Evaluation of Dried Blood Spot Sampling for Clinical Metabolomics: Effects of Different Papers and Sample Storage Stability

Use of dried blood spots in the detection of coronavirus disease 2019 (COVID-19): A systematic review

INTRODUCTION

COVID-19 disease continues to be a global health concern. The current protocol for detecting SARS-CoV-2 requires healthcare professionals to draw blood from patients. Recent studies showed that dried blood spot (DBS) is a valuable sampling procedure that can collect a low blood volume without the need for the presence of medical practitioners. This study synthesized the available literature on using DBS as a blood collection tool to diagnose COVID-19 disease.

MATERIALS AND METHODS

A comprehensive search utilizing OVID, CINAHL, and Scopus databases was done from inception to March 2023. Five reviewers collected, extracted and organized the study data.

RESULTS

This systematic review included 57 articles. DBS was commonly prepared by finger pricking. Most studies showed more favorable results and longer sample stability (more than 1080 days) with lower storage temperature conditions for the DBS. DBS samples were mostly used for serological assays for COVID-19 disease detection. ELISA was the most used detection method (43.66 %). Diagnostic performance of laboratory tests for COVID-19 using DBS sample showed high sensitivity of up to 100 % for immunoassay tests and 100 % specificity in agglutination, PCR, and DELFIA assays.

CONCLUSION

DBS sampling coupled with serological testing can be an alternative method for collecting blood and detecting COVID-19 disease. These tests using DBS samples showed excellent diagnostic performance across various geographic locations and demographics.

Differences in bile acid profiles between cholestatic diseases - Development of a high throughput assay for dried bloodspots

BACKGROUND

Cholestasis causes accumulation of bile acids (BAs) and changes the circulating bile acid profile. Quantification of circulating BAs in dried bloodspots (DBS) may demonstrate obstruction of bile flow and altered bile acid metabolism in the liver. High sample throughput enables rapid screening of cholestatic diseases.

MATERIALS AND METHODS

Ultra high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) was used for optimizing separation and detection of the primary unconjugated BAs cholic acid (CA) and chenodeoxycholic acid (CDCA); the secondary unconjugated BAs ursodeoxycholic acid (UDCA), hyodeoxycholic acid (HDCA) and deoxycholic acid (DCA), as well as the glycine- and taurine-conjugated variants of CA, CDCA, DCA and UDCA. Donor blood was obtained to prepare DBS calibrators and quality controls for method development and validation.

RESULTS

We developed a quantitative bile acid assay with a run-time of two minutes, and one-step sample preparation of 3.2 mm DBS discs. Validation results demonstrated overall good performance and was considered fit for purpose. Children with Alagille syndrome, Aagenaes syndrome and alpha-1 antitrypsin deficiency had increased BAs in DBS from newborn screening samples compared with age matched controls, and had different bile acids profiles.

CONCLUSION

We propose that our high throughput assay allows bile acid profiling in DBS that can be a valuable assessment tool for early screening of cholestasis in children. Assaying BAs in dried bloodspots is key for early detection of cholestasis, and provides transferability to a newborn screening setting.

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.

Estimating Gestational Age and Prediction of Preterm Birth Using Metabolomics Biomarkers

Preterm birth (PTB) is a leading cause of morbidity and mortality in children aged under 5 years globally, especially in low-resource settings. It remains a challenge in many low-income and middle-income countries to accurately measure the true burden of PTB due to limited availability of accurate measures of gestational age (GA), first trimester ultrasound dating being the gold standard. Metabolomics biomarkers are a promising area of research that could provide tools for both early identification of high-risk pregnancies and for the estimation of GA and preterm status of newborns postnatally.

A miniaturized sample preparation method for routine elemental determination in whole blood using volumetric absorptive micro-sampling by ICP-QQQ

Volumetric absorptive micro-sampling (VAMS) has emerged as a simple and safe tool for collecting and storing blood samples in clinical and bioanalytical fields. This study presents a novel method for determining essential and non-essential trace elements (As, Be, Cd, Cs, Cu, Fe, Mg, P, Pb, S, Sb, Se, Tl, V, U) in VAMS-collected blood samples using microwave-assisted digestion with diluted acid as sample preparation method and an inductively coupled plasma triple quadrupole mass spectrometry (ICP-QQQ) as determination technique. While certain elements posed challenges due to VAMS tip background issues (Al, Ti, Cr, Mn, Co, Ni, Sn, Mo, Ba), the method demonstrated high precision and accuracy for the targeted analytes. It was demonstrated that 4.5 mol L-1 HNO3 plus 100 µL H2O2 30% (w/w) was suitable for an efficiency of digestion for further elemental determination using micro-analysis (spending less than 300 µL analytical solution) by ICP-QQQ, given that the residual carbon content (RCC) after the digestion procedure was lower than 5%. All the results higher than limit of quantification (LOQ) were in agreement with reference values for all analytes. Accuracy was assessed through reference material analysis and recovery tests using spiked samples. Moreover, suitable agreements (p > 0.05) between this method (VAMS-M) and the comparative method (liquid sampling method) were obtained for all analytes >LOQ. Furthermore, all results >LOQ showed good precision according to precision requirements (Horwitz equation). In this way, with the use of dilute acid, low dilution factor (30-fold), and excellent digestion efficiency (>95%), the proposed method was able to achieve an excellent detection limit, precision, and accuracy for 15 elements: As, Be, Cd, Cs, Cu, Fe, Mg, P, Pb, S, Sb, Se, Tl, V, and U using ICP-MS/MS, without the need for matrix-matched calibration curves. This research showcases an innovative analytical approach using VAMS for blood samples, offering biosafety, practicality, sensitivity, versatility, and robustness. This method contributes to the advancement of trace element analysis in biomedical research and clinical applications.

Vascular adaptation to exercise: a systematic review and audit of female representation

Biological sex is a salient factor in exercise-induced vascular adaptation. Although a male bias is apparent in the literature, the methodological quality of available studies in females is not yet known. This systematic review with narrative synthesis aimed to assess available evidence of exercise interventions on endothelial function, measured using flow-mediated dilation, in otherwise healthy individuals and athletes. A standardized audit framework was applied to quantify the representation of female participants. Using a tiered grading system, studies that met best-practice recommendations for conducting physiological research in females were identified. A total of 210 studies in 5,997 participants were included, with 18% classified as athletes. The primary exercise mode and duration were aerobic (49%) and acute (61%), respectively. Despite 53% of studies (n = 111) including at least one female, female participants accounted for only 39% of the total study population but 49% of the athlete population. Majority (49%) of studies in females were conducted in premenopausal participants. No studies in naturally menstruating, hormonal contraceptive-users or in participants experiencing menstrual irregularities met all best-practice recommendations. Very few studies (∼5%) achieved best-practice methodological guidelines for studying females and those that did were limited to menopause and pregnant cohorts. In addition to the underrepresentation of female participants in exercise-induced vascular adaptation research, there remains insufficient high-quality evidence with acceptable methodological control of ovarian hormones. To improve the overall methodological quality of evidence, adequate detail regarding menstrual status should be prioritized when including females in vascular and exercise research contexts.

Hematocrit-Independent Sampling Enables White Blood Cell Counts from Patterned Dried Blood Spot Cards

The accurate and efficient measurement of white blood cell (WBC) counts is vital for monitoring general patient health and can aid in the diagnosis of a range of possible infections or diseases. Even with their importance universally acknowledged, access to WBC counts is largely limited to those with access to phlebotomists and centralized clinical laboratories, which house the instruments that perform the tests. As a result, large populations of people (e.g., those that are home-bound or live in remote locations) lack facile access to testing. Dried blood spot (DBS) cards are often used to bridge these gaps in access to testing by offering the ability to collect blood at home for ambient shipping to laboratories. However, it is well understood that these cards, which are prepared from cellulose cardstocks without further modification, suffer from variabilities in accuracy and precision due to uncontrolled sample spreading and hematocrit effects, which have hindered their use to determine WBC counts. In this paper, we present a method to obtain an accurate WBC count using a patterned dried blood spot (pDBS) card, which comprises collection zones that meter volumes of dried blood. Using an input volume of 75 μL of whole blood, we demonstrate that, unlike the gold standard DBS card (Whatman 903), our pDBS design allows for the collection of replicate zones containing a reproducible, average volume of dried blood (12.1 μL, 7.8% CV) over the range of hematocrits from 25 to 55%. We then used qPCR to quantify the 18S rRNA gene to determine WBC counts from the volumes of blood that are metered in pDBS zones. We observe that WBC counts generated from our method are comparable to those measured with a HemoCue point-of-care WBC analyzer. Our approach to using pDBS cards as a blood collection device has the potential to support at-home sampling and other patient populations that need WBC counts but lack access to clinical facilities.

Revolutionizing Blood Collection: Innovations, Applications, and the Potential of Microsampling Technologies for Monitoring Metabolites and Lipids

Blood serves as the primary global biological matrix for health surveillance, disease diagnosis, and response to drug treatment, holding significant promise for personalized medicine. The diverse array of lipids and metabolites in the blood provides a snapshot of both physiological and pathological processes, with many routinely monitored during conventional wellness checks. The conventional method involves intravenous blood collection, extracting a few milliliters via venipuncture, a technique limited to clinical settings due to its dependence on trained personnel. Microsampling methods have evolved to be less invasive (collecting ≤150 µL of capillary blood), user-friendly (enabling self-collection), and suitable for remote collection in longitudinal studies. Dried blood spot (DBS), a pioneering microsampling technique, dominates clinical and research domains. Recent advancements in device technology address critical limitations of classical DBS, specifically variations in hematocrit and volume. This review presents a comprehensive overview of state-of-the-art microsampling devices, emphasizing their applications and potential for monitoring metabolites and lipids in blood. The scope extends to diverse areas, encompassing population studies, nutritional investigations, drug discovery, sports medicine, and multi-omics research.

A new approach with dried plasma spots: a rapid determination of antidepressants and antipsychotics by fast GC-MS

Background: The increasing prevalence of poisoning cases related to antidepressants and antipsychotics has raised concerns. Methods: To address this issue, a new adaptation of the dried plasma spot technique was developed using a 24-well plate and fast gas chromatography-mass spectrometry. The method involves the optimization of extraction variables and sample preparation, and was successfully validated. Results: The limits of quantitation ranged from 20 to 60 ng/ml, and accuracy ranged from 87.8% to 112.2%. The technique was applied to 102 human plasma samples from suspected poisoning cases, with positivity of 90.2%. Conclusion: This method provides a cheap, easy to implement and fast approach, making it ideal for toxicological emergency laboratories and promoting valuable support for healthcare professionals managing poisoning cases involving antidepressants and antipsychotics.

Clinical Blood Metabogram: Application to Overweight and Obese Patients

Recently, the concept of a mass spectrometric blood metabogram was introduced, which allows the analysis of the blood metabolome in terms of the time, cost, and reproducibility of clinical laboratory tests. It was demonstrated that the components of the metabogram are related groups of the blood metabolites associated with humoral regulation; the metabolism of lipids, carbohydrates, and amines; lipid intake into the organism; and liver function, thereby providing clinically relevant information. The purpose of this work was to evaluate the relevance of using the metabogram in a disease. To do this, the metabogram was used to analyze patients with various degrees of metabolic alterations associated with obesity. The study involved 20 healthy individuals, 20 overweight individuals, and 60 individuals with class 1, 2, or 3 obesity. The results showed that the metabogram revealed obesity-associated metabolic alterations, including changes in the blood levels of steroids, amino acids, fatty acids, and phospholipids, which are consistent with the available scientific data to date. Therefore, the metabogram allows testing of metabolically unhealthy overweight or obese patients, providing both a general overview of their metabolic alterations and detailing their individual characteristics. It was concluded that the metabogram is an accurate and clinically applicable test for assessing an individual's metabolic status in disease.

Microsampling tools for collecting, processing, and storing blood at the point-of-care

In the wake of the COVID-19 global pandemic, self-administered microsampling tools have reemerged as an effective means to maintain routine healthcare assessments without inundating hospitals or clinics. Finger-stick collection of blood is easily performed at home, in the workplace, or at the point-of-care, obviating the need for a trained phlebotomist. While the initial collection of blood is facile, the diagnostic or clinical utility of the sample is dependent on how the sample is processed and stored prior to transport to an analytical laboratory. The past decade has seen incredible innovation for the development of new materials and technologies to collect low-volume samples of blood with excellent precision that operate independently of the hematocrit effect. The final application of that blood (i.e., the test to be performed) ultimately dictates the collection and storage approach as certain materials or chemical reagents can render a sample diagnostically useless. Consequently, there is not a single microsampling tool that is capable of addressing every clinical need at this time. In this review, we highlight technologies designed for patient-centric microsampling blood at the point-of-care and discuss their utility for quantitative sampling as a function of collection material and technique. In addition to surveying methods for collecting and storing whole blood, we emphasize the need for direct separation of the cellular and liquid components of blood to produce cell-free plasma to expand clinical utility. Integrating advanced functionality while maintaining simple user operation presents a viable means of revolutionizing self-administered microsampling, establishing new avenues for innovation in materials science, and expanding access to healthcare.

Current State and Future Perspectives on Personalized Metabolomics

Metabolomics is one of the most promising 'omics' sciences for the implementation in medicine by developing new diagnostic tests and optimizing drug therapy. Since in metabolomics, the end products of the biochemical processes in an organism are studied, which are under the influence of both genetic and environmental factors, the metabolomics analysis can detect any changes associated with both lifestyle and pathological processes. Almost every case-controlled metabolomics study shows a high diagnostic accuracy. Taking into account that metabolomics processes are already described for most nosologies, there are prerequisites that a high-speed and comprehensive metabolite analysis will replace, in near future, the narrow range of chemical analyses used today, by the medical community. However, despite the promising perspectives of personalized metabolomics, there are currently no FDA-approved metabolomics tests. The well-known problem of complexity of personalized metabolomics data analysis and their interpretation for the end-users, in addition to a traditional need for analytical methods to address the quality control, standardization, and data treatment are reported in the review. Possible ways to solve the problems and change the situation with the introduction of metabolomics tests into clinical practice, are also discussed.

Metabolic alterations in dairy cattle with lameness revealed by untargeted metabolomics of dried milk spots using direct infusion-tandem mass spectrometry and the triangulation of multiple machine learning models

Lameness is a major challenge in the dairy cattle industry in terms of animal welfare and economic implications. Better understanding of metabolic alteration associated with lameness could lead to early diagnosis and effective treatment, there-fore reducing its prevalence. To determine whether metabolic signatures associated with lameness could be discovered with untargeted metabolomics, we developed a novel workflow using direct infusion-tandem mass spectrometry to rapidly analyse (2 min per sample) dried milk spots (DMS) that were stored on commercially available Whatman® FTA® DMPK cards for a prolonged period (8 and 16 days). An orthogonal partial least squares-discriminant analysis (OPLS-DA) method validated by triangulation of multiple machine learning (ML) models and stability selection was employed to reliably identify important discriminative metabolites. With this approach, we were able to differentiate between lame and healthy cows based on a set of lipid molecules and several small metabolites. Among the discriminative molecules, we identified phosphatidylglycerol (PG 35:4) as the strongest and most sensitive lameness indicator based on stability selection. Overall, this untargeted metabolomics workflow is found to be a fast, robust, and discriminating method for determining lameness in DMS samples. The DMS cards can be potentially used as a convenient and cost-effective sample matrix for larger scale research and future routine screening for lameness.

Volumetric absorptive microsampling-LC-MS/MS assays for quantitation of giredestrant in dried human whole blood

Volumetric absorption microsampling devices offer minimally invasive and user-friendly collection of capillary blood in volumes as low as 10 μl. Herein we describe the assay validation for determination of the selective estrogen receptor degrader giredestrant (GDC-9545) in dried human whole blood collected using the Mitra^® and Tasso-M20 devices. Both LC-MS/MS assays met validation acceptance criteria for the linear range 1-1000 ng/ml giredestrant. Mitra and Tasso-M20 samples were stable for 84 and 28 days at ambient conditions, respectively, and for 7-9 days at 40 and -70°C. Blood hematocrit, hyperlipidemia and anticoagulant did not impact quantitation of giredestrant. These validated assays are suitable for the determination of giredestrant in dried blood samples collected using Mitra and Tasso-M20 microsampling devices.

Development of LC-HRMS untargeted analysis methods for nasal epithelial lining fluid exposomics

BACKGROUND

The nasal mucosa, as a primary site of entry for inhaled substances, contains both inhaled xenobiotic and endogenous biomarkers. Nasal mucosa can be non-invasively sampled (nasal epithelial lining fluid "NELF") and analyzed for biological mediators. However, methods for untargeted analysis of compounds inhaled and/or retained in the nasal mucosa are needed.

OBJECTIVES

This study aimed to develop a high resolution LC-MS untargeted method to analyze collected NELF. Profiling of compounds in NELF samples will also provide baseline data for future comparative studies to reference.

METHODS

Extracted NELF analytes were injected to LC-ESI-MS. After spectrum processing, an in-house library provided annotations with high confidence, while more tentative annotation proposals were obtained via ChemSpider database matching.

RESULTS

The established method successfully detected unique molecular signatures within NELF. Baseline profiling of 27 samples detected 2002 unknown molecules, with 77 and 463 proposed structures by our in-house library and Chemspider matching. High confidence annotations revealed common metabolites and tentative annotations implied various environmental exposure biomarkers are also present in NELF.

SIGNIFICANCE

The experimental pipeline for analyzing NELF samples serves as simple and robust method applicable for future studies to characterize identities/effects of inhaled substances and metabolites retained in the nasal mucosa.

IMPACT STATEMENT

The nasal mucosa contains exogenous and endogenous compounds. The development of an untargeted analysis is necessary to characterize the nasal exposome by deciphering the identity and influence of inhaled compounds on nasal mucosal biology. This study established a high resolution LC-MS based untargeted analysis of non-invasively collected nasal epithelial lining fluid. Baseline profiling of the nasal mucosa (n = 27) suggests the presence of environmental pollutants, along with detection of endogenous metabolites. Our results show high potential for the analytical pipeline to facilitate future respiratory health studies involving inhaled pollutants or pharmaceutical compounds and their effects on respiratory biology.

Thalidomide measurement in plasma and dried plasma spot by SPE combined with UHPLC-MS/MS for therapeutic drug monitoring

Aims: To validate an SPE-ultra-HPLC-MS/MS method for thalidomide (THD) measurement in dried plasma spot (DPS). Methods: Extraction included acetonitrile/water clean-up and online SPE. The LOD, LLOQ, linearity, precision, accuracy, recovery, matrix effect, process efficiency, carryover, stability, drug interference and dilution integrity were assessed. Results: The method was linear from 50 to 2000 ng/ml with a LOD of 20 ng/ml and LLOQ of 50 ng/ml. The coefficient of variation for precision was 0.4-7.9% for intra-assay and 1.3-8.9% for interassay and accuracy was 81.4-97.1%. Adequate matrix effect (100.6-107.0%), recovery (88.7-105.0%) and process efficiency (91.3-109.3%) were registered. DPS was stable for 14 days at room temperature and 45°C and for 4 months at -80°C. The method was applied to quantify THD in both wet plasma and DPS from patients with cutaneous lupus receiving THD treatment. The difference between THD wet plasma and DPS concentration was <15%. Conclusion: The method is suitable to quantify THD in DPS.

Multi-omics analysis from archival neonatal dried blood spots: limitations and opportunities

Newborn screening (NBS) programs operate in many countries, processing millions of dried bloodspot (DBS) samples annually. In addition to early identification of various adverse health outcomes, these samples have considerable potential as a resource for population-based research that could address key questions related to child health. The feasibility of archival DBS samples for emerging targeted and untargeted multi-omics analysis has not been previously explored in the literature. This review aims to critically evaluate the latest advances to identify opportunities and challenges of applying omics analyses to NBS cards in a research setting. Medline, Embase and PubMed databases were searched to identify studies utilizing DBS for genomic, proteomic and metabolomic assays. A total of 800 records were identified after removing duplicates, of which 23 records were included in this review. These papers consisted of one combined genomic/metabolomic, four genomic, three epigenomic, four proteomic and 11 metabolomic studies. Together they demonstrate that the increasing sensitivity of multi-omic analytical techniques makes the broad use of NBS samples achievable for large cohort studies. Maintaining the pre-analytical integrity of the DBS sample through storage at temperatures below -20 °C will enable this important resource to be fully realized in a research capacity.

Patterned Dried Blood Spot Cards for the Improved Sampling of Whole Blood

Dried blood spot (DBS) cards perform many functions for sampling blood that is intended for subsequent laboratory analysis, which include: (i) obviating the need for a phlebotomist by using fingersticks, (ii) enhancing the stability of analytes at ambient or elevated environmental conditions, and (iii) simplifying the transportation of samples without a cold chain. However, a significant drawback of standard DBS cards is the potential for sampling bias due to unrestricted filling caused by the hematocrit of blood, which often limits quantitative or reproducible measurements. Alternative microsampling technologies have minimized or eliminated this bias by restricting blood distribution, but these approaches deviate from clinical protocols and present a barrier to broad adoption. Herein, we describe a patterned dried blood spot (pDBS) card that uses wax barriers to control the flow and restrict the distribution of blood to provide enhanced sampling. These patterned cards reproducibly fill four replicate extraction zones independent of the hematocrit effect. We demonstrate a 3-fold improvement in accuracy for the quantitation of hemoglobin using pDBS cards compared to unpatterned cards. Patterned cards also facilitate the near quantitative recovery (ca. 95%) of sodium with no evidence of a statistically significant difference between dried and liquid blood samples. Similarly, the recovery of select amino acids was conserved in comparison to a recent report with improved intercard precision. We anticipate that this approach presents a viable method for preparing and storing samples of blood in limited resource settings while maintaining current clinical protocols for processing and analyzing dried blood spots.

Vertical Transfer of Metabolites Detectable from Newborn's Dried Blood Spot Samples Using UPLC-MS: A Chemometric Study

The pregnancy period and first days of a newborn's life is an important time window to ensure a healthy development of the baby. This is also the time when the mother and her baby are exposed to the same environmental conditions and intake of nutrients, which can be determined by assessing the blood metabolome. For this purpose, dried blood spots (DBS) of newborns are a valuable sampling technique to characterize what happens during this important mother-child time window. We used metabolomics profiles from DBS of newborns (age 2-3 days) and maternal plasma samples at gestation week 24 and postpartum week 1 from n=664 mother-child pairs of the Copenhagen Prospective Studies on Asthma in Childhood 2010 (COPSAC2010) cohort, to study the vertical mother-child transfer of metabolites. Further, we investigated how persistent the metabolites are from the newborn and up to 6 months, 18 months, and 6 years of age. Two hundred seventy two metabolites from UPLC-MS (Ultra Performance Liquid Chromatography-Mass Spectrometry) analysis of DBS and maternal plasma were analyzed using correlation analysis. A total of 11 metabolites exhibited evidence of transfer (R>0.3), including tryptophan betaine, ergothioneine, cotinine, theobromine, paraxanthine, and N6-methyllysine. Of these, 7 were also found to show persistence in their levels in the child from birth to age 6 years. In conclusion, this study documents vertical transfer of environmental and food-derived metabolites from mother to child and tracking of those metabolites through childhood, which may be of importance for the child's later health and disease.

Advances in Therapeutic Monitoring of Lithium in the Management of Bipolar Disorder

Since the mid-20th century, lithium continues to be prescribed as a first-line mood stabilizer for the management of bipolar disorder (BD). However, lithium has a very narrow therapeutic index, and it is crucial to carefully monitor lithium plasma levels as concentrations greater than 1.2 mmol/L are potentially toxic and can be fatal. The quantification of lithium in clinical laboratories is performed by atomic absorption spectrometry, flame emission photometry, or conventional ion-selective electrodes. All these techniques are cumbersome and require frequent blood tests with consequent discomfort which results in patients evading treatment. Furthermore, the current techniques for lithium monitoring require highly qualified personnel and expensive equipment; hence, it is crucial to develop low-cost and easy-to-use devices for decentralized monitoring of lithium. The current paper seeks to review the pertinent literature rigorously and critically with a focus on different lithium-monitoring techniques which could lead towards the development of automatic and point-of-care analytical devices for lithium determination.

Personal Metabolomics: A Global Challenge

Today, the introduction of metabolomics, like other omics sciences, into clinical practice as a personal omics test that realizes the perfect analytical capabilities of this science has become an important subject. The assembled data show that the metabolome of biosamples is a collection of highly informative and accurate signatures of virtually all diseases that are widespread in the population. However, we have not seen the emergence of personalized metabolomics in clinical practice. This article analyzes the causes of this problem. The complexity of personal metabolic data analysis and its incompatibility with widely accepted data treatment in metabolomics are shown. As a result, the impossibility of translating metabolic signatures accumulated in databases into a personal test is revealed. Problem-solving strategies that may radically change the situation and realize the analytical capabilities of metabolomics in medical laboratory practice are discussed.

homeRNA: A Self-Sampling Kit for the Collection of Peripheral Blood and Stabilization of RNA

Gene expression analysis (e.g., targeted gene panels and transcriptomics) from whole blood can elucidate mechanisms of the immune function and aid in the discovery of biomarkers. Conventional venipuncture offers only a small snapshot of our broad immune landscape as immune responses may occur outside of the time and location parameters available for conventional venipuncture. A self-operated method that enables flexible sampling of liquid whole blood coupled with immediate stabilization of cellular RNA is instrumental in facilitating capture and preservation of acute or transient immune fluxes. To this end, we developed homeRNA, a kit for self-collection of peripheral blood (∼0.5 mL) and immediate stabilization of cellular RNA, using the Tasso-SST blood collection device with a specially designed stabilizer tube containing RNAlater. To assess the feasibility of homeRNA for self-collection and stabilization of whole blood RNA, we conducted a pilot study (n = 47 participants) in which we sent homeRNA to participants aged 21-69, located across 10 US states (94% successful blood collections, n = 61/65). Among participants who successfully collected blood, 93% reported no or minimal pain/discomfort using the kit (n = 39/42), and 79% reported very easy/somewhat easy stabilization protocol (n = 33/42). Total RNA yield from the stabilized samples ranged between 0.20 and 5.99 μg (mean = 1.51 μg), and all but one RNA integrity number values were above 7.0 (mean = 8.1), indicating limited RNA degradation. The results from this study demonstrate the self-collection and RNA stabilization of whole blood with homeRNA by participants themselves in their own home.

Optimization and Stability Testing of Four Commercially Available Dried Blood Spot Devices for Estimating Measles and Rubella IgG Antibodies

Blood collection using dried blood spots (DBS) provides an easier alternative to venipuncture for sample collection, transport, and storage but requires additional processing that can cause variability in results. Whole-blood samples spotted on four DBS devices and respective paired serum samples were tested for antimeasles and antirubella IgG antibody concentrations by enzyme immunoassay. Elution protocols for DBS devices were optimized for comparability relative to serum samples using 12 adult volunteers. Stability of DBS collected on HemaSpot HF was assessed under various temperature conditions (+4, 22 to 25, and 45°C) at six time points (0, 7, 15, 30, 60, and 90 days) in a controlled laboratory setting using six adult volunteers. Devices were shipped and stored for 30 days at four settings with variable temperature and humidity conditions to assess the impact on antibody concentrations. Three DBS devices demonstrated comparable antibody concentrations with paired sera following optimization. Antibodies recovered from DBS were stable for at least 90 days at 4°C and for 30 days at ambient temperature (22 to 25°C) using the HemaSpot HF device. A drastic decline in antibody concentrations was observed at 45°C, resulting in quantitative and qualitative discrepancies by day 7. HemaSpot HF devices shipped to field sites and stored at ambient temperature and humidity resulted in quantitative, but not qualitative, variability. Measurement of antimeasles and antirubella IgG antibodies with DBS devices is an accurate alternative to testing serum, provided elution protocols are optimized. Stability of HemaSpot HF devices at ambient temperature enables broader use in surveys when serum processing and cold storage are not feasible.

IMPORTANCE Dried blood spot (DBS) collection offers various advantages over conventional methods of blood collection, especially when collecting and transporting samples for a serosurvey. Yet use of DBS requires additional processing steps in the laboratory that can add to variability in results. We optimized a protocol to elute IgG antibodies against measles and rubella viruses in four DBS devices, demonstrating high concordance with paired venous sera for most devices. Extensive stability studies with various temperature and storage conditions in the laboratory and in the field were conducted using HemaSpot HF DBS devices prior to its use in one of the largest community-based measles and rubella serological surveys in the world.

Metabolomic Laboratory-Developed Tests: Current Status and Perspectives

Laboratory-developed tests (LDTs) are a subset of in vitro diagnostic devices, which the US Food and Drug Administration defines as "tests that are manufactured by and used within a single laboratory". The review describes the emergence and history of LDTs. The current state and development prospects of LDTs based on metabolomics are analyzed. By comparing LDTs with the scientific metabolomics study of human bio samples, the characteristic features of metabolomic LDT are shown, revealing its essence, strengths, and limitations. The possibilities for further developments and scaling of metabolomic LDTs and their potential significance for healthcare are discussed. The legal aspects of LDT regulation in the United States, European Union, and Singapore, demonstrating different approaches to this issue, are also provided. Based on the data presented in the review, recommendations were made on the feasibility and ways of further introducing metabolomic LDTs into practice.

Dried Blood Spot (DBS) Methodology Study for Biomarker Discovery in Lysosomal Storage Disease (LSD)

Lysosomal storage diseases (LSDs) are a heterogeneous group of inherited metabolic diseases caused by mutations in genes encoding for proteins involved in the lysosomal degradation of macromolecules. They occur in approximately 1 in 5000 live births and pose a lifelong risk. Therefore, to achieve the maximum benefit from LSDs therapies, a fast and early diagnosis of the disease is required. In this framework, biomarker discovery is a significant factor in disease diagnosis and in predicting its outcomes. On the other hand, the dried blood spot (DBS) based metabolomics platform can open up new pathways for studying non-directional hypothesis approaches to biomarker discovery. This study aims to increase the efficiency of the developed methods for biomarker development in the context of rare diseases, with an improved impact on the reliability of the detected compounds. Thereby, we conducted two independent experiments and integrated them into the screening of the human blood metabolome: (1) comparison of EDTA blood and filter cards in terms of their suitability for metabolomics studies; (2) optimization of the extraction method: a side-by-side comparison of a series of buffers to the best utility to the disease of interest. The findings were compared to previous studies across parameters such as metabolite coverage, sample type suitability, and stability. The results indicate that measurements of metabolites are susceptible to differences in pre-analytical conditions and extraction solvents. This proposed approach can increase the positive rate of the future development of biomarkers. Altogether, the procedure can be easily adapted and applied to other studies, where the limited number of samples is a common barrier.

Towards a biochemical approach to occupational stress management

Given the immense and growing cost of occupational stress to society through lost productivity and the burden to healthcare systems, current best practices for detecting, managing and reducing stress in the workplace are clearly sub-optimal and substantially better methods are required. Subjective, self-reported psychology and psychiatry-based instruments are prone to biases whereas current objective, biology-based measures produce conflicting results and are far from reliable. A multivariate approach to occupational stress research is required that reflects the broad, coordinated, physiological response to demands placed on the body by exposure to diverse occupational stressors. A literature review was conducted to determine the extent of application of the emerging multivariate technology of metabolomics to occupational stress research. Of 170 articles meeting the search criteria, three were identified that specifically studied occupational stressors using metabolomics. A further ten studies were not specifically occupational or were of indirect or peripheral relevance. The occupational studies, although limited in number highlight the technological challenges associated with the application of metabolomics to investigate occupational stress. They also demonstrate the utility to evaluate stress more comprehensively than univariate biomarker studies. The potential of this multivariate approach to enhance our understanding of occupational stress has yet to be established. This will require more studies with broader analytical coverage of the metabolome, longitudinal sampling, combination with experience sampling methods and comparison with psychometric models of occupational stress. Progress will likely involve combining multi-omic data into a holistic, systems biology approach to detecting, managing and reducing occupational stress and optimizing workplace performance.

Little to Give, Much to Gain-What Can You Do With a Dried Blood Spot?

PURPOSE OF REVIEW

Technological advances have allowed dried blood spots (DBS) to be utilized for various measurements, helpful in population-based studies. The following is a review of the literature highlighting the advantages and disadvantages of DBS and describing their use in multiple areas of research.

RECENT FINDINGS

DBS can track pollutant exposure to understand their impact on health. DBS can also be used for (epi-)genetic studies, to measure clinical biomarkers, and to monitor drug adherence. Advantages of DBS include being minimally invasive, requiring low blood volume, and being cost-effective to collect, transport, and store. Disadvantages of DBS include the hematocrit effect, which is related to the viscosity of the blood affecting its spread on to the filter paper, causing a major source of error when assessing concentrations, and the possibility of low DNA volume. Numerous uses for DBS make them an important source of biomaterial but they require additional validation for accuracy and reproducibility.

Evaluation of dried blood spots as alternative sampling material for serological detection of anti-SARS-CoV-2 antibodies using established ELISAs

OBJECTIVES

During the current pandemic, antibody testing based on venous serum helps to determine whether the tested person has been previously infected with SARS-CoV-2. Alternatively, capillary blood can be taken via a finger prick (dried blood spots, DBS). In this study, paired DBS and venipuncture samples were tested using two serological assays to evaluate the usability of DBS for the detection of anti-SARS-CoV-2 antibodies.

METHODS

Paired samples of DBS and venous serum were collected from 389 volunteers, of whom 75 had a recent PCR-confirmed SARS-CoV-2 infection, and tested for anti-SARS-CoV-2 IgG antibodies against both viral S1 and nucleocapsid protein (NCP) antigens using two ELISAs. Degree of agreement and correlation coefficients between ELISA results based on the two sampling methods were calculated.

RESULTS

Results of DBS showed almost perfect agreement and high correlations with results from corresponding serum samples in both the S1-based ELISA and the NCP-based ELISA.

CONCLUSIONS

ELISA results derived from DBS showed very high agreement to those obtained with serum, supposing adequate usability and robustness of DBS as sample material for detection of anti-SARS-CoV-2 antibodies. In the near future, large-scale epidemiological screening for antibodies against SARS-CoV-2 will be carried out. Since DBS reduce the strain on healthcare institutions regarding sample collection, they have a potential to facilitate efficient community- and population-based screening in the current SARS-CoV-2 pandemic.

Holistic Metabolomic Laboratory-Developed Test (LDT): Development and Use for the Diagnosis of Early-Stage Parkinson's Disease

A laboratory-developed test (LDT) is a type of in vitro diagnostic test that is developed and used within a single laboratory. The holistic metabolomic LDT integrating the currently available data on human metabolic pathways, changes in the concentrations of low-molecular-weight compounds in the human blood during diseases and other conditions, and their prevalent location in the body was developed. That is, the LDT uses all of the accumulated metabolic data relevant for disease diagnosis and high-resolution mass spectrometry with data processing by in-house software. In this study, the LDT was applied to diagnose early-stage Parkinson's disease (PD), which currently lacks available laboratory tests. The use of the LDT for blood plasma samples confirmed its ability for such diagnostics with 73% accuracy. The diagnosis was based on relevant data, such as the detection of overrepresented metabolite sets associated with PD and other neurodegenerative diseases. Additionally, the ability of the LDT to detect normal composition of low-molecular-weight compounds in blood was demonstrated, thus providing a definition of healthy at the molecular level. This LDT approach as a screening tool can be used for the further widespread testing for other diseases, since 'omics' tests, to which the metabolomic LDT belongs, cover a variety of them.

Diagnostic prediction model development using data from dried blood spot proteomics and a digital mental health assessment to identify major depressive disorder among individuals presenting with low mood

With less than half of patients with major depressive disorder (MDD) correctly diagnosed within the primary care setting, there is a clinical need to develop an objective and readily accessible test to enable earlier and more accurate diagnosis. The aim of this study was to develop diagnostic prediction models to identify MDD patients among individuals presenting with subclinical low mood, based on data from dried blood spot (DBS) proteomics (194 peptides representing 115 proteins) and a novel digital mental health assessment (102 sociodemographic, clinical and personality characteristics). To this end, we investigated 130 low mood controls, 53 currently depressed individuals with an existing MDD diagnosis (established current MDD), 40 currently depressed individuals with a new MDD diagnosis (new current MDD), and 72 currently not depressed individuals with an existing MDD diagnosis (established non-current MDD). A repeated nested cross-validation approach was used to evaluate variation in model selection and ensure model reproducibility. Prediction models that were trained to differentiate between established current MDD patients and low mood controls (AUC = 0.94 ± 0.01) demonstrated a good predictive performance when extrapolated to differentiate between new current MDD patients and low mood controls (AUC = 0.80 ± 0.01), as well as between established non-current MDD patients and low mood controls (AUC = 0.79 ± 0.01). Importantly, we identified DBS proteins A1AG1, A2GL, AL1A1, APOE and CFAH as important predictors of MDD, indicative of immune system dysregulation; as well as poor self-rated mental health, BMI, reduced daily experiences of positive emotions, and tender-mindedness. Despite the need for further validation, our preliminary findings demonstrate the potential of such prediction models to be used as a diagnostic aid for detecting MDD in clinical practice.

Metabolomics Community in Russia: History of Development, Key Participants, and Results

Metabolomics is the latest trend in the “-omics” sciences, of which technologies are widely used today in all life sciences. Metabolomics gave impetus to the description of biochemical processes that occur in many organisms, search for new biomarkers of disease, and laid the foundation for new clinical laboratory diagnostics. The purpose of this review is to show how metabolomics is represented in Russian science, what main research areas were chosen, and to demonstrate the successes and main achievements of Russian scientists in this field. The review is dedicated to the 10th anniversary of Russian metabolomics and also touches on the history of the formation of Russian metabolomics and prospects for the future.

[Ten years of the Russian metabolomics: history of development and achievements]

Metabolomics is one of the omics sciences, the technologies of which are widely used today in many life sciences. Its application influenced the discovery of new biomarkers of diseases, the description of biochemical processes occurring in many organisms, laid the basis for a new generation of clinical laboratory diagnostics. The purpose of this review is to show how metabolomics is represented in the studies of Russian scientists, to demonstrate the main directions and achievements of the Russian science in this field. The review also highlights the history of metabolomics, existing problems and the place of Russian metabolomics in their solution.

Diagnosis of Parkinson's Disease by A Metabolomics-Based Laboratory-Developed Test (LDT)

A laboratory-developed test (LDT) is a type of in vitro diagnostic test that is designed, manufactured and used in the same laboratory (i.e., an in-house test). In this study, a metabolomics-based LDT was developed. This test involves a blood plasma preparation, direct-infusion mass spectrometry analysis with a high-resolution mass spectrometer, alignment and normalization of mass peaks using original algorithms, metabolite annotation by a biochemical context-driven algorithm, detection of overrepresented metabolic pathways and results in a visualization in the form of a pathway names cloud. The LDT was applied to detect early stage Parkinson’s disease (PD)—the diagnosis of which currently requires great effort due to the lack of available laboratory tests. In a case–control study (n = 56), the LDT revealed a statistically sound pattern in the PD-relevant pathways. Usage of the LDT for individuals confirmed its ability to reveal this pattern and thus diagnose PD at the early-stage (1–2.5 stages, according to Hoehn and Yahr scale). The detection of this pattern by LDT could diagnose PD with a specificity of 64%, sensitivity of 86% and an accuracy of 75%. Thus, this LDT can be used for further widespread testing.