1. Introduction

Cardiometabolic risk factors are a group of conditions that increase the likelihood of developing cardiovascular diseases (CVD) and metabolic disorders. Obesity is a major cardiometabolic risk factor. It is commonly assessed using the Body Mass Index (BMI), a simple index of weight for height. High BMI is associated with an increased risk of hypertension, dyslipidemia, and type 2 diabetes. A study has shown that weight loss interventions can significantly reduce cardiometabolic risk factors [1]. Obesity has emerged as a global pandemic, impacting millions of people across diverse age groups and socioeconomic backgrounds. It is characterized by excessive body fat that increases the risk of numerous health problems, including cardiovascular diseases, diabetes, and certain cancers like breast and colorectal cancer [2]. The prevalence of obesity has risen sharply due to a combination of factors such as sedentary lifestyles, poor dietary habits, and genetic predispositions [3]. Its prevalence has increased dramatically over the past few decades. In 2022, approximately 890 million adults and 160 million children and adolescents were living with obesity [4-7].

The Castelli Index 1 (CRI-I) represents the ratio of total cholesterol to high-density lipoprotein (HDL) cholesterol. It is used as an indicator of cardiovascular risk. A higher CRI-I suggests a higher risk of developing cardiovascular diseases, while a lower CRI-I indicates a lower risk [8]. The Castelli Index 2 (CRI-II), or LDL/HDL ratio, provides insight into cardiovascular risk by comparing the levels of "bad" low-density lipoprotein (LDL) cholesterol to "good" high-density lipoprotein (HDL) cholesterol [9, 10].

Atherogenic index of plasma (AIP) reflects the balance between pro-atherogenic (triglycerides) and anti-atherogenic (HDL cholesterol) lipoproteins in the blood. A higher AIP indicates a higher risk of atherosclerosis and cardiovascular diseases, while a lower AIP suggests a healthier lipid profile. Studies have shown that AIP is strongly associated with obesity and cardiovascular risk beyond traditional risk factors like smoking, hyperlipidemia and diabetes. It predicts cardiovascular events and mortality better than conventional lipid components [11].

Leptin is an adipocyte-derived hormone that plays a role in regulating energy balance, metabolism, and body weight. It is referred to as the "satiety hormone" because it helps to suppress appetite and increase energy expenditure. However, in individuals with obesity, leptin resistance can occur, leading to an inability to respond to the hormone's signals, which contributes to further weight gain and metabolic complications [12]. It is produced by adipose (fat) cells and signals the brain to reduce appetite and increase energy expenditure. In a healthy individual, increased fat mass leads to higher leptin levels, suppressing hunger and promoting weight loss [13].

Ficus exasperata, commonly known as the sandpaper fig, is a species of fig tree belonging to the Moraceae family. This plant has been widely studied for its traditional medicinal uses and pharmacological potential. Ficus exasperata has been used in traditional medicine across various regions, particularly in Africa. Different parts of the plant, including the bark, leaves, and roots, are employed for treating a range of ailments. The leaves are particularly significant and are used as analgesics, antiarthritics, diuretics, wound healers, antiparasitics, vermifuges, abortifacients, and for treating haemorrhoids and venereal diseases. Additionally, the plant parts are used as animal fodder [14]. Phytochemical screening of Ficus exasperata has revealed the presence of various bioactive compounds, including tannins, flavonoids, alkaloids, anthraquinones, steroids, and cardiac glycosides. These compounds contribute to the plant's medicinal properties and have been the focus of numerous studies [15]. Research has demonstrated that Ficus exasperata exhibits a wide range of pharmacological activities. Studies have shown its antidiabetic, anticonvulsant, anti-inflammatory, antimicrobial, hypolipidemic, antioxidant, anti-ulcer, anxiolytic, and hypotensive properties [1]. For instance, aqueous extracts of the leaves have been found to inhibit alpha-amylase and alpha-glucosidase activities, which are key enzymes involved in carbohydrate digestion, making it a potential candidate for managing diabetes mellitus [16]. This study evaluated the effect of ethanol leaf extract of Ficus exasperata on cardiometabolic risk factors in olanzapine-induced obese female Wistar rats.

2. Materials and methods

2.1 Materials

Olanzapine USP 10 mg Tablets (10 mg, oral, 10 tabs, N05AH03, B4-7395) were obtained from Chez Resources Pharmaceutical LTD. Orlistat (A08AB01), manufactured by Getz Pharma (Private) Limited, was also acquired. Both orlistat and olanzapine drugs were sourced from City Medics Pharmacy in Abuja, Nigeria. Orlistat is marketed under the trade name Xenical, while Olanzapine is marketed under the trade name Zyprexa.

 

2.2 Plants collection

Ficus exasperata leaves were collected from the environment of the University of Abuja, Abuja, Nigeria. They were identified at the National Institute of Pharmaceutical Research and Development (NIPRD) herbarium in Abuja, with voucher specimen number NIPRD/H/7268. The leaves were dried and blended into powder using an electric blender. The powdered leaves were then weighed using an SJ-30KWP weighing scale, manufactured by Ohaus Corporation, Pine Brook, NJ, USA.

 

2.3 Preparation of extract

Forty grams of Ficus exasperata leaf powder was dissolved in 200 ml of ethanol and left covered for 48 hours. After this period, the mixture was filtered through a nylon sieve into a small container, and the remaining residue was spread out to dry. The residue was then re-extracted with an additional 200 ml of fresh ethanol for 24 hours. The combined dried extract from these processes was used for this study [17].

 

2.4 Experimental animals

For this study, 30 female albino Wistar rats, each weighing between 190-200 g, were used. The animals were sourced from the animal facility of the Faculty of Veterinary Medicine at the University of Abuja. They were housed in plastic cages in the Department of Human Physiology at the same university. The rats were allowed to acclimate to the laboratory environment for two weeks, with conditions maintained at a temperature range of 24-28°C, relative humidity of 60-70%, and a 12-hour light-dark cycle. They had free access to food and water throughout the acclimatization period.

 

2.5 Experimental induction of obesity

Obesity was induced by administering olanzapine 4 mg/kg dissolved in normal saline using 2 ml disposable needles and syringes through oral gavage for 28 days. The weight and naso-anal length (using meter rule) of the Wistar rats were measured. The body mass index (BMI) of each Wistar rat was obtained by dividing the weight of each rat by the square of naso-anal length. Wistar rats with body mass index greater than 0.68 g/cm2 were considered obese [18].

 

2.6 Experimental design

Rats were divided into five groups of six rats each (n=6). Group 1 served as the normal control and was given normal saline (1 ml/kg). Group 2 was designated as the obese-untreated. Group 3 was non-obese and was given Ficus exasperata extract 100 mg/kg. Groups 4 and 5 were obese and were given Ficus exasperata extract 100 mg/kg and orlistat 100 mg/kg, respectively. Administration was done orally for 28 days.

 

2.7 Animal sacrifice

The animals were sacrificed after 28 days of administration. Animals were anaesthetized with sodium phenobarbital 60 mg/kg [19]. Blood samples were collected via cardiac puncture. The blood samples were dispensed in a plain serum bottle. The serum was prepared by using a bench centrifuge to spin blood samples for 20 minutes at a speed of 3500. A clear supernatant was used.

 

2.8 Body Mass Index Assessment

Each rat was weighed using an electronic scale and the body weight was recorded (BW) in grams (g). The naso-anal length of each rat was measured using a flexible ruler and recorded in centimetres (cm). The BMI was calculated according to the method described by Novelli et al [18]. Using the provided mathematical relationship:

 

 

2.9 Assessment of lipid profile indexes

The Castelli risk index-I was calculated from total cholesterol and high-density lipoprotein obtained from the blood sample. It was calculated by dividing the total cholesterol (TC) by the high-density lipoprotein cholesterol (HDL-C) [20].

 

 

 

The Castelli risk index-II was calculated by dividing the low-density lipoprotein cholesterol (LDL-C) by the HDL-C [20].

 

 

The atherogenic index was calculated as the Log of triglycerides divided by high-density lipoprotein [20].

 

 

 

2.10 Serum Leptin assessment

Assessment of serum leptin level was carried out using a commercially available rat-species-specific ELISA kit; (Fine Test; Catalogue Number: ER0115, Range: 0.156-10 ng/mL, Sensitivity: 0.09ng/ mL).

 

2.11 Statistical Analysis

The data obtained were analysed using one-way analysis of variance (ANOVA) on Graph Pad Prism version 9.3.1 and statistical significance was set at P<0.05.  The results were presented as Mean ±  SEM.

3. Results

3.1 Castelli risk index I, II and atherogenic coefficient

Fig. 1 showed the Castelli risk index-I was significantly higher (p <  0.05) in the obese-untreated group than in the NC (1a). In the non-obese group treated with Ficus, Castelli risk index-I was significantly (p < 0.05) higher compared to the NC. However, it was significantly lower (p <  0.05) compared to the obese-untreated group. In the obese groups treated with Ficus and orlistat, the Castelli risk index-I was significantly higher (p <  0.05) than that of the NC, and significantly lower (p <  0.05) compared to the obese-untreated group. In Fig. 1b, the Castelli risk index-II was significantly higher (p <  0.05) in the obese-untreated group compared to the NC. Both in the Ficus-only and the obese+Ficus groups, the Castelli risk index-II was significantly higher compared to the NC and lower (p < 0.05) compared to the obese-untreated group. In the obese+orlistat treated group, the Castelli risk index-II was significantly lower compared to the obese-untreated, Ficus-only and obese+Ficus groups. In Fig. 1c, the atherogenic coefficient was significantly (p< 0.05) higher in the obese-untreated group compared to the NC. In the Ficus-only group, it was lower significantly compared to both NC, obese-untreated, obese+Ficus and obese+orlistat groups. The atherogenic coefficient in the obese groups treated with Ficus and orlistat was significantly (p < 0.05) lower compared to the obese-untreated group.

Figure 1. Results of Castelli risk index I (1a), Castelli risk index-II (1b) and atherogenic coefficient (1c). NC= normal control. Superscripts a=p<0.05 vs NC; b=P<0.05 vs Obese-untreated; c=p<0.05 vs Ficus-only; d=p<0.05 vs Obese+Ficus. Data presented as Mean ± SEM.

 

3.2 Percentage of body weight change, body mass index and serum leptin

Percentage body weight (Fig. 2a) was significantly higher (p < 0.05) in the obese-untreated group compared to the NC and Ficus-only groups. In the obese groups treated with Ficus and orlistat, the percentage of body weight was significantly decreased (p < 0.05) compared to the NC, obese-untreated and Ficus-only groups. BMI in Fig. 2b was significantly higher (p < 0.05) in the obese-untreated group compared to the NC. In all the other groups, BMI was lower significantly (p < 0.05) compared to the obese-untreated group. Serum leptin level was significantly higher in the obese-untreated group compared to the NC. However, in all the other treated groups, serum leptin was significantly lower (p < 0.05) compared to the NC and obese-untreated groups. In the group treated with orlistat, the leptin level was significantly (p < 0.05) higher compared to the Ficus-only treated group.

Figure 2. Results of percentage body weight change (2a), BMI (2b), and Leptin (2c). NC= normal control; TRIG= triglyceride. Superscripts a=p<0.05 vs NC; b=P<0.05 vs Obese-untreated; c=p<0.05 vs Ficus-only; d=p<0.05 vs Obese+Ficus. 

4. Discussion

Obesity often leads to dyslipidemia, characterized by abnormal levels of lipids in the blood. This includes increased triglycerides (TG) and LDL cholesterol, which further exacerbate the imbalance between TC and HDL-C [21]. Obesity often leads to dyslipidemia, characterized by abnormal levels of lipids in the blood. This includes increased triglycerides (TG) and LDL cholesterol, which further exacerbates the imbalance between TC and HDL-C [22, 23]. These changes could account for the significant increase in the Castelli risk index-I observed in the obese-untreated group in this study. In this study, Castelli risk index-II was significantly higher in the obese-untreated group compared to the NC. Obesity has been shown to increase Castelli Risk Index II (CRI-II), which is the ratio of low-density lipoprotein cholesterol (LDL-C) to high-density lipoprotein cholesterol (HDL-C). Obesity, as confirmed by the results of BMI in this group, has been shown to affect Castelli risk indexes I and II by increasing total cholesterol, decreasing high-density lipoprotein, and dyslipidemia [24]. These are consistent with the findings of this study. Elevated leptin levels are often associated with obesity and can impact lipid metabolism, which in turn affects the Castelli Indexes [25]. Elevated leptin is consistent with the findings of this present study in the obese-untreated group. A higher CRI-I and II means that the balance is tilted unfavourably towards more cholesterol which can potentially contribute to plaque buildup in the arteries, leading to atherosclerosis, heart attacks, and strokes [10]. Thus, the result of Ficus administration in this current study on Catelli risk index-I and II suggests its potential effect in the prevention of plaque accumulation in the arteries. Ficus exasperata extracts contain compounds like flavonoids, tannins, and phenols, which have strong antioxidant properties. Antioxidants help reduce oxidative stress, which can damage lipids and lead to higher cholesterol levels [26, 27]. The extracts have been shown to reduce levels of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) while increasing high-density lipoprotein cholesterol (HDL-C). This shift in lipid profile directly lowers the CRI-I and II [27].

In the present study, the atherogenic index (AI) was significantly higher in the obese-untreated group compared to the NC. Obesity is often associated with higher levels of triglycerides, which contribute to AI. Elevated TG levels are a key component in the calculation of AI, leading to a higher index [21, 28]. Obesity is linked to lower levels of high-density lipoprotein cholesterol (HDL-C), which is considered "good" cholesterol. Since HDL-C helps remove excess cholesterol from the bloodstream, lower levels result in a higher AI [29]. Obesity often leads to insulin resistance, which can result in increased production of very low-density lipoprotein (VLDL) and decreased clearance of triglycerides. This imbalance further elevates the AI [30-32].  Thus, the significant effect of Ficus extract on AI in the present study could be attributed to reduced triglycerides and improved HDL-c levels. The action of this extract on AI in the present study could also have been due to its ability to improve insulin sensitivity [33]. Elevated leptin levels as observed in the present study are linked to insulin resistance, which can lead to dyslipidemia (abnormal lipid levels) and increased AI. Insulin resistance results in higher levels of triglycerides and LDL-C, contributing to atherogenesis [34-36]. Therefore, the extract in the present study reduced AI via leptin-related pathway.

The percentage of body weight was significantly higher in the obese-untreated group compared to the NC in this study. Olanzapine increases appetite and food consumption, leading to weight gain. This is partly due to its antagonistic effects on histamine H1 receptors, which play a role in regulating hunger and satiety [37]. Olanzapine can decrease metabolic rate, reducing the amount of energy expended by the body. This contributes to the accumulation of excess calories as fat [38, 39]. Studies have shown that olanzapine promotes the proliferation of adipocytes (fat cells), leading to increased fat mass [40]. In the present study, the administration of Ficus exasperata significantly reduced the percentage of body weight gain. This action could have been via normal regulation of appetite and food consumption by an agonistic action on histamine H1 receptors, as well as increasing metabolic rate. Plant extracts have been shown to modulate the expression of genes involved in adipogenesis (the formation of fat cells), such as peroxisome proliferator-activated receptor gamma (PPARγ) and CCAAT enhancer binding protein alpha (CEBPα), which can reduce the proliferation of adipocytes [41, 42].

Polyphenols can inhibit the differentiation of pre-adipocytes into mature adipocytes (fat cells), which helps reduce fat accumulation [43]. They can stimulate the breakdown of fat (lipolysis), leading to a reduction in body fat [44]. These could account for the effect of Ficus exasperata administration in the current study on body mass index, which was significantly reduced in the obese+Ficus group compared to the obese-untreated group. Hormones like leptin and insulin play crucial roles in regulating appetite and metabolism. Imbalances in these hormones can lead to overeating and weight gain, increasing BMI [45, 46].

Serum leptin in the current study was significantly increased in the obese-untreated group compared to the NC. Olanzapine may affect the function of adipocytes (fat cells), leading to increased fat storage and higher leptin production [47]. With increased fat mass, the body produces more leptin. However, in some cases, the body becomes resistant to leptin, leading to higher circulating levels of the hormone [48]. Treatment with Ficus exasperata and orlistat significantly reduced circulating leptin levels. Oxidative stress is linked to obesity and metabolic disorders, which can affect leptin levels. The antioxidant properties of Ficus exasperata might help mitigate oxidative stress, potentially influencing leptin production and function [49]. The phytochemicals in Ficus exasperata could modulate metabolic pathways involved in fat storage and energy balance, indirectly affecting leptin levels. Additionally, by enhancing insulin sensitivity, Ficus exasperata extract might help regulate leptin levels, as insulin and leptin are closely related to energy homeostasis.

5. Conclusions

The extract of Ficus exasperata demonstrates significant potential in improving various cardiometabolic indexes, BMI, weight management, and leptin regulation. Ficus exasperata extract offers promising therapeutic benefits for improving cardiometabolic health, managing body weight, and regulating leptin, making it a valuable addition to natural health interventions.

Ethical consent

Ethical approval was obtained from the University of Abuja Ethics Committee on Animal Use (UAECAU), with a reference number (UAECAU/2021/0001). Animals were handled per protocols approved by the Institutional Guidelines on Animal Care and Use Committee and conformed to guidelines set by the National Institutes of Health on experiments involving the use of animals.

 

Authors’ contributions

Conceptualization, O.O., B.R.B.; Methodology, O.O.; Software, O.O.; Validation, O.O., B.R.B., E.D.E.; Formal analysis, O.O.; Investigation, O.O.; Resources, O.O.; Data curation, O.O.; Writing – original draft preparation, O.O.; Writing – review & editing, O.O., E.N.S.; Visualization, O.O.; Supervision, O.O.; Project Administration, O.O.; Funding acquisition, B.R.B., E.N.S.

 

Acknowledgements

We acknowledge the staff of the Department of Human Physiology, Faculty of Basic Medical Sciences, University of Abuja. Nigeria and the Department of Physiology, University of Ilesa, Ilesa, Osun State, Nigeria.

 

Funding

“This research received no specific grant from any funding agency “(the public, commercial, or not-for-profit sectors)”.

 

Availability of data and materials

All relevant data are within the paper and its supporting information files. Additional data will be made available on request according to the journal policy.

 

Conflicts of interest

The authors declare no conflict of interest.

 

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