Development and Validation of a Protein Risk Score for Mortality in Heart Failure : A Community Cohort Study.

BACKGROUND: Heart failure (HF) is a complex clinical syndrome with high mortality. Current risk stratification approaches lack precision. High-throughput proteomics could improve risk prediction. Its use in clinical practice to guide the management of patients with HF depends on validation and evidence of clinical benefit. OBJECTIVE: To develop and validate a protein risk score for mortality in patients with HF. DESIGN: Community-based cohort. SETTING: Southeast Minnesota. PARTICIPANTS: Patients with HF enrolled between 2003 and 2012 and followed through 2021. MEASUREMENTS: A total of 7289 plasma proteins in 1351 patients with HF were measured using the SomaScan Assay (SomaLogic). A protein risk score was derived using least absolute shrinkage and selection operator regression and temporal validation in patients enrolled between 2003 and 2007 (development cohort) and 2008 and 2012 (validation cohort). Multivariable Cox regression was used to examine the association between the protein risk score and mortality. The performance of the protein risk score to predict 5-year mortality risk was assessed using calibration plots, decision curves, and relative utility analyses and compared with a clinical model, including the Meta-Analysis Global Group in Chronic Heart Failure mortality risk score and N-terminal pro-B-type natriuretic peptide. RESULTS: The development (n = 855; median age, 78 years; 50% women; 29% with ejection fraction <40%) and validation cohorts (n = 496; median age, 76 years; 45% women; 33% with ejection fraction <40%) were mostly similar. In the development cohort, 38 unique proteins were selected for the protein risk score. Independent of ejection fraction, the protein risk score demonstrated good calibration, reclassified mortality risk particularly at the extremes of the risk distribution, and showed greater clinical utility compared with the clinical model. LIMITATION: Participants were predominantly of European ancestry, potentially limiting the generalizability of the findings to different patient populations. CONCLUSION: Validation of the protein risk score demonstrated good calibration and evidence of predicted benefits to stratify the risk for death in HF superior to that of clinical methods. Further studies are needed to prospectively evaluate the score's performance in diverse populations and determine risk thresholds for interventions. PRIMARY FUNDING SOURCE: Division of Intramural Research at the National Heart, Lung, and Blood Institute of the National Institutes of Health.

The association of microvascular disease and endothelial dysfunction with vertebral trabecular bone mineral density : The MESA study.

Retinopathy and albuminuria are associated with hip fracture risk. We investigated whether these disorders and endothelial dysfunction (which underlies microvascular diseases) were associated with low trabecular bone density. No significant associations were found, suggesting that microvascular diseases are not related to fracture risk through low trabecular bone density. PURPOSE: Microvascular diseases of the eye, kidney, and brain are associated with endothelial dysfunction and increased hip fracture risk. To explore the basis for higher hip fracture risk, we comprehensively examined whether markers of microvascular disease and/or endothelial dysfunction are related to trabecular bone mineral density (BMD), a proximate risk factor for osteoporotic fractures. METHODS: Among 6814 participants in the Multi-Ethnic Study of Atherosclerosis study (MESA), we derived thoracic vertebral trabecular BMD from computed tomography of the chest and measured urine albumin to creatinine ratios (UACR), retinal arteriolar and venular widths, flow mediated dilation (FMD) of the brachial artery after 5 min of ischemia; and levels of five soluble endothelial adhesion markers (ICAM-1, VCAM-1, L-selectin, P-selectin, and E-selectin). Linear regression models were used to examine the association of trabecular BMD with markers of microvascular disease and with markers of endothelial dysfunction. RESULTS: We observed no significant associations of UACR, retinal arteriolar or venular widths, or FMD with BMD. We also observed no statistically significant association of spine trabecular BMD with levels of endothelial adhesion markers. Men and women had largely similar results. CONCLUSION: We conclude that there is little evidence to connect thoracic spine trabecular BMD to microvascular disorders or to endothelial dysfunction among multi-ethnic middle-aged and older adults. Other factors beyond trabecular BMD (e.g., bone quality or predisposition to falling) may be responsible for the associations of microvascular disease with osteoporotic fractures.

Validation of Different Dementia Code-based Definitions in a Population-based Study of Rheumatoid Arthritis.

OBJECTIVE: Rheumatoid arthritis (RA) has been associated with an elevated dementia risk. The study aimed to examine how different diagnostic dementia definitions perform in those with RA compared to individuals without RA. METHODS: This study population included 2050 individuals (1025 with RA) from a retrospective population-based cohort in southern Minnesota and compared the performance of three code-based dementia diagnostic algorithms with medical record review diagnosis of dementia. For the overall comparison, no time frames were used, and each patient's complete medical history was used. Sensitivity analyses were performed using 1, 2, and 5-year windows around the date that dementia was identified in the medical record (reference standard). RESULTS: Algorithms performed very similarly in persons with and without RA. The algorithms generally had high specificity, negative predictive values, and accuracy, regardless of the time window studied (>88%). Sensitivity and positive predictive values varied depending on the algorithm and the time window studied. Sensitivity values ranged from 56.5% to 95.9%, and positive predictive values ranged from 55.2% to 83.1%. Performance measures declined with more restrictive time windows. CONCLUSION: Routinely collected electronic health record (EHR) data was used to define code-based dementia diagnosis algorithms with good performance (vs. diagnosis by medical record review). These results can inform future studies that use retrospective databases (especially in the same or similar EHR infrastructure) to identify dementia in individuals with RA.

The clinical impact of estimating low-density lipoprotein cholesterol (LDL-C) using different equations in the general population.

BACKGROUND: Low-density lipoprotein cholesterol (LDL-C) is associated with atherosclerotic cardiovascular disease (ASCVD). Friedewald, Sampson, and Martin-Hopkins equations are used to calculate LDL-C. This study compares the impact of switching between these equations in a large geographically defined population. MATERIALS AND METHODS: Data for individuals who had a lipid panel ordered clinically between 2010 and 2019 were included. Comparisons were made across groups using the two-sample t-test or chi-square test as appropriate. Discordances between LDL measures based on clinically actionable thresholds were summarized using contingency tables. RESULTS: The cohort included 198,166 patients (mean age 54 years, 54% female). The equations perform similarly at the lower range of triglycerides but began to diverge at a triglyceride level of 125 mg/dL. However, at triglycerides of 175 mg/dL and higher, the Martin-Hopkins equation estimated higher LDL-C values than the Samson equation. This discordance was further exasperated at triglyceride values of 400 to 800 mg/dL. When comparing the Sampson and Friedewald equations, at triglycerides are below 175 mg/dL, 9% of patients were discordant at the 70 mg/dL cutpoint, whereas 42.4% were discordant when triglycerides are between 175 and 400 mg/dL. Discordance was observed at the clinically actionable LDL-C cutpoint of 190 mg/dL with the Friedewald equation estimating lower LDL-C than the other equations. In a high-risk subgroup (ASCVD risk score > 20%), 16.3% of patients were discordant at the clinical cutpoint of LDL-C < 70 mg/dL between the Sampson and Friedewald equations. CONCLUSIONS: Discordance at clinically significant LDL-C cutpoints in both the general population and high-risk subgroups were observed across the three equations. These results show that using different methods of LDL-C calculation or switching between different methods could have clinical implications for many patients.

Missense Genetic Variation of ICAM1 and Incident Heart Failure.

BACKGROUND: Intercellular adhesion molecule-1 (ICAM-1) is a cell surface protein that participates in endothelial activation and is hypothesized to play a central role in heart failure (HF). We evaluated associations of ICAM1 missense genetic variants with circulating ICAM-1 levels and with incident HF. METHODS AND RESULTS: We identified 3 missense variants within ICAM1 (rs5491, rs5498 and rs1799969) and evaluated their associations with ICAM-1 levels in the Coronary Artery Risk Development in Young Adults Study and the Multi-Ethnic Study of Atherosclerosis (MESA). We determined the association among these 3 variants and incident HF in MESA. We separately evaluated significant associations in the Atherosclerosis Risk in Communities (ARIC) study. Of the 3 missense variants, rs5491 was common in Black participants (minor allele frequency [MAF] > 20%) and rare in other race/ethnic groups (MAF < 5%). In Black participants, the presence of rs5491 was associated with higher levels of circulating ICAM-1 at 2 timepoints separated by 8 years. Among Black participants in MESA (n = 1600), the presence of rs5491 was associated with an increased risk of incident HF with preserved ejection fraction (HFpEF; HR = 2.30; [95% CI 1.25-4.21; P = 0.007]). The other ICAM1 missense variants (rs5498 and rs1799969) were associated with ICAM-1 levels, but there were no associations with HF. In ARIC, rs5491 was significantly associated with incident HF (HR = 1.24 [95% CI 1.02 - 1.51]; P = 0.03), with a similar direction of effect for HFpEF that was not statistically significant. CONCLUSIONS: A common ICAM1 missense variant among Black individuals may be associated with increased risk of HF, which may be HFpEF-specific.

Associations of Mitochondrial and Nuclear Mitochondrial Variants and Genes with Seven Metabolic Traits.

Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear genes (MT-nDNA). In the CHARGEmtDNA+ Consortium, we studied genetic associations of mtDNA and MT-nDNA associations with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, and HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation and imputation of mtDNA variants was followed by single-variant and gene-based association testing. We report two significant common variants, one in MT-ATP6 associated (p ≤ 5E-04) with WHR and one in the D-loop with glucose. Five rare variants in MT-ATP6, MT-ND5, and MT-ND6 associated with BMI, WHR, or insulin. Gene-based meta-analysis identified MT-ND3 associated with BMI (p ≤ 1E-03). We considered 2,282 MT-nDNA candidate gene associations compiled from online summary results for our traits (20 unique studies with 31 dataset consortia's genome-wide associations [GWASs]). Of these, 109 genes associated (p ≤ 1E-06) with at least 1 of our 7 traits. We assessed regulatory features of variants in the 109 genes, cis- and trans-gene expression regulation, and performed enrichment and protein-protein interactions analyses. Of the identified mtDNA and MT-nDNA genes, 79 associated with adipose measures, 49 with glucose/insulin, 13 with risk for type 2 diabetes, and 18 with cardiovascular disease, indicating for pleiotropic effects with health implications. Additionally, 21 genes related to cholesterol, suggesting additional important roles for the genes identified. Our results suggest that mtDNA and MT-nDNA genes and variants reported make important contributions to glucose and insulin metabolism, adipocyte regulation, diabetes, and cardiovascular disease.

Association between CYP metabolizer phenotypes and selective serotonin reuptake inhibitors induced weight gain: a retrospective cohort study.

BACKGROUND: Prescription medications such as selective serotonin reuptake inhibitors (SSRIs), commonly used to treat depression, are associated with weight gain. The role of pharmacogenomics in predicting SSRI-induced weight gain is unclear. METHODS: In this retrospective cohort study from participants in the Mayo Clinic RIGHT study who were prescribed citalopram, paroxetine, sertraline, or fluoxetine, our aim was to evaluate the association of metabolizer phenotype and total body weight after 6 months of SSRIs initiation. We evaluated the metabolizer phenotypes (poor/intermediate, normal, and rapid/ultra-rapid) of the cytochromes P450 enzymes genes: CYP2C9, CYP2C19, and CYP2D6 known to influence the metabolism of SSRI medications: CYP2C19 for citalopram, CYP2D6 for paroxetine, CYP2D6 and CYP2C19 for sertraline, and CYP2D6 and CYP2C9 fluoxetine. In addition, we assessed the association of metabolizer phenotype and total body weight change at six months following SSRI prescription using parametric analysis of covariance adjusted for baseline body weight and multivariate regression models. RESULTS: CYP2C19 poor/intermediate metabolizers prescribed citalopram gained significantly more weight than normal or rapid/ultra-rapid metabolizers at 6 months (TBWG %: 2.6 [95% CI 1.3-4.1] vs. 0.4 [95% CI -0.5 - 1.3] vs. -0.1 [-95% CI -1.5-1.1]; p = 0.001). No significant differences in weight outcomes at six months of treatment with paroxetine, sertraline, or fluoxetine were observed by metabolizer status. CONCLUSIONS: Weight gain observed with citalopram may be mediated by CYP2C19 metabolizer status.

Identification of sex-specific genetic associations in response to opioid analgesics in a White, non-Hispanic cohort from Southeast Minnesota.

The study of sex-specific genetic associations with opioid response may improve the understanding of inter-individual variability in pain treatments. We investigated sex-specific associations between genetic variation and opioid response. We identified participants in the RIGHT Study prescribed codeine, tramadol, hydrocodone, and oxycodone between 01/01/2005 and 12/31/2017. Prescriptions were collapsed into codeine/tramadol and hydrocodone/oxycodone. Outcomes included poor pain control and adverse reactions within six weeks after prescription date. We performed gene-level and single-variant association analyses stratified by sex. We included 7169 non-Hispanic white participants and a total of 1940 common and low-frequency variants (MAF > 0.01). Common variants in MACROD2 (rs76026520), CYP1B1 (rs1056837, rs1056836), and CYP2D6 (rs35742686) were associated with outcomes. At the gene level, FAAH, SCN1A, and TYMS had associations for men and women, and NAT2, CYP3A4, CYP1A2, and SLC22A2 had associations for men only. Our findings highlight the importance of considering sex in association studies on opioid response.

Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study.

PURPOSE: The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. METHODS: Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record. RESULTS: For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. CONCLUSION: Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.

Identifying Information Gaps in Electronic Health Records by Using Natural Language Processing: Gynecologic Surgery History Identification.

BACKGROUND: Electronic health records (EHRs) are a rich source of longitudinal patient data. However, missing information due to clinical care that predated the implementation of EHR system(s) or care that occurred at different medical institutions impedes complete ascertainment of a patient's medical history. OBJECTIVE: This study aimed to investigate information discrepancies and to quantify information gaps by comparing the gynecological surgical history extracted from an EHR of a single institution by using natural language processing (NLP) techniques with the manually curated surgical history information through chart review of records from multiple independent regional health care institutions. METHODS: To facilitate high-throughput evaluation, we developed a rule-based NLP algorithm to detect gynecological surgery history from the unstructured narrative of the Mayo Clinic EHR. These results were compared to a gold standard cohort of 3870 women with gynecological surgery status adjudicated using the Rochester Epidemiology Project medical records-linkage system. We quantified and characterized the information gaps observed that led to misclassification of the surgical status. RESULTS: The NLP algorithm achieved precision of 0.85, recall of 0.82, and F1-score of 0.83 in the test set (n=265) relative to outcomes abstracted from the Mayo EHR. This performance attenuated when directly compared to the gold standard (precision 0.79, recall 0.76, and F1-score 0.76), with the majority of misclassifications being false negatives in nature. We then applied the algorithm to the remaining patients (n=3340) and identified 2 types of information gaps through error analysis. First, 6% (199/3340) of women in this study had no recorded surgery information or partial information in the EHR. Second, 4.3% (144/3340) of women had inconsistent or inaccurate information within the clinical narrative owing to misinterpreted information, erroneous "copy and paste," or incorrect information provided by patients. Additionally, the NLP algorithm misclassified the surgery status of 3.6% (121/3340) of women. CONCLUSIONS: Although NLP techniques were able to adequately recreate the gynecologic surgical status from the clinical narrative, missing or inaccurately reported and recorded information resulted in much of the misclassification observed. Therefore, alternative approaches to collect or curate surgical history are needed.

A model-based cost-effectiveness analysis of pharmacogenomic panel testing in cardiovascular disease management: preemptive, reactive, or none?

PURPOSE: Pharmacogenomics (PGx) studies how inherited genetic variations in individuals affect drug absorption, distribution, and metabolism. PGx panel testing can potentially help improve efficiency and accuracy in individualizing therapy. This study compared the cost-effectiveness between preemptive PGx panel testing, reactive PGx panel testing and usual care (no testing) in cardiovascular disease management. METHODS: We developed a decision analytic model from the US payer's perspective for a hypothetical cohort of 10,000 patients ≥45 years old, using a short-term decision tree and long-term Markov model. The testing panel included the following gene-drug pairs: CYP2C19-clopidogrel, CYP2C9/VKORC1-warfarin, and SLCO1B1-statins with 30 test-return days. Costs were reported in 2019 US dollars and effectiveness was measured in quality-adjusted life years (QALYs). The primary outcome was incremental cost-effectiveness ratio (ICER = ΔCost/ΔQALY), assuming 3% discount rate for costs and QALYs. Scenario and probabilistic sensitivity analyses were performed to assess the impact of demographics, risk level, and follow-up timeframe. RESULTS: Preemptive testing was found to be cost-effective compared with usual care (ICER $86,227/QALY) at the willingness-to-pay threshold of $100,000/QALY while reactive testing was not (ICER $148,726/QALY). Sensitivity analyses suggested that our cost-effectiveness results were sensitive to longer follow-up, and the age group 45-64 years. CONCLUSION: Compared with usual care, preemptive PGx panel testing was cost-effective in cardiovascular disease management.

Hepatocyte Growth Factor and Incident Heart Failure Subtypes: The Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: Hepatocyte growth factor (HGF) is a cytokine and marker of cardiovascular disease (CVD) risk. Less is known about HGF and incident heart failure (HF). We examined the association of HGF with incident HF and its subtypes in a multiethnic cohort. METHODS AND RESULTS: We included 6597 participants of the Multi-Ethnic Study of Atherosclerosis (MESA) cohort, free of clinical CVD and HF at baseline, with HGF measured at baseline. Incident hospitalized HF was assessed and adjudicated for HF with preserved ejection fracture (HFpEF) vs HF with reduced ejection fraction (HFrEF). Cox regression models estimated hazard ratios (HR) and 95% confidence intervals (CI) for HF risk by HGF levels, adjusted for socio-demographics, CVD risk factors and N-terminal pro-B-type natriuretic peptide. The mean age was 62 ± 10 years. The median HGF level was 950 pg/mL (interquartile range, 758-1086 pg/mL); 53% were women. Over 14 years (IQR, 11.5-14.7 years), there were 324 cases of HF (133 HFpEF and 157 HFrEF). For the highest HGF tertile compared with lowest, adjusted HRs were 1.59 (95% CI, 1.10-2.31), 1.90 (95% CI, 1.03-3.51), and 1.09 (95% CI, 0.65-1.82) for overall HF, HFpEF, and HFrEF, respectively. For continuous analysis per 1-standard deviation log-transformed HGF, adjusted HRs were 1.22 (95% CI, 1.06-1.41), 1.35 (95% CI, 1.09-1.69), and 1.00 (95% CI, 0.81-1.24) for HF, HFpEF, and HFrEF, respectively. CONCLUSIONS: HGF was independently associated with incident HF. HGF remained significantly associated with HFpEF but not HFrEF upon subtype assessment. Future studies should examine the mechanisms underlying these associations and evaluate whether HGF can be used to improve HF risk prediction or direct therapy.

Next-Generation Sequencing of CYP2C19 in Stent Thrombosis: Implications for Clopidogrel Pharmacogenomics.

PURPOSE: Describe CYP2C19 sequencing results in the largest series of clopidogrel-treated cases with stent thrombosis (ST), the closest clinical phenotype to clopidogrel resistance. Evaluate the impact of CYP2C19 genetic variation detected by next-generation sequencing (NGS) with comprehensive annotation and functional studies. METHODS: Seventy ST cases on clopidogrel identified from the PLATO trial (n = 58) and Mayo Clinic biorepository (n = 12) were matched 1:1 with controls for age, race, sex, diabetes mellitus, presentation, and stent type. NGS was performed to cover the entire CYP2C19 gene. Assessment of exonic variants involved measuring in vitro protein expression levels. Intronic variants were evaluated for potential splicing motif variations. RESULTS: Poor metabolizers (n = 4) and rare CYP2C19*8, CYP2C19*15, and CYP2C19*11 alleles were identified only in ST cases. CYP2C19*17 heterozygote carriers were observed more frequently in cases (n = 29) than controls (n = 18). Functional studies of CYP2C19 exonic variants (n = 11) revealed 3 cases and only 1 control carrying a deleterious variant as determined by in vitro protein expression studies. Greater intronic variation unique to ST cases (n = 169) compared with controls (n = 84) was observed with predictions revealing 13 allele candidates that may lead to a potential disruption of splicing and a loss-of-function effect of CYP2C19 in ST cases. CONCLUSION: NGS detected CYP2C19 poor metabolizers and paradoxically greater number of so-called rapid metabolizers in ST cases. Rare deleterious exonic variation occurs in 4%, and potentially disruptive intronic alleles occur in 16% of ST cases. Additional studies are required to evaluate the role of these variants in platelet aggregation and clopidogrel metabolism.

Adhesion pathway proteins and risk of atrial fibrillation in the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: The cellular adhesion pathway has been suggested as playing an important role in the pathogenesis of atrial fibrillation (AF). However, prior studies that have investigated the role of adhesion pathway proteins in risk of AF have been limited in the number of proteins that were studied and in the ethnic and racial diversity of the study population. Therefore we aimed to study the associations of fifteen adhesion pathway proteins with incident AF in a large, diverse population. METHODS: Multi-Ethnic Study of Atherosclerosis participants from four races/ethnicities (n = 2504) with protein levels measured were followed for incident AF (n = 253). HGF protein was measured on Exam 1 samples (N = 6669; AF n = 851). Cox proportional hazards regression was used to assess the association of AF with 15 adhesion pathway proteins. Bonferroni correction was applied to account for multiple comparisons. RESULTS: After adjusting for potential confounding variables (age, sex, race/ethnicity, height, body mass index, systolic blood pressure, antihypertension therapy, diabetes status, current smoker, current alcohol use, and total and HDL cholesterol), and accounting for multiple testing (P < 0.05/15 = 0.0033), circulating levels of the following proteins were positively associated with a higher risk of AF: MMP-2 (HR per standard deviation increment, 1.27; 95% CI 1.11‒1.45), TIMP-2 (HR 1.28; 95% CI 1.12‒1.46), VCAM-1 (HR 1.32; 95% CI 1.16‒1.50), and SLPI (HR 1.22; 95% CI 1.07‒1.38). The association between proteins and AF did not differ by race/ethnicity. CONCLUSIONS: Circulating levels of MMP-2, TIMP-2, VCAM-1, and SLPI were positively associated with an increased risk of incident AF in a diverse population. Our findings suggest that adhesion pathway proteins may be important risk predictors of AF.

Recent trends in cardiovascular disease deaths: a state specific perspective.

BACKGROUND: The rate of decline in cardiovascular disease (CVD) mortality has lessened nationally. How these findings apply to specific states or causes of CVD deaths is not known. Examining these trends at the state level is important to plan local interventions. METHODS: We analyzed CVD mortality trends in Minnesota (MN) using the U.S. Centers for Disease Control and Prevention (CDC) Wide-ranging ONline Data for Epidemiologic Research (WONDER). Trends were analyzed by age, sex, type of CVD and location of death. RESULTS: CVD mortality rates in MN declined in 2000-2009 and then leveled off in 2010-2018, paralleling national rates. Age- and sex-adjusted CVD mortality decreased by 3.7% per year in 2000-2009 (average annual percent changes [AAPC]: -3.7; 95% CI: - 4.8, - 2.6) with no change observed in 2010-2018. Those aged 65-84 years had the most rapid early decline in CVD mortality (AAPC: -5.9, 95% CI: - 6.2, - 5.7) and had less improvement in 2010-2018 (AAPC: -1.8, 95% CI: - 2.2, - 1.5), and the younger age group (25-64 years) now experiences the most adverse trends (AAPC: 1.2, 95% CI: 0.7-1.8). Coronary heart disease (CHD) and cerebrovascular disease had the largest relative decreases in mortality in 2000-2009 (CHD AAPC: -5.2; 95% CI: - 6.5,-3.9; cerebrovascular disease AAPC: -4.4, 95% CI: - 5.2, - 3.6) with no change 2010-2018. Heart failure (HF)/cardiomyopathy followed similar trends with a 2.5% decrease (AAPC 95% CI: - 3.5, - 1.5) per year in 2000-2009 and no change in 2010-2018. Deaths from other CVD also decreased in the early time period (AAPC: -1.6, 95% CI: - 2.7, - 0.5) but increased in 2010-2018 (AAPC: 1.9, 95% CI: 0.5, 3.3). In- and out-of-hospital death rates improved in 2000-2009 with a slowing in improvement for in-hospital death and no further improvement for out-of-hospital death in 2010-2018. CONCLUSION: Concerning CVD mortality trends occurred in MN. In the most recent decade (2010-2018) mortality from all CVD subtypes plateaued or even increased. CVD mortality among the younger age groups increased as well. These data are congruent with adverse national trends supporting their generalizability. These adverse trends underscore the urgent need for CVD prevention and treatment, as well as continued surveillance to assess progress at the state and national level.

Natural Language Processing and Machine Learning for Identifying Incident Stroke From Electronic Health Records: Algorithm Development and Validation.

BACKGROUND: Stroke is an important clinical outcome in cardiovascular research. However, the ascertainment of incident stroke is typically accomplished via time-consuming manual chart abstraction. Current phenotyping efforts using electronic health records for stroke focus on case ascertainment rather than incident disease, which requires knowledge of the temporal sequence of events. OBJECTIVE: The aim of this study was to develop a machine learning-based phenotyping algorithm for incident stroke ascertainment based on diagnosis codes, procedure codes, and clinical concepts extracted from clinical notes using natural language processing. METHODS: The algorithm was trained and validated using an existing epidemiology cohort consisting of 4914 patients with atrial fibrillation (AF) with manually curated incident stroke events. Various combinations of feature sets and machine learning classifiers were compared. Using a heuristic rule based on the composition of concepts and codes, we further detected the stroke subtype (ischemic stroke/transient ischemic attack or hemorrhagic stroke) of each identified stroke. The algorithm was further validated using a cohort (n=150) stratified sampled from a population in Olmsted County, Minnesota (N=74,314). RESULTS: Among the 4914 patients with AF, 740 had validated incident stroke events. The best-performing stroke phenotyping algorithm used clinical concepts, diagnosis codes, and procedure codes as features in a random forest classifier. Among patients with stroke codes in the general population sample, the best-performing model achieved a positive predictive value of 86% (43/50; 95% CI 0.74-0.93) and a negative predictive value of 96% (96/100). For subtype identification, we achieved an accuracy of 83% in the AF cohort and 80% in the general population sample. CONCLUSIONS: We developed and validated a machine learning-based algorithm that performed well for identifying incident stroke and for determining type of stroke. The algorithm also performed well on a sample from a general population, further demonstrating its generalizability and potential for adoption by other institutions.

Systematic review of the evidence on the cost-effectiveness of pharmacogenomics-guided treatment for cardiovascular diseases.

PURPOSE: To examine the evidence on the cost-effectiveness of implementing pharmacogenomics (PGx) in cardiovascular disease (CVD) care. METHODS: We conducted a systematic review using multiple databases from inception to 2018. The titles and abstracts of cost-effectiveness studies on PGx-guided treatment in CVD care were screened, and full texts were extracted. RESULTS: We screened 909 studies and included 46 to synthesize. Acute coronary syndrome and atrial fibrillation were the predominantly studied conditions (59%). Most studies (78%) examined warfarin-CYP2C9/VKORC1 or clopidogrel-CYP2C19. A payer's perspective was commonly used (39%) for cost calculations, and most studies (46%) were US-based. The majority (67%) of the studies found PGx testing to be cost-effective in CVD care, but cost-effectiveness varied across drugs and conditions. Two studies examined PGx panel testing, of which one examined pre-emptive testing strategies. CONCLUSION: We found mixed evidence on the cost-effectiveness of PGx in CVD care. Supportive evidence exists for clopidogrel-CYP2C19 and warfarin-CYP2C9/VKORC1, but evidence is limited in other drug-gene combinations. Gaps persist, including unclear explanation of perspective and cost inputs, underreporting of study design elements critical to economic evaluations, and limited examination of PGx panel and pre-emptive testing for their cost-effectiveness. This review identifies the need for further research on economic evaluations of PGx implementation.

Circulating adhesion molecules and subclinical interstitial lung disease: the Multi-Ethnic Study of Atherosclerosis.

Adhesion molecules may contribute to the development of interstitial lung disease (ILD) and have been proposed as prognostic biomarkers in idiopathic pulmonary fibrosis. Our objective was to determine whether the circulating adhesion molecules soluble intracellular adhesion molecule (sICAM)-1, soluble vascular cell adhesion molecule (sVCAM)-1 and P-selectin are associated with subclinical ILD in community-dwelling adults.The Multi-Ethnic Study of Atherosclerosis enrolled males and females aged 45-84 years from six communities in the United States in 2000-2002. High attenuation areas were defined as the percentage of imaged lung volume with attenuation -600--250 HU on cardiac computed tomography (CT). Interstitial lung abnormalities were visually assessed on full-lung CT. Spirometry was performed on a subset of individuals. ILD hospitalisations and deaths were adjudicated.In fully adjusted analyses, higher levels of sICAM-1, sVCAM-1 and P-selectin were associated with greater high attenuation areas (2.94%, 95% CI 1.80-4.07%; 1.24%, 95% CI 0.14-2.35%; and 1.58%, 95% CI 0.92-2.23%, respectively), and greater rate of ILD hospitalisations (HR 1.36, 95% CI 1.03-1.80; 1.40, 95% CI 1.07-1.85; and 2.03, 95% CI 1.16-3.5, respectively). sICAM-1 was associated with greater prevalence of interstitial lung abnormalities (OR 1.39, 95% CI 1.13-1.71). sICAM-1 and P-selectin were associated with lower forced vital capacity (44 mL, 95% CI 12-76 mL and 29 mL, 95% CI 8-49 mL, respectively). sVCAM-1 and P-selectin were associated with increased risk of ILD death (HR 2.15, 95% CI 1.26-3.64 and 3.61, 95% CI 1.54-8.46, respectively).Higher levels of circulating sICAM-1, sVCAM-1 and P-selectin are independently associated with CT and spirometric measures of subclinical ILD, and increased rate of adjudicated ILD events among community-dwelling adults.

Increased hepatocyte growth factor levels over 2 years are associated with coronary heart disease: the Multi-Ethnic Study of Atherosclerosis (MESA)

Hepatocyte growth factor (HGF) is associated with subclinical and clinical atherosclerosis. However, the significance of change in HGF and development of atherosclerotic disease is unknown. In a large and diverse population-based cohort, we report that change in the biomarker HGF is an independent predictor of incident CHD.

Pharmacogenomic Next-Generation DNA Sequencing: Lessons from the Identification and Functional Characterization of Variants of Unknown Significance in CYP2C9 and CYP2C19.

CYP2C9 and CYP2C19 are highly polymorphic pharmacogenes; however, clinically actionable genetic variability in drug metabolism due to these genes has been limited to a few common alleles. The identification and functional characterization of less-common open reading frame sequence variation might help to individualize therapy with drugs that are substrates for the enzymes encoded by these genes. The present study identified seven uncharacterized variants each in CYP2C9 and CYP2C19 using next-generation sequence data for 1013 subjects, and functionally characterized the encoded proteins. Constructs were created and transiently expressed in COS-1 cells for the assay of protein concentration and enzyme activities using fluorometric substrates and liquid chromatography- tandem mass spectrometry with tolbutamide (CYP2C9) and (S)-mephenytoin (CYP2C19) as prototypic substrates. The results were compared with the SIFT, Polyphen, and Provean functional prediction software programs. Cytochrome P450 oxidoreductase (CPR) activities were also determined. Positive correlations were observed between protein content and fluorometric enzyme activity for variants of CYP2C9 (P < 0.05) and CYP2C19 (P < 0.0005). However, CYP2C9 709G>C and CYP2C19 65A>G activities were much lower than predicted based on protein content. Substrate intrinsic clearance values for CYP2C9 218C>T, 343A>C, and CYP2C19 337G>A, 518C>T, 556C>T, and 557G>A were less than 25% of wild-type allozymes. CPR activity levels were similar for all variants. In summary, sequencing of CYP2C9 and CYP2C19 in 1013 subjects identified low-frequency variants that had not previously been functionally characterized. In silico predictions were not always consistent with functional assay results. These observations emphasize the need for high-throughput methods for pharmacogene variant mutagenesis and functional characterization.