Science and research

Discover the science behind our innovative Duritect™ tests and read the research that informs and supports them.

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How Duritect™ works

Duritect™ combines a simple blood test with advanced machine learning technology to assess a patient’s risk of having Alzheimer’s disease (AD) or Parkinson’s disease (PD), quickly and reliably.1,2

It utilizes the immune system’s unique yet consistent reaction to the presence of disease pathology by identifying specific autoantibodies in the blood as biomarkers of AD or PD.3-5

Learn more on this page

  • How Duritect™ works
  • Why use autoantibodies as biomarkers?
  • The test workflow
  • Research publications

A blood-based autoantibody test

Utilizing a patient’s immune system to determine their risk of having AD or PD3,6-8

Autoantibodies clear debris
Thousands of autoantibodies are involved in the clearance of debris within the body
Presence of disease
The presence of disease leads to excessive debris from the affected organ(s)
Excessive debris
Excessive debris in the blood leads to changes in autoantibody levels to clear the debris
Difference in autoantibodies
The differences in autoantibody levels serve as effective biomarkers for the disease
antibodies multiple
Multi-analyte approach
Assesses a distinct panel of multiple autoantibodies to indicate the possible presence of disease pathology
Machine learning algorithm
Ensures a robust, unbiased approach to disease risk assessment through rigorous statistical analysis

Why use autoantibodies as biomarkers?

Research has shown that blood-based autoantibodies are effective biomarkers for disease.4
Detect early
Early indicators
of disease
Autoantibody levels in the blood can change in response to disease pathology before other significant changes happen.3
Clear and easy to understand
High sensitivity
and specificity
Autoantibodies have shown high accuracy, sensitivity, and specificity in distinguishing AD or PD from healthy states and other diseases.3-5,9,10
simple admin
Subtype and
stage detection
Autoantibodies could also be useful for differentiating between various stages of diseases, facilitating staging and monitoring.3,11
Stability
Stability in
the blood
Autoantibodies are reliable markers for testing at any given time,3 without needing any preparation before or after collection.
Rapid
Efficiency
and accuracy
Combining a multi-analyte analysis approach with machine learning improves efficiency and accuracy.3
affordable
Minimally invasive and
cost-effective
Blood tests are minimally invasive and affordable, making them accessible in a wide range of healthcare settings.3

The test workflow

Duritect™ measures serum levels of autoantibody biomarkers using protein antigen targets attached to magnetic beads. The tests run on a trusted and widely used technology for high-throughput analysis of biomolecules, including autoantibodies.1-3

Research
Serum
sample collected
The process starts with a simple blood draw in the primary care setting.
Sample sent
to laboratory
The serum sample is delivered to our CLIA/CAP laboratory* for clinical analysis.
Sample analyzed
by laboratory
The serum sample is analyzed by our experts in the lab and resulting data is entered into our ML-algorithm for the risk score prediction.
Sample report
generated
The sample risk score is entered into the final physician & patient reports and signed by medical directors for accuracy.
Research
Sample report
delivered
Signed final reports are delivered to the ordering physician and patient to conclude the analysis.

View Duritect™ clinical validation data

Find out how our Duritect-AD™ and Duritect-PD™ tests perform in real-world patient samples.

Research publications

Read our peer-reviewed publications to understand the research that informs and supports our innovative tests.

Autoantibodies as biomarkers for neurodegenerative diseases

DeMarshall CA, Viviano J, Emrani S, et al. Early detection of Alzheimer's disease-related pathology using a multi-disease diagnostic platform employing autoantibodies as blood-based biomarkers. J Alzheimer's Dis. 2023;92(3):1077–1091.

DeMarshall CA, Goldwaser EL, Sarkar A, et al. Autoantibodies as diagnostic biomarkers for the detection and subtyping of Multiple Sclerosis. J Neuroimmunol. 2017;309:51–57.


DeMarshall CA, Nagele EP, Sarkar A, et al. Detection of Alzheimer's disease at mild cognitive impairment and disease progression using autoantibodies as blood-based biomarkers. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring. 2016;3:51–62.

DeMarshall CA, Han M, Nagele EP, et al. Potential utility of autoantibodies as blood-based biomarkers for early detection and diagnosis of Parkinson's disease. Immunol Letters. 2015;168(1):80–88.

DeMarshall CA, Sarkar A, Nagele RG. Serum autoantibodies as biomarkers for Parkinson's disease: background and utility. AIMS Med Sci. 2015;2(4):316–325.


Nagele E, Han M, DeMarshall CA, Belinka B, Nagele R. Diagnosis of Alzheimer's disease based on disease-specific autoantibody profiles in human sera. PLoS One. 2011;6(8):e23112.

Han M, Nagele E, DeMarshall CA, Acharya N, Nagele R. Diagnosis of Parkinson's disease based on disease-specific autoantibody profiles in human sera. PLoS One. 2012;7(2):e32383.

General autoantibody research

Kheirkhah R, DeMarshall C, Sieber F, Oh E, Nagele RG. The origin and nature of the complex autoantibody profile in cerebrospinal fluid. Brain, Behavior, & Immunity-Health. 2020;2:100032.

DeMarshall C, Sarkar A, Nagele EP, et al. Utility of autoantibodies as biomarkers for diagnosis and staging of neurodegenerative disease. Int Rev Neurobiol. 2015;122:1–51.

Nagele EP, Han M, Acharya NK, et al. Natural IgG autoantibodies are abundant and ubiquitous in human sera, and their number is influenced by age, gender, and disease. PLoS One. 2013;8(4):e60726.

Abbreviations and references

*Certified by the Clinical Laboratory Improvement Amendments (CLIA) and accredited by the College of American Pathologists (CAP).

References

  1. [Duritect-AD™. Indications for use. Durin Life Sciences. 2024.]
  2. [Duritect-PD™. Indications for use. Durin Life Sciences. 2024.]
  3. DeMarshall CA, Viviano J, Emrani S, et al. Early detection of Alzheimer’s disease-related pathology using a multi-disease diagnostic platform employing autoantibodies as blood-based biomarkers. J Alzheimer’s Dis. 2023;92:1077–1091.
  4. DeMarshall CA, Nagele EP, Sarkar A, et al. Blood-based biomarkers. Detection of Alzheimer’s disease at mild cognitive impairment and disease progression using autoantibodies as blood-based biomarkers. Alzheimer’s Dem. 2016;3:51–62.
  5. DeMarshall CA, Han M, Nagele EP, et al. Potential utility of autoantibodies as blood-based biomarkers for early detection and diagnosis of Parkinson’s disease. Immunol Let. 2015;168:80–88.
  6. Nagele EP, Han M, Acharya NK, DeMarshall CA, Kosciuk MC, Nagele RG. Natural IgG autoantibodies are abundant and ubiquitous in human sera, and their number is influenced by age, gender, and disease. PLoS ONE. 2013;8(4):e60726.
  7. DeMarshall CA, Sarkar A, Goldwaser E, Godsey G, Acharya NK, Nagele RG. Utility of autoantibodies as biomarkers for diagnosis and staging of neurodegenerative diseases. Internat Rev Neurobiol. 2015;122:1–51.
  8. Huang BFF, Boutros PC. The parameter sensitivity of random forests. BMC Bioinformatics. 2016;17:331.
  9. Nagele E, Han M, DeMarshall CA, Belinka B, Nagele R. Diagnosis of Alzheimer’s disease based on disease-specific autoantibody profiles in human sera. PLoS ONE. 2011;6(8):e23112.
  10. Han M, Nagele E, DeMarshall C, Acharya N, Nagele R. Diagnosis of Parkinson’s disease based on disease-specific autoantibody profiles in human sera. PLoS ONE. 2012;7(2):e32383.
  11. DeMarshall CA, Goldwaser EL, Sarkar A, et al. Autoantibodies as diagnostic biomarkers for the detection and subtyping of multiple sclerosis. J Neuroimmunol. 2017;309:51–57.