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Objective CYP2C9 and CYP2C19 are highly polymorphic pharmacogenes that encodes enzymes that metabolize a large number of clinically relevant drugs. While the majority of variability in drug metabolism can be explained by a few common alleles, identification of gene sequence variation that alters enzyme activity and incorporation of that information into pharmacogenomic rules for clinical decision support might lead to improved therapy. Using sequence data derived from the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT Protocol), we sought to identify variants of unknown significance (VUSs) for CYP2C9 and CYP2C19, and to characterize the function of the encoded enzymes. Methods Targeted next‐generation sequencing for 84 pharmacogenes using the PGRN‐Seq v1.0 capture reagent was performed with DNA samples from 1013 RIGHT Protocol participants. Plasmids containing VUSs were created using site directed mutagenesis and were transiently expressed in COS‐1 cells. Initial determination of enzyme activity was performed using fluorogenic substrates. Enzyme kinetic parameters (Km and Vmax) for each of the variant allozymes were determined using liquid chromatography mass spectrometry with tolbutamide (CYP2C9) and mephenytoin (CYP2C19) as prototypic substrates. We also compared our results with in silico functional predictions by SIFT and Polyphen. Results Seven VUSs were identified for each gene, none of which had been functionally characterized. There were significant positive correlations between protein content and fluorometric enzyme activity for all variants for both CYP2C9 (P<0.05) and CYP2C19 (P<0.005). Notably, CYP2C9 V237L and CYP2C19 A173V activity was much lower than predicted based on protein content. The substrate intrinsic clearance of CYP2C9 variants P73L , S115R , V237L [6.23E‐05±1.08E‐05; 2.55E‐05±4.1E‐06; 7.28E‐05±2.4E‐05 (uL/mg protein/min)], and CYP2C19 variants V113I , A173V , R186C and R186H [2.49E‐04±2.78E‐05; 1.80E‐05±2.19E‐06; 2.33E‐05±9.2E‐06;1.45E‐04±1.2E‐05 (uL/mg protein/min)] were less than 25% of their respective WT enzyme . Conclusion Sequencing of CYP2C9 and CYP2C19 from 1013 subjects identified low frequency variants that had not been functionally characterized. In silico predictions which showed variable results, can be helpful but are not always accurate, hence functional validation is necessary for VUSs requiring protein expression and determination of kinetic parameters. Efforts to identify variation in diverse populations is resulting in a very large number of VUSs, so there is a need for the application of high throughput mutagenesis approaches and functional characterization methods to help pharmacogenomics contribute to precision medicine. Support or Funding Information NIH RO1 GM28157 and the Mayo Center for Individualized Medicine Pharmacogenomics Program.

AbstractA robust and heterogenous secretory phenotype is a core feature of most senescent cells. In addition to mediators of age‐related pathology, components of the senescence associated secretory phenotype (SASP) have been studied as biomarkers of senescent cell burden and, in turn, biological age. Therefore, we hypothesized that circulating concentrations of candidate senescence biomarkers, including chemokines, cytokines, matrix remodeling proteins, and growth factors, could predict mortality in older adults. We assessed associations between plasma levels of 28 SASP proteins and risk of mortality over a median follow‐up of 6.3 years in 1923 patients 65 years of age or older with zero or one chronic condition at baseline. Overall, the five senescence biomarkers most strongly associated with an increased risk of death were GDF15, RAGE, VEGFA, PARC, and MMP2, after adjusting for age, sex, race, and the presence of one chronic condition. The combination of biomarkers and clinical and demographic covariates exhibited a significantly higher c‐statistic for risk of death (0.79, 95% confidence interval (CI): 0.76–0.82) than the covariates alone (0.70, CI: 0.67–0.74) (p < 0.001). Collectively, these findings lend further support to biomarkers of cellular senescence as informative predictors of clinically important health outcomes in older adults, including death.

BACKGROUND: Hypertensive disorders of pregnancy (HDP) have been associated with an increased risk of chronic hypertension for both mothers and offspring. We sought to quantify the incidence of chronic hypertension in offspring from HDP-affected pregnancies in a large, population-based cohort study. Furthermore, we evaluate the association of HDP exposure in utero and maternal chronic hypertension in offspring. METHODS: We performed a population-based cohort study of 8755 individuals born during 1976 to 1982 to 7544 women who all resided in the same community at the time of delivery. HDP were identified using a previously validated algorithm. Diagnosis of chronic hypertension in mothers and their offspring was determined using diagnostic codes. Cox proportional hazards regression was used to assess the association between HDP and chronic hypertension. RESULTS: HDP exposure (hazard ratio, 1.50 [95% CI, 1.18–1.90]) and maternal chronic hypertension (hazard ratio, 1.73 [95% CI, 1.48–2.02]) were both associated with a significant increased risk for chronic hypertension in offspring. Both risk factors remained significantly associated with increased risk of hypertension in offspring when included together in a multivariate model. Having both exposures was associated with a 2.4-fold increase in the risk of hypertension in offspring, suggesting a synergistic additive interaction. CONCLUSIONS: HDP exposure in gestation and maternal hypertension are both independently associated with an increased risk of chronic hypertension in offspring. Our results suggest that HDP exposure in utero, in addition to maternal chronic hypertension, may lead to a greater risk for the development of hypertension in offspring.

Introduction: Coronary disease is the most common cause of heart failure (HF). HF is classified as ischemic (IHF) or non-ischemic (NIHF) based on this etiology. IHF and NIHF have distinct mechanisms not accounted for by ejection fraction (EF) and an improved understanding of the differences could drive the discovery of novel therapeutic targets. We therefore sought to identify proteomic signatures between IHF and NIHF. Methods: Proteomic profiling using the SomaScan®1.7K was performed using plasma samples from HF patients in a community cohort (Rochester Epidemiology Project, 2003-2012). IHF was defined by prior myocardial infarction, percutaneous coronary intervention or coronary artery bypass graft, or obstructive disease in at least 1 vessel on coronary angiography. We compared the protein expression levels between IHF and NIHF using t-test and applied the Benjamini-Hochberg false-discovery rate (FDR) procedure for multiple comparisons. We explored pathway analysis for functional annotations using the biological process component of the Gene Ontology Resource (Panther 17v). Results: Among 1,388 patients, there were 518 IHF patients (age: 75±12years, 39.4% female, NYHA Class III/IV: 72.5%, EF:45±15%), and 870 NIHF patients (age: 75±14years, 53.6% female, NYHA Class III/IV: 66.9%, EF:49±17%). Among 7335 plasma proteins quantified, 63 unique proteins (FDR < 0.05) were differentially expressed between IHF and NIHF. Thirty-seven proteins including Troponin-I and T, and Myoglobin showed increased expression in IHF compared to NIHF and 26 including IGFBP-3 showed decreased expression. Pathophysiologic pathways including angiogenesis, coagulation, and lipid metabolism were represented in IHF, while inflammation and remodeling signaling pathways were dominant in relation to NIHF. Conclusions: High-throughput proteomic techniques are able to delineate IHF versus NIHF patients based on distinct biomarkers and pathophysiologic processes.

Introduction: Heart failure (HF) is a complex syndrome with high mortality often associated with impaired kidney function. Estimated glomerular filtration rate (eGFR) is central to kidney function assessment in HF. However, novel proteins related to kidney function (lipocalin 2 [LCN2], macrophage inhibitory cytokine 1 [MIC1], T cell immunoglobulin and mucin domain 1 [TIM1]) may improve risk stratification of HF patients, beyond eGFR. Their prognostic contribution remain to be fully explored. Hypothesis: Proteomic assessment of kidney function biomarkers improves risk stratification in HF. Methods: Clinical data and biospecimens were collected from a HF community cohort in Southeastern Minnesota from 2003-2012. Serum creatinine was measured in 1,388 patients and eGFR was calculated with the 2021 Chronic Kidney Disease (CKD) Epidemiology Collaboration equation. CKD was defined as an eGFR <60 mL/min/1.73m 2 . Plasma proteins were measured using the SomaLogic aptamer-based technology SomaScan®. In HF patients with and without CKD, Cox proportional hazard models were used to estimate the association between kidney function biomarkers and mortality, after adjustment for Meta-Analysis Global Group in Chronic HF (MAGGIC) risk score. Results: At HF index, patients were on average 75±13 years of age and 48% female. Patients had a median eGFR of 57 mL/min/1.73m 2 and 64% had CKD. Adjusted geometric mean levels of LCN2, MIC1, and TIM1 levels were 20-30% higher in patients with CKD. Patients with CKD were at higher risk of dying (HR 1.6, 95% CI 1.4-1.8). Patients with above median levels of LCN2, TIM1, MIC1 were at higher risk of dying, irrespective of CKD (See Figure). Conclusions: In a HF community cohort, several novel kidney function biomarkers provided further risk stratification in patients with and without CKD.

Objective Ceramides have been associated with several ageing-related conditions but have not been studied as a general biomarker of multimorbidity (MM). Therefore, we determined whether ceramide levels are associated with the rapid development of MM. Design Retrospective cohort study. Setting Mayo Clinic Biobank. Participants 1809 persons in the Mayo Clinic Biobank ≥65 years without MM at the time of enrolment, and with ceramide levels assayed from stored plasma. Primary outcome measure Persons were followed for a median of 5.7 years through their medical records to identify new diagnoses of 20 chronic conditions. The number of new conditions was divided by the person-years of follow-up to calculate the rate of accumulation of new chronic conditions. Results Higher levels of C18:0 and C20:0 were associated with a more rapid rate of accumulation of chronic conditions (C18:0 z score RR: 1.30, 95% CI: 1.10 to 1.53; C20:0 z score RR: 1.26, 95% CI: 1.07 to 1.49). Higher C18:0 and C20:0 levels were also associated with an increased risk of hypertension and coronary artery disease. Conclusions C18:0 and C20:0 were associated with an increased risk of cardiometabolic conditions. When combined with biomarkers specific to other diseases of ageing, these ceramides may be a useful component of a biomarker panel for predicting accelerated ageing.

Introduction: Over 6 million people in the U.S. have heart failure (HF), less than half are expected to survive beyond 5 years. The need to better stratify mortality risk in HF is recognized. Frailty is associated with mortality in HF but not routinely measured clinically. As frailty is linked to inflammation and malnutrition, we hypothesized that the Metabolic Vulnerability Index (MVX) a multimarker score of systemic inflammation (small HDL particles, GlycA) and malnutrition (leucine, valine, isoleucine, citrate), could serve as a biomarker of frailty to predict mortality risk. Methods: Clinical data and plasma were collected from 1,389 patients from a HF community cohort between 2003-2012. We measured frailty using the Rockwood Index as the proportion of deficits present out of 32 physical limitations and comorbidities. MVX was calculated from the nuclear magnetic resonance LipoProfile® test. Patients were categorized by frailty (0-0.15; 0.16-0.27; 0.28-0.78) and MVX (33.4-50, 50-60, 60-70, 70-85.8) cutpoints. Cox models estimated the association of frailty and MVX assignment with mortality, adjusted for Meta-Analysis Global Group in Chronic HF (MAGGIC) score, a validated clinical risk score for HF mortality. Results: Frailty and MVX scores were available in 985 patients (median age 77, IQR: 67-84; 48% women). Higher frailty was associated with higher MVX (p-trend < 0.001). The highest frailty and MVX groups experienced large increases in risk of death, after adjustment for MAGGIC score (HR=3.3, 95% CI=2.6-4.2) and (HR=2.7, 95% CI=2.1-3.5), respectively. When adjusted for one another and MAGGIC score, MVX and frailty associations with death were only minimally attenuated: frailty (HR=3.2, 95% CI=2.5-4.0) and MVX (HR=2.4, 95% CI=1.9-3.2) (Figure 1). Conclusion: In this community cohort of patients with HF, frailty and MVX are positively associated with one another. However, both indicators are independently associated with an increased risk of death and can contribute to risk stratification.

Introduction: Heart Failure (HF) is a syndrome of high comorbidity and mortality. The impact of comorbidities on life expectancy in HF is well studied, but guideline-recommended disease-centric risk scores such as the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) score may not fully account for the effect of comorbidities. The Charlson Comorbidity Index (Charlson) is a validated measure that quantifies the prognostic impact of comorbidities. Objective: To examine the incremental value of Charlson over MAGGIC in predicting death in HF. Methods: In a population-based HF cohort, we computed MAGGIC and Charlson scores using electronically linked medical records. Patients were divided based on ejection fraction (EF) into reduced [EF <50%, HFrEF] or preserved [EF ≥50%, HFpEF]. Cox regression was performed to assess the association between the risk scores and mortality. The incremental value of Charlson over MAGGIC was tested by calculating the area under the ROC [receiver operating characteristic] curves (AUCs) with 95% confidence interval (CI). Results: We studied 1,388 patients with HF validated using the Framingham criteria (mean age, 75±13 years, 48% female, mean EF, 49±17%). The median Charlson was 7.0 (interquartile range 5.0-9.0) and was higher in HFpEF than HFrEF (7.0 [5.0-9.0] vs. 6.0 [4.0-8.3] respectively. Over a median follow-up of 13.9 years (13.3-14.2), mortality was 17.4% (95% CI, 15.4 -19.3%) and 36.8% (95% CI, 34.2-39.3%) at 1, and 3 years respectively. In regression analysis, increasing MAGGIC and Charlson were independently associated with death (HR 1.09, 95% CI 1.08-1.11 and HR,1.22, 95% CI 1.20-1.24, both p <0.001) irrespective of EF. Discrimination ability was improved by adding Charlson over MAGGIC (Table), reaching statistical significance at 3 years. Conclusion: In this HF cohort, the Charlson index provided an added value over MAGGIC in predicting the risk of death at 3 years. These findings emphasize the importance of accounting for comorbidities in mid-term risk stratification in HF.

Background: Heart failure (HF) is associated with metabolic alterations, including ketogenesis. However, determinants of ketogenesis and risk of mortality in HF is not defined. Total ketone bodies (KB) include β-hydroxybutyrate, acetoacetate, and acetone and can be measured in plasma by nuclear magnetic resonance (NMR). The aim of this study is to determine the relationship between KB and clinical characteristics in a community HF cohort and to assess the association between KB and all-cause mortality. Methods: A population-based cohort of 1,389 HF patients was prospectively enrolled between 2003 and 2012. Plasma KB was measured by LP4 NMR LipoProfile ® assay/test on the Vantera® NMR analyzer platform. A conditional inference tree method (ctree R Package) was used to determine optimal KB group cut points. Associations between clinical characteristics and KB were measured with Wilcoxon rank sum test and Pearson’s Chi-squared test. Kaplan-Meier method estimated survival. Cox regression analyses were used to estimate associations between KB concentrations and mortality. Results: Among the 1,382 HF patients with KB measurements, the median age was 78 years (IQR 68-84) and 52% were men. Median KB was 180 μM (IQR 134-308). Patients were divided into two groups with lower KB (≤471.5 μM) and higher KB (>471.5 μM). Patients with higher KB (N=210) had lower BMI, higher BNP, and were more likely to be in the New York Heart Association class III-IV; however, these patients were less likely to have hyperlipidemia, coronary disease, or diabetes mellitus (P < 0.05). Age, sex, creatinine, ejection fraction, or Meta-Analysis Global Group in Chronic HF (MAGGIC) score did not differ by KB group. Higher KB was associated with worse survival (figure). After adjustment for the MAGGIC score, higher KB was associated with increased risk of mortality (HR 1.3; 95% CI, 1.08-1.48). Conclusions: In this community HF cohort, higher KB was associated with increased mortality, independent of the MAGGIC score.