a targeted metabolomic approach in two German prospective cohorts

Metabolomic approaches in prospective cohorts may offer a unique snapshot into early metabolic perturbations that are associated with a higher risk of cardiovascular diseases (CVD) in healthy people. We investigated the association of 105 serum metabolites, including acylcarnitines, amino acids, phospholipids and hexose, with risk of myocardial infarction (MI) and ischemic stroke in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam (27,548 adults) and Heidelberg (25,540 adults) cohorts. Using case-cohort designs, we measured metabolites among individuals who were free of CVD and diabetes at blood draw but developed MI (n = 204 and n = 228) or stroke (n = 147 and n = 121) during follow-up (mean, 7.8 and 7.3 years) and among randomly drawn subcohorts (n = 2214 and n = 770). We used Cox regression analysis and combined results using meta-analysis. Independent of classical CVD risk factors, ten metabolites were associated with risk of MI in both cohorts, including sphingomyelins, diacyl-phosphatidylcholines and acyl-alkyl- phosphatidylcholines with pooled relative risks in the range of 1.21–1.40 per one standard deviation increase in metabolite concentrations. The metabolites showed positive correlations with total- and LDL-cholesterol (r ranged from 0.13 to 0.57). When additionally adjusting for total-, LDL- and HDL- cholesterol, triglycerides and C-reactive protein, acyl-alkyl- phosphatidylcholine C36:3 and diacyl-phosphatidylcholines C38:3 and C40:4 remained associated with risk of MI. When added to classical CVD risk models these metabolites further improved CVD prediction (c-statistics increased from 0.8365 to 0.8384 in EPIC-Potsdam and from 0.8344 to 0.8378 in EPIC- Heidelberg). None of the metabolites was consistently associated with stroke risk. Alterations in sphingomyelin and phosphatidylcholine metabolism, and particularly metabolites of the arachidonic acid pathway are independently associated with risk of MI in healthy adults

Assessing mesh convergence in discrete-fracture simulations that use random meshes

A pervasive fracturing process is one in which a multitude of cracks are dynamically active, propagating in arbitrary directions, coalescing, and branching. Pervasive fracturing is a highly nonlinear process involving complex material constitutive behavior, postpeak material softening, localization, new surface generation, and ubiquitous contact. A popular computational method for modeling pervasive fracture processes is to only allow fractures to propagate along interelement edges within a predefined finite-element mesh. With this approach, to avoid nonobjectivity in the simulation results, it is necessary to use a random mesh that has no preferred orientation. To define mesh convergence, simulation results are viewed in a weak or probabilistic sense rather than at the level of a single realization. For random variables, there are a number of different modes in which convergence may be understood. These are almost sure convergence, convergence in probability, and convergence in distribution. Each mode of convergence may be stronger or weaker than another. Herein, the fracture convergence assessment is based on demonstrating empirically the mode of convergence in distribution. Specifically, a sequence of cumulative distribution functions is verified to converge in the L∞ norm. The effect of finite sample sizes is quantified using confidence levels from the Kolmogorov–Smirnov statistic. This statistical method and convergence assessment is independent of the underlying distribution

Obesity as risk factor for subtypes of breast cancer: results from a prospective cohort study

Background: Earlier epidemiological studies indicate that associations between obesity and breast cancer risk may not only depend on menopausal status and use of exogenous hormones, but might also differ by tumor subtype. Here, we evaluated whether obesity is differentially associated with the risk of breast tumor subtypes, as defined by 6 immunohistochemical markers (ER, PR, HER2, Ki67, Bcl-2 and p53, separately and combined), in the prospective EPIC-Germany Study (n = 27,012). Methods: Formalin-fixed and paraffin-embedded (FFPE) tumor tissues of 657 incident breast cancer cases were used for histopathological analyses. Associations between BMI and breast cancer risk across subtypes were evaluated by multivariable Cox regression models stratified by menopausal status and hormone therapy (HT) use. Results: Among postmenopausal non-users of HT, higher BMI was significantly associated with an increased risk of less aggressive, i.e. ER+, PR+, HER2-, Ki67low, Bcl-2+ and p53- tumors (HR per 5 kg/m2: 1.44 [1.10, 1.90], p = 0.009), but not with risk of more aggressive tumor subtypes. Among postmenopausal users of HT, BMI was significantly inversely associated with less aggressive tumors (HR per 5 kg/m2: 0.68 [0.50, 0.94], p = 0.018). Finally, among pre- and perimenopausal women, Cox regression models did not reveal significant linear associations between BMI and risk of any tumor subtype, although analyses by BMI tertiles showed a significantly lower risk of less aggressive tumors for women in the highest tertile (HR: 0.55 [0.33, 0.93]). Conclusion: Overall, our results suggest that obesity is related to risk of breast tumors with lower aggressiveness, a finding that requires replication in larger-scale analyses of pooled prospective data

Anthropometric and blood parameters for the prediction of NAFLD among overweight and obese adults

Backround: Non-alcoholic fatty liver disease (NAFLD) comprises non-progressive steatosis and non-alcoholic steatohepatitis (NASH), the latter of which may cause cirrhosis and hepatocellular carcinoma (HCC). As NAFLD detection is imperative for the prevention of its complications, we evaluated whether a combination of blood-based biomarkers and anthropometric parameters can be used to predict NAFLD among overweight and obese adults. Methods: 143 overweight or obese non-smokers free of diabetes (50% women, age: 35–65 years) were recruited. Anthropometric indices and routine biomarkers of metabolism and liver function were measured to predict magnetic resonance (MR) - derived NAFLD by multivariable logistic regression models. In addition, we evaluated to which degree the use of more novel biomarkers (adiponectin, leptin, resistin, C-reactive protein, TNF-α, IL-6, IL-8 and interferon-γ) could improve prediction models. Results: NAFLD was best predicted by a combination of age, sex, waist circumference, ALT, HbA1c, and HOMA-IR at an area under the receiver operating characteristic curve (AUROC) of 0.87 (95% CI: 0.81, 0.93) before and 0.85 (95% CI: 0.78, 0.91) after internal bootstrap validation. The use of additional biomarkers of inflammation and metabolism did not improve NAFLD prediction. Previously published indices predicted NAFLD at AUROCs between 0.71 and 0.82. Conclusions: The AUROC of > 0.8 obtained by our regression model suggests the feasibility of a non-invasive detection of NAFLD by anthropometry and circulating biomarkers, even though further increments in the capacity of prediction models may be needed before NAFLD indices can be applied in routine clinical practice

Circulating prolactin and in situ breast cancer risk in the European EPIC cohort: a case-control study

Introduction: The relationship between circulating prolactin and invasive breast cancer has been investigated previously, but the association between prolactin levels and in situ breast cancer risk has received less attention. Methods: We analysed the relationship between pre-diagnostic prolactin levels and the risk of in situ breast cancer overall, and by menopausal status and use of postmenopausal hormone therapy (HT) at blood donation. Conditional logistic regression was used to assess this association in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, including 307 in situ breast cancer cases and their matched control subjects. Results: We found a significant positive association between higher circulating prolactin levels and risk of in situ breast cancer among all women [pre-and postmenopausal combined, ORlog2 = 1.35 (95% CI 1.04-1.76), P-trend = 0.03]. No statistically significant heterogeneity was found between prolactin levels and in situ cancer risk by menopausal status (P-het = 0.98) or baseline HT use (P-het = 0.20), although the observed association was more pronounced among postmenopausal women using HT compared to non-users (P-trend = 0.06 vs P-trend = 0.35). In subgroup analyses, the observed positive association was strongest in women diagnosed with in situ breast tumors = 4 years after blood donation (P-trend = 0.01 vs P-trend = 0.63; P-het = 0.04) and among nulliparous women compared to parous women (P-trend = 0.03 vs P-trend = 0.15; P-het = 0.07). Conclusions: Our data extends prior research linking prolactin and invasive breast cancer to the outcome of in situ breast tumours and shows that higher circulating prolactin is associated with increased risk of in situ breast cancer. The relationship between circulating prolactin and invasive breast cancer has been investigated previously, but the association between prolactin levels and in situ breast cancer risk has received less attention

Risk and Predictive Factors for Liver Cancer : Analysis of Data from a Cohort Study

The association between the risk of liver cancer and blood chemistry was investigated in a cohort study with 95,150 men and women from two counties in Sweden. In 1963-65, blood tests and physical measurements were undertaken. All individuals were then followed up until 2007, and a total of 312 were diagnosed with liver cancer. Using survival analysis and logistic regression, significant risk factors were identified. Stepwise Cox proportional hazards regression applied to a main effect model revealed that Glutamic Pyruvate Transaminase (GPT) and Thymol Turbidity (TYM) were the most significant risk factors (p<0.0001), followed by Protein-Bound Hexoses (HEX)  (p=0.002), sex (p=0.02), and Serum Iron (p= 0.03). Increasing the level of GPT expressed in U/L from normal (<21) to slightly elevated (21, 31) or substantially elevated (>31) raised the hazard of experiencing liver cancer by a factor of 1.45 and 4.09, respectively. In addition, GPT was found to be the most significant risk factor in almost all age groups among both men and women. However, there was no evidence that elevated GPT levels within the normal range (<21), influenced the risk of liver cancer. Additional subgroup analyses revealed that TYM was highly significant within the group with normal GPT, and a high level of HEX (≥134 mg/dl) increased the hazard 1.55 times in comparison with the lowest HEX group (<115 mg/dl). BMI was significant only in the male subgroup  (p<0.01) and, in the obesity group, the hazard of experiencing liver cancer was 1.99 times higher than in the normal BMI group. A significant three-way interaction between GPT, BMI and gender was present (p=0.05) with a robust significant two-way interaction between GPT and BMI (p<0.01) in the male subgroup

Intra-individual variation of plasma trimethylamine-N-oxide (TMAO), betaine and choline over 1 year

BACKGROUND Circulating trimethylamine-N-oxide (TMAO) has been implicated in the development of cardiovascular and chronic kidney diseases (CKD). However, while higher TMAO levels have been associated with increased risks of cardiovascular or renal events in first prospective studies, it remained unclear how much plasma TMAO concentrations vary over time. METHODS We measured fasting plasma levels of TMAO and two of its precursors, betaine and choline by LC-MS, in two samples of 100 participants of the European Investigation into Cancer and Nutrition (EPIC)-Heidelberg study (age range: 47-80 years, 50% female) that were collected 1 year apart, and assessed their intra-individual variation by Spearman's correlation coefficients (ρ). RESULTS Correlations of metabolite concentrations over 1 year were at ρ=0.29 (p=0.003) for TMAO, ρ=0.81 (p<0.001) for betaine, and ρ=0.61 (p<0.001) for choline. Plasma levels of TMAO were not significantly associated with food intake, lifestyle factors, or routine biochemistry parameters such as C-reactive protein (CRP), low-density lipoprotein (LDL)-cholesterol, or creatinine. CONCLUSIONS In contrast to fasting plasma concentrations of betaine and choline, concentrations of TMAO were more strongly affected by intra-individual variation over 1 year in adults from the general population. The modest correlation of TMAO levels over time should be considered when interpreting associations between TMAO levels and disease endpoints

Essai sur le rôle respectif de la déduction et de l'induction dans les principaux systèmes d'interprétation du droit civil français : thèse pour le doctorat... présentée... / par Nguyen Huy Man,... ; Université de Paris, Faculté de droit

Contient une table des matièresAvec mode text