Technical Performance Evaluation for Alzheimer’s Disease Biomarker Discovery

Alzheimer’s Disease (AD) is a devastating neurodegenerative disorder affecting nearly 50 million worldwide; with only 1-in-4 people diagnosed there is a genuine need for discovery of blood-based biomarkers. A recent paper from a group at Harvard and Massachusetts General Hospital looks at a technical evaluation of reproducibility and biological variation in AD patient samples collected over time.

Alzheimer’s Disease research needs biomarkers for both diagnosis and disease progression

The devastation of Alzheimer’s Disease (AD) is clear: As the most common type of dementia, this progressive neurologic disorder causes brain atrophy and eventual death. Characteristic symptoms of dementia include difficulties with memory, language, problem-solving and other cognitive skills. Aside from AD, other types of dementia include cerebrovascular disease (which could be caused by stroke), Lewy body disease (abnormal aggregation of a protein called alpha-synuclein), Parkinson’s Disease (aggregation of alpha-synuclein in a particular area of the brain called the substantia nigra) and Hippocampal sclerosis (the hardening of hippocampus tissue).

Alzheimer’s Disease is estimated to cause 60% to 80% of all cases of dementia, and for AD and AD-related dementias there is great heterogeneity within the disease. There are well-known risk factors in addition to age such as genetic predisposition, namely mutations in the Apolipoprotein E gene (specifically the e4 form of the gene), medical conditions such as diabetes and high cholesterol, and other factors such as smoking and sedentary lifestyle. Overlapping conditions, such as cardiovascular disease and inflammatory disease complicate this picture.

For adults diagnosed with AD over 65 years of age, studies indicate an average survival of four to eight years, although some individuals live as long as 20 years after diagnosis.

The diagnosis of AD historically has been through clinical symptoms, and the exclusion of other causes of cognitive decline. Autopsy of brain tissue is considered the “gold standard” for definitive diagnosis. An autopsy will identify hallmark plaques, tangles, and a structure of protein buildup called Lewy bodies. Obviously, a biopsy of brain tissue post-mortem for diagnosis is neither practical nor desirable.

It is estimated that 75% of individuals with AD are currently undiagnosed.1

Cerebrospinal Fluid (CSF) is not a practical sample source

Cerebrospinal Fluid (CSF) biomarkers have been identified and are used to diagnose Mild Cognitive Impairment due to AD. These markers, called amyloid-β and tau-Aβ42 have been shown to be useful in a research setting for monitoring neurodegeneration over time. This neurodegenerative process can then define different stages of the disease, relating the levels of specific biomarkers to defined disease progression. In addition, this information is of critical importance in evaluating secondary effects of testing treatments for the disease in a clinical trial setting.

The challenges with repeated CSF sampling are its acceptability and narrow adoption. Lumbar punctures involve greater complexity, have a non-zero increase in risk with the sampling procedure itself, and are generally viewed as inferior to the wide adoption and convenience of blood-based sampling. In addition, amyloid-β is known to be a poor marker for staging the progression of the disease, and there is a critical unmet need to identify early stages of AD, for which non-invasive biomarkers would be invaluable. This critical gap in identifying AD-related biomarkers in blood has resulted in several groups increasing their search. Identifying these markers would enable the monitoring of AD progression, disease staging (that is, its degree of severity), and the further characterization of disease pathophysiology.

Other biomarkers for AD include PET scans looking for amyloid-β deposits or pathologic tau imaging signatures.

An independent technical evaluation for reproducibility

A recent paper titled “Technical Performance Evaluation of Olink Proximity Extension Assay for Blood-Based Biomarker Discovery in Longitudinal Studies of Alzheimer’s Disease”2 examined a set of samples collected from 54 individuals with and without AD, collected annually over three years. Technical reproducibility, temporal stability, and analysis of variation in the measurements were all reported on, across five Olink® Target 96 panels (specifically, the Cardiometabolic, Cardiovascular III, Immuno-Oncology, Inflammation, and Neuro-Exploratory panels), based on Proximity Extension Assay (PEA) technology.

A total of 415 measurements were taken for 377 unique proteins and evaluated for technical and biological variability. Three patient samples were run in duplicate across plates and panels to assess technical variability (both between samples on the same plate – i.e. intraplate – or between samples on different plates – i.e. interplate).

A summary table is provided of their experimental design (Figure 1).

Figure 1: Study design for technical evaluation of AD biomarkers

Longitudinal sample analysis of technical versus biological variability

Intra-plate coefficients of variation (CVs) were considered “excellent, with only five measured analytes displaying CVs > 15%” (and the vast majority of CVs <5%). The higher CVs were strongly associated with lower NPX values.

In total, 36 proteins were present on more than one panel, enabling an opportunity to measure the same analyte on different panels. The correlations across the 36 proteins averaged 0.9, with only 4 out of 36 proteins with a correlation of less than 0.85.

The researchers were also able to look at intra-plate technical variability, inter-plate technical variability, and the biological variability across the three samples run in duplicate. ANOVA analyses indicated that sample variability was “primarily due to individual biological variation”.

A strong endorsement of PEA technology

The discussion states the following: “In accordance with standard criteria for immunocapture-based assays, Olink technology proved to be technically robust, providing acceptable performance for inter-and intraplate precision (CV <15%) for the majority of proteins.” They point out that the Olink PEA technology is “an attractive technology for biomarker analysis as it measures a large number of proteins using a very small volume of sample (1 μL)”.

The biological variation of individual protein levels over time was shown in this research to be larger than technical variability attributing this to a number of external factors such as “circadian rhythms, environmental stressors, sleep, age, diet and disease process.”

Additional technical variability information, both on the Olink Target 48 Cytokine Panel and commonly used multiplex proteomics platforms, can be found on the whitepaper “Multiplex analysis of inflammatory proteins: a comparative study across multiple platforms”.3

References

  1. 2022 Alzheimer’s disease facts and figures. Alzheimers Dement. 2022 18(4):700-789. doi:10.1002/alz.12638
  2. Carlyle BC and Arnold SE et al. Technical Performance Evaluation of Olink Proximity Extension Assay for Blood-Based Biomarker Discovery in Longitudinal Studies of Alzheimer’s Disease. Front Neurol. 2022 13:889647. doi:10.3389/fneur.2022.889647
  3. Olink whitepaper “Multiplex analysis of inflammatory proteins: A comparative study across multiple platforms” available online: https://info.olink.com/olink-multiplex-analysis-of-inflammatory-proteins

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