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The role of the apoliprotein E (APOE) and the angiotensin converting enzyme (ACE) polymorphisms on health and functional status deterioration in old age is still undefined. Recently, a Multidimensional Prognostic Index (MPI) for 1-year mortality derived from a Comprehensive Geriatric Assessment (CGA) was developed and validated in hospitalized elderly patients. The aim of this study was to investigate the possible association of the APOE and ACE gene polymorphisms with the multidimensional impairment, as evaluated by the MPI, in older patients. These polymorphisms were assessed in 1894 geriatric inpatients divided into three groups according to their MPI values: MPI-1 low risk (n = 988), MPI-2 moderate risk (n = 671), and MPI-3 severe risk of mortality (n = 235). A slight deviation from Hardy–Weinberg equilibrium was observed for the APOE genotypes. With the increasing of the MPI grade, a significant increase in the frequencies of 4 allele and the ACE D/D genotype was observed. The APOE 4+ and ACE D/D genotypes were associated with severe MPI grade (APOE 4+, odds ration [OR] = 1.79, 95% confidence interval [CI] 1.20–2.67; ACE D/D, OR = 1.42, 95% CI 1.05–1.92). The combined APOE 4+ and ACE D/D genetic status was associated with higher MPI grade (OR = 2.85, 95% CI 1.75–4.65), without interaction. No significant associations between APOE and ACE polymorphisms and 2-year mortality were found. APOE and ACE genes might predispose individuals to health and functional status deterioration in old age, and their effect is additive.
Recently, a Multidimensional Prognostic Index (MPI) for 1-year mortality derived from data collected in a standardized Comprehensive Geriatric Assessment (CGA) was developed and validated in two independent cohorts of older patients hospitalized for acute diseases or relapse of a chronic disease.1 The strong prognostic value for mortality suggests that the MPI captures a critical dimension of increased susceptibility to disease and impairment that characterizes many frail older persons.2
It has been suggested that some individuals are genetically predisposed to develop strong disease susceptibility earlier in life than others.3 Research on the specific genetic polymorphisms that are associated with old-age poor health and functional status, as marked by high risk of mortality, may help understanding the pathophysiology of frailty.
Amongst the genetic markers associated with enhanced morbidity, the apolipoprotein E (APOE) and the angiotensin converting enzyme (ACE) are pre-eminent candidates. Studies have suggested that the APOE common alleles, i.e., 2, 3, and 4 allelic variation, may play a role in Alzheimer disease,4 cognitive impairment,5 coronary heart disease,6 and possibly cerebrovascular disorders.7 Moreover, persons with the APOE 2 allele are more likely to be long lived.8 Although APOE 4 has been defined as a “frailty gene,”9 a recent study failed to demonstrate a significant association between the APOE 4 allele and frailty.10
Studies have found that an insertion (I)/deletion (D) polymorphism in the ACE gene is a risk factor for atherosclerosis, coronary heart disease, cerebrovascular disease,11 and possibly Alzheimer disease.12 Although data on the relationship between ACE polymorphisms and longevity are still under debate,12,13 a potential role of the ACE system on physical function decline,14 sarcopenia, and potentially frailty15 has been recently reported.
The aim of this study was to investigate the possible association between the APOE and the ACE gene polymorphisms and different grades of global susceptibility for diseases and impairments, as assessed by the MPI, in a large group of hospitalized older patients.
The study was conducted according to the Declaration of Helsinki and the guidelines for Good Clinical Practice and was approved by the local Ethics Committees. Written informed consent was obtained from the patients or from relatives of critically ill patients prior to participation in the study.
From January, 2005, to December, 2006, all patients aged ≥65 years consecutively admitted to the Geriatric Unit of the Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) “Casa Sollievo della Sofferenza,” due to an acute disease or relapse of a chronic disease, were considered for the inclusion in the study.
Inclusion criteria were: (1) age ≥65 years; (2) ability to provide an informed consent or availability of a proxy for informed consent and willingness to participate in the study; and (3) complete CGA during hospitalization.
At baseline, the following parameters were collected by structured interview, clinical evaluation, and review of records from the patients' general practitioners: Date of birth, gender, clinical history, current pathologies, and medication history.
Vital status up to February, 2009, was assessed by directly contacting the participants or consulting the Registry Offices of the cities where the patients were residents at the time of hospital admission. Dates of death were identified from death certificates. Data on vital status were available on 1614 patients.
All patients were Caucasians, with most individuals having central and southern Italian ancestry.
Discharge diagnoses, coded according to the Italian translation of the International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) (available at http://icd9cm.chrisendres.com/icd9cm/) were also recorded.
The CGA included assessment instruments that are widely used in geriatric practice and that were previously validated in two cohorts of hospitalized patients.1 In particular, functional status was evaluated by the Activities of Daily Living (ADL) index and Instrumental Activities of Daily Living (IADL) scale. Cognitive status was assessed by the Short Portable Mental Status Questionnaire (SPMSQ). Co-morbidity was examined using the Cumulative Illness Rating Scale (CIRS). Nutritional status was explored with the Mini Nutritional Assessment (MNA) and the Exton–Smith Scale (ESS) was used to evaluate the risk of developing pressure sores. Medication use was defined according to the Anatomical Therapeutics Chemical (ATC) classification code system (available at www.whocc.no/atcddd/), and the number of drugs used by patients at admission was recorded. Patients were defined as drug users if they took a medication included in the ATC classification. Social aspects included household composition, home services, and institutionalization.
The time approximately required for collecting data for the CGA was 20 min (range from 15 to 25 min per person).
The MPI is an index recently introduced and validated to predict posthospitalization mortality in elderly patients.1 Briefly, a cluster analysis on CGA data was initially made for evaluating the independence of variables and identifying the most relevant domains of the CGA in predicting mortality outcome. Then, in a stepwise method, the domains of the CGA, one at a time, were included progressively in the model, and relative Cox and logistic regression analyses performed. An “eight-domain” MPI, i.e., which included a total of 63 items in eight domains of the CGA, resulted in the best index in predicting 1-year mortality. For each domain, a tripartite hierarchy was used, i.e., 0 = no problems, 0.5 = minor problems, and 1 = major problems, on the basis of conventional cutoff points derived from the literature for the ADL, IADL, SPMSQ, MNA, and ESS and by observing the frequency distribution of the patients at various levels to identify points of separation for co-morbidities and number of drugs accordingly to previous rules-based indexes used for exploring multidimensional impairment in elderly subjects.1 The sum of the calculated scores from the eight domains was divided by 8 to obtain a final MPI score from 0 to 1. For analytical purposes, absolute values of MPI were expressed as low (MPI-1, value ≤ 0.33), moderate (MPI-2, value between 0.34 and 0.66), and severe risk (MPI-3, value >0.66) of mortality. This analytical approach was validated in our previous studies.1
Genomic DNA was manually purified from peripheral blood by organic protein extraction and ethanol precipitation according to standard methods.12,16 For the APOE genotyping, a combination of four allele-specific primers used in three different pairs sharing the same stringent PCR conditions was used. The presence/absence of specific allele PCR products detected by electrophoresis analysis on a 2% agarose gel, identified the six APOE genotypes.16 For the ACE genotyping, a direct analysis of PCR product on a 1.8% agarose gel identified the three ACE I/D genotypes.12
Differences across groups were evaluated using the Student t-test for independent sample and the one-way analysis of variance (ANOVA) test (for continuous variables), and the Pearson chi-squared and the Fisher exact test (for discrete variables).
Agreement of the observed genotype frequencies with the expected Hardy–Weinberg frequencies was verified with the R Software for Statistical Computing, version 2.7.2 (available at www.r-project.org/). Relative allelic frequencies were calculated by the gene-counting method.
In the analysis of the APOE polymorphism, we considered allele carriers according to the three common human APOE 2, 3, and 4 alleles. The 3/3 genotype was the reference category. 2+ and 4+ carriers were considered subjects with those genotypes showing at least one APOE allele, i.e., subjects with the 2/2 or 2/3 genotypes (2+ carriers) and subjects with 3/4 or 4/4 genotypes (4+ carriers). Carriers of 2/4 genotypes were excluded from the analysis. In the analysis of the ACE polymorphism, we considered the three genotypes, homozygotes I/I, homozygotes D/D, and heterozygotes I/D. Carriers of genotypes I/I or I/D (carriers I+) were the reference category.
The analyses of APOE and ACE polymorphism frequencies across the MPI groups were performed comparing frequencies of the MPI-3 group versus frequencies of the MPI-1 and versus frequencies of the MPI-2 groups separately. Logistic regression analysis was carried out, including all APOE and ACE genotypes and their combinations in patients of MPI-3 group versus patients of the MPI-1 + MPI-2 groups. Moreover, logistic analysis was made on the population subdivided according to the tripartite hierarchy of the individual MPI domains, as mentioned above. All analyses were made using gender, age, neurodegenerative disease, cardiovascular disease, cerebrovascular disease, and neoplasia as confounding factors. The occurrence of these pathologies was used as categorical variables, and used in a backward stepwise model to test if they contribute significantly to the model fit. The odds ratio (OR) with the corresponding 95% of confidential interval (95% CI) was also calculated. The possible interaction between APOE and ACE polymorphisms was also investigated.
Survival analysis was performed using the Kaplan–Meier method, with the log rank test for statistical comparisons. Plots for different combinations of alleles were constructed using the age of patients at death or at the end of follow-up, whichever came first. A Cox proportional hazards regression analysis was also performed to determine the hazard risk adjusted for the confounding factors described above. For the analysis of the relationship between MPI grades and mortality, survival time was calculated as the number of days between admission to hospital and time to death or end of follow-up, whichever came first. Given the frequencies of the APOE 4 allele or the ACE D/D genotype in MPI-3 and non-MPI-3 subjects (APOE 4, 0.247 and 0.163, respectively; ACE D/D, 0.464 and 0.392, respectively) we observed a size-effect (h) of 0.209 and 0.145, respectively. Thus, assuming a statistical significance α = 0.05, the powers of the analyses were 0.851 and 0.551, respectively. Considering the combined APOE 4+ – ACE D/D frequency in MPI-3 and non-MPI-3 subjects (0.140 and 0.063, respectively), we observed an h = 0.259; assuming a statistical significance α = 0.05, the power of the study was 0.961. This analysis was performed with the R Software for Statistical Computing, version 2.7.2. All of the other statistical analyses were made with the SPSS statistical software, version 10.1.3 (SPSS Inc., Chicago, IL). In all the analyses, the level of significance was set at a p value <0.05 (two-tailed model).
From a total of 1967 elderly patients consecutively admitted to the Geriatric Unit of the IRCCS “Casa Sollievo della Sofferenza,” 29 patients were excluded because they were younger than 65 years. Also, 44 patients were excluded because they had an incomplete CGA or missing genotypic data. Thus, the final sample included 1894 patients, with 906 men and 988 women.
Baseline characteristics of the study population are shown in Table 1. Women showed a significantly higher mean age (78.8 ± 7.0 years vs. 77.7 ± 6.9 years; p < 0.001), lower educational level (3.6 ± 3.0 years of education vs. 5.0 ± 3.8 years of education; p = 0.001), higher disability at the ADL (4.2 ± 2.2 vs. 4.6 ± 2.1; p = 0.001), higher cognitive impairment according to the SPMS Q score (2.7 ± 2.7 vs. 1.9 ± 2.5; p < 0.001), lower ESS score (15.9 ± 3.4 vs. 16. 8 ± 3.2; p < 0.001), lower nutritional status according to MNA score (21.3 ± 5.4 vs. 22.4 ± 5.3; p < 0.001), and higher MPI mean value (0.4 ± 0.2 vs. 0.3 ± 0.2; p < 0.001) than men.
Table 2 shows concomitant diseases and drugs use of the study population. Compared with men, women had significantly more hypertension (59.8% vs. 50.1%; p < 0.001) and musculoskeletal diseases (17.0% vs. 10.5%; p < 0.001). Conversely, men had significantly more neoplasia (25.7% vs. 16.7%; p < 0.001), ischemic heart diseases (12.7% vs. 6.7%; p < 0.001), and respiratory diseases (26.7% vs. 17.9%; p < 0.001) than women. Women took more cardiovascular drugs (77.0% vs. 68.7%; p < 0.001), musculoskeletal drugs (21.4% vs. 15.7%; p=0.002), and drugs for the nervous system (29.4% vs. 23.7%; p=0.006) than men. Conversely, men took more drugs for the urogenital and respiratory systems (14.0% vs 0.4%; p < 0.001, and 16.7% vs. 9.8%; p < 0.001; respectively) than women.
According to their MPI values, 988 patients (52.2%) were classified as MPI-1 (low risk of mortality), 671 patients (35.4%) were classified as MPI-2 (moderate risk of mortality), and 235 patients (12.4%) were classified as MPI-3 (severe risk of mortality). Higher MPI grades were significantly associated with older age (MPI-1=76.2±6.1 years vs. MPI-2=80.1±7.0 years vs. MPI-3=81.9±7.2; p < 0.001) and female sex (MPI-1=47.3% vs. MPI-2=56.0% vs. MPI-3=61.7%; p < 0.001).
At the end of 2 years of follow-up, data on survival were available on 1614 subjects. During the follow-up, 561 patients (34.8%) died (297 men [52.9%] and 264 women [47.1%]). The mortality rates were significantly higher in patients with a MPI-3 grade than MPI-2 and MPI-1 (56.5% vs. 46.6% vs. 20.9%, p < 0.001). The Kaplan–Meier curves showed significant higher mortality in MPI-3 grade patients than MPI-2 and MPI-1 grade patients (log rank test, p=0.01). Cox regression analysis, adjusted for gender, age, neurodegenerative, cardiovascular and cerebrovascular diseases, and neoplasia, demonstrated that higher MPI grades were significantly associated with higher mortality risk (MPI-2 vs. MPI-1, hazard ratio [HR]=2.35, 95% CI 1.92–2.88, p < 0.001; MPI-3 v.s MPI-1, HR=3.47, 95% CI 2.69–4.48, p < 0.001).
In the study population, the overall frequencies of the APOE genotypes were 10.8% for the 2/3 genotype (n=204), 1.3% for the 2/4 genotype (n=25), 71.9% for the 3/3 genotype (n=1361), 15.3% for the 3/4 genotype (n=289), and 0.8% for the 4/4 genotype (n=15). No 2/2 genotypes were observed. These frequencies were slightly different from the expected Hardy–Weinberg equilibrium frequencies (p=0.04). Estimated allele frequencies were 0.061 for the 2 allele, 0.848 for the 3 allele, and 0.091 for the 4 allele. Distribution of the APOE genotype frequencies did not show significant differences between men and women (2/3, 12.2% vs. 9.4%; 2/4, 1.4% vs. 1.2%; 3/3, 71.8% vs. 71.8%; 3/4, 14.0 vs. 16.4%; 4/4, 0.44% vs. 1.1%, p=0.08). Moreover, no significant differences in mean age across the APOE polymorphisms were observed (2/3, 78.6±6.6; 2/4, 77.4±8.4; 3/3, 78.3±7.1; 3/4, 78.1±6.7; 4/4: 78.2±6.2; p=0.93).
The frequencies of APOE allele carriers according to MPI grades were summarized in Table 3. With the increasing of the MPI grade, a progressive lower prevalence of 3/3 genotype was observed (MPI-1=73.9% vs. MPI-2=73.8% vs. MPI-3=65.2%). Conversely, there was a progressive and significant increasing prevalence of 4+ carriers (MPI-1=14.9% vs. MPI-2=15.9% vs. MPI-3=23.0%; p=0.008). No significant differences were observed in the frequency of 2 carriers. As expected, with increasing MPI grade, the estimated frequency of the 3 allele decreased and the estimated frequency of 4 allele increased significantly (p=0.008).
Logistic regression analysis, adjusted for gender, age, neurodegenerative diseases, cardiovascular diseases, cerebrovascular diseases, and neoplasia (Table 4), confirmed a significant association of the 4+ allele with the highest MPI grade (MPI-3 vs. MPI-1, OR=1.79; 95% CI 1.20 −2.67; and MPI-3 vs. MPI-2, OR=1.62, 95% CI 1.10– 2.26). No significant associations between APOE polymorphisms and 2-year mortality was found (2+, HR=0.88, 95% CI 0.66–1.16, p=0.36; 4+, HR=0.88, 95% CI 0.70–1.12, p=0.30).
Adjusted logistic regression analysis on the individual MPI domains showed significant association between the APOE 4+ allele and higher risk of cognitive impairment as evaluated by the SPMSQ domain (SPMSQ-3 vs. SPMSQ-1, OR=1.66, 95% CI 1.03–2.67). No other significant differences were observed.
In the study population, the overall frequencies of the ACE genotypes were 13.1% for the I/I genotype (n=248), 46.8% for the I/D genotype (n=887), and 40.1% for the D/D genotype (n=759). These frequencies did not significantly differ for the expected Hardy–Weinberg equilibrium frequencies (p=0.66). Estimated allele frequencies were 0.365 for the I allele and 0.635 for the D allele. Distribution of the ACE genotype frequencies did not show significant differences between men and women (I/I, 11.4% vs. 14.7%; I/D, 47.0% vs. 46.6%; D/D, 41.6% vs. 38.7%, p=0.083). A slightly significant difference in mean age was observed across the ACE polymorphism groups (I/I, 79.1±6.8; I/D, 77.9±6.9; D/D: 78.5±7.0, p=0.04).
The frequencies of ACE genotypes according to MPI grades are summarized in Table 3. When the MPI grade is increased, a significant increase in the frequency of the D/D genotype was observed (MPI-1=37.3% vs. MPI-2=41.9% vs. MPI-3=46.4%; p=0.01).
No significant differences in the estimated allelic frequencies were also observed.
Logistic regression analysis, adjusted for gender, age, neurodegenerative diseases, cardiovascular diseases, cerebrovascular diseases, and neoplasia (Table 4)confirmed a significant association of the ACE D/D genotype with the higher MPI grade (MPI-3 vs. MPI-1, OR=1.42, 95% CI 1.05–1.92). No significant associations between ACE polymorphisms and 2-year mortality were found (D/D, HR=1.18, 95% CI 0.99–1.40, p=0.05). Adjusted logistic regression analysis carried out on the individual MPI domains showed significant associations of ACE D/D genotypes with co-morbidity (CIRS-3 vs. CIRS-1, OR=1.69, 95% CI 1.08–2.65) and with malnutrition (MNA-3 vs. MNA-1, OR=1.43, 95% CI 1.13–1.97).
Table 5 shows the combined APOE and ACE genetic status of patients divided according to their MPI grade. With the increasing of the MPI grade, a significant increase in the frequency of patients with both APOE 4+ allele and ACE D/D genotype was observed (MPI-1=5.3% vs. MPI-2=6.2% vs. MPI-3=13.5%; p < 0.001). As shown in Fig. 1, a and b, the risk of being in the MPI-3 group associated with APOE 4+ and ACE D/D genotypes was additive, without interaction. Adjusting for multiple confounders, the APOE 4+ and ACE D/D genotypes were associated with severe MPI grade (MPI-3 vs. MPI-1 + MPI-2, APOE 4+, OR=1.71, 95% CI 1.20–2.44, p=0.003; ACE D/D, OR=1.35, 95% CI 1.02–1.78, p=0.05). The combined APOE 4+ and ACE D/D genetic status was associated with higher MPI grade (MPI-3 vs. MPI-1 + MPI-2, OR=2.85, 95% CI 1.75–4.65; p < 0.001), without interaction. No other significant associations between APOE/ACE polymorphisms and severe MPI grade were found in this population.
Cox regression analyses, adjusted for gender, age, neurodegenerative, cardiovascular and cerebrovascular diseases, and neoplasia, confirmed no significant associations between combined APOE and ACE polymorphisms and 2-year mortality in this population (4+-D/D, HR=1.09, 95% CI 0.77–1.54, p=0.62).
In this study we investigated the association of the APOE and ACE polymorphisms on a global measure of health and functional status in a large population of hospitalized elderly patients. The multidimensional impairment was evaluated by a validated MPI for 1-year mortality, on the basis of data collected from a standardized CGA for hospitalized older patients. As previously demonstrated, this MPI accurately stratifies elderly patients into groups at varying risk of mortality independently from the diagnosis,1 as well as in elderly patients hospitalized for an acute gastrointestinal bleeding,17 pneumonia,18 and also dementia.19
The findings of the study demonstrated a significant association of the APOE 4+ allele and the ACE D/D genotype with a severe MPI grade; no association between APOE or ACE polymorphisms with mortality was found in this population. Previous studies reported controversial results on the relationship between APOE polymorphism and longevity,20 or the risk of vascular or nonvascular mortality21; recently, a significant association of the 4 allele with mortality, independently of cardiovascular disease but not of Alzheimer disease22 or cognitive impairment,10 has been reported.
Also the contribution of the ACE I/D polymorphism to mortality remains a matter of debate. Previous data reported a significant association between the D/D genotype or D allele and an increased risk of cardiovascular diseases and early mortality (below age 65 years), whereas there was no evidence of an association with mortality in subjects older than 65 years of age.23 Moreover, ACE polymorphisms may be involved in skeletal muscle structure and function throughout the renin–angiotensin system, and significant associations between the I/D polymorphism and functional decline or physical performance in older adults has been described.14 The age-related decline in muscle mass and quality, i.e., sarcopenia, is associated with functional impairment, increased disability, morbidity, and mortality,24 and, accordingly to a model of frailty, it may be an initial step of the frailty cascade.25 In agreement with some literature, the findings of our study may suggest a potential role of the APOE and ACE polymorphisms on frailty in the older patients, especially if frailty is considered in relation to the accumulation of deficits.2 Indeed, the MPI that we used to identify patients with a different 1-year mortality risk was based on data available from a standard CGA. This multidimensional approach is quite similar to a cumulative deficits approach to frailty.2 Recent data suggest that this cumulative deficits approach to frailty can precisely evaluate mortality risk in older people because it may capture the global susceptibility to multiple diseases and impairments that often affects frail older persons.26 The findings that the APOE and ACE polymorphisms were significantly associated with the aggregate MPI rather than with the individual domains used to construct the MPI indirectly confirms that tools that effectively identify individuals in a state of high vulnerability for adverse health outcomes, including low life expectancy, should take a multidimensional approach.27,28
Several studies investigated the synergistic effect between two or more genetic polymorphisms, but the results were conflicting. Although it appears that APOE and ACE may play an independent role in age-related diseases,29 a large case-control study on ischemic stroke revealed an interaction effect of the APOE 4 allele and ACE D/D genotype on mortality.30 In our study, the absence of interaction excluded any synergistic effect.
Because a role of APOE and ACE polymorphisms in neurodegenerative, cardiovascular, and cerebrovascular diseases as well as in cancer development and progression have been reported,31,32 in this study we adjusted all the analyses for age, gender, and all of the above-mentioned potential confounders. Results confirmed that the significant associations between APOE and ACE polymorphisms and multidimensional impairment may be independent from all these pathological conditions.
This study has some limitations. To identify patients with different mortality risks, we used a CGA-based MPI that was constructed and validated in hospitalized elderly patients.1 Thus, the results cannot be generalized to older people who are living in different settings, i.e., community dwelling or institutionalized. Moreover, a slight deviation from the Hardy–Weinberg equilibrium of the APOE genotypes observed in this population may potentially hamper the generalizability of the results. Furthermore, the study population was recruited within a single hospital. Larger multicenter studies are needed to confirm the findings.
In conclusion, data from this study suggest that APOE 4 and ACE D/D polymorphisms may be considered genetic markers of the multidimensional impairment of older people. This association seems to be independent from the most common age-related neurodegenerative, vascular, and neo-plastic pathologies. The mechanisms of their association remain undefined. These findings should be replicated in other populations.
This work was supported by grants from Ministero della Salute, IRCCS Research Program 2006-2008, Line 2: “Malattie di rilevanza sociale.” This research was supported in part by the Intramural Research Program of the National Institutes of Health, National Institute on Aging.
There are no competing interests to disclose.