Table Info

Table 2.

Characteristics of biomarkers

Item	Authors	Link	Biomarkers	Potential pathway	Results
1	Lu et al. [20], 2020	https://www.webofscience.com/wos/woscc/full-record/WOS:000515868500001	circPHKA2, circBBS2	PHKA2 gene encodes PbK-subunit alpha involved in cellular energy metabolism. BBS2 gene is part of the BBS family reported to stimulate ciliary biosynthesis via GTPase Rab8.	Mean values of circPHKA2, circBBS2 were statistically significant in IS group vs. control group (P < 0.05). BBS2 function after stroke remains unclear.
2	Ostolaza et al. [23], 2020	https://www.webofscience.com/wos/woscc/full-record/WOS:000520976200005	hsa_circRNA_102488	Six different miRNAs implicated in fatty acid biosynthesis, lysine breakdown, and ARVC have a binding site on hsa_circRNA_102488, encoded on chromosome 19.	The atherothrombotic group had decreased hsa_circRNA_102488 levels (P < 0.01), and UBA52 mRNA levels were also downregulated (P < 0.001).
3	Abe et al. [24], 2020	https://pubmed.ncbi.nlm.nih.gov/32354168/	miR-505-5p, miR-1255b-5p, miR-550b-2-5p, miR-4523, and miR-6795-3p	miRNAs downregulate WDR26, which is an apoptosis repressor factor.	The study identified five miRNAs with fluctuating patterns correlated with the onset and course of cerebral infarction: miR-505-5p, miR-1255b-5p, miR-550b-2-5p, miR-4523, and miR-6795-3p. Higher levels of miR-376a-3p and downregulation of miR-3184-5p were associated with the onset of cerebral infarction.
4	Vijayan et al. [26], 2018	https://www.webofscience.com/wos/woscc/full-record/WOS:000438578900007	PC-3p-57664, PC-5p-12969, hsa-miR-122-5p, hsa-miR-211-5p, hsa-miR-22-3p, PC-3p-32463, hsa-miR-30d-5p, hsa-miR-23a-3p	miRNAs play an essential role in the regulation of leukocyte gene expression.	Sixteen dysregulated miRNAs in the IS group vs. the control group, out of which eight were validated through RT-PCR: four upregulated [PC-3p-57664 (P = 0.01), PC-5p-12969 (P = 0.04), hsa-miR-122-5p (P = 0.01), and hsa-miR-211-5p (P = 0.03)] and four downregulated [hsa-miR-22-3p (P = 0.01), PC-3p-32463 (P = 0.0001), hsa-miR-30d-5p (P = 0.0009), and hsa-miR-23a-3p (P = 0.03)].
5	Mick et al. [28], 2017	https://www.webofscience.com/wos/woscc/full-record/WOS:000398207000017	hsa-miR-877-5p, hsa-miR-124-3p, hsa-miR-320d, SNO1402, hsa-miR-656-3p, hsa-miR-3615, hsa-miR-656-3p, hsa-miR-941	Exosome-derived ncRNAs are implicated in inflammation and fibrosis.	hsa-miR-877-5p [odds ratio, 0.18; 95% CI, 0.06–0.52; P = 0.002], hsa-miR-124-3p (odds ratio, 0.29; 95% CI, 0.11–0.72; P = 0.008), hsa-miR-320d (odds ratio, 0.33; 95% CI, 0.14–0.78; P = 0.01), and SNO1402 (odds ratio, 0.20; 95% CI, 0.07–0.52; P = 0.001).
6	Zhu et al. [29], 2019	https://www.webofscience.com/wos/woscc/full-record/WOS:000457370300001	SCARNA10, TERC, LINC01481, FLJ23867, H3F3AP6, TNPO1P1	LncRNA levels in the pathway of antigen processing and presentation were elevated at 24 h, while lncRNA levels in TRP channels and GABAergic synapses were downregulated on day 7 following stroke.	SCARNA10, TERC, and LINC01481 showed significantly increased expression (P < 0.01), whereas FLJ23867, H3F3AP6, and TNPO1P1 showed significantly decreased expression (P < 0.05) in IS patient PBMCs compared to healthy controls.
7	Cao et al. [31], 2020	https://www.webofscience.com/wos/woscc/full-record/WOS:000513554900005	LncMRT	The PI3K/Akt signaling pathway was recognized by IS as a key route due to dysregulated LncMRTs. Improved cell survival is linked to the serine/ threonine kinase PI3K, and this impact is partially mediated by the activation of the serine/threonine kinase Akt.	The dysregulated LncMRT in IS (formed by PTEN, TFAP2A, and HOTAIR) suggests that PTEN is a key part of the PI3K/Akt signaling pathway by generating LncMRT.
8	Wang et al. [33], 2022	https://www.webofscience.com/wos/woscc/full-record/WOS:000711301400001	LNC_000015, LNC_001727	Because it encourages stem cell development and inhibits erythrocyte apoptosis, lncRNA is also thought to be useful in the treatment of ischemic disorders.	Five differentially expressed lncRNAs (LNC_000015, LNC_001727, SNHG8, MIRLET7BHG, AF001548.5) were found in IS and were used to construct a pathway network that suggests their potential as biomarkers and therapeutic targets in IS linked with the inflammatory response.
9	Zhang et al. [38], 2020	https://www.webofscience.com/wos/woscc/full-record/WOS:000575004300053	MCM3AP-AS1, LINC01089, ITPK1-AS1, HCG27	These hub genes were connected to signaling pathways relevant to inflammation, according to functional analysis.	Inflammatory associated DELs (MCM3AP-AS1/LINC01089/ hsa-miR-125a/FYN, ITPK1-AS1/ hsa-let-7i/RHOA/GRB2/STAT1, and HCG27/hsa-miR-19a/PXN) may function as a ceRNA network to accelerate the development of the genes.
10	Zhu et al. [40], 2020	https://www.webofscience.com/wos/woscc/full-record/WOS:000519997800015	ADIPOR2 rs12342	Immunoinflammatory gene functional polymorphisms.	ADIPOR2 rs12342 was statistically significant for stroke recurrence (GG vs. AA: P = 0.025; GA vs. AA: P = 0.011; GG/GA vs. AA: P = 0.004), but not with the onset age.
11	Li et al. [44], 2018	https://www.webofscience.com/wos/woscc/full-record/WOS:000429737400001	Cx37	The dysregulation of eNOS production and activity is brought on by the Cx37 C1019T polymorphism, which causes the transfer of proline to serine and also influences endothelial function and elasticity, leading to atherosclerosis.	The G allele of the Cx37 SNP rs1764390 was shown to be a risk factor for IS and the genotypes of the Cx37 SNP rs1764390 and rs1764391 are linked to an elevated risk of IS.
12	Xie et al. [45], 2020	https://www.webofscience.com/wos/woscc/full-record/WOS:000601211900010	RPS14, RPS15A, RPS24, FAU, RPL27, RPL31, RPL34, RPL35A, RSL24D1, EEF1B2	The expression of sex-specific ribosomal differential genes during the early stages of stroke recovery may be the main underlying cause of sexually dimorphic diff in inflammatory responses.	They showed that there are 10 upregulated genes with mostly ribosomal and protein synthesis- related functions (RPS14, RPS15A, RPS24, FAU, RPL27, RPL31, RPL34, RPL35A, RSL24D1, and EEF1B2).
13	Shroff et al. [47], 2019	https://www.webofscience.com/wos/woscc/full-record/WOS:000455396400002	HDAC9 polymorphism rs2107595	HDAC9 is a class IIa HDAC that is located at 7p21 and changes the chromatin state by removing acetyl groups from proteins.	Both the rs2107595 risk allele-positive and risk allele-negative LVAS groups, as well as the risk allele-positive and risk allele-negative VRFC groups, did not significantly differ from each other.
14	Williams et al. [48], 2017	https://pubmed.ncbi.nlm.nih.gov/28495826/	rs505922	The production of thrombus during cerebrovascular injury is significantly influenced by vWF.	Their results suggest that high vWF levels associate with the risk of stroke recurrence in both unadjusted (P = 0.0007, HR = 1.26) and fully adjusted (P = 0.018, HR=1.19) models, with the most strongly associated SNP-rs505922.
15	Davis Armstrong et al. [49], 2021	https://pubmed.ncbi.nlm.nih.gov/33661917/	rs7025659, rs10757056, rs10118089, rs7020745, rs10125228, rs10757058, rs10118371	Leukotriene B4 is a pro-inflammatory lipid mediator derived from arachidonic acid.	Sphingosine and sphinganine were nominally related with five common variants and one different variant [rs10757056 (sphingosine only), rs10118089, rs7020745, rs10125228, rs10757058, and rs10118371]. The most significant association included leukotriene B4 and rs7025659- SPTLC1 (P = 6.12e-07; post-hoc comparison between TG to GG genotypes P = 3.00E-07).
16	Davis Armstrong et al. [51], 2021	https://pubmed.ncbi.nlm.nih.gov/34252155/	cg03584380, which is located in an intron of ZDHHC6.	The ZDHHC6 gene, which makes the palmitoyltransferase ZDHHC6, contains this methylation site in its first intron. ZDHHC6 is required for the palmitoylation of numerous significant ER proteins, including calnexin and the ITPR1.	In the African population, cg03584380 [HR = 5.41 (2.91–10.06)] was significantly associated with the recurrence of stroke, but not in the European cohort.
17	Soriano- Tárraga et al. [59], 2018	https://pubmed.ncbi.nlm.nih.gov/29515201/	DNAm	DNAm affects the expression of genes and the structure of DNA, and fluctuates over the length of a human’s life.	Biological aging, an epigenetic biomarker calculated from DNAm values, outperforms chronological aging in predicting mortality three months after an IS. This connection is particularly important in the etiology of LAA stroke.
18	Miao et al. [64], 2021	https://www.webofscience.com/wos/woscc/full-record/WOS:000685052900002	Hypomethylation of the RIN3	The RIN3 gene regulates the movement of the amyloid beta-protein and functions as an inducer to maintain the transit of GTP Rab5 to endosomes at the plasma membrane. This process interferes with the endocytosis of the amyloid protein, which is connected to cellular endocytosis.	In the TIA/MIS group, the RIN3 gene’s overall methylation level was considerably lower than in the control group (diff = 0.02, P = 0.001), a result that was maintained in the cognitive impairment vs. non-cognitive impairment group (diff = −0.013, P = 0.01).
19	Sikora et al. [65], 2019	https://www.webofscience.com/wos/woscc/full-record/WOS:000473756000246	APCS, APOM, C1qA, C4BPA, C4BP2, FBLN1, IGKV1D-12, KLKB1, SERPINF2, AMBP, APOA4, FCN3, ITIH4, LBP, PF4, APOL1, C5, GPX3, GSN, H2AFJ, IGK	The biological pathways of the significant proteins are linked with the clothing cascade (A2M, FBLN1, FGA, PLG, SERPIND1, F13B, etc.), the acute phase response (SAA1, CRP, SERPINA3, SERPINA1, LBP, ORM1, AHSG), and lipids metabolism (APOC1, APOC3, APOL1, etc.).	Nine proteins were unique to differentiate cardioembolic and large-vessel stroke (APCS, APOM, C1qA, C4BPA, C4BP2, FBLN1, IGKV1D-12, KLKB1, SERPINF2), six for differentiating large-vessel and lacunar stroke (APOL1, C5, GPX3, GSN, H2AFJ, IGK) and six for cardioembolic vs. large-vessel stroke (AMBP, APOA4, FCN3, ITIH4, LBP, PF4).
20	Tufekci et al. [66], 2018	https://www.webofscience.com/wos/woscc/full-record/WOS:000426733300001	TRAIL mRNA expression	TRAIL is linked to five different receptors, two of which, DR4 and DR5 that cause apoptosis and inflammation.	Serum TRAIL levels of stroke patients were statistically (P < 0.0001) lower at the time of admission than those of healthy controls. Surprisingly, the follow-up study revealed that serum TRAIL levels considerably raised after the first month following stroke onset (P = 0.002). In addition, the TRAIL mRNA expression in PBMC was substantially higher in the stroke patients than in the controls (P < 0.0001). When compared to the first week after the onset of the stroke, TRAIL mRNA expression in PBMC was observed to be decreased (P < 0.001).
21	Li et al. [68], 2021	https://pubmed.ncbi.nlm.nih.gov/34188129/	serum anti- AP3D1-antibody (s-AP3D1-Ab)	AP3D1 was the target antigen that serum IgG antibodies identified in the plasma of individuals with atherosclerosis.	s-AP3D1-Ab levels were substantially greater in AIS than in healthy donors. The levels of s-AP3D1-Ab were still considerably greater in patients with AIS than in healthy donors even after the subjects’ ages were matched to 65 years. The s-AP3D1-Ab-positive rates in healthy donors and patients with AIS and TIA were 2.4%, 10.1%, and 10.4%, respectively, at a cutoff value comparable to the average plus two SDs of the HD values.

circPHKA2: circRNA phosphorylase kinase regulatory subunit alpha 2; circBBS2: circRNA Bardet-Biedl syndrome 2; PbK: phosphorylase b kinase; BBS2: Bardet-Biedl syndrome 2; miRNAs: microRNAs; ARVC: arrhythmogenic right ventricular cardiomyopathy; UBA52: ubiquitin A-52 residue ribosomal protein fusion product 1; mRNA: messenger RNA; WDR26: WD repeat domain 26; RT-PCR: reverse transcription polymerase chain reaction; CI: confidence interval; SCARNA10: small Cajal body-specific RNA 10; TERC: telomerase RNA component; LINC01481: long intergenic non-protein coding RNA 1481; H3F3AP6: H3 histone, family 3A, pseudogene 6; TNPO1P1: transportin 1 pseudogene 1; PBMCs: peripheral blood mononuclear cells; LncMRT: lncRNA-mediated regulatory triplet; PI3K: phosphatidylinositol 3-kinase; Akt: protein kinase B; PTEN: phosphatase and tensin homolog; TFAP2A: transcription factor (TF) AP-2 alpha; HOTAIR: HOX transcript antisense RNA; SNHG8: small nucleolar RNA (snoRNA) host gene 8; MIRLET7BHG: miRNA let-7b host gene; MCM3AP-AS1: minichromosome maintenance complex component 3 associated protein antisense 1; ITPK1-AS1: inositol-tetrakisphosphate 1-kinase-antisense RNA 1; HCG27: human leukocyte antigen complex group 27; DELs: DNA-encoded libraries; RHOA: Ras homolog family member A; GRB2: growth factor receptor bound protein 2; STAT1: signal transducer and activator of transcription 1; PXN: paxillin; ceRNA: competing endogenous RNA; ADIPOR2: adiponectin receptor 2; Cx37: CONNEXIN37; eNOS: endothelial nitric oxide synthase; SNP: single nucleotide polymorphism; RPS14: ribosomal protein S14; RSL24D1: ribosomal L24 domain containing 1; EEF1B2: eukaryotic translation elongation factor 1 beta 2; HDAC9: histone deacetylase 9; LVAS: large vessel atherosclerotic stroke; VRFC: vascular risk factor controls; vWF: von Willebrand factor; SPTLC1: serine palmitoyltransferase long chain base subunit 1; ZDHHC6: zinc finger DHHC-type palmitoyltransferase 6; ER: endoplasmic reticulum; ITPR1: inositol 1,4,5-trisphosphate receptor type 1; LAA: large artery atherosclerosis; RIN3: Ras and Rab interactor 3; GTP: guanosine triphosphate; TIA: transient ischemic attack; MIS: minor IS; diff: difference; APCS: serum amyloid P component; APOM: apolipoprotein M; C1qA: complement component 1q A chain; C4BPA: complement component 4 binding protein alpha; FBLN1: fibulin 1; IGKV1D-12: immunoglobulin kappa (IGK) variable 1D-12; KLKB1: kallikrein B1; SERPINF2: serpin family F member 2; AMBP: alpha-1-microglobulin/bikunin precursor; FCN3: ficolin 3; ITIH4: inter-alpha-trypsin inhibitor heavy chain 4; LBP: lipopolysaccharide binding protein; PF4: platelet factor 4; C5: complement component 5; GPX3: glutathione peroxidase 3; GSN: gelsolin; H2AFJ: H2A histone family member J; A2M: alpha-2-macroglobulin; FGA: fibrinogen alpha chain; PLG: plasminogen; F13B: coagulation factor XIII B chain; SAA1: serum amyloid A1; CRP: C-reactive protein; ORM1: orosomucoid 1; AHSG: alpha-2 Heremans Schmid glycoprotein; TRAIL: tumor necrosis factor-related apoptosis-inducing ligand; DR4: death receptor 4; AP3D1: adaptor-related protein complex 3 subunit delta 1; s-AP3D1-Ab: serum anti-AP3D1-antibody; IgG: immunoglobulin G; AIS: acute IS; PHKA2: phosphorylase kinase regulatory subunit alpha 2; TRP: transient receptor potential; GABA: gamma-aminobutyric acid; ncRNAs: non-coding RNAs

Supplementary materials

The supplementary material for this article is available at: https://www.explorationpub.com/uploads/Article/file/100610_sup_1.pdf.

Declarations

Author contributions

MAR, DB, RS, and APW: Writing—review & editing. AMC and MA: Investigation. RS and APW: Funding acquisition. DMH, IFC, and TRD: Supervision.

Conflicts of interest

The authors declare no conflicts of interest related to this study.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent to publication

Not applicable.

Availability of data and materials

Data will be made available upon request (aurel.popa-wagner@geriatrics-healthyageing.com).

Funding

APW received funding from the EU Horizon 2020 Research and Innovation Programme [263/16.11.2020]. RS received funding from the EU Horizon 2020 Research and Innovation Programme [PN-III-P1-1.1- PD-2021-0360]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright

References

Wilkins E, Wilson L, Wickramasinghe K, Bhatnagar P, Leal J, Luengo-Fernandez R, et al. European cardiovascular disease statistics 2017. Brussels: European Heart Network; 2017.

Benjamin EJ, Virani SS, Callaway CW, Chamberlain AM, Chang AR, Cheng S, et al.; American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics-2018 update: a report from the American Heart Association. Circulation. 2018;137:e67–492. Erratum in: Circulation. 2018;137:e493. [DOI]

Feigin VL, Norrving B, Mensah GA. Global burden of stroke. Circ Res. 2017;120:439–48. [DOI] [PubMed]

Virani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, et al.; American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics-2021 update: a report from the American Heart Association. Circulation. 2021;143:e254–743. [DOI] [PubMed]

Langhorne P, Coupar F, Pollock A. Motor recovery after stroke: a systematic review. Lancet Neurol. 2009;8:741–54. [DOI] [PubMed]

O’Collins VE, Macleod MR, Donnan GA, Horky LL, van der Worp BH, Howells DW. 1,026 experimental treatments in acute stroke. Ann Neurol. 2006;59:467–77. [DOI] [PubMed]

Ni J, Qu J, Yao M, Zhang Z, Zhong X, Cui L; RESK investigators. Re-evaluate the Efficacy and Safety of Human Urinary Kallidinogenase (RESK): protocol for an open-label, single-arm, multicenter phase IV trial for the treatment of acute ischemic stroke in Chinese patients. Transl Stroke Res. 2017;8:341–6. [DOI] [PubMed]

Dong Y, Qu J, Zhang Z, Wang C, Dong Q. Human urinary kallidinogenase in treating acute ischemic stroke patients: analyses of pooled data from a randomized double-blind placebo-controlled phase IIb and phase III clinical trial. Neurol Res. 2020;42:286–90. [DOI] [PubMed]

Enomoto M, Endo A, Yatsushige H, Fushimi K, Otomo Y. Clinical effects of early edaravone use in acute ischemic stroke patients treated by endovascular reperfusion therapy. Stroke. 2019;50:652–8. [DOI] [PubMed]

10.

Hill MD, Goyal M, Menon BK, Nogueira RG, McTaggart RA, Demchuk AM, et al.; ESCAPE-NA1 Investigators. Efficacy and safety of nerinetide for the treatment of acute ischaemic stroke (ESCAPE-NA1): a multicentre, double-blind, randomised controlled trial. Lancet. 2020;395:878–87. [DOI] [PubMed]

11.

Lyden P, Pryor KE, Coffey CS, Cudkowicz M, Conwit R, Jadhav A, et al.; NeuroNEXT Clinical Trials Network NN104 Investigators. Final results of the RHAPSODY trial: a multi-center, phase 2 trial using a continual reassessment method to determine the safety and tolerability of 3K3A-APC, a recombinant variant of human activated protein C, in combination with tissue plasminogen activator, mechanical thrombectomy or both in moderate to severe acute ischemic stroke. Ann Neurol. 2019;85:125–36. [DOI] [PubMed] [PMC]

12.

Driga MP, Catalin B, Olaru DG, Slowik A, Plesnila N, Hermann DM, et al. The need for new biomarkers to assist with stroke prevention and prediction of post-stroke therapy based on plasma-derived extracellular vesicles. Biomedicines. 2021;9:1226. [DOI] [PubMed] [PMC]

13.

Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001;69:89–95. [DOI] [PubMed]

14.

Montellano FA, Ungethüm K, Ramiro L, Nacu A, Hellwig S, Fluri F, et al. Role of blood-based biomarkers in ischemic stroke prognosis: a systematic review. Stroke. 2021;52:543–51. Erratum in: Stroke. 2021;52:e106. [DOI] [PubMed]

15.

Lai YJ, Hanneman SK, Casarez RL, Wang J, McCullough LD. Blood biomarkers for physical recovery in ischemic stroke: a systematic review. Am J Transl Res. 2019;11:4603–13. [PubMed] [PMC]

16.

Whiteley W, Chong WL, Sengupta A, Sandercock P. Blood markers for the prognosis of ischemic stroke: a systematic review. Stroke. 2009;40:e380–9. [DOI] [PubMed]

17.

Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339:b2700. [DOI] [PubMed] [PMC]

18.

Silva PW, M Shimon SM, de Brito LM, Reis-das-Mercês L, Magalhães L, Araújo G, et al. Novel insights toward human stroke-related epigenetics: circular RNA and its impact in poststroke processes. Epigenomics. 2020;12:1957–68. [DOI] [PubMed]

19.

Patop IL, Wüst S, Kadener S. Past, present, and future of circRNAs. EMBO J. 2019;38:e100836. [DOI] [PubMed] [PMC]

20.

Lu D, Ho ES, Mai H, Zang J, Liu Y, Li Y, et al. Identification of blood circular RNAs as potential biomarkers for acute ischemic stroke. Front Neurosci. 2020;14:81. [DOI] [PubMed] [PMC]

21.

Brushia RJ, Walsh DA. Phosphorylase kinase: the complexity of its regulation is reflected in the complexity of its structure. Front Biosci. 1999;4:D618–41. [DOI] [PubMed]

22.

Nachury MV, Loktev AV, Zhang Q, Westlake CJ, Peränen J, Merdes A, et al. A core complex of BBS proteins cooperates with the GTPase Rab8 to promote ciliary membrane biogenesis. Cell. 2007;129:1201–13. [DOI] [PubMed]

23.

Ostolaza A, Blanco-Luquin I, Urdánoz-Casado A, Rubio I, Labarga A, Zandio B, et al. Circular RNA expression profile in blood according to ischemic stroke etiology. Cell Biosci. 2020;10:34. [DOI] [PubMed] [PMC]

24.

Abe A, Tanaka M, Yasuoka A, Saito Y, Okada S, Mishina M, et al. Changes in whole-blood microRNA profiles during the onset and treatment process of cerebral infarction: a human study. Int J Mol Sci. 2020;21:3107. [DOI] [PubMed] [PMC]

25.

Jickling GC, Ander BP, Zhan X, Noblett D, Stamova B, Liu D. microRNA expression in peripheral blood cells following acute ischemic stroke and their predicted gene targets. PLoS One. 2014;9:e99283. [DOI] [PubMed] [PMC]

26.

Vijayan M, Kumar S, Yin X, Zafer D, Chanana V, Cengiz P, et al. Identification of novel circulatory microRNA signatures linked to patients with ischemic stroke. Hum Mol Genet. 2018;27:2318–29. [DOI] [PubMed] [PMC]

27.

Dhiraj DK, Chrysanthou E, Mallucci GR, Bushell M. miRNAs-19b, -29b-2* and -339-5p show an early and sustained up-regulation in ischemic models of stroke. PLoS One. 2013;8:e83717. [DOI] [PubMed] [PMC]

28.

Mick E, Shah R, Tanriverdi K, Murthy V, Gerstein M, Rozowsky J, et al. Stroke and circulating extracellular RNAs. Stroke. 2017;48:828–34. [DOI] [PubMed] [PMC]

29.

Zhu W, Tian L, Yue X, Liu J, Fu Y, Yan Y. LncRNA expression profiling of ischemic stroke during the transition from the acute to subacute stage. Front Neurol. 2019;10:36. [DOI] [PubMed] [PMC]

30.

Zhou L, Xu DY, Sha WG, Shen L, Lu GY. Long non-coding RNA MALAT1 interacts with transcription factor Foxo1 to regulate SIRT1 transcription in high glucose-induced HK-2 cells injury. Biochem Biophys Res Commun. 2018;503:849–55. [DOI] [PubMed]

31.

Cao Y, Wang J, Lu X, Kong X, Bo C, Li S, et al. Construction of a long non-coding RNA-mediated transcription factor and gene regulatory triplet network reveals global patterns and biomarkers for ischemic stroke. Int J Mol Med. 2020;45:333–42. [DOI] [PubMed] [PMC]

32.

Kohn AD, Takeuchi F, Roth RA. Akt, a pleckstrin homology domain containing kinase, is activated primarily by phosphorylation. J Biol Chem. 1996;271:21920–6. [DOI] [PubMed]

33.

Wang Y, Feng F, Zheng P, Wang L, Wang Y, Lv Y, et al. Dysregulated lncRNA and mRNA may promote the progression of ischemic stroke via immune and inflammatory pathways: results from RNA sequencing and bioinformatics analysis. Genes Genomics. 2022;44:97–108. [DOI] [PubMed] [PMC]

34.

Adams BD, Parsons C, Walker L, Zhang WC, Slack FJ. Targeting noncoding RNAs in disease. J Clin Invest. 2017;127:761–71. [DOI] [PubMed] [PMC]

35.

Feng L, Guo J, Ai F. Circulating long noncoding RNA ANRIL downregulation correlates with increased risk, higher disease severity and elevated pro-inflammatory cytokines in patients with acute ischemic stroke. J Clin Lab Anal. 2019;33:e22629. [DOI] [PubMed] [PMC]

36.

Deng QW, Li S, Wang H, Sun HL, Zuo L, Gu ZT, et al. Differential long noncoding RNA expressions in peripheral blood mononuclear cells for detection of acute ischemic stroke. Clin Sci (Lond). 2018;132:1597–614. [DOI] [PubMed]

37.

Sheng Y, Ma J, Zhao J, Qi S, Hu R, Yang Q. Differential expression patterns of specific long noncoding RNAs and competing endogenous RNA network in alopecia areata. J Cell Biochem. 2019;120:10737–47. [DOI] [PubMed]

38.

Zhang L, Liu B, Han J, Wang T, Han L. Competing endogenous RNA network analysis for screening inflammation-related long non-coding RNAs for acute ischemic stroke. Mol Med Rep. 2020;22:3081–94. [DOI] [PubMed] [PMC]

39.

He W, Wei D, Cai D, Chen S, Li S, Chen W. Altered long non-coding RNA transcriptomic profiles in ischemic stroke. Hum Gene Ther. 2018;29:719–32. [DOI] [PubMed]

40.

Zhu R, Zhao Y, Xiao T, Wang Q, Liu X. Association between microRNA binding site polymorphisms in immunoinflammatory genes and recurrence risk of ischemic stroke. Genomics. 2020;112:2241–6. [DOI] [PubMed]

41.

Kajiho H, Saito K, Tsujita K, Kontani K, Araki Y, Kurosu H, et al. RIN3: a novel Rab5 GEF interacting with amphiphysin II involved in the early endocytic pathway. J Cell Sci. 2003;116:4159–68. [DOI] [PubMed]

42.

Chanson M, Kwak BR. Connexin37: a potential modifier gene of inflammatory disease. J Mol Med (Berl). 2007;85:787–95. [DOI] [PubMed]

43.

Collings A, Raitakari OT, Juonala M, Mansikkaniemi K, Kähönen M, Hutri-Kähönen N, et al. The influence of smoking and homocysteine on subclinical atherosclerosis is modified by the connexin37 C1019T polymorphism - the Cardiovascular Risk in Young Finns Study. Clin Chem Lab Med. 2008;46:1102–8. [DOI] [PubMed]

44.

Li H, Yu S, Wang R, Sun Z, Zhou X, Zheng L, et al. Polymorphism of CONNEXIN37 gene is a risk factor for ischemic stroke in Han Chinese population. Lipids Health Dis. 2018;17:72. [DOI] [PubMed] [PMC]

45.

Xie JQ, Lu YP, Sun HL, Gao LN, Song PP, Feng ZJ, et al. Sex difference of ribosome in stroke-induced peripheral immunosuppression by integrated bioinformatics analysis. Biomed Res Int. 2020;2020:3650935. [DOI] [PubMed] [PMC]

46.

Zhou X, Marks PA, Rifkind RA, Richon VM. Cloning and characterization of a histone deacetylase, HDAC9. Proc Natl Acad Sci U S A. 2001;98:10572–7. [DOI] [PubMed] [PMC]

47.

Shroff N, Ander BP, Zhan X, Stamova B, Liu D, Hull H, et al. HDAC9 polymorphism alters blood gene expression in patients with large vessel atherosclerotic stroke. Transl Stroke Res. 2019;10:19–25. [DOI] [PubMed] [PMC]

48.

Williams SR, Hsu FC, Keene KL, Chen WM, Dzhivhuho G, Rowles JL 3rd, et al.; GARNET (The Genomics and Randomized Trials Network) Collaborative Research Group. Genetic drivers of von Willebrand factor levels in an ischemic stroke population and association with risk for recurrent stroke. Stroke. 2017;48:1444–50. [DOI] [PubMed] [PMC]

49.

Davis Armstrong NM, Spragley KJ, Chen WM, Hsu FC, Brewer MS, Horn PJ, et al. Multi-omic analysis of stroke recurrence in African Americans from the Vitamin Intervention for Stroke Prevention (VISP) clinical trial. PLoS One. 2021;16:e0247257. [DOI] [PubMed] [PMC]

50.

Chan SJ, Ng MPE, Zhao H, Ng GJL, De Foo C, Wong PT, et al. Early and sustained increases in leukotriene B4 levels are associated with poor clinical outcome in ischemic stroke patients. Neurotherapeutics. 2020;17:282–93. [DOI] [PubMed] [PMC]

51.

Davis Armstrong NM, Chen WM, Hsu FC, Brewer MS, Cullell N, Fernández-Cadenas I, et al. DNA methylation analyses identify an intronic ZDHHC6 locus associated with time to recurrent stroke in the Vitamin Intervention for Stroke Prevention (VISP) clinical trial. PLoS One. 2021;16:e0254562. [DOI] [PubMed] [PMC]

52.

Bousette N, Abbasi C, Chis R, Gramolini AO. Calnexin silencing in mouse neonatal cardiomyocytes induces Ca2+ cycling defects, ER stress, and apoptosis. J Cell Physiol. 2014;229:374–83. [DOI] [PubMed]

53.

Portela A, Esteller M. Epigenetic modifications and human disease. Nat Biotechnol. 2010;28:1057–68. [DOI] [PubMed]

54.

Heyn H, Li N, Ferreira HJ, Moran S, Pisano DG, Gomez A, et al. Distinct DNA methylomes of newborns and centenarians. Proc Natl Acad Sci U S A. 2012;109:10522–7. [DOI] [PubMed] [PMC]

55.

Bollati V, Schwartz J, Wright R, Litonjua A, Tarantini L, Suh H, et al. Decline in genomic DNA methylation through aging in a cohort of elderly subjects. Mech Ageing Dev. 2009;130:234–9. [DOI] [PubMed] [PMC]

56.

Jones MJ, Goodman SJ, Kobor MS. DNA methylation and healthy human aging. Aging Cell. 2015;14:924– 32. [DOI] [PubMed] [PMC]

57.

Hannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S, et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell. 2013;49:359–67. [DOI] [PubMed] [PMC]

58.

Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14:R115. Erratum in: Genome Biol. 2015;16:96. [DOI] [PubMed] [PMC]

59.

Soriano-Tárraga C, Giralt-Steinhauer E, Mola-Caminal M, Ois A, Rodríguez-Campello A, Cuadrado-Godia E, et al. Biological age is a predictor of mortality in ischemic stroke. Sci Rep. 2018;8:4148. [DOI] [PubMed] [PMC]

60.

Chen BH, Marioni RE, Colicino E, Peters MJ, Ward-Caviness CK, Tsai PC, et al. DNA methylation-based measures of biological age: meta-analysis predicting time to death. Aging (Albany NY). 2016;8:1844–65. [DOI] [PubMed] [PMC]

61.

Marioni RE, Shah S, McRae AF, Chen BH, Colicino E, Harris SE, et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol. 2015;16:25. [DOI] [PubMed] [PMC]

62.

Shen R, Zhao X, He L, Ding Y, Xu W, Lin S, et al. Upregulation of RIN3 induces endosomal dysfunction in Alzheimer’s disease. Transl Neurodegener. 2020;9:26. [DOI] [PubMed] [PMC]

63.

Boden KA, Barber IS, Clement N, Patel T, Guetta-Baranes T, Brookes KJ, et al.; ARUK Consortium; Morgan K, Seymour GB, Bottley A. Methylation profiling RIN3 and MEF2C identifies epigenetic marks associated with sporadic early onset Alzheimer’s disease. J Alzheimers Dis Rep. 2017;1:97–108. [DOI] [PubMed] [PMC]

64.

Miao M, Yuan F, Ma X, Yang H, Gao X, Zhu Z, et al. Methylation of the RIN3 promoter is associated with transient ischemic stroke/mild ischemic stroke with early cognitive impairment. Neuropsychiatr Dis Treat. 2021;17:2587–98. Erratum in: Neuropsychiatr Dis Treat. 2021;17:3081–3. [DOI] [PubMed] [PMC]

65.

Sikora M, Lewandowska I, Kupc M, Kubalska J, Graban A, Marczak Ł, et al. Serum proteome alterations in human cystathionine β-synthase deficiency and ischemic stroke subtypes. Int J Mol Sci. 2019;20:3096. [DOI] [PubMed] [PMC]

66.

Tufekci KU, Vurgun U, Yigitaslan O, Keskinoglu P, Yaka E, Kutluk K, et al. Follow-up analysis of serum TNF-related apoptosis-inducing ligand protein and mRNA expression in peripheral blood mononuclear cells from patients with ischemic stroke. Front Neurol. 2018;9:102. [DOI] [PubMed] [PMC]

67.

Genc S, Kizildag S, Genc K, Ates H, Atabey N. Interferon gamma and lipopolysaccharide upregulate TNF-related apoptosis-inducing ligand expression in murine microglia. Immunol Lett. 2003;85:271–4. Erratum in: Immunol Lett. 2003;90:65. [DOI] [PubMed]

68.

Li SY, Yoshida Y, Kobayashi E, Kubota M, Matsutani T, Mine S, et al. Serum anti-AP3D1 antibodies are risk factors for acute ischemic stroke related with atherosclerosis. Sci Rep. 2021;11:13450. [DOI] [PubMed] [PMC]