Revisiting sweat chloride test results based on recent guidelines for diagnosis of cystic fibrosis

Literary evidence of the impact of nonbiological risk factors on CRMS/CFSPID: A scoping review

Newborn screening for cystic fibrosis (CF) occasionally results in an inconclusive diagnosis of this disease, and these individuals are designated as CFTR-related metabolic syndrome (CRMS) in the United States, and CF Screen Positive Inconclusive Diagnosis (CFSPID) in other countries. Some of these asymptomatic individuals will progress to symptomatic disease, but risk factors associated with disease progression are not well understood. This scoping review was conducted to comprehensively map nonbiological risk factors in the CRMS/CFSPID literature and to identify understudied topics. Six electronic databases were systematically searched, resulting in 2951 studies. Forty nine eligible works were identified as including information on nonbiological risk factors related to CRMS/CFPSID. Eligible studies were published from 2002 to 2024, most prevalently in the United States (36.7%), and as quantitative data (81.6%). Of the 49 eligible works, 23 articles contributed only intellectual conjecture, while 26 articles contained original data, which underwent full-text qualitative content analysis. Key themes identified in descending order of content coverage included Psychological Impact, Management Care, Newborn Screening and Diagnostics, Communicating Diagnosis, and Lifestyle and External Exposures. This scoping review identified that while nonbiological risk factors are being studied in the CRMS/CFSPID literature, there was nearly equal distribution of works gathering original data to those citing previously published information. These findings indicate a critical need for original data collection on these risk factors, particularly on understudied topics identified herein.

Association between biomarkers of tobacco smoke exposure and clinical efficacy of ivacaftor in the G551D observational trial (GOAL)

BACKGROUND

Acrolein, an aldehyde in smoke from tobacco products, inhibits CFTR function in vitro. Ivacaftor is an FDA-approved potentiator that improves mutant CFTR function. This human clinical study investigated the relationship between two urinary markers of tobacco smoke exposure - the acrolein metabolite 3-HPMA and the nicotine metabolite NNAL - and sweat chloride response to ivacaftor in the G551D Observational Trial (GOAL).

METHODS

3-HPMA (low: <50th centile; moderate: 50-75th centile; high: >75th centile) and NNAL (detectable/undetectable) in GOAL samples was quantified with LC-MS/MS. Self-report of tobacco smoke exposure (Y/N) served as a subjective measure. Change in sweat chloride from pre- to 6 months post-ivacaftor treatment (ΔSC) was the primary CFTR-dependent readout.

RESULTS

The sample included 151 individuals, mean age 20.7 (SD 11.4) years, range 6-59 years. Smoke exposure prevalence was 15 % per self-reports but 27 % based on detectable NNAL. 3-HPMA was increased in those reporting tobacco smoke exposure (607 vs 354 ng/ml, p = 0.008), with a higher proportion of smoke-exposed in the high- vs low-acrolein group (31 % vs 9 %, p=0.040). Compared to low-acrolein counterparts, high-acrolein participants experienced less decrease in sweat chloride (-35.2 vs -48.2 mmol/L; p = 0.020) and had higher sweat chloride values (50.6 vs 37.6 mmol/L; p = 0.020) 6 months post-ivacaftor. The odds of ivacaftor-mediated potentiation to near normative CFTR function (defined as SC6mo <40 mmol/L) was more than twice as high in the low-acrolein cohort (OR: 2.51, p = 0.026).

CONCLUSIONS

Increased urinary 3-HPMA, an acrolein metabolite of tobacco smoke, is associated with a diminished sweat chloride response to ivacaftor potentiation of CFTR function.

Diagnosing Cystic Fibrosis in the 21st Century-A Complex and Challenging Task

Cystic fibrosis (CF) is a chronic and potentially life-threatening condition, wherein timely diagnosis assumes paramount significance for the prompt initiation of therapeutic interventions, thereby ameliorating pulmonary function, addressing nutritional deficits, averting complications, mitigating morbidity, and ultimately enhancing the quality of life and extending longevity. This review aims to amalgamate existing knowledge to provide a comprehensive appraisal of contemporary diagnostic modalities pertinent to CF in the 21st century. Deliberations encompass discrete delineations of each diagnostic modality and the elucidation of potential diagnostic quandaries encountered in select instances, as well as the delineation of genotype-phenotype correlations germane to genetic counseling endeavors. The synthesis underscores that, notwithstanding the availability and strides in diagnostic methodologies, including genetic assays, the sweat test (ST) retains its position as the preeminent diagnostic standard for CF, serving as a robust surrogate for CFTR functionality. Prospective clinical investigations in the realm of CF should be orchestrated with the objective of discerning novel diagnostic modalities endowed with heightened specificity and sensitivity.

Carbon nanomaterials for sweat-based sensors: a review

Sweat is easily accessible from the human skin's surface. It is secreted by the eccrine glands and contains a wealth of physiological information, including metabolites and electrolytes like glucose and Na ions. Sweat is a particularly useful biofluid because of its easy and non-invasive access, unlike other biofluids, like blood. On the other hand, nanomaterials have started to show promise operation as a competitive substitute for biosensors and molecular sensors throughout the last 10 years. Among the most synthetic nanomaterials that are studied, applied, and discussed, carbon nanomaterials are special. They are desirable candidates for sensor applications because of their many intrinsic electrical, magnetic, and optical characteristics; their chemical diversity and simplicity of manipulation; their biocompatibility; and their effectiveness as a chemically resistant platform. Carbon nanofibers (CNFs), carbon dots (CDs), carbon nanotubes (CNTs), and graphene have been intensively investigated as molecular sensors or as components that can be integrated into devices. In this review, we summarize recent advances in the use of carbon nanomaterials as sweat sensors and consider how they can be utilized to detect a diverse range of analytes in sweat, such as glucose, ions, lactate, cortisol, uric acid, and pH.

Real-Time Multi-Ion-Monitoring Front-End With Interference Compensation by Multi-Output Support Vector Regressor

Ion-sensors play a major role in physiology and healthcare monitoring since they are capable of continuously collecting biological data from body fluids. Nevertheless, ion interference from background electrolytes present in the sample is a paramount challenge for a precise multi-ion-monitoring. In this work, we propose the first system combining a battery-powered portable multi-channel electronic front-end, and an embedded Multi-output Support Vector Regressor (M-SVR), that supplies an accurate, continuous, and real-time monitoring of sodium, potassium, ammonium, and calcium ions. These are typical analytes tracked during physical exercise. The front-end interface was characterized through a sensor array built with screen-printed electrodes. Nernstian sensitivity and limit of detection comparable to a bulky laboratory potentiometer were achieved in both water and artificial sweat. The multivariate calibration model was deployed on a Raspberry Pi where the activity of the target ions were locally computed. The M-SVR model was trained, optimized, and tested on an experimental dataset acquired following a design of experiments. We demonstrate that the proposed multivariate regressor is a compact, low-complexity, accurate, and unbiased estimator of sodium and potassium ions activity. A global normalized root mean-squared error improvement of 6.97%, and global mean relative error improvement of 10.26%, were achieved with respect to a standard Multiple Linear Regressor (MLR). Within a real-time multi-ion-monitoring task, the overall system enabled the continuous monitoring and accurate determination of the four target ions activity, with an average accuracy improvement of 27.73% compared to a simple MLR, and a prediction latency of [Formula: see text].

Passively Addressable Ultra-Low Volume Sweat Chloride Sensor

This work demonstrates a novel electrochemical biosensor for the detection of chloride ion levels in ultra-low volumes (1-3 microliters) of passively expressed human sweat. We present here a hydration monitor that the pediatric, geriatric, and other immune-compromised or physically inactive/sedentary population cohort can utilize, for whom the current methods of chloride quantification of active stimulation of sweat glands through iontophoresis or treadmill runs are unsuitable. In this work, non-faradaic electroanalysis using gold microelectrodes deposited on a flexible nanoporous substrate, for high nanoscale surface area to volume enhancement, was leveraged to operate in ultra-low sweat volumes of <3 µL eluted at natural rates. The specific chloride ionophore-based affinity of chloride ions resulted in the modulation of charge transfer within the electrical double layer at the electrode-sweat buffer interface, which was transduced using electrochemical impedance spectroscopy (EIS) and chronoamperometry (CA). Linear calibration dose responses with R-squared values of 0.9746 and 0.9403 for EIS and CA respectively were obtained for a dynamic range of 10-100 mM. The surface charge and the binding chemistry of the capture probe were studied using zeta potential studies and UV-Vis. The dynamic sweat chloride-tracking capability of the sensor was evaluated for a duration of 180 min. Studies were conducted to probe the efficacy of the developed sensor for passive ultra-low sweat chloride assessment on human subjects (n = 3).

Dry sweat as sample for metabolomics analysis

Sweat is gaining popularity in clinical metabolomics as this biofluid is non-invasively sampled and its composition is modified by several pathologies. There is a lack of standardized strategies for collection of human sweat. Most studies have been carried out with fresh sweat collected after stimulation. A promising and simple alternative is sampling dry sweat by a solid support impregnated with a suited solvent. This research was aimed at comparing the metabolomics coverage provided by dry sweat collected by two solid supports (gauzes and filter papers) impregnated with different solvents. The dissolved dry sweat was analyzed by a dual approach: gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Among the tested sampling strategies, filter paper impregnated with 1:1 (v/v) ethanol‒phosphate buffer resulted the combination providing the highest metabolomics coverage (tentative identification of one hundred seventy-five compounds). Dry and fresh sweat were compared by using pools from the same individuals to evaluate compositional differences. Families of metabolites such as carnitines, sphingolipids and N-acyl-amino acids, among others, were exclusively identified in dry sweat. Comparison of both samples allowed concluding that dry sweat is better for analysis of low polar metabolites and fresh sweat is more suited for polar compounds. As most of the identified metabolites are involved in key biochemical pathways, this study opens interesting possibilities to the use of dry sweat as a source of metabolite markers for specific disorders. Sampling of dry sweat could provide a standardized approach for collection of this biofluid, thus overcoming the variability limitations of fresh sweat.

Novel, rare and common pathogenic variants in the CFTR gene screened by high-throughput sequencing technology and predicted by in silico tools

Cystic fibrosis (CF) is caused by ~300 pathogenic CFTR variants. The heterogeneity of which, challenges molecular diagnosis and precision medicine approaches in CF. Our objective was to identify CFTR variants through high-throughput sequencing (HTS) and to predict the pathogenicity of novel variants through in 8 silico tools. Two guidelines were followed to deduce the pathogenicity. A total of 169 CF patients had genomic DNA submitted to a Targeted Gene Sequencing and we identified 63 variants (three patients had three variants). The most frequent alleles were: F508del (n = 192), G542* (n = 26), N1303K (n = 11), R1162* and R334W (n = 9). The screened variants were classified as follows: 41 - pathogenic variants [classified as (I) n = 23, (II) n = 6, (III) n = 1, (IV) n = 6, (IV/V) n = 1 and (VI) n = 4]; 14 - variants of uncertain significance; and seven novel variants. To the novel variants we suggested the classification of 6b-16 exon duplication, G646* and 3557delA as Class I. There was concordance among the predictors as likely pathogenic for L935Q, cDNA.5808T>A and I1427I. Also, Y325F presented two discordant results among the predictors. HTS and in silico analysis can identify pathogenic CFTR variants and will open the door to integration of precision medicine into routine clinical practice in the near future.

Standardized clinical criteria and sweat test combined as a tool to diagnose Cystic Fibrosis

Context

CF is under-diagnosed in Ecuador; one out of every 11,252 live births born in Ecuador could have CF.

Aim

To analyze the clinical findings, based on previously established criteria, with the results of the sweat test, in circumstances where we do not have the routine molecular study.

Methods

Epidemiological, observational, analytic, cross-sectional study. It analyzed 180 patients clinically suspected of CF. Inclusion criteria: children of both sexes older than 30 days and younger than 12 years, who meet at least three clinical criteria suggestive for CF, outpatient and referred by a specialist physician who made a preliminary diagnosis. This is a pilot study.

Results

The combination of criteria pneumonia, chronic cough and chronic obstructive bronchial syndrome is the most frequent, with not a significant relationship with a positive sweat test. On the contrary, a significant relationship was found between the clinical combinations of pneumonia with cough and rhinosinusitis; pneumonia with cough; presence of Pseudomonas aeruginosa; and pneumonia with digital cough and clubbing, so it is recommended to perform the test in all these associations. The most frequent clinical criterion for the reference and performance of the electrolyte test in sweat is pneumonia to repeat for two or more episodes.

Conclusion

Clinical combinations of pneumonia with cough and rhinosinusitis; pneumonia with cough; presence of Pseudomonas aeruginosa; and pneumonia with digital cough and clubbing are pathognomonic for CF and indication for the sweat test. The predictive performance in CF diagnosis, defined as compatible clinical presence plus high values of chloride in sweat test, was 91.1%.