Javaid, Syed Sarmad

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

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.