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Precision medicine for Alzheimer’s Disease

Emerging Paradigm in Genomics, Biomarkers & AI tools

Dr. Parmi Tripathi, Director, Bionarrative

“One size fits all” concept has been traditionally practiced in clinical care setting till date, however with an increased complexity of the diseases, it is of paramount importance to change the perspective in therapeutic management here with shifting the focus more towards precision-based treatment approach specifically for critical neurological conditions. Alzheimer’s Disease (AD), a neurodegenerative disorder & common cause of dementia, represents high incidence rate in elderly population. Clinical manifestations include senile plaque deposition and neurofibrillary tangles. Given its complicated pathophysiology, it is now emerging as a syndrome rather than a disease. Progressive in nature, AD is interlinked with multifaceted aetiologies majorly due to genetic, environmental, or old age. Approved modern medicines for AD offers limited advantage of symptomatic management. Moreover, AD requires a designated framework that offers patient-centric tailored treatment approach. Precision medicine, an individualised therapeutic care, is an advanced management of AD. While offering preventive measures, it is a promising technique to attain better prognosis. The strategy implicates utilisation of a concept-based unique triad of AD specific biomarkers, genetic mapping and imaging technique powered with AI technology. It aims to predefine treatment perspective and may unlock much warranted sustainability of disease management.

Alzheimer’s Disease: Current Clinical Implications

Alzheimer’s disease, a common cause of dementia, is characterised by deposition of senile plaques and neurofibrillary tangles. These protein deposits are inherent key features of AD distinguishing from other types of dementia. AD also notably marks with neuroinflammation & oxidative stress. Predominant pathophysiological events that cause the disease are regulated by hypothesis such as amyloid cascade hypothesis, tau hypothesis, cholinergic hypothesis, and neuroinflammation hypothesis. Decades of research & collective clinical evidence related to pathogenesis critically reflect significance of Aβ deposit as key driver in triggering cascade of events leading to onset and progression of the disease. Two subtypes of AD are prevalent i.e. early onset AD (EOAD) or familial AD (FAD) and late onset AD (LOAD) or sporadic AD (sAD). EOAD is due to inherited genetic mutations in three major genes such as Presenilin 1 (PSEN1), Presenilin 2 (PSEN2) and amyloid precursor protein (APP). FAD accounts for approx. 5-10% of AD cases whereas LOAD is the most common type of AD. Cause for LOAD is majorly due to old age, metabolic factors, environmental or inherent APOE4 allele carriers. Approved medications for AD offer limited advantage of symptom management with negligible impact on delaying progression of the disease. Cholinesterase inhibitors, NMDA receptor antagonist & immunotherapy drugs are few of the handful available treatment for AD. Apart from limited treatment options, primary challenge in AD is its early detection, accurate diagnosis, analyse clinical status of patient to predefine treatment strategy of which crucial challenge remains initiation of treatment on right time.

Precision Medicine (PM) Approach

PM paradigm is a concept-based individualised strategy for patients’ treatment considering their genetics, physiological, lifestyle and clinical status. It is a strong triad relationship of neurobiology & AI technology that offers accurate diagnosis intertwined with better prognosis. Key attribute for ensuring better prognosis is early detection of AD in both symptomatic and non-symptomatic patients to predict treatment. Current diagnostic practice includes combination of cognitive tests, blood tests, medical history, and brain imaging such as MRI & CT scan (limited only to study structural changes). Whereas, mapping of biomarkers, genetic mutations along with neuroimaging can determine in-depth analysis related to severity of the disease to predefine patient specific therapeutic strategy. Biggest advantage can be for the patients diagnosed with mild cognitive impairment or non-symptomatic AD patients; precision approach can analyse the likelihood of advancing to AD or confirm presence of the disease.

Biomarkers

Biomarkers analysis is advocated for assessing early & accurate diagnosis, define subtype of AD, disease stage, progression analysis, identifying relevant treatment and evaluate prognosis certainty. Cerebrospinal fluid (CSF) tests are often conducted for diagnosis of AD and few approved ready to use diagnostic kits are available i.e Elecsys® and Lumipulse®. At present three biomarkers, intrinsic to AD, Aβ1-42, total tau-protein (t-tau), and phosphorylated tau (p-tau181) are strongly recommended. Aβ1-42 is neurotoxic and insoluble, oligomerizes to form senile plaques. Henceforth, clinical determination of CSF Aβ 42/40 ratio is proven to be beneficial at determining the severity. Recently, NIA-AA guidelines classified these CSF markers as A/T/N. Detection of Aβ deposition with normal p-Tau status will be classified as “Alzheimer’s pathological change” whereas detection of both p-Tau and Aβ will be classified as “Alzheimer’s disease.” N biomarker analysis represents only neurodegeneration and is not specific for AD but can help identify another pathogenesis.

Table 1: NIA-AA classification of Biomarkers assessment

SR No	Biomarker	CSF marker
1	Amyloid (A)	CSF Aβ_42,or Aβ₄₂/Aβ₄₀ ratio
2	Tau (T)	CSF phospho-tau
3	Neurodegeneration (N)	CSF total tau

Similarly other less invasive fluids such as blood & saliva are under research to detect these biomarkers. Although studies have successfully detected altered Aβ1-42, p-Tau levels in both blood & saliva, more validation is warranted to determine its precision.

Neurofilament (NFL) is another well- researched biomarker, embedded in myelinated axons expressed in white matter pathway. Patients with AD represents significant loss of white matter thereby increasing CSF concentration of NFL as compared to healthy patients. Novel biomarker i.e. platelet-derived growth factor receptor-β (sPDGFRβ), is emerging to be promising. High CSF concentration is associated with damage to blood brain barrier. Studies suggests that damage to BBB precedes Aβ and p-Tau accumulation. Very few studies have also investigated correlation between other biomarkers with AD such as sTREM2, Neurogranin, HFAB, NSE, VLP-1, s-TREM2. However, AD specificity of these biomarkers is required to be validated in larger studies.

Based on the available clinical evidences, it is evident that analysis of single biomarker has its limitation at predicting the severity of the disease. Henceforth, it is recommended to analyse multiple AD intrinsic biomarkers for accurate predictions.

Genetic Mapping

Genetic mutations, although strongly correlated risk factor for causing FAD, expression of few crucial genes are also found to be associated with sAD. A unique interplay of these genes along with prevalent comorbid condition or environmental factors could possibly play signification role in sAD.

APOE (Apolipoprotein) ɛ4 allele

APOE ɛ4 allele is verified as most common risk factor for developing sAD. It is found to be present in nearly 15% of population and presented in 50% of AD affected patients. Expression of APOE ɛ4 causes reduction in cholesterol transport, impact on amyloid clearance and increased amyloid deposition leading to development of sAD. Carrying one or two copies of ɛ4 allele leads to highest probability of developing AD. Despite of being a carrier, many individuals have not developed AD indicating a role play of external risk factors. Moreover, mapping of this allele can help early detection of sAD and determine likelihood of developing disease.

PSEN2

Presenillin2 gene, part of γ-secretase, encodes PSEN2 protein responsible for amyloid protein production pathway. Mutation of this gene triggers abnormal production of amyloid protein specifically Aβ1-42. 33 such different mutations of this gene have been identified. Unlike PSEN1 mutation (responsible for FAD), PSEN2 mutation exhibits slow progression in production of Aβ1-42 leading to sAD. Environmental factors equally play significant role in determining onset of the disease in individuals expressed with this genetic mutation.

Other Genetic Mutations

Several novel genes are identified by Genome-wide association studies (GWAS) that increases susceptibility of an individual to develop AD. However, these genes are relatively novel and their complete function in AD pathogenesis remains unknown. 11 susceptibility genes including CLU, CR1, TREM2, CD33, BIN1, PICALM, SORL1, ABCA7, EPHA1, CD2AP, MS4A, and have been described so far. However, their exact role in AD pathogenesis is yet to be explored.

Table 2: Genes Listed by GWAS & their function

SR No	Genes	Function
1	CLU	Regulates cholesterol transport. potentially involved in neuroinflammation & amyloid clearance
2	CR1	Regulates immune response. Allegedly associated with amyloid clearance
3	TREM2	Expressed on microglia. Associated with phagocytosis of Amyloid proteins
4	CD33	Immune cell receptor. Possible involvement in phagocytic activity
5	BIN1	Vesicular endocytosis regulation. May be associated with APP processing or generation
6	PICALM	Vesicular endocytosis regulation. May be associated with APP processing or generation
7	SORL1	Allegedly affects Amyloid production
8	ABCA4	Regulates lipid metabolism. Possible role in amyloid clearance
9	EPHA1	Epidermal growth factor receptor. Possible role in neuroinflammation
10	CD2AP	Regulated endocytosis and may be linked to APP processing
11	MS4A	Regulated immunity response

AI based non-invasive neuroimaging techniques

Neuroimaging techniques are recommended diagnostic tool for clinical setting & research. Key imaging techniques used for screening of AD are structural/functional/Volumetric MRI, CT scan & Diffusion tensor imaging (DTI). These diagnostic methods give insights limited only till structural changes of brain and affected areas. Whereas, DTI assesses white matter integrity along with damage to specific nerves. Overall, these techniques lacks providing detailed insights on amyloid and tau protein deposits which is otherwise critical for diagnosing AD.

Amyloid PET scan tests for analysing amyloid protein

Amyloid PET scan detects amyloid protein deposition in brain. The method includes injection of radiotracer having binding affinity for amyloid protein. Scanner detects radiation emission and highlights deposits in affected areas. Recently, these scanning methods are being integrated with AI tools allowing improved quantification and analysis of reports. For instance, BTXBrain-Amyloid AI tool offers improvised benefits of reading the scans such as integrate normal brain templates with scans to study differences in amyloid uptake, recognised least traceable areas of brain with deposits followed with precise evaluation of data and predictive analysis.

PIB PET imaging

The technique uses radioactive tracer specific to amyloid proteins and detects plaque deposition. Though offers higher sensitivity, carbon-11 isotope tracer has shorter half-life limiting its onsite availability. Efforts are being made for integration of AI with PIB PET imaging for more advanced analysis, image enhancements or reconstruction. AI powered computed aided diagnostic tools can help clinicians for accurate prediction & analysis of data.

¹⁸F-fluorodeoxyglucose-positron emission tomography (FDG-PET)

This technique assesses brain function activity and measures glucose metabolism of neural cells which otherwise is reduced in AD patients. It uses radioactive tracer and detects alteration in brain glucose metabolism activity. It can be preferred for early detection but with has limitation of not being specific test for AD.

Future Directions

Futuristic clinical implications of precision medicine approach in AD are subjected to influence on mandating these evaluation techniques in routine diagnosis. Novel biomarkers need to be validated for its specificity in AD. Neuroimaging technique should overcome the challenge of cost-effectiveness & its accessibility. Efficient screening and mapping of all three parameters elucidates the actual bifurcation of AD classified with & without symptoms. The clarity itself offers better opportunity to treat the patients with rightful treatment along with defining its initiation timeline. AI technology should be empowered for faster prediction & analysis.

Conclusion

With growing incidence of AD along with its complexities, it now necessitates improvised professional care not just with approved medications but with curated care for patients. PM paradigm caters predictive insights with outmost clarity on disease severity. Early detection of AD benefits with better prognosis and execution of precision medicine is one such step towards individualised treatment care for patients. With right execution of PM approach, AD can be re-classified as manageable lifestyle condition.

References

Arafah, A., Khatoon, S., Rasool, I., Khan, A., Rather, M.A., Abujabal, K.A., Faqih, Y.A.H., Rashid, H., Rashid, S.M., Bilal Ahmad, S., Alexiou, A., Rehman, M.U., 2023. The Future of Precision Medicine in the Cure of Alzheimer’s Disease. Biomedicines 11, 335. https://doi.org/10.3390/biomedicines11020335
Khoury, R., Ghossoub, E., 2019. Diagnostic biomarkers of Alzheimer’s disease: A state-of-the-art review. Biomarkers in Neuropsychiatry 1, 100005. https://doi.org/10.1016/j.bionps.2019.100005
Krishnamurthy, H.K., Jayaraman, V., Krishna, K., Wang, T., Bei, K., Changalath, C., Rajasekaran, J.J., 2025. An overview of the genes and biomarkers in Alzheimer’s disease. Ageing Research Reviews 104, 102599. https://doi.org/10.1016/j.arr.2024.102599
Precision Medicine: Role of Biomarkers in Early Prediction and Diagnosis of Alzheimer’s Disease | IntechOpen [WWW Document], n.d. URL https://www.intechopen.com/chapters/64435 (accessed 7.8.25).

Dr Parmi is a scientific researcher and an expert medical writer with Ph.D specialising in neurosciences. With an extensive pharmaceutical and healthcare industry experience, she excels at driving innovation. Focused at patient’s centricity, she has played key role in developing innovative medicines that makes meaningful impact on patient’s lives. Dr Parmi has made significant contribution at establishing a patented mouth-dissolving strip (MDS) manufacturing facility. With proven expertise in novel product development, her strong emphasis on quality manufacturing has led to structuring of quality documentation practices for this novel & patented MDS technology aligned with regulatory standards. Dr Parmi has made significant contributions in field of neuroscience research with multiple acclaimed publications. A distinguished medical writer, she serves as editorial board member and peer reviewer in prestigious journals and continuous to make an impact in her field. Author at reputed public health platform, she writes to promote health awareness. Recognised for her exceptional contributions, she is a multiple-time government R&D grant recipient, particularly in neurodegenerative disorder studies.