Prognostic analysis of amyotrophic lateral sclerosis based on clinical features and plasma surface-enhanced Raman spectroscopy

Direct comparison of different protocols to obtain surface enhanced Raman spectra of human serum

Label-free Surface Enhanced Raman Spectroscopy (SERS) is a rapid technique that has been extensively applied in clinical diagnosis and biomedicine for the analysis of biofluids. The purpose of this approach relies on the ability to detect specific "metabolic fingerprints" of complex biological samples, but the full potential of this technique in diagnostics is yet to be exploited, mainly because of the lack of common analytical protocols for sample preparation and analysis. Variation of experimental parameters, such as substrate type, laser wavelength and sample processing can greatly influence spectral patterns, making results from different research groups difficult to compare. This study aims at making a step toward a standardization of the protocols in the analysis of human serum samples with Ag nanoparticles, by directly comparing the SERS spectra obtained from five different methods in which parameters like laser power, nanoparticle concentration, incubation/deproteinization steps and type of substrate used vary. Two protocols are the most used in the literature, and the other three are "in-house" protocols proposed by our group; all of them are employed to analyze the same human serum sample. The experimental results show that all protocols yield spectra that share the same overall spectral pattern, conveying the same biochemical information, but they significantly differ in terms of overall spectral intensity, repeatability, and preparation steps of the sample. A Principal Component Analysis (PCA) was performed revealing that protocol 3 and protocol 1 have the least variability in the dataset, while protocol 2 and 4 are the least repeatable.

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.

Subtype discrimination of acute myeloid leukemia based on plasma SERS technique

Acute myeloid leukemia (AML) is a common hematologic malignancy. To this day, diagnose of AML and its genetic mutation still rely on invasive and time-consuming methods. In this study, 222 plasma samples were collected to discuss the performance of surface-enhanced Raman spectroscopy (SERS) to discriminate AML subtype acute promyelocytic leukemia and acute monocytic leukemia based on plasma. The Ag nanoparticles-based SERS technique was used to explore the biochemical differences among different AML subtypes. With the help of powerful supervised and unsupervised algorithms, the performance using the whole spectra and band intensities was confirmed to identify different subtypes of AML. The results demonstrated the intensities of several bands and band-intensity ratios were significantly different between groups, thus related to the discrimination of several AML subtypes and control. Combining indexes of band-intensity ratios, the result of multi-indexes ROC has excellent performance in differentiating AML patient with healthy control. Our work demonstrated the great potential of SERS technique as a rapid and micro detection method in clinical laboratory field, it's a new and powerful tool for analyzing human blood plasma.

Combination of pathological and spectroscopic characterization to promote diagnosis of retinal pigment epithelium-Bruch's membrane complex in a diabetic rat model

Diabetic retinopathy (DR) is a common condition of diabetes, and approaches to detecting early DR using the unique characteristics of the retinal pigment epithelium-Bruch's membrane complex (RBC) have increasingly attracted attention. A diabetic model was established in Sprague-Dawley rats via streptozocin (STZ) injection for 1 (DM1) and 6 months (DM6), confirmed by weekly blood glucose measurement. Serum and retinal tissue-based advanced glycation endproducts (AGE) levels significantly elevated in diabetic rats, and RBC was evaluated by transmission electron microscopy and Raman spectroscopy. The results showed that whole Raman spectra and all marked band intensities could respectively achieve almost equal and accurate discrimination of all animal groups, along with the determination of important molecules from the band data. Further quantitative analyses indicated series of metabolic disturbance due to hyperglycemia were involved while the body self-regulation mechanism still played a role with different effects during the disease progression. Given this, Raman spectroscopy can reliably distinguish the early characterization of DR in addition to providing intrinsic key molecules that is sensitive to identify the early disease progression.

Serum Uric Acid Levels Predict Mortality Risk in Male Amyotrophic Lateral Sclerosis Patients

Objective: To explore the associations between serum uric acid levels with survival in male and female ALS patients. Methods: A longitudinal cohort study was carried out including 313 sporadic and 16 familial ALS patients with repeated serum uric acid measurements. Multivariate Cox regression models were used to evaluate the survival-related factors. Results: There were 207 male and 122 female, and the mean age of onset was 55.7 ± 11.2 years old. The male patients had significantly higher baseline uric acid levels than that in female patients (342.4 ± 91.4 vs. 279.3 ± 71.4 μmol/L; p < 0.0001). The uric acid levels were inversely associated with the decline rate of ALSFRS-R per month (ΔALSFRS-R). After multivariate Cox regression analysis, a survival advantage was found in male, but not female, with higher serum uric acid levels. In males, a shorter diagnostic delay (≤10 m), lower BMI at baseline (≤18.70 kg/m²), faster disease progression (ΔALSFRS-R > 0.63), and lower baseline uric acid levels (≤292 μmol/L, HR: 1.936; 95% CI: 1.334-2.810) were associated with a shorter survival. During follow-up, the serum uric acid levels were not significantly altered over time. Conclusion: There is an inverse correlation between baseline serum uric acid levels and risk of death, prominently in male ALS patients.

Median Nerve-Neurophysiological Index Correlates With the Survival of Patients With Amyotrophic Lateral Sclerosis

Objective: This study aims to explore the association between median nerve-neurophysiological index (NI) and survival of patients with amyotrophic lateral sclerosis (ALS).

Methods: A retrospective case series with a prospective follow-up study was performed in 238 patients with ALS. Their clinical profiles and NI were recorded. Kaplan-Meier curves and Cox regression were adopted to perform survival analysis.

Results: The median survival time of all ALS cases was 33.0 months. Multivariate analysis showed that older age of onset, shorter diagnostic delay, higher ΔALSFRS-R, and faster progression {NI ≤ 2.15; hazard ratio [HR] = 1.543 [95% confidence interval (CI), 1.136–2.094]} were associated with short survival. NI was correlated with ALSFRS-R at baseline (r_s = 0.3153; p < 0.0001) and ALSFRS-R at different time points of follow-up (r_s = 0.5127; p < 0.0001). The higher NI slope of decline (> 0.25) showed shorter survival compared with the lower group (≤ 0.25; 34.0 vs. 52.0 months; p = 0.0003). A predictive model was constructed based on the age of onset, diagnostic delay, median nerve NI, and ΔALSFRS-R. The higher predictive score (> 14) showed significantly shorter survival compared with the lower group (≤ 14; HR = 3.907, 95% CI, 2.857–5.342).

Conclusion: Median nerve NI and its slope of decline were predictive of survival of ALS.

Promoting identification of amyotrophic lateral sclerosis based on label-free plasma spectroscopy

Objective

Amyotrophic lateral sclerosis (ALS) is an adult‐onset fatal neurodegenerative disease which lacks identified biological markers. A label‐free plasma surface‐enhanced Raman spectroscopy (SERS) method was developed to explore a simple and noninvasive test for ALS.

Methods

ALS patients were enrolled serially and plasma samples were collected at the time of diagnosis prior to the start of ALS treatment. SERS spectra were recorded using a Renishaw micro‐Raman system.

Results

To exclude the interference by varying disease severity, we enrolled three groups of ALS patients, including ALS‐1 (n = 60; ALSFRS‐R ≥ 42 and time interval ≤ 12 months), ALS‐2 (n = 61; ALSFRS‐R < 42 and time interval ≤ 12 months), and ALS‐3 (n = 61; ALSFRS‐R ≥ 38 and time interval> 12 months). The SERS spectra were analyzed using principal component analysis (PCA), which showed that ALS‐1, ALS‐2, ALS‐3, and control groups were separated significantly. Then, decision tree (DT) models and receiver operating characteristic curves were employed and identified that bands at 722 and 739 cm⁻¹, and ratios of 635–722 cm⁻¹ and 635–739 cm⁻¹ were able to distinguish ALS from controls significantly. Finally, we highlighted six metabolism pathways correlated with ALS, including phenylalanine‐tyrosine‐tryptophan biosynthesis, aminoacyl‐tRNA biosynthesis, phenylalanine metabolism, pantothenate and CoA biosynthesis, porphyrin and chlorophyll metabolism, and pyrimidine metabolism.

Interpretation:

Plasma SERS could be a promising tool for the detection of ALS. The bands at 722 and 739 cm⁻¹, and the ratios of 635–722 cm⁻¹ and 635–739 cm⁻¹ could serve as potential indicator for ALS.

Cytological and spectroscopic characteristics of c-KIT N822K mutation in core binding factor acute myeloid leukemia cells

The frequency of N822K mutation is high in the A-loop region of c-KIT which is highly associated with poor prognosis of core binding factor acute myeloid leukemia. The current work used common assays including cell cycle, apoptosis, clone formation and western blot to perform cytological detection for HL60 (wild type), NB4 (carrying t[15;17] chromosome translocation) and Kasumi-1 (with c-KIT N822K mutation); and meanwhile, the laser tweezers Raman spectroscopy (LTRS) was also used to perform label-free detection of single living cells. The results demonstrated that Kasumi-1 cell line bearing c-KIT N822K mutation has a stable cell cycle, while there was a significant difference between early and late apoptosis within 48 hours. The LTRS detection initially reflected the spectral differences induced by genetic abnormalities and highlighted progressive patterns of DNA and amino acids band contents which were appropriately consistent with that of cell clone ratio and the c-KIT phosphorylation level. It is concluded that methodology of LTRS-based single living cell characterization could be potential and effective to reveal gene mutation-induced cell differentiation.