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Background: Chronic kidney disease (CKD) has been linked to elevated inflammatory biomarkers, yet few studies have evaluated these associations using iothalamate-based measures of kidney function, highlighting the need for further research. Research question: Is CKD associated with elevated inflammatory markers when defined by measured glomerular filtration rate (mGFR) and urinary albumin-to-creatinine ratio (UACR)? Methods: Participants from the Genetic Epidemiology Network of Arteriopathy (GENOA) cohort were included if they had data available for at least one inflammatory marker at visit 2. 17 inflammatory markers were assessed, including C-reactive protein (CRP), interleukin-6 (IL-6), IL-18, tumor necrosis factor receptors 1 and 2 (TNFR1, TNFR2), serum amyloid A, intercellular and vascular adhesion molecules (ICAM, VCAM), E-selectin, P-selectin, monocyte chemoattractant protein (MCP), myeloperoxidase (MPO), receptor for advanced glycation end products (RAGE), matrix metalloproteinases 2 and 9 (MMP-2, MMP-9), and tissue inhibitors of metalloproteinases 1 and 2 (TIMP-1, TIMP-2). Kindey function was assessed using the urinary clearance of iothalamate. CKD was defined as mGFR < 60 mL/min/1.73 m 2 or UACR ≥ 30 mg/g. To further assess whether associations persisted without albuminuria, we also defined CKD solely by mGFR < 60 mL/min/1.73 m 2 . Generalized estimating equations (GEE) were used to assess associations between CKD status and inflammatory markers, accounting for familial clustering. Exponentiated beta coefficients from GEE models were used to present geometric mean (GM) ratios of each biomarker by CKD status, adjusted for demographics, lifestyle factors, cardiovascular risk factors, and medication use. Results: Among 1,010 participants (mean age 61 ± 10 years; 67% women; 48% Black adults), 207 were classified as having CKD. After adjusting for potential confounders, individuals with CKD had significantly higher levels of hsCRP, VCAM, TNFR1, and TNFR2 compared to those without CKD (GM ratios > 1; p < 0.05), while the remaining inflammatory markers showed no significant differences ( Figure 1 ). Importantly, these elevations remained significant when CKD was defined by mGFR alone ( Figure 2 ). Conclusion: Our findings suggest that CKD, defined by mGFR, is associated with specific inflammatory biomarkers, underscoring the need for mechanistic studies to investigate these associations.

Background: Hypertension and systemic inflammation are independently associated with adverse cardiovascular outcomes. While hypertension is a known risk factor for left ventricular (LV) hypertrophy, the role of inflammation in LV structural changes remains unclear. It is also uncertain whether concomitant inflammation and hypertension ("inflammatory hypertension") exacerbate LV hypertrophy. Research Question: Is inflammatory hypertension associated with increased LV mass index (LVMI) compared to hypertension without inflammation? Methods: We analyzed baseline data from Black adults enrolled in the Genetic Epidemiology Network of Arteriopathy (GENOA) cohort in Jackson, Mississippi. Inflammation was defined by high sensitivity C-reactive protein (hsCRP) >3 mg/L, and hypertension as systolic blood pressure (SBP) >130 mmHg. Participants were classified into four groups: noninflammatory-normotensive (reference group), noninflammatory-hypertensive, inflammatory-normotensive, and inflammatory-hypertensive. The primary outcome was LVMI, assessed by echocardiography. Associations between groups and LVMI were evaluated using generalized estimating equations to account for familial clustering and adjusted for covariates including age, sex, education, smoking status, body mass index, number of antihypertensive medications, statin use, cholesterol, and diabetes. Results: Among 1,027 participants (mean age 64 ± 8.5 years; 71% women), baseline LVMI differed by inflammation-hypertension status. Compared with the LVMI in noninflammatory-normotensive cohort (n=108; 74.5 g/m 2 [70.4–78.6]), significantly higher LVMI was observed in noninflammatory-hypertensive (n=343; 83.6 g/m 2 [81.3–85.9], p<0.001) and inflammatory-hypertensive groups (n=497; 84.7 g/m 2 [82.8–86.7], p<0.001). There was no statistically significant difference between inflammatory-hypertensive and noninflammatory-hypertensive groups (84.7 vs 83.6 g/m 2 )(p=0.460). The inflammatory-normotensive cohort also did not differ from the reference group (74.9 g/m 2 [70.2–79.5], p=0.901). Secondary analyses using elevated IL-6 to define inflammation yielded similar findings ( Figure 1 ). Conclusion: In individuals with inflammatory hypertension, hypertension appears to be the primary driver of LV hypertrophy. Further studies in larger, diverse populations are needed to definitively evaluate the potential additive effect of inflammatory hypertension on LV remodeling.

Key Points Using multiple markers may improve GFR estimation especially in settings where creatinine and cystatin C are known to be limited. Panel eGFR is a novel multimarker eGFR equation consisting of age, sex, cystatin C, and nuclear magnetic resonance–measured creatinine, valine, and myo-inositol. eGFR-Cr and eGFR-Cr-CysC may underestimate measured GFR, while panel eGFR was unbiased among younger Black male individuals. Background Using multiple markers may improve accuracy in GFR estimation. We sought to externally validate and compare the performance of a novel multimarker eGFR (panel eGFR) equation among Black and White persons using the Genetic Epidemiology Network of Arteriopathy cohort. Methods We included 224 sex, race/ethnicity, and measured GFR (mGFR) category–matched persons, with GFR measured using urinary clearance of iothalamate. We calculated panel eGFR using serum creatinine, valine, myo-inositol, cystatin C, age, and sex. We compared its reliability with current eGFR equations (2021 CKD Epidemiology Collaboration creatinine [eGFR-Cr] and creatinine with cystatin C [eGFR-Cr-CysC]) using median bias, precision, and accuracy metrics. We evaluated each equation's performance in age, sex, and race subgroups. Results In the overall cohort, 49% were Black individuals, and mean mGFR was 79 ml/min per 1.73 m 2 . Panel eGFR overestimated mGFR (bias: −2.4 ml/min per 1.73 m 2 ; 95% confidence interval [CI], −4.4 to −0.7), eGFR-Cr-CysC underestimated mGFR (bias: 4.8 ml/min per 1.73 m 2 ; 95% CI, 2.1 to 6.7), while eGFR-Cr was unbiased (bias: 2.0 ml/min per 1.73 m 2 ; 95% CI, −1.1 to 4.6). All equations had comparable accuracy. Among Black male individuals younger than 65 years, both eGFR-Cr (bias: 17.0 ml/min per 1.73 m 2 ; 95% CI, 8.6 to 23.5) and eGFR-Cr-CysC (bias: 14.5 ml/min per 1.73 m 2 ; 95% CI, 6.0 to 19.7) underestimated mGFR, whereas panel eGFR was unbiased (bias: 1.7 ml/min per 1.73 m 2 ; 95% CI, −3.4 to 10.0). Metrics of accuracy for all eGFRs were acceptable in all subgroups except for panel eGFR in Black female individuals younger than 65 years (P30: 73.3%). Conclusions Panel eGFR can be used to estimate mGFR and may have utility among Black male individuals younger than 65 years where current CKD Epidemiology Collaboration equations are biased.

Abstract Background and Aims The use of multiple markers may improve the accuracy in glomerular filtration rate (GFR) estimation especially when the interpretation of creatinine and cystatin C is limited. We sought to externally validate a recently developed multi-marker nuclear magnetic resonance (NMR)-based estimated GFR equation (eGFR-NMR) using the biracial Genetic Epidemiology Network of Arteriopathy cohort. Method We included 224 sex, race/ethnicity, and mGFR-category-matched participants. GFR was measured using urinary clearance of iothalamate (mGFR). We calculated eGFR-NMR using serum creatinine, valine, myo-inositol, and cystatin C, age, and sex. We compared the reliability of eGFR-NMR with current eGFR equations (2021 Chronic Kidney Disease Epidemiology Collaboration equations for creatinine [eGFR-Cr] and creatinine with cystatin C [eGFR-Cr-CysC]) using median bias, precision, and accuracy metrics. In particular, we evaluated its performance in age, sex, and race subgroups. Results In the overall cohort, mean age was 63 (±8) years, 54% were females, 49% were Black individuals, and mean mGFR was 78.7 (±24.3) ml/min/1.73 m2. eGFR-NMR overestimated mGFR by 2 mL/min/1.73 m2 (95% CI, 4 to 0.7) while eGFR-Cr-CysC underestimated mGFR by −5 mL/min/1.73 m2 (95% CI, −2 to −7). All equations had acceptable accuracy metrics. When stratified by age, sex, and race, eGFR-NMR performed the best among Black males age &lt;65 years compared to current equations (Figure 1). In this subgroup, eGFR-NMR was unbiased (bias, 2mL/min/1.73 m2 [95% CI, -3 to 10]) compared to substantial biases of eGFR-Cr (bias, 17 mL/min/1.73 m2 [95% CI, 9 to 24]) and eGFR-Cr-CysC (bias, 15 mL/min/1.73 m2 [95% CI, 6 to 20]). In other subgroups, measures of accuracy for eGFR-NMR, eGFR-Cr, eGFR-Cr-CysC were generally similar. Conclusion eGFR-NMR can be used to estimate mGFR and was more accurate than CKD-EPI equations among Black males age &lt;65 years.

Abstract Background Whether diabetes and adipokine‐driven inflammation explain the association of obesity to cognitive impairment is unknown. Methods Structural equation models estimated the total effects of waist circumference on cognitive outcomes among African American participants cross‐sectionally (index exam) and longitudinally. Total effects were deconstructed into direct pathways of waist circumference to cognitive impairment and indirect mediation pathways through leptin, soluble tumor necrosis factor receptor 2 (sTNFR2), and diabetes. Waist circumference, leptin, and sTNFR2 were standardized. Cognitive impairment was defined as MMSE <21 or a z‐score < −1.5 standard deviation (SD). Incident cognitive impairment was defined among those without cognitive impairment at the index exam as follow‐up MMSE<21, z‐ score < −1.5, MMSE decline >1 point/year, or z‐score decline of >0.1 SD/year. Results Among 1008 participants (70% women, mean age 62.9 years, 14.5% with obesity, 26% with diabetes), 132 (13%) had baseline cognitive impairment. Each SD higher waist circumference was associated with higher odds of cognitive impairment, odds ratio (OR) = 1.63; (95% confidence interval: 1.17, 2.24), with mediating pathways explaining 65% of the total effect (58% from diabetes; 7% from inflammation). At follow‐up (mean 6.8 years), 106 of 535 (19.8%) had developed cognitive impairment. Each SD higher waist circumference was associated with higher odds of developing cognitive impairment (OR = 1.87; 95%CI: 1.18, 2.74); the direct effect of waist circumference explained 37% of the total effect and mediating pathways explained 63% (61% from diabetes; 2% from inflammation), although individual pathways were not statistically supported in the smaller sample. Conclusion Diabetes, and to a lesser degree, adiposity‐driven inflammation, appear to explain a substantial proportion of abdominal adiposity relationships with cognitive impairment. The impact of preventing and treating obesity on cognitive outcomes merits study.

Objectives: Determine relationships between calcification and cognitive function. Background: Dementia affects over 5.4 million Americans; prevalence will quadruple in the next 50 years. Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, may affect cognitive function through microvascular brain effects. Abdominal aortoiliac calcification (AAC) generally precedes CAC and may provide earlier risk determination. Effects of calcification on cognition have not been studied in African Americans (AA). Methods: The 2008-2011 GENOA CAC cohort consists of AA sibships (n=657, mean age 69 [range 40-98], 74% women, 82% hypertensive) enriched with hypertension from Jackson, MS with computed tomography (CT) Agatston calcification measures. Cognition was assessed in 4 domains: global cognitive function (Mini-Mental State Examination); processing speed (Digit Symbol Substitution and Trail Making A); memory (RAVLT and WAIS-III Incidental Learning); and executive function (Trail Making B). Relationships of cognition (standardized) and calcification (log base 2 scale accounting for skewness) were examined using linear regressions with GEE to account for sibship clustering, adjusting parsimoniously for age, sex, and education. Results: Doublings of CAC were significantly associated with poorer processing speed (ß=-0.049 [-0.072, -0.025] p=0.000) and executive function (ß=-0.037 [-0.070, -0.003] p=0.031) in younger subjects and with poorer global function (ß=-0.0648 [-0.096, -0.020] p=0.000), memory (ß=-0.034 [-0.060, -0.007] p=0.013), and processing speed (ß=-0.051 [-0.076, -0.025] p=0.000) in older subjects. Doublings of AAC were significantly associated with poorer processing speed (ß=-0.0381 [-0.056, -0.020] p=0.000) and executive function (ß=-0.045 [-0.070, -0.020] p=0.000) in younger subjects and poorer processing speed (ß=-0.050 [-0.075, -0.025] p=0.000) in older subjects. Conclusions: Calcification is associated with processing speed in young and old AA with prevalent cardiovascular risk factors and may be differentially associated with other cognitive domains by age. Processing speed in particular may be a domain affected early in the calcification process, warranting further study. This supports existing literature addressing the relationship between calcification and cognitive function in ethnically diverse cohorts. Further studies can focus on the temporal and causal relationships between calcification and cognition across age in AA samples enriched for hypertension to identify predictive factors associated with future cognitive decline.