Calibration Practices in Clinical Mass Spectrometry: Review and Recommendations

A predictive model for depression in Chinese middle-aged and elderly people with physical disabilities

BACKGROUND

Middle-aged and older adults with physical disabilities exhibit more common and severe depressive symptoms than those without physical disabilities. Such symptoms can greatly affect the physical and mental health and life expectancy of middle-aged and older persons with disabilities.

METHOD

This study selected 2015 and 2018 data from the China Longitudinal Study of Health and Retirement. After analyzing the effect of age on depression, we used whether middle-aged and older adults with physical disabilities were depressed as the dependent variable and included a total of 24 predictor variables, including demographic factors, health behaviors, physical functioning and socialization, as independent variables. The data were randomly divided into training and validation sets on a 7:3 basis. LASSO regression analysis combined with binary logistic regression analysis was performed in the training set to screen the predictor variables of the model. Construct models in the training set and perform model evaluation, model visualization and internal validation. Perform external validation of the model in the validation set.

RESULT

A total of 1052 middle-aged and elderly persons with physical disabilities were included in this study, and the prevalence of depression in the elderly group > middle-aged group. Restricted triple spline indicated that age had different effects on depression in the middle-aged and elderly groups. LASSO regression analysis combined with binary logistic regression screened out Gender, Location of Residential Address, Shortsightedness, Hearing, Any possible helper in the future, Alcoholic in the Past Year, Difficulty with Using the Toilet, Difficulty with Preparing Hot Meals, and Unable to work due to disability constructed the Chinese Depression Prediction Model for Middle-aged and Older People with Physical Disabilities. The nomogram shows that living in a rural area, lack of assistance, difficulties with activities of daily living, alcohol abuse, visual and hearing impairments, unemployment and being female are risk factors for depression in middle-aged and older persons with physical disabilities. The area under the ROC curve for the model, internal validation and external validation were all greater than 0.70, the mean absolute error was less than 0.02, and the recall and precision were both greater than 0.65, indicating that the model performs well in terms of discriminability, accuracy and generalisation. The DCA curve and net gain curve of the model indicate that the model has high gain in predicting depression.

CONCLUSION

In this study, we showed that being female, living in rural areas, having poor vision and/or hearing, lack of assistance from others, drinking alcohol, having difficulty using the restroom and preparing food, and being unable to work due to a disability were risk factors for depression among middle-aged and older adults with physical disabilities. We developed a depression prediction model to assess the likelihood of depression in Chinese middle-aged and older adults with physical disabilities based on the above risk factors, so that early identification, intervention, and treatment can be provided to middle-aged and older adults with physical disabilities who are at high risk of developing depression.

Serum trace elements during treatment in pancreatic cancer patients and their associations with cancer prognosis

BACKGROUND & AIMS

In this study, we assessed serum trace element concentrations in patients with pancreatic cancer and compared the results to those of healthy controls and patients with chronic pancreatitis. We evaluated the association between trace element concentrations during cancer treatment and the risk of cancer progression and mortality in pancreatic cancer patients.

METHODS

A retrospective cohort study was conducted at a tertiary center in Korea. Serum trace element concentrations of cobalt (Co), copper (Cu), selenium (Se), and zinc (Zn) were measured at diagnosis using an inductively coupled plasma-mass spectrometry in 124 patients with pancreatic cancer, 50 patients with chronic pancreatitis, and 120 healthy controls. Trace elements were measured after a median of 282.5 (95% confidence interval [CI], 224.0-326.5) days from treatment initiation to assess changes in trace element concentrations during treatment.

RESULTS

Serum Co concentrations were significantly higher in patients with chronic pancreatitis and pancreatic cancer compared to healthy controls, while serum Se concentrations were significantly lower. During treatment, serum concentrations of Cu, Se, and Zn significantly decreased in patients with pancreatic cancer. During the follow-up (median 152.5; 95% CI, 142.8-160.0 months), 85.5% of patients experienced progression or relapse, and 84.7% of patients died. Patients with decreased Se and Zn concentrations during treatment had a higher mortality (hazard ratio [HR], 2.10; 95% CI, 1.31-3.38; P = 0.0020 for Se; HR, 1.72; 95% CI, 1.06-2.79; P = 0.0269 for Zn) compared to those with unchanged or increased trace element concentrations during treatment. Patients with a greater reduction in Zn concentrations during treatment had a higher mortality than those with a smaller reduction (HR, 1.59; 95% CI, 1.01-2.52; P = 0.0483). Patients whose Zn status changed from normal to deficient during treatment had an increased mortality (HR, 1.76; 95% CI, 1.16-2.67, P = 0.0084). Patients with multiple (≥2) trace element deficiencies after treatment had poorer outcomes than those with no or single trace element deficiency.

CONCLUSIONS

This study revealed that decreases in Se and Zn concentrations during cancer treatment were associated with adverse outcomes in terms of cancer progression and mortality in patients with pancreatic cancer. Further prospective investigations are recommended.

Integrating a Multiple Isotopologue Reaction-Monitoring Technique and LC-MS/MS for Quantitation of Small Molecules: Ten Mycotoxins in Cereals as an Example

Accurate quantification of mycotoxin in cereals is crucial for ensuring food safety and human health. However, the preparation of traditional multisample external calibration curves (MSCCs) is labor-intensive and error-prone. Here, a multiple isotopologue reaction-monitoring (MIRM)-LC-MS/MS method for accurate quantitation of ten major mycotoxins in cereals was successfully developed and validated, where a novel one-sample multipoint calibration curve (OSCC) strategy is used instead of MSCCs. The OSCC can be established by examining the correlation between the calculated theoretical isotopic abundances and the measured abundance across various MIRM channels. In comparison to the MSCC, the OSCC strategy exhibits outstanding performance including superior selectivity, accuracy (78.4-108.6%), and precision (<12.5%). Furthermore, the proposed OSCC-MIRM-LC-MS/MS method was successfully applied to investigate mycotoxin contamination in cereal samples in China. Considering the advantages of simplified workflows and improved throughput, the OSCC-MIRM-LC-MS/MS methodology holds great promise for accurately quantifying chemical contaminants in foods.

Association between traditional Chinese Medicine and osteoarthritis outcome: A 5-year matched cohort study

Objective

The aim of this study was to investigate the relationship between Traditional Chinese medicine (TCM) and pain reduction, hospital readmission, and joint replacement in patients with osteoarthritis (OA). Chinese herbal medicine (CHM) prescription patterns were further analyzed to confirm the association with prognosis and quality of life in OA patients.

Methods

We retrospectively followed 3,850 hospitalized patients with osteoarthritis between January 2018 and December 2022 using the hospital's HIS system. Propensity score matching (PSM) was used for data matching. Cox's proportional risk model was used to assess the impact of various factors on the outcomes of patients with OA, including pain worsening, readmission, and joint replacement. The Kaplan-Meier survival curve was applied to determine the impact of TCM intervention time on patient outcomes. Data mining methods including association rules, cluster analysis, and random walks have been used to assess the efficacy of TCM.

Results

The utilization rate of TCM in OA patients was 67.01% (2,511/3,747). After PSM matching, 1,228 TCM non-user patients and 1,228 TCM user patients were eventually included. The outcomes of pain worsening, re-admission rate, and joint replacement rate of the TCM non-user group were observably higher than those of the TCM user group with OA (p < 0.05). Based on the Cox proportional risk model, TCM is an independent protective factor. Compared with non-TCM users, TCM users had 58.4% lower rates of pain, 51.1% lower rates of re-admission, and 42% lower rates of joint replacement. In addition, patients in the high-exposure subgroup (TCM＞24 months) had a markedly lower risk of outcome events than those in the low-exposure subgroup (TCM ≤24 months). Data mining methods have shown that TCM therapy can significantly improve immune-inflammatory indices, VAS scores, and SF-36 scale scores in OA patients.

Conclusion

s TCM acts as a protective factor to improve the prognosis of patients with OA, and the benefits of long-term use of herbal medicines are even greater.

Rat Pharmacokinetics and In Vitro Metabolite Identification of KM-819, a Parkinson's Disease Candidate, Using LC-MS/MS and LC-HRMS

FAF1 (FAS-associated factor 1) is involved in the activation of Fas cell surface death receptors and plays a role in apoptosis and necrosis. In patients with Parkinson's disease, FAF1 is overexpressed in dopaminergic neurons in the substantia nigra. KM-819, an FAF1 inhibitor, has shown potential for preventing dopaminergic neuronal cell death, promoting the degradation of α-synuclein and preventing its accumulation. This study aimed to develop and validate a quantitative analytical method for determining KM-819 levels in rat plasma using liquid chromatography-tandem mass spectrometry. This method was then applied to pharmacokinetic (PK) studies in rats. The metabolic stability of KM-819 was assessed in rat, dog, and human hepatocytes. In vitro metabolite identification and metabolic pathways were investigated in rat, dog, and human hepatocytes. The structural analog of KM-819, namely N-[1-(4-bromobenzyl)-3,5-dimethyl-1H-pyrazol-4-yl]-2-(phenylsulfanyl) acetamide, served as the internal standard (IS). Proteins were precipitated from plasma samples using acetonitrile. Analysis was carried out using a reverse-phase C18 column with a mobile phase consisting of 0.1% formic acid in distilled water and 0.1% formic acid in acetonitrile. The analytical method developed for KM-819 exhibited linearity within the concentration range of 0.002-10 μg/mL in rat plasma. The precision and accuracy of the intra- and inter-day measurements were <15% for the lower limit of quantification (LLOQ) and all quality control samples. KM-819 demonstrated stability under various sample storage conditions (6 h at room temperature (25 °C), four weeks at -20 °C, three freeze-thaw cycles, and pretreated samples in the autosampler). The matrix effect and dilution integrity met the criteria set by the Food and Drug Administration and the European Medicines Agency. This sensitive, rapid, and reliable analytical method was successfully applied in pharmacokinetic studies in rats. Pharmacokinetic analysis revealed the dose-independent kinetics of KM-819 at 0.5-5 mg/kg, with a moderate oral bioavailability of ~20% in rats. The metabolic stability of KM-819 was also found to be moderate in rat, dog, and human hepatocytes. Metabolite identification in rat, dog, and human hepatocytes resulted in the discovery of six, six, and eight metabolites, respectively. Glucuronidation and mono-oxidation have been proposed as the major metabolic pathways. Overall, these findings contribute to a better understanding of the pharmacokinetic characteristics of KM-819, thereby aiding future clinical studies.

ReTimeML: a retention time predictor that supports the LC-MS/MS analysis of sphingolipids

The analysis of ceramide (Cer) and sphingomyelin (SM) lipid species using liquid chromatography-tandem mass spectrometry (LC-MS/MS) continues to present challenges as their precursor mass and fragmentation can correspond to multiple molecular arrangements. To address this constraint, we developed ReTimeML, a freeware that automates the expected retention times (RTs) for Cer and SM lipid profiles from complex chromatograms. ReTimeML works on the principle that LC-MS/MS experiments have pre-determined RTs from internal standards, calibrators or quality controls used throughout the analysis. Employed as reference RTs, ReTimeML subsequently extrapolates the RTs of unknowns using its machine-learned regression library of mass-to-charge (m/z) versus RT profiles, which does not require model retraining for adaptability on different LC-MS/MS pipelines. We validated ReTimeML RT estimations for various Cer and SM structures across different biologicals, tissues and LC-MS/MS setups, exhibiting a mean variance between 0.23 and 2.43% compared to user annotations. ReTimeML also aided the disambiguation of SM identities from isobar distributions in paired serum-cerebrospinal fluid from healthy volunteers, allowing us to identify a series of non-canonical SMs associated between the two biofluids comprised of a polyunsaturated structure that confers increased stability against catabolic clearance.

Probing Liquid Chromatography-Tandem Mass Spectrometry Response Dynamics and Nonlinear Effects for Response Level Defined Calibration Strategies with Simple Methods To Expand Linear Dynamic Ranges

The response characteristics of liquid chromatography-tandem mass spectrometry (LC-MS/MS) serve as the basis for selecting calibration methods in quantitative analysis. LC-MS/MS inherently exhibits nonlinear detection behavior, primarily attributed to the disproportionate growth observed between peak area and peak height at elevated response levels, potentially leading to signal saturation. This disproportionate peak growth results in reduced unit response (UR), which quantifies the instrument's detection sensitivity. LC-MS/MS typically operates within a narrow near-linear response range (NLRR) due to approximately proportional peak growth, yet the NLRR width varies across different analytes or platforms. Although the inclusion of stable isotope-labeled (SIL) internal standards (IS) in LC-MS/MS analysis can mitigate certain instrument response variations, it does not eliminate the fundamental cause of nonlinearity. Moreover, the concentration range accommodated by the NLRR can significantly fluctuate at different sensitivity levels. LC-MS/MS also encounters various other nonlinear effects, including ion suppression during ionization, signal cross-contribution between the analyte/IS, and matrix effects (ME). Consequently, quadratic regression emerges as a more adaptable approach to LC-MS/MS nonlinear response dynamics, offering a broader calibration range. The application of linear regression, on the other hand, requires strict conditions. Although the signal saturation zone typically remains inaccessible to calibration methods, reducing responses by employing less-optimal selected reaction monitoring (SRM) transitions and/or lower detection gain can facilitate fitting a wide concentration range into the NLRR, thereby enabling accurate linear regression calibration. This report delves into examining the LC-MS/MS response profile, its dynamics, and major nonlinear effects through instrument response mapping to elucidate their influence on the selection of calibration methods.

Assessing variations in manual pipetting: An under-investigated requirement of good laboratory practice

Pipettes are essential tools for biomedical and analytical laboratories, analogous to workstations for computer scientists. Variation in pipetting is a known unknown, as it is generally accepted that variations exist, but thus far, there have been limited studies on the extent of these variations in practice. In this mini-review, we highlight how manual pipetting is a key technique in the laboratory, and, although simple, inaccuracy and imprecision exist. If variations are not adequately addressed, errors can be compounded and consequently compromise data quality. Determination of the accuracy and precision of manual pipetting is straightforward, and here we review two common approaches that use gravimetry and spectrophotometry as readouts. We also provide detailed protocols for determination of accuracy and precision using manual single and multi-channel pipettes. These simple-to-use methods can be used by any laboratory for competency training and regular checks. Having a common protocol for evaluation of variation will also enable cross-laboratory comparison and potentially facilitate establishment of a reference value of acceptable ranges for operator error. Such a value could be of relevance to the scientific community for benchmarking and assuring good laboratory practice.

Quality Control in Targeted GC-MS for Amino Acid-OMICS

Gas chromatography-mass spectrometry (GC-MS) is suitable for the analysis of non-polar analytes. Free amino acids (AA) are polar, zwitterionic, non-volatile and thermally labile analytes. Chemical derivatization of AA is indispensable for their measurement by GC-MS. Specific conversion of AA to their unlabeled methyl esters (d0Me) using 2 M HCl in methanol (CH3OH) is a suitable derivatization procedure (60 min, 80 °C). Performance of this reaction in 2 M HCl in tetradeutero-methanol (CD3OD) generates deuterated methyl esters (d3Me) of AA, which can be used as internal standards in GC-MS. d0Me-AA and d3Me-AA require subsequent conversion to their pentafluoropropionyl (PFP) derivatives for GC-MS analysis using pentafluoropropionic anhydride (PFPA) in ethyl acetate (30 min, 65 °C). d0Me-AA-PFP and d3Me-AA-PFP derivatives of AA are readily extractable into water-immiscible, GC-compatible organic solvents such as toluene. d0Me-AA-PFP and d3Me-AA-PFP derivatives are stable in toluene extracts for several weeks, thus enabling high throughput quantitative measurement of biological AA by GC-MS using in situ prepared d3Me-AA as internal standards in OMICS format. Here, we describe the development of a novel OMICS-compatible QC system and demonstrate its utility for the quality control of quantitative analysis of 21 free AA and metabolites in human plasma samples by GC-MS as Me-PFP derivatives. The QC system involves cross-standardization of the concentrations of the AA in their aqueous solutions at four concentration levels and a quantitative control of AA at the same four concentration levels in pooled human plasma samples. The retention time (tR)-based isotope effects (IE) and the difference (δ(H/D) of the retention times of the d0Me-AA-PFP derivatives (tR(H)) and the d3Me-AA-PFP derivatives (tR(D)) were determined in study human plasma samples of a nutritional study (n = 353) and in co-processed QC human plasma samples (n = 64). In total, more than 400 plasma samples were measured in eight runs in seven working days performed by a single person. The proposed QC system provides information about the quantitative performance of the GC-MS analysis of AA in human plasma. IE, δ(H/D) and a massive drop of the peak area values of the d3Me-AA-PFP derivatives may be suitable as additional parameters of qualitative analysis in targeted GC-MS amino acid-OMICS.

The pipetting Olympics: Propagating proper pipetting a priori in clinical LC-MS/MS analysis

Introduction

Engaging pipetting events were developed to assess and challenge technicians' practical sample handling using matrices common to the clinical laboratory. As correct pipetting stands as a prerequisite for accurate clinical laboratory testing, this helped to understand sources of imprecision and bias attributed to the underlying step of aspirating and dispensing patient samples and internal standard in clinical LC-MS/MS assays while highlighting the importance for the clinical laboratory to evaluate this source of variability on an on-going basis and mitigate its impact.

Methods

The events involved pipetting water, methanol, serum, and whole blood. Gravimetric analysis was used to determine the exact volumetric delivery of each matrix using two different techniques. Imprecision and bias were calculated based on the volume derived from the mass and density of each matrix, using literature values for each matrix type.

Results

Low imprecision and bias were observed when pipetting water, as in common commercial pipetting assessment programs. Significantly increased imprecision and bias were observed in more applicable matrices (i.e., serum, whole blood, and methanol), indicating that water-based pipetting proficiency assessment leads to a false sense of technical ability. Additionally, the events within illuminated areas for training, leading to improved imprecision and bias. It was shown that pre-rinsing (aspirating and dispensing matrix three times to coat the tip) improved bias, particularly for delivery of methanol and whole blood.

Conclusions

Precise and accurate pipetting within the clinical laboratory should not be taken for granted, nor implicitly inferred from proficiency assessment using aqueous solutions. The engaging and collegial events fostered training opportunities. Assay-specific patient sample delivery considerations (pipets and matrices) can inform the practicality of these events - the Pipetting Olympics - and drive improvements within the laboratory.

Between and within calibration variation: implications for internal quality control rules

The variability between calibrations can be larger than the within calibration variation for some measurement procedures, that is a large CV_between:CV_within ratio. In this study, we examined the false rejection rate and probability of bias detection of quality control (QC) rules at varying calibration CV_between:CV_within ratios. Historical QC data for six representative routine clinical chemistry serum measurement procedures (calcium, creatinine, aspartate aminotransferase, thyrotrophin, prostate specific antigen and gentamicin) were extracted to derive the CV_between:CV_within ratios using analysis of variance. Additionally, the false rejection rate and probability of bias detection of three 'Westgard' QC rules (2:2S, 4:1S, 10X) at varying CV_between:CV_within ratios (0.1-10), magnitudes of bias, and QC events per calibration (5-80) were examined through simulation modelling. The CV_between:CV_within ratios for the six routine measurement procedures ranged from 1.1 to 34.5. With ratios >3, false rejection rates were generally above 10%. Similarly for QC rules involving a greater number of consecutive results, false rejection rates increased with increasing ratios, while all rules achieved maximum bias detection. Laboratories should avoid the 2:2S, 4:1S and 10X QC rules when calibration CV_between:CV_within ratios are elevated, particularly for those measurement procedures with a higher number of QC events per calibration.

From fundamentals in calibration to modern methodologies: A tutorial for small molecules quantification in liquid chromatography-mass spectrometry bioanalysis

Over the last two decades, liquid chromatography coupled to mass-spectrometry (LC‒MS) has become the gold standard to perform qualitative and quantitative analyses of small molecules. When quantitative analysis is developed, an analyst usually refers to international guidelines for analytical method validation. In this context, the design of calibration curves plays a key role in providing accurate results. During recent years and along with instrumental advances, strategies to build calibration curves have dramatically evolved, introducing innovative approaches to improve quantitative precision and throughput. For example, when a labeled standard is available to be spiked directly into the study sample, the concentration of the unlabeled analog can be easily determined using the isotopic pattern deconvolution or the internal calibration approach, eliminating the need for multipoint calibration curves. This tutorial aims to synthetize the advances in LC‒MS quantitative analysis for small molecules in complex matrices, going from fundamental aspects in calibration to modern methodologies and applications. Different work schemes for calibration depending on the sample characteristics (analyte and matrix nature) are distinguished and discussed. Finally, this tutorial outlines the importance of having international guidelines for analytical method validation that agree with the advances in calibration strategies and analytical instrumentation.

Calibration frequency and analytical variability of laboratory measurements

BACKGROUND

There is uncertainty whether increased frequency of calibrations may affect the overall analytical variability of a measurement procedure as reflected in quality control (QC) performance. In this simulation study, we examined the impact of calibration frequencies on the variability of laboratory measurements.

METHODS

A 5-point calibration curve was modeled with simulated concentrations ranging from 10 to 10,000 mmol/l, and signal intensities with CVs of 3 % around the mean, under a Gaussian distribution. 3 levels of QC (20, 150, 600 mmol/l) interspersed within the analytical measurement range were also simulated.

RESULTS

The CV of the 3 QC levels remained stable across the different calibration frequencies simulated (5, 10, 15 and 30 QC measurements per recalibration episode). The imprecision was greatest (18 %) at the lowest concentration of 20 mmol/l, when the calibration curve was derived using ordinary least squares regression, reducing to 3.5 % and 3.8 % at 150 and 600 mmol/l, respectively. The CV of all 3 QC concentrations remained constant at 3.4 % and close the predefined CV (3 %) when weighted least squares regression was used to derive the calibration model. Similar findings were observed with 2-point calibrations using WLS models at narrower concentration ranges (50 and 100 mmol/l as well as 50 and 500 mmol/l).

DISCUSSION

Within the parameters of the simulation study, an increased frequency of calibration events does not adversely impact the overall analytical performance of a measurement procedure under most circumstances.