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High neutrophil to lymphocyte ratio is associated with white matter hyperintensity in a healthy population
Journal of the Neurological Sciences 380 (2017) 128–131
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High neutrophil to lymphocyte ratio is associated with white matter hyperintensity in a healthy population Ki-Woong Nam a, Hyung-Min Kwon c,⁎,1, Han-Yeong Jeong a, Jin-Ho Park b,⁎⁎, Sang Hyuck Kim b, Su-Min Jeong b, Tae Gon Yoo b, Shinhye Kim b a b c
Department of Neurology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea Family Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea Department of Neurology, Seoul National University College of Medicine, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Republic of Korea
a r t i c l e
i n f o
Article history: Received 17 May 2017 Received in revised form 22 June 2017 Accepted 17 July 2017 Available online 19 July 2017 Keywords: Leukoaraiosis Inflammation Small vessel disease White blood cell Neutrophil Lymphocyte
a b s t r a c t High neutrophil to lymphocyte ratio (NLR) is correlated with the occurrence, morbidity and mortality of cerebrovascular disease as a marker of systemic inflammation. However, its effect on cerebral white matter hyperintensity (WMH) is unclear. We investigated high NLR burden as a surrogate marker of WMH volume in a healthy population. Healthy subjects with voluntary health check-ups between January 2006 and December 2013, including brain MRI and laboratory examination, were collected. WMH volumes were rated quantitatively. A total of 2875 subjects were enrolled, and the mean volume of WMH was 2.63 ± 6.26 mL. In multivariate linear regression analysis, NLR [β = 0.191, 95% confidence interval (CI) = 0.104 to 0.279, P b 0.001] remained significant after adjusting for confounders. Age (β = 0.049, 95% CI = 0.045 to 0.054, P b 0.001), hypertension (β = 0.191, 95% CI = 0.101 to 0.281, P b 0.001), diabetes (β = 0.153, 95% CI = 0.045 to 0.261, P = 0.006), and extracranial atherosclerosis (β = 0.348, 95% CI = 0.007 to 0.688, P = 0.045) were also significant independently from NLR. Additionally, the high NLR group (NLR ≥ 1.52) was related to male sex, hypertension, diabetes, current smoking, extracranial atherosclerosis, silent brain infarct, and high WMH volumes. In conclusion, high NLR is associated with larger WMH volumes in a healthy population. Assessment of NLR may be helpful in detecting cerebral WMH burdens in high risk groups. © 2017 Published by Elsevier B.V.
1. Introduction Cerebral white matter hyperintensity (WMH) is a pathologic marker of tissue rarefaction, commonly found in the elderly, especially those with vascular risk factors or symptomatic cerebrovascular disease (CVD) [1]. It is a well-known prognostic marker of CVD [2–6]. However, its pathophysiologic mechanisms are still unclear. Only diffuse hypoperfusion and chronic endothelial dysfunction have been suggested as causes, however these appear inadequate to fully explain the association [7–9]. Inflammation has a key role in development of CVD [10,11]. Focal inflammation which follows local arterial occlusion and systemic inflammation which is related to atherosclerosis formation have been
known to be associated with the burden, morbidity, and even mortality of CVD [12–15]. However, the impact of inflammation on WMH, which shares various risk factors and is thought to be closely related to CVD [16], remains unknown. Neutrophil to lymphocyte ratio (NLR) is a simple marker of systemic inflammation [17], and is easily obtained from differential blood cell counts. Elevated NLR has been used as a predictor of poor prognoses in vascular disease; including cardiovascular disease, peripheral vascular disease, and CVD [10,18–21]. In this study, we evaluated the relationship between NLR levels and WMH volumes, thereby gaining clues as to mechanisms underlying pathophysiology of WMH. 2. Methods
⁎ Correspondence to: Hyung-Min Kwon, Department of Neurology, Seoul National University College of Medicine, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, 20 Boramae-ro 5-gil, Dongjak-Gu, Seoul 07061, Republic of Korea. ⁎⁎ Correspondence to: Jin-Ho Park, Department of Family Medicine, Seoul National University College of Medicine, and Seoul National University Hospital, 101 Daehakno, Jongno-Gu, Seoul 03080, Republic of Korea. E-mail addresses: [email protected] (H.-M. Kwon), [email protected] (J.-H. Park). 1 HM Kwon and JH Park contributed equally as corresponding author.
http://dx.doi.org/10.1016/j.jns.2017.07.024 0022-510X/© 2017 Published by Elsevier B.V.
2.1. Patients and population We reviewed medical records from a consecutively enrolled registry of participants who visited Seoul National University Hospital Health Promotion Center to obtain a voluntary routine health check-up, between January 2006 and December 2013 (n = 3259). The health check-up was designed for participants who have age over 19 years.
K.-W. Nam et al. / Journal of the Neurological Sciences 380 (2017) 128–131
Any, participants without blood cell counts data, including neutrophil or lymphocyte counts, were excluded (n = 44). We also excluded subjects who suffered from severe systemic inflammatory conditions as follows: history of stroke or severe neurological deficit (n = 64), hemato-oncologic conditions or use of immunosuppressant (n = 71), severe allergic disease (n = 77), severe hepatic or renal disease (n = 100), having major surgery or severe trauma (n = 15), or active infections within prior 2 weeks (n = 11). Ultimately, a total of 2875 subjects were included in the analysis (Fig. 1). The current study was approved by the institutional review board at Seoul National University Hospital (IRB No. 1502-026-647). 2.2. Clinical assessment Baseline demographic, clinical, cardiovascular risk factors, and laboratory factors were evaluated, including sex, hypertension (using anti-hypertensive drug, or ≥ 140 mmHg systolic blood pressure, or ≥90 mmHg diastolic blood pressure), diabetes (using glucose lowering agents, or ≥ 6.5% hemoglobin A1c levels), hyperlipidemia (using lipid lowering agents, or ≥240 mg/dL total cholesterol levels, or ≥160 mg/dL low-density lipoprotein cholesterol levels), ischemic heart disease, and current smoking [22]. Blood pressure was checked after 5 min rest in sitting position. All laboratory examinations, including glucose, cholesterol, blood cell counts, and C-reactive protein levels, were conducted on the same day after 12 h of overnight fasting. Blood cell samples were collected in a calcium ethylene diamine tetra-acetic acid (EDTA) tube, and were separated immediately with centrifugation (2000 rpm for 20 min at 4 °C). Blood cell count analysis including total white blood cell, neutrophil, lymphocyte, and platelet was conducted using an auto-analyzer in our hospital (XE-2100, Sysmex, Kobe, Japan). We calculated platelet to lymphocyte ratio and NLR after dividing by absolute lymphocyte counts in peripheral blood [23,24]. 2.3. Radiological assessment In this study, all participants underwent brain MRI and MRA using 1.5-Tesla MR scanners (Signa, GE Healthcare, Milwaukee, WI, or Magnetom SONATA, Siemens, Munich, Germany). The slice thickness was 5 mm, excluding time of flight MRA imaging, and detailed acquisitions of MRI were as following: T1-weighted images (repetition time (TR) / echo time (TE) = 500 / 11 ms), T2-weighted images (TR/ TE = 5000 / 127 ms), T2 fluid-attenuated inversion recovery images (TR/TE = 8800 / 127 ms), T2-gradient echo images (TR/TE = 57 / 20 ms), and three-dimensional time of flight MRA images (TR/TE = 24 / 3.5 ms, slice thickness = 1.2 mm). WMH was rated quantitatively
Fig. 1. Inclusion and exclusion criteria of the study.
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using Medical Imaging Processing, Analysis, and Visualization (MIPAV, version 7.3.0, National Institutes of Health, Bethesda, MD) by an investigator (K.-W.N.) who was blinded to any clinical information [22]. We used a computer-assisted semi-automated technique, measuring from converted DICOM files. We also performed a sensitivity analysis for the relationship between WMH volume and NLR with the Fazekas scale [25]. Periventricular and subcortical WMH were respectively graded, and summed up to compare with the results from total WMH volume by MIPAV. We also evaluated the presence of silent brain infarcts (SBI) and cerebral microbleeds (CMB) as additional small vessel diseases. SBI was defined as an asymptomatic ≥3 mm size well-defined lesion with the same signal characteristics as cerebrospinal fluid on T2 and T1 MRI [26]. CMBs were b 10 mm size focal round lesions with low signal on T2-gradient echo images [26]. Intracranial atherosclerosis (ICAS) [27] and extracranial atherosclerosis (ECAS) [28] were also defined as an occlusion or N50% stenosis of intracranial or extracranial vessels on flight MRA images, respectively. The presence of SBI, CMB, ICAS, and ECAS were rated by two neurologists (K.-W.N. and H.-Y.J) without clinical data, and the mean inter-rater reliability coefficient was P = 0.890. 2.4. Statistical analysis We presented all continuous variables with normal distributions as the mean ± standard deviation, while the others were presented as the median + interquartile range. Continuous variables with skewed data were transformed into a log scale. However, some variables were transformed into a squared root scale, since they had zero values (e.g., hs-CRP, WMH). Univariate linear regression analyses were conducted for the association between WMH volumes and the demographic, clinical, laboratory and radiological factors. Then, variables with P b 0.05 from the results of univariate analysis and sex were introduced as confounders into the multivariate linear regression analysis. Additionally, to evaluate the characteristics of subjects with high NLR values, we dichotomized the cohort with NRL values. Then, we evaluated the baseline demographic, clinical, and radiological characteristics between upper (NLR ≥ 1.52) and lower half (NLR b 1.52) NLR group. The Student's t-test or the Mann-Whitney U-test were conducted for continuous variables, and chi-squared test or Fisher's exact test were used for categorical variables. All statistical analyses were performed using SPSS version 21 (IBM SPSS, Chicago, IL, USA) and all variables with P b 0.05 were considered significant. 3. Results A total of 2875 participants were evaluated. The median age of the cohort was 56 years (range 22 to 86 years), and we had 54% male subjects. Other baseline characteristics are presented in Table 1. As small vessel diseases, the mean WMH volumes were 2.63 ± 6.26 mL, and 245 (9%) and 119 (4%) subjects had SBI and CMBs, respectively. In univariate linear regression analysis, WMH volumes were significantly associated with older age (β = 0.053, P b 0.001), hypertension (β = 0.471, P b 0.001), diabetes (β = 0.448, P b 0.001), current smoking (β = −0.232, P b 0.001), ICAS (β = 0.606, P b 0.001), ECAS (β = 876, P b 0.001), and high levels of white blood cell counts (β = 0.046, P b 0.001), platelet counts (β = −0.001, P = 0.020), neutrophil counts (β = 0.075, P b 0.001), and NLR (β = 0.273, P b 0.001) (Table 2). In multivariate linear regression analysis, NLR [β = 0.191, 95% CI = 0.104 to 0.279, P b 0.001] remained significant after adjusting for confounders (Table 3). Additionally, age (β = 0.049, 95% CI = 0.045 to 0.054, P b 0.001), hypertension (β = 0.191, 95% CI = 0.101 to 0.281, P b 0.001), diabetes (β = 0.153, 95% CI = 0.045 to 0.261, P = 0.006), and ECAS (β = 0.348, 95% CI = 0.007 to 0.688, P = 0.045) were also significant independently from NLR. These positive associations remained significant when ICAS was introduced alternatively to ECAS, considering their close relationship (Supplementary Table 1). Total white blood cell
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Table 1 Baseline characteristics (total n = 2875).
Table 3 Multivariate linear regression analysis adjusted for confounders.
Age, y Sex, male, n (%) Hypertension, n (%) Diabetes, n (%) Hyperlipidemia, n (%) Ischemic heart disease, n (%) Current smoking, n (%) White blood cell, ×103/μL Platelet count, ×103/μL Neutrophil, ×103/μL Lymphocyte, ×103/μL hs-CRP, mg/dL Platelet to lymphocyte ratio Neutrophil to lymphocyte ratio White matter hyperintensity, mL Silent brain infarct, n (%) Cerebral microbleeds, n (%) Intracranial atherosclerosis, n (%) Extracranial atherosclerosis, n (%)
56 ± 9 1565 (54) 641 (22) 399 (14) 727 (25) 102 (4) 447 (16) 5.59 ± 1.68 238 ± 55 3.11 ± 1.30 1.93 ± 0.56 0.18 ± 0.68 132.34 ± 45.15 1.71 ± 0.82 2.63 ± 6.06 245 (9) 119 (4) 86 (3) 33 (1)
counts and neutrophil counts were also not included, due to co-linearity with NLR. These results continued when we underwent subgroup analysis between patients with hypertension (n = 641, β = 0.263, 95% CI = 0.025 to 0.501, P = 0.030) and without hypertension (n = 2234, β = 0.160, 95% CI = 0.069 to 0.251, P = 0.001). To strengthen the association between WMH volume and NLR, we performed a sensitivity analysis using the Fazekas scale. The total Fazekas score was significantly correlated with WMH volumes rated by quantitative manner (P b 0.001, Supplementary Fig. 1). It also showed significant association with NLR values (P b 0.001), even with the dose-response manner (P b 0.001, Supplementary Fig. 2). Differences between high (NLR ≥ 1.52) and low (NLR b 1.52) NLR groups are shown in Table 4. The high NLR group was significantly associated with male sex (58% versus 51%, P = 0.001), hypertension (24% versus 20%, P = 0.006), diabetes (16% versus 12%, P = 0.002), current smoking (17% versus 14%, P = 0.030), ECAS (2% versus 1%, P = 0.009), higher C-reactive protein levels (0.07 (0.01–0.19) mg/dL versus 0.03 (0.01–0.11) mg/dL, P b 0.001) and higher volumes of WMH (1.20 (0.23–2.96) mL versus 0.98 (0.20–2.40) mL, P = 0.001). SBI or CMB were not different between two groups. 4. Discussion In this study, we found that high levels of NLR were associated with larger volumes of WMH in a healthy population. Compared with Table 2 Univariate linear regression analysis between white matter hyperintensity volume and demographic, clinical, laboratory, and radiological factors.
Age, y Sex, male, n (%) Hypertension, n (%) Diabetes, n (%) Hyperlipidemia, n (%) Ischemic heart disease, n (%) Current smoking, n (%) White blood cell, ×103/μL Platelet count, ×103/μL Neutrophil, ×103/μL Lymphocyte, ×103/μL hs-CRP, mg/dLa Platelet to lymphocyte ratiob Neutrophil to lymphocyte ratiob Intracranial atherosclerosis, n (%) Extracranial atherosclerosis, n (%) a b
β (95% CI)
P
0.053 (0.050 to 0.057) −0.003 (−0.084 to 0.079) 0.471 (0.375 to 0.567) 0.448 (0.331 to 0.564) 0.049 (−0.044 to 0.143) 0.201 (−0.019 to 0.421) −0.232 (−0.344 to −0.120) 0.046 (0.022 to 0.070) −0.001 (−0.002 to 0.000) 0.075 (0.044 to 0.106) −0.029 (−0.102 to 0.043) 0.054 (−0.080 to 0.188) −0.038 (−0.162 to 0.087) 0.273 (0.175 to 0.370) 0.606 (0.368 to 0.844) 0.876 (0.495 to 1.257)
b0.001 0.948 b0.001 b0.001 0.302 0.073 b0.001 b0.001 0.020 b0.001 0.429 0.431 0.555 b0.001 b0.001 b0.001
This variable was introduced as squared root scale. These variables were introduced as log scale.
Age, y Sex, male, n (%) Hypertension, n (%) Diabetes, n (%) Current smoking, n (%) Platelet count, ×103/μL Neutrophil to lymphocyte ratioa Extracranial atherosclerosis, n (%) a
β changes in square root of WMH volume (95% CI)
P
0.050 (0.045 to 0.054) 0.015 (−0.064 to 0.093) 0.191 (0.101 to 0.281) 0.153 (0.045 to 0.261) −0.018 (−0.125 to 0.089) 0.000 (−0.001 to 0.000) 0.191 (0.104 to 0.279)
b0.001 0.717 b0.001 0.006 0.740 0.368 b0.001
0.348 (0.007 to 0.688)
0.045
These variables were introduced as log scale.
previous studies of CVD and heart disease patients, our cohort showed a relatively low burden of NLR values, having similar values to control groups in other studies [10,18–20,29]. Despite our group having a relatively low inflammation burden, we found there was a relationship between systemic inflammation and WMH development, using an easy tool which is routinely conducted on admission. It offers a meaningful way to estimate inflammatory pathophysiology of WMH development. High NLR means enhanced innate immunity and attenuated adaptive immunity [20,30]. In CVD, neutrophils infiltrate to ischemic or reperfused areas, and secrete proteolytic enzymes, arachidonic acid, elastase, or free oxygen radicals, destroying neural tissues [10,20,29]. In contrast, lymphocytes are known as healing promotors by with secreting interleukin-10 [20]. In our study, although not actually suffering from CVD, subjects with high NLR could be thought of as being in a subclinical inflammatory condition, which is more easily triggered and vulnerable to injurious conditions. In our cohort, the high NLR group showed significantly higher levels of C-reactive protein than the low NLR group. The absolute levels of C-reactive protein were not much higher, however, it supports the conjecture that these subjects are in subclinical inflammation states. There are several possible explanations for the relationship between high NLR levels and WMH volumes. First, endothelial dysfunction resulting from chronic sub-clinical inflammation could play a role. Normal endothelium produces vasodilator (e.g. nitric oxide, prostacyclin), antithrombotic agents, or anti-atherogenic agents [7,31,32]. In inflammatory conditions, stimulated leukocytes (especially neutrophils) increase their capacity to adhere to vascular endothelium and dysregulated endothelium [31], leading to worsened lipohyalinosis or produce microthombi in perforator vessels. Second, it may be the result of atherosclerotic vessels. We know that chronic systemic inflammation is a well-known mechanism leading to atherosclerosis [13,33]. As seen in our cohort, high NLR subjects showed higher frequencies of ICAS and ECAS. Diffuse
Table 4 Baseline characteristics of patients with low and high NLR.
Age, y Sex, male, n (%) Hypertension, n (%) Diabetes, n (%) Hyperlipidemia, n (%) Ischemic heart disease, n (%) Current smoking, n (%) White matter hyperintensity, mL Silent brain infarct, n (%) Cerebral microbleeds, n (%) hs-CRP, mg/dLa Intracranial atherosclerosis, n (%) Extracranial atherosclerosis, n (%)
Lower half NLR (n = 1435)
Upper half NLR (n = 1440)
P
56 [50–62] 736 (51) 289 (20) 171 (12) 367 (26) 51 (4) 202 (14) 0.98 [0.20–2.40] 110 (8) 56 (4) 0.03 [0.01–0.11] 35 (2) 9 (1)
56 [50–63] 829 (58) 352 (24) 228 (16) 360 (25) 51 (4) 245 (17) 1.20 [0.23–2.96] 135 (9) 63 (4) 0.07 [0.01–0.19] 51 (4) 24 (2)
0.147 0.001 0.006 0.002 0.723 0.986 0.030 0.001 0.101 0.525 b0.001 0.083 0.009
NLR = Neutrophil to lymphocyte ratio. a This variable was introduced as squared root scale.
K.-W. Nam et al. / Journal of the Neurological Sciences 380 (2017) 128–131
hypoperfusion due to major vessel steno-occlusion could worsen WMH volume progression [9]. Last, it could be a coincidence of sharing vascular risk factors. In previous studies, chronic low grade inflammation is related to various vascular risk factors, including diabetes, hypertension, smoking, obesity and metabolic syndrome [31]. We also showed that the high NLR group also presented with higher frequencies of hypertension, diabetes, and smoking. Thus, it may be the result of having a higher burden of known WMH risk factors in the higher NLR group. In the present study, SBI and CMB were not closely associated with high NLR value. Thus, we thought that WMH may be more related to these inflammatory pathophysiology than other known small vessel diseases. There are some caveats in this study. First, it was designed as a retrospective single-center study. Despite relatively large numbers of subjects, selection bias should be considered and generalization to clinical fields may be cautious. Second, rating total WMH volumes without separation of periventricular and subcortical areas due to methodological problems might be a limitation. Last, since our cohort had relatively older median age than that of Korean population, generalization to young subjects should be cautious. Nonetheless, we have several strengths. This is the first study about the relationship between WMH volume and NLR in a healthy population It provides clues to the inflammatory pathophysiology of WMH development. Additionally, we rated WMH volumes in a quantitative manner without the ceiling effect of a grading system. And it was finely correlated with a traditional grading system. In conclusion, high NLR levels were associated with larger WMH volume in a healthy population. If these results can be confirmed at further large-scale prospective study, routine check-ups with easily obtained tool and classifying high risk group with it may be helpful in preventing development of cerebral WMH in clinical fields.
[7]
[8]
[9] [10]
[11] [12]
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[17]
[18]
[19]
[20]
Disclosures
[21]
None
[22]
Source of funding
[23]
None [24]
Potential conflicts of interest None Acknowledgement
[25]
[26]
None [27]
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High neutrophil to lymphocyte ratio is associated with white matter hyperintensity in a healthy population Ki-Woong Nam a, Hyung-Min Kwon c,⁎,1, Han-Yeong Jeong a, Jin-Ho Park b,⁎⁎, Sang Hyuck Kim b, Su-Min Jeong b, Tae Gon Yoo b, Shinhye Kim b a b c
Department of Neurology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea Family Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea Department of Neurology, Seoul National University College of Medicine, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Republic of Korea
a r t i c l e
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Article history: Received 17 May 2017 Received in revised form 22 June 2017 Accepted 17 July 2017 Available online 19 July 2017 Keywords: Leukoaraiosis Inflammation Small vessel disease White blood cell Neutrophil Lymphocyte
a b s t r a c t High neutrophil to lymphocyte ratio (NLR) is correlated with the occurrence, morbidity and mortality of cerebrovascular disease as a marker of systemic inflammation. However, its effect on cerebral white matter hyperintensity (WMH) is unclear. We investigated high NLR burden as a surrogate marker of WMH volume in a healthy population. Healthy subjects with voluntary health check-ups between January 2006 and December 2013, including brain MRI and laboratory examination, were collected. WMH volumes were rated quantitatively. A total of 2875 subjects were enrolled, and the mean volume of WMH was 2.63 ± 6.26 mL. In multivariate linear regression analysis, NLR [β = 0.191, 95% confidence interval (CI) = 0.104 to 0.279, P b 0.001] remained significant after adjusting for confounders. Age (β = 0.049, 95% CI = 0.045 to 0.054, P b 0.001), hypertension (β = 0.191, 95% CI = 0.101 to 0.281, P b 0.001), diabetes (β = 0.153, 95% CI = 0.045 to 0.261, P = 0.006), and extracranial atherosclerosis (β = 0.348, 95% CI = 0.007 to 0.688, P = 0.045) were also significant independently from NLR. Additionally, the high NLR group (NLR ≥ 1.52) was related to male sex, hypertension, diabetes, current smoking, extracranial atherosclerosis, silent brain infarct, and high WMH volumes. In conclusion, high NLR is associated with larger WMH volumes in a healthy population. Assessment of NLR may be helpful in detecting cerebral WMH burdens in high risk groups. © 2017 Published by Elsevier B.V.
1. Introduction Cerebral white matter hyperintensity (WMH) is a pathologic marker of tissue rarefaction, commonly found in the elderly, especially those with vascular risk factors or symptomatic cerebrovascular disease (CVD) [1]. It is a well-known prognostic marker of CVD [2–6]. However, its pathophysiologic mechanisms are still unclear. Only diffuse hypoperfusion and chronic endothelial dysfunction have been suggested as causes, however these appear inadequate to fully explain the association [7–9]. Inflammation has a key role in development of CVD [10,11]. Focal inflammation which follows local arterial occlusion and systemic inflammation which is related to atherosclerosis formation have been
known to be associated with the burden, morbidity, and even mortality of CVD [12–15]. However, the impact of inflammation on WMH, which shares various risk factors and is thought to be closely related to CVD [16], remains unknown. Neutrophil to lymphocyte ratio (NLR) is a simple marker of systemic inflammation [17], and is easily obtained from differential blood cell counts. Elevated NLR has been used as a predictor of poor prognoses in vascular disease; including cardiovascular disease, peripheral vascular disease, and CVD [10,18–21]. In this study, we evaluated the relationship between NLR levels and WMH volumes, thereby gaining clues as to mechanisms underlying pathophysiology of WMH. 2. Methods
⁎ Correspondence to: Hyung-Min Kwon, Department of Neurology, Seoul National University College of Medicine, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, 20 Boramae-ro 5-gil, Dongjak-Gu, Seoul 07061, Republic of Korea. ⁎⁎ Correspondence to: Jin-Ho Park, Department of Family Medicine, Seoul National University College of Medicine, and Seoul National University Hospital, 101 Daehakno, Jongno-Gu, Seoul 03080, Republic of Korea. E-mail addresses: [email protected] (H.-M. Kwon), [email protected] (J.-H. Park). 1 HM Kwon and JH Park contributed equally as corresponding author.
http://dx.doi.org/10.1016/j.jns.2017.07.024 0022-510X/© 2017 Published by Elsevier B.V.
2.1. Patients and population We reviewed medical records from a consecutively enrolled registry of participants who visited Seoul National University Hospital Health Promotion Center to obtain a voluntary routine health check-up, between January 2006 and December 2013 (n = 3259). The health check-up was designed for participants who have age over 19 years.
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Any, participants without blood cell counts data, including neutrophil or lymphocyte counts, were excluded (n = 44). We also excluded subjects who suffered from severe systemic inflammatory conditions as follows: history of stroke or severe neurological deficit (n = 64), hemato-oncologic conditions or use of immunosuppressant (n = 71), severe allergic disease (n = 77), severe hepatic or renal disease (n = 100), having major surgery or severe trauma (n = 15), or active infections within prior 2 weeks (n = 11). Ultimately, a total of 2875 subjects were included in the analysis (Fig. 1). The current study was approved by the institutional review board at Seoul National University Hospital (IRB No. 1502-026-647). 2.2. Clinical assessment Baseline demographic, clinical, cardiovascular risk factors, and laboratory factors were evaluated, including sex, hypertension (using anti-hypertensive drug, or ≥ 140 mmHg systolic blood pressure, or ≥90 mmHg diastolic blood pressure), diabetes (using glucose lowering agents, or ≥ 6.5% hemoglobin A1c levels), hyperlipidemia (using lipid lowering agents, or ≥240 mg/dL total cholesterol levels, or ≥160 mg/dL low-density lipoprotein cholesterol levels), ischemic heart disease, and current smoking [22]. Blood pressure was checked after 5 min rest in sitting position. All laboratory examinations, including glucose, cholesterol, blood cell counts, and C-reactive protein levels, were conducted on the same day after 12 h of overnight fasting. Blood cell samples were collected in a calcium ethylene diamine tetra-acetic acid (EDTA) tube, and were separated immediately with centrifugation (2000 rpm for 20 min at 4 °C). Blood cell count analysis including total white blood cell, neutrophil, lymphocyte, and platelet was conducted using an auto-analyzer in our hospital (XE-2100, Sysmex, Kobe, Japan). We calculated platelet to lymphocyte ratio and NLR after dividing by absolute lymphocyte counts in peripheral blood [23,24]. 2.3. Radiological assessment In this study, all participants underwent brain MRI and MRA using 1.5-Tesla MR scanners (Signa, GE Healthcare, Milwaukee, WI, or Magnetom SONATA, Siemens, Munich, Germany). The slice thickness was 5 mm, excluding time of flight MRA imaging, and detailed acquisitions of MRI were as following: T1-weighted images (repetition time (TR) / echo time (TE) = 500 / 11 ms), T2-weighted images (TR/ TE = 5000 / 127 ms), T2 fluid-attenuated inversion recovery images (TR/TE = 8800 / 127 ms), T2-gradient echo images (TR/TE = 57 / 20 ms), and three-dimensional time of flight MRA images (TR/TE = 24 / 3.5 ms, slice thickness = 1.2 mm). WMH was rated quantitatively
Fig. 1. Inclusion and exclusion criteria of the study.
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using Medical Imaging Processing, Analysis, and Visualization (MIPAV, version 7.3.0, National Institutes of Health, Bethesda, MD) by an investigator (K.-W.N.) who was blinded to any clinical information [22]. We used a computer-assisted semi-automated technique, measuring from converted DICOM files. We also performed a sensitivity analysis for the relationship between WMH volume and NLR with the Fazekas scale [25]. Periventricular and subcortical WMH were respectively graded, and summed up to compare with the results from total WMH volume by MIPAV. We also evaluated the presence of silent brain infarcts (SBI) and cerebral microbleeds (CMB) as additional small vessel diseases. SBI was defined as an asymptomatic ≥3 mm size well-defined lesion with the same signal characteristics as cerebrospinal fluid on T2 and T1 MRI [26]. CMBs were b 10 mm size focal round lesions with low signal on T2-gradient echo images [26]. Intracranial atherosclerosis (ICAS) [27] and extracranial atherosclerosis (ECAS) [28] were also defined as an occlusion or N50% stenosis of intracranial or extracranial vessels on flight MRA images, respectively. The presence of SBI, CMB, ICAS, and ECAS were rated by two neurologists (K.-W.N. and H.-Y.J) without clinical data, and the mean inter-rater reliability coefficient was P = 0.890. 2.4. Statistical analysis We presented all continuous variables with normal distributions as the mean ± standard deviation, while the others were presented as the median + interquartile range. Continuous variables with skewed data were transformed into a log scale. However, some variables were transformed into a squared root scale, since they had zero values (e.g., hs-CRP, WMH). Univariate linear regression analyses were conducted for the association between WMH volumes and the demographic, clinical, laboratory and radiological factors. Then, variables with P b 0.05 from the results of univariate analysis and sex were introduced as confounders into the multivariate linear regression analysis. Additionally, to evaluate the characteristics of subjects with high NLR values, we dichotomized the cohort with NRL values. Then, we evaluated the baseline demographic, clinical, and radiological characteristics between upper (NLR ≥ 1.52) and lower half (NLR b 1.52) NLR group. The Student's t-test or the Mann-Whitney U-test were conducted for continuous variables, and chi-squared test or Fisher's exact test were used for categorical variables. All statistical analyses were performed using SPSS version 21 (IBM SPSS, Chicago, IL, USA) and all variables with P b 0.05 were considered significant. 3. Results A total of 2875 participants were evaluated. The median age of the cohort was 56 years (range 22 to 86 years), and we had 54% male subjects. Other baseline characteristics are presented in Table 1. As small vessel diseases, the mean WMH volumes were 2.63 ± 6.26 mL, and 245 (9%) and 119 (4%) subjects had SBI and CMBs, respectively. In univariate linear regression analysis, WMH volumes were significantly associated with older age (β = 0.053, P b 0.001), hypertension (β = 0.471, P b 0.001), diabetes (β = 0.448, P b 0.001), current smoking (β = −0.232, P b 0.001), ICAS (β = 0.606, P b 0.001), ECAS (β = 876, P b 0.001), and high levels of white blood cell counts (β = 0.046, P b 0.001), platelet counts (β = −0.001, P = 0.020), neutrophil counts (β = 0.075, P b 0.001), and NLR (β = 0.273, P b 0.001) (Table 2). In multivariate linear regression analysis, NLR [β = 0.191, 95% CI = 0.104 to 0.279, P b 0.001] remained significant after adjusting for confounders (Table 3). Additionally, age (β = 0.049, 95% CI = 0.045 to 0.054, P b 0.001), hypertension (β = 0.191, 95% CI = 0.101 to 0.281, P b 0.001), diabetes (β = 0.153, 95% CI = 0.045 to 0.261, P = 0.006), and ECAS (β = 0.348, 95% CI = 0.007 to 0.688, P = 0.045) were also significant independently from NLR. These positive associations remained significant when ICAS was introduced alternatively to ECAS, considering their close relationship (Supplementary Table 1). Total white blood cell
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Table 1 Baseline characteristics (total n = 2875).
Table 3 Multivariate linear regression analysis adjusted for confounders.
Age, y Sex, male, n (%) Hypertension, n (%) Diabetes, n (%) Hyperlipidemia, n (%) Ischemic heart disease, n (%) Current smoking, n (%) White blood cell, ×103/μL Platelet count, ×103/μL Neutrophil, ×103/μL Lymphocyte, ×103/μL hs-CRP, mg/dL Platelet to lymphocyte ratio Neutrophil to lymphocyte ratio White matter hyperintensity, mL Silent brain infarct, n (%) Cerebral microbleeds, n (%) Intracranial atherosclerosis, n (%) Extracranial atherosclerosis, n (%)
56 ± 9 1565 (54) 641 (22) 399 (14) 727 (25) 102 (4) 447 (16) 5.59 ± 1.68 238 ± 55 3.11 ± 1.30 1.93 ± 0.56 0.18 ± 0.68 132.34 ± 45.15 1.71 ± 0.82 2.63 ± 6.06 245 (9) 119 (4) 86 (3) 33 (1)
counts and neutrophil counts were also not included, due to co-linearity with NLR. These results continued when we underwent subgroup analysis between patients with hypertension (n = 641, β = 0.263, 95% CI = 0.025 to 0.501, P = 0.030) and without hypertension (n = 2234, β = 0.160, 95% CI = 0.069 to 0.251, P = 0.001). To strengthen the association between WMH volume and NLR, we performed a sensitivity analysis using the Fazekas scale. The total Fazekas score was significantly correlated with WMH volumes rated by quantitative manner (P b 0.001, Supplementary Fig. 1). It also showed significant association with NLR values (P b 0.001), even with the dose-response manner (P b 0.001, Supplementary Fig. 2). Differences between high (NLR ≥ 1.52) and low (NLR b 1.52) NLR groups are shown in Table 4. The high NLR group was significantly associated with male sex (58% versus 51%, P = 0.001), hypertension (24% versus 20%, P = 0.006), diabetes (16% versus 12%, P = 0.002), current smoking (17% versus 14%, P = 0.030), ECAS (2% versus 1%, P = 0.009), higher C-reactive protein levels (0.07 (0.01–0.19) mg/dL versus 0.03 (0.01–0.11) mg/dL, P b 0.001) and higher volumes of WMH (1.20 (0.23–2.96) mL versus 0.98 (0.20–2.40) mL, P = 0.001). SBI or CMB were not different between two groups. 4. Discussion In this study, we found that high levels of NLR were associated with larger volumes of WMH in a healthy population. Compared with Table 2 Univariate linear regression analysis between white matter hyperintensity volume and demographic, clinical, laboratory, and radiological factors.
Age, y Sex, male, n (%) Hypertension, n (%) Diabetes, n (%) Hyperlipidemia, n (%) Ischemic heart disease, n (%) Current smoking, n (%) White blood cell, ×103/μL Platelet count, ×103/μL Neutrophil, ×103/μL Lymphocyte, ×103/μL hs-CRP, mg/dLa Platelet to lymphocyte ratiob Neutrophil to lymphocyte ratiob Intracranial atherosclerosis, n (%) Extracranial atherosclerosis, n (%) a b
β (95% CI)
P
0.053 (0.050 to 0.057) −0.003 (−0.084 to 0.079) 0.471 (0.375 to 0.567) 0.448 (0.331 to 0.564) 0.049 (−0.044 to 0.143) 0.201 (−0.019 to 0.421) −0.232 (−0.344 to −0.120) 0.046 (0.022 to 0.070) −0.001 (−0.002 to 0.000) 0.075 (0.044 to 0.106) −0.029 (−0.102 to 0.043) 0.054 (−0.080 to 0.188) −0.038 (−0.162 to 0.087) 0.273 (0.175 to 0.370) 0.606 (0.368 to 0.844) 0.876 (0.495 to 1.257)
b0.001 0.948 b0.001 b0.001 0.302 0.073 b0.001 b0.001 0.020 b0.001 0.429 0.431 0.555 b0.001 b0.001 b0.001
This variable was introduced as squared root scale. These variables were introduced as log scale.
Age, y Sex, male, n (%) Hypertension, n (%) Diabetes, n (%) Current smoking, n (%) Platelet count, ×103/μL Neutrophil to lymphocyte ratioa Extracranial atherosclerosis, n (%) a
β changes in square root of WMH volume (95% CI)
P
0.050 (0.045 to 0.054) 0.015 (−0.064 to 0.093) 0.191 (0.101 to 0.281) 0.153 (0.045 to 0.261) −0.018 (−0.125 to 0.089) 0.000 (−0.001 to 0.000) 0.191 (0.104 to 0.279)
b0.001 0.717 b0.001 0.006 0.740 0.368 b0.001
0.348 (0.007 to 0.688)
0.045
These variables were introduced as log scale.
previous studies of CVD and heart disease patients, our cohort showed a relatively low burden of NLR values, having similar values to control groups in other studies [10,18–20,29]. Despite our group having a relatively low inflammation burden, we found there was a relationship between systemic inflammation and WMH development, using an easy tool which is routinely conducted on admission. It offers a meaningful way to estimate inflammatory pathophysiology of WMH development. High NLR means enhanced innate immunity and attenuated adaptive immunity [20,30]. In CVD, neutrophils infiltrate to ischemic or reperfused areas, and secrete proteolytic enzymes, arachidonic acid, elastase, or free oxygen radicals, destroying neural tissues [10,20,29]. In contrast, lymphocytes are known as healing promotors by with secreting interleukin-10 [20]. In our study, although not actually suffering from CVD, subjects with high NLR could be thought of as being in a subclinical inflammatory condition, which is more easily triggered and vulnerable to injurious conditions. In our cohort, the high NLR group showed significantly higher levels of C-reactive protein than the low NLR group. The absolute levels of C-reactive protein were not much higher, however, it supports the conjecture that these subjects are in subclinical inflammation states. There are several possible explanations for the relationship between high NLR levels and WMH volumes. First, endothelial dysfunction resulting from chronic sub-clinical inflammation could play a role. Normal endothelium produces vasodilator (e.g. nitric oxide, prostacyclin), antithrombotic agents, or anti-atherogenic agents [7,31,32]. In inflammatory conditions, stimulated leukocytes (especially neutrophils) increase their capacity to adhere to vascular endothelium and dysregulated endothelium [31], leading to worsened lipohyalinosis or produce microthombi in perforator vessels. Second, it may be the result of atherosclerotic vessels. We know that chronic systemic inflammation is a well-known mechanism leading to atherosclerosis [13,33]. As seen in our cohort, high NLR subjects showed higher frequencies of ICAS and ECAS. Diffuse
Table 4 Baseline characteristics of patients with low and high NLR.
Age, y Sex, male, n (%) Hypertension, n (%) Diabetes, n (%) Hyperlipidemia, n (%) Ischemic heart disease, n (%) Current smoking, n (%) White matter hyperintensity, mL Silent brain infarct, n (%) Cerebral microbleeds, n (%) hs-CRP, mg/dLa Intracranial atherosclerosis, n (%) Extracranial atherosclerosis, n (%)
Lower half NLR (n = 1435)
Upper half NLR (n = 1440)
P
56 [50–62] 736 (51) 289 (20) 171 (12) 367 (26) 51 (4) 202 (14) 0.98 [0.20–2.40] 110 (8) 56 (4) 0.03 [0.01–0.11] 35 (2) 9 (1)
56 [50–63] 829 (58) 352 (24) 228 (16) 360 (25) 51 (4) 245 (17) 1.20 [0.23–2.96] 135 (9) 63 (4) 0.07 [0.01–0.19] 51 (4) 24 (2)
0.147 0.001 0.006 0.002 0.723 0.986 0.030 0.001 0.101 0.525 b0.001 0.083 0.009
NLR = Neutrophil to lymphocyte ratio. a This variable was introduced as squared root scale.
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hypoperfusion due to major vessel steno-occlusion could worsen WMH volume progression [9]. Last, it could be a coincidence of sharing vascular risk factors. In previous studies, chronic low grade inflammation is related to various vascular risk factors, including diabetes, hypertension, smoking, obesity and metabolic syndrome [31]. We also showed that the high NLR group also presented with higher frequencies of hypertension, diabetes, and smoking. Thus, it may be the result of having a higher burden of known WMH risk factors in the higher NLR group. In the present study, SBI and CMB were not closely associated with high NLR value. Thus, we thought that WMH may be more related to these inflammatory pathophysiology than other known small vessel diseases. There are some caveats in this study. First, it was designed as a retrospective single-center study. Despite relatively large numbers of subjects, selection bias should be considered and generalization to clinical fields may be cautious. Second, rating total WMH volumes without separation of periventricular and subcortical areas due to methodological problems might be a limitation. Last, since our cohort had relatively older median age than that of Korean population, generalization to young subjects should be cautious. Nonetheless, we have several strengths. This is the first study about the relationship between WMH volume and NLR in a healthy population It provides clues to the inflammatory pathophysiology of WMH development. Additionally, we rated WMH volumes in a quantitative manner without the ceiling effect of a grading system. And it was finely correlated with a traditional grading system. In conclusion, high NLR levels were associated with larger WMH volume in a healthy population. If these results can be confirmed at further large-scale prospective study, routine check-ups with easily obtained tool and classifying high risk group with it may be helpful in preventing development of cerebral WMH in clinical fields.
[7]
[8]
[9] [10]
[11] [12]
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[17]
[18]
[19]
[20]
Disclosures
[21]
None
[22]
Source of funding
[23]
None [24]
Potential conflicts of interest None Acknowledgement
[25]
[26]
None [27]
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