Mika Ala-Korpela

1H NMR metabonomics approach to the disease continuum of diabetic complications and premature death

Subtle metabolic changes precede and accompany chronic vascular complications, which are the primary causes of premature death in diabetes. To obtain a multimetabolite characterization of these high‐risk individuals, we measured proton nuclear magnetic resonance (1H NMR) data from the serum of 613 patients with type I diabetes and a diverse spread of complications. We developed a new metabonomics framework to visualize and interpret the data and to link the metabolic profiles to the underlying diagnostic and biochemical variables. Our results indicate complex interactions between diabetic kidney disease, insulin resistance and the metabolic syndrome. We illustrate how a single 1H NMR protocol is able to identify the polydiagnostic metabolite manifold of type I diabetes and how its alterations translate to clinical phenotypes, clustering of micro‐ and macrovascular complications, and mortality during several years of follow‐up. This work demonstrates the diffuse nature of complex vascular diseases and the limitations of single diagnostic biomarkers. However, it also promises cost‐effective solutions through high‐throughput analytics and advanced computational methods, as applied here in a case that is representative of the real clinical situation.

Modified LDL - trigger of atherosclerosis and inflammation in the arterial intima.

Abstract. Pentikäinen MO, Öörni K, Ala‐Korpela M, Kovanen PT (Wihuri Research Institute, Helsinki, Finland). Modified LDL – trigger of atherosclerosis and inflammation in the arterial intima (Minisymposium). J Intern Med 2000; 247: 359–370.

A multi-metabolite analysis of serum by 1H NMR spectroscopy: early systemic signs of Alzheimer's disease.

A three-molecular-window approach for (1)H NMR spectroscopy of serum is presented to obtain specific molecular data on lipoproteins, various low-molecular-weight metabolites, and individual lipid molecules together with their degree of (poly)(un)saturation. The multiple data were analysed with self-organising maps, illustrating the strength of the approach as a holistic metabonomics framework in solely data-driven metabolic phenotyping. We studied 180 serum samples of which 30% were related to mild cognitive impairment (MCI), a neuropsychological diagnosis with severely increased risk for Alzheimers disease (AD). The results underline the association between MCI and the metabolic syndrome (MetS). Additionally, the low relativeamount of omega-3 fatty acids appears more indicative of MCI than low serum omega-3 or polyunsaturated fatty acid concentration as such. The analyses also feature the role of elevated glycoproteins in the risk for AD, supporting the view that coexistence of inflammation and the MetS forms a high risk condition for cognitive decline.

Metabolic Phenotypes, Vascular Complications and Premature Deaths in a Population of 4,197 Patients with Type 1 Diabetes

OBJECTIVE—Poor glycemic control, elevated triglycerides, and albuminuria are associated with vascular complications in diabetes. However, few studies have investigated combined associations between metabolic markers, diabetic kidney disease, retinopathy, hypertension, obesity, and mortality. Here, the goal was to reveal previously undetected association patterns between clinical diagnoses and biochemistry in the FinnDiane dataset. RESEARCH DESIGN AND METHODS—At baseline, clinical records, serum, and 24-h urine samples of 2,173 men and 2,024 women with type 1 diabetes were collected. The data were analyzed by the self-organizing map, which is an unsupervised pattern recognition algorithm that produces a two-dimensional layout of the patients based on their multivariate biochemical profiles. At follow-up, the results were compared against all-cause mortality during 6.5 years (295 deaths). RESULTS—The highest mortality was associated with advanced kidney disease. Other risk factors included 1) a profile of insulin resistance, abdominal obesity, high cholesterol, triglycerides, and low HDL2 cholesterol, and 2) high adiponectin and high LDL cholesterol for older patients. The highest population-adjusted risk of death was 10.1-fold (95% CI 7.3–13.1) for men and 10.7-fold (7.9–13.7) for women. Nonsignificant risk was observed for a profile with good glycemic control and high HDL2 cholesterol and for a low cholesterol profile with a short diabetes duration. CONCLUSIONS—The self-organizing map analysis enabled detailed risk estimates, described the associations between known risk factors and complications, and uncovered statistical patterns difficult to detect by classical methods. The results also suggest that diabetes per se, without an adverse metabolic phenotype, does not contribute to increased mortality.

Diagnosing diabetic nephropathy by 1H NMR metabonomics of serum

AbstractObject: The most severe complication of type 1 diabetes (T1DM) is diabetic nephropathy. It is associated with a high risk of cardiovascular complications and premature death and requires early detection to be efficiently treated. The clinical practice to diagnose diabetic nephropathy is also a non-optimal and tedious set up based on albumin excretion rate in multiple overnight or 24h urine samples. Conversely, in this study, these independent diagnostic data are used to provide a realistic testing case for applying 1H NMR metabonomics of serum in a diagnostic fashion.n Materials and Methods: 182 T1DM and 21 non-diabetic (non-T1DM) individuals were studied. The 1H NMR of serum at 500xa0MHz was targeted at two molecular windows: lipoprotein lipids and low-molecular-weight metabolites.n Results: T1DM and non-T1DM individuals were exclusively separated by 1H NMR. For diabetic nephropathy diagnosis in the T1DM patients, 1H NMR data (and clinical biochemistry data) gave a sensitivity of 87.1% (83.9%) and a specificity of 87.7% (95.9%). The predictive values of positive and negative tests were 89.0% (95.5%) and 83.6% (79.2%), respectively.n Conclusions: 1H NMR metabonomics clearly distinguishes metabolic characteristics of T1DM and appears approximately as good a means to diagnose diabetic nephropathy from serum as an advanced set of biochemical variables.

Potential role of body fluid 1H NMR metabonomics as a prognostic and diagnostic tool

This review briefly handles the use of 1H NMR spectroscopy in lipoprotein subclass analytics. Potential diagnostic uses of 1H NMR metabonomics of human serum for coronary heart disease, diabetic nephropathy and cancer are also discussed. In addition, miscellaneous recent applications of NMR metabonomics (e.g., a pharmacometabonomic tactic to personalize drug treatment) as well as multi-organ, multispecies and multi-omics approaches to molecular systems biology are featured. Some related experimental and data analysis methodologies are briefly introduced with respect to the biochemical rationales. Critical considerations on the potential diagnostic value of in vitro1H NMR are presented together with optimism toward the usage of body fluid 1H NMR metabonomics in disease risk assessment and as an aid for personalized medicine.

A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic data

BackgroundA key challenge in metabonomics is to uncover quantitative associations between multidimensional spectroscopic data and biochemical measures used for disease risk assessment and diagnostics. Here we focus on clinically relevant estimation of lipoprotein lipids by 1H NMR spectroscopy of serum.ResultsA Bayesian methodology, with a biochemical motivation, is presented for a real 1H NMR metabonomics data set of 75 serum samples. Lipoprotein lipid concentrations were independently obtained for these samples via ultracentrifugation and specific biochemical assays. The Bayesian models were constructed by Markov chain Monte Carlo (MCMC) and they showed remarkably good quantitative performance, the predictive R-values being 0.985 for the very low density lipoprotein triglycerides (VLDL-TG), 0.787 for the intermediate, 0.943 for the low, and 0.933 for the high density lipoprotein cholesterol (IDL-C, LDL-C and HDL-C, respectively). The modelling produced a kernel-based reformulation of the data, the parameters of which coincided with the well-known biochemical characteristics of the 1H NMR spectra; particularly for VLDL-TG and HDL-C the Bayesian methodology was able to clearly identify the most characteristic resonances within the heavily overlapping information in the spectra. For IDL-C and LDL-C the resulting model kernels were more complex than those for VLDL-TG and HDL-C, probably reflecting the severe overlap of the IDL and LDL resonances in the 1H NMR spectra.ConclusionThe systematic use of Bayesian MCMC analysis is computationally demanding. Nevertheless, the combination of high-quality quantification and the biochemical rationale of the resulting models is expected to be useful in the field of metabonomics.

Monitoring of gliomas in vivo by diffusion MRI and 1H MRS during gene therapy‐induced apoptosis: interrelationships between water diffusion and mobile lipids

The measurement of water diffusion by diffusion‐weighted MRI (DWI) in vivo offers a non‐invasive method for assessing tissue responses to anti‐cancer therapies. The pathway of cell death after anti‐cancer treatment is often apoptosis, which leads to accumulation of mobile lipids detectable by 1H MRS in vivo. However, it is not known how these discrete MR markers of cell death relate to each other. In a rodent tumour model [i.e. ganciclovir‐treated herpes simplex thymidine kinase (HSV‐tk) gene‐transfected BT4C gliomas], we studied the interrelationships between water diffusion (Trace{D}) and mobile lipids during apoptosis. Water diffusion and water‐referenced concentrations of mobile lipids showed clearly increasing and interconnected trends during treatment. Of the accumulating 1H MRS‐visible lipids, the fatty acid uf8ffCHuf8feCHuf8ff groups and cholesterol compounds showed the strongest associations with water diffusion (r2u2009=u20090.30; Pu2009<u20090.05 and r2u2009=u20090.48; Pu2009<u20090.01, respectively). These results indicate that the tumour histopathology and apoptotic processes during tumour shrinkage can be interrelated in vivo by DWI of tissue water and 1H MRS of mobile lipids, respectively. However, there is considerable individual variation in the associations, particularly at the end of the treatment period, and in the relative compositions of the accumulating NMR‐visible lipids. The findings suggest that the assessment of individual treatment response in vivo may benefit from combining DWI and 1H MRS. Absolute and relative changes in mobile lipids may indicate initiation of tumour shrinkage even when changes in tissue water diffusion are still small. Conversely, greatly increased water diffusion probably indicates that substantial cell decomposition has taken place in the tumour tissue when the 1H MRS resonances of mobile lipids alone can no longer give a reliable estimate of tissue conditions. Copyright

Reconsideration of hydrophobic lipid distributions in lipoprotein particles.

Lipoprotein particles are commonly known as micellar aggregates with hydrophobic lipids located within the core and amphipathic molecules in the surface. Using a new structural model for optimizing the distribution of hydrophobic lipids, namely triglyceride (TG) and cholesterol ester (CE) molecules, we reveal that particle size-dependent proportion of these core lipids may locate in the surface of lipoprotein particles. The composition of the particles also strongly influences the actual molecular content of the surface. For example, in high-density lipoprotein (HDL) particles the percentage of CEs of all surface lipids is between 13% and 27% due to the high tendency of CEs to locate in the surface and the high concentration of CEs in the particles. Conversely, although the percentage of TG molecules in the surface of HDL particles is also high, approximately 60% as for CE, the percentage of TGs of all surface lipids is low, only up to 5%, because HDL particles have a low-TG concentration. These structural models provide an intuitive and coherent structural rationale for various metabolic cascades in lipoprotein metabolism with the catalytic enzyme action and molecular binding for transport proteins taking place at the surface of the particles.

Estimation of VLDL, IDL, LDL, HDL2, apoA-I, and apoB from the Friedewald inputs—apoB and IDL, but not LDL, are associated with mortality in type 1 diabetes

Background. There is an unmet need for a straightforward and cost-effective assessment of multiple lipoprotein risk factors for vascular diseases. Aims. 1) To study the relation of various lipoprotein lipid and apolipoprotein (apo) measures on the Friedewald inputs, i.e. plasma triglycerides (TG), cholesterol (TC), and high-density lipoprotein cholesterol (HDL-C). 2) To build up regression models for the appropriate measures based solely on the Friedewald inputs. Methods. Data were available for 1,775 plasma samples, from which very-low-density lipoprotein (VLDL), intermediate-density lipoprotein (IDL), low-density lipoprotein (LDL), and HDL were also isolated by ultracentrifugation. For HDL2-C and apolipoproteins, 343 and 247 samples were available, respectively. Results. Accurate models were obtained for VLDL-TG (cross-validation r=0.98), LDL-C (r=0.91), HDL2-C (r=0.92), apoA-I (r=0.92), and apoB (r=0.95). A semi-quantitative model was obtained for IDL-C (r=0.78). Due to the anticipated role of IDL-C in atherosclerosis, it was still kept within the accepted models and pursued further. The associations of the estimates with premature deaths were studied in 4,084 patients with type 1 diabetes. The associations of IDL-C and LDL-C were markedly different, the best predictors of mortality being apoB, apoB to apoA-I ratio, and IDL-C. Conclusions. The new models allow identification of clinically relevant lipoprotein profiles with no added cost to the conventional Friedewald formula.