Four-dimensional flow (4D Flow) CMR affords comprehensive 3D maps of advanced hemodynamics parameters such as wall shear stress (WSS). However, the evaluation of these data is often restricted to spatial averages in large regions of interests, such as the ascending aorta. Recent studies have explored ways of analyzing local intercohort WSS differences by using basic statistical tests with a p-value of 0.05 for determining significance, thus not accounting for the large number of comparisons made when exploring differences for multiple locations across the ascending aorta surface.

Permutation tests, frequently used in brain MRI, permit statistical analysis on a local level while controlling for the family-wise error rate by constructing the null hypothesis distribution based on the maximum statistic over the voxels at each permutation. We sought to use permutation tests to identify local regions of abnormal WSS in the ascending aorta in patients with aortic dilation.

Aims Understanding the mechanisms underlying ascending aortic dilation is imperative for refined risk stratification of these patients, particularly among incidentally identified patients, most commonly presenting with tricuspid valves. The aim of this study was to explore associations between ascending aortic haemodynamics, assessed using four-dimensional flow cardiovascular magnetic resonance imaging (4D flow CMR), and circulating biomarkers in aortic dilation. Methods and results Forty-seven cases with aortic dilation (diameter >= 40 mm) and 50 sex-and age-matched controls (diameter < 40 mm), all with tricuspid aortic valves, underwent 4D flow CMR and venous blood sampling. Associations between flow displacement, wall shear stress (WSS), and oscillatory shear index in the ascending aorta derived from 4D flow CMR, and biomarkers including interleukin-6, collagen type I alpha 1 chain, metalloproteinases (MMPs), and inhibitors of MMPs derived from blood plasma, were investigated. Cases with dilation exhibited lower peak systolic WSS, higher flow displacement, and higher mean oscillatory shear index compared with controls without dilation. No significant differences in biomarkers were observed between the groups. Correlations between haemodynamics and biomarkers were observed, particularly between maximum time-averaged WSS and interleukin-6 (r = 0.539, P < 0.001), and maximum oscillatory shear index and collagen type I alpha 1 chain (r = -0.575, P < 0.001 in cases). Conclusion Significant associations were discovered between 4D flow CMR derived whole-cardiac cycle WSS and circulating biomarkers representing inflammation and collagen synthesis, suggesting an intricate interplay between haemodynamics and the processes of inflammation and collagen synthesis in patients with early aortic dilation and tricuspid aortic valves.

OBJECTIVES: To investigate the association between type I collagen α1 chain (COL1α1) levels and coronary artery disease (CAD) by using absolute quantification in plasma. Also, to investigate the correlates of COL1α1 to clinical characteristics and circulating markers of collagen metabolism.

DESIGN: Life conditions, Stress and Health (LSH) study: prospective cohort study, here with a nested case-control design.Assessing Platelet Activity in Coronary Heart Disease (APACHE) study: prospective cohort study.

SETTING: LSH: primary care setting, southeast Sweden.APACHE: cardiology department, university hospital, southeast Sweden.

PARTICIPANTS: LSH: 1007 randomly recruited individuals aged 45-69 (50% women). Exclusion criteria was serious disease. After 13 years of follow-up, 86 cases with primary endpoint were identified and sex-matched/age-matched to 184 controls.

APACHE: 125 patients with myocardial infarction (MI), 73 with ST-elevation MI and 52 with non-ST-elevation MI.

EXCLUSION CRITERIA: Intervention study participation, warfarin treatment and short life expectancy.

PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome was the association between baseline COL1α1 and first-time major event of CAD, defined as fatal/non-fatal MI or coronary revascularisation after 13 years. Secondary outcomes were the association between the collagen biomarkers PRO-C1 (N-terminal pro-peptide of type I collagen)/C1M (matrix metalloproteinase-mediated degradation of type I collagen) and CAD; temporal change of COL1α1 after acute MI up to 6 months and lastly, correlates between COL1α1 and patient characteristics along with circulating markers of collagen metabolism.

RESULTS: COL1α1 levels were associated with CAD, both unadjusted (HR=0.69, 95% CI=0.56 to 0.87) and adjusted (HR=0.55, 95% CI=0.41 to 0.75). PRO-C1 was associated with CAD, unadjusted (HR=0.62, 95% CI=0.47 to 0.82) and adjusted (HR=0.61, 95% CI=0.43 to 0.86), while C1M was not. In patients with MI, COL1α1 remained unchanged up to 6 months. COL1α1 was correlated to PRO-C1, but not to C1M.

CONCLUSIONS: Plasma COL1α1 was independently and inversely associated with CAD. Furthermore, COL1α1 appeared to reflect collagen synthesis but not degradation. Future studies are needed to confirm whether COL1α1 is a clinically useful biomarker of CAD.