Introduction {#sec1-1}
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Cardiovascular diseases (CVDs) are still the leading cause of death all over the world, despite modern therapeutic advances. It is known that inflammation plays a substantial role in the initiation and propagation of the complex atherosclerotic process ([@ref1]) that lies beneath CVD. The role of inflammation in CVD has been studied extensively, and a consistent relationship between various inflammatory markers and CVD has been established in the past ([@ref2]-[@ref4]). A low blood lymphocyte count has been shown to be related with worse cardiovascular consequences in patients with CAD and chronic heart failure ([@ref5]-[@ref7]). In cases of sustained inflammation, lymphocyte counts decrease due to increased lymphocyte apoptosis. Lymphocytes represent a more convenient immune response, while neutrophils cause a destructive inflammatory reaction. Also, ongoing inflammatory conditions lead to increased proliferation in megakaryocytic series and relative thrombocytosis. Previous studies demonstrated an association between high circulating platelet count and major adverse cardiovascular outcomes in patients with coronary artery disease (CAD) and also in healthy adults ([@ref8]-[@ref10]). Platelet-to-lymphocyte ratio (PLR) is a new prognostic marker that integrates the risk prediction of these 2 parameters into 1. It gives an idea about both the aggregation and inflammation pathways, and it may be more valuable than either platelet or lymphocyte count alone in the prediction of coronary atherosclerotic burden. PLR was found to be useful in predicting poor prognosis in cancer population ([@ref11]-[@ref13]) and in predicting critical limb ischemia in peripheral artery disease ([@ref14]) previously. Moreover, higher PLR value emerged as a significant independent predictor of long-term survival in patients presented with acute coronary syndrome ([@ref15]) and as an independent predictor of no-reflow development in patients undergoing primary PCI ([@ref16]). In line with these findings, a high PLR tertile of a recent study population that presented with STEMI showed poorer outcomes compared to the low PLR group, and PLR was found to be an independent predictor of in-hospital mortality in patients with STEMI ([@ref17]).

Gensini score was established to expose the severity and extent of coronary atherosclerosis. There are many studies demonstrating the relationship between systemic inflammation and coronary atherosclerosis; however, to our knowledge, there are no data about the relationship between PLR and severity of coronary atherosclerosis yet. In this context, we aimed to investigate the usefulness of a recently defined cardiovascular risk marker, PLR, in predicting the severity of coronary atherosclerosis.

Methods {#sec1-2}
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Study population {#sec2-1}
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The present study is a single-center and retrospectively designed study, consisting of 388 eligible consecutive patients who underwent selective coronary angiography between May and July 2013 in our clinic. Informed consent was obtained from all of the participants, and the study was approved by the local ethics committee.

A thorough physical examination was performed for all of the patients included in the study, and they were asked for their history of previous myocardial infarction, hypertension, diabetes mellitus, smoking and non-cardiac diseases and family history of CAD. Arterial hypertension was considered in patients with at least three repeated measurements of blood pressure above 140 mm Hg systolic and 90 mm Hg diastolic or active use of antihypertensive medication. Diabetes mellitus was defined as fasting plasma glucose levels above 126 mg/dL in at least two different measurements or active use of anti-diabetic drugs. Smoking was defined as current smoking or ex-smokers who forwent smoking in the past 6 months. A positive family history for CAD was considered a history of CAD or sudden cardiac death in a first-degree relative before the age of 55 years for men and 65 years for women.

Patients with moderate or advanced valvular heart disease, clinically decompensated congestive heart failure, malignancy, hematological disorder, severe renal or hepatic insufficiency, active infection or systemic inflammatory conditions, or autoimmune disorders and patients using steroids were excluded.

Biochemical and hematological parameters {#sec2-2}
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After an overnight fasting, peripheral venous blood samples were drawn from patients. Total and differential leukocyte counts were measured by an automated hematology analyzer (Abbott Cell-Dyn 3700; Abbott Laboratory, Abbott Park, Illinois, USA). Absolute cell counts were used in the analyses. PLR was computed as platelet count divided by lymphocyte count. Total and high-density lipoprotein cholesterol (HDL), triglycerides, and fasting plasma glucose levels were measured using the Abbott Architect C16000 auto-analyzer (Architect C16000 auto-analyzer;

Abbott Laboratory, Abbott Park, Illinois, USA). Plasma low-density lipoprotein cholesterol (LDL) concentrations were calculated using the Friedewald equation ([@ref18]).

Coronary angiography and assessment of coronary atherosclerosis severity {#sec2-3}
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Selective coronary angiography was performed for all patients enrolled in the study by Judkins technique through the femoral artery using the Allura Xper FD10 (Philips, Amsterdam, the Netherlands). All of the coronary angiograms were evaluated by 2 interventional cardiologists who were blinded to the patient information and to each other. A thorough review of each coronary angiogram established the lesion location and percentage of luminal stenosis among all coronary artery lesions.

CAD was defined as the presence of stenosis of at least 50% of the vessel diameter in any of the main coronary arteries, according to the American College of Cardiology/American Heart Association (ACC/AHA) lesion classification ([@ref19]). The Gensini scoring system was used to identify the severity of CAD ([@ref20]). This method classifies and scores the degree and extent of the stenosis of the coronary arteries. This system scores 1 point for 1% to 25% stenosis, 2 points for 26% to 50%, 4 points for 51% to 75%, 8 points for 76% to 90%, 16 points for 91% to 99% stenosis, and 32 points for total occlusion. The score is then multiplied by a factor representing the importance of the lesion's location in the coronary arterial system. For the location, scores are multiplied by 5 for a left main lesion; 2.5 for the proximal left anterior descending (LAD) or left circumflex (LCX) artery; 1.5 for the mid-segment LAD and LCX; 1 for the distal segment of the LAD and LCX, first diagonal branch, first obtuse marginal branch, right coronary artery, posterior descending artery, and intermediate artery; and 0.5 for the second diagonal and second obtuse marginal branches.

According to their coronary angiograms, patients were categorized into three groups. The first group consisted of 80 patients with normal coronary arteries (control group). The rest of the patients with coronary artery disease were divided into two according to their Gensini score: ([@ref21], [@ref22]) those with mild atherosclerosis (n=156; Gensini score \<25 points) and severe atherosclerosis (n=152; Gensini score \>25 points).

Statistical analysis {#sec2-4}
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Continuous variables were defined as means and standard deviation; categorical variables were given as percentages. The normality of distribution for continuous variables was confirmed with the Kolmogorov-Smirnov test. According to the distribution pattern of the continuous variables, the independent-sample t-test or the Mann-Whitney U test was used for continuous variables, and the chi-square test was used for categorical variables. One-way analysis of variance (ANOVA) or Kruskal-Wallis test was used to compare 3 groups. When there was a significant difference between the three study groups, the comparison of two groups in terms of the relevant parameter was performed with post hoc tests in one-way ANOVA and with Mann-Whitney U test after Bonferroni correction in Kruskal-Wallis test. Correlations were assessed using either Pearson's correlation test or Spearman's rank test according to the distribution pattern of the variable. Independent associations between Gensini score and independent variables were assessed by backward stepwise multiple linear regression analysis by including all parameters showing p value of less than 0.1 on univariate analysis \[patient age, PLR, white blood cell (WBC), high-density lipoprotein (HDL), serum creatinine\]. Standardized ß regression coefficients and their significance from the multiple linear regression analysis were reported. Receiver operating characteristic (ROC) curve analysis was used to determine the optimum cut-off level of pre-procedural PLR values to predict severe coronary atherosclerosis. Statistical analyses were performed using SPSS 16.0 (SPSS Inc, Chicago, Illinois, USA). A two-tailed p value \<0.05 was considered statistically significant.

Results {#sec1-3}
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A total of 308 patients with coronary artery disease (men 63%, mean age: 62±12 years) and 80 control subjects (59% male, mean age: 59±10 years) with normal coronary arteries were enrolled in the study. Baseline demographic, biochemical, and hematological characteristics of the groups are outlined in [Table 1](#T1){ref-type="table"}. The study groups were comparable in terms of gender and traditional coronary risk factors, while patients in the severe atherosclerosis group were older compared to the mild atherosclerosis group and controls (p=0.038 and p=0.033, respectively).

###### 

Comparison of baseline demographic characteristics and cardiovascular risk factors of the study population[\*](#t1f1){ref-type="table-fn"}

                               Control group (n=80)   Mild atherosclerosis (n=156)   Severe atherosclerosis (n=152)   *P*
  ---------------------------- ---------------------- ------------------------------ -------------------------------- ----------------------------------------------------------------------------
  Age, years                   57.8±10.5              59.8±10.8                      63.7±12.2                        \<0.001^[a](#t1f2){ref-type="table-fn"}^
  Male, n (%)                  47 (60)                92 (59)                        102(67)                          0.288
  Coronary risk factors                                                                                               
   Family history, n (%)       6 (8)                  15 (10)                        19 (13)                          0.473
   Smoking, n (%)              27 (34)                39 (25)                        49 (32)                          0.237
   Hypertension, n (%)         27 (34)                56 (36)                        70 (46)                          0.105
   Diabetes, n (%)             20 (25)                37 (24)                        46 (30)                          0.412
  **Biochemical parameters**                                                                                          
   Total cholesterol, mg/dL    180 (154-213)          178 (152-212)                  175 (146-206)                    0.810[\*](#t1f1){ref-type="table-fn"}
   LDL, mg/dL                  110 (85-128)           113 (89-139)                   109 (87-136)                     0.793[\*](#t1f1){ref-type="table-fn"}
  HDL, mg/dL                   40 (33-48)             36 (31-42)                     34 (29-39)                       \<0.001[\*](#t1f1){ref-type="table-fn"}, ^[b](#t1f3){ref-type="table-fn"}^
   Triglyceride, mg/dL         125 (92-201)           140 (105-190)                  136 (91-197)                     0.456[\*](#t1f1){ref-type="table-fn"}
  Glucose, mg/dL               108.9±27.8             129.7±61.8                     146.1±69.5                       \<0.001^[c](#t1f4){ref-type="table-fn"}^
  Creatinine, mg/dL            0.79±0.15              0.87±0.20                      1.01±0.55                        \<0.001^[d](#t1f5){ref-type="table-fn"}^
  **Hematologic parameters**                                                                                          
   Hemoglobin, g/dL            13.5±1.6               13.6±1.5                       13.7±1.6                         0.548
  WBC, x10^9^/L                8.3±2.4                8.5±2.6                        10.1±3.4                         \<0.001^[e](#t1f6){ref-type="table-fn"}^
  Platelet, x10^9^/L           248±63                 241±57                         279±58                           \<0.001^[f](#t1f7){ref-type="table-fn"}^
   Lymphocyte, x10^9^/L        2.5±0.9                2.4±0.9                        2.3± 1. 1                        0.337
  PLR                          106.2±36.9             113.8±60.8                     141.7±73.1                       \<0.001^[g](#t1f8){ref-type="table-fn"}^
   MPV, fL                     8.3±1.3                8.3±1.5                        8.4±1.4                          0.715

HDL - high-density lipoprotein; LDL - low-density lipoprotein; MPV - mean platelet volume; N/S - non-significant, PLR-platelet-to-lymphocyte ratio; SD-standard deviation; WBC-white blood cell count;

Values are mean±SD; median (25-75 percentiles), or n (%). Comparison between three groups was performed with one-way ANOVA or \*Kruskal-Wallis test.

For the results of post hoc tests or Mann-Whitney U test with Bonferroni correction, the significance levels are:

*P*~1~ (control vs. mild atherosclerosis); *P*~2~ (control vs. severe atherosclerosis); *P*~3~ (mild vs. severe atherosclerosis)

*P*~1~=0.450 (N/S); *P*~2~=0.001; *P*~3~=0.010

*P*~1~=0.006; *P*~2~\<0.001; *P*~3~=0.027 (N/S due to Bonferroni correction)

*P*~1~=0.044; *P*~2~\<0.001; *P*~3~=0.058 (N/S)

*P*~1~=0.317 (N/S); *P*~2~\<0.001; *P*~3~=0.005

*P*~1~=0.797 (N/S); *P*~2~\<0.001; *P*~3~\<0.001

*P*~1~=0.509 (N/S); *P*~2~=0.004; *P*~3~\<0.001

*P*~1~=0.729 (N/S); *P*~2~\<0.001; *P*~3~=0.001

Fasting serum glucose was significantly higher in the severe atherosclerosis group than the mild atherosclerosis group (p=0.045) and controls (p\<0.001); also, it was significantly higher in mild atherosclerosis than control subjects (p=0.033). The mean serum creatinine level of the severe atherosclerosis group was significantly higher than that of the mild atherosclerosis and control groups (p=0.003 and p\<0.001, respectively), while it was comparable between the latter two groups (p=0.284). The severe atherosclerosis group had significantly lower HDL levels compared to controls (p\<0.001), whereas it was similar between the severe and mild atherosclerosis groups (p=0.137).

Among hematological parameters, hemoglobin levels were similar between all three groups. WBC was significantly higher in the severe atherosclerosis group than in the other two groups (p\<0.001 for both), whereas it was similar between the mild atherosclerosis and control groups (p=0.779).

The severe atherosclerosis group had significantly higher platelet counts compared to the mild atherosclerosis group (p\<0.001) and controls (p=0.001), though platelet counts of the last two groups were similar (p=0.671). Lymphocyte count was comparable between all three groups (p=0.337). PLR was significantly higher in the severe atherosclerosis group compared to the mild atherosclerosis (p\<0.001) and control groups (p\<0.001) (142±73, 114±61, and 106±37 respectively, p\<0.001 for ANOVA; [Fig.1](#F1){ref-type="fig"}). PLR was also significantly higher in patients with CAD (n=308) compared to controls (n=80) (128±68 vs. 106±37, p\<0.001).

![Mean platelet-to-lymphocyte ratio (PLR) of controls and mild and severe atherosclerosis groups](AJC-15-640-g001){#F1}

PLR was found to be correlated with age (r=0.285; p\<0.001), CRP (r=0.245; p=0.001) (CRP was available for only 144 participants), fasting serum glucose level (r=0.187; p=0.014), and neutrophil count (r=0.922; p\<0.001). Also, PLR values of patients with CAD (n=308) correlated significantly with their Gensini scores (r=0.268, p\<0.001). Using a cut-off level of 111, PLR predicted severe atherosclerosis with a sensitivity of 61% and specificity of 59% (area under ROC curve=0.645, 95% CI: 0.587-0.703; p\<0.001; [Fig. 2](#F2){ref-type="fig"}). Also, fasting plasma glucose was positively correlated with Gensini score (r=0.256, p\<0.001). This correlation was valid after the exclusion of 92 diabetic cases from the study population (r=0.221, p\<0.001).

![The receiver operating characteristic (ROC) curve analysis of platelet-to-lymphocyte ratio for predicting severe atherosclerosis](AJC-15-640-g002){#F2}

Independent associations between Gensini score and independent variables were assessed by multivariate linear regression analysis by including all parameters showing correlation with a p value of less than 0.1 on univariate analysis (patient age, PLR, WBC, HDL, serum creatinine, fasting serum glucose). Pre-procedural PLR was independently associated with Gensini score (ß=0.141, p=0.004), together with WBC (ß=0.265, p\<0.001), HDL (ß=-0.133, p=0.006), and age (ß=0.192, p\<0.001; [Table 2](#T2){ref-type="table"}).

###### 

Multivariate linear regression analysis to determine independent variables significantly associated with Gensini score

  Dependent variable   Independent variables   B        β        t         *P*       VIF
  -------------------- ----------------------- -------- -------- --------- --------- ----------
  Gensini              Age                     0.574    0.192    3.891     \<0.001   1 .1 1 2
  PLR                  0.076                   0.141    2.873    0.004     1.097     
  WBC                  3.019                   0.265    5.514    \<0.001   1.055     
  Glucose              0.036                   0.064    1.284    0.200     1.127     
  Creatinine           8.678                   0.097    1.953    0.052     1.123     
  HDL                  -0.505                  -0.133   -2.787   0.006     1.044     

HDL - high-density lipoprotein; PLR - platelet-to-lymphocyte ration; WBC - white blood cell count. B - standardized ß regression coefficients

In addition, the patients with CAD (n=308) were further divided into three tertiles based upon their PLR values (lower than 97.8, higher than 131.7, and those in between). The mean Gensini score of patients in the high PLR tertile was significantly higher than that of the middle and lower tertiles (p=0.002 and p\<0.001, respectively), while mean Gensini scores of the middle and lower PLR tertiles were similar (p=0.564; [Fig. 3](#F3){ref-type="fig"}).

![Mean Gensini scores of patients in each PLR tertile\
PLR - platelet-to-lymphocyte ration](AJC-15-640-g003){#F3}

Discussion {#sec1-4}
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The association between neutrophil-to-lymphocyte ratio, a novel hematological indicator of inflammatory status in the body, and various cardiac disorders has been studied extensively in previous researches ([@ref23]-[@ref30]), including the prediction of severe atherosclerosis in patients undergoing coronary angiography ([@ref22], [@ref31], [@ref32]). Similarly, PLR, a recent hematological parameter indicating the inflammatory and prothrombotic state, has been shown to be associated with poor prognosis in patients with cardiovascular diseases; however, there are limited data about the association between PLR and coronary artery disease severity.

In the present study, we found that high PLR level was independently associated with the severity of coronary atherosclerosis. Patients with high pre-procedural PLR had significantly higher Gensini scores, and there was a positive correlation between PLR values and Gensini scores of patients with CAD. Additionally, this study showed that pre-procedural PLR \>111 predicted severe atherosclerosis with a sensitivity of 61% and specificity of 59%. PLR was independently associated with Gensini score, together with age, WBC, and low HDL, in the multivariate analysis. To our best knowledge, this study is the first report investigating the relationship between PLR and severity of atherosclerosis.

The initiation, progression, and propagation of atherosclerosis in the coronary arterial wall are influenced by multiple factors. Inflammation plays a crucial role at all stages of atherosclerosis, from initiation through progression and, finally, in the thrombotic consequences of this disease ([@ref1], [@ref22], [@ref32], [@ref33]). Lymphocytopenia is a common finding in chronic inflammatory states because of increased lymphocyte apoptosis. Moreover, the leukocyte production in bone marrow makes a shift towards increasing neutrophils and decreasing lymphocytes in response to stress. Lymphocytes represent a more convenient immune response, while neutrophils cause a destructive inflammatory reaction ([@ref7]). The diagnostic and prognostic usefulness of a low lymphocyte count was demonstrated in patients with acute coronary syndrome and stable CAD, respectively ([@ref6], [@ref34]). Low lymphocyte count was found to be significantly related with the survival in a population-based analysis of patients with known or suspected stable CAD by Ommen et al. ([@ref6]), and they suggested that low lymphocyte count is a potential addition to clinical prognostic models in patients with stable CAD and that it may have possible independent prognostic value. The pathophysiologic mechanisms underlying these findings are speculative. However, it is reasonable that the lymphocyte count indicates an early marker of physiologic stress and systemic inflammation. In our study, the PLR values of participants were positively correlated with CRP levels, and they showed a significant positive correlation with neutrophil count, supporting that PLR may indicate an inflammatory state in the body.

Increased proliferation in megakaryocytic series and relative thrombocytosis are two results of the ongoing inflammatory state in the body, which results in a prothrombotic condition. It is reported that healthy adults with increased platelet counts have an augmented risk of thrombotic complications. The circulating platelets may contribute to the initiation of atheromatous plaque formation and trigger its complications ([@ref10]). High platelet and low lymphocyte counts in the circulation have been suggested to be risk indicators of worse cardiovascular outcomes in previous studies ([@ref6]-[@ref10], [@ref34], [@ref35]). A recently developed new prognostic marker, high PLR, integrates the predictive risk of these 2 parameters into 1. The advantage of PLR calculation could be that it reflects the condition of both aggregation and inflammatory pathways, and it may be more valuable than either platelet or lymphocyte count alone in the prediction of coronary atherosclerotic burden. Several new studies suggesting a relationship between PLR and CAD have been published. Azab et al. ([@ref15]) have shown that higher PLR values are associated with an increase in long-term all-cause mortality in patients admitted with non-ST-segment elevation myocardial infarction (NSTEMI). In a recent study by Acar et al. ([@ref36]), PLR was found to be independently related with coronary collateral development in patients with chronic total occlusions. In our previous study, we showed that high pre-procedural PLR value is a significant and independent predictor of no-reflow development in patients undergoing primary coronary angioplasty ([@ref16]). In the present study, we found that pre-procedural PLR value correlated positively with the amount of coronary atherosclerotic burden in CAD patients. Also, we showed that patients with high pre-procedural PLR value are more likely to exhibit severe atherosclerosis on coronary angiography. We found that PLR is independently associated with Gensini score, with a ß coefficient of 0.141 in the multivariate analysis. It means that a 10-unit increase in PLR value is associated with a 1.41-point increase in Gensini score.

Diabetes mellitus (DM), a systemic disease characterized by hyperglycemia, is a well-known major risk factor for CAD. High serum glucose is associated with earlier micro- and macro-vascular complications of DM. Furthermore, it has been demonstrated that fasting glucose may also be independently associated with the development and severity of atherosclerosis in non-diabetic patients ([@ref37], [@ref38]). Patients in all 3 groups of our study had similar DM rates, and fasting plasma glucose was positively correlated with Gensini score. After the exclusion of 92 diabetic cases from the study population, fasting plasma glucose was still correlated significantly with Gensini score. This indicates that the initiation and progression of coronary atherosclerosis accelerate with increases in fasting plasma glucose, even in non-diabetic patients. So, our results are in line with the literature.

HDL works for protection against CAD, and low plasma level of HDL is another important risk factor for the initiation and progression of coronary atherosclerosis. The inverse association between HDL level and coronary artery disease is strong and consistent in population-based studies ([@ref39]). Thus, in our patient population, it is reasonable to find that plasma HDL level was significantly lower in the severe atherosclerosis group. Our results were compatible with the results of a recent study by Karan et al. ([@ref40]), in which they showed a positive correlation of fasting glucose and a negative correlation of HDL with the severity of coronary atherosclerosis.

Study limitations {#sec1-5}
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Our study has some limitations, including the limited number of study participants from a single center and the cross-sectional design. The amount of coronary atherosclerosis was evaluated only by coronary angiography; since it displays only the lumen of coronary arteries, it does not provide extensive data about the coronary plaque burden. Therefore, further studies performed with intravascular ultrasound and/or coronary CT may provide more accurate information about the amount of coronary atherosclerosis. Lack of other established inflammatory markers, such as C-reactive protein, interleukin-6, and tumor necrosis factor-a, is another limitation of the study. Another limitation of this study is that it does not give an idea about the cause-and-effect relationship between PLR and coronary atherosclerosis. Although we found significant associations, further large-scale, prospective studies are needed to clarify and confirm the association between PLR and coronary artery disease severity and whether it is a result or cause of severe atherosclerosis. Despite these limitations, to our knowledge, this is one of the first studies evaluating the relationship between PLR on admission and the severity of coronary atherosclerosis assessed by Gensini score.

Conclusion {#sec1-6}
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In conclusion, we suggest that high PLR appears to be additive to conventional risk factors and commonly used biomarkers in predicting severe atherosclerosis, and PLR value correlates positively with Gensini score. When we consider that PLR is a calculation of routine complete blood count parameters that does not require any additional expense and is a readily available marker, it can help to identify individuals at high risk for advanced CAD who might need a more aggressive therapeutic approach and closer clinical follow-up.

**Conflict of interest:** None declared.

**Peer-review:** Externally peer-reviewed.

**Authorship contributions:** Concept - M.Y., A.Y., H.K.; Design - M.Y., H.K., A. A., M. A., N.P; Supervision - S. A., M.Y., M.Z.B.; Resource - S. A.; Material - M.Z.B., N.P, H. A., M. A.; Data collection and/or processing - A. A., H. A., N.P, M.Z.B., M.Y.; Analysis and/or Interpretation - M.Y., M.O., K.; Literature search - M.Y., M.O.; Writing - M.Y.; Critical review - H.K., M.O., A.Y.
