Biochemical characterization of atherosclerotic plaque constituents using FTIR spectroscopy and histology

Discrimination of dyslipidemia types with ATR-FTIR spectroscopy and chemometrics associated with multivariate analysis of the lipid profile, anthropometric, and pro-inflammatory biomarkers

BACKGROUND

Obesity, dyslipidemia, and low-grade inflammatory state form a triad of self-sustaining metabolic dysfunction. Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy is a simple, rapid, and non-destructive technique that generates spectral fingerprints of biomolecules that can be correlated with metabolic changes. We verified the efficiency of ATR-FTIR spectroscopy in blood plasma (n = 74) to discriminate the types of dyslipidemias and suggest metabolic inflammatory changes.

METHODS

Principal Component Analysis (PCA) was performed on the biochemical and anthropometric data to verify whether the dyslipidemia types share a similar biochemical profile plausible of discrimination in chemometric modeling. To discriminate the types of dyslipidemias based on spectral data, Orthogonal Partial Least-Squares Discriminant Analysis (OPLS-DA) was used and validated with leave-one-out cross-validation.

RESULTS

Although no significant difference was obtained between the types of dyslipidemia and normal subjects by CRP, leptin, and cfDNA, there was a significant difference between normal subjects vs combined hyperlipidemia (CH) + hypercholesterolemia (HCL) + hypertriglyceridemia (HTG) (p < 0.05) by the 1245 cm^-1 peak [ν_as(PO₂^-)] (possible indication of chronic inflammation by increased cfDNA). The area under the curve of the region between 1770 and 1720 cm^-1 was significantly increased for CH in relation to other dyslipidemias and normal subjects. Furthermore, there were significant differences for the main representative peaks of lipids, proteins, carbohydrates, and nucleic acids between the types of dyslipidemias and between the types of dyslipidemias and normal subjects. The OPLS-DA model achieved 100 % accuracy with 1 latent variable and Standard Error of Cross-Validation (SECV) < 0.004 for all types of dyslipidemia  and the control group.

CONCLUSIONS

Our results suggest that ATR-FTIR spectroscopy associated with chemometric modeling is a plausible applicant for screening the types of dyslipidemias. However, more extensive studies should be conducted to verify the real applicability in clinical analysis laboratories or medical clinics.

Label-free analytic histology of carotid atherosclerosis by mid-infrared optoacoustic microscopy

BACKGROUND AND AIMS

Analysis of atherosclerotic plaque composition is a vital tool for unraveling the pathological metabolic processes that contribute to plaque growth.

METHODS

We visualize the constitution of human carotid plaques by mid-infrared optoacoustic microscopy (MiROM), a method for label-free analytic histology that requires minimal tissue preparation, rapidly yielding large field-of-view en-face images with a resolution of a few micrometers. We imaged endarterectomy specimens (n = 3, 12 sections total) at specific vibrational modes, targeting carbohydrates, lipids and proteins. Additionally, we recorded spectra at selected tissue locations. We identified correlations in the variability in this high-dimensional data set using non-negative matrix factorization (NMF).

RESULTS

We visualized high-risk plaque features with molecular assignment. Consistent NMF components relate to different dominant tissue constituents, dominated by lipids, proteins, and cholesterol and carbohydrates respectively.

CONCLUSIONS

These results introduce MiROM as an innovative, stain-free, analytic histology technology for the biochemical characterization of complex human vascular pathology.

Colloidal Particles for Pickering Emulsion Stabilization Prepared via Antisolvent Precipitation of Lignin-Rich Cocoa Shell Extract

This study concerns the preparation and functionality testing of a new class of Pickering particles for food emulsion stabilization: colloidal lignin-rich particles (CLRPs) derived from ethanol-soluble extract of cocoa shell. A further goal was to achieve Pickering functionality without the need to add co-emulsifying surfactants during emulsion processing. Cocoa shell is a co-product of the food manufacturing industry. As such it is anticipated that the particles would be accepted as a natural food ingredient, provided no harmful solvents are used in any step of their processing. The cocoa shell particles were milled, dispersed in water and exposed to 250 °C for 1 h in a stainless-steel tubular reactor followed by ethanol extraction to obtain a lignin-rich extract (46% (w/w) lignin with the remainder predominantly lipids). CLRPs were then fabricated by the precipitation of ethanol-dissolved extract into water (antisolvent). By employing an agitated process and droplet dosing into a non-agitated process, four particle suspensions of a range of submicron diameters were obtained. All particle suspensions contained the same mass fraction of extract and were surface active, with surface tension decreasing with increasing particle size. The smallest particles were obtained when lipids were removed from the extract prior to particle processing. In contrast to the other four particle suspensions, this one failed to stabilize a 10% (w/w) sunflower oil-in-water emulsion. We hypothesize that the phospholipids indigenously present in these CLRP formulations are a critical component for Pickering functionality. It can be concluded that we have successfully introduced a new class of Pickering particles, fabricated from an industry co-product and anticipated to be food grade.

Molecular imaging of atherosclerosis: spotlight on Raman spectroscopy and surface-enhanced Raman scattering

To accurately predict atherosclerotic plaque progression, a detailed phenotype of the lesion at the molecular level is required. Here, we assess the respective merits and limitations of molecular imaging tools. Clinical imaging includes contrast-enhanced ultrasound, an inexpensive and non-toxic technique but with poor sensitivity. CT benefits from high spatial resolution but poor sensitivity coupled with an increasing radiation burden that limits multiplexing. Despite high sensitivity, positron emission tomography and single-photon emission tomography have disadvantages when applied to multiplex molecular imaging due to poor spatial resolution, signal cross talk and increasing radiation dose. In contrast, MRI is non-toxic, displays good spatial resolution but poor sensitivity. Preclinical techniques include near-infrared fluorescence (NIRF), which provides good spatial resolution and sensitivity; however, multiplexing with NIRF is limited, due to photobleaching and spectral overlap. Fourier transform infrared spectroscopy and Raman spectroscopy are label-free techniques that detect molecules based on the vibrations of chemical bonds. Both techniques offer fast acquisition times with Raman showing superior spatial resolution. Raman signals are inherently weak; however, leading to the development of surface-enhanced Raman spectroscopy (SERS) that offers greatly increased sensitivity due to using metallic nanoparticles that can be functionalised with biomolecules targeted against plaque ligands while offering high multiplexing potential. This asset combined with high spatial resolution makes SERS an exciting prospect as a diagnostic tool. The ongoing refinements of SERS technologies such as deep tissue imaging and portable systems making SERS a realistic prospect for translation to the clinic.

Mechanical, biological and structural characterization of in vitro ruptured human carotid plaque tissue

Recent experimental studies performed on human carotid plaques have focused on mechanical characterization for the purpose of developing material models for finite-element analysis without quantifying the tissue composition or relating mechanical behaviour to preoperative classification. This study characterizes the mechanical and biological properties of 25 human carotid plaques and also investigates the common features that lead to plaque rupture during mechanical testing by performing circumferential uniaxial tests, Fourier transform infrared (FTIR) and scanning electron microscopy (SEM) on each specimen to relate plaque composition to mechanical behaviour. Mechanical results revealed large variations between plaque specimen behaviour with no correlation to preoperative ultrasound prediction. However, FTIR classification demonstrated a statistically significant relationship between stress and stretch values at rupture and the level of calcification (P=0.002 and P=0.009). Energy-dispersive X-ray spectroscopy was carried out to confirm that the calcium levels observed using FTIR analysis were accurate. This work demonstrates the potential of FTIR as an alternative method to ultrasound forpredicting plaque mechanical behaviour. SEM imaging at the rupture sites of each specimen highlighted voids created by the nodes of calcifications in the tissue structure which could lead to increased vulnerability of the plaque.

Prostatic stones: evidence of a specific chemistry related to infection and presence of bacterial imprints

Prostatic stones are a common condition in older men in industrialized countries. However, aging appears not to be the unique pathogenesis of these calcifications. Our morpho-constitutional investigation of 23 stone samples suggested that infection has a significant role in the lithogenic process of prostate calcifications, even without detection of infection by clinical investigation. Most stones (83%) showed bacterial imprints and/or chemical composition, suggestive of a long-term infection process. Chronic infection may induce persistent inflammation of the tissue and secondarily, a cancerization process within a few years. Thus, the discovery of prostate calcifications by computerized tomodensitometry, for example, might warrant further investigation and management to search for chronic infection of the prostate gland.

Nanomechanical properties of calcification, fibrous tissue, and hematoma from atherosclerotic plaques

Clinical events such as heart attack and stroke can be caused by the rupture of atherosclerotic plaques in artery walls. Computational modeling is often used to better understand atherosclerotic disease progression to identify "vulnerable" plaques (i.e., those likely to rupture) and to tailor treatments according to tissue composition. However, because of the heterogeneity of plaque tissue, there are limited data available on the material properties of individual plaque constituents. The goal of this study was to use nanoindentation to measure the mechanical properties of blood clots, fibrous tissue, partially calcified fibrous tissue, and bulk calcifications from human atherosclerotic plaque tissue. Fourier transform infrared (FTIR) spectroscopy was used to quantify the amount of mineral and lipid in each tissue region tested. The results demonstrate that the stiffness of plaque tissue increases with increasing mineral content. In addition, by providing the first experimental data on atherosclerotic calcifications, these data show that some of the estimated modulus values commonly used in computational models greatly underestimate the stiffness of the fully calcified tissue.

Disease recognition by infrared and Raman spectroscopy

Infrared (IR) and Raman spectroscopy are emerging biophotonic tools to recognize various diseases. The current review gives an overview of the experimental techniques, data-classification algorithms and applications to assess soft tissues, hard tissues and body fluids. The methodology section presents the principles to combine vibrational spectroscopy with microscopy, lateral information and fiber-optic probes. A crucial step is the classification of spectral data by a variety of algorithms. We discuss unsupervised algorithms such as cluster analysis or principal component analysis and supervised algorithms such as linear discriminant analysis, soft independent modeling of class analogies, artificial neural networks support vector machines, Bayesian classification, partial least-squares regression and ensemble methods. The selected topics include tumors of epithelial tissue, brain tumors, prion diseases, bone diseases, atherosclerosis, kidney stones and gallstones, skin tumors, diabetes and osteoarthritis.

Application of multivariate data-analysis techniques to biomedical diagnostics based on mid-infrared spectroscopy

The objective of this contribution is to review the application of advanced multivariate data-analysis techniques in the field of mid-infrared (MIR) spectroscopic biomedical diagnosis. MIR spectroscopy is a powerful chemical analysis tool for detecting biomedically relevant constituents such as DNA/RNA, proteins, carbohydrates, lipids, etc., and even diseases or disease progression that may induce changes in the chemical composition or structure of biological systems including cells, tissues, and bio-fluids. However, MIR spectra of multiple constituents are usually characterized by strongly overlapping spectral features reflecting the complexity of biological samples. Consequently, MIR spectra of biological samples are frequently difficult to interpret by simple data-analysis techniques. Hence, with increasing complexity of the sample matrix more sophisticated mathematical and statistical data analysis routines are required for deconvoluting spectroscopic data and for providing useful results from information-rich spectroscopic signals. A large body of work relates to the combination of multivariate data-analysis techniques with MIR spectroscopy, and has been applied by a variety of research groups to biomedically relevant areas such as cancer detection and analysis, artery diseases, biomarkers, and other pathologies. The reported results indeed reveal a promising perspective for more widespread application of multivariate data analysis in assisting MIR spectroscopy as a screening or diagnostic tool in biomedical research and clinical studies. While the authors do not mean to ignore any relevant contributions to biomedical analysis across the entire electromagnetic spectrum, they confine the discussion in this contribution to the mid-infrared spectral range as a potentially very useful, yet underutilized frequency region. Selected representative examples without claiming completeness will demonstrate a range of biomedical diagnostic applications with particular emphasis on the advantageous interaction between multivariate data analysis and MIR spectroscopy.

Detection of pathological aortic tissues by infrared multispectral imaging and chemometrics

Processing of multispectral images is becoming an important issue, especially in terms of data mining for disease diagnosis. We report here an original image analysis procedure developed in order to compare 42 infrared multispectral images acquired on human ascending aortic healthy and pathological tissues. Each image contained about 2500 infrared absorption spectra, each composed of 1641 variables (wavenumbers). To process this large data set, we have restricted the spectral window used to the 1800-950 cm(-1) spectral range and selected 100 spectra from the aortic media, which is the most altered part of the aortic tissue in aneurysms. Prior to this selection, a spectral quality test was performed to eliminate 'bad' spectra. Our data set was first subjected to a discriminant analysis, which allowed separation of aortic tissues in two groups corresponding respectively to normal and aneurysmal states. Then a K-means analysis, based on 20 groups, allowed reconstruction of infrared images using false-colours and discriminated between pathological and healthy tissues. These results demonstrate the usefulness of such data processing methods for the analysis and comparison of a set of spectral images.

Infrared spectroscopic characterization of mineralized tissues

Vibrational spectroscopy (Infrared and Raman), and in particular micro-spectroscopy and micro-spectroscopic imaging has been used to characterize developmental changes in bone and other mineralized tissues, to monitor these changes in cell cultures, and to detect disease and drug-induced modifications. Examples of the use of infrared micro-spectroscopy and micro-spectroscopic imaging are discussed in this review.

Spectroscopic imaging of arteries and atherosclerotic plaques

Fourier transform infrared (FTIR) spectroscopic imaging using a focal plane array detector has been used to study atherosclerotic arteries with a spatial resolution of 3-4 microm, i.e., at a level that is comparable with cellular dimensions. Such high spatial resolution is made possible using a micro-attenuated total reflection (ATR) germanium objective with a high refractive index and therefore high numerical aperture. This micro-ATR approach has enabled small structures within the vessel wall to be imaged for the first time by FTIR. Structures observed include the elastic lamellae of the tunica media and a heterogeneous distribution of small clusters of cholesterol esters within an atherosclerotic lesion, which may correspond to foam cells. A macro-ATR imaging method was also applied, which involves the use of a diamond macro-ATR accessory. This study of atherosclerosis is presented as an illustrative example of the wider potential of these ATR imaging approaches for cardiovascular medicine and biomedical applications.