Expression of plasma microRNA in patients with acromegaly

Cover Page
Open Access Open Access
Restricted Access Subscription Access

Abstract


BACKGROUND: microRNA is a class of small non-coding RNA molecules involved in posttranscriptional regulation of gene expression. MicroRNAs are detectable in blood in stable concentrations, which makes them promising biomarkers for various diseases.

AIM: to assess plasma microRNA expression in patients with active acromegaly compared with healthy controls.

MATERIAL AND METHODS: single-center, case-control study: assessment of plasma microRNA in patients with acromegaly compared with healthy controls. Fasting blood samples were drawn and centrifuged at +5°С temperature and 3000 rpm for 20 minutes, then aliquoted and frozen at –80°C until further analysis. MicroRNA extraction and library preparation was done according to manufacturer’s instructions. Expression analysis was performed on NextSeq sequencer. Bioinformatic analysis using atropos (adapted deletion), STAR (aligning), FastQC (quality control), seqbuster/seqcluster/miRge2 (microRNA annotation, isomiR and new microRNA search, expression analysis). Primary endpoint of the study – differential expression of plasma microRNA in patients with acromegaly compared with healthy controls.

RESULTS: we included 12 patients with acromegaly – age 33.1 [20; 47], BMI 29.3 kg/m2 [24.0; 39.6], IGF-1 686.1 ng/mL [405.9; 1186.0] and 12 healthy subjects – age 36.2 [26; 44], BMI 26.7 kg/m2 [19.5; 42.5], IGF-1 210.4 ng/mL [89.76; 281.90]; gender ratio for both groups – 4 males, 8 females. The groups did not differ in gender (p=0.666), age (p=0.551) and BMI (p=0.378). We found decreased expression of four microRNAs in patients with acromegaly: miR-4446-3p –1.317 (p=0.001), miR-215-5p –3.040 (p=0.005), miR-342-5p –1.875 (p=0.013) and miR-191-5p –0.549 (p=0.039). However, none of these changes were statistically significant after adjustment for multiple comparisons (q >0.1).

CONCLUSION: we found four microRNAs, which could potentially be downregulated in plasma of patients with acromegaly. The result need to be validated using different measurement method with larger sample size.


Alexander S. Lutsenko

Endocrinology Research Centre

Author for correspondence.
Email: some91@mail.ru
ORCID iD: 0000-0002-9314-7831
SPIN-code: 4037-1030

Russian Federation, 11, Dm. Ulyanova street, Moscow, 117036

research scientist of neuroendocrinology and bone diseases department

Zhanna E. Belaya

Endocrinology Research Centre

Email: jannabelaya@gmail.com
ORCID iD: 0000-0002-6674-6441
SPIN-code: 4746-7173

Russian Federation, 11 Dm. Ulyanova street, 117036 Moscow

MD, PhD, Professor

Elena G. Przhiyalkovskaya

Endocrinology Research Centre

Email: przhiyalkovskaya.elena@gmail.com
ORCID iD: 0000-0001-9119-2447
SPIN-code: 9309-3256

Russian Federation, 11, Dm. Ulyanova street, Moscow, 117036

PhD

Alexey G. Nikitin

Pulmonology Scientific Research Institute under FMBA of Russia

Email: avialn@gmail.com
ORCID iD: 0000-0001-9762-3383
SPIN-code: 3367-0680

Russian Federation, 28, Orekhovy boulevard, Moscow, 115682

PhD

Philipp A. Koshkin

Center of medical genetics «Genomed»

Email: philipkoshkin@gmail.com
ORCID iD: 0000-0001-9512-9277
SPIN-code: 5627-2121

Russian Federation, 5-8, Podolskoe h., Moscow, 115093

PhD

Anastasiya M. Lapshina

Endocrinology Research Centre

Email: nottoforget@yandex.ru
ORCID iD: 0000-0003-4353-6705
SPIN-code: 1582-5033

Russian Federation, 11 Dm. Ulyanova street, 117036, Moscow

MD, PhD

Patimat M. Khandaeva

Endocrinology Research Centre

Email: pati_khandaeva@mail.ru
ORCID iD: 0000-0002-6993-5096
SPIN-code: 6950-5200
http://russianyes.com/khandaeva-patimat-magomedovna/

Russian Federation, 11, Dmitriya Ulyanova Street, Moscow, 117036

Research Scientist of Neuroendocrinological department

Galina A. Melnichenko

Endocrinology Research Centre

Email: teofrast2000@mail.ru
ORCID iD: 0000-0002-5634-7877
SPIN-code: 8615-0038

Russian Federation, 11 Dm. Ulyanova street, 117036 Moscow

MD, PhD, Professor

  1. Lavrentaki A, Paluzzi A, Wass JA, Karavitaki N. Epidemiology of acromegaly: review of population studies. Pituitary. 2017;20(1):4-9. doi: https://doi.org/10.1007/s11102-016-0754-x
  2. Pivonello R, Auriemma RS, Grasso LF, et al. Complications of acromegaly: cardiovascular, respiratory and metabolic comorbidities. Pituitary. 2017;20(1):46-62. doi: https://doi.org/10.1007/s11102-017-0797-7
  3. Melmed S, Bronstein MD, Chanson P, et al. A consensus statement on acromegaly therapeutic outcomes. Nat Rev Endocrinol. 2018;14(9):552-561 doi: https://doi.org/10.1038/s41574-018-0058-5.
  4. Sherlock M, Woods C, Sheppard MC. Medical therapy in acromegaly. Nat Rev Endocrinol. 2011;7(5):291300. doi: https://doi.org/10.1038/nrendo.2011.42
  5. Sohel MH. Extracellular/circulating microRNAs: release mechanisms, functions and challenges. Achiev Life Sci. 2016;10(2): 175-186. doi: https://doi.org/10.1016/j.als.2016.11.007
  6. Bottoni A, Piccin D, Tagliati F, et al. miR-15a and miR-16-1 down-regulation in pituitary adenomas. J Cell Physiol. 2005; 204(1):280-285. doi: https://doi.org/10.1002/jcp.20282
  7. Луценко А.С., Белая Ж.Е., Пржиялковская Е.Г., Мельниченко Г.А. МикроРНК и их значение в патогенезе СТГ-продуцирующих аденом гипофиза // Вестник РАМН. – 2017. – Т.72. – №4. – С. 290–298. [Lutsenko AS, Belaya ZE, Przhiyalkovskaya EG, Mel’nichenko GA. MicroRNA: role in GH-secreting pituitary adenoma pathogenesis. Annals of the Russian Academy of Medical Sciences. 2017;72(4):290-298. (In Russ).] doi: https://doi.org/10.15690/vramn856
  8. Pritchard CC, Cheng HH, Tewari M. MicroRNA profiling: approaches and considerations. Nat Rev Genet. 2012;13(5):358-369. doi: https://doi.org/10.1038/nrg3198
  9. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550. doi: https://doi.org/10.1186/s13059-014-0550-8.
  10. Гребенникова Т.А., Белая Ж.Е., Никитин А.Г., и др. Экспрессия микроРНК, регулирующих костное ремоделирование, в плазме крови у пациентов с акромегалией // Ожирение и метаболизм. – 2017 – Т.14 – №3. – С. 32-37. [Grebennikova TA, Belaya ZhE, Nikitin AG, et al. Expression of microRNA related to bone remodeling regulation in plasma in patients with acromegaly. Obesity and metabolism. 2017;14(3):32-37. (In Russ).] doi: https://doi.org/10.14341/omet2017332-37
  11. Valassi E, García-Giralt N, Malouf J, et al. Circulating miR-103a-3p and miR-660-5p are associated with bone parameters in patients with controlled acromegaly. Endocr Connect. 2019;8(1):39-49. doi: https://doi.org/10.1530/EC-18-0482
  12. Feng Y, Mao Z, Wang X, et al. MicroRNAs and target genes in pituitary adenomas. Horm Metab Res. 2018;50(3):179-192. doi: https://doi.org/10.1055/s-0043-123763
  13. Farina NH, Ramsey JE, Cuke ME, et al. Development of a predictive miRNA signature for breast cancer risk among high-risk women. Oncotarget. 2017;8(68):112170-112183. doi: https://doi.org/10.18632/oncotarget.22750
  14. Kim BG, Kang S, Han HH, et al. Transcriptome-wide analysis of compression-induced microRNA expression alteration in breast cancer for mining therapeutic targets. Oncotarget. 2016;7(19): 27468-27478. doi: https://doi.org/10.18632/oncotarget.8322
  15. Wang J, Tan L, Tan L, et al. Circulating microRNAs are promising novel biomarkers for drug-resistant epilepsy. Sci Rep. 2015;5:10201. doi: https://doi.org/10.1038/srep10201
  16. Monterde-Cruz L, Ramírez-Salazar EG, Rico-Martínez G, et al. Circulating miR-215-5p and miR-642a-5p as potential biomarker for diagnosis of osteosarcoma in Mexican population. Hum Cell. 2018;31(4):292-299. doi: https://doi.org/10.1007/s13577-018-0214-1
  17. Vychytilova-Faltejskova P, Merhautova J, Machackova T, et al. MiR-215-5p is a tumor suppressor in colorectal cancer targeting EGFR ligand epiregulin and its transcriptional inducer HOXB9. Oncogenesis. 2017;6(11):399. doi: https://doi.org/10.1038/s41389-017-0006-6
  18. Ahmadi R, Heidarian E, Fadaei R, et al. miR-342-5p expression levels in coronary artery disease patients and its association with inflammatory cytokines. Clin Lab. 2018;64(4):603-609. doi: https://doi.org/10.7754/Clin.Lab.2017.171208.
  19. Yan X, Cao J, Liang L, et al. miR-342-5p is a notch downstream molecule and regulates multiple angiogenic pathways including notch, vascular endothelial growth factor and transforming growth factor β signaling. J Am Heart Assoc. 2016;5(2). pii: e003042. doi: https://doi.org/10.1161/JAHA.115.003042
  20. Yang H, Li Q, Niu J, et al. MicroRNA-342-5p and miR-608 inhibit colon cancer tumorigenesis by targeting NAA10. Oncotarget. 2016;7(3):2709-2720. doi: https://doi.org/10.18632/oncotarget.6458
  21. Rosignolo F, Sponziello M, Giacomelli L, et al. Identification of thyroid-associated serum microrna profiles and their potential use in thyroid cancer follow-up. J Endocr Soc. 2017;1(1):3-13. doi: https://doi.org/10.1210/js.2016-1032
  22. Kumar P, Dezso Z, MacKenzie C, et al. Circulating miRNA biomarkers for Alzheimer’s disease. PLoS One. 2013;8(7):e69807. doi: https://doi.org/10.1371/journal.pone.0069807
  23. Sharma S, Nagpal N, Ghosh PC, Kulshreshtha R. P53-miR-191-SOX4 regulatory loop affects apoptosis in breast cancer. RNA. 2017;23(8):1237-1246. doi: https://doi.org/10.1261/rna.060657.117
  24. Vistbakka J, Sumelahti ML, Lehtimäki T, et al. Evaluation of serum miR-191-5p, miR-24-3p, miR-128-3p, and miR-376c-3 in multiple sclerosis patients. Acta Neurol Scand. 2018;138(2):130-136. doi: https://doi.org/10.1111/ane.12921
  25. Sánchez-Mora C, Soler Artigas M, Garcia-Martínez I, et al. Epigenetic signature for attention-deficit/hyperactivity disorder: identification of miR-26b-5p, miR-185-5p, and miR-191-5p as potential biomarkers in peripheral blood mononuclear cells. Neuropsychopharmacology. 2019;44(5):890-897. doi: https://doi.org/10.1038/s41386-018-0297-0
  26. Nam JW, Rissland OS, Koppstein D, et al. Global analyses of the effect of different cellular contexts on microRNA targeting. Mol Cell. 2014;53(6):1031-1043. doi: https://doi.org/10.1016/j.molcel.2014.02.013
  27. Betel D, Koppal A, Agius P, et al. Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites. Genome Biol. 2010;11(8):R90. doi: https://doi.org/10.1186/gb-2010-11-8-r90.
  28. Reczko M, Maragkakis M, Alexiou P, et al. Functional microRNA targets in protein coding sequences. Bioinformatics. 2012;28(6): 771-776. doi: https://doi.org/10.1093/bioinformatics/bts043
  29. Krek A, Grün D, Poy MN, et al. Combinatorial microRNA target predictions. Nat Genet. 2005;37(5):495-500. doi: https://doi.org/10.1038/ng1536
  30. Riffo-Campos Á, Riquelme I, Brebi-Mieville P. Tools for sequence-based miRNA target prediction: what to choose? Int J Mol Sci. 2016;17(12). pii: E1987. doi: https://doi.org/10.3390/ijms17121987
  31. Alatzoglou KS, Kelberman D, Dattani MT. The role of SOX proteins in normal pituitary development. J Endocrinol. 2009;200(3): 245-258. doi: https://doi.org/10.1677/JOE-08-0447
  32. Ma Y, Qi X, Du J, et al. Identification of candidate genes for human pituitary development by EST analysis. BMC Genomics. 2009; 10(1):109. doi: https://doi.org/10.1186/1471-2164-10-109
  33. Новикова М.В., Рыбко В.А., Хромова Н.В., и др. Роль белков Notch в процессах канцерогенеза // Успехи молекулярной онкологии. – 2015. – Т.2. – №3. – С. 30–42. [Novikova MV, Rybko VA, Khromova NV, et al. The role of Notch pathway in carcinogenesis. Advances in molecular oncology. 2015;2(3):30-42. (In Russ).] doi: https://doi.org/10.17650/2313-805X-2015-2-3-30-42
  34. Perrone S, Zubeldia-Brenner L, Gazza E, et al. Notch system is differentially expressed and activated in pituitary adenomas of distinct histotype, tumor cell lines and normal pituitaries. Oncotarget. 2017;8(34):57072−57088. doi: https://doi.org/10.18632/oncotarget.19046
  35. Liu Q, Tong D, Liu G, et al. Carney complex with PRKAR1A gene mutation. Medicine (Baltimore). 2017;96(50):e8999. doi: https://doi.org/10.1097/MD.0000000000008999
  36. Ezzat S, Caspar-Bell GM, Chik CL, et al. Predictive markers for postsurgical medical management of acromegaly: a systematic review and consensus treatment guideline. Endocr Pract. 2019;25(4):379-393. doi: https://doi.org/10.4158/EP-2018-0500
  37. Agarwal V, Bell GW, Nam J-W, Bartel DP. Predicting effective microRNA target sites in mammalian mRNAs. Elife. 2015;4. doi: https://doi.org/10.7554/eLife.05005
  38. Kameswaran V, Bramswig NC, McKenna LB, et al. Epigenetic regulation of the DLK1-MEG3 microRNA cluster in human type 2 diabetic islets. Cell Metab. 2014;19(1):135-145. doi: https://doi.org/10.1016/j.cmet.2013.11.016
  39. Gottwein E, Corcoran DL, Mukherjee N, et al. Viral microRNA targetome of KSHV-infected primary effusion lymphoma cell lines. Cell Host Microbe. 2011;10(5):515-526. doi: https://doi.org/10.1016/j.chom.2011.09.012
  40. Yang Q, Lu J, Wang S, et al. Application of next-generation sequencing technology to profile the circulating microRNAs in the serum of preeclampsia versus normal pregnant women. Clin Chim Acta. 2011;412(23−24):2167-2173. doi: https://doi.org/10.1016/j.cca.2011.07.029
  41. Suzuki M, Konno S, Makita H, et al. Altered circulating exosomal RNA profiles detected by next-generation sequencing in patients with severe asthma. Eur Res J. 2016;48:PA3410. doi: https://doi.org/10.1183/13993003.congress-2016.PA3410
  42. Van Laar R, Leigh K, Zielinski A, et al. Small RNA next generation sequencing (NGS) of CD138+ plasma cells from multiple myeloma patients and comparison to the 70-gene mRNA-based prognostic risk score. Blood. 2016;128(22):2089. doi: https://doi.org/10.1182/blood.v128.22.2089.2089

Supplementary files

There are no supplementary files to display.

Views

Abstract - 215

PDF (Russian) - 3

Remote (Russian) - 111

Cited-By


PlumX

Dimensions


Copyright (c) 2020 Lutsenko A.S., Belaya Z.E., Przhiyalkovskaya E.G., Nikitin A.G., Koshkin P.A., Lapshina A.M., Khandaeva P.M., Melnichenko G.A.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies