Surface-Enhanced Raman Spectroscopy Combined with Multivariate Analysis for Fingerprinting Clinically Similar Fibromyalgia and Long COVID Syndromes.

Fibromyalgia (FM) is a chronic central sensitivity syndrome characterized by augmented pain processing at diffuse body sites and presents as a multimorbid clinical condition. Long COVID (LC) is a heterogenous clinical syndrome that affects 10-20% of individuals following COVID-19 infection. FM and LC share similarities with regard to the pain and other clinical symptoms experienced, thereby posing a challenge for accurate diagnosis. This research explores the feasibility of using surface-enhanced Raman spectroscopy (SERS) combined with soft independent modelling of class analogies (SIMCAs) to develop classification models differentiating LC and FM. Venous blood samples were collected using two supports, dried bloodspot cards (DBS, n = 48 FM and n = 46 LC) and volumetric absorptive micro-sampling tips (VAMS, n = 39 FM and n = 39 LC). A semi-permeable membrane (10 kDa) was used to extract low molecular fraction (LMF) from the blood samples, and Raman spectra were acquired using SERS with gold nanoparticles (AuNPs). Soft independent modelling of class analogy (SIMCA) models developed with spectral data of blood samples collected in VAMS tips showed superior performance with a validation performance of 100% accuracy, sensitivity, and specificity, achieving an excellent classification accuracy of 0.86 area under the curve (AUC). Amide groups, aromatic and acidic amino acids were responsible for the discrimination patterns among FM and LC syndromes, emphasizing the findings from our previous studies. Overall, our results demonstrate the ability of AuNP SERS to identify unique metabolites that can be potentially used as spectral biomarkers to differentiate FM and LC.

Portable Mid-Infrared Spectroscopy Combined with Chemometrics to Diagnose Fibromyalgia and Other Rheumatologic Syndromes Using Rapid Volumetric Absorptive Microsampling.

The diagnostic criteria for fibromyalgia (FM) have relied heavily on subjective reports of experienced symptoms coupled with examination-based evidence of diffuse tenderness due to the lack of reliable biomarkers. Rheumatic disorders that are common causes of chronic pain such as rheumatoid arthritis, systemic lupus erythematosus, osteoarthritis, and chronic low back pain are frequently found to be comorbid with FM. As a result, this can make the diagnosis of FM more challenging. We aim to develop a reliable classification algorithm using unique spectral profiles of portable FT-MIR that can be used as a real-time point-of-care device for the screening of FM. A novel volumetric absorptive microsampling (VAMS) technique ensured sample volume accuracies and minimized the variation introduced due to hematocrit-based bias. Blood samples from 337 subjects with different disorders (179 FM, 158 non-FM) collected with VAMS were analyzed. A semi-permeable membrane filtration approach was used to extract the blood samples, and spectral data were collected using a portable FT-MIR spectrometer. The OPLS-DA algorithm enabled the classification of the spectra into their corresponding classes with 84% accuracy, 83% sensitivity, and 85% specificity. The OPLS-DA regression plot indicated that spectral regions associated with amide bands and amino acids were responsible for discrimination patterns and can be potentially used as spectral biomarkers to differentiate FM and other rheumatic diseases.

Early Diagnosis of Fibromyalgia Using Surface-Enhanced Raman Spectroscopy Combined with Chemometrics.

Fibromyalgia (FM) is a chronic muscle pain disorder that shares several clinical features with other related rheumatologic disorders. This study investigates the feasibility of using surface-enhanced Raman spectroscopy (SERS) with gold nanoparticles (AuNPs) as a fingerprinting approach to diagnose FM and other rheumatic diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), osteoarthritis (OA), and chronic low back pain (CLBP). Blood samples were obtained on protein saver cards from FM (n = 83), non-FM (n = 54), and healthy (NC, n = 9) subjects. A semi-permeable membrane filtration method was used to obtain low-molecular-weight fraction (LMF) serum of the blood samples. SERS measurement conditions were standardized to enhance the LMF signal. An OPLS-DA algorithm created using the spectral region 750 to 1720 cm-1 enabled the classification of the spectra into their corresponding FM and non-FM classes (Rcv > 0.99) with 100% accuracy, sensitivity, and specificity. The OPLS-DA regression plot indicated that spectral regions associated with amino acids were responsible for discrimination patterns and can be potentially used as spectral biomarkers to differentiate FM and other rheumatic diseases. This exploratory work suggests that the AuNP SERS method in combination with OPLS-DA analysis has great potential for the label-free diagnosis of FM.

Metabolic Fingerprinting for the Diagnosis of Clinically Similar Long COVID and Fibromyalgia Using a Portable FT-MIR Spectroscopic Combined with Chemometrics.

Post Acute Sequelae of SARS-CoV-2 infection (PASC or Long COVID) is characterized by lingering symptomatology post-initial COVID-19 illness that is often debilitating. It is seen in up to 30-40% of individuals post-infection. Patients with Long COVID (LC) suffer from dysautonomia, malaise, fatigue, and pain, amongst a multitude of other symptoms. Fibromyalgia (FM) is a chronic musculoskeletal pain disorder that often leads to functional disability and severe impairment of quality of life. LC and FM share several clinical features, including pain that often makes them indistinguishable. The aim of this study is to develop a metabolic fingerprinting approach using portable Fourier-transform mid-infrared (FT-MIR) spectroscopic techniques to diagnose clinically similar LC and FM. Blood samples were obtained from LC (n = 50) and FM (n = 50) patients and stored on conventional bloodspot protein saver cards. A semi-permeable membrane filtration approach was used to extract the blood samples, and spectral data were collected using a portable FT-MIR spectrometer. Through the deconvolution analysis of the spectral data, a distinct spectral marker at 1565 cm-1 was identified based on a statistically significant analysis, only present in FM patients. This IR band has been linked to the presence of side chains of glutamate. An OPLS-DA algorithm created using the spectral region 1500 to 1700 cm-1 enabled the classification of the spectra into their corresponding classes (Rcv > 0.96) with 100% accuracy and specificity. This high-throughput approach allows unique metabolic signatures associated with LC and FM to be identified, allowing these conditions to be distinguished and implemented for in-clinic diagnostics, which is crucial to guide future therapeutic approaches.

Rapid Biomarker-Based Diagnosis of Fibromyalgia Syndrome and Related Rheumatologic Disorders by Portable FT-IR Spectroscopic Techniques.

Fibromyalgia syndrome (FM), one of the most common illnesses that cause chronic widespread pain, continues to present significant diagnostic challenges. The objective of this study was to develop a rapid vibrational biomarker-based method for diagnosing fibromyalgia syndrome and related rheumatologic disorders (systemic lupus erythematosus (SLE), osteoarthritis (OA) and rheumatoid arthritis (RA)) through portable FT-IR techniques. Bloodspot samples were collected from patients diagnosed with FM (n = 122) and related rheumatologic disorders (n = 70), including SLE (n = 17), RA (n = 43), and OA (n = 10), and stored in conventional protein saver bloodspot cards. The blood samples were prepared by four different methods (blood aliquots, protein-precipitated extraction, and non-washed and water-washed semi-permeable membrane filtration extractions), and spectral data were collected with a portable FT-IR spectrometer. Pattern recognition analysis, OPLS-DA, was able to identify the signature profile and classify the spectra into corresponding classes (Rcv > 0.93) with excellent sensitivity and specificity. Peptide backbones and aromatic amino acids were predominant for the differentiation and might serve as candidate biomarkers for syndromes such as FM. This research evaluated the feasibility of portable FT-IR combined with chemometrics as an accurate and high-throughput tool for distinct spectral signatures of biomarkers related to the human syndrome (FM), which could allow for real-time and in-clinic diagnostics of FM.

Essential Oils and Neuropathic Pain.

Neuropathic pain is one of the most prominent chronic pain syndromes, affecting almost 10% of the United States population. While there are a variety of established pharmacologic and non-pharmacologic treatment options, including tricyclic antidepressants (TCAs), serotonin-noradrenaline reuptake inhibitors, anticonvulsants, trigger point injections, and spinal cord stimulators, many patients continue to have chronic pain or suboptimal symptom control. This has led to an increased interest in alternative solutions for neuropathic pain such as nutritional supplements and essential oils. In this review, we explore the literature on the most commonly cited essential oils, including lavender, bergamot, rosemary, nutmeg, Billy goat weed, and eucalyptus. However, the literature is limited and largely comprised of preclinical animal models and a few experimental studies, some of which were poorly designed and did not clearly isolate the effects of the essential oil treatment. Additionally, no standardized method of dosing or route of administration has been established. Further randomized control studies isolating the active components of various essential oils are needed to provide conclusive evidence on the use of essential oils for neuropathic pain. In this review, we explore the basis behind some of the essential oils of interest to patients with neuropathic pain seen in rheumatology clinics.

Nutritional Supplements for the Treatment of Neuropathic Pain.

Neuropathic pain affects 7-10% of the population and is often ineffectively and incompletely treated. Although the gold standard for treatment of neuropathic pain includes tricyclic antidepressants (TCAs), serotonin-noradrenaline reuptake inhibitors, and anticonvulsants, patients suffering from neuropathic pain are increasingly turning to nonpharmacologic treatments, including nutritional supplements for analgesia. So-called "nutraceuticals" have garnered significant interest among patients seeking to self-treat their neuropathic pain with readily available supplements. The supplements most often used by patients include vitamins such as vitamin B and vitamin D, trace minerals zinc and magnesium, and herbal remedies such as curcumin and St. John's Wort. However, evidence surrounding the efficacy and mechanisms of these supplements in neuropathic pain is limited, and the scientific literature consists primarily of preclinical animal models, case studies, and small randomized controlled trials (RCTs). Further exploration into large randomized controlled trials is needed to fully inform patients and physicians on the utility of these supplements in neuropathic pain. In this review, we explore the basis behind using several nutritional supplements commonly used by patients with neuropathic pain seen in rheumatology clinics.

Intraepidermal Nerve Fiber Density as Measured by Skin Punch Biopsy as a Marker for Small Fiber Neuropathy: Application in Patients with Fibromyalgia.

Small fiber neuropathy (SFN) is a type of peripheral neuropathy that occurs from damage to the small A-delta and C nerve fibers that results in the clinical condition known as SFN. This pathology may be the result of metabolic, toxic, immune-mediated, and/or genetic factors. Small fiber symptoms can be variable and inconsistent and therefore require an objective biomarker confirmation. Small fiber dysfunction is not typically captured by diagnostic tests for large-fiber neuropathy (nerve conduction and electromyographic study). Therefore, skin biopsies stained with PGP 9.5 are the universally recommended objective test for SFN, with quantitative sensory tests, autonomic function testing, and corneal confocal imaging as secondary or adjunctive choices. Fibromyalgia (FM) is a heterogenous syndrome that has many symptoms that overlap with those found in SFN. A growing body of research has shown approximately 40-60% of patients carrying a diagnosis of FM have evidence of SFN on skin punch biopsy. There is currently no clearly defined phenotype in FM at this time to suggest whom may or may not have SFN, though research suggests it may correlate with severe cases. The skin punch biopsy provides an objective tool for use in quantifying small fiber pathology in FM. Skin punch biopsy may also be repeated for surveillance of the disease as well as measuring response to treatments. Evaluation of SFN in FM allows for better classification of FM and guidance for patient care as well as validation for their symptoms, leading to better use of resources and outcomes.

The Search for Biomarkers in Fibromyalgia.

Fibromyalgia is the most common of the central sensitivity syndromes affecting 2-5% of the adult population in the United States. This pain amplification syndrome has enormous societal impact as measured by work absenteeism, decreased work productivity, disability and injury compensation and over-utilization of healthcare resources. Multiple studies have shown that early diagnosis of this condition can improve patient outlook and redirect valuable healthcare resources towards more appropriate targeted therapy. Efforts have been made towards improving diagnostic accuracy through updated criteria. The search for biomarkers for diagnosis and verification of Fibromyalgia is an ongoing process. Inadequacies with current diagnostic criteria for this condition have fueled these efforts for identification of a reproducible marker that can verify this disease in a highly sensitive, specific and reproducible manner. This review focuses on areas of research for biomarkers in fibromyalgia and suggests that future efforts might benefit from approaches that utilize arrays of biomarkers to identify this disorder that presents with a diverse clinical phenotype.

Vibrational Spectroscopy for Identification of Metabolites in Biologic Samples.

Vibrational spectroscopy (mid-infrared (IR) and Raman) and its fingerprinting capabilities offer rapid, high-throughput, and non-destructive analysis of a wide range of sample types producing a characteristic chemical "fingerprint" with a unique signature profile. Nuclear magnetic resonance (NMR) spectroscopy and an array of mass spectrometry (MS) techniques provide selectivity and specificity for screening metabolites, but demand costly instrumentation, complex sample pretreatment, are labor-intensive, require well-trained technicians to operate the instrumentation, and are less amenable for implementation in clinics. The potential for vibration spectroscopy techniques to be brought to the bedside gives hope for huge cost savings and potential revolutionary advances in diagnostics in the clinic. We discuss the utilization of current vibrational spectroscopy methodologies on biologic samples as an avenue towards rapid cost saving diagnostics.

Metabolomics in Central Sensitivity Syndromes.

Central sensitization syndromes are a collection of frequently painful disorders that contribute to decreased quality of life and increased risk of opiate abuse. Although these disorders cause significant morbidity, they frequently lack reliable diagnostic tests. As such, technologies that can identify key moieties in central sensitization disorders may contribute to the identification of novel therapeutic targets and more precise treatment options. The analysis of small molecules in biological samples through metabolomics has improved greatly and may be the technology needed to identify key moieties in difficult to diagnose diseases. In this review, we discuss the current state of metabolomics as it relates to central sensitization disorders. From initial literature review until Feb 2020, PubMed, Embase, and Scopus were searched for applicable studies. We included cohort studies, case series, and interventional studies of both adults and children affected by central sensitivity syndromes. The majority of metabolomic studies addressing a CSS found significantly altered metabolites that allowed for differentiation of CSS patients from healthy controls. Therefore, the published literature overwhelmingly supports the use of metabolomics in CSS. Further research into these altered metabolites and their respective metabolic pathways may provide more reliable and effective therapeutics for these syndromes.

Metabolic fingerprinting for diagnosis of fibromyalgia and other rheumatologic disorders.

Diagnosis and treatment of fibromyalgia (FM) remains a challenge owing to the lack of reliable biomarkers. Our objective was to develop a rapid biomarker-based method for diagnosing FM by using vibrational spectroscopy to differentiate patients with FM from those with rheumatoid arthritis (RA), osteoarthritis (OA), or systemic lupus erythematosus (SLE) and to identify metabolites associated with these differences. Blood samples were collected from patients with a diagnosis of FM (n = 50), RA (n = 29), OA (n = 19), or SLE (n = 23). Bloodspot samples were prepared, and spectra collected with portable FT-IR and FT-Raman microspectroscopy and subjected to metabolomics analysis by ultra-HPLC (uHPLC), coupled to a photodiode array (PDA) and tandem MS/MS. Unique IR and Raman spectral signatures were identified by pattern recognition analysis and clustered all study participants into classes (FM, RA, and SLE) with no misclassifications (p < 0.05, and interclass distances > 2.5). Furthermore, the spectra correlated (r = 0.95 and 0.83 for IR and Raman, respectively) with FM pain severity measured with fibromyalgia impact questionnaire revised version (FIQR) assessments. Protein backbones and pyridine-carboxylic acids dominated this discrimination and might serve as biomarkers for syndromes such as FM. uHPLC-PDA-MS/MS provided insights into metabolites significantly differing among the disease groups, not only in molecular m/z+ and m/z- values but also in UV-visible chromatograms. We conclude that vibrational spectroscopy may provide a reliable diagnostic test for differentiating FM from other disorders and for establishing serologic biomarkers of FM-associated pain.

Fibromyalgia syndrome and small fiber, early or mild sensory polyneuropathy.

INTRODUCTION: Pain mechanisms in fibromyalgia syndrome (FMS) are not clearly understood. Growing evidence appears to suggest a role for small fiber polyneuropathy (SFPN) in some FMS patients, as measured by epidermal nerve fiber density (ENFD). We aimed to better characterize and distinguish the subset of patients with both fibromyalgia and small fiber, early or mild sensory polyneuropathy (FM-SFSPN). METHODS: 155 FMS patients with neuropathic symptoms completed a Short Form McGill Questionnaire and visual analog scale in addition to having skin biopsies, nerve conduction studies (NCS), and serologic testing. RESULTS: Sural and medial plantar (MP) response amplitudes correlated with ENFD, with markers of metabolic syndrome being more prevalent in this subset of patients. Pain intensity and quality did not distinguish patients. DISCUSSION: The FM-SFSPN subset of patients may be identified through sural and MP sensory NCS and/or skin biopsy but cannot be identified by pain features and intensity. Muscle Nerve 58: 625-630, 2018.

A group-mediated physical activity intervention in older knee osteoarthritis patients: effects on social cognitive outcomes.

The objective of the present study was to compare a group-mediated cognitive behavioral (GMCB) physical activity intervention with traditional exercise therapy (TRAD) upon select social cognitive outcomes in sedentary knee osteoarthritis (knee OA) patients. A total of 80 patients (mean age = 63.5 years; 84% women) were recruited using clinic and community-based strategies to a 12-month, single-blind, two-arm, randomized controlled trial. Mobility-related self-efficacy, self-regulatory self-efficacy (SRSE), and satisfaction with physical function (SPF) were assessed at baseline, 3, and 12 months. Results of intent-to-treat 2 (Treatment: GMCB and TRAD) × 2 (Time: 3 and 12 month) analyses of covariance yielded significantly greater increases in SRSE and SPF (P < 0.01) relative to TRAD. Partial correlations revealed that changes in SRSE and SPF were significantly related (P < 0.05) to improvements in physical activity and mobility at 3 and 12-months. The GMCB intervention yielded more favorable effects on important social cognitive outcomes than TRAD; these effects were related to improvements in physical activity and mobility.

A pilot study of health and wellness coaching for fibromyalgia.

BACKGROUND: The purpose of this study was to test the hypothesis that a health and wellness coaching (HWC)-based intervention for fibromyalgia (FM) would result in sustained improvements in health and quality of life, and reductions in health care utilization. METHODS: Nine female subjects meeting American College of Rheumatology criteria for a diagnosis of primary FM were studied. The HWC protocol had two components, which were delivered telephonically over a twelve-month period. First, each patient met individually with a coach during the 12 month study at the patient's preference of schedule and frequency (Range:22-32 × 45-min sessions). Coaches were health professionals trained in health and wellness coaching tasks, knowledge, and skills. Second, each patient participated in bimonthly (first six months) and monthly (second six months) group classes on self-coaching strategies during the 12 month study. Prior to the intervention, and after 6 months and 12 months of coaching, the Revised Fibromyalgia Impact Questionnaire (FIQR) was used to measure health and quality of life, and the Brief Pain Inventory-Short Form (BPI) was used to measure pain intensity and interference with function. Total and rheumatology-related health encounters were documented using electronic medical records. Data were analyzed using repeated measures ANOVA. RESULTS: All nine patients finished the HWC protocol. FIQR scores improved by 35 % (P = 0.001). BPI scores decreased by 32 % overall (P = 0.006), 31 % for severity (P = 0.02), and 44 % for interference (P = 0.006). Health care utilization declined by 86 % (P = 0.006) for total and 78 % (P < 0.0001) for rheumatology-related encounters. CONCLUSION: The HWC program added to standard FM therapy produced clinically significant improvements in quality of life measures (FIQR), pain (BPI), and marked reductions in health care utilization. Such improvements do not typically occur spontaneously in FM patients, suggesting that HWC deserves further consideration as an intervention for FM.

Group-mediated physical activity promotion and mobility in sedentary patients with knee osteoarthritis: results from the IMPACT-pilot trial.

OBJECTIVE: To compare the effects of a group-mediated cognitive behavioral exercise intervention (GMCB) with traditional center-based exercise therapy (TRAD) on objectively assessed levels of physical activity (PA) and mobility in sedentary patients with knee osteoarthritis (OA). METHODS: The Improving Maintenance of Physical Activity in Knee Osteoarthritis Trial-Pilot (IMPACT-P) was a 12-month, 2-arm, single-blind, randomized controlled pilot study designed to compare the effects of GMCB and TRAD on 80 sedentary patients with knee OA with self-reported difficulty in daily activities [mean age 63.5 yrs, 84% women, mean body mass index (BMI) 32.7 kg/m(2)]. Objective assessments of PA (LIFECORDER Plus Accelerometer) and mobility (400-m walk) were obtained at baseline, 3 months, and 12 months by study personnel blinded to participants' treatment assignment. RESULTS: Intent to treat 2 (treatment: GMCB and TRAD) × 2 (time: 3 mos and 12 mos) analyses of covariance of controlling for baseline, age, sex, and BMI-adjusted change in the outcomes demonstrated that the GMCB intervention yielded significantly greater increases in PA (p < 0.01) and a nonsignificant yet more favorable improvement in mobility (p = 0.09) relative to TRAD. Partial correlation analyses also revealed that change in PA was significantly correlated with the 400-m walk performance at 3-month (r = -0.51, p < 0.01) and 12-month (r = -0.40, p < 0.01) followup assessments. CONCLUSION: Findings from the IMPACT-P trial suggest that the GMCB treatment resulted in significantly greater improvement in PA and nonsignificant yet more favorable change in mobility relative to TRAD.

Weight status and differences in mobility performance, pain symptoms, and physical activity in older, knee osteoarthritis patients.

Knee osteoarthritis (OA) is a leading cause of functional disability among American adults. Obesity is a strong independent risk factor for OA. While research emphasizes the role of obesity in the OA-physical function relationship, the extent to which weight status impacts salient physical, health, and pain measures in older, knee OA patients is not well delineated. The primary aim of this study was to assess differences in mobility performance (stair climb and 400-meter walk), mobility-related self-efficacy, pain symptoms (WOMAC), and measures of accelerometer-determined physical activity (PA) as a function of weight status. Analysis of covariance was conducted to examine differences on the dependent variables. Obese class III patients were outperformed by their counterparts on nearly every measure of mobility, mobility-related self-efficacy, and the assessment of pain symptoms. These outcomes did not differ among other weight comparisons. Normal weight subjects outperformed classes I, II, and III counterparts on most measures of PA (engagement in moderate or greater PA and total weekly steps). Additionally, overweight participants outperformed obese class II participants and obese class I participants outperformed obese classes II and III participants on total weekly steps. Collectively, these findings underscore the meaningful differences observed in relevant OA outcomes as a function of increasing levels of body weight.

A bloodspot-based diagnostic test for fibromyalgia syndrome and related disorders.

The aim of this study was to investigate the ability of a rapid biomarker-based method for diagnosis of fibromyalgia syndrome (FM) using mid-infrared microspectroscopy (IRMS) to differentiate patients with FM from those with osteoarthritis (OA) and rheumatoid arthritis (RA), and to identify molecular species associated with the spectral patterns. Under IRB approval, blood samples were collected from patients diagnosed with FM (n = 14), RA (n = 15), or OA (n = 12). Samples were prepared, placed onto a highly reflective slide, and spectra were collected using IRMS. Spectra were analyzed using multivariate statistical modeling to differentiate groups. Aliquots of samples also were subjected to metabolomic analysis. IRMS separated subjects into classes based on spectral information with no misclassifications among FM and RA or OA patients. Interclass distances of 15.4 (FM vs. RA), 14.7 (FM vs. OA) and 2.5 (RA vs. OA) among subjects, demonstrating the ability of IRMS to achieve reliable resolution of unique spectral patterns specific to FM. Metabolomic analysis revealed that RA and OA groups were metabolically similar, whereas biochemical differences were identified in the FM that were quite distinctive from those found in the other two groups. Both IRMS and metabolomic analysis identified changes in tryptophan catabolism pathway that differentiated patients with FM from those with RA or OA.