Lirette, Seth

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 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.

Background Whether the association of blood pressure ( BP ) during sleep (nocturnal BP ) with cognition differs by race is unknown. Methods and Results Participants in the GENOA (Genetic Epidemiology Network of Arteriopathy) Study underwent ambulatory BP measurements, brain magnetic resonance imaging, and cognitive function testing (the Rey Auditory Verbal Learning Test, the Digit Symbol Substitution Task, and the Trail Making Test Part B) between 2000 and 2007. We examined multivariable linear regression models of the nocturnal BP ‐cognition association. Among 755 participants (mean age, 63 years; 64% women; 42% self‐identified black race; 76% taking antihypertensive medication), mean nocturnal systolic BP ( SBP )/diastolic BP was 126/69 mm Hg, daytime SBP / diastolic BP level was 139/82 mm Hg, and mean reduction in SBP from day to night (dipping) was 9%. Among the entire sample, a race interaction was observed in Digit Symbol Substitution Task and Trail Making Test Part B (both P <0.15). Race‐stratified analyses showed that a 1‐ SD increase in nocturnal SBP levels was associated with poorer Digit Symbol Substitution Task and log‐transformed Trail Making Test Part B scores (unstandardized regression coefficient [95% confidence interval ]: −1.98 [−3.28 to −0.69] and 0.06 [0.004–0.12]; both P< 0.05) in black but not white individuals. Additional adjustments for white matter hyperintensity volumes or brain atrophy, measured via brain magnetic resonance imaging, did not change the results. Results were similar when nocturnal SBP dipping was assessed as the exposure, yet daytime SBP levels yielded no association with cognition. Conclusions Nocturnal SBP measurements may be useful in assessing the potential risk for lower cognitive function in middle‐aged and older adults, particularly in black individuals.

432 Background: In clinical trials and clinical practice, tumor response assessment with computed tomography (CT) defines critical end points in patients with metastatic disease treated with systemic agents. Methods to reduce errors and improve efficiency in tumor response assessment could improve patient care. Methods: Eleven readers from 10 different institutions independently categorized tumor response according to three different therapeutic response criteria using paired baseline and initial post-therapy CT studies from 20 randomly selected patients with metastatic renal cell carcinoma treated with sunitinib as part of a completed phase III multi-institutional study. Images were evaluated with a manual tumor response evaluation method (standard-of-care) and with computer-assisted response evaluation (CARE) that included stepwise guidance, interactive error-identification and correction methods, automated tumor metric extraction, calculations, response categorization, and data/image archival. A cross-over design, patient randomization, and two-week washout period were used to reduce recall bias. Comparative effectiveness metrics included error rate and mean patient evaluation time. Results: The standard-of-care method was on average associated with one or more errors in 30.5% (6.1/20) of patients while CARE had a 0.0% (0.0/20) error rate (p<0.001). The most common errors were related to data transfer and arithmetic calculation. In patients with errors, the median number of error types was 1 (range 1-3). Mean patient evaluation time with CARE was twice as fast as the standard-of-care method (6.4 vs. 13.1 minutes, p<0.001). Conclusions: Computer-assisted tumor response evaluation reduced errors and time of evaluation, indicating better overall effectiveness than manual tumor response evaluation methods that are the current standard-of-care.

Objectives To examine associations between adiposity and adiposity change (loss, stable, gain) and subsequent longitudinal cognitive performance in African Americans in mid and late life. Design Cohort study using linear mixed models. Setting Genetic Epidemiology Network of Arteriopathy. Participants African‐American sibships with hypertension in Jackson, Mississippi (N = 1,108). Measurements Waist circumference and body mass index ( BMI ) were measured at two examinations 5 years apart. Stable adiposity was defined as values within 5% of the first measure. A composite cognitive Z ‐score was derived from individual cognitive test Z ‐scores at two study visits 6 years apart. Results Larger waist circumference was associated with greater rate of cognitive decline during follow‐up (beta = −0.0009 per year, P = .001); BMI , change in waist circumference, and change in BMI were not associated with rate of decline. Loss of adiposity in midlife was associated with higher cognitive Z ‐scores in middle‐aged individuals, and loss of adiposity in late life was associated with lower Z ‐scores in older adults ( P = .01 for interaction between waist circumference and age; P = .04 for interaction between BMI and age). Simultaneous inclusion of waist circumference and BMI in the cross‐sectional model suggested an association between larger waist circumference and poorer cognitive performance (beta = −0.009, P = .006) and between higher BMI and better cognitive performance (beta = 0.014, P = .06). Conclusion The results suggested a differential pattern of the relationship between adiposity and cognition according to age (mid‐ or late life) and regional distribution of adiposity.