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Genetics of Alzheimer disease

Genetics of Alzheimer disease
Authors:
Rick Sherva, PhD
Neil W Kowall, MD
Section Editors:
Steven T DeKosky, MD, FAAN, FACP, FANA
Benjamin A Raby, MD, MPH
Deputy Editor:
Janet L Wilterdink, MD
Literature review current through: Dec 2022. | This topic last updated: May 19, 2022.

INTRODUCTION — Alzheimer disease (AD) is the most common form of dementia, with an estimated lifetime risk of nearly 1 in 5 for women and 1 in 10 for men. AD is highly heritable, even in so-called sporadic cases. The genetic basis for AD is best understood in the early-onset form, which accounts for less than 1 percent of cases and typically follows an autosomal dominant inheritance pattern related to mutations in genes that alter amyloid-beta (Aβ) protein production, aggregation, or clearance. The genetic basis of late-onset AD (LOAD) is more complex, with susceptibility likely conferred by a variety of more common but less penetrant genetic factors, such as apolipoprotein E (APOE) alleles, interacting with environmental and epigenetic influences.

This topic will review the genetic basis of AD in both early-onset and late-onset forms. Other risk factors for dementia and the clinical manifestations and diagnosis of AD are discussed separately. (See "Risk factors for cognitive decline and dementia" and "Clinical features and diagnosis of Alzheimer disease".)

APPROACHES TO GENE DISCOVERY — The genetic contribution to AD risk remains poorly understood despite major advances in the 1990s in the identification of three genes that cause early-onset familial AD and one genetic risk factor for late-onset AD (LOAD). There have been three main strategies employed to identify genetic factors that predispose to the development of AD: linkage analysis, candidate gene studies, and genome-wide association studies (GWAS). General principles of genetic variation and genetic association studies are discussed separately. (See "Genetic association and GWAS studies: Principles and applications" and "Basic genetics concepts: DNA regulation and gene expression", section on 'Genetic variation'.)

Linkage analysis — The first progress in understanding the genetic basis of AD resulted from studies of families displaying autosomal dominant inheritance of the disorder. These studies used linkage-based methodology, in which a relatively small number (on the order of several hundred) of nonfunctional genetic markers spaced throughout the genome are genotyped in order to determine whether a given section of chromosome was transmitted from parents to their offspring. By comparing this information with disease status, the genes responsible can be mapped to relatively large chromosomal regions. Early AD studies used linkage analysis to identify culprit regions on chromosomes 1, 14, and 21, eventually leading to discovery of the three known causative AD genes [1-4]. (See 'Early-onset Alzheimer disease' below.)

Whereas linkage analysis has been very successful in identifying monogenic traits in early-onset familial AD, it has had much more limited success in LOAD, which is more likely to be a complex trait. (See 'Challenges' below.)

Candidate gene studies — Candidate gene studies can include family members or unrelated individuals and require some degree of foreknowledge about the genes and pathways involved in AD. In this approach, one or a small number of known genetic variants, called single nucleotide polymorphisms (SNPs), are genotyped and compared in cases and controls. (See "Genetic association and GWAS studies: Principles and applications".)

Drawing on clues about AD pathogenesis emerging from cell biology and neurochemistry, numerous candidate gene association studies have been conducted in AD. Studies typically focus on loci with potential effects on amyloid-beta (Aβ) production, aggregation, or clearance (ie, a functional hypothesis) or on loci suspected to be important based on prior linkage studies (ie, a positional hypothesis).

The primary success of the candidate gene approach in LOAD has been the identification of apolipoprotein E (APOE) risk alleles (whose location was identified originally through linkage studies). Subsequently, nearly 700 other candidate genes have been investigated based on functional hypotheses, with mostly inconsistent results. (See 'Apolipoprotein E' below and 'Other candidate genes' below.)

As exome and whole-genome sequencing becomes more feasible and cost efficient, the candidate gene approach may yield further insights into the heritability of LOAD.

Genome-wide association studies — In the first decade of the 21st century, microarray technology revolutionized genetics research, making it possible to test hundreds of thousands of candidate genes simultaneously. Such GWAS allow for large-scale, largely hypothesis-free inquiries aimed at identifying novel genetic risk factors for AD.

In AD, multiple GWAS have been performed to date, largely confirming the importance of APOE and implicating a growing number of other potential loci (see 'Other candidate genes' below). To date, information from over 1375 candidate gene and genome-wide association studies, implicating nearly 700 candidate genes, has been curated by the Alzheimer Disease Forum in the AlzGene database [5].

EARLY-ONSET ALZHEIMER DISEASE — The first progress in understanding the genetic basis of AD resulted from studies of families displaying autosomal dominant inheritance of the disorder. Families with autosomal dominant AD are those with at least three affected individuals in two or more generations, with two of the individuals being first-degree relatives of the third. In these families, affected individuals typically develop symptoms of AD between the ages of 30 and 60 years. Most, but not all, families with early-onset AD show an autosomal dominant pattern of inheritance. The pattern may be masked in small families or those with premature deaths (ie, prior to the anticipated age of clinical symptom onset) from unrelated causes.

Early studies in families with autosomal dominant AD used linkage-based methodology to isolate relatively large culprit regions on chromosomes 1 [1], 14 [2,3], and 21 [4]. This facilitated the eventual identification of causative mutations in the three genes: amyloid precursor protein (APP) [6], presenilin 1 (PSEN1) [7], and presenilin 2 (PSEN2) [8,9]. Although these mutations collectively account for less than 1 percent of all AD cases and 60 to 70 percent of early-onset AD [10-12], their discovery substantially increased the understanding of basic AD pathophysiology.

Amyloid precursor protein — The APP gene is located on chromosome 21q and encodes the protein product, APP [13]. More than 30 mutations in this gene have been described in association with AD, accounting for 10 to 15 percent of early-onset familial AD [11,12]. Mutations are fully penetrant, and age of onset is closely correlated with parental age of onset and mutation type [14]. The median age of onset across all mutation types is approximately 49 years (figure 1).

The function of APP in neurons is not well understood, but it is believed to be important in synaptic transmission [15]. APP is cleaved proteolytically by three enzymes, known as α-, β-, and γ-secretase. In the amyloidogenic pathway, β-secretase and later γ-secretase cleave APP into two peptides of varying lengths. The longer of the two fragments, amyloid-beta 42 (Aβ42), is more hydrophobic and prone to fibril formation.

Nearly all pathogenic APP mutations identified so far cluster around the three major processing sites that are relevant to the generation of amyloidogenic Aß, increasing production of Aβ, or altering the ratio of Aβ42 to Aβ40 [16-19]. Most are dominant missense mutations, although rare families with APP locus duplication or recessive inheritance patterns have been reported [20-24].

Presenilin 1 — The PSEN1 gene is located on chromosome 14q and encodes the protein product, PSEN1. More than 150 PSEN1 mutations have been described in association with AD, accounting for up to 50 percent of early-onset familial AD. Mutations are fully penetrant and associated with an earlier median age of onset (43 years) compared with APP and PSEN2 mutations (figure 1) [14]. In longitudinal kindred studies, preclinical cognitive decline is evident more than 10 years before the onset of clinical impairment [25].

Several different functions have been ascribed to PSEN1, including regulation of intracellular calcium signaling, cell cycle and cell death, trafficking of membrane proteins, regulation of β-catenin stability, and Notch signaling [26]. PSEN1 likely affects AD pathogenesis through its role as a member of the four-protein complex (PSEN1, APH1, PEN2, nicastrin) responsible for γ-secretase cleavage of APP to release Aβ peptides of varying lengths [26].

Most mutations in PSEN1 increase the generation of the highly fibrillogenic Aβ42 species, alter the kinetics of Aβ peptide turnover, and enhance accumulation of Aβ in the brain [26,27]. Blood and cerebrospinal fluid (CSF) levels of Aβ are also elevated. The majority of PSEN1 mutations are missense mutations, but small deletions and insertions have been described as well [28].

Presenilin 2 — The PSEN2 gene is located on chromosome 1q and encodes the protein product, PSEN2. Fewer than 20 PSEN2 mutations have been described, making it the rarest form of early-onset familial AD. The age of onset in reported cases is later and varies more widely with PSEN2 mutations than it does with mutations in APP or PSEN1. Mutations are estimated to be 95 percent penetrant, meaning that up to 5 percent of patients carrying a disease-causing mutation will not develop symptoms of AD in their lifetime [29-32]. This contrasts with APP and PSEN1 mutations, which are felt to be fully penetrant.

The function of PSEN2 and the role of PSEN2 mutations in the pathogenesis of AD are not well understood. PSEN2 mutations may act in part by enhancing apoptotic activity that leads to neurodegeneration [33]. Similar to PSEN1 mutations, PSEN2 mutations alter the cleavage activity of γ-secretase and increase the ratio of Aβ42 to Aβ40. PSEN2 is approximately 60 percent homologous to PSEN1, and may represent a very early chromosomal separation or partial duplication from the PSEN1 gene.

Trisomy 21 — Adults with trisomy 21 (Down syndrome) commonly develop clinical and neuropathologic features of AD by the fifth decade of life due to the presence of an extra copy of the APP gene, the locus for which is on the long arm of chromosome 21. This results in increased production of messenger ribonucleic acid (mRNA) and subsequently APP protein [34].

Others — APP, PSEN1, and PSEN2 mutations account for approximately two-thirds of familial autosomal dominant AD and less than 10 percent of early-onset AD overall. Rare variants at other loci may contribute to early-onset AD risk, including some that overlap with late-onset AD (LOAD; eg, SORL1, TREM2) and others related to the endolysosomal pathway (eg, RUFY1, PSD2, TCIRG1, RIN3) [35].

LATE-ONSET ALZHEIMER DISEASE — The genetic basis of late-onset Alzheimer disease (LOAD) is more complex, with susceptibility conferred by a variety of more common but less penetrant genetic factors likely interacting with environmental and epigenetic influences. To date, the most firmly established genetic risk factor for late-onset disease is apolipoprotein E (APOE). Many more candidate genes have been identified through genome-wide association studies (GWAS), but their effects on LOAD risk are generally smaller and many have not been validated independently. Some of the more replicated candidate genes are discussed below.

Apolipoprotein E — The APOE gene is located on chromosome 19 and exists in three alleles: epsilon 2, 3, and 4. The APOE epsilon 4 (ε4) allele was first recognized as a risk factor for LOAD in 1993 [36]; since then, multiple studies have confirmed its importance as a risk factor for AD, and possibly vascular dementia as well [36-47].

Epidemiology — The frequency of the APOE ε4 risk allele varies across ethnic groups. In one study in New York city, the allele frequency of the ε4 variant was approximately 21 percent in African Americans and was substantially lower in other groups [48]. Among African populations, the reported frequency ranges from 8 percent in Moroccans to as high as 41 percent in Pygmies [49]. Asian populations generally have lower carrier rates, ranging from 7 percent in the Chinese to 24 percent in Malay Aborigines. Its increased frequency in populations where food is, or was in the recent past, scarce suggests that ε4 is a "thrifty" allele that imparts a competitive advantage through energy conservation/utilization [49].

Strength of association — Estimates for the increased risk conferred by the ε4 allele vary by population studied and differ based on age and gender. Individuals with two copies of the ε4 allele are at the highest risk. Typical estimates suggest that one ε4 allele confers two- to threefold increased odds of AD whereas two copies (ε4 homozygous) confer 8- to 12-fold increased odds of AD compared with noncarriers [10,45,47].

Examples of studies demonstrating the association between APOE ε4 genotype and dementia include:

In the Rotterdam study, a population-based cohort of 7983 people aged 55 or older, carriers of the ε2/ε4 and ε3/ε4 genotypes each had a relative risk of AD and vascular dementia that was approximately double that of ε3/ε3 carriers [45]. Carriers of the ε4/ε4 genotype had a relative risk of dementia approximately eight times that of ε3/ε3 carriers.

In an analysis of 1030 older adults (>70 years) in the Framingham study, APOE ε4 homozygotes had a 30.1 relative risk (95% CI 11-84) for AD compared with noncarriers, while ε3/ε4 heterozygotes had a relative risk of 3.7 (95% CI 1.9-7.5) [47].

APOE is a susceptibility gene, not a determinative gene. Patients homozygous for the ε4 allele are much more likely but not absolutely destined to develop dementia. In addition, almost 40 percent of patients with AD do not carry APOE ε4 [47].

The APOE ε4 allele has been associated with an earlier age of onset in patients with LOAD [50-53]. In a study that included over 9000 individuals with LOAD, each additional copy of the ε4 allele reduced the age of onset by 2.5 years [53]. The mechanisms of action of APOE ε4 are compatible with earlier onset.

The APOE ε4 allele has also been associated with the severity of AD. Among the associations are earlier and faster cognitive decline [54], increased hippocampal atrophy on magnetic resonance imaging (MRI) [55,56], more psychiatric complications [42,57], more neuritic plaques and neurofibrillary tangles in all neocortical regions at autopsy [58,59], and decreased survival time [60].

A variety of factors may influence the impact of APOE ε4 on AD risk:

Gender – Although APOE ε4 is a risk factor for AD in both men and women, the effect is greater in women [10,61-65]. Based on a global meta-analysis of more than 57,000 adults, the differential effect in women compared with men appears to be age-dependent and limited to ages 55 to 70 years for the development of mild cognitive impairment (MCI) and ages 65 to 75 years for the development of AD [65]. The mechanisms underlying this gender- and age-dependent vulnerability are not yet understood.

Race – The strength of the association between APOE ε4 and AD or cognitive decline among African Americans and Africans is less clear. Studies examining this issue have had conflicting results, with some researchers finding results similar to those of White populations and others finding a lower or even no association [10,41,48,66-71]. Possible explanations for these discrepancies include a lower mean age of the African American population in some studies, heterogeneity of African American subgroups at different study sites, and modification of APOE effect by environmental and genetic factors.

Vascular risk factors – Vascular risk factors (smoking, diabetes, hypertension, hypercholesterolemia) may also modify the risk of cognitive decline in individuals with APOE ε4 [72].

Modifier genes – The risk associated with APOE ε4 may be modified by other genes or environmental factors. As an example, the saitohin (STH) gene lies within an intron of the human tau gene and may have a role in regulating tau isoforms and thus neurofibrillary tangle deposition [73,74]. An STH gene A to G polymorphism appears to be overrepresented in patients with AD. While this may not be an independent risk factor for AD, the STH polymorphism may be associated with an increased risk of AD in the presence of the APOE ε4 allele [74]. Polymorphisms in other genes, such as complement component 3b/4b receptor-1 (CR1), appear to lower risk of AD among APOE ε4 carriers [75].

In contrast to the ε4 allele, epidemiologic as well as pathologic studies have suggested a protective effect for the ε2 allele in AD [47,58,76].

Proposed mechanism — The mechanism whereby APOE ε4 influences the development of AD is not known and may involve multiple pathways.

APOE is a prevalent lipoprotein in brain, involved in cholesterol homeostasis. It mediates neuronal protection and repair and is felt to be the carrier that aids in removal of amyloid-beta (Aβ) via transport to the bloodstream [77].

The three APOE isoforms, ε2, ε3, and ε4, differ in amino acid sequence at residues 112 and 158. At these positions, the alleles ε2, ε3, and ε4 contain cysteine/cysteine, cysteine/arginine, and arginine/arginine, respectively [78,79]. The arginine increases the overall charge on the protein. Functional studies have shown that oxidized ε4 binds Aβ much more rapidly than does ε3 and might affect the sequestration of Aβ in plaques [80]. In addition, the ε4 allele is not as efficient at transferring Aβ to the bloodstream and therefore may allow Aβ to build up over time.

Alternately, or in addition to these effects, APOE isoforms bind differentially to microtubule-associated protein tau (MAPT), the major component of neurofibrillary tangles, indicating that APOE could affect microtubule function and tangle formation in AD patients [81]. In preclinical models, APOE ε4 affects MAPT pathogenesis via microglial-mediated inflammation and neuronal damage and death [82]. APOE isoforms also differentially affect choline acetyltransferase activity in the hippocampus of AD patients [83] and may alter the lipid transport system associated with compensatory sprouting and synaptic remodeling following AD-associated brain injury [84,85].

APOE ε4 affects plasma lipid levels and is associated with atherosclerotic vascular disease [86]. In a case-control study, high concentrations of plasma lipoprotein(a) increased the risk of developing LOAD in carriers of the ε4 allele, but not in noncarriers [87]. However, in a prospective cohort study, APOE ε4 was a risk factor for AD, independent from cholesterol, lipid, and lipoprotein levels, suggesting that vascular disease is not the primary mechanism by which APOE ε4 influences the development of AD [88].

APOE may also play a role in early brain development. This was suggested by a study that found alterations in brain volumes of infants according to ε4 carrier status, raising the possibility that such changes could increase vulnerability to the pathobiologic cascades of AD [89].

Diagnostic utility — Genotyping of APOE adds marginally to the predictive value of clinical criteria for AD and may stratify risk of conversion of amnesic MCI to AD, but both false positives and negatives occur [90,91]. It is therefore not recommended except as part of a research protocol.

Other candidate genes — Aside from APOE, more than 29 other genes have been identified through individual candidate gene studies or GWAS and shown to have statistically significant risk effects in later meta-analyses [92-96]. The average allelic summary odds ratios for these candidates are modest, ranging from 1.1 to 1.5, compared with a single APOE ε4 allele, which confers an approximately fourfold increased odds of disease.

Some representative meta-analyses and their findings apart from APOE-related risk include the following:

Alzheimer GWAS cohorts from across Europe were pooled to include a total of 6010 cases and 8625 controls [92]. Genome-wide significant associations were found with single nucleotide polymorphisms (SNPs) in clusterin (CLU), also known as APOJ, and CR1.

In a pooled analysis of 16,000 participants recruited through different AD studies in the United States and Europe, genome-wide significant associations were identified with SNPs in CLU and phosphatidylinositol-binding clathrin assembly protein (PICALM) [93].

Combined data from the Cohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) and several European cohorts also confirmed significant effects of CLU, PICALM, and BIN1 variants. In addition, a region containing the genes EXOC3L2, BLOC1S3, and MARK4 surpassed the genome-wide significance threshold [94].

The Alzheimer's Disease Genetics Consortium (ADGC), which includes nearly all existing GWAS datasets in the United States totaling 12,000 cases and 11,000 controls, also confirmed the effects of CLU, PICALM, CR1, and BIN1 [97]. Genome-wide significant association signals were also seen at EPHA1, in a cluster of genes that includes MS4A4A and MS4A6E, in SNPs near CD33 (which is on chromosome 19, 6 Mb from the APOE locus), and near CD2AP on chromosome 14. A companion meta-analysis replicated many of these findings and also identified one novel locus, ABCA7 [98], which has been validated in subsequent studies [99-104].

In a combined ADGC and European dataset, over 74,000 AD cases and controls were analyzed [105]. The increased statistic power afforded by this combined sample yielded 11 additional AD risk loci that surpassed the statistic threshold for genome-wide significance, bringing the total number of robustly replicated LOAD risk loci to 19.

Two subsequently published meta-analyses, one combining all the cohorts listed above with additional ones for a total of over 94,000 AD cases [95], and one using a proxy AD measure (parental history of AD) in the United Kingdom Biobank cohort for a total of over 76,000 cases [96], bring the total of independent AD risk loci to 29.

Even combined, the predictive value of these genes for LOAD remains quite modest [93]. As an example, the attributable risks for the first three validated AD genes were estimated to be 25.5 percent for APOE, 8.9 percent for CLU, and 3.8 percent for CR1 [92]. Although the population-attributable risk for APOE, CLU, PICALM, and CR1 combined was later estimated to be as high as 56 percent [106], this estimate was likely inflated and driven primarily by APOE. Using a true population sample, a separate study reported a very modest increase in the predictive value of a model containing age, sex, APOE, PICALM, and CLU over one containing just age, sex, and APOE [93].

There are some data to suggest that rare variants in amyloid precursor protein (APP), presenilin 1 (PSEN1), and presenilin 2 (PSEN2) may contribute to disease risk in LOAD [107]. Rare heterozygous variants in the gene that encodes TREM2, a gene known to be associated with a rare autosomal recessive form of dementia, have been associated with increased risk of LOAD [108-112], as have rare variants in phospholipase D3 (PLD3) [113], SORL1 [114], and ABI3 [112].

Hexanucleotide repeat expansions in the chromosome 9 open reading frame 72 (C9ORF72) gene have been identified in a small number of families with clinical LOAD, although in most cases review of pathology has revealed findings consistent with frontotemporal lobar degeneration (FTLD) or coexistent FTLD and AD pathology [115-117]. C9ORF72 repeat expansions are a common cause of sporadic and familial amyotrophic lateral sclerosis (ALS) and frontotemporal dementia. (See "Familial amyotrophic lateral sclerosis", section on 'C9ORF72 gene' and "Frontotemporal dementia: Epidemiology, pathology, and pathogenesis", section on 'C9orf72 expansion'.)

The role of these and other candidate genes in the pathogenesis of AD is an area of active investigation. While these variants are currently not diagnostically useful, they may offer mechanistic insights that will potentially lead to new therapies. (See 'Challenges' below.)

CHALLENGES

Limitations of linkage analyses — Linkage studies suffer from several important limitations, the sum of which largely explains why this technique has not been more effective in determining the specific genetic bases of late-onset Alzheimer disease (LOAD). First, the small number of markers used results in low resolution to identify linked regions and the responsible genes. These studies are also vulnerable to locus heterogeneity, which occurs when different families have different AD risk genes. Since linkage statistics basically sum the evidence for a disease gene in a given region over all families, the net evidence for linkage in a given region is often weak, despite the presence of a true risk gene. Many early linkage studies also suffered from insufficient sample size.

Limitations of candidate gene studies — Of the very large number of AD loci implicated by candidate gene studies, very few have been replicated consistently. Possible explanations include false-positive results, lack of adequate power to detect or replicate an association because of sample size, lack of informative markers within a gene, locus heterogeneity (different genes underlying the same AD phenotype), and clinical heterogeneity (multiple clinical subtypes associated with different sets of susceptibility genes) [106]. Lack of consistency across studies may also be due to intralocus heterogeneity (ie, different risk mutations within the same gene).

Limitations of genome-wide association studies — Although many of the limitations inherent to candidate gene studies have been overcome by genome-wide association studies (GWAS), important limitations and challenges do remain. Overall, GWAS have not explained as much of the variance in AD as was originally expected, a challenge that is not unique to AD [118]. There are several hypotheses about why this might be the case across multiple common diseases. (See "Genetic association and GWAS studies: Principles and applications", section on 'Missing heritability'.)

In AD, one possibility is that the majority of the heritability has already been explained by the net effect of the thousands of single nucleotide polymorphisms (SNPs) nominally associated with AD, but that these SNPs fail to meet the multiple test-corrected significance threshold. If true, sample sizes of hundreds of thousands or more subjects would be needed to separate the true from the false associations. Considering the very small effects these SNPs are predicted to have on AD risk, the disease-predictive value or therapeutic target potential gained would likely be minimal. Larger sample sizes do not result in larger effect sizes, however, and the small effect sizes associated with the vast majority of SNPs thus far identified may be the most important impediment to clinical relevance [118].

As with the candidate gene approach, many individual GWAS findings over the years have not been verified in independent samples. Several factors contribute to this inconsistency, including variable definitions of cases and controls, subject ascertainment, variability of SNP genotyping platforms and microarray chips, and sample size.

Unexplained risk — A basic assumption regarding genetic determinants of a complex disease such as LOAD is that common variants in many genes will each lead to a small rise or fall in the risk of disease, and that the overall risk of disease is determined by the combination of multiple variants and environmental exposures. However, genetic studies to date have a mixed track record, and a substantial proportion of LOAD heritability remains unexplained.

Aside from the limitations of candidate and genome-wide association studies discussed above, one possibility for this is termed the "common disease-rare variant" theory. This theory would posit that multiple, rare, family-specific mutations in common genes and biologic pathways explain the remaining AD heritability. A large proportion of these rare variants are not detectable using the microarray chips used in GWAS. As the cost of next-generation sequencing becomes increasingly affordable, large-scale projects are underway to identify these rare variants and test them for association with AD using gene-based methods.

More complex statistic models are also being tested and used in an attempt to explain the remaining AD heritability. As with most complex diseases and biologic systems in general, AD pathogenesis involves multiple proteins in multiple inter- and intracellular pathways with multiple levels of regulation and feedback loops. Pathway and gene set enrichment analyses combine multiple lines of evidence, such as SNP association, gene expression, animal models, and literature mining, to identify pathways and networks involved in disease [119,120]. As an example, an analysis of 2344 AD cases and 7076 controls showed significant enrichment of AD-associated SNPs in genes in several pathways [119]. As expected, the "Alzheimer disease" pathway showed the greatest level of enrichment, but several other pathways were significant, including "regulation of autophagy," "natural killer cell mediated cytotoxicity," "antigen processing and presentation," and "RIG-I-like receptor signaling."

Translation to therapy — Despite statistic evidence for association, most functional variants in the established AD risk genes have not yet been identified, and the precise roles of their encoded proteins in AD pathogenesis are poorly understood. To date, no therapeutic interventions have been developed to intervene in the genes and pathways identified through GWAS. Functional studies such as mouse knockout models are required to better understand functions in both the context of normal biology and the pathology of AD.

GENETIC TESTING — Individuals with early-onset AD and those with a family history of AD may inquire about genetic testing, which has become more accessible through clinical laboratories. The utility and advisability of testing differs for early-onset versus late-onset disease, and given the evolving nature of the field, formal genetics consultation should be recommended for families who express an interest in testing.

Early-onset Alzheimer disease — Genetic tests are commercially available for each of the early-onset, autosomal dominant forms of AD. Testing can either be symptomatic (ie, an individual patient diagnosed with early-onset AD and a family history suggesting autosomal dominant inheritance) or predictive (ie, presymptomatic individuals with a known mutation in their family). Because the range of symptom onset varies more widely than initially recognized, mutations in amyloid precursor protein (APP), presenilin 1 (PSEN1), and presenilin 2 (PSEN2) should still be considered in cases of late-onset AD (LOAD) with a consistent dominantly inherited pattern [14]. Prenatal testing is also available when a disease-causing mutation has been identified. An overview of genetic testing and specifics of available genetics tests are available online at GeneTests. Since multiple mutations in PSEN1, PSEN2, and APP can all cause AD, sequencing the entire coding regions of the genes is necessary to comprehensively assess risk; this is not covered by commercial testing.

Testing for highly penetrant genetic mutations like APP, PSEN1, and PSEN2 carries important implications for family members. Genetic counseling of symptomatic patients should be performed in the presence of the individual's legal guardian or a family member to ensure adequate informed consent and an understanding of the purpose of testing, the possible results, and their implications for other family members [121]. Studies have shown that relatively few family members of individuals with early-onset AD choose to be tested. Although those that are usually cope well with the results [122], depression has been reported [123]. It is ultimately up to the relatives of early-onset AD patients whether to undergo genetic testing. Clinicians and genetic counselors have the responsibility to inform them of the option and communicate the implications of having potentially inherited a dominant mutation with almost complete penetrance. (See "Genetic testing".)

Late-onset Alzheimer disease — For LOAD, the predictive value of the LOAD risk variants described above is extremely limited, with the lone exception of apolipoprotein E epsilon 4 (APOE ε4). APOE genotyping in presymptomatic individuals is controversial and has generally been discouraged because of the low sensitivity and specificity of testing, the lack of preventive options, and the apparent variability of risk conferred by APOE across genders and ethnicities [121]. (See 'Strength of association' above.)

When testing is performed, it appears that most individuals do not suffer undue psychologic harm in the short term after results are revealed, but the long-term impact has not been well studied. In a randomized study, 162 adults who had a parent with AD were randomized to having their ε4 status disclosed or not. Subjects who learned they were ε4-positive and were therefore at increased risk for AD showed no more anxiety, depression, or test-related distress than those who did not learn their genotype. Conversely, test-related distress was reduced among those who learned that they were APOE ε4-negative [124]. In a separate study, codisclosure of information about cardiac risk associated with APOE genotype resulted in lower distress among APOE ε4-positive individuals compared with disclosure of only dementia risk [125].

SUMMARY

Approaches to gene discovery – Despite decades of research, much of the heritability of Alzheimer disease (AD) remains unexplained. (See 'Challenges' above.)

There have been three main strategies employed to identify genetic factors that predispose to the development of AD: linkage analysis, candidate gene studies, and genome-wide association studies (GWAS). (See 'Approaches to gene discovery' above.)

Early-onset AD – Early-onset AD accounts for less than 1 percent of cases and typically follows an autosomal dominant inheritance pattern.

To date, pathogenic mutations in three genes have been identified as causative of early-onset AD: amyloid precursor protein (APP), presenilin 1 (PSEN1), and presenilin 2 (PSEN2). (See 'Early-onset Alzheimer disease' above.)

Genetic testing is available for the known causative genes in early-onset AD but has not been widely adopted, likely in part because of the current lack of highly effective preventive or therapeutic strategies. (See 'Genetic testing' above.)

Late-onset AD (LOAD) – The genetic basis of LOAD is more complex, with susceptibility conferred by a variety of more common but less penetrant genetic factors, likely interacting with environmental and epigenetic influences.

To date, the most firmly established genetic risk factor for late-onset disease is apolipoprotein E epsilon 4 (APOE ε4). (See 'Late-onset Alzheimer disease' above.)

APOE genotyping in presymptomatic individuals is generally discouraged but is becoming more accessible through direct-to-consumer testing. (See 'Genetic testing' above.)

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Topic 16195 Version 31.0

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