Plasma-glycated CD59 as an early biomarker for gestational diabetes mellitus: prospective cohort study protocol

Andrews, Chloe; Toth-Castillo, Michelle; Aktaş, Hüseyin; Luque-Fernandez, Miguel Ángel; Wong, Steven Koon; Sen, Sarbattama; Halperin, José A.

doi:10.1136/bmjopen-2021-054773

Cited by 2 publications

(1 citation statement)

References 36 publications

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“…To verify this last assertion, we selected three proteins known to be upregulated in several diseases and well described as strong biomarkers in their corresponding pathologies. We chose mucin-16, a cancer biomarker [32], the Serum Amyloid A1 protein (SAA1), a traumatic brain injury marker [33] and CD59, an early biomarker for gestational diabetes mellitus [34]. These three proteins were identified in the LC-MSMS analysis with higher intensities in EVs compared to the WS.…”

Section: Protein Content-based Characterization Of Evs Isolated From ...mentioning

confidence: 99%

Salivary extracellular vesicles isolation methods impact the robustness of downstream biomarkers detection

Boulestreau,

Molina,

Ouedraogo

et al. 2024

Preprint

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Extracellular vesicles (EVs), crucial mediators in cell-to-cell communication, are implicated in both homeostatic and pathological processes. Their detectability in easily accessible peripheral fluids like saliva positions them as promising candidates for non-invasive biomarker discovery. However, the lack of standardized methods for salivary EVs isolation greatly limits our ability to study them. Therefore, we rigourously compared salivary EVs isolated using two scalable techniques - co-precipitation and immuno-affinity - against the long-established but labor-intensive ultracentrifugation method. Employing Cryo-Electron Microscopy, Nanoparticle Tracking Analysis, Western blots (WB), and proteomics, we identified significant method-dependent variances in the size, concentration, and protein content of EVs. Importantly, our study uniquely demonstrates the ability of EV isolation to detect specific biomarkers that remain undetected in whole saliva by WB. RT-qPCR analysis targeting six miRNAs confirmed a consistent enrichment of these miRNAs in EV-derived cargo across all three isolation methods. We also found that pre-filtering saliva samples with 0.22 or 0.45 um pores adversely affects subsequent analyses. Our findings highlight the untapped potential of salivary EVs in diagnostics and advocate for the co-precipitation method as an efficient, cost-effective, and clinically relevant approach for small-volume saliva samples. This work not only sheds light on a neglected source of EVs but also paves the way for their application in routine clinical diagnostics.

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Section: Protein Content-based Characterization Of Evs Isolated From ...mentioning

confidence: 99%

Salivary extracellular vesicles isolation methods impact the robustness of downstream biomarkers detection

Boulestreau,

Molina,

Ouedraogo

et al. 2024

Preprint

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Risk of Neonatal Hypoglycemia in Infants of Mothers With Gestational Glucose Intolerance

Andrews,

Maya,

Schulte

et al. 2024

Diabetes Care

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OBJECTIVE To examine the relationship between gestational glucose intolerance (GGI) and neonatal hypoglycemia. RESEARCH DESIGN AND METHODS This was a secondary analysis of 8,262 mother-infant dyads, with delivery at two hospitals between 2014 and 2023. We categorized maternal glycemic status as normal glucose tolerance (NGT), GGI, or gestational diabetes mellitus (GDM). We defined NGT according to a normal glucose load test result, GGI according to an abnormal glucose load test result with zero (GGI-0) or one (GGI-1) abnormal value on the 100-g oral glucose tolerance test, and GDM according to an abnormal glucose load test result with two or more abnormal values on the glucose tolerance test. Neonatal hypoglycemia was defined according to blood glucose <45 mg/dL or ICD-9 or ICD-10 diagnosis of neonatal hypoglycemia. We used logistic regression analysis to determine associations between maternal glucose tolerance category and neonatal hypoglycemia and conducted a sensitivity analysis using Δ-adjusted multiple imputation, assuming for unscreened infants a rate of neonatal hypoglycemia as high as 33%. RESULTS Of infants, 12% had neonatal hypoglycemia. In adjusted models, infants born to mothers with GGI-0 had 1.28 (95% 1.12, 1.65), GGI-1 1.58 (95% CI 1.11, 2.25), and GDM 4.90 (95% CI 3.81, 6.29) times higher odds of neonatal hypoglycemia in comparison with infants born to mothers with NGT. Associations in sensitivity analyses were consistent with the primary analysis. CONCLUSIONS GGI is associated with increased risk of neonatal hypoglycemia. Future research should include examination of these associations in a cohort with more complete neonatal blood glucose ascertainment and determination of the clinical significance of these findings on long-term child health.

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Plasma-glycated CD59 as an early biomarker for gestational diabetes mellitus: prospective cohort study protocol

Cited by 2 publications

References 36 publications

Salivary extracellular vesicles isolation methods impact the robustness of downstream biomarkers detection

Salivary extracellular vesicles isolation methods impact the robustness of downstream biomarkers detection

Risk of Neonatal Hypoglycemia in Infants of Mothers With Gestational Glucose Intolerance

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