Dumbbell Aptamer Sensor Based on Dual Biomarkers for Early Detection of Alzheimer’s Disease
Abstract
Finding a timely, sensitive, and noninvasive detection method has become an urgent need for asymptomatic early diagnosis of Alzheimer's disease (AD). MicroRNA-193b (miR-193b) and Aβ42 oligomers (AβO42) in neurogenic exosomes were confirmed to reflect pathological changes in the AD early stage. The combination of two biomarkers is promising for the earlier detection of AD. In this study, a detection system based on the principle of the entropy-driven strand displacement reaction (ESDR) was developed, including a dumbbell detection probe (H), an indicator probe (R), and graphene oxide (GO). In the detection system, the two hairpins of H were opened by the interaction of miR-193b (T1) and AβO42 (T2) with the aptamer. Then R hybridized with H and began to displace T, initiating the next round of ESDR to achieve sensitive detection of T. GO specifically adsorbed free R and quenched the fluorescence, further reducing the intensity of the background signal. Both of these points provided the system with a more sensitive analytical performance. The detection limit of miR-193b was 77 pM and the detection limit of AβO42 was 53 pM. This sensor detected the change of "one increase (AβO42) and one decrease (miR-193b)" in the exosome sample. Additionally, results showed that this detection system could distinguish the model of early AD from the non-AD control, which was sufficient for earlier and more sensitive detection of AD. This strategy has strong specificity, high sensitivity, and easy operation, which provides broad prospects for the early diagnosis of AD.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Zhou and colleagues developed a highly sensitive and non-invasive fluorescent biosensor for simultaneously detecting neurogenic exosomes-derived miRNA-193b and Aβ42 oligomers (AβO42) associated with early Alzheimer's disease.
“Recently, Zhou and colleagues have advanced the field of diagnostics with the development of a highly sensitive and non-invasive fluorescent biosensor for simultaneously detecting two critical biomarkers associated with the early stages of AD [236], as illustrated in Fig. 3b.”
From Extracellular vesicles as nanotheranostic platforms for targeted neurological disorder interventions (2024) · cites this paper as [236]
Cites
Sperling, R. A., Aisen, P. S., Beckett, L. A., Bennett, D. A., Craft, S., Fagan, A. M., Iwatsubo, T., Jack, C. R., Kaye, J., Montine, T. J., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.003 · Cited by 7,155 · see citing works
2021 Alzheimer's disease facts and figures
Anonymous (2021) · Alzheimer s & Dementia · doi:10.1002/alz.12328 · Cited by 2,236 · see citing works
Fiandaca, M. S., Kapogiannis, D., Mapstone, M., Boxer, A., Eitan, E., Schwartz, J. B., Abner, E. L., Petersen, R. C., Federoff, H. J., Miller, B. L., et al. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2014.06.008 · Cited by 959 · see citing works
Diagnosis of Early Alzheimer's Disease: Clinical Practice in 2021
Porsteinsson, A. P., Isaacson, R. S., Knox, S., Sabbagh, M. N., & Rubino, I. (2021) · The Journal of Prevention of Alzheimer's Disease · doi:10.14283/jpad.2021.23 · Cited by 744 · see citing works
Early clinical PET imaging results with the novel PHF-tau radioligand [F-18]-T807
Chien, D. T., Bahri, S., Szardenings, A. K., Walsh, J. C., Mu, F., Su, M.-Y., Shankle, W. R., Elizarov, A., & Kolb, H. C. (2013) · Journal of Alzheimer's Disease · doi:10.3233/jad-122059 · Cited by 651 · see citing works
Visualizing Graphene Based Sheets by Fluorescence Quenching Microscopy
Kim, J., Cote, L. J., Kim, F., & Huang, J. (2009) · Journal of the American Chemical Society · doi:10.1021/ja906730d · Cited by 550 · see citing works
Adsorption and Desorption of DNA on Graphene Oxide Studied by Fluorescently Labeled Oligonucleotides
Wu, M., Kempaiah, R., Huang, P. J., Maheshwari, V., & Liu, J. (2011) · Langmuir · doi:10.1021/la1037926 · Cited by 528 · see citing works
Boriachek, K., Islam, M. N., Möller, A., Salomón, C., Nguyen, N., Hossain, M. S. A., Yamauchi, Y., & Shiddiky, M. J. A. (2017) · Small · doi:10.1002/smll.201702153 · Cited by 499 · see citing works
Jia, L., Qiu, Q., Zhang, H., Chu, L., Du, Y., Zhang, J., Zhou, C., Liang, F., Shi, S., Wang, S., et al. (2019) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2019.05.002 · Cited by 376 · see citing works
Self-citationPalmqvist, S., Insel, P. S., Stomrud, E., Janelidze, S., Zetterberg, H., Brix, B., Eichenlaub, U., Dage, J. L., Chai, X., Blennow, K., et al. (2019) · EMBO Molecular Medicine · doi:10.15252/emmm.201911170 · Cited by 353 · see citing works
Wu, C. S., Cansız, S., Zhang, L., Teng, I., Qiu, L., Li, J., Liu, Y., Zhou, C., Hu, R., Zhang, T., et al. (2015) · Journal of the American Chemical Society · doi:10.1021/jacs.5b00542 · Cited by 333 · see citing works
Effects of storage temperature on airway exosome integrity for diagnostic and functional analyses
Maroto, R., Zhao, Y., Jamaluddin, M., Popov, V. L., Wang, H., Kalubowilage, M., Zhang, Y., Luisi, J., Sun, H., Culbertson, C. T., et al. (2017) · Journal of Extracellular Vesicles · doi:10.1080/20013078.2017.1359478 · Cited by 310 · see citing works
Thermophoretic Detection of Exosomal microRNAs by Nanoflares
Zhao, J., Liu, C., Li, Y., Ma, Y., Deng, J., Li, L., & Sun, J. (2020) · Journal of the American Chemical Society · doi:10.1021/jacs.9b13960 · Cited by 288 · see citing works
Yang, T., Liu, C. G., Gao, S. C., Zhang, Y., & Wang, P. C. (2018) · PubMed · doi:10.3967/bes2018.011 · Cited by 230 · see citing works
Mechanisms of DNA Sensing on Graphene Oxide
Liu, B., Sun, Z., Zhang, X., & Liu, J. (2013) · Analytical Chemistry · doi:10.1021/ac401845p · Cited by 228 · see citing works
Liu, C., Song, J., Zhang, Y., & Wang, P. (2014) · Molecular Medicine Reports · doi:10.3892/mmr.2014.2484 · Cited by 221 · see citing works
Selection of DNA Aptamers That Recognize α-Synuclein Oligomers Using a Competitive Screening Method
Tsukakoshi, K., Abe, K., Sode, K., & Ikebukuro, K. (2012) · Analytical Chemistry · doi:10.1021/ac300330g · Cited by 211 · see citing works
Handling and storage of human body fluids for analysis of extracellular vesicles
Yuana, Y., Böing, A. N., Grootemaat, A. E., van der Pol, E., Hau, C. M., Čižmár, P., Buhr, E., Sturk, A., & Nieuwland, R. (2015) · Journal of Extracellular Vesicles · doi:10.3402/jev.v4.29260 · Cited by 208 · see citing works
Li, C., Wang, N., Zheng, G., & Yang, L. (2021) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.1c14818 · Cited by 167 · see citing works
Tian, C., Stewart, T., Hong, Z., Guo, Z., Aro, P., Soltys, D., Pan, C., Peskind, E. R., Zabetian, C. P., Shaw, L. M. J., et al. (2022) · Alzheimer s & Dementia · doi:10.1002/alz.12723 · Cited by 80 · see citing works
Self-citationZhou, Y., Li, C., Li, X., Zhu, X., Ye, B., & Xu, M. (2018) · Analytical Methods · doi:10.1039/c8ay00736e · Cited by 72 · see citing works
Kim, J., Kim, M., Kang, S. M., Lim, K., Kim, T. S., & Kang, J. Y. (2014) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2014.10.042 · Cited by 66 · see citing works
Sequence of Alzheimer disease biomarker changes in cognitively normal adults
Luo, J. R., Agboola, F., Grant, E., Masters, C. L., Albert, M., Johnson, S. C., McDade, E., Vöglein, J., Fagan, A. M., Benzinger, T. L. S., et al. (2020) · Neurology · doi:10.1212/wnl.0000000000010747 · Cited by 61 · see citing works
Alzheimer's disease: progress in prediction
Petersen, R. C. (2009) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70330-8 · Cited by 60 · see citing works
Zhong, W., Pu, Y. D., Tan, W., Liu, J., Liao, J., Liu, B., Chen, K., Yu, B., Hu, Y., Deng, Y., et al. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b01000 · Cited by 60 · see citing works
Self-citationEffects of Aluminium on β-Amyloid (1–42) and Secretases (APP-Cleaving Enzymes) in Rat Brain
Wang, L., Hu, J., Zhao, Y., Lu, X., Zhang, Q., & Niu, Q. L. (2014) · Neurochemical Research · doi:10.1007/s11064-014-1317-z · Cited by 59 · see citing works
Karki, H. P., Jang, Y., Jung, J., & Oh, J. (2021) · Journal of Nanobiotechnology · doi:10.1186/s12951-021-00814-7 · Cited by 51 · see citing works
Alteration of Aβ metabolism-related molecules in predementia induced by AlCl3 and d-galactose
Sun, Z.-Z., Chen, Z.-B., Jiang, H., Li, L.-L., Li, E.-G., & Xu, Y. (2009) · AGE · doi:10.1007/s11357-009-9099-y · Cited by 50 · see citing works
Zhou, J., Meng, L., Ye, W., Wang, Q., Geng, S., & Sun, C. (2018) · Analytica Chimica Acta · doi:10.1016/j.aca.2018.03.016 · Cited by 49 · see citing works
Self-citationNabers, A., Hafermann, H., Wiltfang, J., & Gerwert, K. B. (2019) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2019.01.008 · Cited by 49 · see citing works
Kim, K. Y., Shin, K. Y., & Chang, K. (2021) · Biomolecules · doi:10.3390/biom11070980 · Cited by 35 · see citing works
Aubret, M., Savonnet, M., Laurent, P., Roupioz, Y., Cubizolles, M., & Buhot, A. (2022) · Analytical Chemistry · doi:10.1021/acs.analchem.1c05532 · Cited by 33 · see citing works
Kulichikhin, K. Y., Fedotov, S. A., Rubel, M. S., Zalutskaya, N. M., Zobnina, A. E., Malikova, O. A., Незнанов, Н. Г., Chernoff, Y. O., & Rubel, A. A. (2021) · Prion · doi:10.1080/19336896.2021.1917289 · Cited by 33 · see citing works
Hierarchical and ultra-sensitive amyloid beta oligomer sensor for practical applications
Qin, J., Kim, S., Cho, M., & Lee, Y. (2020) · Chemical Engineering Journal · doi:10.1016/j.cej.2020.126055 · Cited by 31 · see citing works
Huang, Z., Luo, Z., Chen, J., Xu, Y., & Duan, Y. (2018) · ACS Sensors · doi:10.1021/acssensors.8b00935 · Cited by 31 · see citing works
Wu, J., Gao, X. Q., Ge, L., Zhao, G., & Wang, G. (2019) · RSC Advances · doi:10.1039/c9ra02475a · Cited by 27 · see citing works
Zhai, F.-H., Zhan, Q., Wang, K., Chen, S., & He, R. (2020) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2020.128394 · Cited by 20 · see citing works
Zhang, T., Xu, L., Jiang, B., Yuan, R., & Xiang, Y. (2019) · Analytica Chimica Acta · doi:10.1016/j.aca.2019.11.044 · Cited by 17 · see citing works
Shen, X., Zhang, Y., Sun, J., Lü, H., Ouyang, J., & Na, N. (2019) · Chemical Science · doi:10.1039/c9sc01894h · Cited by 16 · see citing works
Li, X., Song, G., Dou, L., Yan, S., Zhang, M., Yuan, W., Lai, S., Jiang, X. Q., Li, K., Sun, K., et al. (2021) · Nanoscale · doi:10.1039/d0nr08729g · Cited by 15 · see citing works
Nardo, L., Re, F., Brioschi, S., Cazzaniga, E., Orlando, A., Minniti, S., Lamperti, M., Gregori, M., Cassina, V., Brogioli, D., et al. (2016) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/j.bbagen.2016.01.003 · Cited by 14 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Extracellular vesicles as nanotheranostic platforms for targeted neurological disorder interventions
Choi, H. K., Chen, M., Goldston, L. L., & Lee, K.-B. (2024) · Nano Convergence · doi:10.1186/s40580-024-00426-5 · Cited by 26 · see citing works
Salvi, S., Garg, L., & Gurupur, V. P. (2025) · Sensors · doi:10.3390/s25175252 · Cited by 22 · see citing works
Central Nervous System-Derived Extracellular Vesicles as Biomarkers in Alzheimer’s Disease
Yu, Y., Wang, Z., Chai, Z., Ma, S., Li, A., & Li, Y. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26178272 · Cited by 22 · see citing works
Entropy driven-based catalytic biosensors for bioanalysis: From construction to application-A review
Yang, S., Zhan, X., Yuan, L., de la Chapelle, M. L., Fu, W., & Xiang, Y. (2024) · Analytica Chimica Acta · doi:10.1016/j.aca.2024.343549 · Cited by 21 · see citing works
Zhang, J., Chen, Q., Gao, X., Lin, Q., Suo, Z., Wu, D., Wu, X., & Chen, Q. (2023) · Biosensors · doi:10.3390/bios13060647 · Cited by 17 · see citing works
Self-citationLin, S.-P., Lee, W.-J., Sun, M.-C., Yang, Y.-H., Vinzons, L. U., Lin, Y.-M., & Wei, Y.-T. (2023) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.3c12766 · Cited by 11 · see citing works
Zhang, J., Zhao, Y., Hu, H., Lv, M., & Zhang, H. (2025) · Microchimica Acta · doi:10.1007/s00604-024-06862-8 · Cited by 9 · see citing works
Self-citationWang, H., Qiu, M., Wang, C., Zhang, L., Fan, N., Chen, Z., Liu, Y., Li, T., Wang, Z., Zhu, Y., et al. (2025) · Research · doi:10.34133/research.0772 · Cited by 9 · see citing works
Cheng, T., Jiao, K., Sun, M., Yu, J., Jiao, J., & Jiao, J. (2024) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2024.136797 · Cited by 8 · see citing works
Biological applications of graphene-based nanomaterials in neurodegenerative diseases
Zhu, R.-K., Shi, J. Y., Zhou, H.-J., Ge, L., Yin, W.-H., Zeng, H., & Wang, X. (2025) · Materials Today Bio · doi:10.1016/j.mtbio.2025.102064 · Cited by 8 · see citing works
Li, Y., Tang, X., Deng, R., Feng, L., Xie, S., Chen, M., Zheng, J., & Chang, K. (2024) · ACS Omega · doi:10.1021/acsomega.4c02652 · Cited by 8 · see citing works
Potential application of aptamers combined with DNA nanoflowers in neurodegenerative diseases
Hang, Z., Zhou, L., Bian, X., Liu, G., Cui, F., Du, H., & Wen, Y. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102444 · Cited by 7 · see citing works
The Diagnostic and Therapeutic Potential of Oligonucleotide Aptamers in Alzheimer’s Disease
Katsipis, G., Tzekaki, E. E., Iasonidou, S., & Pantazaki, Α. A. (2025) · Cells · doi:10.3390/cells14181424 · Cited by 6 · see citing works
Zhong, J., Wang, Q., Li, Q., Cui, S., Chen, K., Gu, T., Li, S., & Bai, P. (2025) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2025.137816 · Cited by 6 · see citing works
Rigid DNA Frameworks Anchored Transistor Enabled Ultrasensitive Detection of Aβ-42 in Serum
Wu, Y., Lu, R., Ren, P., & Xie, Z. (2025) · Sensors · doi:10.3390/s25113260 · Cited by 6 · see citing works
Yin, Z., Liu, X., Li, S., Yuan, R., & Xiang, Y. (2024) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2024.136750 · Cited by 4 · see citing works
Peng, L., Qi, H., Lin, J., & Li, F. (2025) · Measurement · doi:10.1016/j.measurement.2025.119934 · Cited by 4 · see citing works
Cheng, T., Yu, J., Sun, J., Zhou, H., Xu, Z., Hao, G., & Jiao, J. (2025) · Chemical Engineering Journal · doi:10.1016/j.cej.2025.171406 · Cited by 4 · see citing works
He, S., Liu, R., Bao, X., Pang, J., Zhang, X., Liu, Y., Lin, W., Liu, J., Li, T., Li, Y., et al. (2025) · Analytica Chimica Acta · doi:10.1016/j.aca.2025.344964 · Cited by 4 · see citing works
Xie, P., Wang, X., Wang, H., Xue, H., He, S., Li, L., Wong, M. S., & Qiao, X. G. (2026) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2026.118430 · Cited by 2 · see citing works
Hydrogel-based neural engineering for skin wound healing
Zhang, Y., Liu, X., & Wu, G. (2026) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2026.1797417 · Cited by 1 · see citing works
Cao, Y., Li, M. S., Xu, G., Xia, S., Wu, X., Shi, K., Xue, R., Wang, H., Ye, R., Han, Z., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.02.686180
Zhou, J., Dong, X., Feng, J., Wei, Y., Zhang, T., Wang, Y., Song, W., & Chen, X. (2026) · Nanomedicine Nanotechnology Biology and Medicine · doi:10.1016/j.nano.2026.102912
Self-citationMXene–Protein Corona Interfaces for Molecular Profiling of Alzheimer’s Disease
Velazquez, S., Juber, M. C., Brindley, D., Thakur, A., Anasori, B., Lau, E., & Ashkarran, A. A. (2026) · ACS Applied Bio Materials · doi:10.1021/acsabm.6c01228
Nanomaterials and Composites in Biosensing, Disease Detection and Diagnostic Applications
Varghese, A. L., & Abraham, I. (2026) · Advanced structured materials · doi:10.1007/978-981-92-1034-3_7
DNA- and aptamer-based biosensors for Alzheimer's disease biomarkers toward clinical translation
Pahlavan, Y., Nozari-Asbemarz, M., Amani, M., Hasani, E., Aliakbari, M., Khaleghinejad, S. H., Pahlavan, F., Emami, A., & Imanzadeh, H. (2026) · Talanta · doi:10.1016/j.talanta.2026.130583
- Authors
- Zhou, J., Sun, Y., Zhang, J., Luo, F., Ma, H., Guan, M., Feng, J., & Dong, X.
- Affiliations
- Zhengzhou University (CN)
- Corresponding author
- Zhou, Jie
- Venue
- ACS Applied Materials & Interfaces
- Publisher
- American Chemical Society (ACS)
- Published
- 2023-03-23
- Volume
- 15
- Issue
- 13
- Pages
- 16394-16407
- ISSN
- 1944-8244 (ISSN-L)
- 1944-8252
- OpenAlex
- W4360600710
- Cited by
- 26
- References
- 41
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 6 · 2023: 2
- FWCI
- 2.31
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- ACS Applied Materials & Interfaces (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (U1904135)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Physical Sciences › Engineering › Biomedical Engineering › Biosensors and Analytical Detection
- Keywords
- Alzheimer's disease, early diagnosis, aptasensor, amyloid-beta oligomers, exosomes, graphene oxide, fluorescence quenching, nucleic acid biosensors
- MeSH terms
- Alzheimer Disease, Graphite, Humans, Biosensing Techniques, Biomarkers, MicroRNAs, Early Diagnosis, Aptamers, Nucleotide
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review