Noninvasive assessment of organ-specific and shared pathways in multi-organ fibrosis using T1 mapping.

Fibrotic diseases affect multiple organs and are associated with morbidity and mortality. To examine organ-specific and shared biologic mechanisms that underlie fibrosis in different organs, we developed machine learning models to quantify T1 time, a marker of interstitial fibrosis, in the liver, pancreas, heart and kidney among 43,881 UK Biobank participants who underwent magnetic resonance imaging. In phenome-wide association analyses, we demonstrate the association of increased organ-specific T1 time, reflecting increased interstitial fibrosis, with prevalent diseases across multiple organ systems. In genome-wide association analyses, we identified 27, 18, 11 and 10 independent genetic loci associated with liver, pancreas, myocardial and renal cortex T1 time, respectively. There was a modest genetic correlation between the examined organs. Several loci overlapped across the examined organs implicating genes involved in a myriad of biologic pathways including metal ion transport (SLC39A8, HFE and TMPRSS6), glucose metabolism (PCK2), blood group antigens (ABO and FUT2), immune function (BANK1 and PPP3CA), inflammation (NFKB1) and mitosis (CENPE). Finally, we found that an increasing number of organs with T1 time falling in the top quintile was associated with increased mortality in the population. Individuals with a high burden of fibrosis in ≥3 organs had a 3-fold increase in mortality compared to those with a low burden of fibrosis across all examined organs in multivariable-adjusted analysis (hazard ratio = 3.31, 95% confidence interval 1.77-6.19; P = 1.78 × 10-4). By leveraging machine learning to quantify T1 time across multiple organs at scale, we uncovered new organ-specific and shared biologic pathways underlying fibrosis that may provide therapeutic targets.

Assessment of valvular function in over 47,000 people using deep learning-based flow measurements.

Valvular heart disease is associated with a high global burden of disease. Even mild aortic stenosis confers increased morbidity and mortality, prompting interest in understanding normal variation in valvular function at scale. We developed a deep learning model to study velocity-encoded magnetic resonance imaging in 47,223 UK Biobank participants. We calculated eight traits, including peak velocity, mean gradient, aortic valve area, forward stroke volume, mitral and aortic regurgitant volume, greatest average velocity, and ascending aortic diameter. We then computed sex-stratified reference ranges for these phenotypes in up to 31,909 healthy individuals. In healthy individuals, we found an annual decrement of 0.03cm 2 in the aortic valve area. Participants with mitral valve prolapse had a 1 standard deviation [SD] higher mitral regurgitant volume (P=9.6 × 10 -12 ), and those with aortic stenosis had a 4.5 SD-higher mean gradient (P=1.5 × 10 -431 ), validating the derived phenotypes' associations with clinical disease. Greater levels of ApoB, triglycerides, and Lp(a) assayed nearly 10 years prior to imaging were associated with higher gradients across the aortic valve. Metabolomic profiles revealed that increased glycoprotein acetyls were also associated with an increased aortic valve mean gradient (0.92 SD, P=2.1 x 10 -22 ). Finally, velocity-derived phenotypes were risk markers for aortic and mitral valve surgery even at thresholds below what is considered relevant disease currently. Using machine learning to quantify the rich phenotypic data of the UK Biobank, we report the largest assessment of valvular function and cardiovascular disease in the general population.

Baseline assessment and comparison of arterial anatomy, hyperemic flow, and skeletal muscle perfusion in peripheral artery disease: The Cardiovascular Cell Therapy Research Network "Patients with Intermittent Claudication Injected with ALDH Bright Cells" (CCTRN PACE) study.

BACKGROUND: Peripheral artery disease (PAD) is important to public health as a major contributor to cardiovascular morbidity and mortality. Recent developments in magnetic resonance imaging (MRI) techniques permit improved assessment of PAD anatomy and physiology, and may serve as surrogate end points after proangiogenic therapies. METHODS: The PACE study is a randomized, double-blind, placebo-controlled clinical trial designed to assess the physiologic impact and potential clinical efficacy of autologous bone marrow-derived ALDHbr stem cells. The primary MRI end points of the study are as follows: (1) total collateral count, (2) calf muscle plasma volume (a measure of capillary perfusion) by dynamic contrast-enhanced MRI, and (3) peak hyperemic popliteal flow by phase-contrast MRI (PC-MRI). RESULTS: The interreader and intrareader and test-retest results demonstrated good-to-excellent reproducibility (interclass correlation coefficient range 0.61-0.98) for all magnetic resonance measures. The PAD participants (n=82) had lower capillary perfusion measured by calf muscle plasma volume (3.8% vs 5.6%) and peak hyperemic popliteal flow (4.1 vs 13.5mL/s) as compared with the healthy participants (n=16), with a significant level of collateralization. CONCLUSIONS: Reproducibility of the MRI primary end points in PACE was very good to excellent. The PAD participants exhibited decreased calf muscle capillary perfusion as well as arterial flow reserve when compared with healthy participants. The MRI tools used in PACE may advance PAD science by enabling accurate measurement of PAD microvascular anatomy and perfusion before and after stem cell or other PAD therapies.

Effects of Blood Transfusion on Cause-Specific Late Mortality After Coronary Artery Bypass Grafting-Less Is More.

BACKGROUND: Red blood cell transfusion after coronary artery bypass graft surgery has been associated with increased late all-cause death. Yet, whether this association is, first, independent of the packed red blood cells and perioperative morbidity association, and second, of a cardiac versus noncardiac etiology remains unknown. METHODS: We analyzed patients undergoing coronary artery bypass graft surgery at two Ohio hospitals (n = 6,947) from 1994 to 2007. Salvage operations and patients with preoperative renal failure were excluded. Long-term outcomes and leading cause of death (cardiac, noncardiac, all cause) were derived from the US Social Security Death Index and later from Ohio Department of Health Death Index. Fifteen-year mortality cumulative incidence functions were compared for transfusion groups (yes, n = 2,540; no, n = 4,806) overall, and then stratified based on perioperative complications status (yes, n = 2,638; no, n = 4,708). Comprehensive, 32 covariates, risk-adjusted transfusion effects were estimated by competing risk regression. Results were confirmed by propensity score adjusted analysis. RESULTS: Perioperative transfusions and complications occurred in 33.9% and 35.2% of patients, respectively. In all, 3,108 deaths (48.1%) have been documented (median time to death, 7.43 years). Both transfusion rates (25.6% versus 49.1%, p < 0.001) and deaths (58.2% versus 38.5%, p < 0.001) were more frequent among complications patients. Red blood cells transfusion increased intermediate to late mortality risk overall (15-year adjusted hazard ratio [AHR] 1.21, 95% confidence interval [CI]: 1.11 to 1.31), and for complications (AHR 1.24, 95% CI: 1.11 to 1.39) and no complications (AHR 1.16, 95% CI: 1.03 to 1.31). The increased mortality was true for cardiac and noncardiac etiologies (AHR 1.19, 95% CI: 1.03 to 1.36, and AHR 1.14, 95% CI: 1.01 to 1.29, respectively). Red blood cell transfusion increased mostly cardiac deaths (AHR 1.38, 95% CI: 1.14 to 1.66) among the complications group, and noncardiac mortality (AHR 1.24, 95% CI: 1.05 to 1.47) for the no complications group. A parallel propensity matched sensitivity analysis confirmed these findings. CONCLUSIONS: Perioperative red blood cells transfusion is associated with significant adverse late death effects among both complicated patients and noncomplicated patients, principally seen between 0 and 5 years postoperatively, and is driven by both increased cardiovascular and noncardiovascular mortality. Further studies are needed to elucidate the mechanisms behind these findings, including their potential dose dependence.