**Background:** Vascular calcification is a complication of advanced atherosclerosis and a major contributor to cardiovascular disease (CVD). The aortic arch calcification (AoAC) score, assessed semiquantitatively on chest radiographs, is a simple, noninvasive tool that correlates with CT-measured calcification volume and predicts cardiovascular events and mortality. Gut dysbiosis—alterations in the composition of the trillions of microbes colonizing the gut—has been linked to atherosclerosis through pathways involving inflammation, cholesterol metabolism, and bacterial metabolites such as trimethylamine-N-oxide (TMAO) and short-chain fatty acids (SCFAs). While prior studies have associated specific gut microbial changes with coronary artery disease, carotid atherosclerosis, and arterial stiffness, no study had specifically examined the relationship between gut microbiota and AoAC. This study aimed to compare the intestinal microbiome composition between patients with chronic diseases and high versus low AoAC scores.
**Methods:** From March to July 2020, 186 participants (118 males, 68 females; mean age 65.7 years) with chronic diseases (diabetes mellitus 80.6%, hypertension 75.3%, chronic kidney disease 48.9%) were recruited from the outpatient department of Kaohsiung Municipal Siaogang Hospital. Chronic diseases were defined as hypertension, diabetes, or CKD treated for >3 months. Exclusion criteria included active malignancies, abdominal cancer, abdominal radiation, acute/chronic inflammation, or antibiotic use within 3 months before enrollment. AoAC was assessed by a single blinded radiologist who divided the aortic arch on chest radiographs into 16 sections; the AoAC score was the number of sections with calcification. Patients were divided into three groups: low AoAC (score ≤3, n=103), medium AoAC (3<score≤6, n=40), and high AoAC (score >6, n=43). Fecal samples were collected, and bacterial genomic DNA was extracted using a QIAamp PowerFecal DNA Kit. The 16S rRNA gene V3-V4 region was amplified and sequenced on an Illumina MiSeq platform. After quality filtering and ASV construction via DADA2, the dataset was rarified to 27,919 reads per sample. Alpha diversity was assessed using Chao1 and Shannon indices with pairwise Kruskal-Wallis tests (Benjamini-Hochberg correction). Beta diversity was evaluated with PCoA using unweighted and weighted normalized UniFrac distance matrices, with significance tested by ANOSIM (999 permutations). The microbial dysbiosis index (MDI) was calculated, and differences among groups were examined using Kruskal-Wallis and post-hoc Dunn's tests. LEfSe (LDA score >2, Kruskal-Wallis p<0.05) identified discriminative taxa, and MaAsLin2 adjusted for age, sex, hypertension, and CKD as covariates. Functional profiling was performed using PICRUSt2 to estimate KEGG pathway abundances.
**Key Results:** The high AoAC group was older (mean 71.6 vs. 61.6 years), had higher diastolic blood pressure, greater hypertension prevalence with more Beta-blocker and calcium channel blocker use, lower hemoglobin, and lower eGFR compared to the low AoAC group. No significant differences were found in sex, BMI, systolic blood pressure, diabetes, CKD, CVD, cerebrovascular disease, or most medications and laboratory values (albumin, HbA1c, lipids, calcium, phosphorus). Alpha diversity was significantly lower in the high AoAC group (Chao1: 96.89±36.168; Shannon: 4.133±0.601) than in the low AoAC group (Chao1: 114.313±36.902; Shannon: 4.428±0.617), with no significant difference between low and medium AoAC groups (Chao1: 109.361±34.525; Shannon: 4.336±0.626). Kruskal-Wallis tests confirmed overall group differences (Chao1: H=6.577, p=0.037; Shannon: H=6.497, p=0.038). Beta diversity analysis showed significant community composition differences among groups using weighted normalized UniFrac (ANOSIM R=0.0599, p=0.041), with distinct clustering between low and high AoAC groups, while unweighted UniFrac did not reach significance (R=0.0297, p=0.146). The high AoAC group had a higher MDI than the low AoAC group. LEfSe identified 47 taxa differing among groups at various taxonomic levels. At the genus level, the low AoAC group had increased relative abundance of Agathobacter, Eubacterium coprostanoligenes group, Ruminococcaceae UCG-002, Barnesiella, Butyricimonas, Oscillibacter, Ruminococcaceae DTU089, and Oxalobacter. The high AoAC group showed increased relative abundance of class Bacilli. MaAsLin2 confirmed the genus-level associations after adjusting for age, sex, hypertension, and CKD, but did not detect significance at the class level. KEGG pathway analysis also revealed functional differences between groups.
**Clinical Implications:** This study provides the first evidence linking gut microbiota composition to AoAC severity in patients with chronic diseases. The finding that patients with low AoAC scores harbor a greater abundance of butyrate-producing bacteria (Agathobacter, Ruminococcaceae UCG-002, Ruminococcaceae DTU089, Oscillibacter, Butyricimonas) suggests that SCFA-mediated anti-inflammatory and gut barrier-protective mechanisms may play a role in reducing vascular calcification. Additionally, the enrichment of Eubacterium coprostanoligenes group (involved in cholesterol-to-coprostanol conversion) and Barnesiella (anti-inflammatory via SCFAs) in the low AoAC group points to potential cholesterol-lowering and anti-inflammatory pathways. The reduced alpha diversity and increased dysbiosis index in the high AoAC group align with prior evidence linking low microbial diversity to hypertension, diabetes, obesity, and frailty. These findings suggest that modulating the gut microbiome—particularly enhancing butyrate producers—could represent a novel therapeutic target for preventing or slowing vascular calcification. However, the cross-sectional design precludes causal inference, and the lack of a healthy control group limits generalizability. The study was conducted in an Asian population, and dietary differences may affect microbiome composition. Future longitudinal studies with larger, more diverse populations and direct measurement of butyrate and other metabolites are needed to confirm these associations and elucidate underlying mechanisms.