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1.
  • de Rojas, I., et al. (author)
  • Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores
  • 2021
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1
  • Journal article (peer-reviewed)abstract
    • Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease. © 2021, The Author(s).
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  • Frisoni, G. B., et al. (author)
  • Strategic roadmap for an early diagnosis of Alzheimer's disease based on biomarkers
  • 2017
  • In: Lancet Neurology. - 1474-4422 .- 1474-4465. ; 16:8, s. 661-676
  • Journal article (peer-reviewed)abstract
    • The diagnosis of Alzheimer's disease can be improved by the use of biological measures. Biomarkers of functional impairment, neuronal loss, and protein deposition that can be assessed by neuroimaging (ie, MRI and PET) or CSF analysis are increasingly being used to diagnose Alzheimer's disease in research studies and specialist clinical settings. However, the validation of the clinical usefulness of these biomarkers is incomplete, and that is hampering reimbursement for these tests by health insurance providers, their widespread clinical implementation, and improvements in quality of health care. We have developed a strategic five-phase roadmap to foster the clinical validation of biomarkers in Alzheimer's disease, adapted from the approach for cancer biomarkers. Sufficient evidence of analytical validity (phase 1 of a structured framework adapted from oncology) is available for all biomarkers, but their clinical validity (phases 2 and 3) and clinical utility (phases 4 and 5) are incomplete. To complete these phases, research priorities include the standardisation of the readout of these assays and thresholds for normality, the evaluation of their performance in detecting early disease, the development of diagnostic algorithms comprising combinations of biomarkers, and the development of clinical guidelines for the use of biomarkers in qualified memory clinics.
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  • Lista, S., et al. (author)
  • Evolving Evidence for the Value of Neuroimaging Methods and Biological Markers in Subjects Categorized with Subjective Cognitive Decline
  • 2015
  • In: Journal of Alzheimers Disease. - : IOS Press. - 1387-2877 .- 1875-8908. ; 48
  • Journal article (peer-reviewed)abstract
    • There is evolving evidence that individuals categorized with subjective cognitive decline (SCD) are potentially at higher risk for developing objective and progressive cognitive impairment compared to cognitively healthy individuals without apparent subjective complaints. Interestingly, SCD, during advancing preclinical Alzheimer's disease (AD), may denote very early, subtle cognitive decline that cannot be identified using established standardized tests of cognitive performance. The substantial heterogeneity of existing SCD-related research data has led the Subjective Cognitive Decline Initiative (SCD-I) to accomplish an international consensus on the definition of a conceptual research framework on SCD in preclinical AD. In the area of biological markers, the cerebrospinal fluid signature of AD has been reported to be more prevalent in subjects with SCD compared to healthy controls; moreover, there is a pronounced atrophy, as demonstrated by magnetic resonance imaging, and an increased hypometabolism, as revealed by positron emission tomography, in characteristic brain regions affected by AD. In addition, SCD individuals carrying an apolipoprotein epsilon 4 allele are more likely to display AD-phenotypic alterations. The urgent requirement to detect and diagnose AD as early as possible has led to the critical examination of the diagnostic power of biological markers, neurophysiology, and neuroimaging methods for AD-related risk and clinical progression in individuals defined with SCD. Observational studies on the predictive value of SCD for developing AD may potentially be of practical value, and an evidence-based, validated, qualified, and fully operationalized concept may inform clinical diagnostic practice and guide earlier designs in future therapy trials.
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  • König, Alexandra, et al. (author)
  • Screening over Speech in Unselected Populations for Clinical Trials in AD (PROSPECT-AD) : Study Design and Protocol
  • 2023
  • In: Journal of Prevention of Alzheimer's Disease. - : SERDI. - 2274-5807. ; 10, s. 314-321
  • Journal article (peer-reviewed)abstract
    • Background: Speech impairments are an early feature of Alzheimer’s disease (AD) and consequently, analysing speech performance is a promising new digital biomarker for AD screening. Future clinical AD trials on disease modifying drugs will require a shift to very early identification of individuals at risk of dementia. Hence, digital markers of language and speech may offer a method for screening of at-risk populations that are at the earliest stages of AD, eventually in combination with advanced machine learning. To this end, we developed a screening battery consisting of speech-based neurocognitive tests. The automated test performs a remote primary screening using a simple telephone. Objectives: PROSPECT-AD aims to validate speech biomarkers for identification of individuals with early signs of AD and monitor their longitudinal course through access to well-phenotyped cohorts. Design: PROSPECT-AD leverages ongoing cohorts such as EPAD (UK), DESCRIBE and DELCODE (Germany), and BioFINDER Primary Care (Sweden) and Beta-AARC (Spain) by adding a collection of speech data over the telephone to existing longitudinal follow-ups. Participants at risk of dementia are recruited from existing parent cohorts across Europe to form an AD ‘probability-spectrum’, i.e., individuals with a low risk to high risk of developing AD dementia. The characterization of cognition, biomarker and risk factor (genetic and environmental) status of each research participants over time combined with audio recordings of speech samples will provide a well-phenotyped population for comparing novel speech markers with current gold standard biomarkers and cognitive scores. Participants: N= 1000 participants aged 50 or older will be included in total, with a clinical dementia rating scale (CDR) score of 0 or 0.5. The study protocol is planned to run according to sites between 12 and 18 months. Measurements: The speech protocol includes the following neurocognitive tests which will be administered remotely: Word List [Memory Function], Verbal Fluency [Executive Functions] and spontaneous free speech [Psychological and/ or behavioral symptoms]. Speech features on the linguistic and paralinguistic level will be extracted from the recordings and compared to data from CSF and blood biomarkers, neuroimaging, neuropsychological evaluations, genetic profiles, and family history. Primary candidate marker from speech will be a combination of most significant features in comparison to biomarkers as reference measure. Machine learning and computational techniques will be employed to identify the most significant speech biomarkers that could represent an early indicator of AD pathology. Furthermore, based on the analysis of speech performances, models will be trained to predict cognitive decline and disease progression across the AD continuum. Conclusion: The outcome of PROSPECT-AD may support AD drug development research as well as primary or tertiary prevention of dementia by providing a validated tool using a remote approach for identifying individuals at risk of dementia and monitoring individuals over time, either in a screening context or in clinical trials.
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  • Cavedo, E, et al. (author)
  • The Road Ahead to Cure Alzheimer's Disease: Development of Biological Markers and Neuroimaging Methods for Prevention Trials Across all Stages and Target Populations
  • 2014
  • In: The journal of prevention of Alzheimer's disease. - : SERDI. - 2274-5807. ; 1:3, s. 181-202
  • Journal article (peer-reviewed)abstract
    • Alzheimer's disease (AD) is a slowly progressing non-linear dynamic brain disease in which pathophysiological abnormalities, detectable in vivo by biological markers, precede overt clinical symptoms by many years to decades. Use of these biomarkers for the detection of early and preclinical AD has become of central importance following publication of two international expert working group's revised criteria for the diagnosis of AD dementia, mild cognitive impairment (MCI) due to AD, prodromal AD and preclinical AD. As a consequence of matured research evidence six AD biomarkers are sufficiently validated and partly qualified to be incorporated into operationalized clinical diagnostic criteria and use in primary and secondary prevention trials. These biomarkers fall into two molecular categories: biomarkers of amyloid-beta (Aβ) deposition and plaque formation as well as of tau-protein related hyperphosphorylation and neurodegeneration. Three of the six gold-standard ("core feasible) biomarkers are neuroimaging measures and three are cerebrospinal fluid (CSF) analytes. CSF Aβ 1-42 (Aβ1-42), also expressed as Aβ1-42 : Aβ1- 40 ratio, T-tau, and P-tau Thr181 & Thr231 proteins have proven diagnostic accuracy and risk enhancement in prodromal MCI and AD dementia. Conversely, having all three biomarkers in the normal range rules out AD. Intermediate conditions require further patient follow-up. Magnetic resonance imaging (MRI) at increasing field strength and resolution allows detecting the evolution of distinct types of structural and functional abnormality pattern throughout early to late AD stages. Anatomical or volumetric MRI is the most widely used technique and provides local and global measures of atrophy. The revised diagnostic criteria for “prodromal AD” and "mild cognitive impairment due to AD" include hippocampal atrophy (as the fourth validated biomarker), which is considered an indicator of regional neuronal injury. Advanced image analysis techniques generate automatic and reproducible measures both in regions of interest, such as the hippocampus and in an exploratory fashion, observer and hypothesis-indedendent, throughout the entire brain. Evolving modalities such as diffusion-tensor imaging (DTI) and advanced tractography as well as resting-state functional MRI provide useful additionally useful measures indicating the degree of fiber tract and neural network disintegration (structural, effective and functional connectivity) that may substantially contribute to early detection and the mapping of progression. These modalities require further standardization and validation. The use of molecular in vivo amyloid imaging agents (the fifth validated biomarker), such as the Pittsburgh Compound-B and markers of neurodegeneration, such as fluoro-2-deoxy-D-glucose (FDG) (as the sixth validated biomarker) support the detection of early AD pathological processes and associated neurodegeneration. How to use, interpret, and disclose biomarker results drives the need for optimized standardization. Multimodal AD biomarkers do not evolve in an identical manner but rather in a sequential but temporally overlapping fashion. Models of the temporal evolution of AD biomarkers can take the form of plots of biomarker severity (degree of abnormality) versus time. AD biomarkers can be combined to increase accuracy or risk. A list of genetic risk factors is increasingly included in secondary prevention trials to stratify and select individuals at genetic risk of AD. Although most of these biomarker candidates are not yet qualified and approved by regulatory authorities for their intended use in drug trials, they are nonetheless applied in ongoing clinical studies for the following functions: (i) inclusion/exclusion criteria, (ii) patient stratification, (iii) evaluation of treatment effect, (iv) drug target engagement, and (v) safety. Moreover, novel promising hypothesis-driven, as well as exploratory biochemical, genetic, electrophysiological, and neuroimaging markers for use in clinical trials are being developed. The current state-of-the-art and future perspectives on both biological and neuroimaging derived biomarker discovery and development as well as the intended application in prevention trials is outlined in the present publication.
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