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Background: The pathophysiology of lipoprotein (a) [Lp(a)] remains obscure. We conducted a phenome wide analysis study (PheWAS) to identify pleiotropic effects of LPA variants. Methods: Among 51,843 European-ancestry participants (age 58±16 years, 54% female) of the electronic MEdical Records and Genomics (eMERGE) network we assessed whether LPA variants exhibited pleiotropic affects through an electronic health record-based PheWAS. We adjusted significant associations by presence of atherosclerotic cardiovascular disease (ASCVD; defined as a composite of coronary heart disease, cerebrovascular disease, and peripheral artery disease) to determine whether those associations were independent of ASCVD. Results: In PheWAS analysis, we tested 864 phecodes with 36 independent LPA variants. We identified 21 significant associations with non-ASCVD phenotypes including heart failure, aortic valve stenosis, and chronic kidney disease of which 14 were replicated across independent cohorts. The strength of associations between the LPA variant rs10455872 and both heart failure and aortic valve stenosis related phecodes were significantly attenuated after adjustment for ASCVD. However, the association with chronic kidney disease phecode remained independent following adjustment for ASCVD without any attenuation in the estimated odds ratio (Table). Conclusions: LPA genetic variants were associated with aortic valve stenosis, heart failure and chronic kidney disease. The observed association of LPA variant rs10455872 with aortic stenosis and heart failure appear to be partially mediated by ASCVD, while the association with chronic kidney disease appears to be independent of ASCVD. Additional studies are needed to elucidate potential mechanisms by which Lp(a) may contribute to the pathogenesis of non-ASCVD disease phenotypes.

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 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.