Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Beta-cell function is associated with carotid intima-media thickness independently of insulin resistance in healthy individuals

International audienceOBJECTIVE: It is a common belief that early atherosclerosis in prediabetes is causally linked to endothelial insulin resistance. Another condition, a low insulin secretion, may be associated with insufficient insulin action on the vascular wall and consequently favor atherosclerosis. Our aim was to test this hypothesis in people without diabetes, taking into account the gold-standard measurement of insulin sensitivity, a major confounder in the relationship between insulin secretion and atherosclerosis. METHODS: We studied the European Relationship between Insulin Sensitivity and Cardiovascular Risk cohort of 451 men and 593 women (44 ± 8 years, mean ± SD) who were free of diabetes, hypertension, dyslipidemia, and other known chronic or acute conditions. All underwent an oral glucose tolerance test, a euglycemic-hyperinsulinemic clamp (M/I measured insulin sensitivity), and B-mode carotid ultrasound. RESULTS: Intima-media thickness (IMT) in the common carotid artery was negatively associated with insulin secretion indexes, with Spearman partial correlation coefficients: -0.09, -0.08, -0.06 for respectively, the disposition index, the early insulin response and the beta cell glucose sensitivity, after adjusting for established factors, including clamp-measured insulin sensitivity (all P \textless 0.05). For quartiles 1 (lowest) to 4 of the disposition index, the covariate-adjusted geometric means of IMT (mm) were 0.605 (95% confidence interval: 0.596-0.614), 0.596 (0.587-0.605), 0.597 (0.587-0.606), and 0.586 (0.577-0.596) (Ptrend = 0.004). Similar results were found for the two other surrogate measures of insulin secretion. No interaction with sex was observed. CONCLUSION: Insulin secretion was associated with early carotid atherosclerosis in nondiabetic individuals, independently of other risk factors, including insulin sensitivity measured by the gold-standard metho

Influence of warming on soil water potential controls seedling mortality in perennial but not annual species in a temperate grassland

In a water-limited system, the following hypotheses are proposed: warming will increase seedling mortality; elevated atmospheric CO2 will reduce seedling mortality by reducing transpiration, thereby increasing soil water availability; and longevity (i.e. whether a species is annual or perennial) will affect the response of a species to global changes. Here, these three hypotheses are tested by assessing the impact of elevated CO2 (550 μmol mol-1) and warming (+2°C) on seedling emergence, survivorship and establishment in an Australian temperate grassland from autumn 2004 to autumn 2007. Warming impacts on seedling survivorship were dependent upon species longevity. Warming reduced seedling survivorship of perennials through its effects on soil water potential but the seedling survivorship of annuals was reduced to a greater extent than could be accounted for by treatment effects on soil water potential. Elevated CO2 did not significantly affect seedling survivorship in annuals or perennials. These results show that warming will alter recruitment of perennial species by changing soil water potential but will reduce recruitment of annual species independent of any effects on soil moisture. The results also show that exposure to elevated CO2 does not make seedlings more resistant to dry soils

Plasma proteomic signatures of a direct measure of insulin sensitivity in two population cohorts

International audienceAims/hypothesis: The euglycaemic–hyperinsulinaemic clamp (EIC) is the reference standard for the measurement of whole-body insulin sensitivity but is laborious and expensive to perform. We aimed to assess the incremental value of high-throughput plasma proteomic profiling in developing signatures correlating with the M value derived from the EIC. Methods: We measured 828 proteins in the fasting plasma of 966 participants from the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study and 745 participants from the Uppsala Longitudinal Study of Adult Men (ULSAM) using a high-throughput proximity extension assay. We used the least absolute shrinkage and selection operator (LASSO) approach using clinical variables and protein measures as features. Models were tested within and across cohorts. Our primary model performance metric was the proportion of the M value variance explained (R 2). Results: A standard LASSO model incorporating 53 proteins in addition to routinely available clinical variables increased the M value R 2 from 0.237 (95% CI 0.178, 0.303) to 0.456 (0.372, 0.536) in RISC. A similar pattern was observed in ULSAM, in which the M value R 2 increased from 0.443 (0.360, 0.530) to 0.632 (0.569, 0.698) with the addition of 61 proteins. Models trained in one cohort and tested in the other also demonstrated significant improvements in R 2 despite differences in baseline cohort characteristics and clamp methodology (RISC to ULSAM: 0.491 [0.433, 0.539] for 51 proteins; ULSAM to RISC: 0.369 [0.331, 0.416] for 67 proteins). A randomised LASSO and stability selection algorithm selected only two proteins per cohort (three unique proteins), which improved R 2 but to a lesser degree than in standard LASSO models: 0.352 (0.266, 0.439) in RISC and 0.495 (0.404, 0.585) in ULSAM. Reductions in improvements of R 2 with randomised LASSO and stability selection were less marked in cross-cohort analyses (RISC to ULSAM R 2 0.444 [0.391, 0.497]; ULSAM to RISC R 2 0.348 [0.300, 0.396]). Models of proteins alone were as effective as models that included both clinical variables and proteins using either standard or randomised LASSO. The single most consistently selected protein across all analyses and models was IGF-binding protein 2. Conclusions/interpretation: A plasma proteomic signature identified using a standard LASSO approach improves the cross-sectional estimation of the M value over routine clinical variables. However, a small subset of these proteins identified using a stability selection algorithm affords much of this improvement, especially when considering cross-cohort analyses. Our approach provides opportunities to improve the identification of insulin-resistant individuals at risk of insulin resistance-related adverse health consequences. Graphical Abstract: [Figure not available: see fulltext.]

Gamma-glutamyltransferase, arterial remodeling and prehypertension in a healthy population at low cardiometabolic risk

International audiencePlasma gamma-glutamyltransferase (GGT) was suggested to reflect the level of systemic oxidative stress. Oxidative stress induces changes in arterial structure and function and contributes to the development of hypertension. Therefore, GGT may be associated with arterial remodeling and blood pressure (BP) increment, even in absence of disease. To test this hypothesis, we evaluated, in 825 healthy subjects at low cardiometabolic risk, the associations of plasma GGT with carotid artery intima-media thickness (IMT), luminal diameter and prehypertension; in 154 subjects was evaluated also the association with aortic stiffness (cfPWV). Associations were controlled for insulin sensitivity, C-reactive protein, and life-style habits. In the main population, BP was remeasured after 3 years. Carotid diameter and cfPWV, but not IMT, were directly and independently related to plasma GGT. Subjects with prehypertension (N = 330) had higher GGT as compared with subjects with normal BP (22 [14] vs 17 [11] IU/L; adjusted P = 0.001), and within prehypertensive subjects, those who developed hypertension during 3 years had higher GGT than those without incident hypertension (27 [16] vs 21 [14] IU/L; adjusted P < 0.05). Within subjects with arterial stiffness measurement, those with prehypertension (N = 79) had higher both GGT and arterial stiffness (25 [14] vs 16 [20] IU/L and 9.11 ± 1.24 vs 7.90 ± 0.94 m/s; adjusted P < 0.01 and <0.05). In the view of previous evidence linking plasma GGT concentration to the level of systemic oxidative stress, our findings suggest a role of oxidative stress in subclinical arterial damage and in prehypertension, even in healthy subjects free of cardiometabolic risk. Arterial organ damage may represent the link between GGT and hypertension

Coronal Heating as Determined by the Solar Flare Frequency Distribution Obtained by Aggregating Case Studies

Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counter-intuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfv\'en waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold, $\alpha=2$ as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed $>$600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: pre-flare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine that $\alpha = 1.63 \pm 0.03$. This is below the critical threshold, suggesting that Alfv\'en waves are an important driver of coronal heating.Comment: 1,002 authors, 14 pages, 4 figures, 3 tables, published by The Astrophysical Journal on 2023-05-09, volume 948, page 7