SERF2-SNAP25 Antigen Combination for Autoantibody-Based AD Differentiation

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Solution Overview

Problem

Current diagnostic methods for Alzheimer's disease (AD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB) are inadequate in distinguishing between these conditions, leading to high misdiagnosis rates and difficulty in early detection due to similar clinical symptoms and imaging challenges.

Innovation Solution

A protein antigen combination comprising SERF2 and SNAP25, optionally with additional protein fragments, is used to detect autoantibodies that can accurately identify AD and differentiate it from FTD and DLB.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional diagnostic methods (MMSE, imaging tests) are used for Alzheimer's disease, then diagnosis can be made based on clinical symptoms, but misdiagnosis rate is high and early detection is difficult

Engineering Contradiction:
Improvediagnostic accuracyVSAvoidmisdiagnosis rate
Core Design Contradiction:
Measurement precisionVSReliability

Solution Approach 1:

The patent introduces autoantibodies against SERF2 protein as an intermediary biomarker to detect Alzheimer's disease. These autoantibodies serve as a mediator between the disease pathology and detectable signal, enabling more accurate diagnosis than direct clinical assessment. The autoantibody detection acts as an intermediary step that translates complex disease states into measurable immunological responses.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces mechanical/imaging-based diagnostic systems (MRI, CT, PET) with an immunological detection system. Instead of relying on physical imaging techniques that require expensive equipment and expert interpretation, the invention uses antibody-antigen binding reactions that can be detected through standardized immunoassays, substituting complex mechanical systems with simpler biochemical interactions.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If imaging examinations (MRI, SPECT/PET) are used to distinguish AD from DLB and FTD, then differentiation is possible, but physician experience requirements are high and complexity increases

Engineering Contradiction:
Improvedisease differentiation accuracyVSAvoiddiagnostic system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent extracts the diagnostic function from complex imaging systems and concentrates it into a single biochemical marker - autoantibodies against SERF2. By taking out the essential diagnostic information and encoding it in the presence or absence of specific autoantibodies, the invention simplifies the diagnostic workflow while maintaining differentiation capability between AD, DLB, and FTD.

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The patent changes the diagnostic parameter from structural/imaging features (brain atrophy patterns, perfusion changes) to immunological parameters (autoantibody presence, titers, and profiles). This parameter transformation converts a complex multi-dimensional imaging analysis into a more straightforward serological test that reduces dependency on physician expertise.

Inventive Principle:
Principle #35Parameter changes

3Measurement precision

If cerebrospinal fluid biomarkers (beta amyloid, Tau proteins) are used to identify AD, then certain diagnostic information can be obtained, but patient risk increases due to invasive sampling

Engineering Contradiction:
Improvebiomarker detection accuracyVSAvoidpatient risk from invasive procedure
Core Design Contradiction:
Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent uses serum autoantibodies as an intermediary marker that indirectly reflects central nervous system pathology. Instead of directly measuring proteins in the cerebrospinal fluid (which requires lumbar puncture), the invention detects autoantibodies in peripheral blood that are generated in response to brain pathology, providing a non-invasive window into CNS disease processes.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent creates a copy of the diagnostic information by detecting autoantibody responses in peripheral blood that mirror the pathological processes occurring in the central nervous system. The serum autoantibody profile serves as a copy or surrogate of the CSF biomarker profile, providing equivalent diagnostic value without the invasiveness of lumbar puncture.

Inventive Principle:
Principle #26Copying

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The antigen combination effectively identifies AD and distinguishes it from FTD and DLB, providing accurate diagnostic tools with high specificity and sensitivity, reducing misdiagnosis rates.

Implementation Method 1

a protein antigen combination comprising SERF2 and SNAP25, optionally with additional protein fragments, is used to detect autoantibodies

Methodology Applied
Scientific EffectImmunological recognition:

Data Source

PatentUS20250271453A1Protein antigen combination containing serf2 and application thereof
Publication Date: 2025.08.28 SHANGHAI ZHONGQI BIOTECHNOLOGY CO LTD

AI summary

A protein antigen combination containing SERF2 and applications thereof in the field of biological detection are disclosed. The antigen combination for detecting autoantibodies can distinguish Alzheimer's disease (AD) from frontotemporal dementia (FTD) and dementia with Lewy bodies (DLB), and the antigen combination at least includes protein fragments of SERF2. The new protein antigen composition can not only effectively identify patients with AD, but also effectively distinguish AD from FTD and DLB, enabling accurate identification of AD. It is of great importance in terms of diagnostic applications and research.