Leveraging global resources to end the Alzheimer's pandemic

Now is the Time to Improve Cognitive Screening and Assessment for Clinical and Research Advancement

Alzheimer’s disease (AD) is the only cause of death ranked in the top ten globally without precise early diagnosis or effective means of prevention or treatment. Further, AD was identified as a pandemic [1] well before COVID-19 was dubbed a 21st century pandemic [2]. And now, with the realization of the prominent secondary impacts of pandemics, there is a growing, widespread recognition of the tremendous magnitude of the impending burden from AD in an aging world population in the coming decades [3]. This appreciation has amplified the growing and pressing need for a new, efficacious, and practical platform to detect and track cognitive decline, beginning in the preliminary (prodromal) phases of the disease, sensitively, accurately, effectively, reliably, efficiently, and remotely [4–7]. Moreover, the parallel necessity of clarifying and understanding risk factors, developing successful prevention strategies [8–17], and discovering and monitoring viable and effective treatments could all benefit from accurate and efficient screening and assessment platforms. Modern recognition of AD [18] as a common affliction of the elderly began in 1968 with a paper by Blessed, Tomlinson, & Roth [19] in which two tests, one a brief assessment of cognitive function and the other a measure of daily function, demonstrated impairment which was associated with the postmortem counts of neurofibrillary tangles, composed mainly of microtubule-associated protein-tau (tau), in the brain, though not to senile plaques, composed mainly of amyloid-β (Aβ). Even in more recent analyses, the tangles correspond with the severity of dementia more than the plaques [20, 21]. Since 1960, a plethora of cognitive tests, paper and pencil [22, 23], simple screening models [24], and computerized [25–27], have been developed to assess the dysfunction associated with AD. However, there has been limited application of Modern Test Theory, which includes Item Characteristic Curve Analysis, used in the technological development of such tools [28–31], along with widespread failure to understand the underlying AD pathological process to guide test development [32, 33]. The lack of such development has likely been a major contributor to the failure of the field to develop timely screening approaches for AD [34, 35], inaccurate assessment of the progression of AD [36], and even now, failure to find an effective approach to stopping AD.

Associations Between Genetic Variants in 19p13 and 19q13 Regions and Susceptibility to Alzheimer Disease: A Meta-Analysis

BACKGROUND

Alzheimer disease (AD) has become an epidemic within the growing elderly population and effective therapies of AD have not been discovered. Genetic factors accounted for over 70% of the incidence of AD and the disease-related polymorphisms are located on chromosome 19, which is one of several prominent chromosomes related to the development of AD. Many inconsistent associations between polymorphisms in ABCA7, CD33, and TOMM40 genes and the susceptibility to AD have been suggested by several independent studies.

MATERIAL/METHODS

A comprehensive literature search for studies involving the association between gene polymorphisms and AD was performed, and we finally selected 3 genes (4 polymorphisms) for the meta-analysis: ABCA7 (rs3764650), CD33 (rs3865444), and TOMM40 (rs157580, rs2075650).

RESULTS

A total of 25 articles investigating 3 genes (4 polymorphisms) were included in the meta-analysis. The pooled results of 4 polymorphisms were all significantly associated with the susceptibility to AD. The pooled effect of ABCA7 rs3764605 allele G was significantly associated with an increased the risk of AD (OR=1.20, 95% CI: 1.14-1.26, P value <0.001). Similarly, our evidence suggested that allele A of TOMM40 rs2075650 polymorphism was a risk factor for AD (OR=2.87, 95% CI: 2.46-3.34, P value <0.001). Alleles A of CD33 rs3865444 and A of TOMM40 rs157580 were both protective factors for AD onset (OR=0.94, 95% CI: 0.90-0.98, P value=0.003; OR=0.62, 95% CI: 0.57-0.66, P value <0.001). CONCLUSIONS" Results from the meta-analysis revealed that the pooled ABCA7 rs376465, CD33 rs3865444, TOMM40 rs157580, and rs2075650 variants were significantly associated with the susceptibility to AD. However, the association differed significantly between Asian and Caucasian groups for SNPs of CD33 rs3865444, TOMM40 rs157580, and rs2075650.

Prediction of population with Alzheimer's disease in the European Union using a system dynamics model

INTRODUCTION

Alzheimer's disease (AD) is a slowly progressing neurodegenerative brain disease with irreversible brain effects; it is the most common cause of dementia. With increasing age, the probability of suffering from AD increases. In this research, population growth of the European Union (EU) until the year 2080 and the number of patients with AD are modeled.

AIM

The aim of this research is to predict the spread of AD in the EU population until year 2080 using a computer simulation.

METHODS

For the simulation of the EU population and the occurrence of AD in this population, a system dynamics modeling approach has been used. System dynamics is a useful and effective method for the investigation of complex social systems. Over the past decades, its applicability has been demonstrated in a wide variety of applications. In this research, this method has been used to investigate the growth of the EU population and predict the number of patients with AD. The model has been calibrated on the population prediction data created by Eurostat.

RESULTS

Based on data from Eurostat, the EU population until year 2080 has been modeled. In 2013, the population of the EU was 508 million and the number of patients with AD was 7.5 million. Based on the prediction, in 2040, the population of the EU will be 524 million and the number of patients with AD will be 13.1 million. By the year 2080, the EU population will be 520 million and the number of patients with AD will be 13.7 million.

CONCLUSION

System dynamics modeling approach has been used for the prediction of the number of patients with AD in the EU population till the year 2080. These results can be used to determine the economic burden of the treatment of these patients. With different input data, the simulation can be used also for the different regions as well as for different noncontagious disease predictions.

Alzheimer's disease research in the context of the national plan to address Alzheimer's disease

In 2012, the first National Plan to Address Alzheimer's Disease in the United States (U.S.) was released, a component of the National Alzheimer's Project Act legislation. Since that time, there have been incremental increases in U.S. federal funding for Alzheimer's disease and related dementia research, particularly in the areas of biomarker discovery, genetic link and related biological underpinnings, and prevention studies for Alzheimer's. A central theme in each of these areas has been the emphasis of cross-sector collaboration and private-public partnerships between government, non-profit organizations and for-profit organizations. This paper will highlight multiple private-public partnerships supporting the advancement of Alzheimer's research in the context of the National Plan to Address Alzheimer's.

Association of CD33 polymorphism rs3865444 with Alzheimer's disease pathology and CD33 expression in human cerebral cortex

Recent findings identified the minor A allele present in the single-nucleotide polymorphism rs3865444 in the CD33 gene as being associated with the reduced risk of developing Alzheimer's disease (AD). CD33 (Siglec-3) is an immune function protein with anti-inflammatory signaling, cell adhesion, and endocytosis functions with sialic acid-modified proteins or lipids as ligands. Its involvement in AD pathologic mechanisms is still unclear; so, the goal of this study was to investigate if the rs3865444 polymorphism affects the development of AD pathology and the expression of CD33 messenger RNA (mRNA) and protein. For this study, we used DNA from 96 nondemented (ND) and 97 AD neuropathologically diagnosed cases to identify the different rs3865444 alleles and correlate with different measures of AD pathology. Using semiquantitative histologic measures of plaque and tangle pathology, we saw no significant differences between the different genotypes within these disease groups. However, increased expression of CD33 mRNA was associated with increasing AD pathology in temporal cortex brain samples. We also showed that cases with A/A alleles had reduced levels of CD33 protein in temporal cortex but increased levels of the microglia protein IBA-1. Using immunohistochemistry on temporal cortex sections, CD33 was selectively localized to microglia, with greater expression in activated microglia. The factors causing increased CD33 expression by microglia in brain are still unclear, although both genetic and disease factors are involved. Treatment of human microglia isolated from autopsy brains with amyloid-beta peptide and a range of other inflammatory activating agents resulted in reduced CD33 mRNA and protein levels.