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The effect of anemia and white matter hyperintensities (WMH) on cognitive impairment in patients with amnestic mild cognitive impairment (MCI)
Archives of Gerontology and Geriatrics 55 (2012) 251–256
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The effect of anemia and white matter hyperintensities (WMH) on cognitive impairment in patients with amnestic mild cognitive impairment (MCI) Sang Joon Son a,b, Kang Soo Lee c, Duk Lyul Na d, Sang Won Seo d, Chi Hun Kim d, Jong Hun Kim e, Byoung Hoon Oh a,b, Chang Hyung Hong f,g,* a
Department of Psychiatry, Yonsei University College of Medicine, Sungsan-ro 262, Seodaemun-gu, Shinchon-dong, Seoul 120-752, Republic of Korea Institute of Behavioral Science in Medicine, Severance Mental Health Hospital, Yonsei University College of Medicine, 696-6 Tanbul-dong, Gwangju-si, Gyeonggi-do 464-100, Republic of Korea c Department of Psychiatry, Kwandong University College of Medicine, Myongji Hospital, Hwajung-dong, Deokyang-gu, Goyang-si, Gyeonggi-do 412-270, Republic of Korea d Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Kangnam-ku, Seoul 135-710, Republic of Korea e Department of Neurology, Ilsan Hospital, National Health Insurance Corporation, Goyang-shi, Republic of Korea f Department of Psychiatry, Ajou University School of Medicine, San 5, Woncheon-dong, Yeongtong-gu, Suwon-si, Gyeonggi-do 443-721, Republic of Korea g Institute of Aging, Ajou University Medical Center, Suwon, Republic of Korea b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 8 July 2011 Received in revised form 20 October 2011 Accepted 21 October 2011 Available online 16 November 2011
Anemia and subcortical ischemic change might be associated with increased risks for cognitive impairment among the elderly. This study examined the associations among anemia, WMH and cognitive function in patients with amnestic MCI. We recruited 278 subjects with amnestic MCI from the Clinical Research Center for Dementia of South Korea (CREDOS), a hospital-based cohort study. A standardized neuropsychological battery, containing tests of language, visuospatial function, verbal memory and executive function, was used for all patients. Anemia was defined as a hemoglobin concentration below 12 g/dl for women and below 13 g/dl for men. The severity of WMH was also examined using brain magnetic resonance imaging (MRI). After multivariable adjustments, anemia and WMH were associated with poorer performance on cognitive function tests (anemia: Stroop test, F = 4.17, p = 0.042; WMH: Stroop test, F = 6.45, p = 0.002; Rey-complex figure test-copy, F = 4.08, p = 0.018). Moreover, a significant interaction between anemia and the severity of WMH was observed in performance on the Go/no go test (F = 4.50, p = 0.012) and the Stroop test (F = 3.36, p = 0.037). In post hoc analysis, anemic patients with severe WMH had significantly worse scores on measure of executive function (Go/no go test, p = 0.011; Stroop test, p = 0.001). Anemia and WMH had interactive effects on executive function impairment among the elderly with amnestic MCI. ß 2011 Elsevier Ireland Ltd. All rights reserved.
Keywords: Anemia Mild cognitive impairment MCI White matter hyperintensities Cognitive function
1. Introduction Anemia is prevalent among individuals aged 65 years and older (Guralnik et al., 2004). It is associated with many health problems among the elderly (Penninx et al., 2004). In recent studies, abnormal hemoglobin concentrations might be associated with an increased hazard for dementia and rapid cognitive decline among the elderly (Chaves et al., 2006; Shah et al., 2009, 2011; Faux et al., 2010; Terekeci et al., 2010). However, the studies were methodologically varied and the association between hemoglobin level and cognition was complex. So, further research into multiple factors between cognition and anemia needed to be carried out (Peters et al., 2008).
* Corresponding author. Tel.: +82 31 219 5180; fax: +82 31 219 5179. E-mail address: [email protected] (C.H. Hong). 0167-4943/$ – see front matter ß 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.archger.2011.10.015
Growing literatures suggested that the risk of Alzheimer disease increased with the number of cerebrovascular lesions; and thus, such lesions needed to be detected to prevent further cognitive decline among vulnerable populations (De la Torre, 2002a,b; Launer, 2002). Brain MRI studies have reported that WMH in periventricular white matter (PWM) and deep white matter (DWM) was strongly related to amnestic MCI (Luchsinger et al., 2009) and served as an independent predictor of cognitive decline (Verdelho et al., 2010). One potential mechanism underlying the association between anemia and cognition might be a chronic state of brain hypoxia (Croughwell et al., 1994). Despite a few studies having examined the relationship between anemia and cognitive function in older adults (Chaves et al., 2006; Lucca et al., 2008; Deal, 2009), they did not correct for cerebrovascular lesions such as WMH. Relatively little was known about the interactive effects between anemia and WMH on cognitive impairment. Moreover, to the best of our knowledge, no study about these associations has been conducted
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with amnestic MCI patients. The purpose of this study was to investigate the hypothesis that anemic subjects with severe WMH had greater cognitive impairment. In the current study, we investigated the associations between anemia, WMH and cognitive function in amnestic MCI patients. 2. Methods 2.1. Subjects This study was a part of ongoing CREDOS study: a large, prospective, hospital-based cohort study designed to assess the occurrence and risk factors of cognitive disorder since November 2005. The CREDOS study recruited consecutive patients who were diagnosed with normal cognition, subjective memory impairment, MCI, vascular cognitive impairment, Alzheimer disease or subcortical ischemic vascular dementia. More description about CREDOS was detailed in prior literature (Yoon et al., 2011). Of the 4451 CREDOS participants, we studied 278 patients who met the amnestic MCI criteria proposed by Petersen et al. (1999), and Winblad et al. (2004). The inclusion criteria for MCI were as follows: (1) patients with memory complaints; (2) normal functional activities (informant’s report of intact Activity Daily of Living (ADL)); (3) cognitive impairment (at least 1.0 standard deviation (SD) below age-and education-adjusted norms) in more than one cognitive domain (language, visuospatial function, verbal memory and frontal/executive function domains) on neuropsychological test (Ahn et al., 2010); (4) Clinical Dementia Rating (CDR) of 0.5 (Morris, 1993); and (5) not demented according to Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria. None of the subjects presented any of the following exclusion criteria: (1) a history of significant hearing or visual impairment rendering participation in the interview difficult; (2) neurological disorders (e.g., territorial infarction, intracranial hemorrhage, brain tumor, and hydrocephalus); (3) psychiatric disorders (e.g., schizophrenia, mental retardation, severe depression or mania); (4) psychotropic medications, or a history of use of psychoactive substances other than alcohol. (5) Subjects with physical illnesses or disorders that could interfere with the clinical study such as cardiac diseases, respiratory illnesses, uncontrolled diabetes, uncontrolled hypertension, malignancy, hepatic diseases and renal diseases were also excluded. This study was approved by the institutional review boards of the participating centers and informed consent was obtained from all subjects. 2.2. Clinical evaluations and cognitive assessments The clinical evaluation form was filled in by informants after they received appropriate instructions. The clinical evaluation form includes questionnaires related to: (1) basic demographic characteristics; (2) past medical history, including vascular risk factors, such as hypertension, diabetes mellitus, hyperlipidemia, and cardiac diseases (coronary heart disease, arrhythmia, heart failure, and valvular heart disease). Vascular risk factors were rated positive if the patient had either been diagnosed with associated disease previously or if the patient was currently under medical treatment for the disease; (3) Seoul Instrumental Activity Daily Living (S-IADL) (Ku et al., 2004); (4) the 15-item Geriatric Depression Scale (GDS-15) (Sheikh and Yesavage, 1986). All subjects had a clinical interview and blood tests on the same day. All blood parameters were analyzed according to standard protocols of the biochemistry laboratories that participated in the study, both of which operate under a rigorous quality control program. Anemia was defined according to the World Health Organization criteria as hemoglobin concentrations below 12 g/dl for women and below 13 g/dl for men (Beghe et al., 2004).
Estimated glomerular filtration rate (mL/min per 1.73 m2) was calculated using the Cockcroft–Gault equation (Cockcroft and Gault, 1976). Vitamin B12 and folate levels also were examined, and all participants had normal serum levels. Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared. A standardized neuropsychological battery, the Seoul Neuropsychological Screening Battery-Dementia (SNSB-D) Version was used to assess all participants (Ahn et al., 2010). The SNSB-D includes tests of language, visuospatial function, verbal memory and executive function domains. These four domains were assessed using the following tests: the Korean short version of the Boston Naming Test (K-BNT) for testing language, ReyComplex Figure Test-copy (RCFT-copy) for visuospatial function, the Rey-Complex Figure Test-delayed recall (RCFT-delayed recall) for visuospatial memory, the Seoul Verbal Learning Test-delayed recall (SVLT-delayed recall) for verbal memory, and the Stroop test-color reading and Go/no go test for frontal/executive function with (Ahn et al., 2010). 2.3. Measurement of WMH MRI was conducted in accordance with the protocol of MRI acquisition developed for CREDOS. The MRI scans included transaxial T2, T1-weighted, gradient-echo, fluid-attenuated inversion recovery (FLAIR), and coronal T1-weighted images. The severity of WMH was evaluated according to modified Fazekas et al. (1987) and Scheltens et al. (1993) criteria using the T2 axial or FLAIR images. WMH were separately examined in the PWM and DWM. Additionally, PWM and DWM ratings were combined to provide a final measurement of the severity of ischemia. DWM lesions were divided into D1 (DWM < 10 mm), D2 (between 10 mm and 25 mm), and D3 (25 mm) groups based on the longest diameter of the lesions. PWM lesions were classified into P1 (cap and band <5 mm), P2 (between 5 mm and 10 mm), and P3 (cap or band 10 mm) groups based on the size of the cap and band, which were perpendicular and horizontal to the ventricle, respectively. These results were combined to provide a total measurement of mild (D1P1, D1P2), moderate (neither mild nor severe group) or severe (D3P3). The inter-rater reliability for the PWM hyperintensity and DWM hyperintensity was good (intraclass correlation coefficient of 0.73–0.91). 2.4. Statistical analyses Categorical variables were analyzed utilizing chi-square tests or Fisher’s exact test. Continuous variables were analyzed with independent t-tests for each of the anemic groups. Additionally, general characteristics of the participants were examined based on WMH severity utilizing chi-square tests and analysis of variance (ANOVA). An analysis of covariance (ANCOVA) was conducted to analyze the interaction of the presence of anemia and WMH severity on cognitive test scores. To minimize the potential confounding effects of anemia and functional limitations in cognitive function, the following covariates were entered into the adjusted model, as was consistent with previous literature: age, gender, education level, estimated GFR (Model 1) (Astor et al., 2002; Atti et al., 2006; Kurella Tamura et al., 2008). Smoking status, hypertension status, diabetes mellitus status, hyperlipidemia status, cardiac diseases history, depression score and BMI were additionally adjusted in the fully adjusted model, considering relation between WMH and cognitive impairment (Model 2) (Lesser et al., 1996; Knopman, 2006; Stanek et al., 2011). Following ANCOVA, we performed a post hoc test to compare the differences in Go/no go test and Stroop test scores between anemic and nonanemic groups for each WMH level. A value of p < 0.05 was considered statistically significant. In post hoc tests, type I error
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Table 1 Characteristics of participants according to presence of anemia, n (%) or mean SD. Variable WMH Mild Moderate Severe Gender Male MCI type Amnestic single Physical illness Hypertension Diabetes Hyperlipidemia Cardiac disease Current smoking Yes Hb (gm/dl) Age (year) Education (year) BMI (kg/m2) Estimated GFR (ml/min/1.73 m2) GDS-15 S-IADL K-BNT RCFT-copy SVLT-delayed recall RCFT-delayed recall Stroop test-color reading Go/no go test
X2 or t
Anemic (N = 43)
Non-anemic (N = 235)
26 (60.5) 9 (20.9) 8 (18.6)
142 (60.4) 56 (23.8) 37 (15.7)
0.31
0.855
17 (39.5)
86 (36.6)
0.14
0.733
10 (23.3)
67 (28.5)
0.50
0.580
20 (46.5) 8 (18.6) 2 (4.7) 5 (11.6)
130 (55.3) 33 (14.0) 32 (13.6) 26 (11.1)
1.14 0.60 2.72 0.01
0.320 0.482 0.129 1.000
3 (7.0) 11.57 0.87 72.84 7.65 10.02 5.93 22.22 3.12 69.86 14.61 5.47 3.74 5.81 4.51 40.28 9.39 28.83 7.83 2.16 2.25 5.29 5.52 57.48 23.53 18.74 3.51
34 (14.5) 13.74 1.04 71.12 7.56 10.17 4.46 24.28 3.02 78.05 16.17 4.57 3.76 5.73 4.38 39.43 9.31 29.38 6.37 2.86 2.41 6.68 4.77 66.92 23.57 19.39 2.49
1.76 12.84 1.36 0.15 4.09 2.88 1.44 0.11 0.55 0.50 1.76 1.72 2.39 1.45
0.228 <0.001 0.172 0.881 <0.001 0.004 0.152 0.911 0.585 0.613 0.079 0.087 0.017 0.148
was adjusted using the Bonferroni method (0.05/3 = 0.0167). SPSS software, version 12.0 (SPSS Inc., Chicago, IL, USA) was used for all analyses. 3. Results Of the 278 participants, 103 were male (37.1%) and 175 were female (62.9%). The mean age of the sample was 71.38 7.58 (SD) years. The average educational level of the sample was 10.14 4.71 (SD) years.
p
Of the participants, 15.5% (N = 43) met inclusion criteria and were placed in the anemic group. All cases in the anemic group were found to have the normocytic–normochromic type of anemia. All anemic subjects had mild anemia (defined as a hemoglobin concentration of 10.0–11.9 g/dL in women and 10.0– 12.9 g/dL in men) (Tettamanti et al., 2010). Table 1 shows the characteristics of the anemic and non-anemic groups. After adjusting for age, gender, education level and estimated GFR, anemic patients displayed poorer performance on the Stroop test (F = 4.17, p = 0.042).
Table 2 Characteristics of participants according to WMH severity, n (%) or mean SD. Variable
Anemia Anemic Non-anemic Gender Male MCI type Amnestic single Physical illness Hypertension Diabetes Hyperlipidemia Cardiac disease Current smoking Yes Age (year) Education (year) BMI (kg/m2) Estimated GFR GDS-15 S-IADL K-BNT RCFT-copy SVLT-delayed recall RCFT-delayed recall Stroop test-color reading Go/no go test
X2 or F
WMH severity
p
Mild (N = 168)
Moderate (N = 65)
Severe (N = 45)
26 (15.5) 142 (84.5)
9 (13.8) 56 (86.2)
8 (17.8) 37 (82.2)
0.31
0.855
60 (35.7)
27 (41.5)
16 (35.6)
0.73
0.693
54 (32.1)
15 (23.1)
8 (17.8)
4.56
0.102
77 21 17 18
41 (63.1) 9 (13.8) 9 (13.4) 10 (15.4)
32 (71.1) 11 (24.4) 8 (16.7) 3 (6.7)
11.97 4.08 1.46 2.12
0.003 0.130 0.481 0.346
10 (15.4) 74.11 7.12 9.99 4.11 24.22 3.45 74.54 15.40 4.78 3.47 5.62 4.25 37.78 9.09 29.55 6.18 2.72 2.20 6.42 5.19 58.80 24.56 19.00 3.25
6 (13.3) 73.38 5.59 10.52 5.37 23.75 2.97 76.51 14.29 4.53 3.89 6.16 4.84 37.93 10.65 27.41 7.32 2.71 2.70 5.87 4.64 54.29 21.93 19.09 3.09
0.34 10.04 0.19 0.35 0.90 0.06 0.24 3.16 2.21 0.02 0.44 11.63 0.82
0.844 <0.001 0.831 0.704 0.406 0.939 0.787 0.044 0.112 0.982 0.642 <0.001 0.443
(45.8) (12.5) (10.4) (10.7)
21 (12.5) 69.80 7.82 10.10 4.75 29.91 3.04 77.84 16.94 4.73 3.87 5.68 4.35 40.69 8.88 29.70 6.51 2.77 2.39 6.64 4.89 70.65 22.50 19.45 2.29
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According to WMH severity ratings, all participants were classified into mild (N = 168, 60.4%), moderate (N = 65, 23.4%), or severe (N = 45, 16.2%) groups. There were no significant differences in the frequency of anemia associated with WMH severity (X2 = 0.3, p = 0.855). Table 2 lists the characteristics of the participants in each of the WMH severity groups. After adjusting for age, gender, education level, depression score, BMI, smoking status, history of hypertension, diabetes mellitus, hyperlipidemia, and other cardiac diseases, significant between group differences were observed in RCFT-copy scores (F = 4.08, p = 0.018, mild group score > severe group score) and Stroop test scores (F = 6.45, p = 0.002; mild group score > severe group score). Using ANCOVA, the interaction of anemia status and WMH severity on cognitive test scores was examined, after adjusting for gender, education level, estimated GFR (Model 1) (Table 3). Interactive effects were observed on executive function (Go/no go test: F = 4.90, p = 0.008, R2 = 0.07; Stroop test: F = 3.51, p = 0.031, R2 = 0.19). In post hoc test, anemic and non-anemic groups showed significant difference in estimated least squares means of Go/no go and Stroop tests scores for severe WMH level compared to mild WMH level (Go/no go test: mild-severe level, p = 0.011; Stroop test: mild-severe level, p = 0.001) (Fig. 1). Even when confounding effects of cerebrovascular risk factors (Model 2) were considered together, the overall results were unaffected (Go/no go test: F = 4.50, p = 0.012, R2 = 0.11; Stroop test: F = 3.36, p = 0.037, R2 = 0.18) (Table 3).
Table 3 Cognitive test scores according to presence of anemia and WMH severity, n (%) or mean SD. Variable
WMH severity Mild
K-BNT 39.08 10.12 Anemic Non-anemic 40.99 8.65 RCFT-copy Anemic 28.37 8.48 Non-anemic 29.94 6.08 SVLT-delayed recall Anemic 2.50 2.18 Non-anemic 2.82 2.43 RCFT-delayed recall Anemic 5.22 5.51 Non-anemic 6.90 4.74 Stroop test-color reading*,y Anemic 62.88 20.97 Non-anemic 72.08 22.55 Go/no go test*,y Anemic 19.73 0.53 Non-anemic 19.40 2.48
Moderate
Severe
40.56 5.57 37.34 9.50
43.88 10.40 36.65 10.39
26.83 8.15 29.98 5.78
32.56 3.58 26.30 7.47
0.89 1.54 3.02 2.16
2.50 2.83 2.76 2.71
4.72 7.79 6.70 4.68
6.13 1.96 5.81 5.06
58.25 24.08 60.02 24.84
39.13 24.46 57.57 20.23
17.33 4.24 19.27 3.02
17.13 6.56 19.51 1.50
* p < 0.05 by ANCOVA showing interactive effects on cognitive functions between anemia and WMH severity, after adjusting for age, gender, education level and estimated GFR (Model 1). y p < 0.05 by ANCOVA showing interactive effects on cognitive functions between anemia and WMH severity, after adjusting for Model 1 + BMI, hypertension, diabetes mellitus, hyperlipidemia, cardiac diseases, smoking and GDS-15 score (Model 2).
4. Discussion This was the study examining the association between anemia, WMH, and cognitive function among subjects with amnestic MCI. Our results revealed significant differences in cognitive test scores between anemic and non-anemic groups and among WMH severity groups independently in the elderly with amnestic MCI. Moreover, we observed an interactive effect on executive function impairment between anemia and WMH. This interaction was robust even after adjusting for various confounding variables. Several studies reported association between anemia and cognitive function. According to the Women’s Health and Aging Study II (Chaves et al., 2006; Deal et al., 2009), anemia was
associated with poorer performance of executive function tests. A recent study reported an association between mild anemia and impaired selective attention performance (Lucca et al., 2008). Meanwhile, WMH induced by chronic hypoxia was also reported to be an independent predictor of cognitive decline among the elderly in the Leukoaraiosis and Disability prospective multinational European study (LADIS) (Verdelho et al., 2010). Furthermore, our study showed that anemic MCI persons with severe WMH had significantly worse scores on measurement of executive function. This interactive effect might be explained by a failure of compensatory mechanisms under brain hypoxic conditions (Appelman et al., 2010). In healthy or asymptomatic populations,
Fig. 1. The estimated least squares means of Go/no go test and Stroop test scores for each WMH severity according to anemia group after adjustment for confounding variables.
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cerebral vasomotor reactivity in response to a vasodilator stimulus might serve to maintain constant cerebral flow (Kobayashi et al., 1991; Matsuo et al., 2005). Anemia might reduce the effects of this regulatory mechanism and severely exacerbate brain hypo-oxygenation. It was postulated that maximally dilated cerebral vessels due to chronic anemia was unable to dilate further under additional hypercapnic conditions (Kuwabara et al., 2002). Anemia might also result in structural alterations to the cerebral vessels, resulting in reduced vasodilatory capacity (Kuwabara et al., 2002; Inzitari et al., 2008). Another explanation might lie with the negative effect of anemia on subcortical ischemic change. Inzitari et al. (2008) reported that anemia might contribute to worsening of WMH among older adults with high blood pressure. Alternatively, anemia might be viewed as an indicator of pathological processes associated with chronic cerebral hypoperfusion in the frontal cortex (Saxton et al., 2000; Pugh et al., 2003) or neurodegeneration (Faux et al., 2010). Changes in activities of daily living among cognitively impaired elderly individuals might increase nutritional risk, and nutritional deficiencies, thereby, might potentially result in anemia in older adults (Mitrache et al., 2001; Lee et al., 2010). There were several limitations to this study. First, the crosssectional and observational nature of the study did not allow for examination of the nature of the causal relationship between anemia, WMH and the dependent variables. Second, measuring anemia at a single time point might lead clinicians to underestimate or overestimate of the risk of cognitive decline associated with anemia. Third, these effects were not examined in anemia subtypes other than the normocytic–normochromic subtype. Fourth, we did not find an association between anemia and WMH. However, this may have resulted from the small sample size of anemic subjects. We also could not separately evaluate the non-ischemic origin WMH associated with subependymal gliosis and discontinuity of the ependymal lining (Fazekas et al., 1993). Additionally, subtle correlations between memory function and anemia might have been overlooked, as the participants in this study were presented with objective memory impairments regardless of hemoglobin concentrations. In conclusion, anemia and WMH had interactive effects on executive function impairment among individuals with amnestic MCI. Whether these associations were causal or not has remained to be elucidated. Nevertheless, the outcomes of this study had some implications for future research Normocytic–normochromic anemia associated with aging process and age-related chronic disease was very frequently found in older population (Elis et al., 1996), and the treatment of anemia might be viewed as one way to prevent or postpone cognitive impairments among an aged population (Peters et al., 2008). In that regard, this study could provide preliminary evidence for the hypothesis that anemia might aggravate cognitive impairment, in combination with cerebrovascular changes such as WMH in amnestic MCI patients. These results supported the potential value of further research examining the association between anemia, WMH and cognition in the elderly. Conflict of interest None. Role of the funding source The sponsors did not have any role in the design, methods, subject recruitment, data collection, analysis, or preparation of this paper. Acknowledgement This study was supported by a grant of the Korea Healthcare Technology R&D Project, Ministry of Health and Welfare, Republic of Korea (A102065).
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The effect of anemia and white matter hyperintensities (WMH) on cognitive impairment in patients with amnestic mild cognitive impairment (MCI) Sang Joon Son a,b, Kang Soo Lee c, Duk Lyul Na d, Sang Won Seo d, Chi Hun Kim d, Jong Hun Kim e, Byoung Hoon Oh a,b, Chang Hyung Hong f,g,* a
Department of Psychiatry, Yonsei University College of Medicine, Sungsan-ro 262, Seodaemun-gu, Shinchon-dong, Seoul 120-752, Republic of Korea Institute of Behavioral Science in Medicine, Severance Mental Health Hospital, Yonsei University College of Medicine, 696-6 Tanbul-dong, Gwangju-si, Gyeonggi-do 464-100, Republic of Korea c Department of Psychiatry, Kwandong University College of Medicine, Myongji Hospital, Hwajung-dong, Deokyang-gu, Goyang-si, Gyeonggi-do 412-270, Republic of Korea d Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Kangnam-ku, Seoul 135-710, Republic of Korea e Department of Neurology, Ilsan Hospital, National Health Insurance Corporation, Goyang-shi, Republic of Korea f Department of Psychiatry, Ajou University School of Medicine, San 5, Woncheon-dong, Yeongtong-gu, Suwon-si, Gyeonggi-do 443-721, Republic of Korea g Institute of Aging, Ajou University Medical Center, Suwon, Republic of Korea b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 8 July 2011 Received in revised form 20 October 2011 Accepted 21 October 2011 Available online 16 November 2011
Anemia and subcortical ischemic change might be associated with increased risks for cognitive impairment among the elderly. This study examined the associations among anemia, WMH and cognitive function in patients with amnestic MCI. We recruited 278 subjects with amnestic MCI from the Clinical Research Center for Dementia of South Korea (CREDOS), a hospital-based cohort study. A standardized neuropsychological battery, containing tests of language, visuospatial function, verbal memory and executive function, was used for all patients. Anemia was defined as a hemoglobin concentration below 12 g/dl for women and below 13 g/dl for men. The severity of WMH was also examined using brain magnetic resonance imaging (MRI). After multivariable adjustments, anemia and WMH were associated with poorer performance on cognitive function tests (anemia: Stroop test, F = 4.17, p = 0.042; WMH: Stroop test, F = 6.45, p = 0.002; Rey-complex figure test-copy, F = 4.08, p = 0.018). Moreover, a significant interaction between anemia and the severity of WMH was observed in performance on the Go/no go test (F = 4.50, p = 0.012) and the Stroop test (F = 3.36, p = 0.037). In post hoc analysis, anemic patients with severe WMH had significantly worse scores on measure of executive function (Go/no go test, p = 0.011; Stroop test, p = 0.001). Anemia and WMH had interactive effects on executive function impairment among the elderly with amnestic MCI. ß 2011 Elsevier Ireland Ltd. All rights reserved.
Keywords: Anemia Mild cognitive impairment MCI White matter hyperintensities Cognitive function
1. Introduction Anemia is prevalent among individuals aged 65 years and older (Guralnik et al., 2004). It is associated with many health problems among the elderly (Penninx et al., 2004). In recent studies, abnormal hemoglobin concentrations might be associated with an increased hazard for dementia and rapid cognitive decline among the elderly (Chaves et al., 2006; Shah et al., 2009, 2011; Faux et al., 2010; Terekeci et al., 2010). However, the studies were methodologically varied and the association between hemoglobin level and cognition was complex. So, further research into multiple factors between cognition and anemia needed to be carried out (Peters et al., 2008).
* Corresponding author. Tel.: +82 31 219 5180; fax: +82 31 219 5179. E-mail address: [email protected] (C.H. Hong). 0167-4943/$ – see front matter ß 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.archger.2011.10.015
Growing literatures suggested that the risk of Alzheimer disease increased with the number of cerebrovascular lesions; and thus, such lesions needed to be detected to prevent further cognitive decline among vulnerable populations (De la Torre, 2002a,b; Launer, 2002). Brain MRI studies have reported that WMH in periventricular white matter (PWM) and deep white matter (DWM) was strongly related to amnestic MCI (Luchsinger et al., 2009) and served as an independent predictor of cognitive decline (Verdelho et al., 2010). One potential mechanism underlying the association between anemia and cognition might be a chronic state of brain hypoxia (Croughwell et al., 1994). Despite a few studies having examined the relationship between anemia and cognitive function in older adults (Chaves et al., 2006; Lucca et al., 2008; Deal, 2009), they did not correct for cerebrovascular lesions such as WMH. Relatively little was known about the interactive effects between anemia and WMH on cognitive impairment. Moreover, to the best of our knowledge, no study about these associations has been conducted
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with amnestic MCI patients. The purpose of this study was to investigate the hypothesis that anemic subjects with severe WMH had greater cognitive impairment. In the current study, we investigated the associations between anemia, WMH and cognitive function in amnestic MCI patients. 2. Methods 2.1. Subjects This study was a part of ongoing CREDOS study: a large, prospective, hospital-based cohort study designed to assess the occurrence and risk factors of cognitive disorder since November 2005. The CREDOS study recruited consecutive patients who were diagnosed with normal cognition, subjective memory impairment, MCI, vascular cognitive impairment, Alzheimer disease or subcortical ischemic vascular dementia. More description about CREDOS was detailed in prior literature (Yoon et al., 2011). Of the 4451 CREDOS participants, we studied 278 patients who met the amnestic MCI criteria proposed by Petersen et al. (1999), and Winblad et al. (2004). The inclusion criteria for MCI were as follows: (1) patients with memory complaints; (2) normal functional activities (informant’s report of intact Activity Daily of Living (ADL)); (3) cognitive impairment (at least 1.0 standard deviation (SD) below age-and education-adjusted norms) in more than one cognitive domain (language, visuospatial function, verbal memory and frontal/executive function domains) on neuropsychological test (Ahn et al., 2010); (4) Clinical Dementia Rating (CDR) of 0.5 (Morris, 1993); and (5) not demented according to Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria. None of the subjects presented any of the following exclusion criteria: (1) a history of significant hearing or visual impairment rendering participation in the interview difficult; (2) neurological disorders (e.g., territorial infarction, intracranial hemorrhage, brain tumor, and hydrocephalus); (3) psychiatric disorders (e.g., schizophrenia, mental retardation, severe depression or mania); (4) psychotropic medications, or a history of use of psychoactive substances other than alcohol. (5) Subjects with physical illnesses or disorders that could interfere with the clinical study such as cardiac diseases, respiratory illnesses, uncontrolled diabetes, uncontrolled hypertension, malignancy, hepatic diseases and renal diseases were also excluded. This study was approved by the institutional review boards of the participating centers and informed consent was obtained from all subjects. 2.2. Clinical evaluations and cognitive assessments The clinical evaluation form was filled in by informants after they received appropriate instructions. The clinical evaluation form includes questionnaires related to: (1) basic demographic characteristics; (2) past medical history, including vascular risk factors, such as hypertension, diabetes mellitus, hyperlipidemia, and cardiac diseases (coronary heart disease, arrhythmia, heart failure, and valvular heart disease). Vascular risk factors were rated positive if the patient had either been diagnosed with associated disease previously or if the patient was currently under medical treatment for the disease; (3) Seoul Instrumental Activity Daily Living (S-IADL) (Ku et al., 2004); (4) the 15-item Geriatric Depression Scale (GDS-15) (Sheikh and Yesavage, 1986). All subjects had a clinical interview and blood tests on the same day. All blood parameters were analyzed according to standard protocols of the biochemistry laboratories that participated in the study, both of which operate under a rigorous quality control program. Anemia was defined according to the World Health Organization criteria as hemoglobin concentrations below 12 g/dl for women and below 13 g/dl for men (Beghe et al., 2004).
Estimated glomerular filtration rate (mL/min per 1.73 m2) was calculated using the Cockcroft–Gault equation (Cockcroft and Gault, 1976). Vitamin B12 and folate levels also were examined, and all participants had normal serum levels. Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared. A standardized neuropsychological battery, the Seoul Neuropsychological Screening Battery-Dementia (SNSB-D) Version was used to assess all participants (Ahn et al., 2010). The SNSB-D includes tests of language, visuospatial function, verbal memory and executive function domains. These four domains were assessed using the following tests: the Korean short version of the Boston Naming Test (K-BNT) for testing language, ReyComplex Figure Test-copy (RCFT-copy) for visuospatial function, the Rey-Complex Figure Test-delayed recall (RCFT-delayed recall) for visuospatial memory, the Seoul Verbal Learning Test-delayed recall (SVLT-delayed recall) for verbal memory, and the Stroop test-color reading and Go/no go test for frontal/executive function with (Ahn et al., 2010). 2.3. Measurement of WMH MRI was conducted in accordance with the protocol of MRI acquisition developed for CREDOS. The MRI scans included transaxial T2, T1-weighted, gradient-echo, fluid-attenuated inversion recovery (FLAIR), and coronal T1-weighted images. The severity of WMH was evaluated according to modified Fazekas et al. (1987) and Scheltens et al. (1993) criteria using the T2 axial or FLAIR images. WMH were separately examined in the PWM and DWM. Additionally, PWM and DWM ratings were combined to provide a final measurement of the severity of ischemia. DWM lesions were divided into D1 (DWM < 10 mm), D2 (between 10 mm and 25 mm), and D3 (25 mm) groups based on the longest diameter of the lesions. PWM lesions were classified into P1 (cap and band <5 mm), P2 (between 5 mm and 10 mm), and P3 (cap or band 10 mm) groups based on the size of the cap and band, which were perpendicular and horizontal to the ventricle, respectively. These results were combined to provide a total measurement of mild (D1P1, D1P2), moderate (neither mild nor severe group) or severe (D3P3). The inter-rater reliability for the PWM hyperintensity and DWM hyperintensity was good (intraclass correlation coefficient of 0.73–0.91). 2.4. Statistical analyses Categorical variables were analyzed utilizing chi-square tests or Fisher’s exact test. Continuous variables were analyzed with independent t-tests for each of the anemic groups. Additionally, general characteristics of the participants were examined based on WMH severity utilizing chi-square tests and analysis of variance (ANOVA). An analysis of covariance (ANCOVA) was conducted to analyze the interaction of the presence of anemia and WMH severity on cognitive test scores. To minimize the potential confounding effects of anemia and functional limitations in cognitive function, the following covariates were entered into the adjusted model, as was consistent with previous literature: age, gender, education level, estimated GFR (Model 1) (Astor et al., 2002; Atti et al., 2006; Kurella Tamura et al., 2008). Smoking status, hypertension status, diabetes mellitus status, hyperlipidemia status, cardiac diseases history, depression score and BMI were additionally adjusted in the fully adjusted model, considering relation between WMH and cognitive impairment (Model 2) (Lesser et al., 1996; Knopman, 2006; Stanek et al., 2011). Following ANCOVA, we performed a post hoc test to compare the differences in Go/no go test and Stroop test scores between anemic and nonanemic groups for each WMH level. A value of p < 0.05 was considered statistically significant. In post hoc tests, type I error
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Table 1 Characteristics of participants according to presence of anemia, n (%) or mean SD. Variable WMH Mild Moderate Severe Gender Male MCI type Amnestic single Physical illness Hypertension Diabetes Hyperlipidemia Cardiac disease Current smoking Yes Hb (gm/dl) Age (year) Education (year) BMI (kg/m2) Estimated GFR (ml/min/1.73 m2) GDS-15 S-IADL K-BNT RCFT-copy SVLT-delayed recall RCFT-delayed recall Stroop test-color reading Go/no go test
X2 or t
Anemic (N = 43)
Non-anemic (N = 235)
26 (60.5) 9 (20.9) 8 (18.6)
142 (60.4) 56 (23.8) 37 (15.7)
0.31
0.855
17 (39.5)
86 (36.6)
0.14
0.733
10 (23.3)
67 (28.5)
0.50
0.580
20 (46.5) 8 (18.6) 2 (4.7) 5 (11.6)
130 (55.3) 33 (14.0) 32 (13.6) 26 (11.1)
1.14 0.60 2.72 0.01
0.320 0.482 0.129 1.000
3 (7.0) 11.57 0.87 72.84 7.65 10.02 5.93 22.22 3.12 69.86 14.61 5.47 3.74 5.81 4.51 40.28 9.39 28.83 7.83 2.16 2.25 5.29 5.52 57.48 23.53 18.74 3.51
34 (14.5) 13.74 1.04 71.12 7.56 10.17 4.46 24.28 3.02 78.05 16.17 4.57 3.76 5.73 4.38 39.43 9.31 29.38 6.37 2.86 2.41 6.68 4.77 66.92 23.57 19.39 2.49
1.76 12.84 1.36 0.15 4.09 2.88 1.44 0.11 0.55 0.50 1.76 1.72 2.39 1.45
0.228 <0.001 0.172 0.881 <0.001 0.004 0.152 0.911 0.585 0.613 0.079 0.087 0.017 0.148
was adjusted using the Bonferroni method (0.05/3 = 0.0167). SPSS software, version 12.0 (SPSS Inc., Chicago, IL, USA) was used for all analyses. 3. Results Of the 278 participants, 103 were male (37.1%) and 175 were female (62.9%). The mean age of the sample was 71.38 7.58 (SD) years. The average educational level of the sample was 10.14 4.71 (SD) years.
p
Of the participants, 15.5% (N = 43) met inclusion criteria and were placed in the anemic group. All cases in the anemic group were found to have the normocytic–normochromic type of anemia. All anemic subjects had mild anemia (defined as a hemoglobin concentration of 10.0–11.9 g/dL in women and 10.0– 12.9 g/dL in men) (Tettamanti et al., 2010). Table 1 shows the characteristics of the anemic and non-anemic groups. After adjusting for age, gender, education level and estimated GFR, anemic patients displayed poorer performance on the Stroop test (F = 4.17, p = 0.042).
Table 2 Characteristics of participants according to WMH severity, n (%) or mean SD. Variable
Anemia Anemic Non-anemic Gender Male MCI type Amnestic single Physical illness Hypertension Diabetes Hyperlipidemia Cardiac disease Current smoking Yes Age (year) Education (year) BMI (kg/m2) Estimated GFR GDS-15 S-IADL K-BNT RCFT-copy SVLT-delayed recall RCFT-delayed recall Stroop test-color reading Go/no go test
X2 or F
WMH severity
p
Mild (N = 168)
Moderate (N = 65)
Severe (N = 45)
26 (15.5) 142 (84.5)
9 (13.8) 56 (86.2)
8 (17.8) 37 (82.2)
0.31
0.855
60 (35.7)
27 (41.5)
16 (35.6)
0.73
0.693
54 (32.1)
15 (23.1)
8 (17.8)
4.56
0.102
77 21 17 18
41 (63.1) 9 (13.8) 9 (13.4) 10 (15.4)
32 (71.1) 11 (24.4) 8 (16.7) 3 (6.7)
11.97 4.08 1.46 2.12
0.003 0.130 0.481 0.346
10 (15.4) 74.11 7.12 9.99 4.11 24.22 3.45 74.54 15.40 4.78 3.47 5.62 4.25 37.78 9.09 29.55 6.18 2.72 2.20 6.42 5.19 58.80 24.56 19.00 3.25
6 (13.3) 73.38 5.59 10.52 5.37 23.75 2.97 76.51 14.29 4.53 3.89 6.16 4.84 37.93 10.65 27.41 7.32 2.71 2.70 5.87 4.64 54.29 21.93 19.09 3.09
0.34 10.04 0.19 0.35 0.90 0.06 0.24 3.16 2.21 0.02 0.44 11.63 0.82
0.844 <0.001 0.831 0.704 0.406 0.939 0.787 0.044 0.112 0.982 0.642 <0.001 0.443
(45.8) (12.5) (10.4) (10.7)
21 (12.5) 69.80 7.82 10.10 4.75 29.91 3.04 77.84 16.94 4.73 3.87 5.68 4.35 40.69 8.88 29.70 6.51 2.77 2.39 6.64 4.89 70.65 22.50 19.45 2.29
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According to WMH severity ratings, all participants were classified into mild (N = 168, 60.4%), moderate (N = 65, 23.4%), or severe (N = 45, 16.2%) groups. There were no significant differences in the frequency of anemia associated with WMH severity (X2 = 0.3, p = 0.855). Table 2 lists the characteristics of the participants in each of the WMH severity groups. After adjusting for age, gender, education level, depression score, BMI, smoking status, history of hypertension, diabetes mellitus, hyperlipidemia, and other cardiac diseases, significant between group differences were observed in RCFT-copy scores (F = 4.08, p = 0.018, mild group score > severe group score) and Stroop test scores (F = 6.45, p = 0.002; mild group score > severe group score). Using ANCOVA, the interaction of anemia status and WMH severity on cognitive test scores was examined, after adjusting for gender, education level, estimated GFR (Model 1) (Table 3). Interactive effects were observed on executive function (Go/no go test: F = 4.90, p = 0.008, R2 = 0.07; Stroop test: F = 3.51, p = 0.031, R2 = 0.19). In post hoc test, anemic and non-anemic groups showed significant difference in estimated least squares means of Go/no go and Stroop tests scores for severe WMH level compared to mild WMH level (Go/no go test: mild-severe level, p = 0.011; Stroop test: mild-severe level, p = 0.001) (Fig. 1). Even when confounding effects of cerebrovascular risk factors (Model 2) were considered together, the overall results were unaffected (Go/no go test: F = 4.50, p = 0.012, R2 = 0.11; Stroop test: F = 3.36, p = 0.037, R2 = 0.18) (Table 3).
Table 3 Cognitive test scores according to presence of anemia and WMH severity, n (%) or mean SD. Variable
WMH severity Mild
K-BNT 39.08 10.12 Anemic Non-anemic 40.99 8.65 RCFT-copy Anemic 28.37 8.48 Non-anemic 29.94 6.08 SVLT-delayed recall Anemic 2.50 2.18 Non-anemic 2.82 2.43 RCFT-delayed recall Anemic 5.22 5.51 Non-anemic 6.90 4.74 Stroop test-color reading*,y Anemic 62.88 20.97 Non-anemic 72.08 22.55 Go/no go test*,y Anemic 19.73 0.53 Non-anemic 19.40 2.48
Moderate
Severe
40.56 5.57 37.34 9.50
43.88 10.40 36.65 10.39
26.83 8.15 29.98 5.78
32.56 3.58 26.30 7.47
0.89 1.54 3.02 2.16
2.50 2.83 2.76 2.71
4.72 7.79 6.70 4.68
6.13 1.96 5.81 5.06
58.25 24.08 60.02 24.84
39.13 24.46 57.57 20.23
17.33 4.24 19.27 3.02
17.13 6.56 19.51 1.50
* p < 0.05 by ANCOVA showing interactive effects on cognitive functions between anemia and WMH severity, after adjusting for age, gender, education level and estimated GFR (Model 1). y p < 0.05 by ANCOVA showing interactive effects on cognitive functions between anemia and WMH severity, after adjusting for Model 1 + BMI, hypertension, diabetes mellitus, hyperlipidemia, cardiac diseases, smoking and GDS-15 score (Model 2).
4. Discussion This was the study examining the association between anemia, WMH, and cognitive function among subjects with amnestic MCI. Our results revealed significant differences in cognitive test scores between anemic and non-anemic groups and among WMH severity groups independently in the elderly with amnestic MCI. Moreover, we observed an interactive effect on executive function impairment between anemia and WMH. This interaction was robust even after adjusting for various confounding variables. Several studies reported association between anemia and cognitive function. According to the Women’s Health and Aging Study II (Chaves et al., 2006; Deal et al., 2009), anemia was
associated with poorer performance of executive function tests. A recent study reported an association between mild anemia and impaired selective attention performance (Lucca et al., 2008). Meanwhile, WMH induced by chronic hypoxia was also reported to be an independent predictor of cognitive decline among the elderly in the Leukoaraiosis and Disability prospective multinational European study (LADIS) (Verdelho et al., 2010). Furthermore, our study showed that anemic MCI persons with severe WMH had significantly worse scores on measurement of executive function. This interactive effect might be explained by a failure of compensatory mechanisms under brain hypoxic conditions (Appelman et al., 2010). In healthy or asymptomatic populations,
Fig. 1. The estimated least squares means of Go/no go test and Stroop test scores for each WMH severity according to anemia group after adjustment for confounding variables.
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cerebral vasomotor reactivity in response to a vasodilator stimulus might serve to maintain constant cerebral flow (Kobayashi et al., 1991; Matsuo et al., 2005). Anemia might reduce the effects of this regulatory mechanism and severely exacerbate brain hypo-oxygenation. It was postulated that maximally dilated cerebral vessels due to chronic anemia was unable to dilate further under additional hypercapnic conditions (Kuwabara et al., 2002). Anemia might also result in structural alterations to the cerebral vessels, resulting in reduced vasodilatory capacity (Kuwabara et al., 2002; Inzitari et al., 2008). Another explanation might lie with the negative effect of anemia on subcortical ischemic change. Inzitari et al. (2008) reported that anemia might contribute to worsening of WMH among older adults with high blood pressure. Alternatively, anemia might be viewed as an indicator of pathological processes associated with chronic cerebral hypoperfusion in the frontal cortex (Saxton et al., 2000; Pugh et al., 2003) or neurodegeneration (Faux et al., 2010). Changes in activities of daily living among cognitively impaired elderly individuals might increase nutritional risk, and nutritional deficiencies, thereby, might potentially result in anemia in older adults (Mitrache et al., 2001; Lee et al., 2010). There were several limitations to this study. First, the crosssectional and observational nature of the study did not allow for examination of the nature of the causal relationship between anemia, WMH and the dependent variables. Second, measuring anemia at a single time point might lead clinicians to underestimate or overestimate of the risk of cognitive decline associated with anemia. Third, these effects were not examined in anemia subtypes other than the normocytic–normochromic subtype. Fourth, we did not find an association between anemia and WMH. However, this may have resulted from the small sample size of anemic subjects. We also could not separately evaluate the non-ischemic origin WMH associated with subependymal gliosis and discontinuity of the ependymal lining (Fazekas et al., 1993). Additionally, subtle correlations between memory function and anemia might have been overlooked, as the participants in this study were presented with objective memory impairments regardless of hemoglobin concentrations. In conclusion, anemia and WMH had interactive effects on executive function impairment among individuals with amnestic MCI. Whether these associations were causal or not has remained to be elucidated. Nevertheless, the outcomes of this study had some implications for future research Normocytic–normochromic anemia associated with aging process and age-related chronic disease was very frequently found in older population (Elis et al., 1996), and the treatment of anemia might be viewed as one way to prevent or postpone cognitive impairments among an aged population (Peters et al., 2008). In that regard, this study could provide preliminary evidence for the hypothesis that anemia might aggravate cognitive impairment, in combination with cerebrovascular changes such as WMH in amnestic MCI patients. These results supported the potential value of further research examining the association between anemia, WMH and cognition in the elderly. Conflict of interest None. Role of the funding source The sponsors did not have any role in the design, methods, subject recruitment, data collection, analysis, or preparation of this paper. Acknowledgement This study was supported by a grant of the Korea Healthcare Technology R&D Project, Ministry of Health and Welfare, Republic of Korea (A102065).
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