Genomic profiling and diagnostic biomarkers in Alzheimer's disease

Beyond the amyloid cascade: An update of Alzheimer's disease pathophysiology

Alzheimer's disease (AD) is a multi-etiology disease. The biological system of AD is associated with multidomain genetic, molecular, cellular, and network brain dysfunctions, interacting with central and peripheral immunity. These dysfunctions have been primarily conceptualized according to the assumption that amyloid deposition in the brain, whether from a stochastic or a genetic accident, is the upstream pathological change. However, the arborescence of AD pathological changes suggests that a single amyloid pathway might be too restrictive or inconsistent with a cascading effect. In this review, we discuss the recent human studies of late-onset AD pathophysiology in an attempt to establish a general updated view focusing on the early stages. Several factors highlight heterogenous multi-cellular pathological changes in AD, which seem to work in a self-amplifying manner with amyloid and tau pathologies. Neuroinflammation has an increasing importance as a major pathological driver, and perhaps as a convergent biological basis of aging, genetic, lifestyle and environmental risk factors.

Alzheimer's Disease: Pathogenesis and Therapeutic Interventions

BACKGROUND

Alzheimer's Disease (AD) is the most common cause of dementia. Genetics, excessive exposure to environmental pollutants, as well as unhealthy lifestyle practices are often linked to the development of AD. No therapeutic approach has achieved complete success in treating AD; however, early detection and management with appropriate drugs are key to improving prognosis.

INTERVENTIONS

The pathogenesis of AD was extensively discussed in order to understand the reasons for the interventions suggested. The interventions reviewed include the use of different therapeutic agents and approaches, gene therapy, adherence to healthy dietary plans (Mediterranean diet, Okinawan diet and MIND diet), as well as the use of medicinal plants. The potential of nanotechnology as a multidisciplinary and interdisciplinary approach in the design of nano-formulations of AD drugs and the use of Superparamagnetic Iron Oxide Nanoparticles (SPIONs) as theranostic tools for early detection of Alzheimer's disease were also discussed.

Polygenic Hazard Score Associated Multimodal Brain Networks Along the Alzheimer's Disease Continuum

BACKGROUND

Late-onset Alzheimer's disease (AD) is a polygenic neurodegenerative disease. Identifying the neuroimaging phenotypes behind the genetic predisposition of AD is critical to the understanding of AD pathogenesis. Two major questions which previous studies have led to are: (1) should the general "polygenic hazard score" (PHS) be a good choice to identify the individual genetic risk for AD; and (2) should researchers also include inter-modality relationships in the analyses considering these may provide complementary information about the AD etiology.

METHODS

We collected 88 healthy controls, 77 patients with mild cognitive impairment (MCI), and 22 AD patients to simulate the AD continuum included from the ADNI database. PHS-guided multimodal fusion was used to investigate the impact of PHS on multimodal brain networks in AD-continuum by maximizing both inter-modality association and reference-modality correlation. Fractional amplitude of low frequency fluctuations, gray matter (GM) volume, and amyloid standard uptake value ratios were included as neuroimaging features. Eventually, the changes in neuroimaging features along AD continuum were investigated, and relationships between cognitive performance and identified PHS associated multimodal components were established.

RESULTS

We found that PHS was associated with multimodal brain networks, which showed different functional and structural impairments under increased amyloid deposits. Notably, along with AD progression, functional impairment occurred before GM atrophy, amyloid deposition started from the MCI stage and progressively increased throughout the disease continuum.

CONCLUSION

PHS is associated with multi-facets of brain impairments along the AD continuum, including cognitive dysfunction, pathological deposition, which might underpin the AD pathogenesis.

Association of coffee and genetic risk with incident dementia in middle-aged and elderly adults

BACKGROUND

Prior evidence suggests that coffee might be related to dementia, however, little is known about coffee and dementia in individuals with elevated genetic susceptibility for dementia. Additionally, most previous studies have focused on total coffee instead of examining coffee types separately.

METHODS

This study included 203,776 participants (60-73 years old) from the UK Biobank who were initially free of dementia. Polygenic risk scores for dementia were divided into quintile to stratify individuals into low (lowest quintile), intermediate (quintile 2-4), and high (highest quintile) genetic risk categories. Coffee intake was assessed at baseline and included total, instant, ground, and decaffeinated coffee.

RESULTS

During a median follow-up of 11.4 years, 4405 cases of dementia occurred (1856 Alzheimer's disease [AD], 1105 vascular dementia). Compared to non-coffee drinking, heavy instant coffee drinking (> 6 cups/day) and moderate decaffeinated coffee drinking (1-3 cups/day) were associated with a higher risk of dementia (hazard ratio [HR] 1.19-1.34) and AD (HR 1.41-1.51), while moderate ground coffee drinking was associated with a lower risk of dementia (HR, 0.78; P = 0.001) and vascular dementia (HR, 0.58; P < 0.001). Among participants at high genetic risk, heavy coffee drinking was associated with a 95% (HR; 1.95, 95% CI, 1.21-3.16) higher risk of AD than non-coffee drinking. We found an interaction between coffee and genetic risk in relation to AD (P = 0.038).

CONCLUSION

The association of dementia and coffee varied by coffee types. Heavy coffee consumption was associated with a higher risk of AD in individuals with high genetic risk for dementia.

Polygenic Risk Scores in Alzheimer's Disease: Current Applications and Future Directions

Genome-wide association studies have identified nearly 40 genome-wide significant single nucleotide polymorphisms (SNPs) which are associated with Alzheimer's Disease (AD). Due to the polygenicity of AD, polygenic risk scores (PRS) have shown high potential for AD risk prediction. PRSs have been shown to successfully discriminate between AD cases and controls achieving a prediction accuracy of up to 84% based on area under the receiver operating curve. The prediction accuracy in AD is higher compared with other complex genetic disorders. PRS can be restricted to SNPs which reside in biologically relevant gene-sets; the predictive value of these gene-sets in the general population is not as high as genome-wide PRS, but they may play an important role to identify mechanisms of disease development and inform biological experiments. Multiple methods are available to derive PRSs, such as selecting SNPs based on statistical evidence of association with the disease or using prior evidence for SNP selection. All methods have advantages, but PRS produced using different methodologies are often not comparable, and results should be interpreted with care. Similarly, this is true when PRS is based on different background populations. With the exponential growth in development of digital electronic devices it is easy to calculate an individual's disease risk using public databases. A major limitation for the utility of PRSs is that the risk score is sample and method dependent. Therefore, replicability and interpretability of PRS is an important issue. PRS can be used to determine the probability of developing disease which incorporates information about disease risk in the general population or in a specific AD risk group. It is essential to consult with genetic counselors to ensure genetic risk is communicated appropriately.

The multiplex model of the genetics of Alzheimer's disease

Genes play a strong role in Alzheimer's disease (AD), with late-onset AD showing heritability of 58-79% and early-onset AD showing over 90%. Genetic association provides a robust platform to build our understanding of the etiology of this complex disease. Over 50 loci are now implicated for AD, suggesting that AD is a disease of multiple components, as supported by pathway analyses (immunity, endocytosis, cholesterol transport, ubiquitination, amyloid-β and tau processing). Over 50% of late-onset AD heritability has been captured, allowing researchers to calculate the accumulation of AD genetic risk through polygenic risk scores. A polygenic risk score predicts disease with up to 90% accuracy and is an exciting tool in our research armory that could allow selection of those with high polygenic risk scores for clinical trials and precision medicine. It could also allow cellular modelling of the combined risk. Here we propose the multiplex model as a new perspective from which to understand AD. The multiplex model reflects the combination of some, or all, of these model components (genetic and environmental), in a tissue-specific manner, to trigger or sustain a disease cascade, which ultimately results in the cell and synaptic loss observed in AD.

Polygenic hazard score, amyloid deposition and Alzheimer's neurodegeneration

Mounting evidence indicates that the polygenic basis of late-onset Alzheimer's disease can be harnessed to identify individuals at greatest risk for cognitive decline. We have previously developed and validated a polygenic hazard score comprising of 31 single nucleotide polymorphisms for predicting Alzheimer's disease dementia age of onset. In this study, we examined whether polygenic hazard scores are associated with: (i) regional tracer uptake using amyloid PET; (ii) regional volume loss using longitudinal MRI; (iii) post-mortem regional amyloid-β protein and tau associated neurofibrillary tangles; and (iv) four common non-Alzheimer's pathologies. Even after accounting for APOE, we found a strong association between polygenic hazard scores and amyloid PET standard uptake volume ratio with the largest effects within frontal cortical regions in 980 older individuals across the disease spectrum, and longitudinal MRI volume loss within the entorhinal cortex in 607 older individuals across the disease spectrum. We also found that higher polygenic hazard scores were associated with greater rates of cognitive and clinical decline in 632 non-demented older individuals, even after controlling for APOE status, frontal amyloid PET and entorhinal cortex volume. In addition, the combined model that included polygenic hazard scores, frontal amyloid PET and entorhinal cortex volume resulted in a better fit compared to a model with only imaging markers. Neuropathologically, we found that polygenic hazard scores were associated with regional post-mortem amyloid load and neuronal neurofibrillary tangles, even after accounting for APOE, validating our imaging findings. Lastly, polygenic hazard scores were associated with Lewy body and cerebrovascular pathology. Beyond APOE, we show that in living subjects, polygenic hazard scores were associated with amyloid deposition and neurodegeneration in susceptible brain regions. Polygenic hazard scores may also be useful for the identification of individuals at the highest risk for developing multi-aetiological dementia.