Biomarkers and how to use them

Biomarkers are diagnostic tools that can detect disease-specific alterations in the brain. Depending on what moment in the disease process these alterations occur, biomarkers are more suitable for early or differential dementia diagnosis. Ideal biomarkers also allow monitoring of disease progression. Optimisation of existing biomarkers, as well as the development of novel biomarkers, is required to improve early and differential dementia diagnosis.

• Synaptic dysfunction is the best correlate of cognitive impairment that precedes neuronal cell death in patients along the Alzheimer’s disease (AD) continuum. EEG topographical markers were found to correlate with surrogate synaptic markers and therefore contribute to early detection of synaptic dysfunction in patients along the AD continuum [1]. In both patients diagnosed with mild cognitive impairment (MCI, n=40) and AD (n=20), the pattern of regional brain glucose hypometabolism correlated with localisation of brain electrical sources and decreased Global Field Synchronization (GFS). Being a widely available and non-invasive diagnostic method, the authors think EEG might have broad implications in AD drug trials and clinical practice.
• Neurofilament light (NfL) protein is a known marker of neuroaxonal damage, but its levels in cerebrospinal fluid and serum might be associated with age and sub-clinical morphologic brain changes in the normal population as well. A study reported rising and more variable serum NfL levels in healthy individuals >60 years, indicating accelerated neurodegeneration which may be confounded by subclinical pathologic brain changes [2]. Serum NfL was measured by a single molecule array in 335 healthy individuals who were followed for a mean of 6 years. Mean serum NfL levels were more stable below the age of 60 years, but then increased in a non-linear manner (see Figure). An increase of group variances in serum NfL levels above 60 years was also observed. Baseline serum NfL (β=0.549, P<0.0001) and its change over time (β=0.486, P<0.0001) were the strongest independent predictors for future brain atrophy in the age group above 60 years. In younger individuals, baseline normalised brain volume (β=0.530, P<0.01) was the strongest predictor.
• Insulin-like growth factor binding protein-2 (IGFBP2) was identified as a novel biomarker for incident dementia [3]. IGFBP2-related pathways may play an important role in the development of dementia. Plasma IGFBP2 was measured in 1,596 dementia-free Framingham Heart Study Offspring cohort participants (1998-2001), with a mean age of 69 years. During a median follow-up of 12 years, 131 participants developed dementia (of which 98 AD). The highest quintile of IGFBP2, when compared with the lowest quintile, was associated with an increased risk of incident dementia (HR 2.82) as well as AD (HR 3.28). Higher circulating IGFBP2 levels were also associated with poorer performance on tests of global cognition and abstract reasoning.

Figure: Percentile range areas of serum NfL in normal elderly during the course of ageing [2]



Diagnostic algorithm

A consensual diagnostic algorithm to guide the combined use of biomarkers has been developed for the first time [4]. Dementia experts joined a Delphi procedure on behalf of 5 Italian scientific societies (SINdem, AIP, AIMN, AINR, and SIBioC). Their recommendations attempt to maximise biomarkers’ informative value over costs.

The panel identified a diagnostic algorithm including clinical and cognitive assessment, blood examination, and MRI with both exclusionary and inclusionary value at baseline. Different examinations are then prescribed, based on the diagnostic hypothesis: cerebrospinal fluid biomarkers -or amyloid PET as second choice- for suspected AD; FDG-PET for suspected frontotemporal lobar degeneration (FTLD) and low confidence of AD; and I-123 MIBG cardiac scintigraphy for suspected Lewy body dementia (DLB). Biomarker investigation for AD in older patients with consistent clinical and MRI findings should be considered based on its plausible clinical impact.

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   1. Smailovic U, et al. EAN 2019, O1105.
   2. Khalil M, et al. EAN 2019, O1103.
   3. McGrath E, et al. EAN 2019, O3111.
   4. Boccardi K, et al. EAN 2019, O1101.

Posted on 27 August 201929 February 2024