Biomedical subjects

Michael J MacCoss

Publications and source records attributed to Michael J MacCoss.

3 recordsLinked to original sources

PubMed2026

Interlaboratory Comparison of a Glucagon and Oxyntomodulin Immuno-LC-MS/MS Assay: Implications for Diabetes Research.

BACKGROUND: The quantification of plasma glucagon and oxyntomodulin is important in the assessment of α-cell function, which is impaired in patients with diabetes. We aimed to transfer between laboratories a novel assay that uses liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the sensitive and specific measurement of these highly homologous hormones. METHODS: Simultaneous measurement of glucagon and oxyntomodulin used immunoaffinity enrichment and LC-MS/MS. Immunoenrichment used monoclonal antibodies that are available at-cost to researchers (deposited at the Developmental Studies Hybridoma Bank). Pure synthetic glucagon, characterized for purity and concentration, was used as a calibrant and is available to others. A detailed standard operating procedure was shared between 3 laboratories and the performance of the method was evaluated with samples collected from patients with and without diabetes. Method comparison was made with 2 commercially available, FDA-registered glucagon immunoassays. RESULTS: The method was linear over the normal range (1-20 pM). When measured in duplicate, the median interlaboratory imprecision (%CV) of the measurement of 40 samples was 6.3% (IQR 4.5%) and 14.4% (IQR 12.4%) for glucagon and oxyntomodulin, respectively. Method comparison with commercially available immunoassays demonstrated good (Mercodia, R = 0.92) or fair (Ansh, R = 0.70) agreement. Multivariable linear regression using LC-MS/MS glucagon and oxyntomodulin concentrations to predict immunoassay results indicated significant cross-reactivity of each immunoassay with oxyntomodulin. CONCLUSION: We have validated a sensitive and specific assay for glucagon and oxyntomodulin that can be deployed in high-complexity clinical laboratories for research or the care of patients. Commercially available glucagon immunoassays have significant interference from molecules other than glucagon.

Journal Article↗

PubMed2026

Ghrelin Receptor Deletion or Pharmacological Inhibition Improves Muscle Function in Aging Male Mice.

Sarcopenia is characterized by age-related declines in muscle strength and mass, along with impaired physical function. It remains an unmet medical need, and there are no pharmacological interventions approved for this indication. The activation of growth hormone secretagogue receptor (GHSR)-1a, also known as ghrelin receptor, stimulates food intake and has acute anabolic effects. However, its impact on aging muscles remains uncertain. We examined the effects of GHSR-1a deletion on sarcopenia measurements (muscle mass, strength, and endurance) by comparing young and aged male GHSR-1a knockout (KO) and wildtype (WT) mice (6-, 24-, and 28-month-old). Deletion of GHSR-1a improved muscle fatigue resistance, endurance, and muscle strength during aging without affecting muscle mass or longevity. Since muscle endurance is closely related to mitochondrial function, we examined mitochondrial biogenesis marker PGC-1α and mitophagy signaling via PINK1/p62 and found them improved in old mice with GHSR deletion. Proteomics analysis also revealed that mitochondrial components remain central for maintaining muscle mass and function. We further investigated the effects of pharmacological inhibition of GHSR-1a by its inverse agonist, PF-5190457, in male WT mice. PF-5190457 mimicked the effects of GHSR-1a deletion, including improved endurance and increased markers of mitochondrial biogenesis (PGC-1α) and different mitophagy markers (LC3II and Bnip3). PF-5190457 also reduced body weight and adiposity, which were not observed with GHSR-1a deletion. Overall, these findings suggest that GHSR-1a is a promising therapeutic target for age-related sarcopenia.

Receptors, Ghrelin↗

PubMed2025

Carafe enables high quality in silico spectral library generation for data-independent acquisition proteomics.

Data-independent acquisition (DIA)-based mass spectrometry is becoming an increasingly popular mass spectrometry acquisition strategy for carrying out quantitative proteomics experiments. Most of the popular DIA search engines make use of in silico generated spectral libraries. However, the generation of high-quality spectral libraries for DIA data analysis remains a challenge, particularly because most such libraries are generated directly from data-dependent acquisition (DDA) data or are from in silico prediction using models trained on DDA data. In this study, we developed Carafe, a tool that generates high-quality experiment-specific in silico spectral libraries by training deep learning models directly on DIA data. We demonstrate the performance of Carafe on a wide range of DIA datasets, where we observe improved fragment ion intensity prediction and peptide detection relative to existing pretrained DDA models. To make Carafe more accessible to the community, we have integrated Carafe into the widely used Skyline tool.

Journal Article↗