cohort, by summing the number of risk alleles for each SNP weighted by their estimated effect sizes in GWAS catalog or published largest meta-analysis. Results: GRS was associated with presence of AAA: odds ratio (OR) (95% confidence interval): 1.06 (1.03-1.08). The association remained significant after adjustment for age, sex, cardiovascular risk factors, and atherosclerotic cardiovascular diseases: adjusted OR: 1.05 (1.03-1.08). Further adjustment for each SNP did not attenuate association of GRS with presence of AAA (All P<0.001). GRS was not associated with family history of aortic aneurysm (P=0.4). Adding GRS to conventional risk factors improved net reclassification index by 16% (P<0.001).In a subset of patients with AAA who had sequential imaging studies (n=628), GRS was associated with AAA growth rate ≥ 1.75 mm/year (median of the cohort) after adjustment for baseline AAA size: adjusted OR: 1.07 (1.00-1.14). No conventional risk factors were associated with AAA growth. Patients with GRS > 5.24 (median of the cohort) had 1.31 times higher odds of having AAA and 1.64 times higher odds of having AAA growth rate ≥1.75 mm/year compared to those with GRS ≤ 5.24 (both P≤0.005). Conclusions: A multi-locus GRS was associated with presence of AAA and aneurysm growth, suggesting genetic predisposition to disease initiation and progression.

Background The association between the 9p21-3 locus and coronary heart disease (CHD) is well known. We performed a systematic review of the literature to assess whether this locus was associated with severity of coronary atherosclerosis. Data Sources Multiple relevant electronic databases were searched through September 2012 for English language studies with comparative design. Data extraction We tested the association of the 9p21-3 locus: 1) measures of severity of coronary atherosclerosis [number of diseased vessels, Gensini Score, Duke CHD Prognostic Index (Dc.PI)]. 2) angiographic outcomes [change in minimum lumen diameter ([[Unable to Display Character: &#8710;]]MLD) and number of new lesions at follow-up] and 3) key clinical outcomes (all-cause mortality, recurrent myocardial infarction and need for coronary revascularization). Genotypes were classified either as homozygous low risk (Lo) or homozygous high risk (Hi). Data Synthesis Relative risks (RR) were pooled using the random effects model. Seventeen distinct data sets that included 15,826 participants were analyzed. Ten studies (n=9807) reported number of diseased vessels at baseline. Hi genotype was associated with a 33.7% increased risk of triple vessel disease (95% CI 1.08-1.65; p=0.01). The Hi genotype was associated 0.27 higher baseline Gensini Score (95% CI 0.04-0.48; p=0.01) in 3787 individuals. The locus was not associated with Dc.PI [RR=0.21 (95% CI -0.14-0.55; p=0.25)]. The high risk genotype did not predict [[Unable to Display Character: &#8710;]]MLD or number of new lesions at follow-up. There was no difference between Hi and Lo genotypes in terms of all-cause mortality [RR=1.13 (95%CI 0.90-1.41;p=0.28)], recurrent myocardial infarction (95%CI 0.92-1.40; p=0.24) or frequency of coronary revascularization [RR=1.101 95% CI (0.78-1.57); p=0.56]. Conclusion An association between 9p21-3 and greater baseline severity of coronary atherosclerosis was seen in this meta-analysis. However no association was seen between 9p21-3 and adverse angiographic and clinical outcomes which may be due to diminishing genetic risk following dietary modification and statin therapy.

Background: Abdominal aortic aneurysm (AAA) is a complex and heterogeneous disorder. We hypothesized that dense phenomapping using electronic health records (EHR) can identify subtypes of AAA with distinct clinical and genetic characteristics. Methods & Results: AAA cases (n=1108) and controls (n=4694) were identified from the Mayo vascular disease biorepository and had available high-density genotyping data. 132 Candidate genetic variants (p < 10E-5) associated with atherosclerotic cardiovascular disease (ASCVD) or AAA were selected from GWAS catalog. Using model-based Gaussian-mixture cluster analysis of 46 clinical features from 6 data domains, 24 data elements, 204 variables (including age, sex, vital signs, laboratory data, medication use, family history), spanning over 20 years of observational time in the EHR, we identified two subtypes of AAA: subtype 1(S1, n=421) with faster AAA growth rate (baseline size adjusted mean difference, 95% CI: 0.013, 0.001 to 0.020 cm / year faster, p = 0.03), higher all-cause mortality (age & sex adjusted hazard ratio, 95% CI: 1.36, 1.09 - 1.70, p < 0.01) than subtype 2 (S2, n=687). As compared with the controls, thyroid disorder / rheumatoid or osteoarthritis / infectious conditions were uniquely associated with increased odds ratio for S1; ASCVD / hyperlipidemia / hypertension were uniquely associated with increased odds ratio for S2. After adjustment for all group-specific diseases, genetic variants in CDKN2B-AS1, NOA1-REST, ERG, ZNF335-MMP9 and SMAD3 were associated with S1 and variants in MMP12, DAB2IP, LHFPL2, LPA, FSTL5 and SORT1 were associated with S2 (all FDR p < 0.05). After adjustment for disease comorbidities and genetic variants differently associated with S1 and S2, the increased risk for all-cause death of S1 than S2 and the difference in AAA expansion rate in subgroups attenuated (Both p-values > 0.09) Conclusions: We identified two subtypes of AAA with different rates of aneurysm expansion and all-cause mortality, which were associated with subtype-specific disease comorbidities and genetic markers, suggesting the potential of leveraging EHR to facilitate individualized medicine in patients with AAA.