Identification of lipid accumulation product (LAP) as a marker of metabolic syndrome: a study in healthy population of MMU

Metabolic syndrome (MetS), is a collection of lipid and non-lipid cardiac related disease risk factors, is an important public health issue because of its higher prevalence with development of diabetes mellitus and cardiovascular diseases. Henry Kahn anticipated lipid accumulation product (LAP), as a novel marker of central lipid accumulation, to predict the risk of MetS. This study was conducted in Department of Biochemistry of MMIMSR, Ambala, Haryana. In the current study, we are researching over a new diagnostic tool for diagnosing MetS by LAP use. MetS is diagnosed by National Cholesterol Education Program Adults treatment panel III (NCEPATP III) and then compared with LAP to find its efficacy over other variables. 200 volunteers were enrolled in this study, their biochemical parameters were estimated and anthropometric measurements were taken. MetS was diagnosed in apparently healthy subjects. LAP was calculated by Henry Kahn formula and required statistical tools were applied to analyse results. The parameters of MetS positive cases were compared with LAP and its validity was tested statistically. 56 (28%) out of 200 subjects were positive for MetS. More females (30) than males (26) were diagnosed positive for MetS. LAP values were found to be higher in MetS cases, its efficacy was confirmed by ROC curves. MetS was diagnosed in volunteers who were considering themselves as healthy. Raised LAP and LAP2 were found, in MetS positive subjects than MetS negative. Relation of LAP and MetS came to be strong. Further, researches in this area are definitely recommended.


INTRODUCTION
The metabolic syndrome (MetS) is de ined as a bundling of components that re lects the growing waist lines of the world (Cornier et al., 2008). MetS, is a group of lipid and non-lipid factors revolving around risk of cardiovascular disease of metabolic origin. Mets is an important community health issue because of its high occurrence and relationship with development of diabetes mellitus (DM) and cardiovascular disease (CVD) (Sung et al., 2009). MetS refers to a constellation of risk factors when occur-ring together surges the risk for coronary artery disease (CAD), stroke, DM (Sharma et al., 2013) , metabolic abnormities including obesity, abnormal fat distribution (Tung et al., 2011), dysglycemia, dyslipidemia and hypertension (Katulanda et al., 2012).
Irrespective of the presence of any abnormalities of glucose metabolism, persons with MetS are at increased risk of DM. The presence of DM and MetS simultaneously potentiates the cardiovascular risk related with each of the two conditions. Characterizing MetS with the incidence of diabetes is therefore bene icial for the purpose of cardiovascular prevention (Kengne et al., 2012). Clinically, exposure of MetS is also vital to catch a high-risk group of individuals who require intervention to prevent further complications. The most widely acceptable and used de initions are by the National Cholesterol Education Program (NCEP) on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults treatment panel III (ATP-III) proposed in 2001 and the International Diabetes Federation (IDF) proposed in 2005 (Mangat et al., 2010).
Prevalence of MetS is in Pakistan and India was shown 34.8% and 25.3% respectively (Katulanda et al., 2012). There is currently a debate surrounding the identity of MetS and its academic utility and diagnostic capacity. Along with the increase of visceral adipose cells, the serum concentrations of certain lipids would raise, during periods of lipid excess. This state is referred to as "lipid over accumulation" could tip to ectopic deposits of lipids in non-adipose tissues, where metabolic abnormalities and insulin resistance (IR) de initely would come into action. Henry Kahn projected the use of "lipid accumulation product" (LAP), as a novel guide of principal lipid accumulation, to calculate the risk of MetS. LAP is based on a blend of waist circumference (WC) and plasma TG levels. The LAP method was shown to predict DM and identify cardiovascular risk better than basal metabolic index (BMI) in previous studies (Kahn, 2006). Analysis done by areas under the curves (AUCs) for receiveroperating characteristic (ROC) curves showed that LAP was a better predictor of diabetes when compared to waist-to-hip ratio (WHR), WC and BMI, in both genders (Chiang and Koo, 2012).
Recently, a strong relation between LAP and MetS was de ined using the revised diagnostic standards of National Cholesterol Education Program/Adult Treatment Panel III (NCEP/ATP III), with area under ROC (0.91) in Argentinean males (apparently healthy), was reported (Taverna et al., 2011). Crosssectional analysis of the NHANES III cohort presented that higher LAP, was associated with LDL-C, apo B, uric acid levels, higher total cholesterol (TC)/HDL-C, apo B/apo A1 ratios and lower HDL-C levels when compared to BMI. In the present study, we are trying to stumble on a new diagnostic and economical tool for diagnosing MetS (NCEPATP III) by the help of LAP and moreover to ind its ef icacy over other variables.
Recently, a strong relation between LAP and MetS was de ined using the revised diagnostic standards of National Cholesterol Education Program/Adult Treatment Panel III (NCEP/ATP III), with area under ROC (0.91) in Argentinean males (apparently healthy), was reported (Taverna et al., 2011). Crosssectional analysis of the NHANES III cohort presented that higher LAP, was associated with LDL-C, apo B, uric acid levels, higher total cholesterol (TC)/HDL-C, apo B/apo A1 ratios and lower HDL-C levels when compared to BMI. In the present study, we are trying to stumble on a new diagnostic and economical tool for diagnosing MetS (NCEPATP III) by the help of LAP and moreover to ind its ef icacy over other variables.

Study design
Cross sectional and observational.

Target population and selection
The prevalence of MetS in India has been documented to be from 11% to 41% across vast country of India with numerous socio-cultural varieties (Kahn, 2006). Considering 15% prevalence 196 subjects were required so we took total 200 subjects who volunteered by random selection method.

Study area
This study was carried in Biochemistry department of Maharishi Markandeshwar Institute of Medical Sciences and Research, Mullana, Ambala, Haryana. The study was conducted among the residents and staff members of MMU campus.

Study plan
200 total apparently healthy subjects were randomly selected, after taking consent. Out of them, 100 were females and 100 were males. A cross sectional study design was used for studying the predictive ef icacy of LAP in diagnosing MetS (NCEPAT-PIII). Pregnant females, subjects on medicines or steroid therapy or any other hormonal therapy, any endocrine disorders (hypothyroid or hyperthyroid, Cushing syndrome) etc., were excluded.
All procedures completed in studies were in accordance with the ethical standards of the institutional research committee. Informed consent, both in English and vernacular language, was taken from the volunteers included in the study. Biochemical and other investigations were done to meet the criteria of NCEPATPIII for diagnosing MetS [fasting blood glucose, serum triglycerides, serum HDL]. LAP was calculated from data available. Gender wise data was collected and results were tabulated. Anthropometric measurements included WC, weight, height, hip circumference and BP. All measurements were taken with standard instruments and standard techniques. LAP was calculated by using formula (Kahn, 2006), We additionally calculated LAP2 by modifying the original formula according to our indings. In the original formula, LAP= [WC-65] ×TG in males,  ×TG in females. Where, 65 and 58 were lowest WC found in men and women respectively in that particular study. In our study, the minimum WC of 69 cm was found in men and 71 cm in women. This measurement was quiet similar in men but different in females, hence we calculated LAP2 and compared its values with original LAP and its usefulness in diagnosis of MetS.

Statistical analysis
Frequency distribution was presented in simple number and proportions (percentage). Descriptive statistics was calculated for the continuous data and to test the differences between means, independent t-test was used. ROC for various risk parameters was prepared. A 95% CI and p-value <0.05 have been re lected to be statistically signi icant. All the data was analyzed by using SPSS version 20 (IBM, Chicago, USA).

RESULTS AND OBSERVATIONS
In the present study overall BMI for 200 subjects was minimum was 16.15, maximum 51.6 with mean as 26.63±5.22 kg/m 2 . Minimum, Maximum and mean of SBP was 110,130 and 117.050±6.93 mm Hg. Minimum, Maximum and mean of DBP was 60,90 and 78.10±7.11 mm Hg. Table 1 is depicting overall descriptive of total volunteers. All the parameters with minimum, maximum and mean with std deviation is shown. Table 2 is depicting gender variation signi icant difference of values are found (0.013) in FSG, (0.000) in TG, (0.000) in TG/HDL, (0.000) in WHR, (0.000) in height, (0.000) in weight, and (0.002) in LAP2.
These signi icant values are positive outcomes of our study. LAP was insigni icant between males and females.  Table 4 is depicting AUC for parameters again LAP and LAP2 has achieved its position being better marker than rest with auc (0.867, 0.822) respectively. Table 5 is depicting Diagnosis of MetS by NCEPATP III criteria.

DISCUSSION
The MetS is a multiplex risk factor for CVD. The syndrome develops through interplay of obesity and metabolic susceptibility (Grundy, 2007). Primary and timely identi ication of high risk persons for MetS could be important to forecast and prevent CVD and DM. NCEP and other organisations have proposed that MetS can be recognised clinically by a clustering of simple clinical measures including WC, BP, TG, HDL and glucose. According to NCEP ATPIII (2001) at least three of the following criteria should be met (Song and Hardisty, 2008).
In many initial studies, LAP method proved its ef icacy to predict diabetes and recognize cardiovascular risk better than BMI (Chiang and Koo, 2012).
Mean of LAP and LAP2 in MetS positive subjects was found to be on higher side than MetS negative subjects. The large difference could be easily seen in Figure 1a, b this gives the evidence of LAP/LAP2 being an important marker for identifying MetS. Similar results were found in the study by Ejike, independent samples t-tests presented that mean LAP (p<0.001) and mean WHtR (p=0.022) dimensions were signi icant and higher in the MetS group, relative to the group without the syndrome (Ejike, 2011).
Descriptive statistics on total 200 subjects is given in        LAP in our study was higher than found in the study of Taverna et al. (35.65±28.74) but LAP2 was closer to it. This could be probably due to the difference in WC of our collected data (Taverna et al., 2011). Table 2 (Liu et al., 2011). In their study, most of the lipid parameters were more in males similar to our indings.

Data in
The data in Table 3 (Kawamoto et al., 2011). Table 4 is self-explanatory with higher achievements of LAP and LAP2.

Comparison of LAP, LAP2 as test variable
The area under ROC curve quanti ies the total ability of the test to differentiate between various parameters to be used as diagnostic tool for MetS.  (Kawamoto et al., 2011). In another study by Ejike (2011), the ROC analyses showed that LAP (AUC = 0.937) and WHtR (AUC = 0.905) predicted the MetS, better than the other indices. In a study by Chiang and Koo (2012), LAP showed the highest prediction accuracy among adiposity measures with an AUC of 0.901. LAP showed the highest diagnostic accuracy for MS-NCEP/ATP III (AUC 0.91 and 0.90 among males and females) in the study by Taverna et al. (2011). In a study by Yuan-Lung Cheng et al., males were strongly found associated with Mets, and the LAP and Fatty liver index (FLI) were better when compared to other variables to diagnose Mets among the 29,797 individuals. Both indexes were also found to be better than other variables to diagnose Mets in persons without fatty liver disease (AUROC: 0.871 and 0.879, resp.) and the predictive power was higher among women (Cheng et al., 2017).
The diagnosis of MetS needs ive factors -one anthropometric and four clinical. The measurement of blood pressure via auscultation method bring observer bias, and could possibly expose the individual and practitioner to mercury (if broken) and is moreover problematic to use in large epidemiological studies. Measurements of anthropometric indices could also include some observers prejudice. The measurement of circulating blood proiles for glucose, TG and HDL-C are all time consuming and costly implications. Therefore, the outcome that LAP delivers is sensitive and smart screening method for MetS. LAP requires only the measuring of circulating serum TG and the measurement of WC. Utilisation of LAP method (the superior marker of the MetS, based on the data presented in many researches) would be more economic to diagnose MetS considerably. According to a study of Ray. L, LAP index is a better predictor of MetS when compared to WC and BMI and should be merged in laboratory reports as timely, accurate, and budget friendly marker of metabolic syndrome (Ray et al., 2018). The LAP method comes out as a superior predictor of the MetS, not just because of its speciicity and analysis, but because it captures both indices of anthropometric and metabolic scopes of visceral fat over-accumulation. This suggests that no matter whether excess lipids are stored as visceral fat or as TG, it is arrested by LAP. Rationally speaking, LAP will tend to increase as more fats are deposited in non-adipose "ectopic" organs like liver, arteries, pancreas or kidneys, where they may undesirably affect tissue function and interfere with systems of cardiovascular regulation and/or when they are stored as TG with its attendant cardio-metabolic associations (Ejike, 2011).

CONCLUSIONS
To conclude, 56 Persons (28%) out of total subjects were positive for MetS, which is remarkable achievement both for researcher and subject as well. More females (30) than males (26) were positive for MetS. High values of LAP and LAP2 were found, in MetS positive subjects when compared with MetS negative which was statistically proven. The minimum and maximum value of LAP was (26.7, 396.5 cm mmol/l) and LAP2 was (17 and 375.4 cm mmol/l) in males MetS+ve. In females of MetS+ve the minimum and maximum value of LAP was (24.15, 214.33 cm mmol/l) and LAP2 was (2.52 and 157.4 cm mmol/l) respectively. LAP and LAP2 are predicted to be highly ef icient markers of MetS.