In the study of Small Cell Lung Cancer it was found that women had the greatest survival benefit from adding atezolizumab medication, and that optimal BMI and uric acid levels, female sex, lower LDH, and specific metabolite profiles* may serve as predictors of better immunotherapy response.

This study reveals that patients with spondyloarthritis (SpA), including ankylosing spondylitis and psoriatic arthritis, show distinct metabolic* changes—especially in amino acid and lipid metabolism—with glucose and glycerol levels helping to differentiate between the two conditions, offering new avenues for diagnosis and understanding disease mechanisms.

In the study evaluating NMR* vs isotope-dilution LC–MS/MS for piperacillin measurement in plasma, the authors report good concordance (concordance correlation coefficient ≈ 0.895, slope ≈ 1.03, intercept ≈ –0.50 mg/L), a small negative bias (–0.85 mg/L), and wide limits of agreement (−18.67 to +16.97 mg/L), suggesting that NMR may be a promising alternative for therapeutic drug monitoring.

In this study with 200 rheumatoid arthritis patients there were no clear metabolite* differences linked to disease activity or treatment, but that metabolic* abnormalities were strongly tied to cardiovascular risk factors — in particular, people reporting high stress (“distress”) showed abnormal histidine metabolism, suggesting histidine levels might serve as a biomarker of CV risk.

Using NMR spectroscopy* and machine learning, this study analyzed 99 metabolites in cerebrospinal fluid and serum to accurately distinguish multiple sclerosis, Parkinson’s disease, and other neurodegenerative disorders—with Parkinson’s patients showing notably lower CSF propionic acid levels, highlighting a potential biomarker for diagnosis.

In a study of 1,078 men undergoing prostate biopsy, a metabolite* panel combined with clinical data improved detection of clinically significant prostate cancer (AUC 0.84 vs 0.73), with key metabolites like ornithine and dimethylglycine helping to better distinguish aggressive disease and potentially reduce unnecessary biopsies.

In this study, researchers highlight GlycA and GlycB, two NMR-based biomarkers of low-grade inflammation*, as stable and reproducible tools that outperform traditional inflammatory markers in predicting cardiometabolic risk and may enable earlier detection of silent disease processes like cardiovascular disease and diabetes.