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Cellular senescence has been implicated in the aging-related dysfunction of satellite cells, the resident muscle stem cell population primarily responsible for the repair of muscle fibers. Despite being in a state of permanent cell cycle arrest, these cells remain metabolically active and release an abundance of factors that can have detrimental effects on the cellular microenvironment. This phenomenon is known as the senescence-associated secretory phenotype (SASP), and its metabolic profile is poorly characterized in senescent muscle. In the present investigation, we examined the intracellular and extracellular metabolome of C 2 C 12 myoblasts using a bleomycin (BLEO)-mediated model of DNA damage-induced senescence. We also evaluated the relationship between the senescent metabolic phenotype and SASP signaling through molecular and network-based analyses. Senescent myoblasts exhibited a significantly altered extracellular metabolome (i.e., exometabolome), including increased secretion of several aging-associated metabolites. Four of these metabolites-trimethylamine- N -oxide (TMAO), xanthine, choline, and oleic acid-were selected for individual dose-response experiments to determine whether they could drive the senescence phenotype. Although most of the tested metabolites did not independently alter senescence markers, oleic acid treatment of healthy myoblasts significantly upregulated the SASP genes Ccl2 , Cxcl12 , and Il33 ( p < 0.05). A gene-metabolite interaction network further revealed that oleic acid was one of the most interconnected metabolites to key senescence-associated genes. Notably, oleic acid interacted with several prominent SASP genes, suggesting a potential epigenetic effect between this monounsaturated fatty acid and SASP regulation. In summary, the exometabolome, particularly oleic acid, is implicated in SASP signaling within senescent myoblasts. NEW & NOTEWORTHY Cellular senescence and its accompanying secretory phenotype [i.e., the senescence-associated secretory phenotype (SASP)] have been linked to the aging-associated dysfunction of skeletal muscle, yet little is known about this phenomenon in satellite cells. We report that senescent myoblasts experience a significantly altered extracellular metabolome primarily characterized by the substantial release of nonesterified fatty acids. Targeted evaluation of several extracellular senescence-associated metabolites reveals a potential epigenetic role for long-chain fatty acids, particularly oleic acid, in regulating SASP-related gene expression.

Background: The role of circulating metabolites on child development is understudied. We investigated associations between children's serum metabolome and early childhood development (ECD)., Methods: Untargeted metabolomics was performed on serum samples of 5004 children aged 6-59 months, a subset of participants from the Brazilian National Survey on Child Nutrition (ENANI-2019). ECD was assessed using the Survey of Well-being of Young Children's milestones questionnaire. The graded response model was used to estimate developmental age. Developmental quotient (DQ) was calculated as the developmental age divided by chronological age. Partial least square regression selected metabolites with a variable importance projection ≥1. The interaction between significant metabolites and the child's age was tested., Results: Twenty-eight top-ranked metabolites were included in linear regression models adjusted for the child's nutritional status, diet quality, and infant age. Cresol sulfate ( β =-0.07; adjusted-p <0.001), hippuric acid ( β =-0.06; adjusted-p <0.001), phenylacetylglutamine ( β =-0.06; adjusted-p <0.001), and trimethylamine- N -oxide ( β =-0.05; adjusted-p=0.002) showed inverse associations with DQ. We observed opposite directions in the association of DQ for creatinine (for children aged -1 SD: β =-0.05; p P =0.01;+1 SD: β =0.05; p=0.02) and methylhistidine (-1 SD: β = - 0.04; p=0.04;+1 SD: β =0.04; p=0.03)., Conclusions: Serum biomarkers, including dietary and microbial-derived metabolites involved in the gut-brain axis, may potentially be used to track children at risk for developmental delays., Funding: Supported by the Brazilian Ministry of Health and the Brazilian National Research Council., Competing Interests: MP, VK, PN, RS, NF, SF, FD, Id, EL, DF, ZK, MS, PB, GK No competing interests declared, (© 2025, Padilha et al.)

Mass spectrometry (MS)-based metabolomics often rely on separation techniques when analyzing complex biological specimens to improve method resolution, metabolome coverage, quantitative performance, and/or unknown identification. However, low sample throughput and complicated data preprocessing procedures remain major barriers to affordable metabolomic studies that are scalable to large populations. Herein, we introduce PeakMeister as a new software tool in the R statistical environment to enable standardized processing of serum metabolomic data acquired by multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS), a high-throughput separation platform (<4 min/sample) which takes advantage of a serial injection format of 13 samples within a single analytical run. We performed a rigorous validation of PeakMeister by analyzing 47 cationic metabolites consistently measured in 5,000 serum and 420 quality control samples from the Brazilian National Survey on Child Nutrition (ENANI-2019) comprising a total of 224,983 metabolite peaks acquired in 40 days across three batches over an eight-month period. A migration time index using a panel of 11 internal standards was introduced to correct for large variations in migration times, which allowed for reliable peak annotation, peak integration, and sample position assignment for serum metabolites having two flanking internal standards or a single comigrating stable-isotope internal standard. PeakMeister accelerated data preprocessing times by 30-fold compared to manual processing of MSI-CE-MS data by an experienced analyst using vendor software, while also achieving excellent peak annotation fidelity (median accuracy >99.9%), acceptable intermediate precision (median CV = 16.0%), consistent metabolite peak integration (mean bias = -2.1%), and good mutual agreement when quantifying 16 plasma metabolites from NIST SRM-1950 (mean bias = -1.3%). Reference ranges are also reported for 40 serum metabolites in a national nutritional survey of Brazilian children under 5 years of age from the ENANI-2019 study. MSI-CE-MS in conjunction with PeakMeister allows for rapid and automated processing of large-scale metabolomic studies that tolerate nonlinear migration time shifts without complicated dynamic time warping or effective mobility scale transformations.

Estimated glomerular filtration rate (eGFR) impacts the concentration of plasma biomarkers confounding biomarker association studies of eGFR with reverse causation. To identify biomarkers causally associated with eGFR, we performed a proteome-wide Mendelian randomization study. Genetic variants nearby biomarker coding genes were tested for association with plasma concentration of 1,161 biomarkers in a multi-ancestry sample of 12,066 participants from the Prospective Urban and Rural Epidemiological (PURE) study. Using two-sample Mendelian randomization, individual variants' effects on biomarker concentration were correlated with their effects on eGFR and kidney traits from published genome-wide association studies (GWAS). Genetically altered concentrations of 22 biomarkers were associated with eGFR above a Bonferroni-corrected significance threshold. Five biomarkers were previously identified by GWAS (UMOD, FGF5, LGALS7, NINJ1, COL18A1). Nine biomarkers were within 1 Mb of the lead GWAS variant but the gene for the biomarker was unidentified as the candidate for the GWAS signal (INHBC, TNFRSF11A, TCN2, PXN1, PRTN3, PSMD9, TFPI, ITGB6, CA3). Single-cell transcriptomic data indicated the 22 biomarkers are expressed in kidney tubules, collecting duct, fibroblasts, and immune cells. Pathway analysis showed significant enrichment of identified biomarkers in the extracellular kidney parenchyma. Thus, using genetic regulators of biomarker concentration via proteome-wide Mendelian randomization, we identified 22 biomarkers that appear to causally impact eGFR in either a beneficial or adverse manner. The current study provides rationale for novel therapeutic targets for eGFR and emphasized a role for extracellular proteins produced by tubular cells and fibroblasts for impacting eGFR., (Copyright © 2023 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)

The Omega-3 Index (O3I) reflects eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content in erythrocytes. While the O3I is associated with numerous health outcomes, its widespread use is limited. We investigated whether urinary metabolites could be used to non-invasively monitor the O3I in an exploratory analysis of a previous placebo-controlled, parallel arm randomized clinical trial in males and females ( n = 88) who consumed either ~3 g/d olive oil (OO; control), EPA, or DHA for 12 weeks. Fasted blood and first-void urine samples were collected at baseline and following supplementation, and they were analyzed via gas chromatography and multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS), respectively. We tentatively identified S -carboxypropylcysteamine (CPCA) as a novel urinary biomarker reflecting O3I status, which increased following both EPA and DHA ( p < 0.001), but not OO supplementation, and was positively correlated to the O3I (R = 0.30, p < 0.001). Additionally, an unknown dianion increased following DHA supplementation, but not EPA or OO. In ROC curve analyses, CPCA outperformed all other urinary metabolites in distinguishing both between OO and EPA or DHA supplementation groups (AUC > 80.0%), whereas the unknown dianion performed best in discriminating OO from DHA alone (AUC = 93.6%). Candidate urinary biomarkers of the O3I were identified that lay the foundation for a non-invasive assessment of omega-3 status.

Background: Childhood obesity is a global health concern and can lead to lifetime cardiometabolic disease. New advances in metabolomics can provide biochemical insights into the early development of obesity, so we aimed to characterize serum metabolites associated with overweight and adiposity in early childhood and to stratify associations by sex., Methods: Nontargeted metabolite profiling was conducted in the Canadian CHILD birth cohort (discovery cohort) at age 5 years (n = 900) by multisegment injection-capillary electrophoresis-mass spectrometry. Clinical outcome was defined using novel combined measures of overweight (WHO-standardized body mass index ≥ 85th percentile) and/or adiposity (waist circumference ≥ 90th percentile). Associations between circulating metabolites and child overweight/adiposity (binary and continuous outcomes) were determined by multivariable linear and logistic regression, adjusting for covariates and false discovery rate, and by subsequent sex-stratified analysis. Replication was assessed in an independent replication cohort called FAMILY at age 5 years (n = 456)., Results: In the discovery cohort, each standard deviation (SD) increment of branched-chain and aromatic amino acids, glutamic acid, threonine, and oxoproline was associated with 20-28% increased odds of overweight/adiposity, whereas each SD increment of the glutamine/glutamic acid ratio was associated with 20% decreased odds. All associations were significant in females but not in males in sex-stratified analyses, except for oxoproline that was not significant in either subgroup. Similar outcomes were confirmed in the replication cohort, where associations of aromatic amino acids, leucine, glutamic acid, and the glutamine/glutamic acid ratio with childhood overweight/adiposity were independently replicated., Conclusions: Our findings show the utility of combining measures of both overweight and adiposity in young children. Childhood overweight/adiposity at age 5 years has a specific serum metabolic phenotype, with the profile being more prominent in females compared to males., (© 2023. The Author(s).)

Background: In pregnancy, choline is deemed an essential nutrient and carnitine needs are increased, but amounts remain undefined., Objectives: We aimed to measure choline and total dietary protein and dairy protein intake from food and supplements across pregnancy and the response to intake by profiling choline and carnitine metabolites across pregnancy and in cord blood., Methods: An exploratory analysis of choline and protein intake from 3-d diet records and measures of 36 serum choline and carnitine metabolites in early (12-17 wk) and late (36-38 wk) pregnancy was conducted in participants from the Be Healthy in Pregnancy study randomized to high dairy protein+walking exercise or usual care. Metabolites were measured in fasted maternal and cord serum using multisegment injection-capillary electrophoresis-mass spectrometry. Mixed ANOVA adjusted for body mass index was performed for comparison of metabolites across pregnancy and between intervention and control., Results: In 104 participants, the median (Q1, Q3) total choline intake was 347 (263, 427) mg/d in early and 322 (270, 437) mg/d in late pregnancy. Only ∼20% of participants achieved the recommended adequate intake (450 mg/d) and ∼10% consumed supplemental choline (8-200 mg/d). Serum-free choline (μmol/L) was higher in late compared with early pregnancy [12.9 (11.4, 15.1) compared with 9.68 (8.25, 10.61), P < 0.001], but choline downstream metabolites were similar across pregnancy. Serum carnitine [10.3 (9.01, 12.2) compared with 15.9 (14.1, 17.9) μmol/L, P < 0.001] and acetylcarnitine [2.35 (1.92, 2.68) compared with 3.0 (2.56, 3.59), P < 0.001] were significantly lower in late pregnancy. High cord:maternal serum metabolite ratios were found in most measured metabolites., Conclusions: Despite inadequate choline intake, serum-free choline was elevated in late pregnancy and enriched in cord blood compared with maternal serum. Serum carnitine declined in late pregnancy despite a high protein diet. The higher cord:maternal concentrations in choline and carnitine metabolites suggest active uptake in late pregnancy, reflecting the importance of these circulating metabolites in fetal development. This trial was registered at clinicaltrials.gov as NCT01689961., (Copyright © 2023 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

Aside from centrally induced trained immunity in the bone marrow (BM) and peripheral blood by parenteral vaccination or infection, evidence indicates that mucosal-resident innate immune memory can develop via a local inflammatory pathway following mucosal exposure. However, whether mucosal-resident innate memory results from integrating distally generated immunological signals following parenteral vaccination/infection is unclear. Here we show that subcutaneous Bacillus Calmette-Guérin (BCG) vaccination can induce memory alveolar macrophages (AMs) and trained immunity in the lung. Although parenteral BCG vaccination trains BM progenitors and circulating monocytes, induction of memory AMs is independent of circulating monocytes. Rather, parenteral BCG vaccination, via mycobacterial dissemination, causes a time-dependent alteration in the intestinal microbiome, barrier function and microbial metabolites, and subsequent changes in circulating and lung metabolites, leading to the induction of memory macrophages and trained immunity in the lung. These data identify an intestinal microbiota-mediated pathway for innate immune memory development at distal mucosal tissues and have implications for the development of next-generation vaccine strategies against respiratory pathogens., (© 2022. The Author(s).)

Background: Defining the metabolic syndrome (MetS) in children remains challenging. Furthermore, a dichotomous MetS diagnosis can limit the power to study associations. We sought to characterize the serum metabolite signature of the MetS in early childhood using high-throughput metabolomic technologies that allow comprehensive profiling of metabolic status from a biospecimen., Methods: In the Family Atherosclerosis Monitoring In earLY life (FAMILY) prospective birth cohort study, we selected 228 cases of MetS and 228 matched controls among children age 5 years. In addition, a continuous MetS risk score was calculated for all 456 participants. Comprehensive metabolite profiling was performed on fasting serum samples using multisegment injection-capillary electrophoresis-mass spectrometry. Multivariable regression models were applied to test metabolite associations with MetS adjusting for covariates of screen time, diet quality, physical activity, night sleep, socioeconomic status, age, and sex., Results: Compared to controls, thirteen serum metabolites were identified in MetS cases when using multivariable regression models, and using the quantitative MetS score, an additional eight metabolites were identified. These included metabolites associated with gluconeogenesis (glucose (odds ratio (OR) 1.55 [95% CI 1.25-1.93]) and glutamine/glutamate ratio (OR 0.82 [95% CI 0.67-1.00])) and the alanine-glucose cycle (alanine (OR 1.41 [95% CI 1.16-1.73])), amino acids metabolism (tyrosine (OR 1.33 [95% CI 1.10-1.63]), threonine (OR 1.24 [95% CI 1.02-1.51]), monomethylarginine (OR 1.33 [95% CI 1.09-1.64]) and lysine (OR 1.23 [95% CI 1.01-1.50])), tryptophan metabolism (tryptophan (OR 0.78 [95% CI 0.64-0.95])), and fatty acids metabolism (carnitine (OR 1.24 [95% CI 1.02-1.51])). The quantitative MetS risk score was more powerful than the dichotomous outcome in consistently detecting this metabolite signature., Conclusions: A distinct metabolite signature of pediatric MetS is detectable in children as young as 5 years old and may improve risk assessment at early stages of development., (© 2021. The Author(s).)

Metabolomics offers new insights into disease mechanisms that is enhanced when adopting orthogonal instrumental platforms to expand metabolome coverage, while also reducing false discoveries by independent replication. Herein, we report the first inter-method comparison when using multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS) and nuclear magnetic resonance (NMR) spectroscopy for characterizing the serum metabolome of patients with liver fibrosis in chronic hepatitis C virus (HCV) infection ( n = 20) and non-HCV controls ( n = 14). In this study, 60 and 30 serum metabolites were detected frequently (>75%) with good technical precision (median CV < 10%) from serum filtrate samples ( n = 34) when using standardized protocols for MSI-CE-MS and NMR, respectively. Also, 20 serum metabolite concentrations were consistently measured by both methods over a 500-fold concentration range with an overall mean bias of 9.5% ( n = 660). Multivariate and univariate statistical analyses independently confirmed that serum choline and histidine were consistently elevated ( p < 0.05) in HCV patients with late-stage (F2-F4) as compared to early-stage (F0-F1) liver fibrosis. Overall, the ratio of serum choline to uric acid provided optimal differentiation of liver disease severity ( AUC = 0.848, p = 0.00766) using a receiver operating characteristic curve, which was positively correlated with liver stiffness measurements by ultrasound imaging ( r = 0.606, p = 0.0047). Moreover, serum 5-oxo-proline concentrations were higher in HCV patients as compared to non-HCV controls ( F = 4.29, p = 0.0240) after adjustment for covariates (age, sex, BMI), indicative of elevated oxidative stress from glutathione depletion with the onset and progression of liver fibrosis. Both instrumental techniques enable rapid yet reliable quantification of serum metabolites in large-scale metabolomic studies with good overlap for biomarker replication. Advantages of MSI-CE-MS include greater metabolome coverage, lower operating costs, and smaller sample volume requirements, whereas NMR offers a robust platform supported by automated spectral and data processing software., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Shanmuganathan, Sarfaraz, Kroezen, Philbrick, Poon, Don-Wauchope, Puglia, Wishart and Britz-McKibbin.)

A standardized data workflow is described for large-scale serum metabolomic studies using multisegment injection-capillary electrophoresis-mass spectrometry. Multiplexed separations increase throughput (<4 min/sample) for quantitative determination of 66 polar/ionic metabolites in serum filtrates consistently detected (coefficient of variance (CV) <30%) with high frequency (>75%) from a multi-ethnic cohort of pregnant women (n = 1,004). We outline a validated protocol implemented in four batches over a 7-month period that includes details on preventive maintenance, sample workup, data preprocessing and metabolite authentication. We achieve stringent quality control (QC) and robust batch correction of long-term signal drift with good mutual agreement for a wide range of metabolites, including serum glucose as compared to a clinical chemistry analyzer (mean bias = 11%, n = 668). Control charts for a recovery standard (mean CV = 12%, n = 2,412) and serum metabolites in QC samples (median CV = 13%, n = 202) demonstrate acceptable intermediate precision with a median intraclass coefficient of 0.87. We also report reference intervals for 53 serum metabolites from a diverse population of women in their second trimester of pregnancy.

Short-chain fatty acids (SCFAs) and electrolytes are major constituents of human feces involved in maintaining gastrointestinal homeostasis that underlie complex diet, host and microbiome interactions. Reliable quantification of SCFAs and electrolytes is challenging given the heterogeneity of stool specimens from pediatric patients with diarrhea-predominate inflammatory bowel disease (IBD). Herein, we introduce two validated methods for determination of 3 SCFAs and 5 electrolytes consistently quantified from fecal extracts when using capillary electrophoresis with indirect UV detection (CE-iUV), where concentrations are normalized to total dried weight (mmol/kg d.w.). Lyophilization facilitates sample handling and extraction of heterogeneous stool specimens (∼ 15 mg) from a cohort of children with Crohn's disease (CD, n = 12) and ulcerative colitis (UC, n = 10) treated with exclusive enteral nutrition (EEN) or corticosteroid (CS) therapy to induce remission, respectively. Good technical precision (mean CV = 13 %, n = 14) and accuracy (recovery from 84 to 116%) is demonstrated for SCFAs and electrolytes from freeze dried stool extracts using a modified Bligh-Dyer protocol with low micromolar detection limits (∼ 2-15 μM). Fecal butyrate is 2.6-fold higher in CD as compared to UC patients (effect size = 1.51; p = 0.00291), and there is a strong co-linearity between fecal butyrate and acetate (r = 0.835) unlike propionate, which is correlated with fecal calprotectin (r = 0.517), a protein biomarker of intestinal inflammation. Also, a longitudinal study of matching stool samples collected from a sub-set of IBD patients revealed about a 7-fold enrichment in magnesium and calcium following 4 weeks of EEN as compared to baseline (F > 4.1 ; p < 0.05) unlike the CS treatment arm with no changes in other fecal SCFAs and electrolytes, including sodium, potassium, and ammonium. CE-iUV enables rapid fecal SCFA and electrolyte determination as required for new insights into the role of gut dysbiosis in IBD, as well as treatment monitoring of nutritional interventions that stabilize the disease course in affected children., Competing Interests: Declaration of Competing Interest The authors report no declarations of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Acetylsalicylic acid (ASA), also known as aspirin, appears to be ineffective in inhibiting platelet aggregation in 20-30% of patients. Light transmission aggregometry (LTA) is a gold standard platelet function assay. In this pilot study, we used LTA to personalize ASA therapy ex vivo in atherosclerotic patients. Patients were recruited who were on 81 mg ASA, presenting to ambulatory clinics at St. Michael's Hospital ( n = 64), with evidence of atherosclerotic disease defined as clinical symptoms and diagnostic findings indicative of symptomatic peripheral arterial disease (PAD), with an ankle brachial index (ABI) of <0.9 ( n = 52) or had diagnostic features of asymptomatic carotid arterial stenosis (CAS), with >50% stenosis of internal carotid artery on duplex ultrasound ( n = 12). ASA compliance was assessed via multisegmented injection-capillary electrophoresis-mass spectrometry based on measuring the predominant urinary ASA metabolite, salicyluric acid. LTA with arachidonic acid was used to test for ASA sensitivity. Escalating ASA dosages of 162 mg and 325 mg were investigated ex vivo for ASA dose personalization. Of the 64 atherosclerotic patients recruited, 8 patients (13%) were non-compliant with ASA. Of ASA compliant patients ( n = 56), 9 patients (14%) were non-sensitive to their 81 mg ASA dosage. Personalizing ASA therapy in 81 mg ASA non-sensitive patients with escalating dosages of ASA demonstrated that 6 patients became sensitive to a dosage equivalent to 162 mg ASA and 3 patients became sensitive to a dosage equivalent to 325 mg ASA. We were able to personalize ASA dosage ex vivo in all ASA non-sensitive patients with escalating dosages of ASA within 1 h of testing.

Capillary zone electrophoresis-mass spectrometry (CE-MS) is a mature analytical tool for the efficient profiling of (highly) polar and ionizable compounds. However, the use of CE-MS in comparison to other separation techniques remains underrepresented in metabolomics, as this analytical approach is still perceived as technically challenging and less reproducible, notably for migration time. The latter is key for a reliable comparison of metabolic profiles and for unknown biomarker identification that is complementary to high resolution MS/MS. In this work, we present the results of a Metabo-ring trial involving 16 CE-MS platforms among 13 different laboratories spanning two continents. The goal was to assess the reproducibility and identification capability of CE-MS by employing effective electrophoretic mobility (μ eff ) as the key parameter in comparison to the relative migration time (RMT) approach. For this purpose, a representative cationic metabolite mixture in water, pretreated human plasma, and urine samples spiked with the same metabolite mixture were used and distributed for analysis by all laboratories. The μ eff was determined for all metabolites spiked into each sample. The background electrolyte (BGE) was prepared and employed by each participating lab following the same protocol. All other parameters (capillary, interface, injection volume, voltage ramp, temperature, capillary conditioning, and rinsing procedure, etc.) were left to the discretion of the contributing laboratories. The results revealed that the reproducibility of the μ eff for 20 out of the 21 model compounds was below 3.1% vs 10.9% for RMT, regardless of the huge heterogeneity in experimental conditions and platforms across the 13 laboratories. Overall, this Metabo-ring trial demonstrated that CE-MS is a viable and reproducible approach for metabolomics.

New analytical methods are urgently needed to enable high-throughput, yet comprehensive drug screening, given an alarming opioid and prescription drug crisis in public health. Conventional urine drug testing based on a two-tier immunoassay screen followed by a gas chromatography-tandem mass spectrometry (GC-MS/MS) or liquid chromatography-tandem mass spectrometry (LC-MS/MS) method are expensive and prone to bias while being limited to targeted panels of known drugs of abuse (DoA). Herein, we outline an improved method for drug surveillance that allows for the resolution and detection of an expanded panel of DoA and their metabolites when using multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). Multiplexed separations of ten urine samples with a quality control by CE (< 3 min/sample) in conjunction with full-scan data acquisition using a time-of-flight mass spectrometer (TOF-MS) under positive ion mode detection allows for the identification and quantification of DoA above recommended cut-off levels. An excellent resolution of drug isomers and isobars, including background interferences, are achieved when using MSI-CE-MS with an electrokinetic spacer between sample segments, where accurate mass/molecular formula together with the comigration of a matching deuterated internal standard and the detection of one or more bio-transformed metabolites facilitate DoA identification over a wider detection window. Additionally, urine samples can be analyzed directly without enzyme deconjugation for the rapid screening without complicated sample workup. MSI-CE-MS enables the surveillance of a broad spectrum of DoA that is required for the treatment monitoring of high-risk patients, including confirming prescribed drug adherence, revealing illicit drug use/substitution, and evaluating optimal dosage regimes as required for new advances in precision medicine.