Citations

Objective To test the ability of machine learning (ML) approaches with clinical and genomic biomarkers to predict methotrexate treatment response in patients with early rheumatoid arthritis (RA). Methods Demographic, clinical, and genomic data from 643 patients of European ancestry with early RA (mean age 54 years; 70% female) subdivided into a training (n = 336) and validation cohort (n = 307) were used. The genomic data comprised 160 single‐nucleotide polymorphisms (SNPs) previously associated with RA or methotrexate metabolism. Response to methotrexate monotherapy was defined as good or moderate by the European Alliance of Associations for Rheumatology (EULAR) response criteria at the 3‐month follow‐up. Supervised ML methods were trained with 5 repeats and 10‐fold cross‐validation using the training cohort. Prediction performance was validated in the independent validation cohort. Results Supervised ML methods combining age, sex, smoking, rheumatoid factor, baseline Disease Activity Score in 28 joints (DAS28) scores and 160 SNPs predicted EULAR response at 3 months with the area under the receiver operating curve of 0.84 ( P = 0.05) in the training cohort and achieved a prediction accuracy of 76% ( P = 0.05) in the validation cohort (sensitivity 72%, specificity 77%). Intergenic SNPs rs12446816, rs13385025, rs113798271, and ATIC (rs2372536) had variable importance above 60.0 and along with baseline DAS28 scores were among the top predictors of methotrexate response. Conclusion Pharmacogenomic biomarkers combined with baseline DAS28 scores can be useful in predicting response to methotrexate in patients with early RA. Applying ML to predict treatment response holds promise for guiding effective RA treatment choices, including timely escalation of RA therapies.

Rapid and accurate diagnostic testing is essential to bring the ongoing COVID-19 pandemic to an end. As the demand for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing continues to increase amid supply shortages, many laboratories have investigated the use of sources other than nasopharyngeal (NP) swabs.

Candida auris is an emerging fungal pathogen with cases reported in countries around the world and in 19 states within the United States as of August 2020. The CDC has recommended that hospitals perform active surveillance upon admission for patients with the appropriate risk factors. Currently, active surveillance requires that local hospitals send surveillance swabs to a public health laboratory for analysis. In this work, a real-time PCR assay was developed for the specific detection of C. auris from surveillance swabs, blood, and urine to enable rapid detection of this pathogen. The assay uses commercially available primers and reporter probes and it was verified on the LightCycler 480 PCR platform. Contrived specimens and prospectively collected composite groin/axilla surveillance swabs were used to validate the assay. The performance of the PCR assay on surveillance swabs was also compared to a second PCR assay targeting C. auris that was performed at the Minnesota Department of Health–Public Health Laboratory (MDH-PHL). Our PCR assay is able to detect and differentiate C. auris from closely related Candida species such as C. duobushaemulonii, C. haemulonii, and C. pseudohaemulonii on the basis of melting curve temperature differences.

ABSTRACT The value of matrix-assisted laser desorption ionization−time of flight mass spectrometry (MALDI-TOF MS) for the identification of bacteria and yeasts is well documented in the literature. Its utility for the identification of mycobacteria and Nocardia spp. has also been reported in a limited scope. In this work, we report the specificity of MALDI-TOF MS for the identification of 162 Mycobacterium species and subspecies, 53 Nocardia species, and 13 genera (totaling 43 species) of other aerobic actinomycetes using both the MALDI-TOF MS manufacturer's supplied database(s) and a custom database generated in our laboratory. The performance of a simplified processing and extraction procedure was also evaluated, and, similar to the results in an earlier literature report, our viability studies confirmed the ability of this process to inactivate Mycobacterium tuberculosis prior to analysis. Following library construction and the specificity study, the performance of MALDI-TOF MS was directly compared with that of 16S rRNA gene sequencing for the evaluation of 297 mycobacteria isolates, 148 Nocardia species isolates, and 61 other aerobic actinomycetes isolates under routine clinical laboratory working conditions over a 6-month period. MALDI-TOF MS is a valuable tool for the identification of these groups of organisms. Limitations in the databases and in the ability of MALDI-TOF MS to rapidly identify slowly growing mycobacteria are discussed.

ABSTRACT The PLEX-ID system is a novel technology that couples PCR amplification and electrospray ionization-mass spectrometry to identify pathogens directly in clinical specimens. The analytical performance of the PLEX-ID Broad Fungal assay was compared with that of traditional culture identification by using 91 characterized fungal culture isolates (64 manufacturer-claimed and 27 nonclaimed organisms) and directly by using 395 respiratory specimens. Discordant results were resolved by D2 large-subunit ribosomal DNA fungal sequencing. Environmental studies were performed to monitor for potential contamination. The PLEX-ID Broad Fungal assay correctly identified 95.6% (87/91) and 81.3% (74/91) of the culture isolates to the genus and species levels, respectively. Of the manufacturer-claimed organisms, 100% (64/64) and 92.2% (59/64) were correctly identified to the genus and species levels, respectively. Direct analysis of respiratory specimens resulted in 67.6% (267/395) and 66.6% (263/395) agreement with culture results to the genus and species levels, respectively, with 16.2% (64/395) of the results discordant with culture and 16.2% (64/395) not detected by the system. The majority (>95%) of the isolates not detected directly by the PLEX-ID system ultimately grew in low quantities in culture (≤20 colonies). In 20.3% (35/172) of the respiratory specimens where no growth was observed in culture, the PLEX-ID system identified a fungus, suggesting a potential increase in sensitivity over culture in some instances. The PLEX-ID system provides a rapid method for the detection of a broad array of fungi directly in respiratory specimens and has the potential of impacting turnaround times and patient care by reducing the need to wait for the growth of an organism in culture.

ABSTRACT An on-plate testing method using formic acid was evaluated on the Bruker Biotyper matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) mass spectrometry system using 90 yeast and 78 Corynebacterium species isolates, and 95.6 and 81.1% of yeast and 96.1 and 92.3% of Corynebacterium isolates were correctly identified to the genus and species levels, respectively. The on-plate method using formic acid yielded identification percentages similar to those for the conventional but more laborious tube-based extraction.