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AimsTo test the hypothesis that soluble cellular adhesion molecules would be positively and independently associated with risk of diabetes.MethodsSoluble levels of six cellular adhesion molecules (ICAM-1, E-selectin, VCAM-1, E-cadherin, L-selectin and P-selectin) were measured in participants in the Multi-Ethnic Study of Atherosclerosis, a prospective cohort study. Participants were then followed for up to 10 years to ascertain incident diabetes.ResultsSample sizes ranged from 826 to 2185. After adjusting for age, sex, race/ethnicity, BMI and fasting glucose or HbA1c , four cellular adhesion molecules (ICAM-1, E-selectin, VCAM-1 and E-cadherin) were positively associated with incident diabetes and there was a statistically significant trend across quartiles. Comparing the incidence of diabetes in the highest and lowest quartiles of each cellular adhesion molecule, the magnitude of association was largest for E-selectin (hazard ratio 2.49; 95% CI 1.26-4.93) and ICAM-1 (hazard ratio 1.76; 95% CI 1.22-2.55) in fully adjusted models. Tests of effect modification by racial/ethnic group and sex were not statistically significant for any of the cellular adhesion molecules (P > 0.05).ConclusionsThe finding of significant associations between multiple cellular adhesion molecules and incident diabetes may lend further support to the hypothesis that microvascular endothelial dysfunction contributes to risk of diabetes.

Paul Y Takahashi,1 Euijung Ryu,2 Suzette J Bielinski,3 Matthew Hathcock,2 Gregory D Jenkins,2 James R Cerhan,3 Janet E Olson3 1Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA; 2Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; 3Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USACorrespondence: Paul Y TakahashiDivision of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USATel +1-507-284-2511Fax +1-507-266-2297Email Takahashi.paul@mayo.eduBackground: The use of pharmacogenomics data is increasing in clinical practice. However, it is unknown if pharmacogenomics data can be used more broadly to predict outcomes like hospitalization or emergency department (ED) visit. We aim to determine the association between selected pharmacogenomics phenotypes and hospital utilization outcomes (hospitalization and ED visits).Methods: This cohort study utilized 10,078 patients from the Mayo Clinic Biobank in the RIGHT protocol with sequence and interpreted phenotypes for 10 selected pharmacogenes including CYP2D6, CYP2C9, CYP2C19, CYP3A5, HLA B 5701, HLA B 5702, HLA B 5801, TPMT, SLCO1B1, and DPYD. The primary outcome was hospitalization with ED visits as a secondary outcome. We used Cox proportional hazards model to test the association between each pharmacogenomics phenotype and the risk of the outcomes.Results: During the follow-up period (median [in years] = 7.3), 13% (n=1354) and 8% (n=813) of the subjects experienced hospitalization and ED visits, respectively. Compared to subjects who did not experience hospitalization, hospitalized patients were older (median age [in years]: 67 vs 65), poorer self-rated health (15% vs 4.7% for fair/poor), and higher disease burden (median number of chronic conditions: 7 vs 4) at baseline. There was no association of hospitalization with any of the pharmacogenomics phenotypes. The pharmacogenomics phenotypes were not associated with disease burden, a well-established risk factor for hospital utilization outcomes. Similar findings were observed for patients with ED visits during the follow-up period.Conclusion: We found no association of 10 well-established pharmacogenomics phenotypes with either hospitalization or ED visits in this relatively large biobank population and outside the context of specific drug use related to these genes. Traditional risk factors for hospitalization like age and self-rated health were much more likely to predict hospitalization and/or ED visits than this pharmacogenomics information.Keywords: pharmacogenomics, emergency department, hospitalization

Guilherme S Lopes,1,2 Suzette J Bielinski,2 Ann M Moyer,3 John Logan Black III,3 Debra J Jacobson,1 Ruoxiang Jiang,1 Nicholas B Larson,1 Jennifer L St Sauver2 1Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; 2Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; 3Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USACorrespondence: Guilherme S LopesDivision of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USATel +1 507 422 6094Email lopes.guilherme@mayo.eduBackground: Several small studies have previously investigated associations between the cytochrome P450 2D6 (CYP2D6) metabolism and response to opioids. We used a large sample of patients to study associations between CYP2D6 phenotypes and estimated CYP2D6 enzymatic activity scores with pain control and adverse reactions related to codeine and tramadol use. We conducted additional analyses to determine whether our results were consistent among men and women.Methods: We used data from 2,877 participants in the RIGHT Protocol who were prescribed codeine and/or tramadol between 01/01/2005 and 12/31/2017 and who were not prescribed CYP2D6 inhibitors within 1 year prior to the opioid prescription. CYP2D6 phenotype categories were condensed into four groups: (1) Ultra-rapid and Rapid (n = 61), (2) Normal and Intermediate to Normal (n = 1,448), (3) Intermediate and Intermediate to Poor (n = 1,175), and (4) Poor metabolizer status (n = 193). Opioid-related outcomes included indications of poor pain control or adverse reactions related to medication use. We modeled the risk of each outcome using logistic regression, adjusting for age, sex, race, and ethnicity.Results: The results revealed a trend from poor to ultra-rapid and rapid CYP2D6 phenotypes in which the risk of adverse reactions incrementally increased and the risk of poor pain control incrementally decreased. This trend reached statistical significance among female (but not male) participants. Among normal and intermediate to normal metabolizers, a larger proportion of women experienced adverse reactions relative to men.Discussion: We replicated and extended the findings of previous research indicating associations between CYP2D6 phenotypes and response to opioids. In addition, the observed associations were stronger in women than in men. We recommend sex differences to be factored in future research investigating associations between pharmacogenomics and response to medications.Keywords: opioids, codeine, tramadol, pharmacogenomics, sex differences, CYP2D6

Jyothsna Giri,1 Ann M Moyer,2 Suzette J Bielinski,3 Pedro J Caraballo4,5 1Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA; 2Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA; 3Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; 4Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA; 5Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USACorrespondence: Pedro J CaraballoCenter for the Science of Health Care Delivery, Mayo Clinic, 200 First Street SW, Rochester, MN 55904, USATel +1 507 284 8586Fax +1 507 284 5370Email caraballo.pedro@mayo.eduAbstract: Pharmacogenomics (PGx) is often promoted as the domain of precision medicine with the greatest potential to readily impact everyday healthcare. Rapid advances in PGx knowledge derived from extensive basic and clinical research along with decreasing costs of laboratory testing have led to an increased interest in PGx and expectations of imminent clinical translation with substantial clinical impact. However, the implementation of PGx into clinical workflows is neither simple nor straightforward, and comprehensive processes and multidisciplinary collaboration are required. Several national and international institutions have pioneered models for implementing clinical PGx, and these initial models have led to a better understanding of unresolved challenges. In this review, we have categorized and explored the most relevant of these challenges to highlight potential gaps and present possible solutions. We describe the ongoing need for basic and clinical research to drive further developments in evidence-based medicine. Integration into daily clinical workflows introduces new challenges requiring innovative solutions; specifically those related to the electronic health record and embedded clinical decision support. We describe advances in PGx testing and result reporting and describe the critical need for increased standardization in these areas across laboratories. We also explore the complexity of the PGx knowledge required for clinical practice and the need for educational strategies to ensure adequate understanding among members of current and future healthcare teams. Finally, we evaluate knowledge obtained from previous implementation efforts and discuss how to best apply these learnings to future projects. Despite these challenges, the future of precision medicine appears promising due to the rapidity of recent advances in the field and current multidisciplinary efforts to effectively translate PGx to everyday clinical practice.Keywords: precision medicine, pharmacogenomics, clinical implementation, clinical decision support, delivery of health care, medication therapy management

Paul Y Takahashi,1 Euijung Ryu,2 James R Cerhan,3 Suzette J Bielinski,3 Janet E Olson3 1Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA; 2Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; 3Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USACorrespondence: Paul Y TakahashiDivision of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USATel +1-507-284-2511Fax +1-507-266-2297Email Takahashi.paul@mayo.edu We appreciate the thoughts of Dr. Roman and his comments. We understand that the number of identified pharmacogenomic genes continues to increase with time, and the clinical utility also increases with time and expert opinion. We chose theseselected pharmacogenes because of their strong clinical practice recommendations and the data available at the time of the gene selection.1 Due largely to the efforts associated with other initiatives within the RIGHT study, our clinical practice set upspecific electronic medical record best practice alerts for these pharmacogenes, and it was believed that there was the potential for change in clinical care for patients with extreme phenotypes.2 We did not design the study to specifically look at allpharmacogenomic genes. View the original paper by Takahashi and colleagues This is in response to the Letter to the Editor

Jennifer L St Sauver,1,2 Janet E Olson,1,3 Veronique L Roger,1,2,4 Wayne T Nicholson,5 John L Black III,3,6 Paul Y Takahashi,7 Pedro J Caraballo,7 Elizabeth J Bell,2 Debra J Jacobson,1,2 Nicholas B Larson,1 Suzette J Bielinski,1,3 1Department of Health Sciences Research, 2Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, 3Center for Individualized Medicine, 4Department of Cardiovascular Diseases, 5Department of Anesthesiology and Perioperative Medicine, 6Department of Laboratory Medicine and Pathology, 7Department of Primary Care Internal Medicine, Mayo Clinic, Rochester, MN, USA Background: Variation in the CYP2D6 gene may affect response to opioids in both poor and ultrarapid metabolizers, but data demonstrating such associations have been mixed, and the impact of variants on toxicity-related symptoms (e.g., nausea) is unclear. Therefore, we examined the association between CYP2D6 phenotype and poor pain control or other adverse symptoms related to the use of opioids in a sample of primary care patients.Materials and methods: We identified all patients in the Mayo Clinic RIGHT Protocol who were prescribed an opioid medication between July 01, 2013 and June 30, 2015, and categorized patients into three phenotypes: poor, intermediate to extensive, or ultrarapid CYP2D6 metabolizers. We reviewed the electronic health record of these patients for indications of poor pain control or adverse symptoms related to medication use. Associations between phenotype and outcomes were assessed using Chi-square tests and logistic regression.Results: Overall, 257 (25% of RIGHT Protocol participants) patients received at least one opioid prescription; of these, 40 (15%) were poor metabolizers, 146 (57%) were intermediate to extensive metabolizers, and 71 (28%) were ultrarapid metabolizers. We removed patients that were prescribed a CYP2D6 inhibitor medication (n=38). After adjusting for age and sex, patients with a poor or ultrarapid phenotype were 2.7 times more likely to experience either poor pain control or an adverse symptom related to the prescription compared to patients with an intermediate to extensive phenotype (odds ratio: 2.68; 95% CI: 1.39, 5.17; p=0.003).Conclusion: Our results suggest that >30% of patients with a poor or ultrarapid CYP2D6 phenotype may experience an adverse outcome after being prescribed codeine, tramadol, oxycodone, or hydrocodone. These medications are frequently prescribed for pain relief, and ~39% of the US population is expected to carry one of these phenotypes, suggesting that the population-level impact of these gene–drug interactions could be substantial. Keywords: CYP2D6, opioid, phenotype, adverse effects

Paul Y Takahashi,1 Euijung Ryu,2 Jyotishman Pathak,2 Gregory D Jenkins,2 Anthony Batzler,2 Matthew A Hathcock,2 John Logan Black,3 Janet E Olson,2 James R Cerhan,2 Suzette J Bielinski2 1Division of Primary Care Internal Medicine, Department of Medicine, 2Department of Health Sciences Research, 3Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA Background: Cytochrome P450 2D6 (CYP2D6) is responsible for the metabolism of clinically used drugs and other environmental exposures, but it is unclear whether the CYP2D6 phenotype is associated with adverse health outcomes. The aim was to determine the association of CYP2D6 phenotype with the risk of hospitalization or an emergency department (ED) visit among a group of primary care patients. Methods: In this study, 929 adult patients underwent CYP2D6 testing. The primary outcome was risk of hospitalization or an ED visit from January 2005 through September 2014. CYP2D6 genotypes were interpreted as 1 of 7 clinical phenotypes, from ultrarapid to poor metabolizer, and patients with the extensive metabolizer phenotype were used as the reference group. The hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for finding the association of CYP2D6 phenotypes with the risk of hospitalization or an ED visit by using Cox proportional hazard models and adjusting for age and sex. Results: The median age was 49 years (interquartile range, 46–52 years); 74% of patients had 3 or fewer chronic conditions, 285 had at least 1 hospitalization, and 496 had at least 1 ED visit. The risk of hospitalization was higher among patients who were ultrarapid metabolizers compared to extensive metabolizers (47% vs 30%; HR, 1.69; 95% CI, 1.11–2.57), as was the risk of an ED visit (62% vs 49%; HR, 1.50; 95% CI, 1.05–2.14). For poor metabolizers compared to extensive metabolizers, there was no difference in the risk of hospitalization (HR, 0.95; 95% CI, 0.58–1.56), but there was an increase in the risk of an ED visit (HR, 1.38; 95% CI, 0.96–1.98) (the difference was not statistically significant). Conclusion: We found an increased risk of hospitalization or an ED visit among ultrarapid compared to extensive CYP2D6 metabolizers. Further research identifying the mechanisms of the association and ultimate clinical utility is warranted. Keywords: cohort study, pharmacogenomics, emergency department, hospitalization

Paul Y Takahashi,1,2 Euijung Ryu,3 Janet E Olson,3 Erin M Winkler,4 Matthew A Hathcock,3 Ruchi Gupta,3 Jeff A Sloan,3 Jyotishman Pathak,3 Suzette J Bielinski,3 James R Cerhan3 1Division of Primary Care Internal Medicine, 2Department of Internal Medicine, 3Department of Health Sciences Research, 4Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA Background: Hospital risk stratification models using electronic health records (EHRs) often use age and comorbid health burden. Our primary aim was to determine if quality of life or health behaviors captured in an EHR-linked biobank can predict future risk of hospitalization. Methods: Participants in the Mayo Clinic Biobank completed self-administered questionnaires at enrollment that included quality of life and health behaviors. Participants enrolled as of December 31, 2010 were followed for one year to ascertain hospitalization. Data on comorbidities and hospitalization were derived from the Mayo Clinic EHR. Hazard ratios (HR) and 95% confidence interval (CI) were used, adjusted for age and sex. We used gradient boosting machines models to integrate multiple factors. Different models were compared using C-statistic. Results: Of the 8,927 eligible Mayo Clinic Biobank participants, 834 (9.3%) were hospitalized. Self-perceived health status and alcohol use had the strongest associations with risk of hospitalization. Compared to participants with excellent self-perceived health, those reporting poor/fair health had higher risk of hospitalization (HR =3.66, 95% CI 2.74–4.88). Alcohol use was inversely associated with hospitalization (HR =0.57 95% CI 0.45–0.72). The gradient boosting machines model estimated self-perceived health as the most influential factor (relative influence =16%). The predictive ability of the model based on comorbidities was slightly higher than the one based on the self-perceived health (C-statistic =0.67 vs 0.65). Conclusion: This study demonstrates that self-perceived health may be an important piece of information to add to the EHR. It may be another method to determine hospitalization risk. Keywords: alcohol, aging, multiple chronic conditions, EHR, health behavior, hospitalization, quality of life

Objective: Elevated fasting glucose level is associated with increased carotid intima-media thickness (IMT), a measure of subclinical atherosclerosis. It is unclear if this association is causal. Using the principle of Mendelian randomization, we sought to explore the causal association between circulating glucose and IMT by examining the association of a genetic risk score with IMT.Research Design and Methods: The sample was drawn from the Atherosclerosis Risk in Communities (ARIC) study and included 7,260 nondiabetic Caucasian individuals with IMT measurements and relevant genotyping. Components of the fasting glucose genetic risk score (FGGRS) were selected from a fasting glucose genome-wide association study in ARIC. The score was created by combining five single nucleotide polymorphisms (SNPs) (rs780094 [GCKR], rs560887 [G6PC2], rs4607517 [GCK], rs13266634 [SLC30A8], and rs10830963 [MTNR1B]) and weighting each SNP by its strength of association with fasting glucose. IMT was measured through bilateral carotid ultrasound. Mean IMT was regressed on the FGGRS and on the component SNPs, individually.Results: The FGGRS was significantly associated (P = 0.009) with mean IMT. The difference in IMT predicted by a 1 SD increment in the FGGRS (0.0048 mm) was not clinically relevant but was larger than would have been predicted based on observed associations between the FFGRS, fasting glucose, and IMT. Additional adjustment for baseline measured glucose in regression models attenuated the association by about one third.Conclusions: The significant association of the FGGRS with IMT suggests a possible causal association of elevated fasting glucose with atherosclerosis, although it may be that these loci influence IMT through nonglucose pathways. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study was to determine whether a variation in the transcription factor 7-like 2 (TCF7L2) gene, which influences diabetes risk, is associated with incidence of cancers.Research Design and Methods: We related diabetes and TCF7L2 variation with occurrence of several common cancers in a prospective cohort study of 13,117 middle-aged adults initially free of cancer in 1987-1989. We assessed five single nucleotide polymorphisms (SNPs) in TCF7L2 including the putative SNP (rs7903146) for diabetes. We identified incident cancers through 2000 via cancer registries, supplemented by hospital records.Results: Diabetes was associated marginally inversely with incidence of prostate cancer but not with incidence of colorectal, colon, lung, or breast cancer. The T allele of rs7903146 (frequency 30%) was associated with increased risk of colorectal cancer and, more specifically, colon cancer, with adjusted hazard ratios (95% CI) of 1.0 for CC, 1.25 (0.85-1.83) for CT, and 2.15 (1.27-3.64) for TT genotypes (P(trend) = 0.009). TCF7L2 variation also was associated with lung cancer incidence in whites but not blacks, but residual confounding by smoking may be present.Conclusions: Subjects who were initially cancer-free and carrying certain genetic variants of TCF7L2, most notably the T allele of rs7903146, have an increased risk of colon cancer. This association appears to be an independent gene effect not explained by diabetes. Because the T allele of rs7903146 is common, if a causal link is established, this variant could account for a sizable proportion ( approximately 17% here) of cases of colon cancer in the general population. [ABSTRACT FROM AUTHOR]

Objectives: The aims of the study were to identify conditions diagnosed in at least 10% of midlife women living in the US upper midwest and to assess prevalence by age, race, ethnicity, and sociodemographic status., Methods: The Rochester Epidemiology Project was used to conduct a cross-sectional prevalence study of 86,946 women between 40 and 59 years residing in a 27-county region of the United States on January 1, 2020. Diagnostic billing codes were extracted and grouped into broader condition categories using the Clinical Classification System Refined. The prevalence of 424 conditions was calculated by age, race, ethnicity, and area deprivation index quartiles. Logistic regression was used to examine associations between participant characteristics and conditions that affected 10% or more of the study population., Results: Twenty-eight conditions affected ≥10% of women, and eight conditions increased by ≥45% between the ages of 40 and 59 (disorders of lipid metabolism, hypertension, sleep/wake disorders, thyroid disorders, esophageal disorders, osteoarthritis, tendon and synovial disorders, and menopausal disorders; all test for trend P < 0.01). Black women had a significantly higher prevalence of hypertension and esophageal disorders at all ages (adjusted P values <0.05). Women living in more deprived areas had a significantly higher prevalence of hyperlipidemia, hypertension, sleep/wake disorders, and esophageal disorders (adjusted P values <0.05). Women living in less deprived areas had a significantly higher prevalence of thyroid disorders at age 40 to 44 and menopausal disorders at ages 50 to 59 (adjusted P values <0.05)., Conclusions: These data suggest that additional attention should focus on Black women and women with a lower socioeconomic status to ensure that common midlife conditions are diagnosed and treated., Competing Interests: Financial disclosure/conflicts of interest: J.L.S.S. receives ongoing institutional funding from Moderna and received past institutional funding from Exact Sciences. E.K. receives funding from Mithra Pharmaceuticals, Astellas Pharmaceuticals, and Womaness. K.L.M.'s institution was paid by NORC for her time as a subject matter expert and the American Cancer Society paid for travel costs related to her volunteer role as co-chair of a National Roundtable on Cervical Cancer work group to attend national meetings. Money was paid to her institution from her institution with Internal Mayo Clinic grants: Mayo Clinic Women's Health Research Center and Mayo Clinic Women's Health Pilot, Mayo Clinic Comprehensive Cancer Center (MCCCC) Disease Group, and Mayo Family Medicine Small Grants Program. She also receives ongoing institutional funding from the National Cancer Institute. S.S.F. received past funding from PriMed and Optum Health as a lecturer. The other authors have nothing to disclose., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of The Menopause Society.)

Background: Angiographic evidence of the anatomy of coronary arteries and the type of coronary artery lesions in women with a history of hypertensive disorders of pregnancy (HDP) are poorly documented., Objectives: This study sought to determine the role of a history of HDP as a unique risk factor for early coronary artery disease (CAD) and type of acute coronary syndrome (ACS) (ie, atherosclerotic vs myocardial infarction with nonobstructive coronary arteries [MINOCA]) in women who underwent coronary angiography., Methods: This study used a population-based cohort of parous female patients with incident CAD who underwent coronary angiography and age-matched control subjects. The SYNTAX (Synergy between PCI [percutaneous coronary intervention] with TAXUS [Boston Scientific] and Cardiac Surgery) score was assessed to determine the complexity and degree of CAD; MINOCA was diagnosed in the presence of clinical acute myocardial infarction in the absence of obstructive coronary disease., Results: A total of 506 parous female Olmsted County, Minnesota (USA) residents had incident CAD and angiographic data from November 7, 2002 to December 31, 2016. Women with HDP were younger than normotensive women at the time of the event (median: 64.8 years vs 71.8 years; P = 0.030). There was a strong association between HDP and ACS (unadjusted P = 0.018). Women with HDP compared with women with normotensive pregnancies were more likely to have a higher SYNTAX score (OR: 2.28; 95% CI: 1.02-5.12; P = 0.046), and MINOCA (OR: 2.08; 95% CI: 1.02-4.25; P = 0.044)., Conclusions: A history of HDP is associated with CAD earlier in life and with a future risk for myocardial infarction with both obstructive and nonobstructive coronary arteries. This study underscores the need for timely detection and treatment of nonobstructive disease, in addition to traditional risk factors., Competing Interests: Funding Support and Author Disclosures This study used the resources of the Rochester Epidemiology Project (REP) medical records-linkage system, which is supported by the National Institute on Aging (grant AG 058738), by the Mayo Clinic Research Committee, and by fees paid annually by REP users. The content of this article is solely the responsibility of the authors and does not represent the official views of the National Institutes of Health (NIH) or the Mayo Clinic. Dr Garovic has received support from NIH grant R01HL136348. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Introduction: The High mortality rates associated with heart failure (HF) have propelled the strategy of drug repurposing, which seeks new therapeutic uses for existing, approved drugs to enhance the management of HF symptoms effectively. An emerging trend focuses on utilizing real-world data, like EHR, to mimic randomized controlled trials (RCTs) for evaluating treatment outcomes through what are known as emulated trials (ET). Nonetheless, the intricacies inherent in EHR data-comprising detailed patient histories in databases, the omission of certain biomarkers or specific diagnostic tests, and partial records of symptoms-introduce notable discrepancies between EHR data and the stringent standards of RCTs. This gap poses a substantial challenge in conducting an ET to accurately predict treatment efficacy., Objective: The objective of this research is to predict the efficacy of drugs repurposed for HF in randomized trials by leveraging EHR in ET., Methods: We proposed an ET framework to predict drug efficacy, integrating target prediction based on biomedical databases with statistical analysis using EHR data. Specifically, we developed a novel target prediction model that learns low-dimensional representations of drug molecules, protein sequences, and diverse biomedical associations from a knowledge graph. Additionally, we crafted strategies to improve the prediction by considering the interactions between HF drugs and biological factors in the context of HF prognostic markers., Results: Our validation of the drug-target prediction model against the BETA benchmark demonstrated superior performance, with an average AUCROC of 97.7%, PRAUC of 97.4%, F1 score of 93.1%, and a General Score of 96.1%, surpassing existing baseline algorithms. Further analysis of our ET framework on identifying 17 repurposed drugs-derived from 266 phase 3 HF RCTs-using data from 59,000 patients at the Mayo Clinic highlighted the framework's remarkable predictive accuracy. This analysis took into account various factors such as biological variables (e.g., gender, age, ethnicity), HF medications (e.g., ACE inhibitors, Beta-blockers, ARBs, Loop Diuretics), types of HF (HFpEF and HFrEF), confounders, and prognostic markers (e.g., NT-proBNP, bUn, creatinine, and hemoglobin). The ET framework significantly improved the accuracy compared to the baseline efficacy analysis that utilized EHR data. Notably, the best results were improved in AUC-ROC from 75.71% to 93.57% and in PRAUC from 78.66% to 90.34%, compared to the baseline models., Conclusion: Our study presents an ET framework that significantly enhances drug efficacy emulation by integrating EHR-based analysis with target prediction. We demonstrated substantial success in predicting the efficacy of 17 HF drugs repurposed for phase 3 RCTs, showcasing the framework's potential in advancing HF treatment strategies., Competing Interests: Declaration of interests None

Objective: Rheumatoid arthritis (RA) has been associated with an elevated dementia risk. This study aimed to examine how different diagnostic dementia definitions perform in patients with RA compared to individuals without RA., Methods: The study population included 2050 individuals (1025 with RA) from a retrospective, population-based cohort in southern Minnesota and compared the performance of 3 code-based dementia diagnostic algorithms with medical record review diagnosis of dementia. For the overall comparison, each patient's complete medical history was used, with no time frames. 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. Sensitivity values ranged 56.5-95.9%, and positive predictive values ranged 55.2-83.1%. Performance measures declined with more restrictive time windows., Conclusion: Routinely collected electronic health record (EHR) data were used to define code-based dementia diagnostic 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 a similar EHR infrastructure, to identify dementia in individuals with RA., (Copyright © 2024 by the Journal of Rheumatology.)

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., (© 2024. International Osteoporosis Foundation and Bone Health and Osteoporosis Foundation.)

Objectives: Heart failure (HF) impacts millions of patients worldwide, yet the variability in treatment responses remains a major challenge for healthcare professionals. The current treatment strategies, largely derived from population based evidence, often fail to consider the unique characteristics of individual patients, resulting in suboptimal outcomes. This study aims to develop computational models that are patient-specific in predicting treatment outcomes, by utilizing a large Electronic Health Records (EHR) database. The goal is to improve drug response predictions by identifying specific HF patient subgroups that are likely to benefit from existing HF medications., Materials and Methods: A novel, graph-based model capable of predicting treatment responses, combining Graph Neural Network and Transformer was developed. This method differs from conventional approaches by transforming a patient's EHR data into a graph structure. By defining patient subgroups based on this representation via K-Means Clustering, we were able to enhance the performance of drug response predictions., Results: Leveraging EHR data from 11 627 Mayo Clinic HF patients, our model significantly outperformed traditional models in predicting drug response using NT-proBNP as a HF biomarker across five medication categories (best RMSE of 0.0043). Four distinct patient subgroups were identified with differential characteristics and outcomes, demonstrating superior predictive capabilities over existing HF subtypes (best mean RMSE of 0.0032)., Discussion: These results highlight the power of graph-based modeling of EHR in improving HF treatment strategies. The stratification of patients sheds light on particular patient segments that could benefit more significantly from tailored response predictions., Conclusions: Longitudinal EHR data have the potential to enhance personalized prognostic predictions through the application of graph-based AI techniques., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

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., (© 2024. The Author(s).)

Background: Higher total serum cholesterol is associated with lower mortality in heart failure. Evaluating associations between lipoprotein subfractions and mortality among people with heart failure may provide insights into this observation., Methods: We prospectively enrolled a community cohort of people with heart failure from 2003 to 2012 and assessed vital status through 2021. Plasma collected at enrollment was used to measure lipoprotein subfractions via nuclear magnetic resonance spectroscopy. A composite score of 6 lipoprotein subfractions was generated using the lipoprotein insulin resistance index (LP-IR) algorithm. Using covariate-adjusted proportional hazards regression models, we evaluated associations between LP-IR score and all-cause mortality., Results: Among 1382 patients with heart failure (median follow-up 13.9 years), a one-standard-deviation (SD) increment in LP-IR score was associated with lower mortality (hazard ratio [HR] 0.93; 95% confidence interval [CI], 0.97-0.99). Among LP-IR parameters, mean high-density lipoprotein (HDL) particle size was significantly associated with lower mortality (HR per 1-SD decrement in mean HDL particle size = 0.83; 95% CI, 0.78-0.89), suggesting that the inverse association between LP-IR score and mortality may be driven by smaller mean HDL particle size., Conclusions: LP-IR score was inversely associated with mortality among patients with heart failure and may be driven by smaller HDL particle size., (Published by Elsevier Inc.)

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., Competing Interests: Disclosures None.

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., Competing Interests: Disclosures Dr Connelly is an employee of and holds stock in Labcorp. Dr Otvos is a consultant, stockholder, and former employee of Labcorp. The other authors report no conflicts.

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.

National or statewide estimates of excess deaths have limited value to understanding the impact of the COVID-19 pandemic regionally. We assessed excess deaths in a 9-county geographically defined population that had low rates of COVID-19 and widescale availability of testing early in the pandemic, well-annotated clinical data, and coverage by 2 medical examiner's offices. We compared mortality rates (MRs) per 100,000 person-years in 2020 and 2021 with those in the 2019 reference period and MR ratios (MRRs). In 2020 and 2021, 177 and 219 deaths, respectively, were attributed to COVID-19 (MR = 52 and 66 per 100,000 person-years, respectively). COVID-19 MRs were highest in males, older persons, those living in rural areas, and those with 7 or more chronic conditions. Compared with 2019, we observed a 10% excess death rate in 2020 (MRR = 1.10 [95% CI, 1.04 to 1.15]), with excess deaths in females, older adults, and those with 7 or more chronic conditions. In contrast, we did not observe excess deaths overall in 2021 compared with 2019 (MRR = 1.04 [95% CI, 0.99 to 1.10]). However, those aged 18 to 39 years (MRR = 1.36 [95% CI, 1.03 to 1.80) and those with 0 or 1 chronic condition (MRR = 1.28 [95% CI, 1.05 to 1.56]) or 7 or more chronic conditions (MRR = 1.09 [95% CI, 1.03 to 1.15]) had increased mortality compared with 2019. This work highlights the value of leveraging regional populations that experienced a similar pandemic wave timeline, mitigation strategies, testing availability, and data quality., (Copyright © 2023 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Background: Inflammation and protein energy malnutrition are associated with heart failure (HF) mortality. The metabolic vulnerability index (MVX) is derived from markers of inflammation and malnutrition and measured by nuclear magnetic resonance spectroscopy. MVX has not been examined in HF., Objectives: The authors sought to examine the prognostic value of MVX in patients with HF., Methods: The authors prospectively assembled a population-based cohort of patients with HF from 2003 to 2012 and measured MVX scores with a nuclear magnetic resonance scan from plasma collected at enrollment. Patients were divided into 4 MVX score groups and followed until March 31, 2021., Results: The authors studied 1,382 patients (median age: 78 years; 48% women). The median MVX score was 64.6. Patients with higher MVX were older, more likely to be male, have atrial fibrillation, have higher NYHA functional class, and have HF duration of >18 months. Higher MVX was associated with mortality independent of Meta-analysis Global Group in Chronic Heart Failure score, ejection fraction, and other prognostic biomarkers. Compared to those with the lowest MVX, the HRs for MVX groups 2, 3, and 4 were 1.2 (95% CI: 0.9-1.4), 1.6 (95% CI: 1.3-2.0), and 1.8 (95% CI: 1.4-2.2), respectively (P trend  < 0.001). Measures of model improvement document the added value of MVX in HF for classifying the risk of death beyond the Meta-analysis Global Group in Chronic Heart Failure score and other biomarkers., Conclusions: In this HF community cohort, MVX was strongly associated with mortality independently of established clinical factors and improved mortality risk classification beyond clinically validated markers. These data underscore the potential of MVX to stratify risk in HF., Competing Interests: Funding Support and Author Disclosures The investigators were supported by the Intramural Research program of the National Heart, Lung, and Blood Institute of the National Institutes of Health. This study also used in part the resources from the Rochester Epidemiology Project medical records linkage system, which is supported by the National Institute on Aging (AG 058738), by the Mayo Clinic Research Committee, and by fees paid annually by Rochester Epidemiology Project users. The funding institution did not play a role in the design, conduct, analysis, or reporting or in the decision to submit this manuscript for publication. The study was approved by the Mayo Clinic and Olmsted Medical Center Institutional Review Boards. Dr Connelly is an employee of and holds stock in LabCorp. Dr Otvos is a consultant, stockholder, and former employee of LabCorp. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Published by Elsevier Inc.)

Background: The relationship between ketone bodies (KB) and mortality in patients with heart failure (HF) syndrome has not been well established., Objectives: The aim of this study is to assess the distribution of KB in HF, identify clinical correlates, and examine the associations between plasma KB and all-cause mortality in a population-based HF cohort., Methods: The plasma KB levels were measured by nuclear magnetic resonance spectroscopy. Multivariable linear regression was used to examine associations between clinical correlates and KB levels. Proportional hazard regression was employed to examine associations between KB (represented as both continuous and categorical variables) and mortality, with adjustment for several clinical covariates., Results: Among the 1,382 HF patients with KB measurements, the median (IQR) age was 78 (68, 84) and 52% were men. The median (IQR) KB was found to be 180 (134, 308) μM. Higher KB levels were associated with advanced HF (NYHA class III-IV) and higher NT-proBNP levels (both P  < 0.001). The median follow-up was 13.9 years, and the 5-year mortality rate was 51.8% [95% confidence interval (CI): 49.1%-54.4%]. The risk of death increased when KB levels were higher (HR high vs. low group 1.23; 95% CI: 1.05-1.44), independently of a validated clinical risk score. The association between higher KB and mortality differed by ejection fraction (EF) and was noticeably stronger among patients with preserved EF., Conclusions: Most patients with HF exhibited KB levels that were consistent with those found in healthy adults. Elevated levels of KB were observed in patients with advanced HF. Higher KB levels were found to be associated with an increased risk of death, particularly in patients with preserved EF., Competing Interests: MC is an employee of and holds stocks in LabCorp. JO is a consultant, stockholder, and former employee of LabCorp. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest, (© 2024 Oyetoro, Conners, Joo, Turecamo, Sampson, Wolska, Remaley, Otvos, Connelly, Larson, Bielinski, Hashemian, Shearer and Roger.)

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., Competing Interests: Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M23-2328.

A 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., (© 2023 Mayo Clinic. Aging Cell published by Anatomical Society and John Wiley & Sons Ltd.)

The National Institutes of Health's (NIH) K99/R00 Pathway to Independence Award offers promising postdoctoral researchers and clinician-scientists an opportunity to receive research support at both the mentored and the independent levels with the goal of facilitating a timely transition to a tenure-track faculty position. This transitional program has been generally successful, with most K99/R00 awardees successfully securing R01-equivalent funding by the end of the R00 period. However, often highly promising proposals fail because of poor grantsmanship. This overview provides guidance from the perspective of long-standing members of the National Heart, Lung, and Blood Institute's Mentored Transition to Independence study section for the purpose of helping mentors and trainees regarding how best to assemble competitive K99/R00 applications., Competing Interests: The authors have no conflicts of interest to declare., (© The Author(s) 2023.)

Background and Objectives: Prevention strategies for Alzheimer disease and Alzheimer disease-related dementias (AD/ADRDs) are urgently needed. Lipid variability, or fluctuations in blood lipid levels at different points in time, has not been examined extensively and may contribute to the risk of AD/ADRD. Lipid panels are a part of routine screening in clinical practice and routinely available in electronic health records (EHR). Thus, in a large geographically defined population-based cohort, we investigated the variation of multiple lipid types and their association to the development of AD/ADRD., Methods: All residents living in Olmsted County, Minnesota on the index date January 1, 2006, aged 60 years or older without an AD/ADRD diagnosis were identified. Persons with ≥3 lipid measurements including total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), or high-density lipoprotein cholesterol (HDL-C) in the 5 years before index date were included. Lipid variation was defined as any change in individual's lipid levels over time regardless of direction and was measured using variability independent of the mean (VIM). Associations between lipid variation quintiles and incident AD/ADRD were assessed using Cox proportional hazards regression. Participants were followed through 2018 for incident AD/ADRD., Results: The final analysis included 11,571 participants (mean age 71 years; 54% female). Median follow-up was 12.9 years with 2,473 incident AD/ADRD cases. After adjustment for confounding variables including sex, race, baseline lipid measurements, education, BMI, and lipid-lowering treatment, participants in the highest quintile of total cholesterol variability had a 19% increased risk of incident AD/ADRD, and those in highest quintile of triglycerides, variability had a 23% increased risk., Discussion: In a large EHR derived cohort, those in the highest quintile of variability for total cholesterol and triglyceride levels had an increased risk of incident AD/ADRD. Further studies to identify the mechanisms behind this association are needed., (Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.)

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., Competing Interests: Disclosures This study used the resources of the Rochester Epidemiology Project (REP) medical records-linkage system, which is supported by the National Institute on Aging (NIA; AG 058738), by the Mayo Clinic Research Committee, and by fees paid annually by REP users. The content of this article is solely the responsibility of the authors and does not represent the official views of the National Institutes of Health (NIH) or the Mayo Clinic.

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., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Context: Metformin is the first-line drug for treating diabetes but has a high failure rate., Objective: To identify demographic and clinical factors available in the electronic health record (EHR) that predict metformin failure., Methods: A cohort of patients with at least 1 abnormal diabetes screening test that initiated metformin was identified at 3 sites (Arizona, Mississippi, and Minnesota). We identified 22 047 metformin initiators (48% female, mean age of 57 ± 14 years) including 2141 African Americans, 440 Asians, 962 Other/Multiracial, 1539 Hispanics, and 16 764 non-Hispanic White people. We defined metformin failure as either the lack of a target glycated hemoglobin (HbA1c) (<7%) within 18 months of index or the start of dual therapy. We used tree-based extreme gradient boosting (XGBoost) models to assess overall risk prediction performance and relative contribution of individual factors when using EHR data for risk of metformin failure., Results: In this large diverse population, we observed a high rate of metformin failure (43%). The XGBoost model that included baseline HbA1c, age, sex, and race/ethnicity corresponded to high discrimination performance (C-index of 0.731; 95% CI 0.722, 0.740) for risk of metformin failure. Baseline HbA1c corresponded to the largest feature performance with higher levels associated with metformin failure. The addition of other clinical factors improved model performance (0.745; 95% CI 0.737, 0.754, P < .0001)., Conclusion: Baseline HbA1c was the strongest predictor of metformin failure and additional factors substantially improved performance suggesting that routinely available clinical data could be used to identify patients at high risk of metformin failure who might benefit from closer monitoring and earlier treatment intensification., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Aspirin-exacerbated respiratory disease (AERD) is an acquired inflammatory condition characterized by the presence of asthma, chronic rhinosinusitis with nasal polyposis, and respiratory hypersensitivity reactions on ingestion of aspirin or other nonsteroidal anti-inflammatory drugs (NSAIDs). Despite AERD having a classic constellation of symptoms, the diagnosis is often overlooked, with an average of greater than 10 years between the onset of symptoms and diagnosis of AERD. Without a diagnosis, individuals will lack opportunities to receive effective treatments, such as aspirin desensitization or biologic medications., Objective: Our aim was to develop a combined algorithm that integrates both natural language processing (NLP) and machine learning (ML) techniques to identify patients with AERD from an electronic health record (EHR)., Methods: A rule-based decision tree algorithm incorporating NLP-based features was developed using clinical documents from the EHR at Mayo Clinic. From clinical notes, using NLP techniques, 7 features were extracted that included the following: AERD, asthma, NSAID allergy, nasal polyps, chronic sinusitis, elevated urine leukotriene E4 level, and documented no-NSAID allergy. MedTagger was used to extract these 7 features from the unstructured clinical text given a set of keywords and patterns based on the chart review of 2 allergy and immunology experts for AERD. The status of each extracted feature was quantified by assigning the frequency of its occurrence in clinical documents per subject. We optimized the decision tree classifier's hyperparameters cutoff threshold on the training set to determine the representative feature combination to discriminate AERD. We then evaluated the resulting model on the test set., Results: The AERD algorithm, which combines NLP and ML techniques, achieved an area under the receiver operating characteristic curve score, sensitivity, and specificity of 0.86 (95% CI 0.78-0.94), 80.00 (95% CI 70.82-87.33), and 88.00 (95% CI 79.98-93.64) for the test set, respectively., Conclusions: We developed a promising AERD algorithm that needs further refinement to improve AERD diagnosis. Continued development of NLP and ML technologies has the potential to reduce diagnostic delays for AERD and improve the health of our patients., (©Thanai Pongdee, Nicholas B Larson, Rohit Divekar, Suzette J Bielinski, Hongfang Liu, Sungrim Moon. Originally published in JMIR AI (https://ai.jmir.org), 12.06.2023.)

Objective: To compare the 1-year health care utilization and mortality in persons living with heart failure (HF) before and during the coronavirus disease 2019 (COVID-19) pandemic., Patients and Methods: Residents of a 9-county area in southeastern Minnesota aged 18 years or older with a HF diagnosis on January 1, 2019; January 1, 2020; and January 1, 2021, were identified and followed up for 1-year for vital status, emergency department (ED) visits, and hospitalizations., Results: We identified 5631 patients with HF (mean age, 76 years; 53% men) on January 1, 2019, 5996 patients (mean age, 76 years; 52% men) on January 1, 2020, and 6162 patients (mean age, 75 years; 54% men) on January 1, 2021. After adjustment for comorbidities and risk factors, patients with HF in 2020 and patients with HF in 2021 experienced similar risks of mortality compared with those in 2019. After adjustment, patients with HF in 2020 and 2021 were less likely to experience all-cause hospitalizations (2020: rate ratio [RR], 0.88; 95% CI, 0.81-0.95; 2021: RR, 0.90; 95% CI, 0.83-0.97) compared with patients in 2019. Patients with HF in 2020 were also less likely to experience ED visits (RR, 0.85; 95% CI, 0.80-0.92)., Conclusion: In this large population-based study in southeastern Minnesota, we observed an approximately 10% decrease in hospitalizations among patients with HF in 2020 and 2021 and a 15% decrease in ED visits in 2020 compared with those in 2019. Despite the change in health care utilization, we found no difference in the 1-year mortality between patients with HF in 2020 and those in 2021 compared with those in 2019. It is unknown whether any longer-term consequences will be observed., Competing Interests: Given his role as an Editorial Board Member, Dr Paul Takahashi, was not involved in the peer-review of this article and had no access to information regarding its peer-review. All other authors report no potential competing interests., (© 2023 The Authors.)

Family history (FH) is important for disease risk assessment and prevention. However, incorporating FH information derived from electronic health records (EHRs) for downstream analytics is challenging due to the lack of standardization. We aimed to automatically align FH concepts derived from a clinical corpus to disease category resources popularly used, including Clinical Classification System (CCS), Phecode, Comparative Toxicogenomics Database (CTD), Human phenotype ontology, and Human disease ontology (HDO). Leveraging the Unified Medical Language System (UMLS), we achieved high mapping coverages of FH concepts in those resources, using the parent and broader/alike relations available in the UMLS. Among the five resources, CTD has the best coverage (93%) of FH concepts, HDO has the coarsest granularity of FH disease categories, while CCS showed the finest-grained regarding disease categories. The study suggests that we can mitigate the challenge of various degrees of granularity of NLP-derived FH using those ontology or terminological resources., (©2022 AMIA - All rights reserved.)

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., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The incorporation of information from clinical narratives is critical for computational phenotyping. The accurate interpretation of clinical terms highly depends on their associated context, especially the corresponding clinical section information. However, the heterogeneity across different Electronic Health Record (EHR) systems poses challenges in utilizing the section information., Objectives: Leveraging the eMERGE heart failure (HF) phenotyping algorithm, we assessed the heterogeneity quantitatively through the performance comparison of machine learning (ML) classifiers which map clinical sections containing HF-relevant terms across different EHR systems to standard sections in Health Level 7 (HL7) Clinical Document Architecture (CDA)., Methods: We experimented with both random forest models with sentence-embedding features and bidirectional encoder representations from transformers models. We trained MLs using an automated labeled corpus from an EHR system that adopted HL7 CDA standard. We assessed the performance using a blind test set (n = 300) from the same EHR system and a gold standard (n = 900) manually annotated from three other EHR systems., Results: The F-measure of those ML models varied widely (0.00-0.91%), indicating MLs with one tuning parameter set were insufficient to capture sections across different EHR systems. The error analysis indicates that the section does not always comply with the corresponding standardized sections, leading to low performance., Conclusions: We presented the potential use of ML techniques to map the sections containing HF-relevant terms in multiple EHR systems to standard sections. However, the findings suggested that the quality and heterogeneity of section structure across different EHRs affect applications due to the poor adoption of documentation standards., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Moon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background Larger within-patient variability of lipid levels has been associated with increased risk of cardiovascular disease (CVD); however, measures of lipid variability require ≥3 measurements and are not currently used clinically. We investigated the feasibility of calculating lipid variability within a large electronic health record-based population cohort and assessed associations with incident CVD. Methods and Results We identified all individuals ≥40 years of age who resided in Olmsted County, MN, on January 1, 2006 (index date), without prior CVD, defined as myocardial infarction, coronary artery bypass graft surgery, percutaneous coronary intervention, or CVD death. Patients with ≥3 measurements of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, or triglycerides during the 5 years before the index date were retained. Lipid variability was calculated using variability independent of the mean. Patients were followed through December 31, 2020 for incident CVD. We identified 19 652 individuals (mean age 61 years; 55% female), who were CVD-free and had variability independent of the mean calculated for at least 1 lipid type. After adjustment, those with highest total cholesterol variability had a 20% increased risk of CVD (Q5 versus Q1 hazard ratio, 1.20 [95% CI, 1.06-1.37]). Results were similar for low-density lipoprotein cholesterol and high-density lipoprotein cholesterol. Conclusions In a large electronic health record-based population cohort, high variability in total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol was associated with an increased risk of CVD, independent of traditional risk factors, suggesting it may be a possible risk marker and target for intervention. Lipid variability can be calculated in the electronic health record environment, but more research is needed to determine its clinical utility.

Background: The Framingham Heart Study Dementia Risk Score (FDRS) was developed in a general population of older persons. It is unknown how the FDRS variables predict Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD) in heart failure and atrial fibrillation populations. We aimed to evaluate the predictive ability of the FDRS variables in population-based cohorts of heart failure and atrial fibrillation and to determine whether the addition of other comorbidities and risk factors improves risk prediction for AD/ADRD., Methods: Residents aged ≥50 years from 7 southeastern Minnesota counties with a first diagnosis of heart failure or atrial fibrillation between January 1, 2013, and December 31, 2017, were identified. Patients with AD/ADRD before or within 6 months after index atrial fibrillation or heart failure and patients who died within 6 months after index were excluded. For both cohorts, models were constructed to predict AD/ADRD after index including the variables in the FDRS. Additional comorbidities and risk factors were added to the models. For all models, c-statistics using 5-fold cross-validation were calculated., Results: Among 3052 patients with heart failure (mean age 75 years, 53% male), 626 developed AD/ADRD; among 4107 patients with atrial fibrillation (mean age 74 years, 57% male), 736 developed AD/ADRD. Among patients with heart failure, the FDRS variables predicted AD/ADRD with c-statistic = 0.69. Adding comorbidities and risk factors improved the c-statistic slightly to 0.70. The FDRS variables also performed well (c-statistic = 0.73) in patients with atrial fibrillation; adding comorbidities and risk factors slightly improved performance (c-statistic = 0.75)., Conclusions: The variables from the FDRS predict AD/ADRD well in both heart failure and atrial fibrillation populations. The addition of comorbidities and risk factors only modestly improved prediction, indicating that the FDRS variables are appropriate to predict AD/ADRD in patients with heart failure and atrial fibrillation., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Hepatocyte growth factor (HGF) is a cytokine linked to incident heart failure (HF), particularly HF with preserved ejection fraction (HFpEF). Increases in left ventricular (LV) mass and concentric remodelling defined by increasing mass-to-volume (M:V) ratios are imaging risk markers for HFpEF. We aimed to determine if HGF is associated with adverse LV remodelling., Methods: We studied 4907 participants in the M ulti- E thnic S tudy of A therosclerosis (MESA), free of cardiovascular disease and HF at baseline, who had HGF measured and cardiac magnetic resonance imaging (CMR) performed at baseline. Of these, 2921 completed a second CMR at 10 years. We examined the cross-sectional and longitudinal associations of HGF and LV structural parameters using multivariable-adjusted linear mixed-effect models, adjusting for cardiovascular disease risk factors and N-terminal pro B-type natriuretic peptide., Results: The mean (SD) for age was 62 (10) years; 52% were female. Median (interquartile range) for HGF level was 890 pg/mL (745-1070). At baseline, the highest HGF tertile, compared to the lowest, was associated with a greater M:V ratio (relative difference 1.94 [95% confidence interval [CI]: 0.72, 3.17]) and lower LV end-diastolic volume (-2.07 mL [95% CI: -3.72, -0.42)]. In longitudinal analysis, the highest HGF tertile was associated with increasing M:V ratio (10-year difference: 4.68 [95% CI: 2.64, 6.72]) and decreasing LV end-diastolic volume (-4.74 [95% CI: -6.87, -2.62])., Conclusions: In a community-based cohort, higher HGF levels were independently associated with a concentric LV remodelling pattern of increasing M:V ratio and decreasing LV end-diastolic volume by CMR over 10 years. These associations may reflect an intermediate phenotype explaining the association of HGF with HFpEF risk., (© 2023 The Authors.)

Circulating protease inhibitors are important regulators of inflammation that are implicated in the pathophysiology of heart failure (HF). Secretory leukocyte protease inhibitor (SLPI) is a serine protease inhibitor which protects pulmonary tissues against inflammatory damage; however, its role in HF is not well understood. We sought to evaluate associations of circulating SLPI and genetically-mediated serum SLPI with incident HF and its subtypes in a multi-ethnic cohort of adults using clinical and genetic epidemiological approaches. Among 2,297 participants in the Multi-Ethnic Study of Atherosclerosis (MESA), each doubling of serum SLPI was independently associated with incident HF (HR 1.77; 95% CI 1.02-3.02; P = 0.04), particularly incident HF with preserved ejection fraction (HFpEF; HR 2.44; 95% CI 1.23-4.84; P = 0.01) but not HF with reduced ejection fraction (HFrEF; HR 0.95; 95% CI 0.36-2.46; P = 0.91). Previously reported circulating SLPI protein quantitative trait loci (pQTLs) were not associated with serum SLPI levels or incident HF among MESA participants. In conclusion, baseline serum SLPI levels, but not genetically-determined serum SLPI, were significantly associated with incident HF and HFpEF over long-term follow-up in a multi-ethnic cohort. Serum circulating SLPI may be a correlate of inflammation that sheds insight on the pathobiology of HFpEF., (© 2023. The Author(s).)