Within PRISMA, the Laboratory for Complex Genetics (KU Leuven) focused on the development of the PRS itself and is exploring different tools and methodologies to calculate the genetic risk scores. Other research partners have investigated the link between the PRS scores and AD symptoms and characterized the behavior of immune cells (i.e., microglia) with a high PRS score vs. those with a low PRS score.

Besides these clinical and scientific endeavors, it is also of importance to investigate the usefulness of PRS in clinical practice, with potential future valorization of PRS for AD in mind.

Based on high-level and explorative literature search, Hict developed a framework to capture the different contexts in which PRS could potentially be used. This framework encompasses both the drug development process and the clinical journey (Figure 14), which both aim to optimize AD management: the drug development process aims to develop new (and better) treatments, while throughout the clinical journey, the aim is to optimally manage the disease, including the optimization of pharmacological treatment.

With this framework as theoretical backbone, a semi-structured literature search was performed to detect articles on the usage of PRS within the specific context of the drug development process and the clinical pathway. Additionally, an overview on the potential limitations and barriers of the use of PRS in each context was developed. Based on the analysis of the available literature, internal discussions and discussions with the other consortium partners, with experience with PRS calculation and clinical practice of AD, a critical reflection was made on the potential use in AD.

In drug development, PRS can be used during research to facilitate the development of drugs for AD and during the patient journey.The usage of PRS in basic research can help to better understand the disease and to identify and validate new targets. Preclinical studies can use PRS to improve the efficacy of new drugs and to reduce toxicology. In clinical studies, PRS can facilitate identification and selection of trial participants. For example PRS might help to identify patients with MCI due to AD, before the appearance of the first symptoms.

In the patient journey, PRS holds the potential to support early diagnosis as well as support risk prediction for AD development. During treatment and prognosis, PRS can be of use for example to support treatment decisions or to predict the disease course and outcome.

Besides the explorative landscape analysis, Hict developed an early value model to evaluate the potential impact of PRS implementation as a screening tool in the clinical practice of AD diagnosis. Several analyses were undertaken to explore the potential of an early value model, addressing the following questions:

• What is the potential impact of PRS within the diagnostic process of mild cognitive impairments?
• What is the potential long-term impact of a DMT for AD?
• What is the potential long-term impact of PRS in the diagnostic pathway if a DMT for AD becomes available?

The early value model serves to understand the possible impact of PRS under different (future and thus uncertain) circumstances and aims to guide future decision-making once DMT becomes available.

Exploratory literature research and interviews were conducted to develop the most suitable model to answer each research question. If available, existing models were leveraged and adapted to the context and setting of this analysis. Methods of health-economic modeling were applied to quantify health outcomes (identified cases and QALYs) and costs. A decision tree (Figure 15) and Markov model, as accepted health economic models were developed, and expected benefits and costs were calculated using probabilities, resource use, and costs derived from the literature or governmental sources. Cost estimates for PRS were based on literature and expert discussions. 

Figure 15. Diagnostic tree for MCI patients due to AD. AD: Alzheimer’s disease; CT: Computed tomography; DMT: disease-modifying treatment; GP: general practitioner; MCI: Mild cognitive impairment; MRI: Magnetic resonance imaging; PMP: patient management program; Sympt: symptomatic treatment.

The early value model allows for the adoption of different scenario’s of PRS use within the clinical journey of AD, ranging from pre-diagnostic screening to identification of AD patients who might (not) benefit from treatment. For each of these scenario’s, the number of identified cases, the incremental and total cost (from a healthcare payer perspective) can be calculated. The early value model also allows to evaluate the impact of DMT on QALYs, life years won, and incremental costs in different scenarios where DMT effectivity, annual treatment costs, the cost of PRS, etc. can vary. However, since the current diagnostic pathway identifies only a small proportion of AD, it is unlikely that the use of PRS will soon be cost-effective, even if DMT becomes available.