Over 160 mutations on three genetic loci have been identified to be responsible for most cases of familial early-onset, autosomal-dominant AD (with onset before the age 65 years) – chromosome 14, presenilin-1; chromosome 1, presenilin-2; chromosome 21, APP. These early-onset forms are responsible for less than 1–2% of cases.
The discovery of these genetic loci linked to AD has led to important insights into the disease pathogenesis. The APP gene product from chromosome 21 is cleaved by three enzymes known as the α-, β- and γ-secretases to produce amyloidogenic Aβ or nonamyloidogenic breakdown products. The activity of these alternative pathways of APP catabolism, as well as the rate of APP expression, is controlled by genotype as well as environment.
The mutations of human presenilin genes PSEN1
, are linked to early onset AD. They are localized to chromosomes 1 and 14 [62
]. Although the function of human presenilins is currently not fully understood, their homologs are involved in Notch processing and signaling. These two proteins have redundant roles in cell fate [63
], cytoskeletal anchorage, cell division, early embryonic development [66
] and tumorigenesis [67
]. In addition, presenilins interact with centrosomes and kinetochores, thus giving them a significant role during chromosomal segregation and mitosis [66
Presenilin overexpression also leads to G1
arrest and this overexpression is potentiated by the PSEN2
(N141I) mutation. Bearing in mind that presenilin expression arrests cells in the G1
phase of the cell cycle, changes in the levels of cell-cycle inhibitory proteins p21, p27 and p53, and the cell-cycle regulatory proteins c-myc and pRb were examined in presenilin-transfected cell lysates. No increases or decreases were evident, suggesting that the presenilins mediate cell-cycle arrest by mechanisms other than simple changes in the steady-state levels of these cell-cycle-related proteins [68
What is interesting is that presenilin over-expression, in the environment of the adult neuron, leads to oxidative stress, loss of calcium balance and also to greater vulnerability to apoptosis [69
]. Indeed, AD-linked presenilins demonstrate greater apoptotic effects [71
]. Neurons that are vulnerable to AD have exited from G0
and entered G1
but may be blocked from progressing into the S phase at the G1
/S boundary by the presenilin (and possibly APP) mutations. A G1
blockage would allow cell-cycle regulatory proteins to accumulate and produce the stasis as is found in AD; hence, these mutations yield a contracted time course of the basic pathophysiology in AD. Furthermore, the presenilin and APP mutations may lead to the upregulation of CDKs, which can have dual roles in both cell-cycle regulation as well as signaling cell death [72
]. Indeed, the role of the cell-cycle inhibitory proteins, such as p16, p19 and p21 that accumulate in AD, can act to shunt possible apoptotic stimulation in early AD [72
While presenilins may have relevance to both apoptotic and developmental mechanisms due to the inter-relationship of cell death, growth and differentiation, they are not the only genetically determined AD-related factor associated with the cell cycle. The most important genetic risk factor for sporadic AD is the ApoE ε4 allele. The ApoE ε4 allele is associated with a two- to threefold increased risk of getting the disease when one copy is present, and when there are two copies the risk is increased as much as 12-times (the ApoE gene is codominant). However, the ApoE ε4 allele is not necessary or sufficient for AD, and perhaps 50% of the inherited risk of getting the disease is currently unknown. The strong association of the ApoE genotype to AD is a potent indicator of the importance of lipid metabolism and diet in the pathogenesis of the disease. Among the genetic markers, the ApoE gene has been widely examined owing to its well-documented role in AD and vascular diseases. A number of reports on human longevity demonstrate that ApoE ε4 allele frequency is lower in older age groups than younger or middle-aged subjects. ApoE is a polymorphic glycoprotein that plays an essential part in the binding to receptors for the uptake of chylomicrons, very-low-density lipoprotein remnants and of low-density lipoprotein. The three major isoforms are ApoE ε3 (Cys112/Arg158), ε4 (Arg112/Arg158) and ε2 (Cys112/Cys158). ApoE polymorphism is an essential determinant in the interindividual variations of lipids in healthy subjects, in various populations. Its influence can be significant on the efficacy of nutritional or therapeutic interventions. The allele ε4 appears to be associated with an increased risk of premature atherosclerosis. ApoE polymorphism contributes to the lipid disorders in diabetes and obesity.
Studies have demonstrated that genetics play a role in the extracellular deposition of amyloid. Individuals afflicted with AD carrying the ApoE
ε4 isoform have a greater number of Aβ plaques when compared with ApoE
ε3 carriers, and inheritance of an ApoE
ε4 allele increases the risk of AD when compared with ApoE
ε2 and ApoE
ε3 carriers [74
]. The relationship of ApoE to AD is based on a meta-analysis from population-based studies. Farrer et al.
examined the association between ApoE
genotype and AD in relation to age, gender and various ethnic and racial groups [75
]. A total of 40 research teams contributed data on ApoE
genotype, gender, age at disease onset and ethnic background for 5930 patients who met criteria for probable or definite AD and 8607 controls without dementia who were recruited from clinical, community and brain bank sources. In this study, odds ratios (OR) and 95% confidence intervals for AD, adjusted for age and study, and stratified by major ethnic group (Caucasian, African–American, Hispanic and Japanese) and source, were computed for ApoE
genotypes ε2/ε2, ε2/ε3, ε2/ε4, ε3/ε4 and ε4/ε4 relative to the ε3/ε3 group. The influence of age and sex on the OR for each genotype was assessed using logistic regression procedures. Among Caucasian subjects from clinic- or autopsy-based studies, the risk of AD was significantly increased for people with genotypes ε2/ε4 (OR: 2.6; 95% CI: 1.6–4.0), ε3/ε4 (OR: 3.2; 95% CI: 2.8–3.8) and ε4/ε4 (OR: 14.9; 95% CI: 10.8–20.6); whereas, the ORs were decreased for people with genotypes ε2/ε2 (OR: 0.6; 95% CI: 0.2–2.0) and ε2/ε3 (OR: 0.6; 95% CI: 0.5–0.8). The ApoE
ε4–AD association was weaker among African–Americans and Hispanics, but there was significant heterogeneity in ORs among studies of African–Americans. In addition, the ApoE
ε4–AD association in Japanese subjects was stronger than in Caucasian subjects (ε3/ε4, OR: 5.6; 95% CI: 3.9–8.0; ε4/ε4, OR: 33.1; 95% CI: 13.6–80.5). The ε2/ε3 genotype appears equally protective across ethnic groups. Among Caucasians, ApoE
genotype distributions are similar in groups of patients with AD whose diagnoses were determined clinically or by autopsy. In addition, the ApoE
ε4 effect is evident at all ages between 40 and 90 years but diminishes after 70 years of age, and the risk of AD associated with a given genotype varies between sexes. The general conclusion was that the ApoE
ε4 allele represents a major risk factor for AD in all ethnic groups studied, across all ages between 40 and 90 years, and in both men and women.
From a population perspective, it is possible to calculate the ‘attributable’ risk of a factor if one knows the frequency of the risk factor in the matched, nonaffected population and the relative risk or OR. For example, the attributable risk due to family history can be calculated as 26%. That is, in the group studied, 26% of all AD cases could be attributed to probable genetic factors. A similar calculation for ApoE
ε4 suggests that over 30% of the cases between 65 and 80 years of age may be attributed to the ε4 allele. The degree to which family history and ApoE
represent the same cases is unknown. If these risk factors are additive at the population level, family history/ApoE
ε4 would account for over 30% of the attributable risk for AD [76
There are still many uncertainties regarding the epidemiology of AD. It is crucial that these weaknesses are addressed, particularly in longitudinal studies carried out on community samples or well-defined cohorts, in which the history of exposure to putative risk factors is obtained in detail before the development of AD.
Recently, Potkin et al.
, using hippocampal atrophy as a quantitative phenotype in a genome-wide scan, identified candidate risk genes for sporadic AD [77
Researchers performed a genome-wide association study on 381 participants in the previously mentioned ADNI study. Samples were genotyped using the Illumina Human610-Quad BeadChip (San Diego, CA, USA). A total of 516,645 unique single-nucleotide polymorphisms (SNPs) were included in the analysis following quality-control measures. Two analyses were completed – a standard case–control analysis and a novel approach using hippocampal atrophy measured on MRI as an objectively defined, quantitative phenotype. A general linear model was applied to identify SNPs for which there was an interaction between the genotype and diagnosis on the quantitative trait. The case–control analysis identified ApoE
and a new risk gene, translocase of outer mitochondrial membrane (TOMM
risk alleles were approximately twice as frequent in AD subjects as controls. The quantitative trait analysis identified 21 genes or chromosomal areas with at least one SNP, which can be considered potential a ‘new’ candidate loci to explore in the etiology of sporadic AD. These candidates included EFNA5
, genes involved in the regulation of protein degradation, apoptosis, neuronal loss and neurodevelopment [77
Therefore, genetic factors may be useful as part of the group of parameters, with certain implication on risk, to form the complex multifactorial biomarker.