Faculty Bibliography

BACKGROUND:Plant-based diets are associated with a lower risk of cardiovascular disease (CVD). Proteomics may improve our understanding of the biological pathways underlying these associations. OBJECTIVES/OBJECTIVE:Using large-scale proteomics, we aimed to examine if plant-based diet-related proteins, which have been previously identified, are associated with incident CVD and subtypes of CVD in the Atherosclerosis Risk in Communities (ARIC) Study and Framingham Heart Study (FHS) Offspring cohort. METHODS:Discovery analyses were based on 9,078 participants free of CVD at ARIC visit 3 (1993-1995). Cox proportional hazards regression was used to evaluate the associations between plant-based diet-related proteins and incident CVD, coronary heart disease, heart failure, and stroke. Replication analyses were based on 1,279 participants without CVD in FHS Offspring cohort. RESULTS:In the ARIC Study, over a median follow-up of 21 years, there were 3,167 CVD events. At a false discovery rate (FDR) <0.05, 26 out of 73 plant-based diet-related proteins were significantly associated with incident CVD, after adjusting for important confounders. 18, 1, and 0 proteins were associated with heart failure, stroke, and coronary heart disease, respectively. Three, and 2 additional proteins were associated with CVD, and heart failure risk in FHS Offspring cohort at the nominal threshold (p value <0.05). Soluble advanced glycosylation end product-specific receptor (AGER) was inversely associated with incident CVD whereas thrombospondin-2 (THBS2) and N-terminal pro-BNP (NT-proBNP) was positively associated with incident CVD. THBS2 was positively associated with incident heart failure, whereas neuronal growth factor regulator 1 (NEGR1) and insulin-like growth factor-binding protein 1 (IGFBP1) was inversely associated. CONCLUSION/CONCLUSIONS:These proteins highlight several pathways that could explain plant-based diets-CVD associations.

OBJECTIVE:To examine the associations between patient out-of-pocket (OOP) costs and nonadherence to glucagon-like peptide 1 receptor agonists (GLP-1a), and the consequent impact on adverse outcomes, including hospitalizations and emergency department (ED) visits. RESEARCH DESIGN AND METHODS/METHODS:This retrospective cohort study used MarketScan Commercial data (2016-2021). The cohort included nonpregnant adults aged 18-64 years with type 2 diabetes who initiated GLP-1a therapy. Participants were continuously enrolled in the same private insurance plan for 6 months before the prescription date and 1 year thereafter. Exposures included average first 30-day OOP costs for GLP-1a, categorized into quartiles (lowest [Q1] to highest [Q4]). Primary outcomes were the annual proportion of days covered (PDC) for GLP-1a and nonadherence, defined as PDC <0.8. Secondary outcomes included diabetes-related and all-cause hospitalizations and ED visits 1 year post-GLP-1a initiation. RESULTS:Among 61,907 adults who initiated GLP-1a, higher 30-day OOP costs were associated with decreased adherence. Patients in the highest OOP cost quartile (Q4: $80-$3,375) had significantly higher odds of nonadherence (odds ratio [OR]1.25; 95% CI 1.19-1.31) compared with those in Q1 ($0-$21). Nonadherence was linked to increased incidence rates of diabetes-related hospitalizations or ED visits (incidence rate ratio [IRR] 1.86; 95% CI 1.43-2.42), cumulative length of hospitalization (IRR 1.56; 95% CI 1.41-1.72), all-cause ED visits (IRR 1.38; 95% CI 1.32-1.45), and increased ED-related costs ($69.81, 95% CI $53.54-$86.08). CONCLUSIONS:Higher OOP costs for GLP-1a were associated with reduced adherence and increased rates of adverse outcomes among type 2 diabetes patients.

INTRODUCTION/BACKGROUND:The number of assays on proteomic platforms has grown rapidly. The leading platforms, SomaScan and Olink, have strengths and limitations. Comparisons of precision on the latest platforms-SomaScan 11k and Olink Explore HT-have not yet been established. METHODS:Among 102 participants in the Atherosclerosis Risk in Communities Study (mean age 74 years, 53% women, 47% Black), we used split plasma samples to measure platform precision. CV and Spearman correlations were calculated for each assay. Cross-platform agreement was assessed for overlapping proteins. RESULTS:SomaScan 11k demonstrated a median correlation of 0.85 for the 10 778 assays and a median CV of 6.8%, similar precision to earlier versions. The 5420 assays on Olink Explore HT exhibited a median correlation of 0.65 and median CV of 35.7%, which was higher than observed in its predecessors (e.g., 19.8% for Olink Explore 3072). Precision of Olink assays was inversely correlated with the percentage of samples above the limit of detection (LOD) (r = -0.77). Upon replacing Olink values below the LOD with values half the LOD, the median correlation for Olink assays measured in duplicate increased to 0.79; the median CV decreased to 13.3%. The distribution of between-platform correlations for the 4443 overlapping proteins had peaks at r approximately 0 and at r approximately 0.8. One-tenth of the protein pairs had cross-platform correlations r ≥ 0.8. CONCLUSIONS:Precision of these 2 proteomics platforms in human plasma has diverged as the coverage has increased. These results highlight the need for careful consideration in platform selection based on specific research requirements.

PURPOSE OF REVIEW/OBJECTIVE:Despite emerging studies on neighborhood-level risk factors for chronic kidney disease (CKD), our understanding of the causal links between neighborhood characteristics and CKD is limited. In particular, there is a gap in identifying modifiable neighborhood factors, such as the built environment, in preventing CKD, that could be targets for feasible place-based interventions. RECENT FINDINGS/RESULTS:Most published studies on neighborhood factors and CKD have focused on a single social attribute, such as neighborhood disadvantage, while research on the role of the built environment is more nascent. Early studies on this topic have yielded inconsistent results, particularly regarding whether food deserts are an environmental risk factor for CKD onset. International studies have shown that walkable neighborhoods - characterized by features such as urban design, park access, and green spaces - can be protective against both the onset and progression of CKD. However, these findings are inconclusive and understudied in the context of United States, where neighborhood environments differ from those in other countries. SUMMARY/CONCLUSIONS:Future research on modifiable neighborhood factors and CKD using advanced study designs and population-representative datasets can yield stronger evidence on potential causal associations and suggest feasible place-based interventions as strategies for preventing CKD. As an example, we demonstrated the potential of electronic health record-based studies to advance research in this area.

In 2017, Kidney Disease: Improving Global Outcomes (KDIGO) published a Clinical Practice Guideline Update for the Diagnosis, Evaluation, Prevention, and Treatment of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD). Since then, new lines of evidence have been published related to evaluating disordered mineral metabolism and bone quality and turnover, identifying and inhibiting vascular calcification, targeting vitamin D levels, and regulating parathyroid hormone. For an in-depth consideration of the new insights, in October 2023, KDIGO held a Controversies Conference on CKD-MBD: Progress and Knowledge Gaps Toward Personalizing Care. Participants concluded that the recommendations in the 2017 CKD-MBD guideline remained largely consistent with the available evidence. However, the framework of the 2017 Guideline, with 3 major sections-biochemical abnormalities in mineral metabolism; bone disease; and vascular calcification-may no longer best reflect currently available evidence related to diagnosis and treatment. Instead, future guideline efforts could consider mineral homeostasis and deranged endocrine systems in adults within a context of 2 clinical syndromes: CKD-associated osteoporosis, encompassing increased fracture risk in patients with CKD; and CKD-associated cardiovascular disease, including vascular calcification and structural abnormalities, such as valvular calcification and left ventricular hypertrophy. Participants emphasized that the complexity of bone and cardiovascular manifestations of CKD-MBD necessitates personalized approaches to management.

BACKGROUND:Cardiovascular risk models have been developed primarily for incident events. Well-performing models are lacking to predict secondary cardiovascular events among people with a history of coronary heart disease, stroke, or heart failure who also have chronic kidney disease (CKD). We sought to develop a proteomics-based risk score for cardiovascular events in individuals with CKD and a history of cardiovascular disease. METHODS:We measured 4638 plasma proteins among 1067 participants from the Chronic Renal Insufficiency Cohort (CRIC) and 536 individuals from the Atherosclerosis Risk in Communities Cohort (ARIC). All had non-dialysis-dependent CKD and coronary heart disease, heart failure, or stroke at study baseline. A proteomic risk model for secondary cardiovascular events was derived by elastic net regression in CRIC, validated in ARIC, and compared to clinical models. Biologic mechanisms of secondary events were characterized through proteomic pathway analysis. RESULTS:A 16-protein risk model was superior to the Framingham risk score for secondary events, including a modified score that included estimated glomerular filtration rate (eGFR). In CRIC, the annualized area under the receiver operating characteristic (AUC) within 1 to 5 years ranged between 0.77 and 0.80 for the protein model and 0.57 and 0.72 for the clinical models. These findings were replicated in the ARIC validation cohort. Biologic pathway analysis identified pathways and proteins for cardiac remodeling and fibrosis, vascular disease, and thrombosis. CONCLUSIONS:The proteomic risk model for secondary cardiovascular events outperformed clinical models based on traditional risk factors and eGFR.

AIMS/HYPOTHESIS/OBJECTIVE:39-47 mmol/mol [5.7-6.4%] or fasting glucose 5.6-6.9 mmol/l) is associated with elevated risks of microvascular and macrovascular complications. It is unknown to what extent these risks in prediabetes remain after accounting for progression to diabetes. METHODS:In 10,310 participants from the Atherosclerosis Risk in Communities (ARIC) Study (aged 46-70 years, ~55% women, ~20% Black adults) without diabetes at baseline (1990-1992), we used Cox regression to characterise age- and sex-adjusted associations of prediabetes with ~30 year incidence of complications (composite and separately), including atherosclerotic CVD (ASCVD), heart failure, chronic kidney disease (CKD) and all-cause mortality before and after accounting for intervening incidence of diabetes, modelled as a time-varying variable. We calculated the excess risk of complications in prediabetes remaining after accounting for progression to diabetes. RESULTS:Of the 60% of adults with prediabetes at baseline, ~30% progressed to diabetes (median time to diabetes, 7 years). Over the maximum follow-up of ~30 years, there were 7069 events (1937 ASCVD, 2109 heart failure, 3288 CKD and 4785 deaths). Prediabetes was modestly associated with risk of any complication (HR 1.21 [95% CI 1.15, 1.27]) vs normoglycaemia. This association remained significant after accounting for progression to diabetes (HR 1.18 [95% CI 1.12, 1.24]) with 85% (95% CI 75, 94%) of the excess risk of any complication in prediabetes remaining. Results were similar for the individual complications. CONCLUSIONS/INTERPRETATION/CONCLUSIONS:Progression to diabetes explained less than one-quarter of the risks of clinical outcomes associated with prediabetes. Prediabetes contributes to the risk of clinical outcomes even without progression to diabetes.

The timely and rational institution of therapy is a key step towards reducing the global burden of chronic kidney disease (CKD). CKD is a heterogeneous entity with varied aetiologies and diverse trajectories, which include risk of kidney failure but also cardiovascular events and death. Developments in the past decade include substantial progress in CKD risk prediction, driven in part by the accumulation of electronic health records data. In addition, large randomized clinical trials have demonstrated the effectiveness of sodium-glucose co-transporter 2 inhibitors, glucagon-like peptide 1 receptor agonists and mineralocorticoid receptor antagonists in reducing adverse events in CKD, greatly expanding the options for effective therapy. Alongside angiotensin-converting enzyme inhibitors and angiotensin receptor blockers, these classes of medication have been proposed to be the four pillars of CKD pharmacotherapy. However, all of these drug classes are underutilized, even in individuals at high risk. Leveraging prognostic estimates to guide therapy could help clinicians to prescribe CKD-related therapies to those who are most likely to benefit from their use. Risk-based CKD management thus aligns patient risk and care, allowing the prioritization of absolute benefit in determining therapeutic selection and timing. Here, we discuss CKD prognosis tools, evidence-based management and prognosis-guided therapies.