Skip to content
2000
Volume 32, Issue 29
  • ISSN: 0929-8673
  • E-ISSN: 1875-533X

Abstract

Introduction

microRNAs (miRNAs) are a class of non-coding RNAs that play important roles in gene regulation. miRNAs are transcribed from DNA sequences into primary miRNAs and then processed into precursor miRNAs and mature miRNAs. miRNA gene counts in chromosomes for different species have been studied.

Methods

Certain chromosomes have higher numbers of miRNA genes in all species, such as the X chromosome, while the Y chromosome has the fewest or no miRNA genes. miRNA counts in different chromosomes might have a positive correlation with coding gene counts in many species. In this study, a regression model was used to find the relationship between the miRNA count and the coding gene count across human chromosomes, and miRNA counts for 23 human chromosomes were predicted based on this regression model. In addition, the chromosome locations for the miRNA biomarkers of major depression, diabetes, Parkinson’s disease, and COVID-19 are discussed.

Results

The results reveal that miRNA biomarkers of these diseases are located in various chromosomes. The dispersion of miRNA locations across different chromosomes might explain the complication of the pathology of these diseases. Moreover, diabetes and COVID-19 have the largest number of miRNA biomarkers from Chromosome X.

Conclusion

As Chromosome X is a sex chromosome, this phenomenon may explain the gender difference in the prevalence or severity of diabetes and COVID-19. The significant gender difference in the prevalence or severity of diabetes and COVID-19 might be due to the regulation function of their miRNA biomarkers from Chromosome X.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cmc/10.2174/0109298673341375241009105556
2024-10-24
2025-10-27

  • From This Site

    /content/journals/cmc/10.2174/0109298673341375241009105556
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. LeeR.C. FeinbaumR.L. AmbrosV. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14.Cell199375584385410.1016/0092‑8674(93)90529‑Y8252621
     [Google Scholar]
  2. PasquinelliA.E. ReinhartB.J. SlackF. MartindaleM.Q. KurodaM.I. MallerB. HaywardD.C. BallE.E. DegnanB. MüllerP. SpringJ. SrinivasanA. FishmanM. FinnertyJ. CorboJ. LevineM. LeahyP. DavidsonE. RuvkunG. Conservation of the sequence and temporal expression of let-7 heterochronic regulatory RNA.Nature20004086808868910.1038/3504055611081512
     [Google Scholar]
  3. O’BrienJ. HayderH. ZayedY. PengC. Overview of microRNA biogenesis, mechanisms of actions, and circulation.Front. Endocrinol.2018940210.3389/fendo.2018.0040230123182
     [Google Scholar]
  4. KimV.N. HanJ. SiomiM.C. Biogenesis of small RNAs in animals.Nat. Rev. Mol. Cell Biol.200910212613910.1038/nrm263219165215
     [Google Scholar]
  5. DaiL. ChenK. YoungrenB. KulinaJ. YangA. GuoZ. LiJ. YuP. GuS. Cytoplasmic Drosha activity generated by alternative splicing.Nucleic Acids Res.20164421gkw66810.1093/nar/gkw66827471035
     [Google Scholar]
  6. TurunenT.A. RobertsT.C. LaitinenP. VäänänenM.A. KorhonenP. MalmT. Ylä-HerttualaS. TurunenM.P. Changes in nuclear and cytoplasmic microRNA distribution in response to hypoxic stress.Sci. Rep.2019911033210.1038/s41598‑019‑46841‑131316122
     [Google Scholar]
  7. KozomaraA. BirgaoanuM. Griffiths-JonesS. miRBase: From microRNA sequences to function.Nucleic Acids Res.201947D1D155D16210.1093/nar/gky114130423142
     [Google Scholar]
  8. KozomaraA. Griffiths-JonesS. miRBase: Annotating high confidence microRNAs using deep sequencing data.Nucleic Acids Res.201442D1D68D7310.1093/nar/gkt118124275495
     [Google Scholar]
  9. FrommB. BillippT. PeckL.E. JohansenM. TarverJ.E. KingB.L. NewcombJ.M. SempereL.F. FlatmarkK. HovigE. PetersonK.J. A uniform system for the annotation of vertebrate microRNA genes and the evolution of the human microRNAome.Annu. Rev. Genet.201549121324210.1146/annurev‑genet‑120213‑09202326473382
     [Google Scholar]
  10. FrommB. DomanskaD. HøyeE. OvchinnikovV. KangW. Aparicio-PuertaE. JohansenM. FlatmarkK. MathelierA. HovigE. HackenbergM. FriedländerM.R. PetersonK.J. MirGeneDB 2.0: The metazoan microRNA complement.Nucleic Acids Res.202048D1D132D14110.1093/nar/gkz88531598695
     [Google Scholar]
  11. PengY. CroceC.M. The role of microRNAs in human cancer.Signal Transduct. Target. Ther.2016111500410.1038/sigtrans.2015.429263891
     [Google Scholar]
  12. JanssonM.D. LundA.H. microRNA and cancer.Mol. Oncol.20126659061010.1016/j.molonc.2012.09.00623102669
     [Google Scholar]
  13. ZhouK. LiuM. CaoY. New insight into microRNA functions in cancer: Oncogene–microRNA–tumor suppressor gene network.Front. Mol. Biosci.201744610.3389/fmolb.2017.0004628736730
     [Google Scholar]
  14. CalinG.A. DumitruC.D. ShimizuM. BichiR. ZupoS. NochE. AldlerH. RattanS. KeatingM. RaiK. RassentiL. KippsT. NegriniM. BullrichF. CroceC.M. Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia.Proc. Natl. Acad. Sci. USA20029924155241552910.1073/pnas.24260679912434020
     [Google Scholar]
  15. WangH. Predicting microRNA biomarkers for cancer using phylogenetic tree and microarray analysis.Int. J. Mol. Sci.201617577310.3390/ijms1705077327213352
     [Google Scholar]
  16. HsiehW.J. LinF.M. HuangH.D. WangH. Investigating microRNA-target interaction-supported tissues in human cancer tissues based on miRNA and target gene expression profiling.PLoS One201494e9569710.1371/journal.pone.009569724756070
     [Google Scholar]
  17. WangH. TaguchiY.H. LiuX. Editorial: MiRNAs and neurological diseases.Front. Neurol.20211266237310.3389/fneur.2021.66237333959091
     [Google Scholar]
  18. ZhouZ. XiongH. XieF. WuZ. FengY. A meta-analytic review of the value of miRNA for multiple sclerosis diagnosis.Front. Neurol.20201113210.3389/fneur.2020.0013232158427
     [Google Scholar]
  19. WangH. microRNAs, multiple sclerosis, and depression.Int. J. Mol. Sci.20212215780210.3390/ijms2215780234360568
     [Google Scholar]
  20. TaguchiY. WangH. Exploring microRNA biomarker for amyotrophic lateral sclerosis.Int. J. Mol. Sci.2018195131810.3390/ijms1905131829710810
     [Google Scholar]
  21. GohS.Y. ChaoY.X. DheenS.T. TanE.K. TayS.S.W. Role of microRNAs in parkinson’s disease.Int. J. Mol. Sci.20192022564910.3390/ijms2022564931718095
     [Google Scholar]
  22. GrassoM. Plasma microRNA profiling distinguishes patients with frontotemporal dementia from healthy subjects.Neurobiol Aging2019240240e110.1016/j.neurobiolaging.2019.01.024
     [Google Scholar]
  23. WangW.X. RajeevB.W. StrombergA.J. RenN. TangG. HuangQ. RigoutsosI. NelsonP.T. The expression of microRNA miR-107 decreases early in Alzheimer’s disease and may accelerate disease progression through regulation of β-site amyloid precursor protein-cleaving enzyme 1.J. Neurosci.20082851213122310.1523/JNEUROSCI.5065‑07.200818234899
     [Google Scholar]
  24. MagriF. VanoliF. CortiS. mi RNA in spinal muscular atrophy pathogenesis and therapy.J. Cell. Mol. Med.201822275576710.1111/jcmm.1345029160009
     [Google Scholar]
  25. WangH. microRNAs, parkinson’s disease, and diabetes mellitus.Int. J. Mol. Sci.2021226295310.3390/ijms2206295333799467
     [Google Scholar]
  26. TaguchiY. WangH. Exploring microRNA biomarkers for parkinson’s disease from mRNA expression profiles.Cells201871224510.3390/cells712024530563060
     [Google Scholar]
  27. ZhangJ. XuX. ZhaoS. GongZ. LiuP. GuanW. HeX. WangT. PengT. TengJ. JiaY. The expression and significance of the plasma let-7 family in anti-n-methyl-d-aspartate receptor encephalitis.J. Mol. Neurosci.201556353153910.1007/s12031‑015‑0489‑625603816
     [Google Scholar]
  28. WangH. microRNA pathological mechanisms between Parkinson’s disease, Alzheimer’s disease, glaucoma and macular degeneration.Expert Rev. Mol. Med.202325e2410.1017/erm.2023.1937469309
     [Google Scholar]
  29. WangH. Phylogenetic analysis to explore the association between anti-NMDA receptor encephalitis and tumors based on microRNA biomarkers.Biomolecules201991057210.3390/biom910057231590348
     [Google Scholar]
  30. WangH. Anti-NMDA receptor encephalitis and vaccination.Int. J. Mol. Sci.201718119310.3390/ijms1801019328106787
     [Google Scholar]
  31. WangH. Anti-NMDA receptor encephalitis, human papillomavirus, and microRNA.Curr. Med. Chem.202438549528
     [Google Scholar]
  32. HammondS.M. An overview of microRNAs.Adv. Drug Deliv. Rev.20158731410.1016/j.addr.2015.05.00125979468
     [Google Scholar]
  33. AllesJ. FehlmannT. FischerU. BackesC. GalataV. MinetM. HartM. Abu-HalimaM. GrässerF.A. LenhofH.P. KellerA. MeeseE. An estimate of the total number of true human miRNAs.Nucleic Acids Res.20194773353336410.1093/nar/gkz09730820533
     [Google Scholar]
  34. GhoraiA. GhoshU. miRNA gene counts in chromosomes vary widely in a species and biogenesis of miRNA largely depends on transcription or post-transcriptional processing of coding genes.Front. Genet.2014510010.3389/fgene.2014.0010024808907
     [Google Scholar]
  35. SherwinE. ReaK. DinanT.G. CryanJ.F. A gut (microbiome) feeling about the brain.Curr. Opin. Gastroenterol.20163229610210.1097/MOG.000000000000024426760398
     [Google Scholar]
  36. BansalY. KuhadA. Mitochondrial dysfunction in depression.Curr. Neuropharmacol.201614661061810.2174/1570159X1466616022911475526923778
     [Google Scholar]
  37. Franscina PintoE. AndradeC. Interferon-related depression: A primer on mechanisms, treatment, and prevention of a common clinical problem.Curr. Neuropharmacol.201614774374810.2174/1570159X1466616010615512926733280
     [Google Scholar]
  38. HobanA.E. StillingR.M. M MoloneyG. MoloneyR.D. ShanahanF. DinanT.G. CryanJ.F. ClarkeG. Microbial regulation of microRNA expression in the amygdala and prefrontal cortex.Microbiome20175110210.1186/s40168‑017‑0321‑328838324
     [Google Scholar]
  39. TahamtanA. Teymoori-RadM. NakstadB. SalimiV. Anti-inflammatory microRNAs and their potential for inflammatory diseases treatment.Front. Immunol.20189137710.3389/fimmu.2018.0137729988529
     [Google Scholar]
  40. TangX. TangG. OzcanS. Role of microRNAs in diabetes.Biochim. Biophys. Acta. Gene Regul. Mech.200817791169770110.1016/j.bbagrm.2008.06.01018655850
     [Google Scholar]
  41. LeeH.W. KhanS.Q. KhaliqdinaS. AltintasM.M. GrahammerF. ZhaoJ.L. KohK.H. TardiN.J. FaridiM.H. GeraghtyT. CimbalukD.J. SusztakK. MoitaL.F. BaltimoreD. TharauxP.L. HuberT.B. KretzlerM. BitzerM. ReiserJ. GuptaV. Absence of miR-146a in podocytes increases risk of diabetic glomerulopathy via up-regulation of ErbB4 and notch-1.J. Biol. Chem.2017292273274710.1074/jbc.M116.75382227913625
     [Google Scholar]
  42. HaaxmaC.A. BloemB.R. BormG.F. OyenW.J.G. LeendersK.L. EshuisS. BooijJ. DluzenD.E. HorstinkM.W.I.M. Gender differences in Parkinson’s disease.J. Neurol. Neurosurg. Psychiatry200778881982410.1136/jnnp.2006.10378817098842
     [Google Scholar]
  43. CerriS. MusL. BlandiniF. Parkinson’s disease in women and men: What’s the difference?J. Parkinsons Dis.20199350151510.3233/JPD‑19168331282427
     [Google Scholar]
  44. RoserA.E. Caldi GomesL. SchünemannJ. MaassF. LingorP. Circulating miRNAs as diagnostic biomarkers for parkinson’s disease.Front. Neurosci.20181262510.3389/fnins.2018.0062530233304
     [Google Scholar]
  45. SerafinA. FocoL. ZanigniS. BlankenburgH. PicardA. ZanonA. GianniniG. PichlerI. FacherisM.F. CortelliP. PramstallerP.P. HicksA.A. DominguesF.S. SchwienbacherC. Overexpression of blood microRNAs 103a, 30b, and 29a in l -dopa–treated patients with PD.Neurology201584764565310.1212/WNL.000000000000125825596505
     [Google Scholar]
  46. XingR.X. LiL.G. LiuX.W. TianB.X. ChengY. Down regulation of miR -218, miR -124, and miR -144 relates to Parkinson’s disease via activating NF-κB signaling.Kaohsiung J. Med. Sci.2020361078679210.1002/kjm2.1224132492291
     [Google Scholar]
  47. HoweK.L. AchuthanP. AllenJ. AllenJ. Alvarez-JarretaJ. AmodeM.R. ArmeanI.M. AzovA.G. BennettR. BhaiJ. BillisK. BodduS. CharkhchiM. CumminsC. Da Rin FiorettoL. DavidsonC. DodiyaK. El HoudaiguiB. FatimaR. GallA. Garcia GironC. GregoT. Guijarro-ClarkeC. HaggertyL. HemromA. HourlierT. IzuoguO.G. JuettemannT. KaikalaV. KayM. LavidasI. LeT. LemosD. Gonzalez MartinezJ. MarugánJ.C. MaurelT. McMahonA.C. MohananS. MooreB. MuffatoM. OhehD.N. ParaschasD. ParkerA. PartonA. ProsovetskaiaI. SakthivelM.P. SalamA.I.A. SchmittB.M. SchuilenburgH. SheppardD. SteedE. SzpakM. SzubaM. TaylorK. ThormannA. ThreadgoldG. WaltsB. WinterbottomA. ChakiachviliM. ChaubalA. De SilvaN. FlintB. FrankishA. HuntS.E. IIsleyG.R. LangridgeN. LovelandJ.E. MartinF.J. MudgeJ.M. MoralesJ. PerryE. RuffierM. TateJ. ThybertD. TrevanionS.J. CunninghamF. YatesA.D. ZerbinoD.R. FlicekP. Ensembl 2021.Nucleic Acids Res.202149D1D884D89110.1093/nar/gkaa94233137190
     [Google Scholar]
  48. ChenY.H. WangH. The association between depression and gastroesophageal reflux based on phylogenetic analysis of miRNA biomarkers.Curr. Med. Chem.202027386536654710.2174/092986732766620042521490632334497
     [Google Scholar]
  49. SongM.F. DongJ.Z. WangY.W. HeJ. JuX. ZhangL. ZhangY.H. ShiJ.F. LvY.Y. CSF miR-16 is decreased in major depression patients and its neutralization in rats induces depression-like behaviors via a serotonin transmitter system.J. Affect. Disord.2015178253110.1016/j.jad.2015.02.02225779937
     [Google Scholar]
  50. GururajanA. NaughtonM.E. ScottK.A. O’ConnorR.M. MoloneyG. ClarkeG. DowlingJ. WalshA. IsmailF. ShortenG. ScottL. McLoughlinD.M. CryanJ.F. DinanT.G. microRNAs as biomarkers for major depression: A role for let-7b and let-7c.Transl. Psychiatry201668e86210.1038/tp.2016.13127483380
     [Google Scholar]
  51. Bocchio-ChiavettoL. MaffiolettiE. BettinsoliP. GiovanniniC. BignottiS. TarditoD. CorradaD. MilanesiL. GennarelliM. Blood microRNA changes in depressed patients during antidepressant treatment.Eur. Neuropsychopharmacol.201323760261110.1016/j.euroneuro.2012.06.01322925464
     [Google Scholar]
  52. ShiY. Non-coding RNAs in depression: Promising diagnostic and therapeutic biomarkers.EBioMedicine.20217110356910.1016/j.ebiom.2021.103569
     [Google Scholar]
  53. DantzerR. O’ConnorJ.C. FreundG.G. JohnsonR.W. KelleyK.W. From inflammation to sickness and depression: When the immune system subjugates the brain.Nat. Rev. Neurosci.200891465610.1038/nrn229718073775
     [Google Scholar]
  54. PearsonS. SchmidtM. PattonG. DwyerT. BlizzardL. OtahalP. VennA. Depression and insulin resistance: Cross-sectional associations in young adults.Diabetes Care20103351128113310.2337/dc09‑194020185745
     [Google Scholar]
  55. ShadrinaM. BondarenkoE.A. SlominskyP.A. Genetics factors in major depression disease.Front. Psychiatry2018933410.3389/fpsyt.2018.0033430083112
     [Google Scholar]
  56. CuiC. ZhongB. FanR. CuiQ. HMDD v4.0: A database for experimentally supported human microRNA-disease associations.Nucleic Acids Res.202452D1D1327D133210.1093/nar/gkad71737650649
     [Google Scholar]
  57. HuangZ. ShiJ. GaoY. CuiC. ZhangS. LiJ. ZhouY. CuiQ. HMDD v3.0: A database for experimentally supported human microRNA–disease associations.Nucleic Acids Res.201947D1D1013D101710.1093/nar/gky101030364956
     [Google Scholar]
  58. KokkinopoulouI. MaratouE. MitrouP. BoutatiE. SiderisD.C. FragoulisE.G. ChristodoulouM.I. Decreased expression of microRNAs targeting type-2 diabetes susceptibility genes in peripheral blood of patients and predisposed individuals.Endocrine201966222623910.1007/s12020‑019‑02062‑031559537
     [Google Scholar]
  59. AssmannT.S. Recamonde-MendozaM. PuñalesM. TschiedelB. CananiL.H. CrispimD. microRNA expression profile in plasma from type 1 diabetic patients: Case-control study and bioinformatic analysis.Diabetes Res. Clin. Pract.2018141354610.1016/j.diabres.2018.03.04429679626
     [Google Scholar]
  60. PordzikJ. JakubikD. Jarosz-PopekJ. WicikZ. EyiletenC. De RosaS. IndolfiC. Siller-MatulaJ.M. CzajkaP. PostulaM. Significance of circulating microRNAs in diabetes mellitus type 2 and platelet reactivity: Bioinformatic analysis and review.Cardiovasc. Diabetol.201918111310.1186/s12933‑019‑0918‑x31470851
     [Google Scholar]
  61. WangJ. PanY. DaiF. WangF. QiuH. HuangX. Serum miR-195-5p is upregulated in gestational diabetes mellitus.J. Clin. Lab. Anal.2020348e2332510.1002/jcla.2332532301163
     [Google Scholar]
  62. WanS. WangJ. WangJ. WuJ. SongJ. ZhangC.Y. ZhangC. WangC. WangJ.J. Increased serum miR-7 is a promising biomarker for type 2 diabetes mellitus and its microvascular complications.Diabetes Res. Clin. Pract.201713017117910.1016/j.diabres.2017.06.00528646700
     [Google Scholar]
  63. WangH. microRNA, diabetes mellitus and colorectal cancer.Biomedicines202081253010.3390/biomedicines812053033255227
     [Google Scholar]
  64. JohansenJ.S. HarrisA.K. RychlyD.J. ErgulA. Oxidative stress and the use of antioxidants in diabetes: Linking basic science to clinical practice.Cardiovasc. Diabetol.200541510.1186/1475‑2840‑4‑515862133
     [Google Scholar]
  65. Galicia-GarciaU. Benito-VicenteA. JebariS. Larrea-SebalA. SiddiqiH. UribeK.B. OstolazaH. MartínC. Pathophysiology of type 2 diabetes mellitus.Int. J. Mol. Sci.20202117627510.3390/ijms2117627532872570
     [Google Scholar]
  66. WangH. Tolerance limits for mixture-of-normal distributions with application to COVID-19 data.Wiley Interdiscip. Rev. Comput. Stat.2023156e161110.1002/wics.1611
     [Google Scholar]
  67. ChenY.H. WangH. Exploring diversity of COVID-19 based on substitution distance.Infect. Drug Resist.2020133887389410.2147/IDR.S27762033149633
     [Google Scholar]
  68. WangH. COVID−19, anti-NMDA receptor encephalitis and microRNA.Front. Immunol.20221382510310.3389/fimmu.2022.82510335392089
     [Google Scholar]
  69. WangH. A review of the effects of collagen treatment in clinical studies.Polymers20211322386810.3390/polym1322386834833168
     [Google Scholar]
  70. TramuntB. SmatiS. GrandgeorgeN. LenfantF. ArnalJ.F. MontagnerA. GourdyP. Sex differences in metabolic regulation and diabetes susceptibility.Diabetologia202063345346110.1007/s00125‑019‑05040‑331754750
     [Google Scholar]
  71. JinJ.M. BaiP. HeW. WuF. LiuX.F. HanD.M. LiuS. YangJ.K. Gender differences in patients with COVID-19: Focus on severity and mortality.Front. Public Health2020815210.3389/fpubh.2020.0015232411652
     [Google Scholar]
  72. PinheiroI. DejagerL. LibertC. X-chromosome-located microRNAs in immunity: Might they explain male/female differences?BioEssays2011331179180210.1002/bies.20110004721953569
     [Google Scholar]
  73. CasertaS. GangemiS. MurdacaG. AllegraA. Gender differences and miRNAs expression in cancer: Implications on prognosis and susceptibility.Int. J. Mol. Sci.202324141154410.3390/ijms24141154437511303
     [Google Scholar]
  74. BellenghiM. PuglisiR. PontecorviG. De FeoA. CarèA. MattiaG. Sex and gender disparities in melanoma.Cancers2020127181910.3390/cancers1207181932645881
     [Google Scholar]
  75. ChabchoubG. UzE. MaalejA. MustafaC.A. RebaiA. MnifM. BahloulZ. FaridN.R. OzcelikT. AyadiH. Analysis of skewed X-chromosome inactivation in females with rheumatoid arthritis and autoimmune thyroid diseases.Arthritis Res. Ther.2009114R10610.1186/ar275919589151
     [Google Scholar]
  76. KhalifaO. PersY.M. FerreiraR. SénéchalA. JorgensenC. ApparaillyF. Duroux-RichardI. X-linked miRNAs associated with gender differences in rheumatoid arthritis.Int. J. Mol. Sci.20161711185210.3390/ijms1711185227834806
     [Google Scholar]
/content/journals/cmc/10.2174/0109298673341375241009105556
Loading
Distribution of microRNA Counts Across Human Chromosomes
Curr. Med. Chem. 32, 6380 (2025); https://doi.org/10.2174/0109298673341375241009105556
/content/journals/cmc/10.2174/0109298673341375241009105556
/content/journals/cmc/10.2174/0109298673341375241009105556
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher’s website along with the published article.

file format download Download

  • Article Type:     Research Article
Keyword(s): Biomarkers; chromosomes; COVID-19; genes; microRNA; regression model

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test