Modelling impacts of drivers on biodiversity and ecosystems

Purpose of this chapter: Explores key issues in modelling impacts of changes in direct drivers on biodiversity and ecosystems; and critically reviews major types of models for generating outputs that are either directly relevant to assessment and decision-support activities, or are required as inputs to subsequent modelling of nature’s benefits to people. Key findings: 1-Models of biodiversity and ecosystem function are critical to our capability to predict and understand responses to environmental change; 2- There is a need to match biodiversity and ecosystem function model development to stakeholder and policy needs; 3- Biodiversity and ecosystem modelling depends heavily on our understanding of ecosystem structure, function and process and on their adequate representation in models; 4- Uncertainty in ecosystem dynamics is inherent in ecosystem modelling.EEA Santa CruzFil: Brotons, Lluís. InForest jru. Creaf-Ctfc; EspañaFil: Christensen, Villy. The University of British Columbia; Canadá.Fil: Ravindranath, N. H. India Center for Sustainable Technologies. Indian Institute of Science; India.Fil: Cao, Mingchang. Keqiang Zhao; China.Fil: Chun, Jung Hwa. National Institute of Forest Science, Division of Forest Ecology; Corea del SurFil: Maury, Olivier. Institut de Recherche pour le Développement (IRD); Francia.Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Proença, Vânia. Instituto Superior Tecnico - UNIU Lisboa; Portugal.Fil: Salihoglu, Baris. Middle East Technical University. Institute of Marine Sciences; Turquí

Association Between Patient Sex and Familial Hypercholesterolemia and Long-Term Cardiovascular Risk Factor Management 5 Years After Acute Coronary Syndrome.

BACKGROUND Long-term control of cardiovascular risk factors after acute coronary syndrome (ACS) is the cornerstone for preventing recurrence. We investigated the extent of cardiovascular risk factor management in males and females with and without familial hypercholesterolemia (FH) 5 years after ACS. METHODS We studied patients hospitalized for ACS between 2009 and 2017 in a Swiss multicenter prospective cohort study. FH was defined based on clinical criteria from the Dutch Lipid Clinic Network and Simon Broome definitions. Five years post-ACS, we assessed low-density lipoprotein-cholesterol (LDL-c) levels, lipid-lowering therapy (LLT), and other cardiovascular risk factors, comparing males to females with and without FH using generalized estimating equations. RESULTS A total of 3139 patients were included; mean age was 61.4 years (SD, 12.1), 620 (19.8%) were female, and 747 (23.5%) had possible FH. Compared with males at 5-years post-ACS, females were more likely to not use statins (odds ratio, 1.61 [95% CI, 1.28-2.03]) and less likely to have combination LLT (odds ratio, 0.72 [95% CI, 0.55-0.93]), without difference between patients with FH and without FH. Females in both FH and non-FH groups less frequently reached LDL-c values ≤1.8 mmol/L (odds ratio, 0.78 [95% CI, 0.78-0.93]). Overall, patients with FH were more frequently on high-dose statins compared with patients without FH (51.0% versus 42.9%; P=0.001) and presented more frequently with a combination of 2 or more LLT compared with patients without FH (33.8% versus 17.7%; P<0.001), but less frequently reached LDL-c targets of ≤1.8 mmol/L (33.5% versus 44.3%; P<0.001) or ≤2.6 mmol/L (70.2% versus 78.1%; P=0.001). CONCLUSIONS Five years after ACS, females had less intensive LLT and were less likely to reach target LDL-c levels than males, regardless of FH status. Males and females with FH had less optimal control of LDL-c despite more frequently taking high-dose statins or combination LLT compared with patients without FH. Long-term management of patients with ACS and FH, especially females, warrants optimization

CCN family member 1 (CCN1) is an early marker of infarct size and left ventricular dysfunction in STEMI patients

BACKGROUND AND AIMS CCN family member 1 (CCN1) has recently been proposed as a novel biomarker of myocardial injury, improving prediction of 30-day and one-year mortality following acute coronary syndromes. Among ST-elevation myocardial infarction (STEMI) patients, we evaluated the utility of CCN1 measured immediately before primary percutaneous coronary intervention (PPCI) as a predictor of two earlier endpoints: final myocardial infarct size and post-infarction left ventricular ejection fraction (LVEF). Furthermore, we evaluated the impact of CCN1 on the discriminatory power of the CADILLAC score. METHODS STEMI patients were obtained from the SPUM-ACS cohort. Serum CCN1 was measured prior to PPCI. Linear regression assessed the association between CCN1, peak creatinine kinase (CK), and post-infarction LVEF. Cox models assessed an association between CCN1 and 30-day all-cause mortality. RESULTS CCN1 was measured in 989 patients with a median value of 706.2 ng/l (IQR 434.3-1319.6). A significant correlation between CCN1, myocardial infarct size (peak CK) and LVEF was observed in univariate and multivariate analysis (both p < 0.001). Even among patients with normal classical cardiac biomarker levels at the time of PPCI, CCN1 correlated significantly with final infarct size. CCN1 significantly improved prediction of 30-day all-cause mortality by the CADILLAC score (C-index 0.864, likelihood-ratio chi-square test statistic 6.331, p = 0.012; IDI 0.026, p= 0.050). CONCLUSIONS Compared with classical cardiac biomarkers, CCN1 is potentially the earliest predictor of final myocardial infarct size and post-infarction LVEF. CCN1 improved the discriminatory capacity of the CADILLAC score suggesting a potential role in the very-early risk stratification of STEMI patients

CCN family member 1 (CCN1) is an early marker of infarct size and left ventricular dysfunction in STEMI patients.

BACKGROUND AND AIMS CCN family member 1 (CCN1) has recently been proposed as a novel biomarker of myocardial injury, improving prediction of 30-day and one-year mortality following acute coronary syndromes. Among ST-elevation myocardial infarction (STEMI) patients, we evaluated the utility of CCN1 measured immediately before primary percutaneous coronary intervention (PPCI) as a predictor of two earlier endpoints: final myocardial infarct size and post-infarction left ventricular ejection fraction (LVEF). Furthermore, we evaluated the impact of CCN1 on the discriminatory power of the CADILLAC score. METHODS STEMI patients were obtained from the SPUM-ACS cohort. Serum CCN1 was measured prior to PPCI. Linear regression assessed the association between CCN1, peak creatinine kinase (CK), and post-infarction LVEF. Cox models assessed an association between CCN1 and 30-day all-cause mortality. RESULTS CCN1 was measured in 989 patients with a median value of 706.2 ng/l (IQR 434.3-1319.6). A significant correlation between CCN1, myocardial infarct size (peak CK) and LVEF was observed in univariate and multivariate analysis (both p < 0.001). Even among patients with normal classical cardiac biomarker levels at the time of PPCI, CCN1 correlated significantly with final infarct size. CCN1 significantly improved prediction of 30-day all-cause mortality by the CADILLAC score (C-index 0.864, likelihood-ratio chi-square test statistic 6.331, p = 0.012; IDI 0.026, p= 0.050). CONCLUSIONS Compared with classical cardiac biomarkers, CCN1 is potentially the earliest predictor of final myocardial infarct size and post-infarction LVEF. CCN1 improved the discriminatory capacity of the CADILLAC score suggesting a potential role in the very-early risk stratification of STEMI patients

Smoking cessation and depression after acute coronary syndrome.

Smoking and depression are risk factors for acute coronary syndrome (ACS) that often co-exist. We investigated the evolution of depression according to smoking cessation one-year after ACS. Data from 1822 ACS patients of the Swiss multicenter SPUM-ACS cohort study were analyzed over a one-year follow-up. Participants were classified in three groups based on smoking status one-year post-ACS - continuous smokers, smokers who quit within the year, and non-smokers. Depression status at baseline and one-year was assessed with the Center for Epidemiologic Studies Depression scale (CES-D) and antidepressant drug use. A CES-D score ≥ 16 defined depression. A multivariate-adjusted logistic regression model was used to calculate odds ratios (OR) between groups. The study sample mean age was 62.4 years and females represented 20.8%. At baseline, 22.6% were depressed, 40.9% were smokers, and 47.5% of these quit smoking over the year post-ACS. In comparison to depressed continuous smokers, depressed smokers who quit had an adjusted OR 2.59 (95% confidence interval (CI) 1.27-5.25) of going below a CES-D score of 16 or not using antidepressants. New depression at one-year was found in 24.4% of non-depressed smokers who quit, and in 27.1% of non-depressed continuous smokers, with an adjusted OR 0.85 (95% CI 0.55-1.29) of moving to a CES-D score of ≥16 or using antidepressants. In conclusion, smokers with depression at time of ACS who quit smoking improved their depression more frequently compared to continuous smokers. The incidence of new depression among smokers who quit after ACS was similar compared to continuous smokers

Prevalence and management of familial hypercholesterolaemia in patients with acute coronary syndromes

Aims We aimed to assess the prevalence and management of clinical familial hypercholesterolaemia (FH) among patients with acute coronary syndrome (ACS). Methods and results We studied 4778 patients with ACS from a multi-centre cohort study in Switzerland. Based on personal and familial history of premature cardiovascular disease and LDL-cholesterol levels, two validated algorithms for diagnosis of clinical FH were used: the Dutch Lipid Clinic Network algorithm to assess possible (score 3-5 points) or probable/definite FH (>5 points), and the Simon Broome Register algorithm to assess possible FH. At the time of hospitalization for ACS, 1.6% had probable/definite FH [95% confidence interval (CI) 1.3-2.0%, n = 78] and 17.8% possible FH (95% CI 16.8-18.9%, n = 852), respectively, according to the Dutch Lipid Clinic algorithm. The Simon Broome algorithm identified 5.4% (95% CI 4.8-6.1%, n = 259) patients with possible FH. Among 1451 young patients with premature ACS, the Dutch Lipid Clinic algorithm identified 70 (4.8%, 95% CI 3.8-6.1%) patients with probable/definite FH, and 684 (47.1%, 95% CI 44.6-49.7%) patients had possible FH. Excluding patients with secondary causes of dyslipidaemia such as alcohol consumption, acute renal failure, or hyperglycaemia did not change prevalence. One year after ACS, among 69 survivors with probable/definite FH and available follow-up information, 64.7% were using high-dose statins, 69.0% had decreased LDL-cholesterol from at least 50, and 4.6% had LDL-cholesterol ≤1.8 mmol/L. Conclusion A phenotypic diagnosis of possible FH is common in patients hospitalized with ACS, particularly among those with premature ACS. Optimizing long-term lipid treatment of patients with FH after ACS is require

Prognosis of cardiovascular and non-cardiovascular multimorbidity after acute coronary syndrome.

OBJECTIVE To examine the prognosis of patients with cardiovascular and non-cardiovascular multimorbidity after acute coronary syndrome compared to patients without prior multimorbidity. METHODS This multicenter prospective cohort study in Switzerland included 5,635 patients hospitalized with acute coronary syndrome between 2009 and 2014, with a one-year follow-up period. We defined cardiovascular and non-cardiovascular multimorbidity as having at least two prior comorbidities before the index hospitalization. Multivariable adjusted Cox proportional models were built to assess the one-year risk of recurrent cardiovascular events, defined as cardiovascular mortality and non-fatal myocardial infarction or stroke. The final model was adjusted for age, gender, body mass index, tobacco consumption, education, and family history of cardiovascular disease, prescription of high-dose statinsat discharge and use of cardiac rehabilitation after discharge. RESULTS Overall, 3,664 patients (65%) had no multimorbidity, 1,839 (33%) had cardiovascular multimorbidity, 62 (1%) had non-cardiovascular multimorbidity, and 70 (1%) had both cardiovascular and non-cardiovascular multimorbidity. The multivariate risk of recurrent cardiovascular events was increased among patients with cardiovascular multimorbidity (hazard ratio (HR) 2.05, 95% CI: 1.54-2.73, p<0.001) and patients with non-cardiovascular multimorbidity (HR 2.57, 95% CI: 1.04-6.35, p = 0.04) compared to patients without multimorbidity. Patients with cardiovascular and non-cardiovascular multimorbidity had the highest risk of recurrence with a HR of 5.19, 95% CI: 2.79-9.64, p<0.001, compared to patients without multimorbidity. CONCLUSIONS Multimorbidity increased by two-fold the risk of cardiovascular events over the year after an acute coronary syndrome. The magnitude of this increased risk was similar for patients with cardiovascular or non-cardiovascular multimorbidity

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis

Overexpression of the Mitochondrial T3 Receptor p43 Induces a Shift in Skeletal Muscle Fiber Types

In previous studies, we have characterized a new hormonal pathway involving a mitochondrial T3 receptor (p43) acting as a mitochondrial transcription factor and consequently stimulating mitochondrial activity and mitochondrial biogenesis. We have established the involvement of this T3 pathway in the regulation of in vitro myoblast differentiation.We have generated mice overexpressing p43 under control of the human α-skeletal actin promoter. In agreement with the previous characterization of this promoter, northern-blot and western-blot experiments confirmed that after birth p43 was specifically overexpressed in skeletal muscle. As expected from in vitro studies, in 2-month old mice, p43 overexpression increased mitochondrial genes expression and mitochondrial biogenesis as attested by the increase of mitochondrial mass and mt-DNA copy number. In addition, transgenic mice had a body temperature 0.8°C higher than control ones and displayed lower plasma triiodothyronine levels. Skeletal muscles of transgenic mice were redder than wild-type animals suggesting an increased oxidative metabolism. In line with this observation, in gastrocnemius, we recorded a strong increase in cytochrome oxidase activity and in mitochondrial respiration. Moreover, we observed that p43 drives the formation of oxidative fibers: in soleus muscle, where MyHC IIa fibers were partly replaced by type I fibers; in gastrocnemius muscle, we found an increase in MyHC IIa and IIx expression associated with a reduction in the number of glycolytic fibers type IIb. In addition, we found that PGC-1α and PPARδ, two major regulators of muscle phenotype were up regulated in p43 transgenic mice suggesting that these proteins could be downstream targets of mitochondrial activity. These data indicate that the direct mitochondrial T3 pathway is deeply involved in the acquisition of contractile and metabolic features of muscle fibers in particular by regulating PGC-1α and PPARδ