Company: APM
Filing Date: 2025-12-05
Form Type: 424B5
Source: 0001213900-25-118752
Chunk: 300

Company: Aptorum Group Ltd
Filing Date: 2025-12-05
Form: 424B5
Chunk 300
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, on credit outcomes using national credit and Medicare databases. The authors reported weaken credit scores and payment delinquency,
particularly for mortgage and credit cards, “years prior to eventual diagnosis.” DiamiR believes these data on financial impact
of neurodegenerative diseases, such as MCI and AD, on patients and their families further supports the importance of developing and making
available minimally invasive biomarkers, such as CogniMIRpanel, for early detection, including at pre-symptomatic stages,
for broader use.

COGNIMIR ®PANEL OF miRNA BIOMARKERS for MCI and AD RISK ASSESSMENT

The table below presents the
CogniMIR panel of miRNA biomarkers in its current form. The miRNAs listed below are detectable in blood plasma and include
miRNAs which are enriched in specific brain regions and present in synapses and those associated with inflammation. In 2023 DiamiR performed
analytical validation of the technology, demonstrating that all CogniMIR panel miRNAs can be reliably and consistently
detected in plasma samples (Kunwar et al. (2023) Diagnostics 13:2170). In 2H 2023 DiamiR introduced machine learning with AI analytics
into its laboratory to optimize the panel, and, if feasible, reduce the number of miRNAs in CogniMIR to improve COGS and
laboratory workflow without sacrificing performance.

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Brain-enriched miRNAs detectable in blood plasma hold strong potential as peripheral biomarkers of AD and AD related dementias

The data generated by DiamiR
over the last fourteen years provide strong support for the use of circulating brain-enriched and inflammation-associated miRNAs
as biomarkers for detecting and assessing the course of neurodegenerative diseases at early, including preclinical, and later stages.
Most notable findings include:

DIFFERENTIATION BETWEEN MCI AND AGE-MATCHED CONTROL

| In studies conducted with plasma samples collected                                                                                      
 at Roskamp Institute, Sarasota, FL, miR-132 and miR-134 biomarker families detecting clinically diagnosed MCI with up to 0.95 accuracy  
 (n=60) were identified. The data were replicated in an independent cohort of samples (n=100). Progression from a normal cognitive state 
 to MCI was predicted with 0.84 accuracy