Differences in iron kinetics during cardiac load between patients with atrial fibrillation and those with sinus rhythm.

INTRODUCTION: The prevalence of atrial fibrillation (AF) increases with age. Although most AF cases are caused by irregular electrical impulses near the pulmonary vein, not all elderly individuals develop AF. Moreover, risk factors such as hypertension and diabetes do not always lead to AF, even in severe conditions such as pneumonia. We aimed to examine iron kinetics, including ferritin, in patients with AF and individuals in normal sinus rhythm (NSR) using peripheral blood samples. METHODS: This case-control study included 178atients who visited the outpatient clinic of a cardiovascular and arrhythmia specialist at the National Center for Geriatrics and Gerontology between August and October 2023. Patients with missing iron-related blood tests and those with pacemaker implantation were excluded. Iron parameters (ferritin, free iron, transferrin saturation) were compared between AF (n = 53) and NSR (n = 125) groups. RESULTS: The AF group had higher Log brain natriuretic peptide (BNP) levels, indicating increased cardiac load (AF 2.18 vs NSR 1.53). However, there were no significant differences in iron parameters between the AF and NSR groups. After matching for age, sex, and coronary artery disease, the AF group showed an increasing trend in ferritin and a decreasing trend in free iron with BNP elevation, suggesting chronic inflammation. In contrast, the NSR group showed no significant changes in iron parameters with BNP elevation. CONCLUSION: Patients with AF are more likely to have elevated ferritin levels and decreased free iron levels during cardiac overload. Thus, they are more likely to present with chronic inflammation associated with cardiac overload in AF. Future studies should investigate the mechanisms underlying this phenomenon and its implications for AF treatment.

Upregulated Genes in Atrial Fibrillation Blood and the Left Atrium.

INTRODUCTION: Atrial fibrillation (AF) is a common arrhythmia associated with aging. Many known risk factors are associated with AF, but many senior individuals do not develop AF despite having multiple risk factors. This finding suggests that other factors may be involved in AF onset. This study aimed to identify upregulated genes in the peripheral blood and left atrium of patients with AF. These genes may serve as potential biomarkers to predict AF onset risk and its complications. METHODS: Gene expression data was analyzed from blood (n = 3) and left atrial samples (n = 15) of patients with AF and sinus rhythm. We evaluated the significant genes identified using p-value analysis of weighted average difference to confirm their rankings. We created figures for the genes using GeneMANIA and performed a functional analysis using Cytoscape3.10.1. Hub and bottleneck genes were identified based on degree and betweenness centrality. We used RefEx to confirm the organs in which the extracted genes were expressed. Heatmaps and Gene ontology term evaluation were performed to further elucidate the biological functions of the genes. RESULTS: We identified 12 upregulated genes (CAST, ASAH1, MAFB, VCAN, DDIT4, FTL, HEXB, PROS1, BNIP3L, PABPC1, YBX3, and S100A6) in both the blood and left atrium of patients with AF. We analyzed the gene functions using GeneMANIA and Cytoscape. The identified genes were involved in a variety of pathways, including lysosomal function and lipid and sphingolipid catabolism. Next, we investigated whether the 12 identified genes identified were systemically expressed or had high organ specificity. Finally, Reference expression (RefEx) was used to analyze the gene expression levels in various tissues. Four genes; FTL, ASAH1, S100A6, and PABPC1, were highly expressed in the normal heart tissue. Finally, we evaluated the expression levels of the 12 genes in the blood of patients with AF using a heatmap. Our findings suggest that the 12 genes identified in this study, especially the lysosome-related genes (FTL and ASAH1), may be involved in AF pathogenesis. CONCLUSION: Lysosome-related genes may be important to understand the AF pathophysiology and to develop AF-related future studies.

Adherence to Medication Regimens is an Effective Indicator of Cognitive Dysfunction in Elderly Individuals.

BACKGROUND: Cognitive abilities strongly influence medication adherence among elderly individuals. We aimed to evaluate the relationship between medication adherence and cognitive decline using Lawton's instrumental activities of daily living (IADL) scoring system and the Mini-Mental State Examination (MMSE). METHODS: Receiver-operating characteristic (ROC) curves were used to evaluate the IADL scores and MMSE results. RESULTS: The ROC curve analysis of the IADL and MMSE results revealed that the shopping (MMSE cutoff = 22 points, sensitivity = 0.726, and specificity = 0.683) and responsibility for own medications (MMSE cutoff = 22 points, sensitivity = 0.759, and specificity = 0.720) categories were associated with declining IADL scores during early stage cognitive dysfunction. CONCLUSION: Declining IADL scores in the shopping and responsibility for own medications categories may be effective indices for predicting early-stage cognitive dysfunction in elderly individuals. Cognitive dysfunction screening at pharmacy counters may be useful.