Health economics and the value of therapy in Alzheimer's disease

Telomere Length, Brain Imaging-Derived Phenotypes, and Alzheimer's Disease: Mendelian Randomization Analysis

Previous studies have reported a correlation between telomere length (TL) and Alzheimer's disease (AD); however, the specific biological mechanisms supporting this association remain unclear. We used two-sample Mendelian randomization (MR) to systematically explore the putative causal relationships between TL, brain imaging-derived phenotypes (IDPs), and AD, while further evaluating the mediating role of IDPs using both two-step MR and multivariable MR. In addition, we utilized several independent validation cohorts to repeat the analysis, further strengthening our inferences. The MR analysis showed that a longer TL was causally associated with a lower risk for AD (OR, 0.84; 95% CI, 0.75 to 0.93; P = 0.001). In addition, the subsequent two-step MR results indicate that nine brain IDPs partially mediate the effect of TL on AD. The inverse association of genetically predicted TL with AD was attenuated after adjusting for these IDPs in multivariable MR. Our study provides further evidence for the causal relationship between TL and AD, with IDPs potentially partially mediating this association. Therefore, telomere biology may be a potential pathway involved in AD development, and identifying the important role of telomeres can draw more attention to the development of telomere-related diagnostics, treatments, and AD therapies.

Multi-omics analysis of druggable genes to facilitate Alzheimer's disease therapy: A multi-cohort machine learning study

BACKGROUND

The swift rise in the prevalence of Alzheimer's disease (AD) alongside its significant societal and economic impact has created a pressing demand for effective interventions and treatments. However, there are no available treatments that can modify the progression of the disease.

METHODS

Eight AD brain tissues datasets and three blood datasets were obtained. Consensus clustering was utilized as a method to discern the various subtypes of AD. Then, module genes were screened using weighted correlation network analysis (WGCNA). Furthermore, screening hub genes was conducted through machine-learning analyses. Finally, A comprehensive analysis using a systematic approach to druggable genome-wide Mendelian randomization (MR) was conducted.

RESULTS

Two AD subclasses were identified, namely cluster.A and cluster.B. The levels of gamma secretase activity, beta secretase activity, and amyloid-beta 42 were found to be significantly elevated in patients classified within cluster A when compared to those in cluster B. Furthermore, by utilizing the differentially expressed genes shared among these clusters, along with identifying druggable genes and applying WGCNA to these subtypes, we were able to develop a scoring system referred to as DG.score. This scoring system has demonstrated remarkable predictive capability for AD when evaluated against multiple datasets. Besides, A total of 30 distinct genes that may serve as potential drug targets for AD were identified across at least one of the datasets investigated, whether derived from brain samples or blood analyses. Among the identified genes, three specific candidates that are considered druggable (LIMK2, MAPK8, and NDUFV2) demonstrated significant expression levels in both blood and brain tissues. Furthermore, our research also revealed a potential association between the levels of LIMK2 and concentrations of CSF Aβ (OR 1.526 (1.155-2.018)), CSF p-tau (OR 1.106 (1.024-01.196)), and hippocampal size (OR 0.831 (0.702-0.948)).

CONCLUSIONS

This study provides a notable advancement to the existing literature by offering genetic evidence that underscores the potential therapeutic advantages of focusing on the druggable gene LIMK2 in the treatment of AD. This insight not only contributes to our understanding of AD but also guides future drug discovery efforts.

Systematic druggable genome-wide Mendelian randomisation identifies therapeutic targets for Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is the leading cause of dementia. Currently, there are no effective disease-modifying treatments for AD. Mendelian randomisation (MR) has been widely used to repurpose licensed drugs and discover novel therapeutic targets. Thus, we aimed to identify novel therapeutic targets for AD and analyse their pathophysiological mechanisms and potential side effects.

METHODS

A two-sample MR integrating the identified druggable genes was performed to estimate the causal effects of blood and brain druggable expression quantitative trait loci (eQTLs) on AD. A repeat study was conducted using different blood and brain eQTL data sources to validate the identified genes. Using AD markers with available genome-wide association studies data, we evaluated the causal relationship between established AD markers to explore possible mechanisms. Finally, the potential side effects of the druggable genes for AD treatment were assessed using a phenome-wide MR.

RESULTS

Overall, 5883 unique druggable genes were aggregated; 33 unique potential druggable genes for AD were identified in at least one dataset (brain or blood), and 5 were validated in a different dataset. Among them, three prior druggable genes (epoxide hydrolase 2 (EPHX2), SERPINB1 and SIGLEC11) reached significant levels in both blood and brain tissues. EPHX2 may mediate the pathogenesis of AD by affecting the entire hippocampal volume. Further phenome-wide MR analysis revealed no potential side effects of treatments targeting EPHX2, SERPINB1 or SIGLEC11.

CONCLUSIONS

This study provides genetic evidence supporting the potential therapeutic benefits of targeting the three druggable genes for AD treatment, which will be useful for prioritising AD drug development.

A qualitative exploration of the content and face validity of preference-based measures within the context of dementia

BACKGROUND

Assessing the cost-effectiveness of interventions for people with dementia, based on cost per quality-adjusted life years (QALYs) gained, requires that the measures used to derive QALYs are preference-based whilst also being valid, feasible to use, comprehensible and acceptable for people with dementia. The aim of this study was to assess the content and face validity of six preference-based measures (PBMs) within the context of dementia.

METHODS

Qualitative focus groups and interviews were conducted with community-dwelling individuals with mild dementia and carers of people with dementia. After exploring participants' understanding of 'quality of life' (QoL), six PBMs were assessed for content and face validity: two measures assessing health-related QoL (EQ-5D-5L and AQoL-8D); two covering broader aspects of capability wellbeing and social care-related QoL (ICECAP-O and ASCOT); and two dementia-specific QoL measures (DEMQOL-U and AD-5D). A random mix of one health-related QoL measure, one wellbeing measure, and one dementia-specific measure was explored in each session. All sessions were audiotaped and transcribed verbatim. Data were analysed thematically.

RESULTS

Nine individuals with mild dementia and 17 carers of people with dementia participated across 4 focus groups and 10 interviews. Participants perceived 9 broad QoL domains as relevant to them: Activity, Autonomy, Cognition, Communication, Coping, Emotions, End-of-Life, Physical Functioning, and Relationships. These domains had limited overlap with the content of the six PBMs. Assessment of face validity was summarized into eight themes: (1) ambiguous questions, (2) double -barrelled questions, (3) difficult/abstract questions, (4) judgemental/confronting questions, (5) lack of relevance and comprehensiveness, (6) response options, (7) layout/format and (8) proxy-response. There was no clear preference for one of the six measures explored; participants identified advantages and disadvantages across all measures. Although particularly designed for individuals with dementia, dementia-specific QoL measures were not always favoured over non-specific measures.

CONCLUSION

Given the shortcomings of PBMs identified in this study, further empirical comparative analyses are necessary to guide the selection of PBMs for future dementia research.

Selenium status in elderly: relation to cognitive decline

Studies show that decreased antioxidant system is related to cognitive decline. Thus we aimed to measure selenium (Se) status in Alzheimer's disease (AD) and mild cognitive impairment (MCI) elderly and compared them with a control group (CG). 27 AD, 17 MCI and 28 control elderly were evaluated. Se concentration was determined in plasma and erythrocyte by using hydride generation atomic absorption spectroscopy. Erythrocyte Se concentration in AD group was lower than CG (43.73±23.02μg/L and 79.15±46.37μg/L; p=0.001), but not statistically different from MCI group (63.97±18.26μg/L; p=0.156). AD group exhibited the lowest plasma Se level (34.49±19.94μg/L) when compared to MCI (61.36±16.08μg/L; p=0.000) and to CG (50.99±21.06μg/L; p=0.010). It is observed that erythrocyte Se decreases as cognition function does. Since erythrocyte reflects longer-term nutritional status, the data point to the importance of the relation between Se exposure and cognitive function. Our findings suggest that the deficiency of Se may contribute to cognitive decline among aging people.

Novel approaches to incorporating pharmacoeconomic studies into phase III clinical trials for Alzheimer's disease

The societal and individual costs of Alzheimer's disease are significant, worldwide. As the world ages, these costs are increasing rapidly, while health systems face finite budgets. As a result, many regulators and payers will require or at least consider phase III cost-effectiveness data (in addition to safety and efficacy data) for drug approval and reimbursement, increasing the risks and costs of drug development. Incorporating pharmacoeconomic studies in phase III clinical trials for Alzheimer's disease presents a number of challenges. We propose several specific suggestions to improve the design of pharmacoeconomic studies in phase III clinical trials. We propose that acute episodes of care are key outcome measures for pharmacoeconomic studies. To improve the possibility of detecting a pharmacoeconomic impact in phase III, we suggest several strategies including; study designs for enrichment of pharmacoeconomic outcomes that include co-morbidity of patients; reducing variability of care that can affect pharmacoeconomic outcomes through standardized care management; employing administrative claims data to better capture meaningful pharmacoeconomic data; and extending clinical trials in open label follow-up periods in which pharmacoeconomic data are captured electronically by administrative claims. Specific aspects of power analysis for pharmacoeconomic studies are presented. The particular pharmacoeconomic challenges caused by the use of biomarkers in clinical trials, the increasing use of multinational studies, and the pharmacoeconomic challenges presented by biologicals in development for Alzheimer's disease are discussed. In summary, since we are entering an era in which pharmacoeconomic studies will be essential in drug development for supporting regulatory approval, payor reimbursement and integration of new therapies into clinical care, we must consider the design and incorporation of pharmacoeconomic studies in phase III clinical trials more seriously and more creatively.