Identify biological Alzheimer's disease using a novel nucleic acid-linked protein immunoassay

Yi-Ting Wang^{1

2

3}, Nicholas J Ashton^{4

5

6

7}, Joseph Therriault^{1

2}, Andréa L Benedet⁴, Arthur C Macedo^{1

2

3}, Ilaria Pola⁴, Etienne Aumont^{1

2

3}, Guglielmo Di Molfetta⁴, Jaime Fernandez-Arias^{1

2

3}, Kubra Tan⁴, Nesrine Rahmouni^{1

2

3}, Stijn Johannes G Servaes¹, Richard Isaacson^{8

9}, Tevy Chan^{1

2}, Seyyed Ali Hosseini^{1

2

3}, Cécile Tissot¹⁰, Sulantha Mathotaarachchi¹, Jenna Stevenson¹, Firoza Z Lussier¹¹, Tharick A Pascoal¹¹, Serge Gauthier^{1

3}, Kaj Blennow^{4

12

13

14}, Henrik Zetterberg^{4

12

15

16

17

18}, Pedro Rosa-Neto^{1

2

3}

Affiliations

¹ Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, QC, Canada H4H 1R2.
² Montreal Neurological Institute, Montreal, QC, Canada H3A 2B4.
³ Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada H3A 0G4.
⁴ Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, 431 39 Mölndal, Sweden.
⁵ Centre for Age-Related Medicine, Stavanger University Hospital, 4011 Stavanger, Norway.
⁶ Maurice Wohl Clinical Neuroscience Institute, King's College London, London SE5 9RX, UK.
⁷ NIHR Maudsley Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London SE5 8AZ, UK.
⁸ Department of Neurology, Weill Cornell Medicine and New York-Presbyterian, New York, NY 10065, USA.
⁹ Department of Neurology, Florida Atlantic University, Charles E. Schmidt College of Medicine, Boca Raton, FL 33431, USA.
¹⁰ Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
¹¹ Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.
¹² Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 45 Mölndal, Sweden.
¹³ Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, 75013 Paris, France.
¹⁴ Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei 101127, P. R.China.
¹⁵ Department of Neurodegenerative Disease, UCL Institute of Neurology, London WC1N 3BG, UK.
¹⁶ UK Dementia Research Institute at UCL, London W1CE 6BT, UK.
¹⁷ Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China.
¹⁸ Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA.

PMID: 39845736
PMCID: PMC11753389
DOI: 10.1093/braincomms/fcaf004

Identify biological Alzheimer's disease using a novel nucleic acid-linked protein immunoassay

Yi-Ting Wang et al. Brain Commun. 2025.

. 2025 Jan 7;7(1):fcaf004.

doi: 10.1093/braincomms/fcaf004. eCollection 2025.

Authors

Affiliations

¹ Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, QC, Canada H4H 1R2.
² Montreal Neurological Institute, Montreal, QC, Canada H3A 2B4.
³ Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada H3A 0G4.
⁴ Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, 431 39 Mölndal, Sweden.
⁵ Centre for Age-Related Medicine, Stavanger University Hospital, 4011 Stavanger, Norway.
⁶ Maurice Wohl Clinical Neuroscience Institute, King's College London, London SE5 9RX, UK.
⁷ NIHR Maudsley Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London SE5 8AZ, UK.
⁸ Department of Neurology, Weill Cornell Medicine and New York-Presbyterian, New York, NY 10065, USA.
⁹ Department of Neurology, Florida Atlantic University, Charles E. Schmidt College of Medicine, Boca Raton, FL 33431, USA.
¹⁰ Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
¹¹ Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.
¹² Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 45 Mölndal, Sweden.
¹³ Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, 75013 Paris, France.
¹⁴ Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei 101127, P. R.China.
¹⁵ Department of Neurodegenerative Disease, UCL Institute of Neurology, London WC1N 3BG, UK.
¹⁶ UK Dementia Research Institute at UCL, London W1CE 6BT, UK.
¹⁷ Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China.
¹⁸ Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA.

PMID: 39845736
PMCID: PMC11753389
DOI: 10.1093/braincomms/fcaf004

Abstract

Blood-based biomarkers have been revolutionizing the detection, diagnosis and screening of Alzheimer's disease. Specifically, phosphorylated-tau variants (p-tau₁₈₁, p-tau₂₁₇ and p-tau₂₃₁) are promising biomarkers for identifying Alzheimer's disease pathology. Antibody-based assays such as single molecule arrays immunoassays are powerful tools to investigate pathological changes indicated by blood-based biomarkers and have been studied extensively in the Alzheimer's disease research field. A novel proteomic technology-NUcleic acid Linked Immuno-Sandwich Assay (NULISA)-was developed to improve the sensitivity of traditional proximity ligation assays and offer a comprehensive outlook for 120 protein biomarkers in neurodegenerative diseases. Due to the relative novelty of the NULISA technology in quantifying Alzheimer's disease biomarkers, validation through comparisons with more established methods is required. The main objective of the current study was to determine the capability of p-tau variants quantified using NULISA for identifying abnormal amyloid-β and tau pathology. We assessed 397 participants [mean (standard deviation) age, 64.8 (15.7) years; 244 females (61.5%) and 153 males (38.5%)] from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort where participants had plasma measurements of p-tau₁₈₁, p-tau₂₁₇ and p-tau₂₃₁ from NULISA and single molecule arrays immunoassays. Participants also underwent neuroimaging assessments, including structural MRI, amyloid-PET and tau-PET. Our findings suggest an excellent agreement between plasma p-tau variants quantified using NULISA and single molecule arrays immunoassays. Plasma p-tau₂₁₇ measured with NULISA shows excellent discriminative accuracy for abnormal amyloid-PET (area under the receiver operating characteristic curve = 0.918, 95% confidence interval = 0.883 to 0.953, P < 0.0001) and tau-PET (area under the receiver operating characteristic curve = 0.939; 95% confidence interval = 0.909 to 0.969, P < 0.0001). It also presents the capability for differentiating tau-PET staging. Validation of the NULISA-measured plasma biomarkers adds to the current analytical methods for Alzheimer's disease diagnosis, screening and staging and could potentially expedite the development of a blood-based biomarker panel.

Keywords: Alzheimer’s disease; PET; blood-based biomarker; head-to-head comparison.

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Conflict of interest statement

Outside the work presented in this paper, P.R.-N. provides consultancy services for Roche, Cerveau Radiopharmaceuticals, Lilly, Eisai, Pfizer and Novo Nordisk. He also serves as a clinical trial investigator for Biogen, Novo Nordisk and Biogen. S.G. is a member of the scientific advisory boards of Alzheon, AmyriAD, Eisai Canada, Enigma USA, Lilly Canada, Medesis, Okutsa Canada, Roche Canada and TauRx. He is a member of the editorial board of JPAD and of the Neurotorium. He has given lectures under the auspices of Biogen Canada and Lundbeck Korea. H.Z. has served at scientific advisory boards and/or as a consultant for Abbvie, Acumen, Alector, Alzinova, ALZPath, Amylyx, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito Therapeutics, CogRx, Denali, Eisai, Merry Life, Nervgen, Novo Nordisk, Optoceutics, Passage Bio, Pinteon Therapeutics, Prothena, Red Abbey Labs, reMYND, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics and Wave; has given lectures in symposia sponsored by Alzecure, Biogen, Cellectricon, Fujirebio, Lilly, Novo Nordisk and Roche; and is a co-founder of Brain Biomarker Solutions (BBS) in Gothenburg AB, which is a part of the GU Ventures Incubator Program (outside submitted work). K.B. has served as a consultant and on advisory boards for Acumen, ALZPath, BioArctic, Biogen, Eisai, Julius Clinical, Lilly, Novartis, Ono Pharma, Prothena, Roche Diagnostics and Siemens Healthineers; has served at data monitoring committees for Julius Clinical and Novartis; has given lectures, produced educational materials and participated in educational programmes for Biogen, Eisai and Roche Diagnostics; and is a co-founder of BBS in Gothenburg AB, which is a part of the GU Ventures Incubator Program. The remaining authors have no conflicts of interest to report related to this work.

Figures

**Figure 1**
**Head-to-head comparison of the association between amyloid-PET and tau-PET with plasma p-tau concentrations measured using NULISA and Simoa immunoassays.** Voxel-based multivariate linear regression analysis (n = 310) revealed positive associations between amyloid-PET and tau-PET signals in the brain and the concentrations of plasma p-tau biomarkers (p-tau₁₈₁, p-tau₂₁₇ and p-tau₂₃₁) quantified using different immunoassays. Age, sex and *APOEε4* carriage status were employed as covariates in the models. To account for the effects of participants’ biological stage of Alzheimer’s disease, amyloid-PET status (A− or A+) and pathological status (A−T−, A+T− or A+T+) were included as a covariate when assessing the relationship between plasma p-tau biomarkers with amyloid-PET and tau-PET, respectively. Images represent voxel-based t-statistical parametric maps overlaid on the structural MRI reference template. Results were also corrected for multiple comparisons using an FDR cluster threshold of P < 0.001.

**Figure 2**
**Head-to-head comparison of the sex-specific association between amyloid-PET and tau-PET with plasma p-tau₂₁₇ concentrations measured using NULISA and Simoa immunoassays.** Voxel-based multivariate linear regression analysis (n = 310) was conducted. Amyloid-PET: Positive correlations were identified between plasma p-tau₂₁₇ concentration and amyloid-PET in female subjects, whereas this correlation disappeared in males after correcting for amyloid status. Tau-PET: Conversely, concerning the link between plasma p-tau₂₁₇ and tau-PET, both males and females exhibit a positive association in similar brain regions. Images represent voxel-based t-statistical parametric maps overlaid on the structural MRI reference template. Results were corrected for age, *APOEε4* carriage status and multiple comparisons using an FDR cluster threshold of P < 0.001. To account for the effects of participants’ biological stage of Alzheimer’s disease, amyloid-PET status (A− or A+) and pathological status (A−T−, A+T− or A+T+) were also corrected when assessing the relationship between plasma p-tau biomarkers with amyloid-PET and tau-PET, respectively.

**Figure 3**
**Discriminative accuracy of NULISA and Simoa immunoassay–derived p-tau concentrations for biological Alzheimer’s disease.** ROC analyses (n = 310) display discriminative accuracy of plasma p-tau for amyloid-PET status and tau-PET status. (A and B) Overall, plasma p-tau₂₁₇^NULISA performed the best for differentiating amyloid-PET status [(A) entire cohort: AUC = 0.918, 95% CI: 0.883 to 0.953, P < 0.0001; (B) CU individuals only: AUC = 0.879, 95% CI: 0.805 to 0.952, P < 0.0001], followed by plasma p-tau₂₁₇^ALZpath (entire cohort: AUC = 0.910, 95% CI: 0.870 to 0.951, P < 0.0001; CU individuals only: AUC = 0.855, 95% CI: 0.765 to 0.944, P < 0.0001). (C and D) For discriminating tau-PET status, plasma p-tau₂₁₇^Janssen showed the highest accuracy [(C) entire cohort: AUC = 0.961, 95% CI: 0.939 to 0.982, P < 0.0001; (D) CI individuals only: AUC = 0.974, 95% CI: 0.952 to 0.996, P < 0.0001) followed by plasma p-tau₂₁₇^NULISA (entire cohort: AUC = 0.939; 95% CI: 0.909 to 0.969, P < 0.0001; CI individuals only: AUC = 0.965, 95% CI: 0.938 to 0.992, P < 0.0001). CI, cognitively impaired.

**Figure 4**
**Predicting amyloid-PET and tau-PET staging with plasma p-tau₂₁₇ biomarkers.** The scatter plots illustrated the distribution of predicted probabilities of an abnormal amyloid-PET (left) and a tau-PET proxy of moderate/high severity (right) based on a logistic regression model (n = 310) including log2-transformed plasma p-tau₂₁₇ concentrations. The predicted probabilities are displayed for (A) male, (B) female, (C) *APOEε4* non-carrier and (D) *APOEε4* carrier. The x-axis corresponds to individuals’ amyloid and tau status determined by PET. The y-axis displays the predicted probabilities of plasma p-tau₂₁₇ biomarkers for an abnormal PET status (positivity for amyloid-PET and moderate/high severity for tau-PET). Detailed statistical information is displayed in Table 3.

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Identify biological Alzheimer's disease using a novel nucleic acid-linked protein immunoassay

Affiliations

Identify biological Alzheimer's disease using a novel nucleic acid-linked protein immunoassay

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Grants and funding

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