Fallacies in Neuroscience: The Alzheimer's Edition

Communicating scientific evidence: drugs for Alzheimer's disease as a case study

This paper reviews the scientific evidence on new anti-amyloid monoclonal antibodies for treating Alzheimer's disease as a case study for improving scientific evidence communication. We introduce five guidelines condensed from the biomedical evidence literature but adapted to the short format of science communication in e.g. journal opinion pieces and newspaper articles. Given the major importance and recent confusion regarding the discussed drugs, with certain disagreements seen e.g. between FDA and EMA, the suggested guidelines may be useful to clinicians discussing with their patients and to scientists communicating the evidence in balance. More generally, we hope that the guidelines may help us to improve communication of scientific evidence on complex topics in opinion pieces in the scientific literature, in advocacy, and in media appearances.

DeepDrug as an expert guided and AI driven drug repurposing methodology for selecting the lead combination of drugs for Alzheimer's disease

Alzheimer's Disease (AD) significantly aggravates human dignity and quality of life. While newly approved amyloid immunotherapy has been reported, effective AD drugs remain to be identified. Here, we propose a novel AI-driven drug-repurposing method, DeepDrug, to identify a lead combination of approved drugs to treat AD patients. DeepDrug advances drug-repurposing methodology in four aspects. Firstly, it incorporates expert knowledge to extend candidate targets to include long genes, immunological and aging pathways, and somatic mutation markers that are associated with AD. Secondly, it incorporates a signed directed heterogeneous biomedical graph encompassing a rich set of nodes and edges, and node/edge weighting to capture crucial pathways associated with AD. Thirdly, it encodes the weighted biomedical graph through a Graph Neural Network into a new embedding space to capture the granular relationships across different nodes. Fourthly, it systematically selects the high-order drug combinations via diminishing return-based thresholds. A five-drug lead combination, consisting of Tofacitinib, Niraparib, Baricitinib, Empagliflozin, and Doxercalciferol, has been selected from the top drug candidates based on DeepDrug scores to achieve the maximum synergistic effect. These five drugs target neuroinflammation, mitochondrial dysfunction, and glucose metabolism, which are all related to AD pathology. DeepDrug offers a novel AI-and-big-data, expert-guided mechanism for new drug combination discovery and drug-repurposing across AD and other neuro-degenerative diseases, with immediate clinical applications.

Lost in translation: Inconvenient truths on the utility of mouse models in Alzheimer's disease research

The recent, controversial approval of antibody-based treatments for Alzheimer's disease (AD) is fueling a heated debate on the molecular determinants of this condition. The discussion should also incorporate a critical revision of the limitations of preclinical mouse models in advancing our understanding of AD. We critically discuss the limitations of animal models, stressing the need for careful consideration of how experiments are designed and results interpreted. We identify the shortcomings of AD models to recapitulate the complexity of the human disease. We dissect these issues at the quantitative, qualitative, temporal, and context-dependent levels. We argue that these models are based on the oversimplistic assumptions proposed by the amyloid cascade hypothesis (ACH) of AD and fail to account for the multifactorial nature of the condition. By shedding light on the constraints of current experimental tools, this review aims to foster the development and implementation of more clinically relevant tools. While we do not rule out a role for preclinical models, we call for alternative approaches to be explored and, most importantly, for a re-evaluation of the ACH.

Alzheimer's disease and its treatment-yesterday, today, and tomorrow

Alois Alzheimer described the first patient with Alzheimer's disease (AD) in 1907 and today AD is the most frequently diagnosed of dementias. AD is a multi-factorial neurodegenerative disorder with familial, life style and comorbidity influences impacting a global population of more than 47 million with a projected escalation by 2050 to exceed 130 million. In the USA the AD demographic encompasses approximately six million individuals, expected to increase to surpass 13 million by 2050, and the antecedent phase of AD, recognized as mild cognitive impairment (MCI), involves nearly 12 million individuals. The economic outlay for the management of AD and AD-related cognitive decline is estimated at approximately 355 billion USD. In addition, the intensifying prevalence of AD cases in countries with modest to intermediate income countries further enhances the urgency for more therapeutically and cost-effective treatments and for improving the quality of life for patients and their families. This narrative review evaluates the pathophysiological basis of AD with an initial focus on the therapeutic efficacy and limitations of the existing drugs that provide symptomatic relief: acetylcholinesterase inhibitors (AChEI) donepezil, galantamine, rivastigmine, and the N-methyl-D-aspartate receptor (NMDA) receptor allosteric modulator, memantine. The hypothesis that amyloid-β (Aβ) and tau are appropriate targets for drugs and have the potential to halt the progress of AD is critically analyzed with a particular focus on clinical trial data with anti-Aβ monoclonal antibodies (MABs), namely, aducanumab, lecanemab and donanemab. This review challenges the dogma that targeting Aβ will benefit the majority of subjects with AD that the anti-Aβ MABs are unlikely to be the "magic bullet". A comparison of the benefits and disadvantages of the different classes of drugs forms the basis for determining new directions for research and alternative drug targets that are undergoing pre-clinical and clinical assessments. In addition, we discuss and stress the importance of the treatment of the co-morbidities, including hypertension, diabetes, obesity and depression that are known to increase the risk of developing AD.

Preclinical trials in Alzheimer's disease: Sample size and effect size for behavioural and neuropathological outcomes in 5xFAD mice

5xFAD transgenic (TG) mice are used widely in AD preclinical trials; however, data on sample sizes are largely unaddressed. We therefore performed estimates of sample sizes and effect sizes for typical behavioural and neuropathological outcome measures in TG 5xFAD mice, based upon data from single-sex (female) groups. Group-size estimates to detect normalisation of TG body weight to WT littermate levels at 5.5m of age were N = 9-15 depending upon algorithm. However, by 1 year of age, group sizes were small (N = 1 -<6), likely reflecting the large difference between genotypes at this age. To detect normalisation of TG open-field hyperactivity to WT levels at 13-14m, group sizes were also small (N = 6-8). Cued learning in the Morris water maze (MWM) was normal in Young TG mice (5m of age). Mild deficits were noted during MWM spatial learning and memory. MWM reversal learning and memory revealed greater impairment, and groups of up to 22 TG mice were estimated to detect normalisation to WT performance. In contrast, Aged TG mice (tested between 13 and 14m) failed to complete the visual learning (non-spatial) phase of MWM learning, likely due to a failure to recognise the platform as an escape. Estimates of group size to detect normalisation of this severe impairment were small (N = 6-9, depending upon algorithm). Other cognitive tests including spontaneous and forced alternation and novel-object recognition either failed to reveal deficits in TG mice or deficits were negligible. For neuropathological outcomes, plaque load, astrocytosis and microgliosis in frontal cortex and hippocampus were quantified in TG mice aged 2m, 4m and 6m. Sample-size estimates were ≤9 to detect the equivalent of a reduction in plaque load to the level of 2m-old TG mice or the equivalent of normalisation of neuroinflammation outcomes. However, for a smaller effect size of 30%, larger groups of up to 21 mice were estimated. In light of published guidelines on preclinical trial design, these data may be used to provide provisional sample sizes and optimise preclinical trials in 5xFAD TG mice.

Apolipoprotein E ε4 disrupts oligodendrocyte differentiation by interfering with astrocyte-derived lipid transport

Carriers of the APOE4 (apolipoprotein E ε4) variant of the APOE gene are subject to several age-related health risks, including Alzheimer's disease (AD). The deficient lipid and cholesterol transport capabilities of the APOE4 protein are one reason for the altered risk profile. In particular, APOE4 carriers are at elevated risk for sporadic AD. While deposits o misfolded proteins are present in the AD brain, white matter (WM) myelin is also disturbed. As myelin is a lipid- and cholesterol-rich structure, the connection to APOE makes considerable biological sense. To explore the APOE-WM connection, we have analyzed the impact of human APOE4 on oligodendrocytes (OLs) of the mouse both in vivo and in vitro. We find that APOE proteins is enriched in astrocytes but sparse in OL. In human APOE4 (hAPOE4) knock-in mice, myelin lipid content is increased but the density of major myelin proteins (MBP, MAG, and PLP) is largely unchanged. We also find an unexpected but significant reduction of cell density of the OL lineage (Olig2+ ) and an abnormal accumulation of OL precursors (Nkx 2.2+ ), suggesting a disruption of OL differentiation. Gene ontology analysis of an existing RNA-seq dataset confirms a robust transcriptional response to the altered chemistry of the hAPOE4 mouse brain. In culture, the uptake of astrocyte-derived APOE during Lovastatin-mediated depletion of cholesterol synthesis is sufficient to sustain OL differentiation. While endogenous hAPOE protein isoforms have no effects on OL development, exogenous hAPOE4 abolishes the ability of very low-density lipoprotein to restore myelination in Apoe-deficient, cholesterol-depleted OL. Our data suggest that APOE4 impairs myelination in the aging brain by interrupting the delivery of astrocyte-derived lipids to the oligodendrocytes. We propose that high myelin turnover and OL exhaustion found in APOE4 carriers is a likely explanation for the APOE-dependent myelin phenotypes of the AD brain.

The Case for a Novel Therapeutic Approach to Dementia: Small Molecule Hepatocyte Growth Factor (HGF/MET) Positive Modulators

An estimated 6.5 million Americans aged 65 years or older have Alzheimer's disease (AD), which will grow to 13.8 million Americans by 2060. Despite the growing burden of dementia, no fundamental change in drug development for AD has been seen in > 20 years. Currently approved drugs for AD produce only modest symptomatic improvements in cognition with small effect sizes. A growing mismatch exists between the urgent need to develop effective drugs for symptomatic AD and the largely failed search for disease modification. The failure rate of clinical trials in AD is high overall, and in particular for disease-modifying therapies. Research efforts in AD have focused predominantly on amyloid-β and tau pathologies, but limiting clinical research to these "classical hallmarks" of the disease does not address the most urgent patient, caregiver, or societal needs. Rather, clinical research should consider the complex pathophysiology of AD. Innovative approaches are needed that provide outside-the-box thinking, and re-imagine trial design, interventions, and outcomes as well as progress in proteomics and fluid biomarker analytics for both diagnostics and disease monitoring. A new approach offering a highly specific, yet multi-pronged intervention that exerts positive modulation on the HGF/MET neurotrophic system is currently being tested in mid-to-late-stage clinical trials in mild to moderate AD. Findings from such trials may provide data to support novel approaches for development of innovative drugs for treating AD at various disease stages, including among patients already symptomatic, and may offer benefits for other neurodegenerative diseases.

Demand Coupling Drives Neurodegeneration: A Model of Age-Related Cognitive Decline and Dementia

The societal burden of Alzheimer's Disease (AD) and other major forms of dementia continues to grow, and multiple pharmacological agents directed towards modifying the pathological "hallmarks" of AD have yielded disappointing results. Though efforts continue towards broadening and deepening our knowledge and understanding of the mechanistic and neuropathological underpinnings of AD, our previous failures motivate a re-examination of how we conceptualize AD pathology and progression. In addition to not yielding effective treatments, the phenotypically heterogeneous biological processes that have been the primary area of focus to date have not been adequately shown to be necessary or sufficient to explain the risk and progression of AD. On the other hand, a growing body of evidence indicates that lifestyle and environment represent the ultimate level of causation for AD and age-related cognitive decline. Specifically, the decline in cognitive demands over the lifespan plays a central role in driving the structural and functional deteriorations of the brain. In the absence of adequate cognitive stimulus, physiological demand-function coupling leads to downregulation of growth, repair, and homeostatic processes, resulting in deteriorating brain tissue health, function, and capacity. In this setting, the heterogeneity of associated neuropathological tissue hallmarks then occurs as a consequence of an individual's genetic and environmental background and are best considered downstream markers of the disease process rather than specific targets for direct intervention. In this manuscript we outline the evidence for a demand-driven model of age-related cognitive decline and dementia and why it mandates a holistic approach to dementia treatment and prevention that incorporates the primary upstream role of cognitive demand.