Bielinski, Suzette

Abstract Background Computational phenotyping from electronic health records (EHRs) is essential for clinical research, decision support, and quality/population health assessment, but the proliferation of algorithms for the same conditions makes it difficult to identify which algorithm is most appropriate for reuse. Objective To develop a framework for assessing phenotyping algorithm fitness for purpose and reuse. Fitness for Purpose Phenotyping algorithms are fit for purpose when they identify the intended population with performance characteristics appropriate for the intended application. Fitness for Reuse Phenotyping algorithms are fit for reuse when the algorithm is implementable and generalizable—that is, it identifies the same intended population with similar performance characteristics when applied to a new setting. Conclusions The PhenoFit framework provides a structured approach to evaluate and adapt phenotyping algorithms for new contexts increasing efficiency and consistency of identifying patient populations from EHRs.

BACKGROUND: Heart failure (HF) is a heterogeneous syndrome with high mortality. The need for a new taxonomy of HF is recognized; up to now, such phenomapping efforts have primarily used clinical data. Proteomics offers potential for more precise phenotypic identification and mechanistic insights. However, few phenomapping studies have used this approach, and all have focused on targeted cardiovascular proteomics panels and a restricted HF ejection fraction group. METHODS: We measured over 7000 plasma proteins in a population-based cohort of 1351 patients with HF, used k-means clustering to identify distinct phenogroups, and compared their clinical characteristics and all-cause mortality. RESULTS: Three proteomics-defined phenogroups were identified, with substantial differences in survival (phenogroup 1 5-year survival probability, 65% [95% CI, 61%–68%]; phenogroup 2, 45% [40%–51%]; phenogroup 3, 26% [22%–30%]), independent of clinical characteristics. Phenogroups also exhibited differences in several measures suggesting poorer health, including NT-proBNP (N-terminal pro-B-type natriuretic peptide), kidney function, and Meta-Analysis Global Group in Chronic Heart Failure scores, but did not differ by ejection fraction or New York Heart Association class. CONCLUSIONS: Our study demonstrates that molecular phenomapping can stratify patients with HF into distinct subgroups that go beyond predefined clinical classifications.

Background: As more healthcare institutions consider providing preemptive pharmacogenomic (PGx) testing to greater numbers of their patients, it will be important to consider the potential concerns patients may have about the generation of preemptive PGx information. To date, few studies have examined the nature and incidence of patient concerns about preemptive PGx testing. Methods: We conducted a longitudinal survey study of 5000 patients receiving preemptive PGx testing in the Mayo Clinic RIGHT study. We assessed patient concerns regarding issues of data confidentiality, cost implications, comprehension of results, and potential disruption of pre-existing medication regimens. Participants were surveyed before and after they received PGx results from the RIGHT study. Results: We achieved 92.8% and 74.4% response rates on the pre- and post-results surveys, respectively. Participants had low levels of concern about PGx testing overall. However, 25.5% of participants were “quite/extremely concerned” about insurance implications, and 30.1% were “quite/extremely” concerned about increased out-of-pocket costs for prescription medications that might result from PGx testing. These same concerns were significantly reduced on the post-results survey. Patients who initially expressed concerns regarding their ability to understand PGx results were more likely to report having difficulty understanding results on the post-results survey. Conclusions: Our findings suggest that as healthcare institutions look to increase preemptive PGx screening, attention should be given to potential concerns patients may have around such testing. Educational interventions aimed at supporting patient understanding of PGx results and addressing potential concerns will be important elements of a successful PGx program.

Abstract Background: Pharmacogenomic studies on antidepressant treatment outcomes could be conducted using previously collected data from electronic health record (EHR)-linked biobanks. However, absence of EHR based outcome measures is an unmet need in designing such studies We aimed to define EHR-derived antidepressant outcome measures and explore their utility in showing associations between treatment outcomes and Cytochrome P450 (CYP) metabolizer phenotypes in a proof-of-concept study. Methods: Using data from the EHR-linked cohort, Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT 10K) Study, we collected prescription data and patient health questionnaire 9 (PHQ-9) scores to compute 3 proxy measures for antidepressant response, efficacy, and acceptability: change in PHQ-9 scores, longest treatment interval with a single antidepressant, and antidepressant non-refill. Subsequently, we tested the association of both prescription-based outcomes with DNA-predicted CYP metabolizer phenotypes in European-ancestry participants. Results: We identified 3920 RIGHT 10K participants with at least 1 antidepressant prescription and European-ancestry. Participants had a mean age of 61 years and 72% were women. Implementation of the PHQ-9 outcome was not feasible because of missingness. Of both prescription-based outcomes, antidepressant non-refill reproduced several known antidepressant-CYP interactions. However, the pilot was limited by small subgroups of participants with non-normal metabolizer phenotypes. Conclusions: Derived from structured data, antidepressant non-refill is a promising outcome measure for EHR-linked biobanks that partially reproduced antidepressant-CYP interactions. However, testing on larger datasets is necessary to understand whether it would be a useful for pharmacogenomic research.

Purpose The Sangre Por Salud (SPS) Biobank was established to facilitate biomedical research opportunities for the Latino community by creating an easily accessible prospective cohort for scientists interested in studying health conditions and health disparities in this population. Participants Individuals self-identifying as Latino, aged 18–85 years, were prospectively recruited from the primary care Internal Medicine clinic at Mountain Park Health Center in Phoenix, Arizona. After obtaining informed consent, detailed medical history questionnaires were captured, and blood samples were obtained for common laboratory tests. Participants authorised the research team to access their electronic health records for research purposes. In addition, participants had serum, plasma and DNA samples isolated and stored at the Mayo Clinic Arizona Biorepository Laboratory for long-term storage and future access. As part of the study, participants consented and agreed to be contacted for potential participation in future research studies. Findings to date 3756 participants provided informed consent, of whom 3733 completed all study questionnaires, an oral glucose tolerance test and had blood collected and stored. The SPS cohort is predominantly composed of females (72%), with a median age at time of consent of 42 years. All participants self-identified as Hispanic/Latino, 45% were married, 53% were employed for wages and 60% had less than a high school degree. Around 25% of participants met diagnostic criteria for overweight (BMI 25–29 kg/m 2 ), and 49% met for obesity (BMI≥30 kg/m 2 ). At time of recruitment, hypertension, hyperlipidaemia and depression affected 22%, 20% and 13% of the cohort, respectively. Future plans We plan to regularly update the participants’ electronic health records and self-reported health data to longitudinal research. Additionally, we plan to obtain a more comprehensive genomic analysis on the entire cohort, ensuring greater research interest and investigation into the underlying genetic factors that contribute to disease susceptibility in this cohort.

BACKGROUND: Senescence, a mechanism of cellular aging, which is characterized by irreversible proliferation arrest and a proinflammatory secretory phenotype, has been documented in women with preeclampsia. As cellular senescence can persist and progress, we postulated that it is associated with accelerated aging phenotype and accumulation of comorbidities in women with a history of preeclampsia. METHODS: We included a cohort of women with a history of preeclampsia (n=40) age- and parity-matched to a group of referent women with normotensive pregnancies (n=40). Women with prior major cardiovascular events, neurological, or autoimmune conditions were excluded. We collected urine and blood samples to study markers of aging, data on multimorbidity at the time of enrollment, and prospectively followed them for events over the course of 6 years, on average. RESULTS: Women with a history of preeclampsia exhibited unfavorable aging profiles compared with referent women, including decreased urinary α-Klotho ( P =0.018); increased leptin ( P =0.016) and leptin/adiponectin ratio ( P =0.027), and increased extracellular vesicles positive for tissue factor ( P =0.025). Women with a history of preeclampsia likewise had a higher rate of comorbidities at the time of enrollment ( P =0.003) and had a 4× higher risk of developing major cardiovascular events compared with referent women ( P =0.003). CONCLUSIONS: Our data suggest that a history of preeclampsia is associated with accelerated aging as indicated by senescence marker differences and the accumulation of multimorbidity later in life. Targeting cellular senescence may offer novel, mechanism-based approaches for the diagnosis and treatment of adverse health outcomes in women with a history of preeclampsia.

Background Clinical risk scores are used to identify those at high risk of atherosclerotic cardiovascular disease (ASCVD). Despite preventative efforts, residual risk remains for many individuals. Very low‐density lipoprotein cholesterol (VLDL‐C) and lipid discordance could be contributors to the residual risk of ASCVD. Methods and Results Cardiovascular disease–free residents, aged ≥40 years, living in Olmsted County, Minnesota, were identified through the Rochester Epidemiology Project. Low‐density lipoprotein cholesterol (LDL‐C) and VLDL‐C were estimated from clinically ordered lipid panels using the Sampson equation. Participants were categorized into concordant and discordant lipid pairings based on clinical cut points. Rates of incident ASCVD, including percutaneous coronary intervention, coronary artery bypass grafting, stroke, or myocardial infarction, were calculated during follow‐up. The association of LDL‐C and VLDL‐C with ASCVD was assessed using Cox proportional hazards regression. Interaction between LDL‐C and VLDL‐C was assessed. The study population (n=39 098) was primarily White race (94%) and female sex (57%), with a mean age of 54 years. VLDL‐C (per 10‐mg/dL increase) was significantly associated with an increased risk of incident ASCVD (hazard ratio, 1.07 [95% CI, 1.05–1.09]; P <0.001]) after adjustment for traditional risk factors. The interaction between LDL‐C and VLDL‐C was not statistically significant ( P =0.11). Discordant individuals with high VLDL‐C and low LDL‐C experienced the highest rate of incident ASCVD events, 16.9 per 1000 person‐years, during follow‐up. Conclusions VLDL‐C and lipid discordance are associated with a greater risk of ASCVD and can be estimated from clinically ordered lipid panels to improve ASCVD risk assessment.

Background Frailty is common in heart failure (HF) and is associated with death but not routinely captured clinically. Frailty is linked with inflammation and malnutrition, which can be assessed by a novel plasma multimarker score: the metabolic vulnerability index (MVX). We sought to evaluate the associations between frailty and MVX and their prognostic impact. Methods and Results In an HF community cohort (2003–2012), we measured frailty as a proportion of deficits present out of 32 physical limitations and comorbidities, MVX by nuclear magnetic resonance spectroscopy, and collected extensive longitudinal clinical data. Patients were categorized by frailty score (≤0.14, >0.14 and ≤0.27, >0.27) and MVX score (≤50, >50 and ≤60, >60 and ≤70, >70). Cox models estimated associations of frailty and MVX with death, adjusted for Meta‐Analysis Global Group in Chronic Heart Failure (MAGGIC) score and NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide). Uno's C‐statistic measured the incremental value of MVX beyond frailty and clinical factors. Weibull's accelerated failure time regression assessed whether MVX mediated the association between frailty and death. We studied 985 patients (median age, 77; 48% women). Frailty and MVX were weakly correlated (Spearman's ρ=0.21). The highest frailty group experienced an increased rate of death, independent of MVX, MAGGIC score, and NT‐proBNP (hazard ratio, 3.3 [95% CI, 2.5–4.2]). Frailty improved Uno's c‐statistic beyond MAGGIC score and NT‐proBNP (0.69–0.73). MVX only mediated 3.3% and 4.5% of the association between high and medium frailty groups and death, respectively. Conclusions In this HF cohort, frailty and MVX are weakly correlated. Both independently contribute to stratifying the risk of death, suggesting that they capture distinct domains of vulnerability in HF.

BACKGROUND: Heart failure is heterogeneous syndrome with persistently high mortality. Nuclear magnetic resonance spectroscopy enables high-throughput metabolomics, suitable for precision phenotyping. We aimed to use targeted metabolomics to derive a metabolic risk score (MRS) that improved mortality risk stratification in heart failure. METHODS: Nuclear magnetic resonance was used to measure 21 metabolites (lipoprotein subspecies, branched-chain amino acids, alanine, GlycA (glycoprotein acetylation), ketone bodies, glucose, and citrate) in plasma collected from a heart failure community cohort. The MRS was derived using least absolute shrinkage and selection operator penalized Cox regression and temporal validation. The association between the MRS and mortality and whether risk stratification was improved over the Meta-Analysis Global Group in Chronic Heart Failure clinical risk score and NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels were assessed. RESULTS: The study included 1382 patients (median age, 78 years, 52% men, 43% reduced ejection fraction) with a 5-year survival rate of 48% (95% CI, 46%–51%). The MRS included 9 metabolites measured. In the validation data set, a 1 standard deviation increase in the MRS was associated with a large increased rate of death (hazard ratio, 2.2 [95% CI, 1.9–2.5]) that remained after adjustment for Meta-Analysis Global Group in Chronic Heart Failure score and NT-proBNP (hazard ratio, 1.6 [95% CI, 1.3–1.9]). These associations did not differ by ejection fraction. The integrated discrimination and net reclassification indices, and Uno’s C statistic, indicated that the addition of the MRS improved discrimination over Meta-Analysis Global Group in Chronic Heart Failure and NT-proBNP. CONCLUSIONS: This MRS developed in a heart failure community cohort was associated with a large excess risk of death and improved risk stratification beyond an established risk score and clinical markers.

Background Although VCAM‐1 (vascular cell adhesion molecule‐1) and ICAM‐1 (intercellular adhesion molecule‐1) have been associated with incident heart failure with preserved ejection fraction (HFpEF) and atrial fibrillation (AF), the associations of VCAM‐1 and ICAM‐1 with sensitive measures of cardiac structure/function are unclear. The objective of this study is to evaluate associations between VCAM‐1, ICAM‐1, and measures of cardiac structure and function as potential pathways through which cellular adhesion molecules promote HFpEF and AF risk. Methods and Results In MESA (Multi‐Ethnic Study of Atherosclerosis), we evaluated the associations of circulating VCAM‐1 and ICAM‐1 at examination 2 (2002–2004) with measures of cardiac structure/function on cardiac magnetic resonance imaging at examination 5 (2010–2011) after multivariable adjustment. Mediation analysis of left atrial (LA) strain on the association between VCAM‐1 or ICAM‐1 and AF or HFpEF was also performed. Overall, 2304 individuals (63±10 years; 47% men) with VCAM‐1 or ICAM‐1, cardiac magnetic resonance imaging, and covariate data were included in analysis. Higher VCAM‐1 and ICAM‐1 were associated with lower LA peak longitudinal strain and worse global circumferential left ventricular strain but were not associated with left ventricular myocardial scar or interstitial fibrosis. Lower LA peak longitudinal strain mediated 8% (95% CI, 2–30) of the relationship between VCAM‐1 and HFpEF and 9% (95% CI, 2–21) of the relationship between VCAM‐1 and AF. Conclusions Higher VCAM‐1 and ICAM‐1 were associated with lower LA function and left ventricular systolic function but were not associated with myocardial scar or interstitial fibrosis. VCAM‐1 and ICAM‐1 may promote HFpEF and AF risk through impaired LA reservoir function.