Variability of lipids in patients with Type 2 diabetes taking statin treatment: implications for target setting

Glutathione Plays a Positive Role in the Proliferation of Pinus koraiensis Embryogenic Cells

In the large-scale breeding of conifers, cultivating embryogenic cells with good proliferative capacity is crucial in the process of somatic embryogenesis. In the same cultural environment, the proliferative capacity of different cell lines is significantly different. To reveal the regulatory mechanism of proliferation in woody plant cell lines with different proliferative potential, we used Korean pine cell lines with high proliferative potential 001#-001 (Fast) and low proliferative potential 001#-010 (Slow) for analysis. A total of 17 glutathione-related differentially expressed genes was identified between F and S cell lines. A total of 893 metabolites was obtained from the two cell lines in the metabolomic studies. A total of nine metabolites related to glutathione was significantly upregulated in the F cell line compared with the S cell line. The combined analyses revealed that intracellular glutathione might be the key positive regulator mediating the difference in proliferative capacity between F and S cell lines. The qRT-PCR assay validated 11 differentially expressed genes related to glutathione metabolism. Exogenous glutathione and its synthase inhibitor L-buthionine-sulfoximine treatment assay demonstrated the positive role of glutathione in the proliferation of Korean pine embryogenic cells.

LDL cholesterol variability in patients with Type 2 diabetes taking atorvastatin and simvastatin: a comparison of two formulae for LDL-C estimation

Background

A new formula was recently proposed by Cordovo et al. that was more highly correlated with low-density lipoprotein (LDL) measured directly than the Friedewald LDL formula. We conducted this prospective study to establish whether the new formula allows true variations in LDL within the same individual to be tracked more closely than that of the Friedewald formula.

Methods

A cross-over study of biological variation of lipids in 26 patients with Type 2 diabetes (T2DM) taking either a short half-life statin, simvastatin 40 mg ( n = 10), or a long half-life statin, atorvastatin 10 mg. After three months on one statin, fasting lipids were measured on 10 occasions over a five-week period. The same procedure was then followed for the other statin. The LDL was measured by a direct LDL immunoassay and was compared to the LDL estimated by the Friedewald and Cordova (0.7516) × (total cholesterol [TC]−high-density lipoprotein cholesterol [HDL-C]) formulae.

Results

As a group, the calculated or measured mean LDL was no different between statins. However, the biological coefficient of variation (CV) of directly measured LDL was far larger with simvastatin than atorvastatin. This difference was detected by Cordova LDL but not found with the Friedewald LDL formula.

Conclusions

In contrast to Friedewald LDL, Cordova LDL estimation revealed LDL to be much more stable in T2DM patients taking atorvastatin rather than simvastatin that was in accord with LDL when measured directly. Therefore, Cordova LDL which is a measure of non-HDL-cholesterol is the simplest, cheapest and the most convenient measurement for assessment of response to statin treatment.

Biological variation of cardiovascular risk factors in patients with diabetes

Biological variation refers to the natural fluctuations found when repeated measurements are made in a biological system. Generally, biological variation remains within narrow boundaries in health, but may differ in pathological states, with implications for the diagnosis and monitoring of disease processes. In disease, biological variation may alter such that any subsequent measurement may need to have a greater difference compared with a healthy control to be biologically relevant. Treatments such as insulin or anti-hypertensive therapy have been shown to reduce biological variability closer to normal levels and theoretically this may help prevent complication development or progression in conditions such as diabetes. This article reviews how biological variation can influence our identification and assessment of vascular risk factors in a person with diabetes. The role of biological variation in the diagnosis of diabetes (glucose and HbA1c) is then examined. Finally, the influence that common treatments in diabetes have in modifying biological variation is described.

The effect of atorvastatin and simvastatin on vitamin D, oxidative stress and inflammatory marker concentrations in patients with type 2 diabetes: a crossover study

The pleiotropic effect of statins may be mediated in part through raising 25 hydroxy vitamin D (25OHD) concentrations. It has also been shown that an increase in oxidative stress and inflammatory markers are a feature of the patients with type 2 diabetes (T2DM). A cross-over study of 26 patients with T2DM taking either simvastatin 40 mg or atorvastatin 10 mg was undertaken. After 3 months on one statin, lipids, C-reactive protein (hsCRP), 25OHD and malondialdehyde (MDA) were measured repeatedly. The same procedure was then followed taking the other statin. Despite similar lipid-lowering, the mean 25OHD was higher on atorvastatin compared with simvastatin and the mean MDA and hsCRP levels lower, irrespective of which statin the patients were taking before crossover. The changes in 25OHD predicted changes in CRP and MDA levels. Thus, compared with simvastatin, atorvastatin shows apparently beneficial pleiotropic effects with respect to 25OHD concentrations as well as markers of oxidative stress and inflammation in patients with T2DM.

Metabolomics and ischaemic heart disease

Ischaemic heart disease accounts for nearly half of the global cardiovascular disease burden. Aetiologies relating to heart disease are complex, but dyslipidaemia, oxidative stress and inflammation are cardinal features. Despite preventative measures and advancements in treatment regimens with lipid-lowering agents, the high prevalence of heart disease and the residual risk of recurrent events continue to be a significant burden to the health sector and to the affected individuals and their families. The development of improved risk models for the early detection and prevention of cardiovascular events in addition to new therapeutic strategies to address this residual risk are required if we are to continue to make inroads into this most prevalent of diseases. Metabolomics and lipidomics are modern disciplines that characterize the metabolite and lipid complement respectively, of a given system. Their application to ischaemic heart disease has demonstrated utilities in population profiling, identification of multivariate biomarkers and in monitoring of therapeutic response, as well as in basic mechanistic studies. Although advances in magnetic resonance and mass spectrometry technologies have given rise to the fields of metabolomics and lipidomics, the plethora of data generated presents challenges requiring specific statistical and bioinformatics applications, together with appropriate study designs. Nonetheless, the predictive and re-classification capacity of individuals with various degrees of risk by the plasma lipidome has recently been demonstrated. In the present review, we summarize evidence derived exclusively by metabolomic and lipidomic studies in the context of ischaemic heart disease. We consider the potential role of plasma lipid profiling in assessing heart disease risk and therapeutic responses, and explore the potential mechanisms. Finally, we highlight where metabolomic studies together with complementary -omic disciplines may make further inroads into the understanding, detection and treatment of ischaemic heart disease.

Choosing targets for glycaemia, blood pressure and low-density lipoprotein cholesterol in elderly individuals with diabetes mellitus

Diabetes mellitus in the 'elderly' poses unique management challenges that contribute to conflicting priorities. Individualized management requires taking into account each patient's medical history, functional ability, home care situation, life expectancy and his/her health beliefs; individuals value trade-offs (e.g. quantity versus quality of life, and side effects as well as risks versus long-term benefits) differently. Moreover, this decision making relies on imperfect evidence. Target goals for three intermediate outcomes - glycaemic control (glycosylated haemoglobin [HbA(1c)]), blood pressure control and lipid control (low-density lipoprotein cholesterol [LDL-C]) - help keep management on track. Of these, glycaemic control is usually the most complex. Glycaemic control alleviates symptoms of hyperglycaemia and can improve micro- and macrovascular outcomes. Tight glycaemic control (HbA(1c) <7%) clearly improves microvascular outcomes. However, hypoglycaemia and polypharmacy are the main drawbacks of tight control. Factors that influence the benefits and drawbacks include age, longevity and co-morbidities, including the geriatric 'syndromes' of frailty and falls. We favour the explicit risk-stratified approach of the Department of Veterans Affairs/Department of Defense (VA/DoD) guidelines, which set HbA(1c) target ranges based on physiological age or the presence/severity of major co-morbidities and microvascular complications. There are clear benefits of blood pressure and cholesterol control (primarily reduction of macrovascular events, but also microvascular events), and their overall cost effectiveness exceeds that of glycaemic control. Issues with treatment for hypertension include potential side effects of drugs, a potential increased risk of falls and risks of polypharmacy. Nevertheless, the evidence for a blood pressure target of <140/80 mmHg is reasonably strong if it can be achieved safely. In general, we recommend use of an HMG-CoA reductase inhibitor (statin) and an LDL-C target of <100 mg/dL, especially if an individual cannot tolerate a moderate dose of a statin.

Daytime triglyceride variability in men and women with different levels of triglyceridemia

BACKGROUND

Triglyceride (TG) levels measured in either the fasting or non-fasting state predict the risk of cardiovascular disease (CVD). Since CVD risk assessment is affected by variability in TG, the aim of the study was to investigate intra-individual variability of non-fasting TG.

METHODS

Capillary triglyceride (cTG) levels were measured in 246 free-living individuals at six time-points during the day on three separate occasions. Intra-individual variability in cTG was assessed by calculating the standard deviation of three measures at each time-point. Subjects were analyzed by gender and by fasting TG level.

RESULTS

In the fasting state, intra-individual variability was similar in males and females (0.28 and 0.35 mmol/l, respectively), but increased significantly in male but not in female subjects during the day, i.e., 0.28 to 0.69, and 0.35 to 0.36 mmol/l, resp. Subjects with higher fasting TG levels had greater absolute variability in both fasting and non-fasting TG.

CONCLUSIONS

The variability in non-fasting TG is greater in males and in individuals with higher levels of TG. Since greatest variability in non-fasting TG occurs very late in the day, it is unlikely to affect the assessment of CVD risk, which is based on a blood sample taken during daylight hours.

Disparate effects of atorvastatin compared with simvastatin on C-reactive protein concentrations in patients with type 2 diabetes

OBJECTIVE

Reduction in LDL and high sensitivity (hs) C-reactive protein (CRP) are independent indicators of successful cardiovascular risk reduction with statins. This study compared the effect of equivalent LDL-lowering doses of simvastatin and atorvastatin on hsCRP in type 2 diabetic patients.

RESEARCH DESIGN AND METHODS

A crossover study of 26 patients with type 2 diabetes taking either 40 mg simvastatin or 10 mg atorvastatin was undertaken. After 3 months on one statin, lipids and hsCRP were measured on 10 occasions over a 5-week period. The same procedure was then followed taking the other statin.

RESULTS

LDL was comparable on either treatment: atorvastatin 2.2 +/- 0.2 vs. 2.1 +/- 0.3 mmol/l (mean +/- SD; P = 0.19). CRP of individuals taking atorvastatin was significantly lower than when they were taking simvastatin (median 1.08 vs. 1.47 mg/l, P = 0.0002) and was less variable (median SD of logCRP 0.0036 vs. 0.178, P = 0.0001).

CONCLUSIONS

Compared with simvastatin, atorvastatin reduced hsCRP and its variability in type 2 diabetic patients. This enhanced anti-inflammatory effect may prove beneficial if lower CRP is associated with improved cardiovascular risk.

Lipidomic analysis of variation in response to simvastatin in the Cholesterol and Pharmacogenetics Study

Statins are commonly used for reducing cardiovascular disease risk but therapeutic benefit and reductions in levels of low-density lipoprotein cholesterol (LDL-C) vary among individuals. Other effects, including reductions in C-reactive protein (CRP), also contribute to treatment response. Metabolomics provides powerful tools to map pathways implicated in variation in response to statin treatment. This could lead to mechanistic hypotheses that provide insight into the underlying basis for individual variation in drug response. Using a targeted lipidomics platform, we defined lipid changes in blood samples from the upper and lower tails of the LDL-C response distribution in the Cholesterol and Pharmacogenetics study. Metabolic changes in responders are more comprehensive than those seen in non-responders. Baseline cholesterol ester and phospholipid metabolites correlated with LDL-C response to treatment. CRP response to therapy correlated with baseline plasmalogens, lipids involved in inflammation. There was no overlap of lipids whose changes correlated with LDL-C or CRP responses to simvastatin suggesting that distinct metabolic pathways govern statin effects on these two biomarkers. Metabolic signatures could provide insights about variability in response and mechanisms of action of statins. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-010-0207-x) contains supplementary material, which is available to authorized users.

Low density lipoprotein-cholesterol variability in patients with type 2 diabetes taking atorvastatin compared to simvastatin: justification for direct measurement?

AIM

The benefit of direct, as opposed to calculated, low density lipoprotein -cholesterol (LDL-C) measurement remains unclear. This study compared the biological variability of direct LDL in patients with type 2 diabetes (T2DM) on equivalent doses of the short half-life statin, simvastatin or the longer half-life statin, atorvastatin.

METHODS

A cross-over study of biological variation of lipids in 26 patients with T2DM taking either simvastatin 40 mg (n = 10) or atorvastatin 10 mg. After 3 months on one statin, fasting lipids were measured on 10 occasions over a 5-week period. The same procedure was then followed on the other statin. The variability of LDL-C was established using a Beckman direct assay.

RESULTS

As a group, mean LDL was no different between statins (mean +/- s.d.) (1.69 +/- 0.60 mmol/l simvastatin vs. 1.67 +/- 0.60 mmol/l atorvastatin, p = 0.19). However, in all patients, the intraindividual biological variability of LDL while taking simvastatin was markedly higher than with atorvastatin (average s.d. = 0.17 mmol /l simvastatin vs. 0.01 mmol/l, p < 0.0001). Friedewald calculated LDL variability was no different between statins (average s.d. = 0.34 mmol /l simvastatin vs. 0.21 mmol/l atorvastatin, p = 0.19).

CONCLUSIONS

In contrast to calculated values, direct measurement revealed LDL to be much more stable (the s.d. being an order of magnitude) in T2DM patients taking atorvastatin rather than simvastatin. This means LDL targets can be consistently met with less lipid monitoring using atorvastatin rather than simvastatin. Direct LDL measurement may therefore have a particular role in monitoring patients on statin treatment.