Mutations
APOE c.-558A>T (rs449647)
Other Names: rs449647, -491A/T
Quick Links
Overview
Clinical
Phenotype: Alzheimer's Disease, Multiple Conditions
Position: (GRCh38/hg38):Chr19:44905307 A>T
Position: (GRCh37/hg19):Chr19:45408564 A>T
Transcript: NM_000041; ENSG00000130203
dbSNP ID: rs449647
Coding/Non-Coding: Non-Coding
DNA
Change: Substitution
Reference
Isoform: APOE Isoform 1
Genomic
Region: 2kb upstream
Findings
This common polymorphism was identified in a search for regulators of APOE gene expression (Artiga et al., 1998a). Sequencing nucleotides −1017 to +406 in samples of 75 unrelated Spanish individuals, the authors identified three polymorphisms, including c.-558A>T, also known as -491A/T, in the APOE promoter.
Studies evaluating the association of this variant with Alzheimer’s disease (AD) risk have yielded mixed results. Bullido and colleagues first reported that the A allele, in homozygous form, was associated with increased AD risk in a small group of Spanish individuals as well as in a small group of North Americans (Bullido et al., 1998). Data from multiple subsequent studies of small cohorts showed inconsistent results, with some showing associations and others detecting none. Although larger studies and meta-analyses with more statistical power have now revealed a clear association with AD risk (see table below), it is still unclear to what degree other variants traveling together with c.-558A>T underlie or contribute to these associations.
A meta-analysis including more than 3,500 individuals (Lambert et al., 2002) indicated c.-558A and APOE4 are often inherited together, i.e. are in partial linkage disequilibrium (LD coefficient = 72.8 percent, range: 49.9-100 percent, p=1x10-6). However, larger studies suggest the extent of linkage is modest. For example, citing data from the HapMap Consortium (International HapMap Consortium 2007), Watts and colleagues reported r2 values of 0.054 in Western Europeans (CEU), 0.068 in Yoruban from Idaban (YRI), 0.10 in Japanese from Tokyo (JPT) and 0.08 in Han Chinese from Beijing (CHB) (Watts et al., 2022).
c.-558A>T may act as a modulator of risk by modifying APOE expression, either in an APOE4-dependent or APOE4-independent manner. One meta-analysis found that those with the AA genotype had an increased risk of AD compared to those carrying one or two T alleles specifically in APOE4 carriers, suggesting the c.-558A>T AA genotype might boost APOE4 risk (Xin et al., 2010). Other studies have suggested that c.-558A>T may alter AD risk independently of APOE4. The earliest study of this issue revealed an elevated risk in APOE4 non-carriers with the AA genotype (Bullido et al., 1998), and a subsequent meta-analysis showed a moderate, but significant, effect of the AA genotype independent of the APOE4 allele (Lambert et al., 2002).
The effect of c.-558A>T on AD risk may also depend on other polymorphisms. For example, Artiga and colleagues reported increased risk in carriers of both the c.-558A and the C allele of c.-494T>C in two small cohorts (Artiga et al., 1998b). This enhanced risk was independent of APOE4 and, in fact, higher in APOE4 non-carriers. Two additional studies also reported increased AD risk with specific sets of alleles, or haplotypes, including other APOE promoter variants, the common APOE isoforms, and a variant in the APOC1 gene (Parker et al., 2005; Bizzarro et al., 2009). Of note, all of the haplotypes associated with increased AD risk in these studies included the c.-558A allele. However, other studies that have examined haplotypes including some of the same variants have failed to identify significant AD risk associations (e.g., Perry et al., 2001; Nicodemus et al., 2004). As in the case of assessing the effects of the common APOE isoforms, it is important to consider the degree of linkage disequilibrium between variants. Even weak linkage can lead to confounding effects without proper adjustment (Andrews et al., 2019). Data on the linkage between this variant and other nearby variants, across several populations, can be found in the GWAS catalog (click on “Linkage Disequilibrium” tab in the “Available data” section).
Moreover, additional factors, such as age and ancestry, may influence the association of the c.-558A>T polymorphism with AD risk. For example, a meta-analysis including 3,658 individuals showed a moderate effect of the AA genotype on AD risk independent of APOE4, but the association was not observed in a cohort of individuals older than 81 years of age (Lambert et al., 2002, see table). Similarly, a genome-wide association study identified the c.-558A allele as associated with AD, but only in 60–79-year-olds, not in those aged 80 years and older (Lo et al., 2019, see table). Moreover, in a study including AD patients and controls from East Asian countries, the T allele, rather than the A allele, was associated with increased AD risk (see table below, Choi et al., 2019) and found to be present at a much lower frequency than in Europeans or Africans (also see gnomAD v2.1.1: European (non-Finnish) frequency = 0.19, African/African American frequency = 0.31, East Asian frequency = 0.028). The finding is consistent with a previous study of a small population of Japanese individuals that also reported the T allele association and noted it disappeared after controlling for the presence of APOE4 (Kimura et al., 2000). Of note, differences in the frequency of this allele between groups of different ancestries were much smaller among APOE4 homozygotes (Choi et al., 2019).
A few studies have examined the effect of this variant on AD endophenotypes, but again, results are mixed. Two studies reported increased deposition of amyloid-β in carriers of the AA genotype (Lambert et al., 2001; Pahnke et al., 2003), but others, including a follow-up study from one of the groups that originally reported an association, failed to detect such an effect (Myllykangas et al., 2002; Lambert et al., 2005). Also, the AA genotype and the A allele have been associated with poorer cognitive profiles in Italian AD patients (Valenza et al., 2010) and Australian individuals with subjective memory impairment (Laws et al., 2002), however, a British study found no effect of the variant on the rate of cognitive decline in AD patients (Belbin et al., 2007). No association with normal cognitive ability was found in a cohort of 819 older American men (Prada et al., 2014), nor in a study of 202 British children (Turic et al., 2001).
Other Neurological Conditions
Whether c.-558A>T alters the risk of other neurological conditions also remains uncertain. Studies testing for an association with general dementia in the elderly (Lambert et al., 2004; Heijmans et al., 2002) and in individuals who had suffered a stroke (Arpa et al., 2003) failed to detect an effect. Moreover, studies of small cohorts examining associations with Parkinson’s disease (Oliveri et al., 1999; Pal et al., 2019), frontotemporal dementia (Seripa et al., 2011), multiple sclerosis (Ferri et al., 1999; Oliveri et al., 1999; Savettieri et al., 2003; Parmenter et al., 2007), epilepsy (Gambardella et al., 1999), and glaucoma (Guo et al., 2015; Chen et al., 2019) have failed to detect an association or have yielded contradictory results.
Non-neurological Conditions
Similarly, associations of c.-558A>T with non-neurological conditions are unclear. Although a couple of studies indicated that the T allele was associated with increased risk of cardiovascular disease (Yang et al., 2007; Artieda et al., 2008), others have found little or no effect (Casadei et al., 1999; Corbo et al., 2001; Yang et al., 2014; Heijmans et al., 2002), and one small study reported a protective association (Bañares et al., 2012). Ancestry may contribute to some of the differences in findings. For example, a study of 313 Caucasians and 215 African Americans found associations of c.-558A>T with atherogenic lipoprotein levels that differed substantially between the two groups (Ozturk et al., 2010). A subsequent study including 623 non-Hispanic whites and 788 African blacks reported similar findings, with the T allele associated with lower levels of low-density lipoprotein (LDL) cholesterol in whites and with higher levels in blacks (Radwan et al., 2014, Pirim et al., 2019). However, these associations failed to reach statistical significance after adjusting for the common APOE2 and APOE4 alleles.
Biological Effect
c.-558A>T has been reported to affect APOE transcription, but findings are mixed. The effects appear to be cell type- and condition-dependent, as well as modified by the presence of other genetic variants. Based on data from the Genotype-Tissue Expression (GTEx) project, the A allele of this variant is associated with lower APOE expression in different tissues, including the testis and colon (Watts et al., 2022). Moreover, two studies examining serum and plasma found the A allele correlated with lower levels of ApoE (Roks et al., 2002; Limon-Sztencel et al., 2016), although Roks and colleagues noted the effect was small, accounting for no more than 1 percent variance.
On the other hand, in vitro studies using human hepatic and astrocytic cells, suggested the T allele decreases APOE transcription relative to the A allele (Bullido et al., 1998; Artiga et al., 1998a; Geng et al., 2011). Also, Lambert and colleagues found lower levels of ApoE4 mRNA in the brains of AD patients with the AT genotype versus AA genotype (Lambert et al., 1998b), and subsequently others reported increased levels of ApoE in the plasma and brains of AA homozygotes, particularly in AD patients (Scacchi et al., 2002; Laws et al., 1999; Laws et al., 2002). Also of note, a group that reported high ApoE plasma levels in AD patients with an AA genotype found no such effect in patients with coronary heart disease (Corbo et al., 2001).
Several factors may modulate the effects of c.-558A>T on transcription. For example, Artiga et al. found that, in astrocytoma cells, the A allele together with the C allele of c.-494T>C boosted APOE transcription more than the c.-558A allele on its own (Artiga et al., 1998b). In addition, others have reported differential expression effects of the c.-558A allele associated with the common APOE2/3/4 alleles (Lambert et al., 1998b; Limon-Sztencel et al., 2016). The location of c.-558A>T alleles relative to the common isoforms on individual chromosomes—whether they are in cis or trans (i.e., the phasing of the variants)—is expected to contribute to effects on transcription and associated disease risk (Lambert et al., 1998b; Bratosiewicz-Wasik et al., 2018).
c.-558A is within the APOE promoter (Paik et al., 1988), in the HuD functional domain which spans nucleotides -651 to -366 (Maloney et al., 2007). HuD was shown to act as a negative regulatory element in multiple cell types, including neuronal-like rat chromaffin cells (PC12), SK-N-SH neuroblastoma cells, C6 glial cells, and U373 astroctyoma cells. Interestingly, a subsequent study showed that c.-558A is part of an enhancer RNA, AANCR, that appears to regulate APOE transcription in a cell type- and state-dependent manner (Watts et al., 2022). In some cells and under stress, AANCR is fully transcribed and promotes APOE expression, whereas in others, it is only partially transcribed adopting a nonfunctional configuration that represses expression. Interestingly, in astrocytes, AANCR appears to induce an inflammatory phenotype (Wan et al., 2024).
Also of note, c.-558A>T was identified as a candidate single nucleotide polymorphism affecting the expression of APOE in a microglial subtype (Micro1) (Gamache et al., 2023, see suppl table 13). The T allele was predicted to increase affinity for transcription factor SREBPF1.
This variant's PHRED-scaled CADD score (6.92), which integrates diverse information in silico, did not reach 20, a commonly used threshold to predict deleteriousness (CADD v.1.6, Nov 2022).
Table
Study Type | Risk Allele(s) | Allele Freq. AD | CTRL | N Cases | CTRL |
Association Results | Ancestry (Cohort) | Reference |
---|---|---|---|---|---|---|
GWAS Meta-analysis |
42,034 | 272,244a | p=2x10-58 | European (UK Biobank) | Marioni et al., 2018b | ||
GWAS | A | 21,392 | 38,164 | p=8.7x10-18 | Mixed ancestry (ADGC: Transethnic LOAD: All Samples) | Jun et al., 2017c | |
GWAS Meta-analysis |
A | 21,982 | 41,944 | p=5.88x10-48 | European (IGAP Rare Variants: Stage 1) |
Kunkle et al., 2019c | |
GWAS Meta-analysis |
A | 17,536 | 36,175 |
3.04x10-40 (APOE-Stratified Analysis: All Samples) |
(IGAP) | Jun et al., 2016c | |
GWAS Meta-analysis |
T | 17,008 | 37,154 | p=1.5x10-39 | European (IGAP 2013: Stage 1) | Lambert et al., 2013c | |
GWAS Meta-analysis |
A | 8,572 | 11,312 | p=2.6x10-31 | European ( IGAP 2013: ADGC Subset ) |
Lambert et al., 2013c | |
Targeted | 0.024 (total) | 2,302 | 17,096 | p=1.89x10-9 | East Asian (GARD, NRCD) | Choi et al., 2019 | |
Meta-analysis | T vs A | 6,286 | 6,683 | OR=0.72 [CI=0.63-0.82] p=2.6x10-7 |
Mixed | Bertram et al., 2007 | |
Meta-analysis | A | 5,789 | 5,962 (32 studies) | OR=1.45 [CI=1.27-1.65] p<0.001 |
Mixed | Xin et al., 2010 | |
Meta-analysis | AA vs. TA+TT | 5,789 | 5,962 (32 studies) | OR=1.49 [CI=1.29-1.72] p<0.001 |
Mixed | Xin et al., 2010 | |
Meta-analysis | AA vs. TA+TT | (16 studies) | OR=1.42 [CI=1.15-1.76] p=0.001 |
Mixed (APOE4 carriers) | Xin et al., 2010 | |
Meta-analysis | AA vs. TA+TT | (16 studies) | OR=1.20 [CI=0.94-1.53] p=0.14 |
Mixed (APOE4 non-carriers) | Xin et al., 2010 | |
GWAS | T | 0.113 | 11,032 (total) | OR=0.62 [CI=0.56-0.69] p=8.71x10-22 |
European (ADGC multi-cohort sample, 60-79 years) | Lo et al., 2019 |
GWAS Meta-analysis |
A | 7,184 | 26,968 |
p=3.83x10-6 (APOE-Stratified Analysis) |
(IGAP, APOEε4 non-carriers) | Jun et al., 2016c | |
GWAS | T | 0.139 | 4,809 (total) | OR=0.80 [CI=0.70-0.92] p=0.0012 |
European (ADGC multi-cohort sample, >=80 years) | Lo et al., 2019 |
GWAS | T | 0.117 | 4,010 | 4,672 | OR=0.702 [CI=0.619-0.797] p=4x10-8 |
European, U.S. | Wang et al., 2021b |
Meta-analysis | T vs A | 2,819 | 2,567 (19 studies) |
OR=0.962 [CI=0.74-1.25] p=0.77 |
Mixed | Xiao et al., 2017 | |
Meta-analysis | TT vs AA | 2,819 | 2,567 (19 studies) |
OR=1.11 [CI=0.89-1.38] p=0.35 |
Mixed | Xiao et al., 2017 | |
Meta-analysis | TT vs AT | 2,819 | 2,567 (19 studies) |
OR=1.02 [CI=0.70-1.49] p=0.92 |
Mixed | Xiao et al., 2017 | |
Meta-analysis | AT+TT vs AA | 2,819 | 2,567 (19 studies) |
OR=0.94 [CI=0.72-1.23] p=0.65 |
Mixed | Xiao et al., 2017 | |
Meta-analysis | TT vs AA+AT | 2,819 | 2,567 (19 studies) |
OR=0.93 [CI=0.58-1.48] p=0.75 |
Mixed | Xiao et al., 2017 | |
GWAS | A | 1,968 | 3,928 | p=7.48x10-7 | African American (ADGC 2013) |
Reitz et al., 2013c | |
Targeted Meta-analysis |
AA | 0.76 | 0.65 | 1,732 | 1,926 | OR=1.7 [CI=1.5-1.9] p<1x10-4 |
White, multiple countries | Lambert et al., 2002 |
Targeted Meta-analysis |
AA | 0.76 | 0.65 | 1,732 | 1,926 (subgroup N N/A) |
OR=1.3 [CI=1.1-1.6] p<3x10-3 |
White, multiple countries (APOE4 non-carriers) |
Lambert et al., 2002 |
Targeted Meta-analysis |
AA | 0.76 | 0.65 | 1,732 | 1,926 (subgroup N N/A) |
OR=1.4 [CI=1.0-1.8] p<0.04 |
White, multiple countries (APOE4 carriers) | Lambert et al., 2002 |
Targeted Meta-analysis |
AA | 0.76 | 0.65 | 1,732 | 1,926 (subgroup N N/A) |
OR=1.4 [CI=1.1-1.7] p<9x10-3 |
White, multiple countries (APOE4 non-carriers, <=81 years) | Lambert et al., 2002 |
Targeted Meta-analysis |
AA | 0.76 | 0.65 | 1,732 | 1,926 (subgroup N N/A) |
OR=1.6 [CI=1.1-2.1] p<7x10-3 |
White, multiple countries (APOE4 carriers, <=81 years) | Lambert et al., 2002 |
Targeted Meta-analysis |
AA | 0.76 | 0.65 | 1,732 | 1,926 (subgroup N N/A) |
OR=1.2 [CI=0.9-1.7] p<0.25 |
White, multiple countries (APOE4 non-carriers, >81 years) |
Lambert et al., 2002 |
Targeted Meta-analysis |
AA | 0.76 | 0.65 | 1,732 | 1,926 (subgroup N N/A) |
OR=0.9 [CI=0.5-1.7] p<0.9 |
White, multiple countries (APOE4 carriers, >81 years) | Lambert et al., 2002 |
Targeted | 1,398 | 1,082 |
χ2=0.01 p=0.923 |
Italian | Lescai et al., 2011 | ||
Targeted | T | 0.13 | 0.18 | 573 | 509 | OR=0.67 [CI=0.52-0.88] p=0.004 |
French | Lambert et al., 1998 |
Targeted | T | 0.13 | 0.18 | 573 | 509 | OR=0.82 [CI=0.62-1.10] p=0.19 |
French (adjusted for APOE4) |
Lambert et al., 1998 |
acases = max with parental history of AD; controls = min with no parental history of AD
bData from GWAS Catalog rs449647, May 2022
cData from the National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS) rs449647, June 2022
OR=odds ratio, GWAS=genome-wide association study. Statistically significant associations (as assessed by the authors) are in bold. For data retrieved from NIAGADS, p-values <5x10-8 are in bold. All data retrieved from the GWAS catalog (p-values <1x10-5) are in bold.
For Caucasian and mixed ancestry cohorts, all GWAS in this table included >=2,000 cases, and all targeted association studies included >=500 cases (subgroups within a study may be smaller).
This table is meant to convey the range of results reported in the literature. As specific analyses, including co-variates, differ among studies, this information is not intended to be used for quantitative comparisons, and readers are encouraged to refer to the original papers. Thresholds for statistical significance were defined by the authors of each study. (Significant results are in bold.) Note that data from some cohorts may have contributed to multiple studies, so each row does not necessarily represent an independent dataset. While every effort was made to be accurate, readers should confirm any values that are critical for their applications.
Last Updated: 21 Aug 2024
References
Mutations Citations
Paper Citations
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- Watts JA, Grunseich C, Rodriguez Y, Liu Y, Li D, Burdick JT, Bruzel A, Crouch RJ, Mahley RW, Wilson SH, Cheung VG. A common transcriptional mechanism involving R-loop and RNA abasic site regulates an enhancer RNA of APOE. Nucleic Acids Res. 2022 Nov 28;50(21):12497-12514. PubMed.
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External Citations
Further Reading
No Available Further Reading
Protein Diagram
Primary Papers
- Bullido MJ, Artiga MJ, Recuero M, Sastre I, García MA, Aldudo J, Lendon C, Han SW, Morris JC, Frank A, Vázquez J, Goate A, Valdivieso F. A polymorphism in the regulatory region of APOE associated with risk for Alzheimer's dementia. Nat Genet. 1998 Jan;18(1):69-71. PubMed.
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