Scheltens, P. et al. Alzheimer’s disease. Lancet 397, 1577–1590 (2021).

Article CAS PubMed PubMed Central Google Scholar

Swaddiwudhipong, N. et al. Pre-diagnostic cognitive and functional impairment in multiple sporadic neurodegenerative diseases. Alzheimers Dement. 19, 1752–1763 (2023).

Article PubMed Google Scholar

Shah, H. et al. Research priorities to reduce the global burden of dementia by 2025. Lancet Neurol. 15, 1285–1294 (2016).

Article PubMed Google Scholar

Teunissen, C. E. et al. Blood-based biomarkers for Alzheimer’s disease: towards clinical implementation. Lancet Neurol. 21, 66–77 (2022).

Article CAS PubMed Google Scholar

Zetterberg, H. Biofluid-based biomarkers for Alzheimer’s disease-related pathologies: an update and synthesis of the literature. Alzheimers Dement. 18, 1687–1693 (2022).

Article PubMed PubMed Central Google Scholar

Hansson, O. et al. The Alzheimer’s Association appropriate use recommendations for blood biomarkers in Alzheimer’s disease. Alzheimers Dement. 18, 2669–2686 (2022).

Article CAS PubMed PubMed Central Google Scholar

Nakamura, A. et al. High performance plasma amyloid-beta biomarkers for Alzheimer’s disease. Nature 554, 249–254 (2018).

Article ADS CAS PubMed Google Scholar

Palmqvist, S. et al. Prediction of future Alzheimer’s disease dementia using plasma phospho-tau combined with other accessible measures. Nat. Med. 27, 1034–1042 (2021).

Article CAS PubMed Google Scholar

Verberk, I. M. W. et al. Serum markers glial fibrillary acidic protein and neurofilament light for prognosis and monitoring in cognitively normal older people: a prospective memory clinic-based cohort study. Lancet Healthy Longev. 2, e87–e95 (2021).

Article PubMed Google Scholar

Kim, K. et al. Clinically accurate diagnosis of Alzheimer’s disease via multiplexed sensing of core biomarkers in human plasma. Nat. Commun. 11, 119 (2020).

Article ADS CAS PubMed PubMed Central Google Scholar

Ashton, N. J. et al. Differential roles of Aβ42/40, p-tau231 and p-tau217 for Alzheimer’s trial selection and disease monitoring. Nat. Med. 28, 2555–2562 (2022).

Article CAS PubMed PubMed Central Google Scholar

Karikari, T. K. et al. Blood phosphorylated tau 181 as a biomarker for Alzheimer’s disease: a diagnostic performance and prediction modelling study using data from four prospective cohorts. Lancet Neurol. 19, 422–433 (2020).

Article CAS PubMed Google Scholar

Mattsson-Carlgren, N. et al. Prediction of longitudinal cognitive decline in preclinical Alzheimer disease using plasma biomarkers. JAMA Neurol. 80, 360–369 (2023).

Article PubMed PubMed Central Google Scholar

Karikari, T. K. et al. Blood phospho-tau in Alzheimer disease: analysis, interpretation, and clinical utility. Nat. Rev. Neurol. 18, 400–418 (2022).

Article CAS PubMed Google Scholar

Tanaka, T. et al. Plasma proteomic signatures predict dementia and cognitive impairment. Alzheimers Dement. (N Y) 6, e12018 (2020).

Article PubMed Google Scholar

Hye, A. et al. Proteome-based plasma biomarkers for Alzheimer’s disease. Brain 129, 3042–3050 (2006).

Article CAS PubMed Google Scholar

Bai, B. et al. Proteomic landscape of Alzheimer’s disease: novel insights into pathogenesis and biomarker discovery. Mol. Neurodegener. 16, 55 (2021).

Article CAS PubMed PubMed Central Google Scholar

Walker, K. A. et al. Large-scale plasma proteomic analysis identifies proteins and pathways associated with dementia risk. Nat. Aging 1, 473–489 (2021).

Article PubMed PubMed Central Google Scholar

Dubois, B. et al. Clinical diagnosis of Alzheimer’s disease: recommendations of the International Working Group. Lancet Neurol. 20, 484–496 (2021).

Article CAS PubMed PubMed Central Google Scholar

de Wolf, F. et al. Plasma tau, neurofilament light chain and amyloid-β levels and risk of dementia; a population-based cohort study. Brain 143, 1220–1232 (2020).

Article PubMed PubMed Central Google Scholar

Ma, W. et al. Elevated levels of serum neurofilament light chain associated with cognitive impairment in vascular dementia. Dis. Markers 2020, 6612871 (2020).

Article PubMed PubMed Central Google Scholar

Benedet, A. L. et al. Differences between plasma and cerebrospinal fluid glial fibrillary acidic protein levels across the Alzheimer disease continuum. JAMA Neurol. 78, 1471–1483 (2021).

Article PubMed Google Scholar

Cicognola, C. et al. Plasma glial fibrillary acidic protein detects Alzheimer pathology and predicts future conversion to Alzheimer dementia in patients with mild cognitive impairment. Alzheimers Res. Ther. 13, 68 (2021).

Article CAS PubMed PubMed Central Google Scholar

McGrath, E. R. et al. Growth differentiation factor 15 and NT-proBNP as blood-based markers of vascular brain injury and dementia. J. Am. Heart Assoc. 9, e014659 (2020).

Article CAS PubMed PubMed Central Google Scholar

Whelan, C. D. et al. Multiplex proteomics identifies novel CSF and plasma biomarkers of early Alzheimer’s disease. Acta Neuropathol. Commun. 7, 169 (2019).

Article PubMed PubMed Central Google Scholar

Dulewicz, M., Kulczyńska-Przybik, A., Słowik, A., Borawska, R. & Mroczko, B. Neurogranin and neuronal pentraxin receptor as synaptic dysfunction biomarkers in Alzheimer’s disease. J. Clin. Med. 10, 4575 (2021).

Article CAS PubMed PubMed Central Google Scholar

O’Connor, A. et al. Plasma GFAP in presymptomatic and symptomatic familial Alzheimer’s disease: a longitudinal cohort study. J. Neurol. Neurosurg. Psychiatry 94, 90–92 (2023).

Article PubMed Google Scholar

Kuhle, J. et al. Serum neurofilament light chain is a biomarker of human spinal cord injury severity and outcome. J. Neurol. Neurosurg. Psychiatry 86, 273–279 (2015).

Article PubMed Google Scholar

Fuchs, T. et al. Macrophage inhibitory cytokine-1 is associated with cognitive impairment and predicts cognitive decline – the Sydney Memory and Aging Study. Aging Cell 12, 882–889 (2013).

Article CAS PubMed Google Scholar

Babu, H. et al. Systemic inflammation and the increased risk of inflamm-aging and age-associated diseases in people living with HIV on long term suppressive antiretroviral therapy. Front. Immunol. 10, 1965 (2019).

Article CAS PubMed PubMed Central Google Scholar

Castellano, J. M. et al. Low-density lipoprotein receptor overexpression enhances the rate of brain-to-blood Aβ clearance in a mouse model of β-amyloidosis. Proc. Natl Acad. Sci. USA 109, 15502–15507 (2012).

Article ADS CAS PubMed PubMed Central Google Scholar

Li, W. et al. Dl-3-n-butylphthalide reduces cognitive impairment induced by chronic cerebral hypoperfusion through GDNF/GFRα1/Ret signaling preventing hippocampal neuron apoptosis. Front. Cell Neurosci. 13, 351 (2019).

Article CAS PubMed PubMed Central Google Scholar

Oeckl, P. et al. Serum GFAP differentiates Alzheimer’s disease from frontotemporal dementia and predicts MCI-to-dementia conversion. J. Neurol. Neurosurg. Psychiatry 93, 659–667 (2022).

Article Google Scholar

Kivisäkk, P. et al. Plasma biomarkers for diagnosis of Alzheimer’s disease and prediction of cognitive decline in individuals with mild cognitive impairment. Front. Neurol. 14, 1069411 (2023).

Article PubMed PubMed Central Google Scholar

Beyer, L. et al. Amyloid-beta misfolding and GFAP predict risk of clinical Alzheimer’s disease diagnosis within 17 years. Alzheimers Dement. 19, 1020–1028 (2023).

Article CAS Google Scholar

Stocker, H. et al. Association of plasma biomarkers, p-tau181, glial fibrillary acidic protein, and neurofilament light, with intermediate and long-term clinical Alzheimer’s disease risk: results from a prospective cohort followed over 17 years. Alzheimers Dement. 19, 25–35 (2023).

Article CAS PubMed Google Scholar

Oeckl, P. et al. Glial fibrillary acidic protein in serum is increased in Alzheimer’s disease and correlates with cognitive impairment. J. Alzheimers Dis. 67, 481–488 (2019).

Article CAS PubMed Google Scholar

Heller, C. et al. Plasma glial fibrillary acidic protein is raised in progranulin-associated frontotemporal dementia. J. Neurol. Neurosurg. Psychiatry 91, 263–270 (2020).

Article PubMed Google Scholar

Verberk, I. M. W. et al. Combination of plasma amyloid beta_(1-42/1-40) and glial fibrillary acidic protein strongly associates with cerebral amyloid pathology. Alzheimers Res. Ther. 12, 118 (2020).

Article CAS PubMed PubMed Central Google Scholar

Rajan, K. B. et al. Remote blood biomarkers of longitudinal cognitive outcomes in a population study. Ann. Neurol. 88, 1065–1076 (2020).

Article CAS PubMed PubMed Central Google Scholar

Katisko, K. et al. GFAP as a biomarker in frontotemporal dementia and primary psychiatric disorders: diagnostic and prognostic performance. J. Neurol. Neurosurg. Psychiatry 92, 1305–1312 (2021).

Article PubMed Google Scholar

Katsanos, A. H. et al. Plasma glial fibrillary acidic protein in the differential diagnosis of intracerebral hemorrhage. Stroke 48, 2586–2588 (2017).

Article CAS PubMed Google Scholar

Undén, J. et al. Explorative investigation of biomarkers of brain damage and coagulation system activation in clinical stroke differentiation. J. Neurol. 256, 72–77 (2009).

Article PubMed Google Scholar

Elahi, F. M. et al. Plasma biomarkers of astrocytic and neuronal dysfunction in early- and late-onset Alzheimer’s disease. Alzheimers Dement. 16, 681–695 (2020).

Article CAS PubMed PubMed Central Google Scholar

Shir, D. et al. Association of plasma glial fibrillary acidic protein (GFAP) with neuroimaging of Alzheimer’s disease and vascular pathology. Alzheimers Dement. (Amst.) 14, e12291 (2022).

Article PubMed Google Scholar

Vermeer, S. E. et al. Silent brain infarcts and the risk of dementia and cognitive decline. N. Engl. J. Med. 348, 1215–1222 (2003).

Article PubMed Google Scholar

Prins, N. D. & Scheltens, P. White matter hyperintensities, cognitive impairment and dementia: an update. Nat. Rev. Neurol. 11, 157–165 (2015).

Article PubMed Google Scholar

Cullen, N. C. et al. Plasma biomarkers of Alzheimer’s disease improve prediction of cognitive decline in cognitively unimpaired elderly populations. Nat. Commun. 12, 3555 (2021).

Article ADS CAS PubMed PubMed Central Google Scholar

Fyfe, I. Neurofilament light chain – new potential for prediction and prognosis. Nat. Rev. Neurol. 15, 557 (2019).

Article PubMed Google Scholar

Pilotto, A. et al. Plasma neurofilament light chain predicts cognitive progression in prodromal and clinical dementia with Lewy bodies. J. Alzheimers Dis. 82, 913–919 (2021).

Article CAS PubMed Google Scholar

Gisslén, M. et al. Plasma concentration of the neurofilament light protein (NFL) is a biomarker of CNS injury in HIV infection: a cross-sectional study. EBioMedicine 3, 135–140 (2016).

Article PubMed Google Scholar

Chai, Y. L. et al. Growth differentiation factor-15 and white matter hyperintensities in cognitive impairment and dementia. Medicine (Baltimore) 95, e4566 (2016).

Article CAS PubMed Google Scholar

Walker, K. A. et al. Proteomics analysis of plasma from middle-aged adults identifies protein markers of dementia risk in later life. Sci. Transl. Med. 15, eadf5681 (2023).

Article CAS PubMed Google Scholar

Schindowski, K. et al. Regulation of GDF-15, a distant TGF-β superfamily member, in a mouse model of cerebral ischemia. Cell Tissue Res. 343, 399–409 (2011).

Article CAS PubMed Google Scholar

Andersson, C. et al. Associations of circulating growth differentiation factor-15 and ST2 concentrations with subclinical vascular brain injury and incident stroke. Stroke 46, 2568–2575 (2015).

Article CAS PubMed PubMed Central Google Scholar

van Dijk, E. J. et al. Progression of cerebral small vessel disease in relation to risk factors and cognitive consequences: Rotterdam Scan study. Stroke 39, 2712–2719 (2008).

Article PubMed Google Scholar

Conte, M. et al. GDF15, an emerging key player in human aging. Ageing Res. Rev. 75, 101569 (2022).

Article CAS PubMed Google Scholar

Wang, D. et al. GDF15: emerging biology and therapeutic applications for obesity and cardiometabolic disease. Nat. Rev. Endocrinol. 17, 592–607 (2021).

Article CAS PubMed Google Scholar

Marks, J. D. et al. Comparison of plasma neurofilament light and total tau as neurodegeneration markers: associations with cognitive and neuroimaging outcomes. Alzheimers Res. Ther. 13, 199 (2021).

Article CAS PubMed PubMed Central Google Scholar

Cousins, K. A. Q. et al. ATN incorporating cerebrospinal fluid neurofilament light chain detects frontotemporal lobar degeneration. Alzheimers Dement. 17, 822–830 (2021).

Article CAS PubMed Google Scholar

Illán-Gala, I. et al. Plasma tau and neurofilament light in frontotemporal lobar degeneration and Alzheimer disease. Neurology 96, e671–e683 (2021).

Article PubMed PubMed Central Google Scholar

Jiang, Y. et al. Large-scale plasma proteomic profiling identifies a high-performance biomarker panel for Alzheimer’s disease screening and staging. Alzheimers Dement. 18, 88–102 (2022).

Article CAS PubMed Google Scholar

Prince, M. et al. World Alzheimer Report 2015—The Global Impact of Dementia: An Analysis of Prevalence, Incidence, Cost and Trends. Alzheimer’s Disease International www.alzint.org/resource/world-alzheimer-report-2015/ (2015).

You, J. et al. Development of a novel dementia risk prediction model in the general population: a large, longitudinal, population-based machine-learning study. EClinicalMedicine 53, 101665 (2022).

Article PubMed PubMed Central Google Scholar

Sun, B. B. et al. Plasma proteomic associations with genetics and health in the UK Biobank. Nature 622, 329–338 (2023).

Article CAS PubMed PubMed Central Google Scholar

Dhindsa, R. S. et al. Rare variant associations with plasma protein levels in the UK Biobank. Nature 622, 339–347 (2023).

Article ADS CAS PubMed PubMed Central Google Scholar

Wik, L. et al. Proximity extension assay in combination with next-generation sequencing for high-throughput proteome-wide analysis. Mol. Cell Proteomics 20, 100168 (2021).

Article CAS PubMed PubMed Central Google Scholar

Elliott, P., Peakman, T. C. & UK Biobank The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine. Int. J. Epidemiol. 37, 234–244 (2008).

Article PubMed Google Scholar

You, J. et al. Plasma proteomic profiles predict individual future health risk. Nat. Commun. 14, 7817 (2023).

Article ADS CAS PubMed PubMed Central Google Scholar

Tynkkynen, J. et al. Association of branched-chain amino acids and other circulating metabolites with risk of incident dementia and Alzheimer’s disease: a prospective study in eight cohorts. Alzheimers Dement. 14, 723–733 (2018).

Article PubMed PubMed Central Google Scholar

Chen, E. Y. et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14, 128 (2013).

Article PubMed PubMed Central Google Scholar

Korthauer, K. et al. A practical guide to methods controlling false discoveries in computational biology. Genome Biol. 20, 118 (2019).

Article MathSciNet PubMed PubMed Central Google Scholar

Guolin K. et al. LightGBM: a highly efficient gradient boosting decision tree. In Advances in Neural Information Processing Systems 30 (NIPS 2017) (eds von Luxburg, U., Guyon, I., Bengio, S., Wallach, H. & Fergus, R.) 3149–3157 (Curran Associates Inc., 2017).

DeLong, E. R., DeLong, D. M. & Clarke-Pearson, D. L. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44, 837–845 (1988).

Article CAS PubMed Google Scholar

Robin, X. et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 12, 77 (2011).

Article PubMed PubMed Central Google Scholar

Fang, F. et al. Lipids, apolipoproteins, and the risk of Parkinson disease. Circ. Res. 125, 643–652 (2019).

Article CAS PubMed Google Scholar

Central articles