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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 62:899-907 (2007)
© 2007 The Gerontological Society of America

Differences in the Association Between Apolipoprotein E Genotype and Mortality Across Populations

Douglas C. Ewbank

Population Studies Center, University of Pennsylvania, Philadelphia.

Address correspondence to Douglas Ewbank, PhD, Population Studies Center, University of Pennsylvania, 3718 Locust Walk, Philadelphia, PA 19104-6298. E-mail: ewbank{at}pop.upenn.edu


   Abstract
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 Abstract
Methods
 Results
 Discussion
 Appendix I. Effect of...
 Appendix II. Comparison of...
 References
 
Background. The gene for apolipoprotein-E (APOE) has three common alleles ({epsilon}2, {epsilon}3, and {epsilon}4) that have been shown to be associated with differences in the risk of death in persons older than 60 years in European populations. However, previous research suggests that they may not be associated with mortality in African Americans, and the evidence in Asians is mixed. It is now possible to examine the effects of these genotypes on mortality in African American, Chinese, Japanese, and Korean populations.

Methods. The analysis is based on two types of published data: genotype by age and mortality by genotype. Demographic synthesis uses a multistate model to combine data from these case–control and cohort studies to provide maximum likelihood estimates of the relative risks of death.

Results. In general, the APOE {epsilon}2 allele is associated with 5%–10% lower mortality than the {epsilon}3/3 genotype. The {epsilon}4/4 allele is generally associated with a moderately high relative risk of death. The {epsilon}3/4 genotype is associated with 22% excess risk in Europeans and U.S. whites and with about 35% in Chinese. However, there is no evidence of excess risk with {epsilon}3/4 among African Americans and little excess risk among Japanese and Koreans. The relationship between genotype and mortality is consistent within these ethnic groups. For example, the estimates of R3/4 for Japanese in Japan and Hawaii are both low, and the estimates for Chinese in Taiwan and Shanghai are relatively high.

Conclusions. The relationship between APOE genotype and mortality differs across population groups but shows little evidence of variation within groups.

APOLIPOPROTEIN-E (APOE) is central to the metabolism of cholesterol and triglycerides, and the three main polymorphisms of the APOE gene are associated with variation in total and low-density lipoprotein (LDL) cholesterol levels. Compared with the {epsilon}3 allele, {epsilon}4 is associated with an increased risk of Alzheimer's disease (AD) (1) and coronary heart disease (CHD) (2,3). The {epsilon}2 allele is associated with a lower risk of AD, but its association with CHD is not clear (4).

In populations of European origin (Europeans and U.S. whites) the {epsilon}3/4 genotype is associated with an elevated mortality risk relative to {epsilon}3/3, and {epsilon}2/3 is associated with a slightly lower risk (5). Differences in APOE genotype frequencies explain a substantial proportion of the variation in mortality rates in persons older than 65 years across European countries (6).

The evidence for mortality differentials is less clear in other populations. Two studies of African Americans did not find an association with {epsilon}4 (7–9). In a third study, the number of {epsilon}4 alleles was associated with mortality in persons younger than 75 years (10). A study in Korea did not find a significant difference in the allele frequencies between centenarians and younger controls. Two studies of centenarians in Japan suggest that the {epsilon}2 allele is associated with lower mortality, but there is no significant association with the {epsilon}4 allele (11–13).

Additional data and improved estimation techniques make it possible to estimate the risks associated with the rarer APOE genotypes in European populations and to derive improved estimates for non-European populations.


   METHODS
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 Methods
Results
 Discussion
 Appendix I. Effect of...
 Appendix II. Comparison of...
 References
 
There are two study designs for examining the genetics of longevity in samples of unrelated individuals. Case–control studies compare genotype frequencies at younger and older ages. In the absence of significant migration, a lower frequency of an allele at higher ages suggests elevated mortality rates. Cohort studies measure mortality differences directly.

Data from case–control and cohort studies are combined using a multistate model termed "demographic synthesis" (5). The relative risks of death at age 60 years for each genotype relative to {epsilon}3/3, Ri/j(60), are estimated using maximum likelihood to maximize the probability of observing the reported genotype frequencies at given ages or among deaths. (For simplicity, the age index is generally omitted.) Between ages 20 and 60 years, the relative risks increase from 1.0 to Ri/j(60) in proportion to the increase in the proportion of deaths due to ischemic heart disease in the U.S. in 1990 (6). A parameter, {gamma}, controls for unobserved differences among individuals which can cause the relative risks to converge towards 1.0 at the oldest ages (see Appendix I). This model can be used with cohort data, case–control data, or a combination of the two. Therefore, it is more powerful than the methods that are generally used to analyze either kind of data separately.

Likelihood ratio tests were used to estimate confidence intervals for the Ri/j. For each genotype, the Ri/j was found such that maximizing on all the other parameters led to a likelihood ratio p value of.05 relative to the best fit. This was repeated for upper and lower values.

Identification of Relevant Studies
The data were collected for other purposes, generally to study CHD, AD, or aging. Published studies were identified through Medline pairing APOE and mortality (as a Medical Subject Heading [MESH] term or as a keyword), various age groups (e.g., centenarians, 85+), country and region names, and the names of several large longitudinal studies. Some studies were identified by following references in articles.

Inclusion criteria were population-based studies that provide either mortality data by genotype or case–control data on allele or genotype frequencies for at least one group of persons older than 65 years. Other studies were identified for data on younger age groups to serve as controls.

It is not likely that the analysis is affected by publication bias because many of the published studies addressed questions other than the topic of interest here. In addition, many of the articles that directly address the relationship between APOE and mortality did not report a significant relationship.


   RESULTS
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Discussion
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Populations of European Origin
The data sources for European populations are summarized in Tables A1 and A2. They include cohort studies that observed 8199 individuals for an average of 5.7 years. This is more than six times the sample size of studies examined previously (5). Case–control studies provide APOE genotype frequencies for 935 centenarians and > 1900 other individuals older than 85 years. Additional studies provide gene frequencies at younger ages which serve as controls. The data come from Denmark, Finland, France, Ireland, Italy, The Netherlands, Sweden, and the United Kingdom. The data for Ireland and the United Kingdom are limited and were combined for this analysis.


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  		Table A1. Characteristics of Cohort Studies of European Populations.

 

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  		Table A2. Characteristics of Case–Control Studies of European Populations.

 
The data on U.S. whites (Tables A3 and A4) include cross-sectional data for > 13,500 individuals older than 65 years, five times the previous sample. The cohort studies include about 9050 individuals followed for an average of 6 years, three times the previous sample. Unpublished tabulations by sex and 5-year age groups were available from two studies (7,8).


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  		Table A3. Characteristics of Cohort Studies of U.S. Whites.

 

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  		Table A4. Characteristics of Case–Control Studies of U.S. Whites.

 
The estimates for Europeans and U.S. whites are very similar (Table 1) and are not significantly different (p =.24). At age 60 years, R2/3 is 0.91 and R3/4 is 1.22. Both are significantly different from 1.0 (both p <.001). The confidence intervals are less than one-third the width of those estimated previously. These estimates suggest smaller differences than previous studies (0.84 and 1.34) (5). This is primarily due to the fact that the Ri/j values do not change as rapidly with age as previously estimated (see Appendix I). There is little difference in the estimates for older ages: The new estimate of R3/4 at age 85 years for Swedish women born in 1898–1902 is 1.19 compared to 1.23 estimated previously.


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  		Table 1. Estimates of the Risks of Death at Age 60 Years for Each Apolipoprotein E Genotype Relative to Genotype {epsilon}3/3 for Europe, U.S. Whites, African Americans, Chinese, Japanese, and Koreans (With 95% Confidence Intervals).

 
The estimate of R4/4 is 1.56 (p <.001). It is not significantly different from the square of R3/4 (p =.41). R2/4 is not significant (p >.50), which reflects the counteracting effects of the {epsilon}2 and {epsilon}4 alleles. Although {epsilon}2/3 is associated with lower mortality, a second copy of the {epsilon}2 allele is associated with little, if any, further reduction in mortality. R2/2 is larger than but not significantly different from the square of R2/3 (0.96 vs 0.91; p =.096). There are no significant differences by sex (p >.75). Estimates based on only the case–control or the cohort data are very similar and not significantly different (p >.17; see Appendix II and Table A5).


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  		Table A5. Comparison of Estimates of the Relative Risks of Death for Apolipoprotein E Genotypes at Age 60 Years Based Only on Case–Control or Cohort Data with the Cohort Data Modeled Using Odds Ratios (OR) or the Multinomial Distribution of Deaths by Genotype Using Data from Finland, The Netherlands, Sweden, Cache County, Utah, North Carolina, Northern Manhattan, and Western Pennsylvania.

 
Estimates of R2/3 and R3/4 for each European country and each study in the United States are shown in Figures 1 and 2. Since some of the studies do not provide enough data to get precise estimates of all five relative risks, R2/2 is set equal to R2/3, R2/4 is fixed at 1.0, and R4/4 is set equal to R3/42. None of the estimates is significantly different from the overall estimates.


Figure 01
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  		Figure 1. Estimates of R2/3 (A) and R3/4 (B) at age 60, Europe and seven areas. APOE = apolipoprotein-E

 

Figure 02
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  		Figure 2. Estimates of R2/3 (A) and R3/4 (B) at age 60 for the five studies of U.S. whites. APOE = apolipoprotein-E; NLTCS = National Long Term Care Survey

 
The differences in mortality by genotype diminish at the oldest ages. The estimated relative risks change by age faster in populations with higher levels of mortality as a result of the frailty model. Figure 3 shows the estimates of R3/4(x) and R4/4(x) using the estimates for Europeans and life tables for men born in Finland in 1885–1895 and women born in Sweden in 1900–1904. The life expectancies at age 60 years for these cohorts were 14.1 and 21.1 years. Since these Ri/j(x) values are based on the same estimates of Ri/j(60) and {gamma}, the differences in the relative risks at the oldest ages reflect only the different life tables.


Figure 03
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  		Figure 3. Estimated risk of death by age for the apolipoprotein-E (APOE) {epsilon}3/4 and {epsilon}4/4 relative to {epsilon}3/3, based on the estimated relative risks among Europeans and the life tables for men born in Finland in 1885–1889 and for women born in Sweden in 1900–1904

 
African-Americans
Studies in North Carolina and northern Manhattan provide cohort data for African Americans (references in Table A6). Genotype data are also available for 396 African Americans in Indianapolis in two age groups: younger and older than 75 years. This includes 343 persons without dementia and 41 with dementia (10,14). Genotype frequencies for younger ages from two studies help to anchor the estimates of the allele frequencies (15,16) but do not change the parameter estimates appreciably.


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  		Table A6. Characteristics of Cohort Studies of African Americans.

 
The mortality differences by genotype are smaller than those estimated in Europeans (Table 1). R2/3 is < 1.0 but not significant. R2/2 is significant (p =.042) and much lower than the estimate for Europeans. R3/4 shows no evidence of an effect and is significantly different from the estimate of R3/4 for Europeans (p =.001). However, R4/4 is significant and very similar to the estimate for Europeans.

The three studies lead to very similar estimates for R3/4: 1.03, 1.07, and 1.05 for North Carolina, northern Manhattan, and Indianapolis, respectively. The data for men and women also lead to similar estimates (1.05 and 0.97).

Data for Nigerians older than 65 years in the Indianapolis-Ibadan Dementia Study suggest little or no relationship between genotype and mortality, but the data are not sufficient to draw firm conclusions (10). The estimated risk for carriers of the {epsilon}4 allele ({epsilon}3/4 and {epsilon}4/4 combined) is 1.05 (0.87-1.25), which is the same as the estimate for African Americans (1.05, 0.94-1.17).

Asian Populations
There are data for Chinese populations in Shanghai and Taiwan, for Japanese in Japan and Hawaii, and for Koreans (Table A7). The data for Taiwan include unpublished data from the Social Environmental and Biomarkers for Aging Study (SEBAS) (17). The Honolulu-Asian Aging Study (18,19) gives cohort data on 3564 Japanese American men older than 70 years.


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  		Table A7. Characteristics of Case–Control Studies of Asians.

 
Table 1 gives the estimates for Asian populations. The estimates of R3/4 for Koreans and Japanese are both quite low. Data from the Shanghai metropolitan area (20) lead to a higher estimate, 1.46 (confidence interval [CI], 1.09–1.93), which is not significantly different from the estimate for Taiwan, 1.30 (CI, 0.99–1.70, p >.25). Combining the data for Chinese populations leads to an estimate of R3/4 of 1.37, which is significantly different from the estimates for Japanese (p =.04) and Koreans (p =.02). The estimates of R3/4 for Japanese in Japan and Japanese in Hawaii are very similar (1.10 and 1.09) and not significantly different (p =.36). The estimate for Japanese in Japan is very sensitive to the assumed value of {gamma}. However, using other reasonable values for {gamma} does not change these conclusions (see Appendix I). The only other significant estimates for Asians are the R2/2 and R4/4 for Japanese (Table 1).

The Indo-US Cross-National Dementia Study (21) provides genotype frequencies for four age groups in Haryana State in northwestern India. As in Japan and Korea, there is no evidence of excess mortality associated with the {epsilon}3/4 genotype (R3/4 = 1.00, CI, 0.81–1.22).


   DISCUSSION
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 Methods
 Results
 Discussion
Appendix I. Effect of...
 Appendix II. Comparison of...
 References
 
APOE genotypes are associated with differences in mortality at older ages in a wide variety of ethnic groups. The {epsilon}2 allele is associated with slightly lower risks in Europeans, African Americans, and Japanese. The elevated risks associated with the {epsilon}3/4 genotype are modest in populations of Europeans and Chinese, but are small or nonexistent in African Americans, Japanese, and Koreans and possibly in Nigerians and parts of northern India. These differences in R3/4 do not mirror the well-known differences in the {epsilon}4 allele frequency across populations. Populations with {epsilon}4 frequencies in the range of 0.08–0.10 have low estimates of R3/4 (Japanese), medium estimates (Italians), and high estimates (Chinese). Similarly, Finns and African Americans both have {epsilon}4 frequencies of about 0.20, but they have very different estimates of R3/4.

The {epsilon}4/4 genotype is associated with moderately high levels of excess risk in Europeans, African Americans, and Japanese, even though R3/4 is not significant in the latter two populations. Earlier studies of African Americans using the same data from North Carolina and northern Manhattan (7–9) combined the {epsilon}3/4 and {epsilon}4/4 genotypes and did not find an association with the presence of the {epsilon}4 allele. However, the analysis of the data from Indianapolis did reveal a significant association with the number of {epsilon}4 alleles among individuals younger than 75 years who were not demented at baseline (10). In a meta-analysis of APOE and AD, Farrer and colleagues (1) also found a significant association in African Americans with {epsilon}4/4, but not {epsilon}3/4.

The groups compared here are defined in terms of place of birth and (in the case of U.S. whites and African Americans) self-identification—not on the basis of genetics. There is both genetic and environmental variation within each of these groups and among them. However, the only significant differences we find are between groups, not within them. For example, the data for Japanese in Japan and in Hawaii both lead to estimates of R3/4 of about 1.09, and the data for Taiwan and Shanghai both lead to relatively high estimates. There are also no significant differences in the Ri/j for African Americans living in three different communities or between African Americans and Nigerians. In contrast, there are significant differences among the estimates for Europeans, African Americans, Japanese, and Chinese. This finding suggests that gene interactions (G x G) might be more important than environmental (G x E) effects.

Linkages with other genes involved in lipid metabolism might be especially important. The APOE gene is part of a cluster on chromosome 19 that also includes the genes for APOC-I and APOC-II. The linkages between some alleles of the APOC-I gene and APOE {epsilon}4 have been shown to be different in U.S. whites, African Americans, and Chinese (22,23).

Linkages with variants in the APOE promoter region that have been linked to phenotypic variation (24–26) might also be important. Some of these variants have only been observed in a single ethnic group (27). In European populations, the three common APOE polymorphisms explain up to 30% of the variation in serum levels of APOE (28). Differences in serum levels of APOE are a more important determinant of serum lipids than APOE genotype (29). Therefore, the effects of the APOE genotypes might be due to both quantitative (serum APOE levels) and qualitative (different binding properties) differences.

The differences among the R3/4 for Chinese, Koreans, and Japanese are surprising. These three populations are very closely related genetically, with the Koreans somewhat more similar to the Japanese (30). It is possible that some of the observed differences may be due to environmental differences.

The APOE gene is the only gene that has been conclusively shown to have common polymorphisms that explain significant differences in overall mortality. It is now clear that these associations vary across populations. These differences suggest important G x G or G x E interactions that might provide insights into the pathways through which these subtle differences in a single gene can have such an important impact on mortality.


   APPENDIX I. EFFECT OF ASSUMED VALUE OF {Gamma} ON THE ESTIMATES
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 Appendix I. Effect of...
Appendix II. Comparison of...
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Given a value of {gamma}, the Ri/j(60) sets the relative risks at all ages. Cohort studies provide information that is useful for estimating {gamma}. In contrast, studies that only provide genotype frequencies for centenarians and individuals younger than 60 years provide no evidence of how the relative risks change with age. For centenarian studies, the estimates of the Ri/j(60) are very sensitive to the value of {gamma}. This issue is particularly relevant to the estimates for Japanese living in Japan, which are based on two centenarian studies.

With gamma distributed unobserved heterogeneity, the Ri/j(x) are given by:


Formula

where Si/j,x is the proportion of persons with genotype i/j who survive to age x. Therefore, the rate of change with age in ln(Ri/j) is proportional to {gamma}2 (5).

Figure A1 shows estimates of R3/4(60), given various estimates of {gamma}. It takes very large sample sizes to estimate {gamma} with any precision. Maximum likelihood estimates of {gamma} for Europe and the United States are in the range of 0.25–0.40. Over this range, the estimates of R3/4(60) are relatively stable. At values > 0.5, the estimates change more rapidly. The parameter estimates for all population groups assumed that {gamma} = 0.35, which eases comparisons across groups.

The estimates for Japanese in Japan and Hawaii are very similar if {gamma} is less than about 0.55. The estimates of R3/4(60) for all Japanese and Chinese are always significantly different from each other (p <.01) for all values of {gamma}. The estimates are also significantly different if we assume a value of 0.50 for the Japanese and 0.25 for the Chinese (p =.045).

The estimates of R2/3(60) are less sensitive and R4/4(60) more sensitive to the estimate of {gamma}. However, this does not change the conclusion that, in general, R2/3(60) is slightly < 1.0 and R4/4(60) is generally moderately large.


   APPENDIX II. COMPARISON OF ESTIMATES BASED ON CASE–CONTROL AND COHORT DATA
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 Methods
 Results
 Discussion
 Appendix I. Effect of...
 Appendix II. Comparison of...
References
 
There are enough cohort data for Europeans and U.S. whites to support meaningful comparisons of estimates based on the case–control data with those based on the cohort data. However, this comparison cannot be made using the multinomial distribution to estimate the likelihood of observing the distribution of deaths by genotype. The distribution of deaths by genotype is dependent on the distribution of the population at risk by genotype. The baseline data for some cohort studies do not provide sufficient information on the genotype distribution. For example, fitting the model to all of the available cohort data leads to an estimated {epsilon}4 allele frequency for Finland of > 0.65, which is much higher than the 0.19 that emerges when all of the data are used. Using the genotype frequencies from the control data with the cohort data is essentially the same as using the baseline data as case data for the case–control.

An alternative approach is to calculate odds ratios from the data and from the model. The logs of the estimates can be compared using a normal distribution with variance:


Formula

where the Di/j and Si/j are the reported numbers of deaths and survivors among genotype i/j. If any of these four values is 0, then pseudo-odds ratios and their variances are constructed by adding 0.5 to all of the reported and estimated values (31).

The problem with using odds ratios is that the relative estimates depend on the same reported values for {epsilon}3/3. Therefore, the estimates are not independent. This will change the weight given to each population or age group and, therefore, affect the estimates. It also leads to confidence intervals that are too narrow.

Table A5 presents estimates based on the data for the populations for which cohort data are available. The estimates based on all of the data are very similar whether we use the multivariate distribution of deaths or the odds ratios. However, the estimates based only on the cohort data using the odds ratios show slightly smaller differences in mortality between the {epsilon}3/3, {epsilon}2/3, and {epsilon}3/4 genotypes than the estimates based on the case–control data. However, the CI values from the cohort data are quite large (even though they are underestimated). Overall, the estimates based on the case–control and cohort data are not significantly different (p =.17, which is an underestimate).


Figure 01
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  		Figure A1. Estimates of the relative risk of death at age 60 for Chinese, Europeans, Japanese in Japan, Japanese in Hawaii, and Koreans given various estimates of the shape parameter {gamma}

 

   Acknowledgments
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This research was supported by a grant from the National Institute on Aging (NIA) (R01-AG-016683). The SEBAS project in Taiwan is supported by NIA grants R01AG16790 and R01AG16661. Collection of the data from northern Manhattan was supported by grant AG07232. The North Carolina Established Populations for Epidemiologic Studies of the Elderly (EPESE) was supported by the NIA through grants N01-AG12102, R01-AG12765, and R01-AG17559.


   Footnotes
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 Appendix II. Comparison of...
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Decision Editor: Luigi Ferrucci, MD, PhD

Received March 17, 2006

Accepted November 10, 2006


   References
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