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. 2024 Apr;389(1):34–39. doi: 10.1124/jpet.122.001253

Endothelial Extracellular Vesicles Enriched in microRNA-34a Predict New-Onset Diabetes in Coronavirus Disease 2019 (COVID-19) Patients: Novel Insights for Long COVID Metabolic Sequelae

Pasquale Mone 1, Stanislovas S Jankauskas 1, Maria Virginia Manzi 1, Jessica Gambardella 1, Antonietta Coppola 1, Urna Kansakar 1, Raffaele Izzo 1, Giuseppe Fiorentino 1, Angela Lombardi 1, Fahimeh Varzideh 1, Daniela Sorriento 1, Bruno Trimarco 1, Gaetano Santulli 1,✉
PMCID: PMC10949163  PMID: 38336381

Abstract

Emerging evidence indicates that the relationship between coronavirus disease 2019 (COVID-19) and diabetes is 2-fold: 1) it is known that the presence of diabetes and other metabolic alterations poses a considerably high risk to develop a severe COVID-19; 2) patients who survived a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have an increased risk of developing new-onset diabetes. However, the mechanisms underlying this association are mostly unknown, and there are no reliable biomarkers to predict the development of new-onset diabetes. In the present study, we demonstrate that a specific microRNA (miR-34a) contained in circulating extracellular vesicles released by endothelial cells reliably predicts the risk of developing new-onset diabetes in COVID-19. This association was independent of age, sex, body mass index (BMI), hypertension, dyslipidemia, smoking status, and D-dimer.

SIGNIFICANCE STATEMENT

We demonstrate for the first time that a specific microRNA (miR-34a) contained in circulating extracellular vesicles released by endothelial cells is able to reliably predict the risk of developing diabetes after having contracted coronavirus disease 2019 (COVID-19). This association was independent of age, sex, body mass index (BMI), hypertension, dyslipidemia, smoking status, and D-dimer. Our findings are also relevant when considering the emerging importance of post-acute sequelae of COVID-19, with systemic manifestations observed even months after viral negativization (long COVID).

Introduction

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to a global healthcare crisis: >110 million Americans and >700 million worldwide have been diagnosed as infected by SARS-CoV-2, leading to ∼1.2 million and ∼7 million deaths, respectively.

The relationship between COVID-19 and diabetes is 2-fold: although it is known that the presence of diabetes and other metabolic alterations poses a considerably high risk to develop a severe COVID-19 (Zhu et al., 2020; Kastora et al., 2022; Kazakou et al., 2022; Kim et al., 2022), emerging evidence indicates that patients who survived a SARS-CoV-2 infection have a significantly increased risk of developing new-onset diabetes (Rubino et al., 2020; Accili, 2021; Kamrath et al., 2021; Khunti et al., 2021; Metwally et al., 2021; Nassar et al., 2021; Sathish et al., 2021; Lai et al., 2022; Rahmati et al., 2022; Rathmann et al., 2022; Ssentongo et al., 2022; Steenblock et al., 2022; Wander et al., 2022; Xie and Al-Aly, 2022; Zhang et al., 2022; Abumayyaleh et al., 2023; Ali et al., 2023; Bellia et al., 2023; Cefalu, 2023; Chourasia et al., 2023; Gorchane et al., 2023; Izzo et al., 2023; Kim et al., 2023; Li et al., 2023; Naveed et al., 2023; O’Mahoney et al., 2022; Weiss et al., 2023; Zhou et al., 2023; Pantea Stoian et al., 2024; Trimarco et al., 2024). Of note, a retrospective analysis of more than 27 million patients (Cerner Real-World Data) revealed that COVID-19 is associated with an increased risk of diabetes and that Black, Asian/Pacific Islander, and American Indian/Alaskan Native populations are disproportionately at risk (Qeadan et al., 2022); a significant rise in new-onset type-2 diabetes has been observed among children and adolescents of Alabama during the COVID-19 pandemic (Schmitt et al., 2022); equally important, a meta-analysis has evidenced that the incidence of diabetic ketoacidosis among pediatric patients has significantly increased during COVID-19 pandemic (Alfayez et al., 2022).

Quantifying the expression levels of microRNAs (miRNAs) shuttled by extracellular vesicles (EVs) has been shown to be extremely valuable in clinical practice (Cha et al., 2021; Esmaeili et al., 2021; Gu et al., 2021; Liao et al., 2021; Liu et al., 2021; Papiewska-Pająk et al., 2021; Silvestro et al., 2021; Sonoda et al., 2021; Wang et al., 2021; Yang and Rhee, 2021; Chen et al., 2022; Pavani et al., 2022; Fullerton et al., 2023). We have recently demonstrated that endothelial EVs (EC-EVs) enriched in miR-24 independently predict cerebrovascular events in COVID-19 (Gambardella et al., 2021). In a preliminary assay comparing circulating levels of EC-EVs of COVID-19 patients who developed diabetes to COVID-19 patients who did not develop diabetes, we identified miR-34a as one of the top upregulated miRNAs. Therefore, we hypothesized the existence of a significant association between the onset of diabetes and plasma levels of EC-EV miR-34a in patients who have been hospitalized for COVID-19.

Materials and Methods

Study Design and Participants.

In this prospective study, we obtained plasma from consecutive patients hospitalized for COVID-19, enrolled at the “Ospedali dei Colli” in Naples, Italy. The diagnosis of diabetes was defined according to the guidelines of the American Diabetes Association (Draznin et al., 2022). The study was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.

Inclusion criteria: age >18 years old, willingness to participate (informed consent signed by each patient or an authorized representative), and diagnosis of COVID-19 confirmed by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) on nasal swab as described (Fiorentino et al., 2021; Gambardella et al., 2021; Trimarco et al., 2022, 2023).

Exclusion criteria: we excluded patients for whom admission blood samples were unavailable, patients with cancer, patients with a preexistent diagnosis of diabetes or prediabetes (Mone et al., 2023a), patients who were not treated with steroids, and patients who received the first diagnosis of diabetes fewer than 30 days after discontinuation of steroid-based treatments.

Experimental Procedures.

EC-EVs were isolated from plasma via serial centrifugation and magnetic isolation (Miltenyi Biotec, Auburn, CA) as we described and validated (Morelli et al., 2019; Wang et al., 2020; Gambardella et al., 2021), and DNA was extracted as reported earlier (Gambardella et al., 2021; Jankauskas et al., 2023; Mone et al., 2023b); EC-EVs miR-34a levels were quantified via droplet digital polymerase chain reaction (ddPCR) using a QX200 ddPCR System (Bio-Rad, Hercules, CA) following the manufacturer’s instructions. A SARS-CoV-2 test (RT-qPCR) was performed in all subjects to confirm or rule out the COVID-19 diagnosis. Blood levels of interleukin-6 (IL-6), D-dimer, high-sensitivity C-reactive protein (hs-CRP), and tumor necrosis factor α (TNFα) were measured in all patients on admission as we described (Fiorentino et al., 2021; Gambardella et al., 2021).

Statistical Analysis.

All data were analyzed using the SPSS software (version 29.0; SPSS, IBM, Armonk, NY), establishing a significant difference at a P value < 0.05. Data are expressed as means ± S.D. or numbers and percentages. The unpaired two-tailed t test using (when appropriate) Welch’s correction for unequal variances was performed. The χ2 test was applied to compare categorical variables. A multivariable linear regression analysis was used to assess the association between miR-34a and new-onset diabetes, adjusting for potential confounders. Receiver operating characteristic (ROC) curves were analyzed to identify the optimal cutoff value of miR-34a levels, calculating the Youden’s index to integrate sensitivity and specificity information, as we previously described (Santulli et al., 2019; Gambardella et al., 2022).

Results

We obtained plasma from 388 COVID-19 patients. We excluded 73 patients who did not fulfill the aforementioned inclusion/exclusion criteria; consequently, the study was conducted with 315 subjects, with a median follow up of 12 months.

Table 1 reports the main clinical parameters of our population. New onset diabetes was diagnosed in 28 COVID-19 patients. No significant differences in therapeutic management and in the presence of comorbidities were observed. As per our exclusion criteria, all subjects received steroids as standard therapy for hospitalized COVID-19 patients.

TABLE 1.

Main characteristics of our population at hospital admission Data on quantitative parameters are expressed as mean ± standard deviation or as median and interquartile range; data on qualitative characteristics are expressed as absolute numbers and percentage values.

No New-Onset Diabetes
(287)		 New-Onset Diabetes
(28)		 P
Age (years) 60.7 ± 14.1 64.28 ± 15.2 0.213
Sex (male, %) 156 (54.3) 14 (50) 0.660
BMI (kg/m2) 24.8 ± 3.4 26.2 ± 3.5 0.067
Glycemia (mg/dl) 100.2 ± 12.1 103.1 ± 23.6 0.281
SBP (mmHg) 137.76 ± 19.5 142.2 ± 19.3 0.114
DBP (mmHg) 84.46 ± 9.47 86.3 ± 14.9 0.239
Hypertension (%) 103 (35.9) 10 (35.7) 0.690
Dyslipidemia (%) 86 (29.9) 9 (32.1) 0.811
Current smoking (%) 126 (43.9) 12 (42.9) 0.916
Duration of steroid treatment (days) 7 (7, 9) 7 (7, 8) 0.843
Interval from steroid discontinuation (days) 166 (137, 193) 171 (140, 178) 0.929
D-dimer (μg/ml) 2.70 ± 1.6 2.94 ± 1.8 0.463
IL-6 (pg/ml) 7.5 ± 4.0# 8.4 ± 5.5# 0.121
TNFα (pg/ml) 6.5 ± 4.2 5.8 ± 4.7 0.271
hs-CRP (μg/ml) 3.6 ± 3.2# 4.2 ± 2.9# 0.144
EC-EV miR-34a (copies/10 nl) 1867.4 ± 1490 3485.8 ± 1998* 0.001
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BMI, body mass index; DBP, diastolic blood pressure; EC-EV miR-34a, level of miR-34a within endothelial extracellular vesicles; hs-CRP, high-sensitivity C-reactive protein; IL-6, interleukin-6; SBP, systolic blood pressure; TNFα, tumor necrosis factor α.

*P < 0.05.

We found that circulating levels of EC-EV miR-34a were significantly upregulated (P < 0.001) in patients with versus without new-onset diabetes (Table 1).

Applying ROC curves, we determined that 3300 copies/10 nl was the optimal cutoff value for miR-34a levels to predict new-onset diabetes, yielding the following results: sensitivity 71.43% [95% confidence interval (CI): 51.33% to 86.78%], specificity 98.61% (95% CI: 96.47% to 99.62%), positive predictive value 83.33% (95% CI: 64.76% to 93.15%), and negative predictive value 97.25% (95% CI: 95.17% to 98.45%).

Using a stepwise multiple regression analysis, adjusting for age, sex, body mass index (BMI), hypertension, dyslipidemia, smoking status, and D-dimer (Table 2), the association between EC-EV miR-34a and new-onset diabetes in COVID-19 patients was confirmed (P < 0.001).

TABLE 2.

Multivariable linear regression analysis assessing the association between miR-34a and new-onset diabetes in COVID-19 patients

B SE Beta t 95.0% CI for B P
Lower Bound Upper Bound
Age 0.002 0.001 0.103 1.859 0.000 0.004 0.064
Sex 0.000 0.032 0.000 −0.008 −0.063 0.062 0.993
BMI 0.007 0.004 0.090 1.665 −0.001 0.016 0.097
Hypertension −0.038 0.035 −0.063 −1.068 −0.107 0.032 0.286
Dyslipidemia 0.017 0.036 0.027 0.472 −0.054 0.088 0.637
Smoking 0.023 0.038 0.039 0.602 −0.051 0.097 0.548
D-Dimer 0.010 0.011 0.058 0.902 −0.012 0.032 0.368
EC-EV miR-34a 5.351 × 10−5 0.000 0.302 5.449 0.000 0.000 <0.001
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BMI, body mass index; EC-EV miR-34a, level of miR-34a within endothelial extracellular vesicles.

Discussion

To the best of our knowledge, this is the first study showing a significant association between EC-EV noncoding RNAs and new-onset diabetes in COVID-19 patients.

In the spring of 2020, we were among the first groups to indicate a link between COVID-19 and endothelial dysfunction (Gambardella et al., 2020; Santulli et al., 2020; Sardu et al., 2020), and our view was later confirmed by other investigators, associating the systemic manifestations of the disease to a direct or indirect involvement of the endothelium (D’Agnillo et al., 2021; Gelzo et al., 2021; Higashikuni et al., 2021; Kalicińska et al., 2021; Qin et al., 2021; Beltrán-Camacho et al., 2022; Casciola-Rosen et al., 2022; Haffke et al., 2022; Kelliher et al., 2022; Ma et al., 2022; Maldonado et al., 2022; Montiel et al., 2022; Otifi and Adiga, 2022; Santoro et al., 2022; Seitz and Ong, 2022; Tarnawski and Ahluwalia, 2022). Indeed, endothelial cells (ECs) express all cofactors necessary for the internalization of SARS-CoV-2 in host cells, including angiotensin-converting enzyme 2 (ACE2), transmembrane protease serine 2, cathepsins B and D, neuropilin-1, vimentin, and others, thereby representing a natural target of SARS-CoV-2 (Gambardella and Santulli, 2021; Mone et al., 2021; Kansakar et al., 2022; Gambardella et al., 2023). Furthermore, the systemic inflammatory viral reaction observed in patients affected by COVID-19 has been shown to be linked to endothelial dysfunction (Bernard et al., 2020; Loo et al., 2021; Sabioni et al., 2021). Hence, COVID-19 affects not only the epithelial cells of the lung parenchyma but also ECs across the whole body, thus leading to a generalized endothelial damage. Such a damage, caused directly by SARS-CoV-2 infection and/or by the ensuing cytokine storm, can shift the vascular equilibrium toward an altered vascular tone and an increased permeabilization; most of these findings have been substantiated from autopsies of COVID-19 patients since the pandemic outbreak (Otifi and Adiga, 2022). Further supporting our theory of a central role of ECs in COVID-19, clinical trials testing whether interventions that ameliorate endothelial dysfunction can have beneficial effects in COVID-19 patients are ongoing and the available results are very encouraging (Adebayo et al., 2021; Fiorentino et al., 2021; Trimarco et al., 2023).

Consistent with our findings, a significantly augmented risk of newly diagnosed diabetes after SARS-CoV-2 infection, independent of steroid use (which was instead linked to transient hyperglycemia), has been recently demonstrated in a large study (Barrett et al., 2022) performed by the Centers for Disease Control and Prevention (CDC). Current COVID-19 guidelines recommend the use of steroids in hospitalized patients up to 10 days or until discharge and should not be prescribed beyond discharge (Huang et al., 2022). Notably, in our study we ruled out cases of transient hyperglycemia due to steroids by including only patients in which the first diagnosis of new-onset diabetes had been formulated at least 1 month after the discontinuation steroid-based therapies.

A Nature paper (Al-Aly et al., 2021) demonstrated that survivors of COVID-19 had a 39% increased likelihood of receiving a new diabetes diagnosis within 6 months after infection compared with noninfected patients (Al-Aly et al., 2021); the cohort included 73,435 COVID-19 patients of the Veterans Health Administration and ∼5 million control subjects who did not have COVID-19 (Al-Aly et al., 2021). The same team of researchers lately published another paper evidencing that people with COVID-19 exhibit an augmented risk of new-onset diabetes that increased according to the severity of the infection as proxied by the care setting: nonhospitalized, hospitalized, and admitted to intensive care (Xie and Al-Aly, 2022). Another study conducted in 47,780 hospitalized patients with COVID-19 found out that these patients had a ∼50% increased likelihood of developing diabetes ∼20 weeks after discharge compared with matched control patients (Ayoubkhani et al., 2021). In full alignment with these reports, we demonstrated in a population of more than 200,000 individuals that the risk of new-onset diabetes is markedly increased when comparing the years of the pandemic (2020–2022) to the triennium 2017–2019 (Izzo et al., 2023). All of these findings provide solid support for a diabetogenic effect of COVID-19 beyond the stress response associated with severe illness.

Our results are particularly relevant if we consider that chronic manifestations of the disease, including metabolic disturbances, have been reported even months after the initial infection occurred (“long COVID”) (Feldman et al., 2020; Iqbal et al., 2021; Montefusco et al., 2021; Raveendran and Misra, 2021; Sathish et al., 2021a; Narayan and Staimez, 2022; Scherer et al., 2022).

Our study is not exempt from limitations, including the relatively small size of our population and brief follow-up; moreover, our findings refer exclusively to hospitalized COVID-19 patients and therefore cannot be generalized to subjects with a mild disease. We also reckon that the exact molecular mechanisms linking EC-EV miR-34a to the development of diabetes need to be defined in dedicated research projects, whereas our study merely identified miR-34a as a novel and independent biomarker of disease; nonetheless, a biomarker-centric approach has been shown to be crucial in drug development (Fader et al., 2021).

In conclusion, we identified a significant association between EC-EV miR-34a and new-onset diabetes, which could be instrumental toward the understanding of the molecular mechanisms underlying the pathophysiology of metabolic complications in COVID-19 as well as long COVID. Further analyses in larger groups are warranted to confirm our results, ratify their prognostic value, and explore the potential role of miR-34a in other metabolic events.

Acknowledgments

The authors thank X. Wang for valuable assistance.

Abbreviations

CI

confidence interval

COVID-19

coronavirus disease 2019

EC

endothelial cell

EC-EV

endothelial extracellular vesicle

EV

extracellular vesicle

SARS-CoV-2

severe acute respiratory syndrome coronavirus 2

Authorship Contributions

Participated in research design: Jankauskas, Gambardella, Santulli.

Conducted experiments: Mone, Jankauskas, Manzi, Gambardella, Coppola, Kansakar, Fiorentino, Lombardi, Varzideh, Sorriento, Trimarco, Santulli.

Contributed new reagents or analytic tools: Mone, Jankauskas, Manzi, Gambardella, Coppola, Kansakar, Fiorentino, Lombardi, Varzideh, Sorriento, Trimarco, Santulli.

Performed data analysis: Izzo, Santulli.

Wrote or contributed to the writing of the manuscript: Mone, Jankauskas, Santulli.

Footnotes

Santulli’s Laboratory is supported in part by National Institutes of Health National Heart, Lung, and Blood Institute [Grant R01-HL159062], [Grant R01-HL146691], and [Grant T32-HL144456] and National Institute of Diabetes and Digestive and Kidney Diseases [Grant R01-DK123259] and [Grant R01-DK033823] (to G.S.), by the Diabetes Action Research and Education Foundation (to G.S.), by the Samuel Waxman Foundation (to G.S.), and by the Monique Weill-Caulier and Irma T. Hirschl Trusts (to G.S.). This publication was also produced with the cofunding of the European Union – Next Generation EU, in the context of The National Recovery and Resilience Plan, PE8 Investment, Project Age-It (Ageing Well in an Ageing Society) (to P.M.). S.S.J., J.G., U.K., and F.V. are supported in part by postdoctoral fellowships of the American Heart Association (AHA-836407, AHA-35211151, AHA-1026190, and AHA-241195524).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

1P.M., S.S.J., and M.V.M. share the first authorship.

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