Funding:
This work was supported by the European Union’s Horizon 2020 research
and innovation program by grant No 860329 (Marie-Curie ITN
“STRATEGY-CKD”) and No 848011 (“DC-ren”).
References: [1] Cho, N. H., Shaw, J. E.,
Karuranga, S., Huang, Y., et al. , IDF Diabetes Atlas: Global
estimates of diabetes prevalence for 2017 and projections for 2045.Diabetes research and clinical practice 2018, 138 ,
271-281.
[2] Sun, H., Saeedi, P.,
Karuranga, S., Pinkepank, M., et al. , IDF Diabetes Atlas:
Global, regional and country-level diabetes prevalence estimates for
2021 and projections for 2045. Diabetes research and clinical
practice 2022, 183 , 109119.
[3] Kotwas, A., Karakiewicz, B.,
Zabielska, P., Wieder-Huszla, S., Jurczak, A., Epidemiological factors
for type 2 diabetes mellitus: evidence from the Global Burden of
Disease. Archives of public health = Archives belges de sante
publique 2021, 79 , 110.
[4] Tinajero, M. G., Malik, V.
S., An Update on the Epidemiology of Type 2 Diabetes: A Global
Perspective. Endocrinology and metabolism clinics of North
America 2021, 50 , 337-355.
[5] Schmidt, A. M., Highlighting
Diabetes Mellitus: The Epidemic Continues. Arteriosclerosis,
thrombosis, and vascular biology 2018, 38 , e1-e8.
[6] Beckman, J. A., Creager, M.
A., Vascular Complications of Diabetes. Circulation research2016, 118 , 1771-1785.
[7] Thipsawat, S., Early
detection of diabetic nephropathy in patient with type 2 diabetes
mellitus: A review of the literature. Diabetes & vascular
disease research 2021, 18 , 14791641211058856.
[8] Nauck, M. A., Wefers, J.,
Meier, J. J., Treatment of type 2 diabetes: challenges, hopes, and
anticipated successes. The lancet. Diabetes & endocrinology2021, 9 , 525-544.
[9] Vilsboll, T., Christensen,
M., Junker, A. E., Knop, F. K., Gluud, L. L., Effects of glucagon-like
peptide-1 receptor agonists on weight loss: systematic review and
meta-analyses of randomised controlled trials. BMJ 2012,344 , d7771.
[10] Mokdad, A. H., Ford, E.
S., Bowman, B. A., Dietz, W. H., et al. , Prevalence of obesity,
diabetes, and obesity-related health risk factors, 2001. Jama2003, 289 , 76-79.
[11] Iqbal, J., Wu, H. X., Hu,
N., Zhou, Y. H., et al. , Effect of glucagon-like peptide-1
receptor agonists on body weight in adults with obesity without
diabetes mellitus-a systematic review and meta-analysis of randomized
control trials. Obesity reviews : an official journal of the
International Association for the Study of Obesity 2022, 23 ,
e13435.
[12] Artasensi, A., Pedretti,
A., Vistoli, G., Fumagalli, L., Type 2 Diabetes Mellitus: A Review of
Multi-Target Drugs. Molecules 2020, 25 .
[13] ElSayed, N. A., Aleppo,
G., Aroda, V. R., Bannuru, R. R., et al. , 1. Improving Care and
Promoting Health in Populations: Standards of Care in Diabetes-2023.Diabetes care 2023, 46 , S10-S18.
[14] Sheahan, K. H., Wahlberg,
E. A., Gilbert, M. P., An overview of GLP-1 agonists and recent
cardiovascular outcomes trials. Postgraduate medical journal2020, 96 , 156-161.
[15] DeFronzo, R. A., Triplitt,
C. L., Abdul-Ghani, M., Cersosimo, E., Novel Agents for the Treatment
of Type 2 Diabetes. Diabetes spectrum : a publication of the
American Diabetes Association 2014, 27 , 100-112.
[16] Abdul-Ghani, M., DeFronzo,
R. A., Is It Time to Change the Type 2 Diabetes Treatment Paradigm?
Yes! GLP-1 RAs Should Replace Metformin in the Type 2 Diabetes
Algorithm. Diabetes care 2017, 40 , 1121-1127.
[17] Brunton, S. A., Wysham, C.
H., GLP-1 receptor agonists in the treatment of type 2 diabetes: role
and clinical experience to date. Postgraduate medicine 2020,132 , 3-14.
[18] Defronzo, R. A., Banting
Lecture. From the triumvirate to the ominous octet: a new paradigm for
the treatment of type 2 diabetes mellitus. Diabetes 2009,58 , 773-795.
[19] Taylor, S. I., Yazdi, Z.
S., Beitelshees, A. L., Pharmacological treatment of hyperglycemia in
type 2 diabetes. The Journal of clinical investigation 2021,131 .
[20] Holst, J. J., The
physiology of glucagon-like peptide 1. Physiological reviews2007, 87 , 1409-1439.
[21] Gentilella, R., Pechtner,
V., Corcos, A., Consoli, A., Glucagon-like peptide-1 receptor agonists
in type 2 diabetes treatment: are they all the same?Diabetes/metabolism research and reviews 2019, 35 ,
e3070.
[22] Greco, E. V., Russo, G.,
Giandalia, A., Viazzi, F., et al. , GLP-1 Receptor Agonists and
Kidney Protection. Medicina (Kaunas) 2019, 55 .
[23] Nauck, M. A., Quast, D.
R., Wefers, J., Meier, J. J., GLP-1 receptor agonists in the treatment
of type 2 diabetes - state-of-the-art. Molecular metabolism2021, 46 , 101102.
[24] Trujillo, J. M., Nuffer,
W., Smith, B. A., GLP-1 receptor agonists: an updated review of
head-to-head clinical studies. Therapeutic advances in
endocrinology and metabolism 2021, 12 , 2042018821997320.
[25] Sirolli, V., Pieroni, L.,
Di Liberato, L., Urbani, A., Bonomini, M., Urinary Peptidomic
Biomarkers in Kidney Diseases. International journal of
molecular sciences 2019, 21 .
[26] Latosinska, A., Siwy, J.,
Faguer, S., Beige, J., et al. , Value of Urine Peptides in
Assessing Kidney and Cardiovascular Disease. Proteomics.
Clinical applications 2021, 15 , e2000027.
[27] Siwy, J., Klein, T.,
Rosler, M., von Eynatten, M., Urinary Proteomics as a Tool to Identify
Kidney Responders to Dipeptidyl Peptidase-4 Inhibition: A
Hypothesis-Generating Analysis from the MARLINA-T2D Trial.Proteomics. Clinical applications 2019, 13 , e1800144.
[28] Eder, S., Leierer, J.,
Kerschbaum, J., Rosivall, L., et al. , A Prospective Cohort
Study in Patients with Type 2 Diabetes Mellitus for Validation of
Biomarkers (PROVALID) - Study Design and Baseline Characteristics.Kidney & blood pressure research 2018, 43 , 181-190.
[29] Latosinska, A., Siwy, J.,
Cherney, D. Z., Perkins, B. A., et al. , SGLT2-Inhibition
reverts urinary peptide changes associated with severe COVID-19: An
in-silico proof-of-principle of proteomics-based drug repurposing.Proteomics 2021, 21 , e2100160.
[30] Frantzi, M., Gomez Gomez,
E., Blanca Pedregosa, A., Valero Rosa, J., et al. , CE-MS-based
urinary biomarkers to distinguish non-significant from significant
prostate cancer. British journal of cancer 2019, 120 ,
1120-1128.
[31] Zurbig, P., Renfrow, M.
B., Schiffer, E., Novak, J., et al. , Biomarker discovery by
CE-MS enables sequence analysis via MS/MS with platform-independent
separation. Electrophoresis 2006, 27 , 2111-2125.
[32] Mischak, H., Vlahou, A.,
Ioannidis, J. P., Technical aspects and inter-laboratory variability
in native peptide profiling: the CE-MS experience. Clinical
biochemistry 2013, 46 , 432-443.
[33] Jantos-Siwy, J., Schiffer,
E., Brand, K., Schumann, G., et al. , Quantitative urinary
proteome analysis for biomarker evaluation in chronic kidney disease.Journal of proteome research 2009, 8 , 268-281.
[34] Schanstra, J. P., Zurbig,
P., Alkhalaf, A., Argiles, A., et al. , Diagnosis and Prediction
of CKD Progression by Assessment of Urinary Peptides. Journal of
the American Society of Nephrology : JASN 2015, 26 , 1999-2010.
[35] Klein, J., Papadopoulos,
T., Mischak, H., Mullen, W., Comparison of CE-MS/MS and LC-MS/MS
sequencing demonstrates significant complementarity in natural peptide
identification in human urine. Electrophoresis 2014, 35 ,
1060-1064.
[36] Benjamini, Y., Hochberg,
Y., Controlling the False Discovery Rate - a Practical and Powerful
Approach to Multiple Testing. J R Stat Soc B 1995, 57 ,
289-300.
[37] Mavrogeorgis, E., Mischak,
H., Latosinska, A., Siwy, J., et al. , Reproducibility
Evaluation of Urinary Peptide Detection Using CE-MS. Molecules2021, 26 .
[38] Klein, J., Eales, J.,
Zurbig, P., Vlahou, A., et al. , Proteasix: a tool for automated
and large-scale prediction of proteases involved in naturally
occurring peptide generation. Proteomics 2013, 13 ,
1077-1082.
[39] Franceschini, A.,
Szklarczyk, D., Frankild, S., Kuhn, M., et al. , STRING v9.1:
protein-protein interaction networks, with increased coverage and
integration. Nucleic acids research 2013, 41 , D808-815.
[40] von Mering, C., Jensen, L.
J., Snel, B., Hooper, S. D., et al. , STRING: known and
predicted protein-protein associations, integrated and transferred
across organisms. Nucleic acids research 2005, 33 ,
D433-437.
[41] He, T., Pejchinovski, M.,
Mullen, W., Beige, J., et al. , Peptides in Plasma, Urine, and
Dialysate: Toward Unravelling Renal Peptide Handling.Proteomics. Clinical applications 2021, 15 , e2000029.
[42] Mavrogeorgis, E., Mischak,
H., Latosinska, A., Vlahou, A., et al. , Collagen-Derived
Peptides in CKD: A Link to Fibrosis. Toxins 2021, 14 .
[43] Rossing, K., Mischak, H.,
Dakna, M., Zurbig, P., et al. , Urinary proteomics in diabetes
and CKD. Journal of the American Society of Nephrology : JASN2008, 19 , 1283-1290.
[44] Genovese, F., Manresa, A.
A., Leeming, D. J., Karsdal, M. A., Boor, P., The extracellular matrix
in the kidney: a source of novel non-invasive biomarkers of kidney
fibrosis? Fibrogenesis & tissue repair 2014, 7 , 4.
[45] Ding, H. X., Dong, N. X.,
Zhou, C. X., Wang, F. J., et al. , Liraglutide Attenuates
Restenosis After Vascular Injury in Rabbits With Diabetes Via the
TGF-beta/Smad3 Signaling Pathway. Alternative therapies in
health and medicine 2022, 28 , 22-28.
[46] Cardoso, L. E. M.,
Marinho, T. S., Martins, F. F., Aguila, M. B., Mandarim-de-Lacerda, C.
A., Treatment with semaglutide, a GLP-1 receptor agonist, improves
extracellular matrix remodeling in the pancreatic islet of
diet-induced obese mice. Life sciences 2023, 319 ,
121502.
[47] Gallego-Colon, E.,
Klych-Ratuszny, A., Kosowska, A., Garczorz, W., et al. ,
Exenatide modulates metalloproteinase expression in human cardiac
smooth muscle cells via the inhibition of Akt signaling pathway.Pharmacological reports : PR 2018, 70 , 178-183.
[48] Garczorz, W.,
Gallego-Colon, E., Kosowska, A., Siemianowicz, K., et al. ,
Exenatide modulates expression of metalloproteinases and their tissue
inhibitors in TNF-alpha stimulated human retinal pigment epithelial
cells. Pharmacological reports : PR 2019, 71 , 175-182.
[49] Dehghan, F., Soori, R.,
Gholami, K., Abolmaesoomi, M., et al. , Purslane (Portulaca
oleracea) Seed Consumption And Aerobic Training Improves Biomarkers
Associated with Atherosclerosis in Women with Type 2 Diabetes (T2D).Scientific reports 2016, 6 , 37819.
[50] Li, H., Chen, J., Li, B.,
Fang, X., The protective effects of dulaglutide against advanced
glycation end products (AGEs)-induced degradation of type Ⅱ collagen
and aggrecan in human SW1353 chondrocytes. Chemico-biological
interactions 2020, 322 , 108968.
[51] Tao, Y., Ge, G., Wang, Q.,
Wang, W., et al. , Exenatide ameliorates inflammatory response
in human rheumatoid arthritis fibroblast-like synoviocytes.IUBMB life 2019, 71 , 969-977.
[52] Rafiullah, M.,
Benabdelkamel, H., Masood, A., Ekhzaimy, A. A., et al. , Urinary
Proteome Differences in Patients with Type 2 Diabetes Pre and Post
Liraglutide Treatment. Current issues in molecular biology2023, 45 , 1407-1421.
[53] Adiels, M., Taskinen, M.
R., Bjornson, E., Andersson, L., et al. , Role of apolipoprotein
C-III overproduction in diabetic dyslipidaemia. Diabetes,
obesity & metabolism 2019, 21 , 1861-1870.
[54] Marques, E. S., Formato,
E., Liang, W., Leonard, E., Timme-Laragy, A. R., Relationships between
type 2 diabetes, cell dysfunction, and redox signaling: A
meta-analysis of single-cell gene expression of human pancreatic
alpha- and beta-cells. Journal of diabetes 2022, 14 ,
34-51.
[55] Pasello, M., Manara, M.
C., Scotlandi, K., CD99 at the crossroads of physiology and pathology.Journal of cell communication and signaling 2018, 12 ,
55-68.
[56] Yang, K., Sun, J., Zhang,
Z., Xiao, M., et al. , Reduction of mRNA m(6)A associates with
glucose metabolism via YTHDC1 in human and mice. Diabetes
research and clinical practice 2023, 198 , 110607.
[57] Gluvic, Z., Obradovic, M.,
Lackovic, M., Samardzic, V., et al. , HbA1C as a marker of
retrograde glycaemic control in diabetes patient with co-existed
beta-thalassaemia: A case report and a literature review.Journal of clinical pharmacy and therapeutics 2020, 45 ,
379-383.
[58] Pandey, G. K.,
Balasubramanyam, J., Balakumar, M., Deepa, M., et al. , Altered
Circulating Levels of Retinol Binding Protein 4 and Transthyretin in
Relation to Insulin Resistance, Obesity, and Glucose Intolerance in
Asian Indians. Endocrine practice : official journal of the
American College of Endocrinology and the American Association of
Clinical Endocrinologists 2015, 21 , 861-869.
[59] Hu, X., Guo, Q., Wang, X.,
Wang, Q., et al. , Plasma Transthyretin Levels and Risk of Type
2 Diabetes Mellitus and Impaired Glucose Regulation in a Chinese
Population. Nutrients 2022, 14 .
[60] Fernandez-Real, J. M.,
Grasa, M., Casamitjana, R., Pugeat, M., et al. , Plasma total
and glycosylated corticosteroid-binding globulin levels are associated
with insulin secretion. The Journal of clinical endocrinology
and metabolism 1999, 84 , 3192-3196.
[61] Fernandez-Real, J. M.,
Pugeat, M., Grasa, M., Broch, M., et al. , Serum
corticosteroid-binding globulin concentration and insulin resistance
syndrome: a population study. The Journal of clinical
endocrinology and metabolism 2002, 87 , 4686-4690.
[62] Benchoula, K., Parhar, I.
S., Hwa, W. E., The molecular mechanism of vgf in appetite, lipids,
and insulin regulation. Pharmacological research 2021,172 , 105855.
[63] Derezanin, L., Blazyte,
A., Dobrynin, P., Duchene, D. A., et al. , Multiple types of
genomic variation contribute to adaptive traits in the mustelid
subfamily Guloninae. Molecular ecology 2022, 31 ,
2898-2919.
[64] Sundkvist, A., Myte, R.,
Boden, S., Enroth, S., et al. , Targeted plasma proteomics
identifies a novel, robust association between cornulin and Swedish
moist snuff. Scientific reports 2018, 8 , 2320.
[65] Odum, E. P., Young, E. E.,
Elevated cardiac troponin I, creatine kinase and myoglobin and their
relationship with cardiovascular risk factors in patients with type 2
diabetes. Diabetes & metabolic syndrome 2018, 12 ,
141-145.
[66] Wu, R., Shu, Z., Zou, F.,
Zhao, S., et al. , Identifying myoglobin as a mediator of
diabetic kidney disease: a machine learning-based cross-sectional
study. Scientific reports 2022, 12 , 21411.
[67] Krawczyk, K. M., Nilsson,
H., Nystrom, J., Lindgren, D., et al. , Localization and
Regulation of Polymeric Ig Receptor in Healthy and Diseased Human
Kidney. The American journal of pathology 2019, 189 ,
1933-1944.
[68] He, T., Mischak, M.,
Clark, A. L., Campbell, R. T., et al. , Urinary peptides in
heart failure: a link to molecular pathophysiology. European
journal of heart failure 2021, 23 , 1875-1887.
Legends to Figures
Figure 1: Study design. Urine samples from thirty-two
T2DM patients were collected at two time points: pre-treatment and
post-treatment with the intervention of GLP-1R agonists at 4.4 ± 4.11
months from first sample collection. Naturally occurring urinary
peptides were quantified in the urine samples by CE-MS analysis,
followed by statistical and bioinformatic analysis of the CE-MS
generated urinary peptide profiles.
Figure 2 : Results of the urinary peptidomic analysis.(A) Distribution of peptide intensity for all the 329 sequenced urinary
peptides identified in this study, red dots indicate the statistically
significant peptides. (B) Volcano plot depicting the regulation of the
329 peptides in response to GLP-1R agonist treatment. (C) Urinary
peptide profiles of the 70 significant peptides in pre-treatment, as
obtained from CE-MS analysis. (D) Urinary peptide profiles of the 70
significant peptides in post-treatment, as obtained from CE-MS analysis.
(E) Box and Whisker plots depicting the down-regulation of all the
COL1A1 peptides, in response to GLP-1R agonists treatment. (F) Box and
Whisker plots depicting the up- and down-regulation of all the COL3A1
peptides, in response to GLP-1R agonists treatment. (G) Alignment of
identified peptide sequences in the primary structure of protein COL1A1.
(H) Alignment of identified peptide sequences in this study in the
primary structure of protein COL3A1. (I) Protein-protein interaction
network including the 26 parental proteins giving the origin to 70
GLP-1R agonists-associated peptides. In, (G) and (H), the amino
acids in green and red depict the down-regulated and up-regulated
peptide sequences, respectively.
Figure 3: Hypothesis. The beneficial effects of GLP-1R
agonists treatment on the different pathophysiological pathways
associated with T2DM as suggested by the role of the down-regulated
non-collagen peptides, respectively in each pathway.
Tables
Table 1: Clinical information of the T2DM patients in mean ±
SD; from pre- and post-treatment with GLP-1R agonists