On artherogenic index of plasma in sickle cell anaemia patients

Introduction Sickle cell anaemia (SCA) is an inherited abnormality of haemoglobin associated with reduced life expectancy. Patients' complications include dyslipideamia. This study was aimed at determining the artherogenic index of plasma (AIP) in sickle cell anaemia patients and compares the value to HbAA controls value. A high AIP is strongly predictive of elevated cardiovascular risk. Methods A comparative study was conducted among SCA patients attending the haematology clinic, Lagos State University Teaching Hospital (LASUTH) and HbAA Phenotype controls. A total of 304 participants were recruited consisting of equal numbers of SCA and HbAA controls. Single lipid profiles were done; logarithms of triglycerides/high density lipoprotein were calculated to obtain AIP and lipid profile ratios established for all participants. Results There were lower mean values of Total Cholesterol (TC), High Density Lipoprotein(HDL) and Low Density Lipoprotein (LDL) amongst SCD participants than controls and higher mean values of triglycerides (TG) and Very Low Density Lipoprotein (VLDL) in SCD p < 0.05. The AIP in SCD ranges from -0.62 to 1.32 while that of controls ranges from -0.56 to 0.61.The mean AIP were 0.14 ± 0.29 and -0.009 ± 0.26 in SCD and controls respectively. P value = 0.002. Conclusion AIP value is higher in sickle cell anaemia than controls, the former have lower mean values of TC, HDL and LDL and higher mean values of TG and VLDL.


Introduction
In 1910 Dr James Herrick first described SCA in a Dental student in Chicago, USA [1]. Sickle cell gene is characterized by a point mutation in the 6 th codon of the haemoglobin gene in which adenine is replaced by thymine (GAG→GTG).The mutation results in the replacement of glutamic acid by valine on the 6 th amino acid in the β globin chain of the haemoglobin molecule. Considerable variation in clinical severity occurs in SCA patients despite possessing the same basic identical genetic mutation (GAG→GTG) [2]. Recognized causes of these variations include co-inheritance of α-thalassaemia [3], expression of adhesion molecules on white blood cells [4], steady state neutrophil counts and function [5], haemoglobin haplotypes and HbF concentrations [6], levels of transferrin/Creactive protein [7], socio-economic status [8], plasma level of IgG and in particular IgG3 [9], levels of circulating immune complexes [10] and dyslipidaemia [11].

Lipid
Profile: Dyslipidaemia depicts deranged plasma concentration of the lipid profile [12]. thrombo-embolism (VTE) [13] in SCA and general population. These complications are common causes of morbidity in SCA [11].
Pulmonary embolism and hypertension are also common causes of morbidity and mortality in SCA consequent upon thrombo-embolic disease as a result of dyslipidaemia [14].

Dyslipidaemia, cardiovascular diseases and venous
thrombo-embolism in SCA: There are several reports on risk factors of cardiovascular diseases (CVD), these are dyslipidaemia, smoking, poor diet, hypertension, sedentary life style and obesity [15][16][17][18]. SCA patients are known to be more predisposed to VTE than the general population [19]. Various reported processes involved in the development of VTE in SCA include dyslipidaemia and associated erythrocyte adhesions [20], platelet aggregation [21], coagulation defects [22], free hemoglobin-induced oxidative damage [23], leukocyte activation in the setting of chronic inflammation and erythrocyte-induced endothelial dysfunction [24].
However, amongst these risk factors, dyslipideamia is the most important [25].

Results
A total of 304 participants were finally recruited after excluding nonconsenting SCD patients and controls including 25 controls that have sickle cell trait and are double heterozygotes like HbSC, participants consisted of equal numbers of sickle cell patients and controls. The mean age of SCD was lower compared with controls and expectedly the mean BMI of SCD was also lower than that of controls. There are more males than females in both groups. The mean number of crisis/year in SCD was 1.6 ± 0.6 and the mean number of blood transfusion per year was 1.79 ± 1.28 (Table 1).
The reference ranges of total cholesterol, triglyceride, HDL, VLDL and LDL in SCD and controls are presented in Table 2. The means of total cholesterol, triglyceride, HDL, VLDL and LDL in SCD and that of controls are shown in Table 3. Analysis of variance (ANOVA) of these means produced F ratio of 581.70 and 685.90 for SCD and controls respectively with p values of both groups being < 0.05. The ratio of LDL/HDL, TG/HDL and TC/HDL for both the SCD and controls are also presented in Table 3. ANOVA of the ratios also produced F ratio of 74.41 and 265.50 of both the SCD and controls respectively and p values < 0.05 for both groups. The artherogenic index of plasma (AIP) in SCD ranges from -0.62 to 1.32 while that of controls ranges from -0.56 to 0.61. The mean AIP were 0.14 ± 0.29 and -0.009 ± 0.26 in SCD and controls respectively (Table III).
Using independent t-test for comparisons of SCD and controls, the  [29].
A study on lipid homeostasis in SCA is necessary because red blood cells membrane is made up approximately 50% of lipid and plasma phospholipids contributes significantly to the synthesis of erythrocytes membranes [42]. Plasma non esterified fatty acids (NEFA) are also building blocks of erythrocyte membranes and its alteration could impact on the structure and function of red blood cells [43]. Therefore, abnormal lipid homeostasis could alter red blood cell membrane fluidity and functions leading to a significant worsening in sickle cell anaemia [44]. Abnormalities in total cholesterol either an increased or decreased level is associated with increased mortality from all causes [45]. Several authors have reported lower than reference value of cholesterol in SCA than general population [46][47][48]. Though, in our study the mean values of these parameters were generally lower and statistically significant in SCA than in controls, they were within normal reference ranges (Table 2). Similar findings were reported amongst Nigerians in 2017 [49].
It is well established that various haemolytic anaemias with high erythropoietic activity including sickle cell anaemia have been described to be associated with hypocholesterolemia [50]. The pathogenesis of sickle cell anaemia-lipid associated abnormalities have been linked to high erythropoietic activity because of increased cholesterol use, defective liver function secondary to iron overload and malfunctioning post absorptive plasma homeostasis of fatty acids in sickle cell anaemia [51]. The clinical relevance of hypocholesterolemia in SCA include a risk factor to developing depression and suicidal tendencies as reported in 1994 [52]. It may also increase probability of mortality in SCA than in controls [53,54]. Weather impacts on serum cholesterol and triglycerides.
The latter is reported normally lower in winter than in summer, while cholesterol is higher in winter than summer [55,56]. This study was carried out in rainy season in Nigeria which could have impacted on the results. Prolonged tourniquet application between 2-5 minutes before sample collection which was avoided during samples collection in this study is known to increase cholesterol level from 5 to 15% [57]. Disease conditions such as hypothyroidism and nephrotic syndrome also impact on LDLcholesterol, VLDL-cholesterol and total cholesterol by increasing their levels [58], while infection and inflammation may decrease total cholesterol and HDL cholesterol and increase triglycerides [59] Dilutional effect due to a postural change from an upright to a supine position could reduce the cholesterol levels by 10% and triglycerides by 12% [60]. All these could have influenced the AIP results obtained for SCA and controls and are all possible limitations of the study.
Our study participants were fasted before blood samples were drawn for lipid profile, should a lipid profile sample be fasting or

Competing interests
The authors declare no competing interests.

Acknowledgments
The authors wish to thank Mr Femi Olaosebikan who analyzed the samples and all LASUTH/APIN Project Laboratory personnel.