|Year : 2022 | Volume
| Issue : 4 | Page : 931-938
Small dense low-density lipoprotein or low-density lipoprotein for cardiovascular disease in Indians: Meta-analysis addressing the diagnostic dilemma
Komal Shah, VP Varna, Nimi Elizabeth Thomas
Department of Public Health, Indian Institute of Public Health, Gandhinagar, Gujarat, India
|Date of Submission||30-Jan-2022|
|Date of Acceptance||11-Apr-2022|
|Date of Web Publication||10-Feb-2023|
Dr. Komal Shah
Indian Institute of Public Health, Gandhinagar, Opp. Air Force Head Quarters, Nr. Lekawada Bus Stop, Gandhinagar-Chiloda Road, Gandhinagar - 382 042, Gujarat
Source of Support: None, Conflict of Interest: None
Background: We aimed to assess the association of small dense low-density lipoprotein (sdLDL) – a novel lipid marker for cardiovascular disease (CVD) risk estimation in Indians with the meta-analysis approach. Methods: Various databases, namely PubMed, MEDLINE, and EMBASE, were used to identify the prospective studies showing an association between CVD risk and lipid profile in the Indian population. Heterogeneity was assessed using Q and I2 statistics, and data were expressed using the standardized mean difference (SMD) with 95% confidence interval (CI). Results: After database search, six eligible studies assessing levels of sdLDL and LDL in Indian patients with premature CVD were identified. Level of sdLDL was found to have positive relation with CVD risk in Indians (SMD = 1.352, 95% CI: 0.744–1.96 mg/dL, I2 94.04%, P < 0.001) along with LDL (SMD = 0.680, 95% CI: 0.180–1.180 mg/dL) levels. However, the degree of association was greater with sdLDL. Conclusions: The current meta-analysis clearly identifies sdLDL as the better marker of premature CVD in Indians, especially in case of normal values of classical markers such as LDL.
Keywords: Cardiovascular disease, Indians, meta-analysis, small dense low-density lipoprotein
|How to cite this article:|
Shah K, Varna V P, Thomas NE. Small dense low-density lipoprotein or low-density lipoprotein for cardiovascular disease in Indians: Meta-analysis addressing the diagnostic dilemma. J Datta Meghe Inst Med Sci Univ 2022;17:931-8
|How to cite this URL:|
Shah K, Varna V P, Thomas NE. Small dense low-density lipoprotein or low-density lipoprotein for cardiovascular disease in Indians: Meta-analysis addressing the diagnostic dilemma. J Datta Meghe Inst Med Sci Univ [serial online] 2022 [cited 2023 Apr 1];17:931-8. Available from: http://www.journaldmims.com/text.asp?2022/17/4/931/369503
| Introduction|| |
The process of epidemiological and demographic transition is happening at a remarkable pace all over the world. The changes in population size and distribution, the improvement in health care, and the transition of disease patterns from communicable to noncommunicable diseases have led to low mortality, high morbidity and a dual burden of disease in India. Noncommunicable diseases are the major cause of deaths, accounting for 68% (38 million) of all the deaths globally. Every year nearly 5.8 million (60%) people die from noncommunicable diseases, with cardiovascular diseases (CVD) being the leading cause of death in India. CVDs contributed to 28·1% of total deaths and 14·1% of total disability-adjusted life years in Indians in 2016 compared with 15·2% and 6·9%, respectively, in 1990.
“Atherogenic dyslipidemia” a condition characterized by a combination of hypertriglyceridemia, high levels of low-density lipoprotein (LDL), and low levels of high-density lipoprotein (HDL) cholesterol is typical of Asian Indians. This condition is often associated with the interaction between environmental, lifestyle, dietary factors, and socioeconomic factors.,, After more than 30 years of research, a causal relationship between LDL cholesterol levels and CVD outcomes was established. However, substantial number of studies report the lack of association between LDL and risk of CVD in Indians.
LDLs are a group of lipoproteins consisting of discrete subsets possessing numerous atherogenic properties. LDL has three subclasses, namely large buoyant LDL, intermediate-density LDL, and small density LDL (sdLDL). Individuals with the lipoprotein Type A phenotype are characterized by the prevalence of large buoyant LDL (LDL >25.5 nm). The type B phenotype has a predominance of sdLDL (LDL ≤25.5 nm) levels along with high triglyceride (TG) levels, reduced HDL cholesterol and high hepatic lipase activity. Many individuals with CVD manifestations have LDL levels within the normal range, thus demanding the need to identify the best biomarkers in predicting CVD risk. Recently, sdLDL has been suggested as a good biomarker of CVD risk. It is expressed in adulthood due to the interaction of genetic and environmental factors such as dyslipidemia, insulin resistance, and obesity. Due to their small size, biochemical and biophysical properties, sdLDL penetrates the arterial wall and serves as a source of cholesterol and lipid storage. The susceptibility of sdLDL to oxidation further enhances its atherogenic potential.,
A subgroup analysis of the INTERHEART study performed on Asians suggested a need to identify the association between sdLDL and CVD, to further refine the risk prediction in this ethnic group. Although several studies gave promising results, the public health usage of sdLDL as lipid markers is not yet practised. Keeping in mind the economics of the conventional lipid tests and the test rates for detecting novel biomarkers, there is a need to clearly identify the better marker for the prediction of CVD risk in Indians. A cost-effectiveness analysis perspective will help in making better informed decisions. The critical components for the gap in translational research are as follows: (1) lack of systematic ethnicity-based assessment of prevalence and patterns of LDL sub-fraction abnormalities and (2) reported contradictory studies stating the lack of association between CVD and sdLDL after multivariate adjustment of confounding factors, mainly TG and HDL levels.
The current study aims to compare the diagnostic efficacy of sdLDL with LDL for premature CVD in Indians through the meta-analysis approach.
| Methods|| |
The current systematic review and meta-analysis was conducted in accordance with the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-analyses and is presented in [Figure 1].
|Figure 1: Preferred reporting items for systematic reviews and meta-analyses chart|
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Inclusion and exclusion criteria
The screening process to identify all the potentially relevant articles was performed by two independent reviewers. The articles selected for the review were limited to original papers in English with full text and abstract availability. Further only original articles from India and those that compared mean sdLDL levels in patients with coronary artery disease (CAD) and without CAD (≥18 years) were chosen for the review. Articles that used median as a measure for estimating sdLDL levels were excluded. Duplicated reports, studies on non-Indians, migrated population, and studies reporting association with other diseases were also excluded from the review.
Potentially relevant articles for the review were identified by searching various electronic databases-MEDLINE, EMBASE, and PubMed from inception to December 2021 using the following search terms: “small dense LDL” or “sdLDL,” and “cardiovascular disease” or “coronary artery disease” and “Indians” or “Indian population. Reference articles of the primary studies were also screened for identifying potential papers. Both the authors performed the literature search independently to avoid bias and any conflict was settled by discussion and mutual consent. Details collected from relevant publications were: first author, years of data collection, year of publication, number of cases and controls, and mean and standard deviations of various lipid parameters.
Risk of bias assessment
The Cochrane risk of bias tool was used to assess the quality of individual studies by two authors. The studies were categorized into low risk of bias, showing some concerns or high risk of bias domain based on the quality assessment.
The relationship between various lipid markers and CVD was extracted from each study in terms of standardized mean difference (SMD) with 95% confidence interval (CI) levels. I2 statistic (significant at P < 0.10) was used as a continuous measure of heterogeneity with various Grades of I2 indicating the level of heterogeneity (high– 75%–100%, medium– 50%–70%, low– 0%–50%). A two-tailed value of P < 0.05 was considered statistically significant where a fixed-effect model was used in cases with I2 below 50%, and in cases of I2 above 50%, a random-effect model was adopted. Statistical analyses were performed using MedCalc for Windows, version 20.013 (MedCalc Software, Ostend, Belgium). The association of lipid markers with CVD incidence is graphically presented as forest plots.
| Results|| |
In the initial stage, we have identified 598 articles, of which 135 duplicate reports were removed. After first screening, remaining 463 articles were further evaluated based on abstract and titles, and finally, six articles were found suitable for the meta-analysis [Figure 1].,,,,, The details of lipid parameters (both cases and control) of the included studies are presented in [Table 1] and [Table 2].
|Table 2: The detailed lipid parameters of the studies included in the meta-analysis|
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Relationship between cardiovascular disease and conventional lipid markers
The overall CVD risk prediction by conventional LDL lipid parameters is presented in [Figure 2]. Overall pooled effect showed that the CVD risk increases with increasing TG (SMD = 0.464, 95% CI: 0.250–0.678 mg/dL, I2 – 36.93%, P = 0.1905) and LDL (SMD = 0.680, 95% CI: 0.180–1.180 mg/dL, I2 – 87.85%, P < 0.0001) levels, whereas it was found to decrease with increasing HDL (SMD = ‒0.427, 95% CI: ‒0.751 to ‒0.104 mg/dL, I2 – 72.08%, P = 0.0132) levels as compared to placebo group.
|Figure 2: Forest plot showing the association of low-density lipoprotein with premature cardiovascular disease in Indians|
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Relationship between cardiovascular disease and small dense low density lipoprotein levels
[Figure 3] shows the pooled results from combining effect sizes for CVD risk with sdLDL levels using random and fixed effect models. Overall direct relation was observed between sdLDL levels and CVD (SMD = 1.352, 95% CI: 0.744–1.960 mg/dL, I2 – 94.04%, P < 0.0001). A study that contributed maximum to the heterogeneity showed inverse relationship between sdLDL levels and CVD risk, showing higher sdLDL values in control as compared to cases. Elimination of this study resulted in reduction in the heterogeneity. The same study showed inverse association in case of LDL levels also. Two other studies by Bansal et al., showed discrepancies between the sdLDL values given in data table and its interpretation in the results section, hence it was removed. In summary findings of individual studies reporting association of LDL with CVD were inconsistent, pooled results (through meta-analysis) showed significant relationship between both. In case of sdLDL, all the individual studies observed significant association with CVD, irrespective of LDL status of the patients and this was clearly reflected in pooled analysis. The degree of association was almost double with sdLDL as compared to LDL with premature CVD in Indians.
|Figure 3: Forest plot showing the association of small dense low-density lipoprotein with premature cardiovascular disease in Indians|
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| Discussion|| |
Lipoproteins have been considered as a risk factor for CVD since many years, and hence, screening for lipid profiles is critical for the early detection and treatment of CVDs. High levels of LDL play a key role in the development and progression of atherosclerosis and CVD. Based on the plasma lipid profile, individuals are categorized into Type A and Type B phenotype. Phenotype B with predominance of sdLDL was found in individuals with metabolic disorders, obesity, and Type 2 diabetes mellitus. The National Cholesterol Education Program III considers predominance of sdLDL as a risk factor for CVD. The graphical presentation of sdLDL effect and its association with premature CVD found in the current study is shown in [Figure 4].
|Figure 4: The graphical presentation of small dense low density lipoprotein and its association with premature cardiovascular disease|
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Atherosclerotic plaques formed by the accumulation of foam cells and lipids in the arterial wall are mainly due to LDL deposition. The native LDL particles do not exhibit the property of lipid accumulation in cultured cells, whereas sdLDL with its longer circulation time is prone to the formation of lipid complexes increasing its atherogenic potential. The atherogenicity of sdLDL can be attributed to the multiple atherogenic modifications such as deacylation, glycation, and oxidation in the blood plasma. Smaller and denser LDLs are more prone to uptake by arterial tissues as compared to larger dense LDL. sdLDL has greater affinity for proteoglycans, which can be attributed to the sialic acid content of the particle. This induces immunological changes leading to atherosclerosis., Thus, this review aims to identify if sdLDL levels can act as a better marker for predicting CVD risk in Indians.
To the best of our knowledge, this is the first and only available meta-analysis performed on the Indian population to measure the association between sdLDL and CVD and to compare it with the classical marker-LDL. The results presented here represent the most relevant information on efficacy/potency of sdLDL as CAD associate in this ethnic group. It is noteworthy to assess whether the inability of current lipid markers in estimating CVD risk in Indians, could be overcome by incorporating sdLDL levels with clinically relevant cut-offs.
Nine articles selected initially, assessed the role of LDL sub-fractions and conventional lipids in Asian Indian CAD patients. Although the cumulative results showed a positive association between CAD and sdLDL, three studies showed an inverse relationship between sdLDL levels and CVD. The discrepancy found between Todur and Ashavaid results and other reports could be attributed to the differences in the methods used for estimating sdLDL. Subgrouping of the population according to genotype, caused significant reduction in the level of sdLDL in healthy control indicating the prime role of polymorphisms in influencing lipoprotein sub-fractions. Moreover, the heterogeneity in data collection can also be ascribed to the varying results. The other two studies by Bansal et al. showed discrepancies in the interpreted results and values in the table, hence it was removed.,
Indians are genetically diverse populations with a unique risk factor profiling having great confounding effect of life style and environmental factors.,,, The CURES-8 study investigated the levels of sdLDL in native Indian patients having diabetes with or without CAD and compared it with healthy individuals. CURES-8 study was a part of large epidemiological study and is of noteworthy importance as they have collected data from Indians residing in Chennai– South Indian state, representing true Indian lipid levels. One of the key findings of the study was the strong association of sdLDL with TGs/HDL ratio. A value of 3.0 had the optimum sensitivity and specificity to detect elevated sdLDL. In contrast to the popular belief, LDL was found to be within normal limits in more than 50% of the subjects and this paradox could be explained by different sizes of LDL, with sdLDL being more atherogenic in nature as compared to large buoyant LDL particles. Similar to CURES-8, other two studies performed on North Indian population also showed a marked increase in sdLDL in cases as compared to controls and also are clinically significant in relation to severity of the CAD., Singh et al. in his study observed higher levels of sd-LDL levels in males, thus suggesting greater chances of developing acute coronary syndrome when compared to females.
Another study by Sharma et al. examined the links between conventional and novel risk factors for CAD in parents and descendants. Metabolic syndrome was identified as a relatively greater risk factor for CAD. The multiple analysis of variance test performed in the study suggested that LDL cholesterol particle size had the strongest association in patients with CAD. Although a majority of the studies suggested a significant association between sdLDL levels and risk of CVD, our findings generated through meta-analysis suggests that both LDL and sdLDL levels correlates well with premature CVD in Indians.
This meta-analysis has several limitations that must be considered: (1) Lack of representative Indian data for sdLDL on diseased and normal population (2) Lack of studies that explored the association by equation derived sdLDL levels, which led to difficulty in matching/calibrating/standardizing lab derived data with those of equation derived data. (3) The results of the study showed high heterogeneity.
| Conclusions|| |
Current meta-analysis clearly identifies sdLDL as better marker of premature CVD in Indians, especially in case of normal values of classical markers such as LDL. These findings can have huge implication in screening guidelines for young Indians where the country is witnessing an increasing burden of disease. Although in order to make it clinically, more applicable and reliable larger prospective studies with longer follow-up in this ethnic group are highly recommended.
As this is a secondary data analysis based study using already published data, the study was exempted from ethical review.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2]