1
|
Zakharova NV, Bugrova AE, Indeykina MI, Fedorova YB, Kolykhalov IV, Gavrilova SI, Nikolaev EN, Kononikhin AS. Proteomic Markers and Early Prediction of Alzheimer's Disease. BIOCHEMISTRY. BIOKHIMIIA 2022; 87:762-776. [PMID: 36171657 DOI: 10.1134/s0006297922080089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 06/06/2022] [Accepted: 06/07/2022] [Indexed: 06/16/2023]
Abstract
Alzheimer's disease (AD) is the most common socially significant neurodegenerative pathology, which currently affects more than 30 million elderly people worldwide. Since the number of patients grows every year and may exceed 115 million by 2050, and due to the lack of effective therapies, early prediction of AD remains a global challenge, solution of which can contribute to the timely appointment of a preventive therapy in order to avoid irreversible changes in the brain. To date, clinical assays for the markers of amyloidosis in cerebrospinal fluid (CSF) have been developed, which, in conjunction with the brain MRI and PET studies, are used either to confirm the diagnosis based on obligate clinical criteria or to predict the risk of AD developing at the stage of mild cognitive impairment (MCI). However, the problem of predicting AD at the asymptomatic stage remains unresolved. In this regard, the search for new protein markers and studies of proteomic changes in CSF and blood plasma are of particular interest and may consequentially identify particular pathways involved in the pathogenesis of AD. Studies of specific proteomic changes in blood plasma deserve special attention and are of increasing interest due to the much less invasive method of sample collection as compared to CSF, which is important when choosing the object for large-scale screening. This review briefly summarizes the current knowledge on proteomic markers of AD and considers the prospects of developing reliable methods for early identification of AD risk factors based on the proteomic profile.
Collapse
Affiliation(s)
- Natalia V Zakharova
- Emanuel Institute for Biochemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia.
| | - Anna E Bugrova
- Emanuel Institute for Biochemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | - Maria I Indeykina
- Emanuel Institute for Biochemical Physics, Russian Academy of Sciences, Moscow, 119334, Russia
| | | | | | | | - Evgeny N Nikolaev
- Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
| | | |
Collapse
|
2
|
Prognosis of Alzheimer’s Disease Using Quantitative Mass Spectrometry of Human Blood Plasma Proteins and Machine Learning. Int J Mol Sci 2022; 23:ijms23147907. [PMID: 35887259 PMCID: PMC9318764 DOI: 10.3390/ijms23147907] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/14/2022] [Accepted: 07/16/2022] [Indexed: 12/16/2022] Open
Abstract
Early recognition of the risk of Alzheimer’s disease (AD) onset is a global challenge that requires the development of reliable and affordable screening methods for wide-scale application. Proteomic studies of blood plasma are of particular relevance; however, the currently proposed differentiating markers are poorly consistent. The targeted quantitative multiple reaction monitoring (MRM) assay of the reported candidate biomarkers (CBs) can contribute to the creation of a consistent marker panel. An MRM-MS analysis of 149 nondepleted EDTA–plasma samples (MHRC, Russia) of patients with AD (n = 47), mild cognitive impairment (MCI, n = 36), vascular dementia (n = 8), frontotemporal dementia (n = 15), and an elderly control group (n = 43) was performed using the BAK 125 kit (MRM Proteomics Inc., Canada). Statistical analysis revealed a significant decrease in the levels of afamin, apolipoprotein E, biotinidase, and serum paraoxonase/arylesterase 1 associated with AD. Different training algorithms for machine learning were performed to identify the protein panels and build corresponding classifiers for the AD prognosis. Machine learning revealed 31 proteins that are important for AD differentiation and mostly include reported earlier CBs. The best-performing classifiers reached 80% accuracy, 79.4% sensitivity and 83.6% specificity and were able to assess the risk of developing AD over the next 3 years for patients with MCI. Overall, this study demonstrates the high potential of the MRM approach combined with machine learning to confirm the significance of previously identified CBs and to propose consistent protein marker panels.
Collapse
|
3
|
Lin H, Himali JJ, Satizabal CL, Beiser AS, Levy D, Benjamin EJ, Gonzales MM, Ghosh S, Vasan RS, Seshadri S, McGrath ER. Identifying Blood Biomarkers for Dementia Using Machine Learning Methods in the Framingham Heart Study. Cells 2022; 11:1506. [PMID: 35563811 PMCID: PMC9100323 DOI: 10.3390/cells11091506] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 04/20/2022] [Accepted: 04/27/2022] [Indexed: 11/25/2022] Open
Abstract
Blood biomarkers for dementia have the potential to identify preclinical disease and improve participant selection for clinical trials. Machine learning is an efficient analytical strategy to simultaneously identify multiple candidate biomarkers for dementia. We aimed to identify important candidate blood biomarkers for dementia using three machine learning models. We included 1642 (mean 69 ± 6 yr, 53% women) dementia-free Framingham Offspring Cohort participants attending examination, 7 who had available blood biomarker data. We developed three machine learning models, support vector machine (SVM), eXtreme gradient boosting of decision trees (XGB), and artificial neural network (ANN), to identify candidate biomarkers for incident dementia. Over a mean 12 ± 5 yr follow-up, 243 (14.8%) participants developed dementia. In multivariable models including all 38 available biomarkers, the XGB model demonstrated the strongest predictive accuracy for incident dementia (AUC 0.74 ± 0.01), followed by ANN (AUC 0.72 ± 0.01), and SVM (AUC 0.69 ± 0.01). Stepwise feature elimination by random sampling identified a subset of the nine most highly informative biomarkers. Machine learning models confined to these nine biomarkers showed improved model predictive accuracy for dementia (XGB, AUC 0.76 ± 0.01; ANN, AUC 0.75 ± 0.004; SVM, AUC 0.73 ± 0.01). A parsimonious panel of nine candidate biomarkers were identified which showed moderately good predictive accuracy for incident dementia, although our results require external validation.
Collapse
Affiliation(s)
- Honghuang Lin
- The Framingham Heart Study, Framingham, MA 01701, USA; (H.L.); (J.J.H.); (C.L.S.); (A.S.B.); (D.L.); (E.J.B.); (M.M.G.); (S.G.); (R.S.V.); (S.S.)
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Jayandra J. Himali
- The Framingham Heart Study, Framingham, MA 01701, USA; (H.L.); (J.J.H.); (C.L.S.); (A.S.B.); (D.L.); (E.J.B.); (M.M.G.); (S.G.); (R.S.V.); (S.S.)
- School of Public Health, Boston University, Boston, MA 02118, USA
- School of Medicine, Boston University, Boston, MA 02118, USA
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 77072, USA
| | - Claudia L. Satizabal
- The Framingham Heart Study, Framingham, MA 01701, USA; (H.L.); (J.J.H.); (C.L.S.); (A.S.B.); (D.L.); (E.J.B.); (M.M.G.); (S.G.); (R.S.V.); (S.S.)
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 77072, USA
| | - Alexa S. Beiser
- The Framingham Heart Study, Framingham, MA 01701, USA; (H.L.); (J.J.H.); (C.L.S.); (A.S.B.); (D.L.); (E.J.B.); (M.M.G.); (S.G.); (R.S.V.); (S.S.)
- School of Public Health, Boston University, Boston, MA 02118, USA
- School of Medicine, Boston University, Boston, MA 02118, USA
| | - Daniel Levy
- The Framingham Heart Study, Framingham, MA 01701, USA; (H.L.); (J.J.H.); (C.L.S.); (A.S.B.); (D.L.); (E.J.B.); (M.M.G.); (S.G.); (R.S.V.); (S.S.)
- Population Sciences Branch, National Heart, Lung and Blood Institutes of Health, Bethesda, MD 20824, USA
| | - Emelia J. Benjamin
- The Framingham Heart Study, Framingham, MA 01701, USA; (H.L.); (J.J.H.); (C.L.S.); (A.S.B.); (D.L.); (E.J.B.); (M.M.G.); (S.G.); (R.S.V.); (S.S.)
- School of Public Health, Boston University, Boston, MA 02118, USA
- School of Medicine, Boston University, Boston, MA 02118, USA
| | - Mitzi M. Gonzales
- The Framingham Heart Study, Framingham, MA 01701, USA; (H.L.); (J.J.H.); (C.L.S.); (A.S.B.); (D.L.); (E.J.B.); (M.M.G.); (S.G.); (R.S.V.); (S.S.)
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 77072, USA
| | - Saptaparni Ghosh
- The Framingham Heart Study, Framingham, MA 01701, USA; (H.L.); (J.J.H.); (C.L.S.); (A.S.B.); (D.L.); (E.J.B.); (M.M.G.); (S.G.); (R.S.V.); (S.S.)
- School of Medicine, Boston University, Boston, MA 02118, USA
| | - Ramachandran S. Vasan
- The Framingham Heart Study, Framingham, MA 01701, USA; (H.L.); (J.J.H.); (C.L.S.); (A.S.B.); (D.L.); (E.J.B.); (M.M.G.); (S.G.); (R.S.V.); (S.S.)
- School of Medicine, Boston University, Boston, MA 02118, USA
| | - Sudha Seshadri
- The Framingham Heart Study, Framingham, MA 01701, USA; (H.L.); (J.J.H.); (C.L.S.); (A.S.B.); (D.L.); (E.J.B.); (M.M.G.); (S.G.); (R.S.V.); (S.S.)
- School of Medicine, Boston University, Boston, MA 02118, USA
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 77072, USA
| | - Emer R. McGrath
- The Framingham Heart Study, Framingham, MA 01701, USA; (H.L.); (J.J.H.); (C.L.S.); (A.S.B.); (D.L.); (E.J.B.); (M.M.G.); (S.G.); (R.S.V.); (S.S.)
- HRB Clinical Research Facility, National University of Ireland Galway, University Road, H91TK33 Galway, Ireland
| |
Collapse
|
4
|
Álvarez-Sánchez L, Peña-Bautista C, Baquero M, Cháfer-Pericás C. Novel Ultrasensitive Detection Technologies for the Identification of Early and Minimally Invasive Alzheimer's Disease Blood Biomarkers. J Alzheimers Dis 2022; 86:1337-1369. [PMID: 35213367 DOI: 10.3233/jad-215093] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND Single molecule array (SIMOA) and other ultrasensitive detection technologies have allowed the determination of blood-based biomarkers of Alzheimer's disease (AD) for diagnosis and monitoring, thereby opening up a promising field of research. OBJECTIVE To review the published bibliography on plasma biomarkers in AD using new ultrasensitive techniques. METHODS A systematic review of the PubMed database was carried out to identify reports on the use of blood-based ultrasensitive technology to identify biomarkers for AD. RESULTS Based on this search, 86 works were included and classified according to the biomarker determined. First, plasma amyloid-β showed satisfactory accuracy as an AD biomarker in patients with a high risk of developing dementia. Second, plasma t-Tau displayed good sensitivity in detecting different neurodegenerative diseases. Third, plasma p-Tau was highly specific for AD. Fourth, plasma NfL was highly sensitive for distinguishing between patients with neurodegenerative diseases and healthy controls. In general, the simultaneous determination of several biomarkers facilitated greater accuracy in diagnosing AD (Aβ42/Aβ40, p-Tau181/217). CONCLUSION The recent development of ultrasensitive technology allows the determination of blood-based biomarkers with high sensitivity, thus facilitating the early detection of AD through the analysis of easily obtained biological samples. In short, as a result of this knowledge, pre-symptomatic and early AD diagnosis may be possible, and the recruitment process for future clinical trials could be more precise. However, further studies are necessary to standardize levels of blood-based biomarkers in the general population and thus achieve reproducible results among different laboratories.
Collapse
Affiliation(s)
| | - Carmen Peña-Bautista
- Alzheimer Disease Research Group, Health Research Institute La Fe, Valencia, Spain
| | - Miguel Baquero
- Division of Neurology, University and Polytechnic Hospital La Fe, Valencia, Spain
| | | |
Collapse
|
5
|
Pathak N, Vimal SK, Tandon I, Agrawal L, Hongyi C, Bhattacharyya S. Neurodegenerative Disorders of Alzheimer, Parkinsonism, Amyotrophic Lateral Sclerosis and Multiple Sclerosis: An Early Diagnostic Approach for Precision Treatment. Metab Brain Dis 2022; 37:67-104. [PMID: 34719771 DOI: 10.1007/s11011-021-00800-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 07/11/2021] [Indexed: 12/21/2022]
Abstract
Neurodegenerative diseases (NDs) are characterised by progressive dysfunction of synapses, neurons, glial cells and their networks. Neurodegenerative diseases can be classified according to primary clinical features (e.g., dementia, parkinsonism, or motor neuron disease), anatomic distribution of neurodegeneration (e.g., frontotemporal degenerations, extrapyramidal disorders, or spinocerebellar degenerations), or principal molecular abnormalities. The most common neurodegenerative disorders are amyloidosis, tauopathies, a-synucleinopathy, and TAR DNA-binding protein 43 (TDP-43) proteopathy. The protein abnormalities in these disorders have abnormal conformational properties along with altered cellular mechanisms, and they exhibit motor deficit, mitochondrial malfunction, dysfunctions in autophagic-lysosomal pathways, synaptic toxicity, and more emerging mechanisms such as the roles of stress granule pathways and liquid-phase transitions. Finally, for each ND, microglial cells have been reported to be implicated in neurodegeneration, in particular, because the microglial responses can shift from neuroprotective to a deleterious role. Growing experimental evidence suggests that abnormal protein conformers act as seed material for oligomerization, spreading from cell to cell through anatomically connected neuronal pathways, which may in part explain the specific anatomical patterns observed in brain autopsy sample. In this review, we mention the human pathology of select neurodegenerative disorders, focusing on how neurodegenerative disorders (i.e., Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and multiple sclerosis) represent a great healthcare problem worldwide and are becoming prevalent because of the increasing aged population. Despite many studies have focused on their etiopathology, the exact cause of these diseases is still largely unknown and until now with the only available option of symptomatic treatments. In this review, we aim to report the systematic and clinically correlated potential biomarker candidates. Although future studies are necessary for their use in early detection and progression in humans affected by NDs, the promising results obtained by several groups leads us to this idea that biomarkers could be used to design a potential therapeutic approach and preclinical clinical trials for the treatments of NDs.
Collapse
Affiliation(s)
- Nishit Pathak
- Department of Pharmaceutical Sciences and Chinese Traditional Medicine, Southwest University, Beibei, Chongqing, 400715, People's Republic of China
| | - Sunil Kumar Vimal
- Department of Pharmaceutical Sciences and Chinese Traditional Medicine, Southwest University, Beibei, Chongqing, 400715, People's Republic of China
| | - Ishi Tandon
- Amity University Jaipur, Rajasthan, Jaipur, Rajasthan, India
| | - Lokesh Agrawal
- Graduate School of Comprehensive Human Sciences, Kansei Behavioural and Brain Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki, 305-8577, Japan
| | - Cao Hongyi
- Department of Pharmaceutical Sciences and Chinese Traditional Medicine, Southwest University, Beibei, Chongqing, 400715, People's Republic of China
| | - Sanjib Bhattacharyya
- Department of Pharmaceutical Sciences and Chinese Traditional Medicine, Southwest University, Beibei, Chongqing, 400715, People's Republic of China.
| |
Collapse
|
6
|
Chiang TI, Yu YH, Lin CH, Lane HY. Novel Biomarkers of Alzheimer's Disease: Based Upon N-methyl-D-aspartate Receptor Hypoactivation and Oxidative Stress. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE 2021; 19:423-433. [PMID: 34294612 PMCID: PMC8316669 DOI: 10.9758/cpn.2021.19.3.423] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 12/07/2020] [Accepted: 12/14/2020] [Indexed: 12/29/2022]
Abstract
Early detection and prevention of Alzheimer’s disease (AD) is important. The current treatment for early AD is acetylcholine esterase inhibitors (AChEIs); however, the efficacy is poor. Besides, AChEI did not show efficacy in mild cognitive impairment (MCI). Beta-amyloid (Aβ) deposits have been regarded to be highly related to the pathogenesis of AD. However, many clinical trials aiming at the clearance of Aβ deposits failed to improve the cognitive decline of AD, even at its early phase. There should be other important mechanisms unproven in the course of AD and MCI. Feasible biomarkers for the diagnosis and treatment response of AD are lacking to date. The N-methyl-D-aspartate receptor (NMDAR) activation plays an important role in learning and memory. On the other hand, oxidative stress has been regarded to contribute to aging with the assumption that free radicals damage cell constituents and connective tissues. Our recent study found that an NMDAR enhancer, sodium benzoate (the pivotal inhibitor of D-amino acid oxidase [DAAO]), improved the cognitive and global function of patients with early-phase AD. Further, we found that peripheral DAAO levels were higher in patients with MCI and AD than healthy controls. We also found that sodium benzoate was able to change the activity of antioxidant. These pieces of evidence suggest that the NMDAR function is associated with anti-oxidation, and have potential to be biomarkers for the diagnosis and treatment response of AD.
Collapse
Affiliation(s)
- Ting-I Chiang
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yi-Hsiang Yu
- Department of Dermatology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Chieh-Hsin Lin
- Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.,School of Medicine, Chang Gung University, Taoyuan, Taiwan.,Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
| | - Hsien-Yuan Lane
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan.,Department of Psychiatry and Brain Disease Research Center, China Medical University Hospital, Taichung, Taiwan.,Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan
| |
Collapse
|
7
|
Zhao X, Kang J, Svetnik V, Warden D, Wilcock G, David Smith A, Savage MJ, Laterza OF. A Machine Learning Approach to Identify a Circulating MicroRNA Signature for Alzheimer Disease. J Appl Lab Med 2021; 5:15-28. [PMID: 31811079 DOI: 10.1373/jalm.2019.029595] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 10/29/2019] [Indexed: 01/04/2023]
Abstract
BACKGROUND Accurate diagnosis of Alzheimer disease (AD) involving less invasive molecular procedures and at reasonable cost is an unmet medical need. We identified a serum miRNA signature for AD that is less invasive than a measure in cerebrospinal fluid. METHODS From the Oxford Project to Investigate Memory and Aging (OPTIMA) study, 96 serum samples were profiled by a multiplex (>500 analytes) microRNA (miRNA) reverse transcription quantitative PCR analysis, including 51 controls, 32 samples from patients with AD, and 13 samples from patients with mild cognitive impairment (MCI). Clinical diagnosis of a subset of AD and the controls was confirmed by postmortem (PM) histologic examination of brain tissue. In a machine learning approach, the AD and control samples were split 70:30 as the training and test cohorts. A multivariate random forest statistical analysis was applied to construct and test a miRNA signature for AD identification. In addition, the MCI participants were included in the test cohort to assess whether the signature can identify early AD patients. RESULTS A 12-miRNA signature for AD identification was constructed in the training cohort, demonstrating 76.0% accuracy in the independent test cohort with 90.0% sensitivity and 66.7% specificity. The signature, however, was not able to identify MCI participants. With a subset of AD and control participants with PM-confirmed diagnosis status, a separate 12-miRNA signature was constructed. Although sample size was limited, the PM-confirmed signature demonstrated improved accuracy of 85.7%, largely owing to improved specificity of 80.0% with comparable sensitivity of 88.9%. CONCLUSION Although additional and more diverse cohorts are needed for further clinical validation of the robustness, the miRNA signature appears to be a promising blood test to diagnose AD.
Collapse
Affiliation(s)
- Xuemei Zhao
- Translational Molecular Biomarkers, MRL, Merck & Co., Kenilworth, NJ
| | - John Kang
- Biometrics, MRL, Merck & Co., Rahway, NJ
| | | | - Donald Warden
- Department of Pharmacology, Oxford University, Oxford, UK
| | - Gordon Wilcock
- Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, Oxford, UK
| | - A David Smith
- Department of Pharmacology, Oxford University, Oxford, UK
| | - Mary J Savage
- Translational Companion Diagnostics, MRL, Merck & Co., Kenilworth, NJ
| | - Omar F Laterza
- Translational Molecular Biomarkers, MRL, Merck & Co., Kenilworth, NJ
| |
Collapse
|
8
|
Khan MJ, Desaire H, Lopez OL, Kamboh MI, Robinson RA. Why Inclusion Matters for Alzheimer’s Disease Biomarker Discovery in Plasma. J Alzheimers Dis 2021; 79:1327-1344. [DOI: 10.3233/jad-201318] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Background: African American/Black adults have a disproportionate incidence of Alzheimer’s disease (AD) and are underrepresented in biomarker discovery efforts. Objective: This study aimed to identify potential diagnostic biomarkers for AD using a combination of proteomics and machine learning approaches in a cohort that included African American/Black adults. Methods: We conducted a discovery-based plasma proteomics study on plasma samples (N = 113) obtained from clinically diagnosed AD and cognitively normal adults that were self-reported African American/Black or non-Hispanic White. Sets of differentially-expressed proteins were then classified using a support vector machine (SVM) to identify biomarker candidates. Results: In total, 740 proteins were identified of which, 25 differentially-expressed proteins in AD came from comparisons within a single racial and ethnic background group. Six proteins were differentially-expressed in AD regardless of racial and ethnic background. Supervised classification by SVM yielded an area under the curve (AUC) of 0.91 and accuracy of 86%for differentiating AD in samples from non-Hispanic White adults when trained with differentially-expressed proteins unique to that group. However, the same model yielded an AUC of 0.49 and accuracy of 47%for differentiating AD in samples from African American/Black adults. Other covariates such as age, APOE4 status, sex, and years of education were found to improve the model mostly in the samples from non-Hispanic White adults for classifying AD. Conclusion: These results demonstrate the importance of study designs in AD biomarker discovery, which must include diverse racial and ethnic groups such as African American/Black adults to develop effective biomarkers.
Collapse
Affiliation(s)
- Mostafa J. Khan
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - Heather Desaire
- Department of Chemistry, University of Kansas, Lawrence, KS, USA
| | - Oscar L. Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - M. Ilyas Kamboh
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Renã A.S. Robinson
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| |
Collapse
|
9
|
Diniz Pereira J, Gomes Fraga V, Morais Santos AL, Carvalho MDG, Caramelli P, Braga Gomes K. Alzheimer's disease and type 2 diabetes mellitus: A systematic review of proteomic studies. J Neurochem 2020; 156:753-776. [PMID: 32909269 DOI: 10.1111/jnc.15166] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 07/15/2020] [Accepted: 08/25/2020] [Indexed: 12/16/2022]
Abstract
Similar to dementia, the risk for developing type 2 diabetes mellitus (T2DM) increases with age, and T2DM also increases the risk for dementia, particularly Alzheimer's disease (AD). Although T2DM is primarily a peripheral disorder and AD is a central nervous system disease, both share some common features as they are chronic and complex diseases, and both show involvement of oxidative stress and inflammation in their progression. These characteristics suggest that T2DM may be associated with AD, which gave rise to a new term, type 3 diabetes (T3DM). In this study, we searched for matching peripheral proteomic biomarkers of AD and T2DM based in a systematic review of the available literature. We identified 17 common biomarkers that were differentially expressed in both patients with AD or T2DM when compared with healthy controls. These biomarkers could provide a useful workflow for screening T2DM patients at risk to develop AD.
Collapse
Affiliation(s)
- Jessica Diniz Pereira
- Departamento de Análises Clínicas e Toxicológicas, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Vanessa Gomes Fraga
- Departamento de Análises Clínicas e Toxicológicas, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Anna Luiza Morais Santos
- Departamento de Análises Clínicas e Toxicológicas, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Maria das Graças Carvalho
- Departamento de Análises Clínicas e Toxicológicas, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Paulo Caramelli
- Departamento de Clínica Médica, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Karina Braga Gomes
- Departamento de Análises Clínicas e Toxicológicas, Faculdade de Farmácia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| |
Collapse
|
10
|
Rehiman SH, Lim SM, Neoh CF, Majeed ABA, Chin AV, Tan MP, Kamaruzzaman SB, Ramasamy K. Proteomics as a reliable approach for discovery of blood-based Alzheimer's disease biomarkers: A systematic review and meta-analysis. Ageing Res Rev 2020; 60:101066. [PMID: 32294542 DOI: 10.1016/j.arr.2020.101066] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 04/03/2020] [Accepted: 04/03/2020] [Indexed: 02/08/2023]
Abstract
In order to gauge the impact of proteomics in discovery of Alzheimer's disease (AD) blood-based biomarkers, this study had systematically reviewed articles published between 1984-2019. Articles that fulfilled the inclusion criteria were assessed for risk of bias. A meta-analysis was performed for replicable candidate biomarkers (CB). Of the 1651 articles that were identified, 17 case-control and two cohort studies, as well as three combined case-control and longitudinal designs were shortlisted. A total of 207 AD and mild cognitive impairment (MCI) CB were discovered, with 48 reported in >2 studies. This review highlights six CB, namely alpha-2-macroglobulin (α2M)ps, pancreatic polypeptide (PP)ps, apolipoprotein A-1 (ApoA-1)ps, afaminp, insulin growth factor binding protein-2 (IGFBP-2)ps and fibrinogen-γ-chainp, all of which exhibited consistent pattern of regulation in >three independent cohorts. They are involved in AD pathogenesis via amyloid-beta (Aβ), neurofibrillary tangles, diabetes and cardiovascular diseases (CVD). Meta-analysis indicated that ApoA-1ps was significantly downregulated in AD (SMD = -1.52, 95% CI: -1.89, -1.16, p < 0.00001), with low inter-study heterogeneity (I2 = 0%, p = 0.59). α2Mps was significantly upregulated in AD (SMD = 0.83, 95% CI: 0.05, 1.62, p = 0.04), with moderate inter-study heterogeneity (I2 = 41%, p = 0.19). Both CB are involved in Aβ formation. These findings provide important insights into blood-based AD biomarkers discovery via proteomics.
Collapse
|
11
|
Nabers A, Hafermann H, Wiltfang J, Gerwert K. Aβ and tau structure-based biomarkers for a blood- and CSF-based two-step recruitment strategy to identify patients with dementia due to Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2019; 11:257-263. [PMID: 30911600 PMCID: PMC6416642 DOI: 10.1016/j.dadm.2019.01.008] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Alzheimer's disease (AD) diagnosis requires invasive CSF analysis or expensive brain imaging. Therefore, a minimal-invasive reliable and cost-effective blood test is requested to power large clinical AD trials at reduced screening failure. METHODS We applied an immuno-infrared sensor to measure the amyloid-β (Aβ) and tau secondary structure distribution in plasma and CSF as structure-based biomarkers for AD (61 disease controls, 39 AD cases). RESULTS Within a first diagnostic screening step, the structure-based Aβ blood biomarker supports AD identification with a sensitivity of 90%. In a second diagnostic validation step, the combined use of the structure-based CSF biomarkers Aβ and tau excluded false-positive cases which offers an overall specificity of 97%. DISCUSSION The primary Aβ-based blood biomarker funnels individuals with suspected AD for subsequent validation of the diagnosis by structure-based combined analysis of the CSF biomarkers Aβ and tau. Our novel two-step recruitment strategy substantiates the diagnosis of AD with a likelihood of 29.
Collapse
Affiliation(s)
- Andreas Nabers
- Department of Biophysics, Ruhr-University Bochum, Bochum, Germany
| | - Henning Hafermann
- LVR-Hospital Essen, Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen (UMG), Georg-August-University Goettingen, Göttingen, Germany
- German Center for Neurodegenrative Diseases (DZNE), Göttingen, Germany
- iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Klaus Gerwert
- Department of Biophysics, Ruhr-University Bochum, Bochum, Germany
| |
Collapse
|
12
|
Gatt A, Whitfield DR, Ballard C, Doherty P, Williams G. Alzheimer's Disease Progression in the 5×FAD Mouse Captured with a Multiplex Gene Expression Array. J Alzheimers Dis 2019; 72:1177-1191. [PMID: 31683485 DOI: 10.3233/jad-190805] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) is an incurable complex neurodegenerative condition with no new therapies licensed in the past 20 years. AD progression is characterized by the up- and downregulation of distinct biological processes that can be followed through the expression level changes of associated genes and gene networks. OBJECTIVE Our study aims to establish a multiplex gene expression tracking platform to follow disease progression in an animal model facilitating the study of treatment paradigms. METHODS We have established a multiplex platform covering 47 key genes related to immunological, neuronal, mitochondrial, and autophagy cell types and processes that capture disease progression in the 5×FAD mouse model. RESULTS We show that the immunological response is the most pronounced change in aged 5×FAD mice (8 months and above), and in agreement with early stage human disease samples, observe an initial downregulation of microglial genes in one-month-old animals. The less dramatic downregulation of neuronal and mitochondrial gene sets is also reported. CONCLUSION This study provides the basis for a quantitative multi-dimensional platform to follow AD progression and monitor the efficacy of treatments in an animal model.
Collapse
Affiliation(s)
- Ariana Gatt
- Wolfson Centre for Age-Related Diseases, King's College London, London Bridge, London, UK
| | - David R Whitfield
- Wolfson Centre for Age-Related Diseases, King's College London, London Bridge, London, UK
| | - Clive Ballard
- College of Medicine and Health, University of Exeter, Exeter, UK
| | - Patrick Doherty
- Wolfson Centre for Age-Related Diseases, King's College London, London Bridge, London, UK
| | - Gareth Williams
- Wolfson Centre for Age-Related Diseases, King's College London, London Bridge, London, UK
| |
Collapse
|
13
|
Eke CS, Jammeh E, Li X, Carroll C, Pearson S, Ifeachor E. Identification of Optimum Panel of Blood-based Biomarkers for Alzheimer's Disease Diagnosis Using Machine Learning. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019; 2018:3991-3994. [PMID: 30441233 DOI: 10.1109/embc.2018.8513293] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
With the increasing number of people living with Alzheimer's disease (AD), there is a need for low-cost and easy to use methods to detect AD early to facilitate access to appropriate care pathways. Neuroimaging biomarkers (such as those based on PET and MRI) and biochemical biomarkers (such as those based on CSF) are recommended by international guidelines to facilitate diagnosis. However, neuroimaging is expensive and may not be widely available and CSF testing is invasive. Bloodbased biomarkers offer the potential for the development of a low-cost and more time efficient tool to detect AD to complement CSF and neuroimaging as blood is much easier to obtain. Although no single blood biomarker is yet able to detect AD, combinations of biomarkers (also called panels) have shown good results. However, a large number of biomarkers are often needed to achieve a satisfactory detection performance. In addition, it is difficult to reproduce reported results within and across different study cohorts because of data overfitting and lack of access to the datasets used in the studies. In this study, our focus is to identify an optimum panel (in terms of the least number of blood biomarkers to meet the specified diagnostic performance of 80% sensitivity and specificity) based on a widely accessible data set, and to demonstrate a testing methodology that reinforces reproducibility of results. Realizing a panel with reduced number of markers will have significant impact on the complexity and cost of diagnosis and potential development of cost-effective point of care devices.
Collapse
|
14
|
Naveed M, Mubeen S, Khan A, Ibrahim S, Meer B. Plasma Biomarkers: Potent Screeners of Alzheimer's Disease. Am J Alzheimers Dis Other Demen 2019; 34:290-301. [PMID: 31072117 PMCID: PMC10852434 DOI: 10.1177/1533317519848239] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Alzheimer's disease (AD), a neurological disorder, is as a complex chronic disease of brain cell death that usher to cognitive decline and loss of memory. Its prevalence differs according to risk factors associated with it and necropsy performs vital role in its definite diagnosis. The stages of AD vary from preclinical to severe that proceeds to death of patient with no availability of treatment. Biomarker may be a biochemical change that can be recognized by different emerging technologies such as proteomics and metabolomics. Plasma biomarkers, 5-protein classifiers, are readily being used for the diagnosis of AD and can also predict its progression with a great accuracy, specificity, and sensitivity. In this review, upregulation or downregulation of few plasma proteins in patients with AD has also been discussed, when juxtaposed with control, and thus serves as potent biomarker in the diagnosis of AD.
Collapse
Affiliation(s)
- Muhammad Naveed
- Department of Biotechnology, Faculty of Life Sciences, University of Central Punjab, Lahore, Pakistan
| | - Shamsa Mubeen
- Department of Biochemistry and Molecular Biology, University of Gujrat, Gujrat, Pakistan
| | - Abeer Khan
- Department of Biotechnology, University of Gujrat, Gujrat, Pakistan
| | - Sehrish Ibrahim
- Department of Biotechnology, University of Gujrat, Gujrat, Pakistan
| | - Bisma Meer
- Department of Biotechnology, University of Gujrat, Gujrat, Pakistan
| |
Collapse
|
15
|
Nabers A, Perna L, Lange J, Mons U, Schartner J, Güldenhaupt J, Saum KU, Janelidze S, Holleczek B, Rujescu D, Hansson O, Gerwert K, Brenner H. Amyloid blood biomarker detects Alzheimer's disease. EMBO Mol Med 2019; 10:emmm.201708763. [PMID: 29626112 PMCID: PMC5938617 DOI: 10.15252/emmm.201708763] [Citation(s) in RCA: 122] [Impact Index Per Article: 24.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Alzheimer's disease (AD) is currently incurable, but there is general agreement that a minimally invasive blood biomarker for screening in preclinical stages would be crucial for future therapy. Diagnostic tools for detection of AD are either invasive like cerebrospinal fluid (CSF) biomarkers or expensive such as positron emission tomography (PET) scanning. Here, we determine the secondary structure change of amyloid‐β (Aβ) in human blood. This change used as blood amyloid biomarker indicates prodromal AD and correlates with CSF AD biomarkers and amyloid PET imaging in the cross‐sectional BioFINDER cohort. In a further population‐based longitudinal cohort (ESTHER), the blood biomarker detected AD several years before clinical diagnosis in baseline samples with a positive likelihood ratio of 7.9; that is, those who were diagnosed with AD over the years were 7.9 times more likely to test positive. This assay may open avenues for blood screening of early AD stages as a funnel for further more invasive and expensive tests.
Collapse
Affiliation(s)
- Andreas Nabers
- Department of Biophysics, Ruhr-University Bochum, Bochum, Germany
| | - Laura Perna
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Julia Lange
- Department of Biophysics, Ruhr-University Bochum, Bochum, Germany
| | - Ute Mons
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jonas Schartner
- Department of Biophysics, Ruhr-University Bochum, Bochum, Germany
| | - Jörn Güldenhaupt
- Department of Biophysics, Ruhr-University Bochum, Bochum, Germany
| | - Kai-Uwe Saum
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | | | - Dan Rujescu
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Halle, Halle, Germany
| | - Oskar Hansson
- Department of Clinical Sciences, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Klaus Gerwert
- Department of Biophysics, Ruhr-University Bochum, Bochum, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Network Aging Research (NAR), University of Heidelberg, Heidelberg, Germany
| |
Collapse
|
16
|
Zetterberg H, Burnham SC. Blood-based molecular biomarkers for Alzheimer's disease. Mol Brain 2019; 12:26. [PMID: 30922367 PMCID: PMC6437931 DOI: 10.1186/s13041-019-0448-1] [Citation(s) in RCA: 158] [Impact Index Per Article: 31.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Accepted: 03/15/2019] [Indexed: 12/18/2022] Open
Abstract
A major barrier to the effective conduct of clinical trials of new drug candidates against Alzheimer’s disease (AD) and to identifying patients for receiving future disease-modifying treatments is the limited capacity of the current health system to find and diagnose patients with early AD pathology. This may be related in part to the limited capacity of the current health systems to select those people likely to have AD pathology in order to confirm the diagnosis with available cerebrospinal fluid and imaging biomarkers at memory clinics. In the current narrative review, we summarize the literature on candidate blood tests for AD that could be implemented in primary care settings and used for the effective identification of individuals at increased risk of AD pathology, who could be referred for potential inclusion in clinical trials or future approved treatments following additional testing. We give an updated account of blood-based candidate biomarkers and biomarker panels for AD-related brain changes. Our analysis centres on biomarker candidates that have been replicated in more than one study and discusses the need of further studies to achieve the goal of a primary care-based screening algorithm for AD.
Collapse
Affiliation(s)
- Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, he Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden. .,Clinical Neurochemistry Laboratory, Sahlgrenska, University Hospital, Mölndal, Sweden. .,Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London, UK. .,UK Dementia Research Institute at UCL, London, UK.
| | - Samantha C Burnham
- CSIRO Health and Biosecurity, Parkville, Victoria, 3052, Australia. .,Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia.
| |
Collapse
|
17
|
Peña-Bautista C, Baquero M, Vento M, Cháfer-Pericás C. Omics-based Biomarkers for the Early Alzheimer Disease Diagnosis and Reliable Therapeutic Targets Development. Curr Neuropharmacol 2019; 17:630-647. [PMID: 30255758 PMCID: PMC6712290 DOI: 10.2174/1570159x16666180926123722] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Revised: 08/31/2018] [Accepted: 09/19/2018] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Alzheimer's disease (AD), the most common cause of dementia in adulthood, has great medical, social, and economic impact worldwide. Available treatments result in symptomatic relief, and most of them are indicated from the early stages of the disease. Therefore, there is an increasing body of research developing accurate and early diagnoses, as well as diseasemodifying therapies. OBJECTIVE Advancing the knowledge of AD physiopathological mechanisms, improving early diagnosis and developing effective treatments from omics-based biomarkers. METHODS Studies using omics technologies to detect early AD, were reviewed with a particular focus on the metabolites/lipids, micro-RNAs and proteins, which are identified as potential biomarkers in non-invasive samples. RESULTS This review summarizes recent research on metabolomics/lipidomics, epigenomics and proteomics, applied to early AD detection. Main research lines are the study of metabolites from pathways, such as lipid, amino acid and neurotransmitter metabolisms, cholesterol biosynthesis, and Krebs and urea cycles. In addition, some microRNAs and proteins (microglobulins, interleukins), related to a common network with amyloid precursor protein and tau, have been also identified as potential biomarkers. Nevertheless, the reproducibility of results among studies is not good enough and a standard methodological approach is needed in order to obtain accurate information. CONCLUSION The assessment of metabolomic/lipidomic, epigenomic and proteomic changes associated with AD to identify early biomarkers in non-invasive samples from well-defined participants groups will potentially allow the advancement in the early diagnosis and improvement of therapeutic interventions.
Collapse
Affiliation(s)
| | | | | | - Consuelo Cháfer-Pericás
- Address correspondence to this author at the Health Research Institute La Fe, Avda de Fernando Abril Martorell, 106; 46026 Valencia, Spain;Tel: +34 96 124 66 61; Fax: + 34 96 124 57 46; E-mail:
| |
Collapse
|
18
|
Cheng Z, Yin J, Yuan H, Jin C, Zhang F, Wang Z, Liu X, Wu Y, Wang T, Xiao S. Blood-Derived Plasma Protein Biomarkers for Alzheimer's Disease in Han Chinese. Front Aging Neurosci 2018; 10:414. [PMID: 30618720 PMCID: PMC6305130 DOI: 10.3389/fnagi.2018.00414] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Accepted: 11/30/2018] [Indexed: 11/13/2022] Open
Abstract
It is well known that Alzheimer's disease (AD) is one of the most common progressive neurodegenerative diseases; it begins gradually, and therefore no effective medicine is administered in the beginning. Thus, early diagnosis and prevention of AD are crucial. The present study focused on comparing the plasma protein changes between patients with AD and their healthy counterparts, aiming to explore a specific protein panel as a potential biomarker for AD patients in Han Chinese. Hence, we recruited and collected plasma samples from 98 AD patients and 101 elderly healthy controls from Wuxi and Shanghai Mental Health Centers. Using a Luminex assay, we investigated the expression levels of fifty plasma proteins in these samples. Thirty-two out of 50 proteins were found to be significantly different between AD patients and healthy controls (P < 0.05). Furthermore, an eight-protein panel that included brain-derived neurotrophic factor (BDNF), angiotensinogen (AGT), insulin-like growth factor binding protein 2 (IGFBP-2), osteopontin (OPN), cathepsin D, serum amyloid P component (SAP), complement C4, and prealbumin (transthyretin, TTR) showed the highest determinative score for AD and healthy controls (all P = 0.00). In conclusion, these findings suggest that a combination of eight plasma proteins can serve as a promising diagnostic biomarker for AD with high sensitivity and specificity in Han Chinese populations; the eight plasma proteins were proven important for AD diagnosis by further cross-validation studies within the AD cohort.
Collapse
Affiliation(s)
- Zaohuo Cheng
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Jiajun Yin
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Hongwei Yuan
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Chunhui Jin
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Fuquan Zhang
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Zhiqiang Wang
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Xiaowei Liu
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Yue Wu
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Tao Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shifu Xiao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| |
Collapse
|
19
|
Lista S, Zetterberg H, O'Bryant SE, Blennow K, Hampel H. Evolving Relevance of Neuroproteomics in Alzheimer's Disease. Methods Mol Biol 2018; 1598:101-115. [PMID: 28508359 DOI: 10.1007/978-1-4939-6952-4_5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
Substantial progress in the understanding of the biology of Alzheimer's disease (AD) has been achieved over the past decades. The early detection and diagnosis of AD and other age-related neurodegenerative diseases, however, remain a challenging scientific frontier. Therefore, the comprehensive discovery (relating to all individual, converging or diverging biochemical disease mechanisms), development, validation, and qualification of standardized biological markers with diagnostic and prognostic functions with a precise performance profile regarding specificity, sensitivity, and positive and negative predictive value are warranted.Methodological innovations in the area of exploratory high-throughput technologies, such as sequencing, microarrays, and mass spectrometry-based analyses of proteins/peptides, have led to the generation of large global molecular datasets from a multiplicity of biological systems, such as biological fluids, cells, tissues, and organs. Such methodological progress has shifted the attention to the execution of hypothesis-independent comprehensive exploratory analyses (opposed to the classical hypothesis-driven candidate approach), with the aim of fully understanding the biological systems in physiology and disease as a whole. The systems biology paradigm integrates experimental biology with accurate and rigorous computational modelling to describe and foresee the dynamic features of biological systems. The use of dynamically evolving technological platforms, including mass spectrometry, in the area of proteomics has enabled to rush the process of biomarker discovery and validation for refining significantly the diagnosis of AD. Currently, proteomics-which is part of the systems biology paradigm-is designated as one of the dominant matured sciences needed for the effective exploratory discovery of prospective biomarker candidates expected to play an effective role in aiding the early detection, diagnosis, prognosis, and therapy development in AD.
Collapse
Affiliation(s)
- Simone Lista
- AXA Research Fund & UPMC Chair, Paris, France. .,Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, Inserm, CNRS, Institut du cerveau et dela moelle (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), HôpitalPitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France.
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Sid E O'Bryant
- Institute for Healthy Aging, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,The Torsten Söderberg Professorship in Medicine at the Royal Swedish Academy of Sciences, Stockholm, Sweden
| | - Harald Hampel
- AXA Research Fund & UPMC Chair, Paris, France.,Sorbonne Universités, Université Pierre et Marie Curie, Paris 06, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A) & Institut du Cerveau et de la Moelle Épinière (ICM), Paris, France; Département de Neurologie, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France
| |
Collapse
|
20
|
Counts SE, Ikonomovic MD, Mercado N, Vega IE, Mufson EJ. Biomarkers for the Early Detection and Progression of Alzheimer's Disease. Neurotherapeutics 2017; 14:35-53. [PMID: 27738903 PMCID: PMC5233625 DOI: 10.1007/s13311-016-0481-z] [Citation(s) in RCA: 99] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The recent failures of potential disease-modifying drugs for Alzheimer's disease (AD) may reflect the fact that the enrolled participants in clinical trials are already too advanced to derive a clinical benefit. Thus, well-validated biomarkers for the early detection and accurate diagnosis of the preclinical stages of AD will be crucial for therapeutic advancement. The combinatorial use of biomarkers derived from biological fluids, such as cerebrospinal fluid (CSF), with advanced molecular imaging and neuropsychological testing may eventually achieve the diagnostic sensitivity and specificity necessary to identify people in the earliest stages of the disease when drug modification is most likely possible. In this regard, positive amyloid or tau tracer retention on positron emission tomography imaging, low CSF concentrations of the amyloid-β 1-42 peptide, high CSF concentrations in total tau and phospho-tau, mesial temporal lobe atrophy on magnetic resonance imaging, and temporoparietal/precuneus hypometabolism or hypoperfusion on 18F-fluorodeoxyglucose positron emission tomography have all emerged as biomarkers for the progression to AD. However, the ultimate AD biomarker panel will likely involve the inclusion of novel CSF and blood biomarkers more precisely associated with confirmed pathophysiologic mechanisms to improve its reliability for detecting preclinical AD. This review highlights advancements in biological fluid and imaging biomarkers that are moving the field towards achieving the goal of a preclinical detection of AD.
Collapse
Affiliation(s)
- Scott E Counts
- Department of Translational Science and Molecular Medicine, Michigan State University, Grand Rapids, MI, USA
- Department of Family Medicine, Michigan State University, Grand Rapids, MI, USA
- Hauenstein Neuroscience Center, Mercy Health Saint Mary's Hospital, Grand Rapids, MI, USA
| | - Milos D Ikonomovic
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Geriatric Research Education and Clinical Center, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Natosha Mercado
- Department of Translational Science and Molecular Medicine, Michigan State University, Grand Rapids, MI, USA
| | - Irving E Vega
- Department of Translational Science and Molecular Medicine, Michigan State University, Grand Rapids, MI, USA
| | - Elliott J Mufson
- Department of Neurobiology and Neurology, Barrow Neurological Institute, Phoenix, AZ, USA.
| |
Collapse
|
21
|
Adav SS, Sze SK. Insight of brain degenerative protein modifications in the pathology of neurodegeneration and dementia by proteomic profiling. Mol Brain 2016; 9:92. [PMID: 27809929 PMCID: PMC5094070 DOI: 10.1186/s13041-016-0272-9] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Accepted: 10/16/2016] [Indexed: 02/06/2023] Open
Abstract
Dementia is a syndrome associated with a wide range of clinical features including progressive cognitive decline and patient inability to self-care. Due to rapidly increasing prevalence in aging society, dementia now confers a major economic, social, and healthcare burden throughout the world, and has therefore been identified as a public health priority by the World Health Organization. Previous studies have established dementia as a 'proteinopathy' caused by detrimental changes in brain protein structure and function that promote misfolding, aggregation, and deposition as insoluble amyloid plaques. Despite clear evidence that pathological cognitive decline is associated with degenerative protein modifications (DPMs) arising from spontaneous chemical modifications to amino acid side chains, the molecular mechanisms that promote brain DPMs formation remain poorly understood. However, the technical challenges associated with DPM analysis have recently become tractable due to powerful new proteomic techniques that facilitate detailed analysis of brain tissue damage over time. Recent studies have identified that neurodegenerative diseases are associated with the dysregulation of critical repair enzymes, as well as the misfolding, aggregation and accumulation of modified brain proteins. Future studies will further elucidate the mechanisms underlying dementia pathogenesis via the quantitative profiling of the human brain proteome and associated DPMs in distinct phases and subtypes of disease. This review summarizes recent developments in quantitative proteomic technologies, describes how these techniques have been applied to the study of dementia-linked changes in brain protein structure and function, and briefly outlines how these findings might be translated into novel clinical applications for dementia patients. In this review, only spontaneous protein modifications such as deamidation, oxidation, nitration glycation and carbamylation are reviewed and discussed.
Collapse
Affiliation(s)
- Sunil S. Adav
- Division of Structural Biology and Biochemistry, School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551 Singapore
| | - Siu Kwan Sze
- Division of Structural Biology and Biochemistry, School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551 Singapore
| |
Collapse
|
22
|
Abstract
Although the prevalence of dementia continues to increase worldwide, incidence in the western world might have decreased as a result of better vascular care and improved brain health. Alzheimer's disease, the most prevalent cause of dementia, is still defined by the combined presence of amyloid and tau, but researchers are gradually moving away from the simple assumption of linear causality as proposed in the original amyloid hypothesis. Age-related, protective, and disease-promoting factors probably interact with the core mechanisms of the disease. Amyloid β42, and tau proteins are established core cerebrospinal biomarkers; novel candidate biomarkers include amyloid β oligomers and synaptic markers. MRI and fluorodeoxyglucose PET are established imaging techniques for diagnosis of Alzheimer's disease. Amyloid PET is gaining traction in the clinical arena, but validity and cost-effectiveness remain to be established. Tau PET might offer new insights and be of great help in differential diagnosis and selection of patients for trials. In the search for understanding the disease mechanism and keys to treatment, research is moving increasingly into the earliest phase of disease. Preclinical Alzheimer's disease is defined as biomarker evidence of Alzheimer's pathological changes in cognitively healthy individuals. Patients with subjective cognitive decline have been identified as a useful population in whom to look for preclinical Alzheimer's disease. Moderately positive results for interventions targeting several lifestyle factors in non-demented elderly patients and moderately positive interim results for lowering amyloid in pre-dementia Alzheimer's disease suggest that, ultimately, there will be a future in which specific anti-Alzheimer's therapy will be combined with lifestyle interventions targeting general brain health to jointly combat the disease. In this Seminar, we discuss the main developments in Alzheimer's research.
Collapse
Affiliation(s)
- Philip Scheltens
- Department of Neurology & Alzheimer Center, VU University Medical Center, Amsterdam, Netherlands.
| | - Kaj Blennow
- Clinical Neurochemistry Lab, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Monique M B Breteler
- German Center for Neurodegenerative diseases (DZNE), and Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany
| | - Bart de Strooper
- VIB Center for the Biology of Disease, VIB-Leuven, Leuven, Belgium; KU Leuven Center for Human Genetics, LIND en Universitaire ziekenhuizen, Leuven, Belgium; Institute of Neurology, University College London, London, UK
| | - Giovanni B Frisoni
- University Hospitals and University of Geneva, Geneva, Switzerland; IRCCS Fatebenefratelli, Brescia, Italy
| | - Stephen Salloway
- Warren Alpert Medical School, Brown University, Providence, RI, USA
| | | |
Collapse
|
23
|
Jaeger PA, Lucin KM, Britschgi M, Vardarajan B, Huang RP, Kirby ED, Abbey R, Boeve BF, Boxer AL, Farrer LA, Finch N, Graff-Radford NR, Head E, Hofree M, Huang R, Johns H, Karydas A, Knopman DS, Loboda A, Masliah E, Narasimhan R, Petersen RC, Podtelezhnikov A, Pradhan S, Rademakers R, Sun CH, Younkin SG, Miller BL, Ideker T, Wyss-Coray T. Network-driven plasma proteomics expose molecular changes in the Alzheimer's brain. Mol Neurodegener 2016; 11:31. [PMID: 27112350 PMCID: PMC4845325 DOI: 10.1186/s13024-016-0095-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2015] [Accepted: 04/08/2016] [Indexed: 12/17/2022] Open
Abstract
Background Biological pathways that significantly contribute to sporadic Alzheimer’s disease are largely unknown and cannot be observed directly. Cognitive symptoms appear only decades after the molecular disease onset, further complicating analyses. As a consequence, molecular research is often restricted to late-stage post-mortem studies of brain tissue. However, the disease process is expected to trigger numerous cellular signaling pathways and modulate the local and systemic environment, and resulting changes in secreted signaling molecules carry information about otherwise inaccessible pathological processes. Results To access this information we probed relative levels of close to 600 secreted signaling proteins from patients’ blood samples using antibody microarrays and mapped disease-specific molecular networks. Using these networks as seeds we then employed independent genome and transcriptome data sets to corroborate potential pathogenic pathways. Conclusions We identified Growth-Differentiation Factor (GDF) signaling as a novel Alzheimer’s disease-relevant pathway supported by in vivo and in vitro follow-up experiments, demonstrating the existence of a highly informative link between cellular pathology and changes in circulatory signaling proteins. Electronic supplementary material The online version of this article (doi:10.1186/s13024-016-0095-2) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Philipp A Jaeger
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA. .,Institute of Chemistry and Biochemistry, Free University Berlin, Berlin, Germany. .,Departments of Bioengineering and Medicine, University of California San Diego, La Jolla, CA, USA.
| | - Kurt M Lucin
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.,Present address: Biology Department, Eastern Connecticut State University, Willimantic, CT, USA
| | - Markus Britschgi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.,Present address: Roche Pharma Research and Early Development, NORD DTA, Roche Innovation, Center Basel, Basel, Switzerland
| | - Badri Vardarajan
- Department of Medicine (Biomedical Genetics), Boston University Schools of Medicine, Boston, MA, USA
| | - Ruo-Pan Huang
- RayBiotech, Guangzhou, China.,RayBiotech, Norcrosse, GA, USA
| | - Elizabeth D Kirby
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Rachelle Abbey
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Adam L Boxer
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Lindsay A Farrer
- Department of Medicine (Biomedical Genetics), Boston University Schools of Medicine, Boston, MA, USA.,Departments of Neurology, Ophthalmology, Genetics and Genomics, Epidemiology, and Biostatistics, Boston University Schools of Medicine and Public Health, Boston, MA, USA
| | - NiCole Finch
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | - Elizabeth Head
- Departments of Pharmacology and Nutritional Sciences and Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA
| | - Matan Hofree
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Ruochun Huang
- RayBiotech, Guangzhou, China.,RayBiotech, Norcrosse, GA, USA
| | - Hudson Johns
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Anna Karydas
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | | | - Andrey Loboda
- Genetics and Pharmacogenomics, Merck Research Laboratories, West Point, PA, USA
| | - Eliezer Masliah
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Ramya Narasimhan
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | | | | | - Suraj Pradhan
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Rosa Rademakers
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Chung-Huan Sun
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Bruce L Miller
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Trey Ideker
- Departments of Bioengineering and Medicine, University of California San Diego, La Jolla, CA, USA
| | - Tony Wyss-Coray
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA. .,Center for Tissue Regeneration, Repair and Restoration, VA Palo Alto Health Care System, Palo Alto, CA, USA.
| |
Collapse
|
24
|
Trends in the Design and Development of Specific Aptamers Against Peptides and Proteins. Protein J 2016; 35:81-99. [DOI: 10.1007/s10930-016-9653-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
|
25
|
Galasko D. Expanding the Repertoire of Biomarkers for Alzheimer's Disease: Targeted and Non-targeted Approaches. Front Neurol 2015; 6:256. [PMID: 26733934 PMCID: PMC4680926 DOI: 10.3389/fneur.2015.00256] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Accepted: 11/23/2015] [Indexed: 01/12/2023] Open
Abstract
The first biofluid markers developed for Alzheimer’s disease (AD) used targeted approaches for discovery. These initial biomarkers were directed at key protein constituents of the hallmark brain lesions in AD. Biomarkers for plaques targeted the amyloid beta protein (Aβ) and for tangles, the microtubule-associated protein tau. Cerebrospinal fluid levels of Aβ and tau have excellent diagnostic utility and can be used to monitor aspects of therapeutic development. Recent research has extended our current concepts of AD, which now include a slow buildup of pathology during a long pre-symptomatic period, a complex cascade of pathological pathways in the brain that may accelerate once symptoms develop, the potential of aggregated proteins to spread across brain pathways, and interactions with vascular and other age-associated brain pathologies. There are many potential roles for biomarkers within this landscape. A more diverse set of biomarkers would provide a better picture of the staging and state of pathological events in the brain across the stages of AD. The aim of this review is to focus on methods of biomarker discovery that may help to expand the currently accepted biomarkers. Opportunities and approaches for targeted and non-targeted (or −omic) biomarker discovery are highlighted, with examples from recent studies. How biomarker discoveries can be developed and integrated to become useful tools in diagnostic and therapeutic efforts is discussed.
Collapse
Affiliation(s)
- Douglas Galasko
- Department of Neurosciences, Shiley-Marcos Alzheimer's Disease Research Center, University of California, San Diego , La Jolla, CA , USA
| |
Collapse
|
26
|
Lehallier B, Essioux L, Gayan J, Alexandridis R, Nikolcheva T, Wyss-Coray T, Britschgi M. Combined Plasma and Cerebrospinal Fluid Signature for the Prediction of Midterm Progression From Mild Cognitive Impairment to Alzheimer Disease. JAMA Neurol 2015; 73:203-212. [PMID: 26659895 DOI: 10.1001/jamaneurol.2015.3135] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Importance A reliable method of detecting Alzheimer disease (AD) in its prodromal state is needed for patient stratification in clinical trials or for personalizing existing or potential upcoming therapies. Current cerebrospinal fluid (CSF)- or imaging-based single biomarkers for AD offer reliable identification of patients with underlying AD but insufficient prediction of the rate of AD progression. Objective To optimize prediction of progression from mild cognitive impairment (MCI) to AD dementia by combining information from diverse patient variables. Design, Setting, and Participants This cohort study from the Alzheimer Disease Neuroimaging Initiative (ADNI) enrolled 928 patients with MCI at baseline and 249 selected variables available in the ADNI data set. Variables included clinical and demographic data, cognitive scores, magnetic resonance imaging-based brain volumetric data, the apolipoprotein E (APOE) and translocase of outer mitochondrial membrane 40 homolog (TOMM40) genotypes, and analyte levels measured in the CSF and plasma. Data were collected in July 2012 and analyzed from July 1, 2012, to June 1, 2015. Main Outcomes and Measures Progression from MCI to AD within 1 to 6 years. To determine whether combinations of markers could predict progression from MCI to AD within 1 to 6 years, the elastic net algorithm was used in an iterative resampling of a training- and test-based variable selection and modeling approach. Results Among the 928 patients with MCI in the ADNI database, 94 had 224 of the required variables available for the modeling. The results showed the contributions of age, Clinical Dementia Rating Sum of Boxes composite test score, hippocampal volume, and multiple plasma and CSF factors in modeling progression to AD. A combination of apolipoprotein A-II and cortisol levels in plasma and fibroblast growth factor 4, heart-type fatty acid binding protein, calcitonin, and tumor necrosis factor-related apoptosis-inducing ligand receptor 3 (TRAIL-R3) in CSF allowed for reliable prediction of disease status 3 years from the time of sample collection (80% classification accuracy, 88% sensitivity, and 70% specificity). Conclusions and Relevance These study findings suggest that a combination of markers measured in plasma and CSF, distinct from β-amyloid and tau, could prove useful in predicting midterm progression from MCI to AD dementia. Such a large-scale, multivariable-based analytical approach could be applied to other similar large data sets involving AD and beyond.
Collapse
Affiliation(s)
- Benoit Lehallier
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Laurent Essioux
- Translational Technologies and Bioinformatics, Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche, Ltd, Basel, Switzerland
| | - Javier Gayan
- Translational Technologies and Bioinformatics, Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche, Ltd, Basel, Switzerland
| | - Roxana Alexandridis
- Translational Technologies and Bioinformatics, Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche, Ltd, Basel, Switzerland
| | - Tania Nikolcheva
- Roche Pharma Development, F. Hoffmann-La Roche, Ltd, Basel, Switzerland
| | - Tony Wyss-Coray
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California4Center for Tissue Regeneration, Repair and Restoration, Veterans Affairs Palo Alto Health Care System, Palo Alto, California
| | - Markus Britschgi
- Neuroscience, Ophthalmology, and Rare Diseases Discovery and Translational Areas, Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche, Ltd, Basel, Switzerland
| | | |
Collapse
|
27
|
Baird AL, Westwood S, Lovestone S. Blood-Based Proteomic Biomarkers of Alzheimer's Disease Pathology. Front Neurol 2015; 6:236. [PMID: 26635716 PMCID: PMC4644785 DOI: 10.3389/fneur.2015.00236] [Citation(s) in RCA: 86] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Accepted: 10/26/2015] [Indexed: 12/31/2022] Open
Abstract
The complexity of Alzheimer’s disease (AD) and its long prodromal phase poses challenges for early diagnosis and yet allows for the possibility of the development of disease modifying treatments for secondary prevention. It is, therefore, of importance to develop biomarkers, in particular, in the preclinical or early phases that reflect the pathological characteristics of the disease and, moreover, could be of utility in triaging subjects for preventative therapeutic clinical trials. Much research has sought biomarkers for diagnostic purposes by comparing affected people to unaffected controls. However, given that AD pathology precedes disease onset, a pathology endophenotype design for biomarker discovery creates the opportunity for detection of much earlier markers of disease. Blood-based biomarkers potentially provide a minimally invasive option for this purpose and research in the field has adopted various “omics” approaches in order to achieve this. This review will, therefore, examine the current literature regarding blood-based proteomic biomarkers of AD and its associated pathology.
Collapse
Affiliation(s)
- Alison L Baird
- Department of Psychiatry, University of Oxford , Oxford , UK
| | - Sarah Westwood
- Department of Psychiatry, University of Oxford , Oxford , UK
| | - Simon Lovestone
- Department of Psychiatry, University of Oxford , Oxford , UK
| |
Collapse
|
28
|
Blennow K, Zetterberg H. The past and the future of Alzheimer's disease CSF biomarkers-a journey toward validated biochemical tests covering the whole spectrum of molecular events. Front Neurosci 2015; 9:345. [PMID: 26483625 PMCID: PMC4586276 DOI: 10.3389/fnins.2015.00345] [Citation(s) in RCA: 64] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2015] [Accepted: 09/14/2015] [Indexed: 11/28/2022] Open
Abstract
This paper gives a short review on cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease (AD), from early developments to high-precision validated assays on fully automated lab analyzers. We also discuss developments on novel biomarkers, such as synaptic proteins and Aβ oligomers. Our vision for the future is that assaying a set of biomarkers in a single CSF tube can monitor the whole spectrum of AD molecular pathogenic events. CSF biomarkers will have a central position not only for clinical diagnosis, but also for the understanding of the sequence of molecular events in the pathogenic process underlying AD and as tools to monitor the effects of novel drug candidates targeting these different mechanisms.
Collapse
Affiliation(s)
- Kaj Blennow
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg Mölndal, Sweden
| |
Collapse
|
29
|
Zhao X, Modur V, Carayannopoulos LN, Laterza OF. Biomarkers in Pharmaceutical Research. Clin Chem 2015; 61:1343-53. [PMID: 26408531 DOI: 10.1373/clinchem.2014.231712] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2015] [Accepted: 08/17/2015] [Indexed: 11/06/2022]
Abstract
BACKGROUND Biomarkers are important tools in drug development and are used throughout pharmaceutical research. CONTENT This review focuses on molecular biomarkers in drug development. It contains sections on how biomarkers are used to assess target engagement, pharmacodynamics, safety, and proof-of-concept. It also covers the use of biomarkers as surrogate end points and patient selection/companion diagnostics and provides insights into clinical biomarker discovery and biomarker development/validation with regulatory implications. To survey biomarkers used in drug development--acknowledging that many pharmaceutical development biomarkers are not published--we performed a focused PubMed search employing "biomarker" and the names of the largest pharmaceutical companies as keywords and filtering on clinical trials and publications in the last 10 years. This yielded almost 500 entries, the majority of which included disease-related (approximately 60%) or prognostic/predictive (approximately 20%) biomarkers. A notable portion (approximately 8%) included HER2 (human epidermal growth factor receptor 2) testing, highlighting the utility of biomarkers for patient selection. The remaining publications included target engagement, safety, and drug metabolism biomarkers. Oncology, cardiovascular disease, and osteoporosis were the areas with the most citations, followed by diabetes and Alzheimer disease. SUMMARY Judicious biomarker use can improve pharmaceutical development efficiency by helping to select patients most appropriate for treatment using a given mechanism, optimize dose selection, and provide earlier confidence in accelerating or discontinuing compounds in clinical development. Optimal application of biomarker technology requires understanding of candidate drug pharmacology, detailed modeling of biomarker readouts relative to pharmacokinetics, rigorous validation and qualification of biomarker assays, and creative application of these elements to drug development problems.
Collapse
Affiliation(s)
| | - Vijay Modur
- Translational Medicine, Genzyme Corporation, Cambridge, MA
| | | | | |
Collapse
|
30
|
Kiddle SJ, Steves CJ, Mehta M, Simmons A, Xu X, Newhouse S, Sattlecker M, Ashton NJ, Bazenet C, Killick R, Adnan J, Westman E, Nelson S, Soininen H, Kloszewska I, Mecocci P, Tsolaki M, Vellas B, Curtis C, Breen G, Williams SCR, Lovestone S, Spector TD, Dobson RJB. Plasma protein biomarkers of Alzheimer's disease endophenotypes in asymptomatic older twins: early cognitive decline and regional brain volumes. Transl Psychiatry 2015; 5:e584. [PMID: 26080319 PMCID: PMC4490288 DOI: 10.1038/tp.2015.78] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2015] [Accepted: 05/07/2015] [Indexed: 01/08/2023] Open
Abstract
There is great interest in blood-based markers of Alzheimer's disease (AD), especially in its pre-symptomatic stages. Therefore, we aimed to identify plasma proteins whose levels associate with potential markers of pre-symptomatic AD. We also aimed to characterise confounding by genetics and the effect of genetics on blood proteins in general. Panel-based proteomics was performed using SOMAscan on plasma samples from TwinsUK subjects who are asymptomatic for AD, measuring the level of 1129 proteins. Protein levels were compared with 10-year change in CANTAB-paired associates learning (PAL; n = 195), and regional brain volumes (n = 34). Replication of proteins associated with regional brain volumes was performed in 254 individuals from the AddNeuroMed cohort. Across all the proteins measured, genetic factors were found to explain ~26% of the variability in blood protein levels on average. The plasma level of the mitogen-activated protein kinase (MAPK) MAPKAPK5 protein was found to positively associate with the 10-year change in CANTAB-PAL in both the individual and twin difference context. The plasma level of protein MAP2K4 was found to suggestively associate negatively (Q < 0.1) with the volume of the left entorhinal cortex. Future studies will be needed to assess the specificity of MAPKAPK5 and MAP2K4 to eventual conversion to AD.
Collapse
Affiliation(s)
- S J Kiddle
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK,Institute of Psychiatry, Psychology and Neuroscience, King's College London, Box P092, SGDP Building, De Crespigny Park, London SE5 8AF, UK. E-mail: or
| | - C J Steves
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - M Mehta
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - A Simmons
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - X Xu
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - S Newhouse
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - M Sattlecker
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - N J Ashton
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK,Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - C Bazenet
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK,Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - R Killick
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - J Adnan
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - E Westman
- Department of Neurobiology, Care Sciences and Society, Karolinska Instituet, Stockholm, Sweden
| | | | - H Soininen
- Institute of Clinical Medicine – Neurology, University of Eastern Finland, Kuopio, Finland,NeuroCenter, Kuopio University Hospital, Kuopio, Finland
| | - I Kloszewska
- Department of Old Age Psychiatry and Psychotic disorders, Medical University of Łódź, Łódź, Poland
| | - P Mecocci
- Institute of Gerontology and Geriatrics, University of Perugia, Perugia, Italy
| | - M Tsolaki
- 3rd Department of Neurology, Aristotle University, Thessaloniki, Greece
| | - B Vellas
- Department of Internal Medicine and Geriatric Medicine, INSERM University of Toulouse, Toulouse, France
| | - C Curtis
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - G Breen
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - S C R Williams
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - S Lovestone
- Department of Psychiatry, Oxford University, Warneford Hospital, Oxford, UK
| | - T D Spector
- Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
| | - R J B Dobson
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK,Institute of Psychiatry, Psychology and Neuroscience, King's College London, Box P092, SGDP Building, De Crespigny Park, London SE5 8AF, UK. E-mail: or
| |
Collapse
|
31
|
Voyle N, Baker D, Burnham SC, Covin A, Zhang Z, Sangurdekar DP, Tan Hehir CA, Bazenet C, Lovestone S, Kiddle S, Dobson RJ. Blood Protein Markers of Neocortical Amyloid-β Burden: A Candidate Study Using SOMAscan Technology. J Alzheimers Dis 2015; 46:947-61. [PMID: 25881911 PMCID: PMC4923714 DOI: 10.3233/jad-150020] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/26/2015] [Indexed: 12/18/2022]
Abstract
BACKGROUND Four previously reported studies have tested for association of blood proteins with neocortical amyloid-β burden (NAB). If shown to be robust, these proteins could have utility as a blood test for enrichment in clinical trials of Alzheimer's disease (AD) therapeutics. OBJECTIVE This study aimed to investigate whether previously identified blood proteins also show evidence for association with NAB in serum samples from the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL). The study considers candidate proteins seen in cohorts other than AIBL and candidates previously discovered in the AIBL cohort. METHODS Our study used the SOMAscan platform for protein quantification in blood serum. Linear and logistic regressions were used to model continuous NAB and dichotomized NAB respectively using single proteins as a predictor. Multiple protein models were built using stepwise regression techniques and support vectors machines. Age and APOEɛ4 carriage were used as covariates for all analysis. RESULTS Of the 41 proteins previously reported, 15 AIBL candidates and 20 non-AIBL candidates were available for testing. Of these candidates, pancreatic polypeptide (PPY) and IgM showed a significant association with NAB. Notably, IgM was found to associate with continuous NAB across cognitively normal control subjects. CONCLUSIONS We have further demonstrated the association of PPY and IgM with NAB, despite technical differences between studies. There are several reasons for a lack of significance for the other candidates including platform differences and the use of serum rather than plasma samples. To investigate the possibility of technical differences causing lack of replication, further studies are required.
Collapse
Affiliation(s)
- Nicola Voyle
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- MRC Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK
| | - David Baker
- Janssen R&D, Neurosciences, Titusville, NJ, USA
| | - Samantha C. Burnham
- CSIRO Digital Productivity and Food and Nutrition Flagships: eHealth, Floreat, WA, Australia
| | | | | | | | | | - Chantal Bazenet
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - Simon Lovestone
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Department of Psychiatry, Oxford University, Oxford, UK
| | - Steven Kiddle
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- MRC Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK
| | - Richard J.B. Dobson
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| |
Collapse
|