Introduction
Alzheimer’s disease (AD) is a neurodegenerative disorder and represents the most common form of dementia. At present, an estimated 50% of million people worldwide suffer from some form of dementia. AD is characterized by chronic and acquired memory impairment and cognitive deficits in domains, such as language, spatio-temporal orientation, and executive capacity.
Histopathologically, AD is characterized by two pathognomonic hallmarks (Figure 1):
- The intracellular deposition of abnormally phosphorylated Tau protein promotes the formation of neurofibrillary tangles (NFTs) in the cerebral cortex and subcortical gray matter (Figure 1a).
- Extracellular aggregates of Amyloid-beta peptide (Aβ) fibrils in the form of neuritic plaques (NPs) (Figure 1b).
Figure 1. Histopathological hallmarks of Alzheimer’s disease. (a) Triple immunofluorescence showing a neurofibrillary tangle (conformational change: green channel; C-terminal tail: red channel; N-terminal of intact tau protein: blue channel). (b) Immunofluorescence showing an amyloid plaque (Aβ 1-40: green channel). Photomicrographs at 100X, calibration bar = 10 µm. Adapted from source.
It has been postulated that endogenous “damage signals”, such as Aβ oligomers, could cause the activation of microglial cells with the consequent release of proinflammatory cytokines, which would trigger signaling cascades in neurons causing hyperphosphorylation and the aggregation of Tau protein. This protein is released when neurons die, triggering microglial cell activation, and therefore becomes a cyclic pathological process that culminates in neurodegeneration. Thus, both NPs and NFTs are involved in several neuronal processes and ultimately trigger neuronal death, synaptic alteration, mitochondrial dysfunction, oxidative stress, neuroinflammation, alterations in the permeability of the blood-brain barrier (BBB), and neurovascular unit dysfunction.
Two forms of AD have been described: familial and sporadic. The familial presentation is autosomal dominant, early onset (EOAD) in individuals under 65 years of age, and characterized by the alteration of specific genes, like the presenilin 1 gene (PSEN1), identified in up to 70% of cases with familial AD, the presenilin 2 gene (PSEN1) and the Amyloid precursor protein gene (APP). The sporadic presentation is late onset (LOAD) and happens in individuals older than 65 years of age. The main risk factor is assessed to be age, but sporadic AD is a complex disorder, and other risk factors have been identified, such as traumatic brain injury, depression, environmental pollution, physical inactivity, social isolation, metabolic syndrome, and genetic susceptibility, mainly mutations in the e4 allele of apolipoprotein E (APOE), considering a heritability of up to 60-80%.
Multiple hypotheses have been developed to explain the growth of AD, including the amyloidogenic cascade, tauopathy, vascular therapy, oxidative stress, and bacterial infections theory among others. However, due to the intricate complexity of the human brain and partial characterization of the polymorphisms associated with AD, the molecular mechanisms involved in each of these hypotheses and their correlation with the genetic load or predisposition of each individual are poorly understood.
Thus, characterizing the genetic risk factors in AD is a priority to understand the several neuropathological events involved.Recent, genome-wide association studies (GWAS) have allowed the identification of several genes associated with AD, however, the relationship of many loci to the risk of developing AD has not been clarified.
The Four Classical Genes Associated with Alzheimer’s disease
AD is a complex and multigenic disease. Familial AD is associated with the genes that encode PSEN1, PSEN2, and APP, which interfere with the physiological processing of the Aβ peptide.
More than 300 mutations of the PSEN1 gene and 80 mutations of the PSEN2 gene have been specified. These mutations have been related to the genesis of familial AD. The spectrum of PSEN genes includes missense mutations, small insertions, deletions, and genomic deletions, specifically in PSEN1. PSEN1 mutations cause the most severe forms of AD with complete penetrance and the onset of disease can occur as early as 25 years of age. Missense mutations in the PSEN2 gene may indicate incomplete penetrance, and carriers show an older age of disease onset than those with PSEN1 mutations.
The APP gene encoding this protein consists of a total of 17 exons and encoded several isoforms resulting from the alternative splicing of exons 7 and 8, three of which are relevant to AD and are expressed only in the Central nervous system. The physiological isoform, or ApoE-ε3 is present in 50% to 90% of the healthy population.
Unraveling the Genetics of Alzheimer’s disease: What Is New?
A wide variety of genes in the development of AD have been identified as possible early biomarkers and therapeutic targets. Together, these genes could explain up to 70% of LOAD cases and point to new disease-related phenomena such as the association of genes with multiple neuropathological events.
Figure 2. Schematic representation of multiple genes and their association with neuropathological events in AD. The four classical genes associated with familial AD are in the blue box, whereas other novel genes related to sporadic AD are in the red boxes. Word color-coding: red: increased production/aggregation of Aβ or tau; green: alteration in the clearance of Aβ or tau; blue: Aβ- or tau-mediated neuronal damage; purple: Tau phosphorylation. Furthermore, the respective associations with neuropathological mechanisms are indicated in yellow boxes. Abbreviations: AICD: amyloid precursor protein intracellular domain; APP: amyloid precursor protein; BACE1: β secretase; BBB: blood–brain barrier; CTF: C-terminal fragment; sAPP-β: soluble amyloid precursor protein β. Adapted from source.
According to the amyloid hypothesis, a wide variety of genes identified are involved in pathological Aβ processing such as the disintegrin and metalloproteinase domain-containing protein 10, which is the most important α-secretase in the brain that could cause an increase in the Aβ42/Aβ40 ratio. However, pathological Aβ processing is not the only mechanism involved, and it does not explain the complexity of AD. More than 29 risk loci have been identified, as well as more than 215 potential causative genes. These genes are strongly expressed in immune-related tissues and cell types, including the spleen, liver, and microglia cells. The neuroimmunomodulation hypothesis has been postulated, which suggests that the appearance of AD is a consequence of the response of glial cells to signals of damage that trigger a neuroinflammatory response and the subsequent dysregulation of protein kinases and phosphatases that promote Tau protein hyperphosphorylation and oligomerization. Tau oligomers and filaments released after neuronal apoptosis are in turn capable of reactivating microglial cells, thus promoting a deleterious molecular signaling cycle responsible for the neurodegeneration observed in AD and other tauopathies. Supporting this hypothesis, several genes involved in the immune response have been specified. For example, the transcription factor PU.1 (SPI1), involved in the expression of immune-related genes in myeloid cells, could contribute to AD by regulating key pathways associated with the immune response and altering the epigenetic landscape. Furthermore, the myeloid cell surface antigen CD33, expressed on the surface of microglial cells, is involved in the negative regulation of cytokine production and, therefore, could play a role in AD by modulating microglial activation.
Similar to the immunomodulation hypothesis, there is the infectious one, which could also explain the pathological processing of both Tau and Aβ. The infectious hypothesis proposes that a pathogen triggers an inflammatory response and promotes the aggregation of Tau and Ab, which in turn cause further inflammation. The paired immunoglobulin-like type 2 receptor alpha (PILRA), an inhibitory immunoglobulin receptor involved in the regulation of the immune system and a co-receptor of herpes simplex virus type 1 (HSV-1), is related to dysfunctions in microglial activation and may represent a link to infectious factors that have been connected to AD. This is extremely important since a close relationship is established between infectious diseases and AD and, therefore, represents an opportunity both for diagnostic and therapeutic strategies. In addition, the pathological processing of Tau and Aβ, such as other neuropathological events, could be triggered by some genes involved in metabolic disorders, mainly lipid/atherosclerosis pathways and insulin resistance.
Impact of GWAS on Understanding Alzheimer’s Disease
Multiple genetic studies have tracked most of the genes that conform to the human genome. These genetic studies are known as Genome-wide Association Studies (GWAS) and their objective is to associate certain genes with multiple pathologies or disorders. Multiple analyses have been performed with GWAS technology, demonstrating many possible genes associated with LOAD. Targeted genetic approaches and next-generation sequencing studies have also specified several low-frequency genes that are associated with a relatively high risk of developing AD, therefore providing insight into the pathogenesis. GWAS have associated more than 40 risk alleles with AD, identifying variants that trigger neurodegeneration, such as lipid metabolism, innate immunity, inflammation, and endosomal vesicle recycling. In particular, GWAS has also allowed us to specify those genes related to the development of both EOAD and LOAD. Since genetic variants have been evidenced between different ethnic groups, researchers must perform GWAS in AD across ethnicities and identify polymorphisms associated with each of them.
On the other hand, GWAS has allowed the identification of genetic components that are not related to the neuropathological processes, affecting only cognitive reserve, which refers to individual differences in susceptibility to age-related brain changes or AD-related pathology. Growing evidence suggests that, among cognitively healthy patients with a genetic risk of developing AD, women exhibit better global cognition than men. This event is maintained during the early stages of the disease, despite showing increased Tau pathology, hippocampal atrophy, and metabolic dysfunction. This demonstrates that although women have greater resilience to the disease, there are still unidentified factors that cause them to have a greater risk of developing the disease.
Interestingly, GWAS in AD have transitioned from identifying only a couple of novel genes to identifying a large number of previously unreported associations. This is probably due to an increase in the size of the samples and the diversification of the populations studied. Thus, future GWAS must adopt a better definition of cases and controls, as well as designs based on the comparison of ethnic groups, sex, and age, since there may be various environmental, exposure, and genetic factors that modify the risk load conferred by each locus. Likewise, these associations should be replicated and validated in multiple populations and followed by a downstream functional dissection to benefit knowledge of pathophysiology.
DNA methylation, an epigenetic modification, plays an important role in regulating gene expression and thus in a wide range of diseases and biological processes. However, GWAS present certain limitations:
- They eventually involve the entire genome in disease predisposition
- The identification of multiple loci without a clear mechanism can be uninformative and cause confusion with respect to AD
- The vast majority of GWAS focus on the European population and lack population stratification
- The scarce data can lead to the fact that the heritability of diseases is not fully explained and therefore fail to detect epistasis in humans, which is the main component of the genetic architecture of complex traits.
Despite these limitations, GWAS have multiple benefits given their diverse clinical applications and allow the identification of new biological mechanisms as well as ethnic variations in the health-disease process. On the other hand, it should be noted that genetics is only one factor that can impact the treatment of AD, since other factors, such as age, general state of health, and stage of the disease, can also influence the efficacy of the treatment. Similarly, the use of more general approaches to prevent or delay the onset of AD, such as lifestyle interventions or changes to prevent or delay the onset of AD, could be useful: maintaining a healthy diet, engaging in regular physical activity, and participating in cognitively stimulating activities.
Conclusion
In conclusion, this review indicates the significant role that genetics plays in the development of not only EOAD but also LOAD. The GWAS and other genetic examinations will promote the identification of possible biomarkers that allow an early diagnosis of the disease or the risk of developing it in susceptible people, as well as its relationship with other pathological processes