Clinical Relevance of Nuclear Magnetic Resonance LipoProfile

Dyslipidemias in multiple sclerosis

PURPOSE

To investigate the frequency of dyslipidemia phenotypes in multiple sclerosis and to assess the associations with lipoprotein particle size distributions.

METHODS

This cross-sectional study included 203 healthy controls (HC), 221 relapsing-remitting MS (RRMS), and 126 progressive MS (PMS). A lipid profile with total cholesterol, high-density lipoprotein cholesterol (HDL-C), triglycerides, and apolipoprotein B levels were measured. Low density lipoprotein cholesterol (LDL-C), very low-density lipoprotein cholesterol, large buoyant LDL-C and small dense LDL-C were calculated using the Sampson-NIH equations method. Dyslipidemia phenotypes were categorized by their nonHDL-C and triglyceride values. The diameters and concentrations of triglyceride-rich lipoprotein particles (TRLP), LDL particles (LDLP), and HDL particles (HDLP) were measured with proton NMR lipoprotein profiling. Serum proprotein convertase subtilisin/kexin type 9 (PCSK9) levels were obtained using immunoassay.

RESULTS

The frequencies of normolipidemia, and various dyslipidemia phenotypes were similar in HC, RRMS, and PMS. The size of the TRLP, very large TRLP, large TRLP, and small LDLP concentrations had a decreasing pattern of HC>RR>PMS. The lowest tertile of EDSS was associated with higher concentrations of HDLP and small HDLP in PMS. PCSK9 was associated with concentration of HDL particles, primarily via its effects on the concentration of small HDL particles.

CONCLUSIONS

There were no differences in the frequency of dyslipidemias in MS compared to healthy controls. Higher HDLP concentrations are associated with lower disability in PMS.

Nuclear-Magnetic-Resonance-Spectroscopy-Derived Serum Biomarkers of Metabolic Vulnerability Are Associated with Disability and Neurodegeneration in Multiple Sclerosis

PURPOSE

Metabolic vulnerabilities can exacerbate inflammatory injury and inhibit repair in multiple sclerosis (MS). The purpose was to evaluate whether blood biomarkers of inflammatory and metabolic vulnerability are associated with MS disability and neurodegeneration.

METHODS

Proton nuclear magnetic resonance spectra were obtained from serum samples from 153 healthy controls, 187 relapsing-remitting, and 91 progressive MS patients. The spectra were analyzed to obtain concentrations of lipoprotein sub-classes, glycated acute-phase proteins, and small-molecule metabolites, including leucine, valine, isoleucine, alanine, and citrate. Composite indices for inflammatory vulnerability, metabolic malnutrition, and metabolic vulnerability were computed. MS disability was measured on the Expanded Disability Status Scale. MRI measures of lesions and whole-brain and tissue-specific volumes were acquired.

RESULTS

Valine, leucine, isoleucine, alanine, the Inflammatory Vulnerability Index, the Metabolic Malnutrition Index, and the Metabolic Vulnerability Index differed between healthy control and MS groups in regression analyses adjusted for age, sex, and body mass index. The Expanded Disability Status Scale was associated with small HDL particle levels, inflammatory vulnerability, and metabolic vulnerability. Timed ambulation was associated with inflammatory vulnerability and metabolic vulnerability. Greater metabolic vulnerability and inflammatory vulnerability were associated with lower gray matter, deep gray matter volumes, and greater lateral ventricle volume.

CONCLUSIONS

Serum-biomarker-derived indices of inflammatory and metabolic vulnerability are associated with disability and neurodegeneration in MS.

Plasma Biomarker Profiles for Premature and Nonpremature Coronary Heart Disease in Women

BACKGROUND

Premature coronary heart disease (CHD) is a major cause of death in women. We aimed to characterize biomarker profiles of women who developed CHD before and after age 65 years.

METHODS

In the Women's Health Study (median follow-up 21.5 years), women were grouped by age and timing of incident CHD: baseline age <65 years with premature CHD by age 65 years (25 042 women; 447 events) and baseline age ≥65 years with nonpremature CHD (2982 women; 351 events). Associations of 44 baseline plasma biomarkers measured using standard assays and a nuclear magnetic resonance (NMR)-metabolomics assay were analyzed using Cox models adjusted for clinical risk factors.

RESULTS

Twelve biomarkers showed associations only with premature CHD and included lipoprotein(a), which was associated with premature CHD [adjusted hazard ratio (HR) per SD: 1.29 (95% CI 1.17-1.42)] but not with nonpremature CHD [1.09(0.98-1.22)](Pinteraction = 0.02). NMR-measured lipoprotein insulin resistance was associated with the highest risk of premature CHD [1.92 (1.52-2.42)] but was not associated with nonpremature CHD (Pinteraction <0.001). Eleven biomarkers showed stronger associations with premature vs nonpremature CHD, including apolipoprotein B. Nine NMR biomarkers showed no association with premature or nonpremature CHD, whereas 12 biomarkers showed similar significant associations with premature and nonpremature CHD, respectively, including low-density lipoprotein (LDL) cholesterol [1.30(1.20-1.45) and 1.22(1.10-1.35)] and C-reactive protein [1.34(1.19-1.50) and 1.25(1.08-1.44)].

CONCLUSIONS

In women, a profile of 12 biomarkers was selectively associated with premature CHD, driven by lipoprotein(a) and insulin-resistant atherogenic dyslipoproteinemia. This has implications for the development of biomarker panels to screen for premature CHD.

Serum lipoprotein subfractions are associated with the periodontal status: Results from the population-based cohort SHIP-TREND

AIM

To investigate the medium-term associations of serum protein subfractions derived from proton nuclear magnetic resonance (1 H-NMR) spectroscopy with periodontitis and tooth loss.

MATERIALS AND METHODS

A total of 3031 participants of the cohort Study of Health in Pomerania (SHIP-TREND) were included. In addition to conventional serum testing, serum lipoprotein contents and subfractions were analysed by 1 H-NMR spectroscopy. Confounder-adjusted associations of lipoprotein variables with periodontitis and the number of missing teeth variables were analysed using mixed-effects models with random intercepts for time across individuals, accounting for multiple testing.

RESULTS

While only spurious associations between lipoprotein levels from conventional blood tests were found-that is, triglycerides were associated with mean clinical attachment level (CAL) and low-density lipoprotein cholesterol/high-density lipoprotein cholesterol (LDL-C/HDL-C) ratio with the number of missing teeth - several associations emerged from serum lipoprotein subfractions derived from 1 H-NMR analysis. Specifically, elevated LDL triglycerides were associated with higher levels of mean probing depth (PD), mean CALs, and increased odds of having <20 teeth. HDL-4 cholesterol levels were inversely associated with mean PD. Systemic inflammation (C-reactive protein) might mediate the effects of LDL and HDL triglyceride contents on periodontitis severity.

CONCLUSIONS

Several associations between serum lipoprotein subfractions and periodontitis were observed. As the underlying biochemical mechanisms remain unclear, further research is needed.

Fingerprinting and profiling in metabolomics of biosamples

This review focuses on metabolomics from an NMR point of view. It attempts to cover the broad scope of metabolomics and describes the NMR experiments that are most suitable for each sample type. It is addressed not only to NMR specialists, but to all researchers who wish to approach metabolomics with a clear idea of what they wish to achieve but not necessarily with a deep knowledge of NMR. For this reason, some technical parts may seem a bit naïve to the experts. The review starts by describing standard metabolomics procedures, which imply the use of a dedicated 600 MHz instrument and of four properly standardized 1D experiments. Standardization is a must if one wants to directly compare NMR results obtained in different labs. A brief mention is also made of standardized pre-analytical procedures, which are even more essential. Attention is paid to the distinction between fingerprinting and profiling, and the advantages and disadvantages of fingerprinting are clarified. This aspect is often not fully appreciated. Then profiling, and the associated problems of signal assignment and quantitation, are discussed. We also describe less conventional approaches, such as the use of different magnetic fields, the use of signal enhancement techniques to increase sensitivity, and the potential of field-shuttling NMR. A few examples of biomedical applications are also given, again with the focus on NMR techniques that are most suitable to achieve each particular goal, including a description of the most common heteronuclear experiments. Finally, the growing applications of metabolomics to foodstuffs are described.

The association between triglyceride-rich lipoproteins, circulating leukocytes, and low-grade inflammation: The Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

BACKGROUND

Experimental studies have linked triglyceride-rich lipoproteins (TRLs) to inflammation, but the extent of this phenomenon in vivo has not been completely elucidated.

OBJECTIVE

We investigated the association between TRL subparticles and inflammatory markers (circulating leukocytes, plasma high-sensitivity C-reactive protein [hs-CRP], and GlycA) in the general population.

METHODS

This was a cross-sectional analysis of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). TRLs (number of particles per unit volume) and GlycA were measured by nuclear magnetic resonance spectroscopy. The association between TRLs and inflammatory markers was determined by multiple linear regression models adjusted for demographic data, metabolic conditions, and lifestyle factors. Standardized regression coefficients (beta) with 95% confidence intervals are reported.

RESULTS

The study population comprised 4,001 individuals (54% females, age 50 ± 9 years). TRLs, especially medium and large subparticles, were associated with GlycA (beta 0.202 [0.168, 0.235], p<0.001 for total TRLs). There was no association between TRLs and hs-CRP (beta 0.022 [-0.011, 0.056], p = 0.190). Medium, large, and very large TRLs were associated with leukocytes, with stronger connections with neutrophils and lymphocytes than monocytes. When TRL subclasses were analyzed as the proportion of the total pool of TRL particles, medium and large TRLs were positively related to leukocytes and GlycA, whereas smaller particles were inversely associated.

CONCLUSIONS

There are different patterns of association between TRL subparticles and inflammatory markers. The findings support the hypothesis that TRLs (especially medium and larger subparticles) may induce a low-grade inflammatory environment that involves leukocyte activation and is captured by GlycA, but not hs-CRP.