Lipoprotein (a) and biochemical parameters in elderly

Abstract

Background: Lipoprotein (a) [Lp(a)] is an low-density lipoprotein like particle and is an important independent risk factor for coronary artery diseases (CAD). Few studies on Lp(a) level in Thai elderly to screening risk of CAD may concerned. Aims: To study the relation of Lp(a) level and routine biochemical parameters including lipid profiles and fasting blood glucose in elderly and to determine risk of subclinical symptoms by using Lp(a) levels as early risk predictor. Settings and Design: Cross-sectional study during January to March 2015 at Amphawa district, Samut Songkhram province, Thailand. Materials and Methods: Anthropometric data and CAD risk factors (such as, blood pressure, cigarette smoking and body mass index) were recorded, and blood samples were collected from elderly farmers (N = 60). Each collected blood sample was prepared to serum for determining lipid profiles and sodium fluoride plasma for determine fasting blood glucose. Results : Only the average of prehypertension was out of reference range. There were found that Lp(a) can be used to indicate the risk of dyslipedemia [odds ratio (OR) = 8.80 and relative risk (RR) = 3.60] and prehypertension (OR = 15.67 and RR = 6.50). Statistical Analysis Used: The CAD risk and biochemical parameters were presented in mean ± standard deviation. The calculation of OR and RR of Lp (a) for hypercholesteremia, prediabetes, and prehypertension were calculated by MedCalc (Medcalc software bvba, Belgium). Conclusion: This study can be conclude that Lp(a) check together with lipid profile and blood pressure can be useful to screening of CAD with more accuracy especially in subclinical group.

Keywords: Cholesterol, Dyslipidemia, Lipoprotein (a), Lipid profile, Prehypertension

How to cite this article:
Sudjaroen Y. Lipoprotein (a) and biochemical parameters in elderly. Ann Trop Med Public Health 2016;9:312-5
How to cite this URL:
Sudjaroen Y. Lipoprotein (a) and biochemical parameters in elderly. Ann Trop Med Public Health [serial online] 2016 [cited 2016 Oct 14];9:312-5. Available from: https://www.atmph.org/text.asp?2016/9/5/312/188499
Introduction

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in patients in the USA. [1] The annual costs for CVD hospitalizations was estimated to be $320.1 billion in 2011 alone, approximately $100 billion more than estimated hospitalization costs for cancers and benign neoplasms in a recent year. [1] The study in Thai population (2003-2005) showed that the death rate from the above two diseases is in the top three of fatal diseases. Moreover, there are about 20 million people who are heart disease and coronary artery subclinical people. There were 77 323 subclinical people with coronary artery disease and 32 903 died. [2] Numerous circulating biomarkers representing a variety of pathophysiological pathways including inflammation [C-reactive protein, interleukin-6 and lipoprotein-associated phospholipase A2, lipid metabolism [lipoprotein(a)], and endothelial dysfunction (urinary microalbuminuria) have been shown to promote atherogenesis. In more recent years, some of these biomarkers have had additional evidence to signify utility for CVD risk assessment. [3]

Lipoprotein (a) or Lp(a) is an low-density lipoprotein like particle discovered by Berg in 1963 and is an important independent risk factor for coronary artery diseases. It is indeterminate pathophysiological mechanism, as well as the considerable variations found in its blood levels in different racial/ethnic groups, and have consistently intrigued researchers. Though still not completely elucidated, Lp(a) may constitute a link between the processes of atherosclerosis and thrombosis. Also, new facts about the interactions between Lp(a) and other established risk factors like low-density lipoprotein, high-density lipoprotein, and homocysteine have emerged in recent studies. [4],[5] Although unclear, the mechanism through which Lp(a) may be proatherogenic is based on the proinflammatory effects of the apo(a), as well as Lp(a)’s preferential binding to proinflammatory and proarthrogenic oxidized phospholipids which help to destabilize atherosclerotic lesions. [6] A variety of assays are available for the measurement of Lp(a). They include immunoturbidity, nephelometry, enzyme-linked immunosorbent assays, and fluorescence assays. The standardization of the analytical method for Lp(a) is highly complicated as the majority of the methods determining its serum concentration are affected by the heterogeneity in apo(a) size. Also, in most of the clinical studies, Lp(a) has been estimated by methods affected by apo(a) size heterogeneity. Lp(a) is usually reported as mg/dL representing the entire Lp(a) mass (protein, lipid, and carbohydrate). However, these assays must be validated with reference standards because despite using polyclonal antibodies independent of isoform size, apo(a) size dependent bias has been observed with assay calibrators. Hence, manufacturers of Lp(a) testing should focus on producing assays which are minimally impacted by apo(a) size variability, assay imprecision as well as the variable effects of the antibodies used. Also, data should be compared from different populations to exclude ethnic and race related differences. [7]

Prior studies have shown modest reclassification of subjects for CVD and increase in c-index for intermediate/high-risk FRS categories when Lp(a) was added to predictors of total cholesterol and high-density lipoprotein-cholesterol (HDL-C). [8] A study by Albers et al[9] showed that elevated Lp(a) levels were a significant risk factor in patients with myocardial infarction, especially in the younger age group. [9] In another study involving Swedish male patients who were monitored for 6 years, the Lp(a) levels in the fatal or nonfatal CAD group were higher than the control group. [10]

The average life expectancy of people in western cultures has increased significantly over the last 50 years with the average age of death for a person reaching the age of 65 now being 85 years for men and 87 years for women. Importantly, CVD accounts for >75% of deaths in the elderly. Effective lipid management in the elderly should reduce the risk of developing CVD with improvement of quality of life and potentially a further increase in longevity. Epidemiological studies have consistently shown that CVD risk increases with age in both sexes, and that increasing age is one of the most powerful factors predicting CVD risk. CVD in older patients is also associated with worse outcomes. With increasing age, the burden of CVD risk factors (other than cigarette smoking, total cholesterol, and body mass index [BMI] increases progressively. [11] Hence, Lp(a) may useful for lipid management in elderly to reduce the risk of developing CVD with improvement of quality of life and potentially a further increase in longevity.

Few studies in Thai elderly about Lp(a) level may or may not relate to routine biochemical parameters, such as lipid profiles and fasting blood glucose (FBG). When determination of Lp(a) to screening risk of CAD with other biochemical substances such as, lipid profile and FBG, which may useful by improving sensitivity especially for subclinical group, such as, dyslipedemia, prehypertension and prediabetics. The researchers were aimed to to study on the relation of Lp(a) level and routine biochemical parameters including lipid profiles and FBG in elderly and to determine risk of subclinical symptoms by using Lp(a) levels as early risk predictor.

Materials and Methods

Anthropometric data and CAD risk factors (such as blood pressure, cigarette smoking, and BMI) were recorded, and blood samples were collected from elderly farmers (N = 60) who came for academic health service from Saun Sunandha Rajabhat University at Amphawa district, Samut Songkhram province from January to March 2015. Blood pressure values between 120 > to < 139 mmHg of systolic blood pressure and between >80 and < 89 mmHg of diastolic blood pressure were defined as prehypertension according to the prehypertension; Joint National Commission 7 criteria. [12] Each blood pressure measurement was done at resting blood pressure (after 5 minute resting two times). For the prediabetes, the measurement will be done during fasting to get 110 mg/dL < fasting blood glucose, FBG < 126 mg/dL and/ or the level of HbA1C between 5.7% and 6.4%. This can be used to indicate prediabetes according to American Diabetes Association diagnostic criteria. [13] Samples were divided to risk group [Lp (a) ≥ 30 mg/dL] and normal group [Lp (a) < 30 mg/dL]. The research program had to pass the approval of Board of Human Research Ethics Committees from Saun Sunandha Rajabhat University and all subjects gave written consent. Biochemical parameters including lipid profile and FBG were interpreted by reference values according by Clinical and Laboratory Standards Institute.

Preparation laboratory assay and specimen

Each collected blood sample was prepared to serum for determine lipid profiles [triglyceride, cholesterol, HDL-C and low-density lipoprotein cholesterol (LDL-C] and Lp(a) 2) NaF plasma for determine fasting blood glucose. All biochemical parameters were analyzed by automatic analyzer, COBAS Integra® 400 plus (Roche-diagnostics, Rotkreuz, Switzerland). The repeatability of the analysis was assessed based on triplicate analysis of three blood samples. In each case, the coefficient of variation calculated was 10% or less. All analyses were performed in certified clinical laboratories.

Data analysis

The CAD risk and biochemical parameters were presented in mean ± standard deviation. Statistical analysis was performed using the SPSS computer program version 11.0 (SPSS Inc., Chicago, IL, USA). The calculation of odds ratio (OR) and relative risk (RR) of Lp (a) for hypercholesteremia, prediabetes, and prehypertension was calculated by MedCalc (Medcalc software bvba, Belgium).The analysis of differences was judged by using p < 0.05 at 95% confidence interval as the statistical significance.

Results

Only the average of prehypertension was out of reference range, while average of other parameters, included BMI, lipid profile (cholesterol, triglyceride, HDL-C and LDL-C), FBG and Lp(a) were still in normal range [Table 1]. The anthropometric and biochemical data of elderly were almost normal; therefore, some of them were dyslipidemia (n =14), slightly high blood pressure (n = 8) and slightly high blood glucose (n = 11). When using Lp(a) level (≥ 30 mg/dL as out of normal range) for calculated OR and RR for risk prediction of dyslipedemia, prehypertension, and prediabetes [Table 2], [Table 3] and [Table 4], it was found that Lp(a) can be used to indicate the risk of dyslipedemia (OR = 8.80 and RR = 3.60) and prehypertension (OR = 15.67 and RR = 6.50) at statistically significance (p < 0.05); however, Lp(a) level cannot predict risk of prediabetes due to statistical insignificance [Table 2], [Table 3] and [Table 4]. It may implied that Lp(a) can use for screening of dyslipidemia and hypertension and when determine Lp(a) level with lipid profile and blood pressure, the interpretation of clinical laboratories results was corresponded.

Table 1: The anthropometric and biochemical parameters in elderly (n = 60) from Amphawa district, Samut Songkhram province, Thailand

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Table 2: Lp(a) level to indicate risk prediction for dyslipidemia*, **

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Table 3: Lp(a) level to indicate risk prediction for prehypertension*, **

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Table 4: Lp(a) level to indicate risk prediction for prediabetes

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Discussion

Lp(a) is an LDL like particle composed of a lipid core and two disulphide linked subunits: apolipoprotein B 100 and apolipoprotein, apo (a). The lipid core and apo B 100 are similar to that in LDL. The essential difference between the structure of Lp(a) and LDL is the presence of the glycoprotein apo(a), which is structurally similar to plasminogen, a precursor of plasmin, the fibrinolytic enzyme. This allows Lp(a) to bind to fibrin and to the membrane proteins of endothelial cells and monocytes. Since Lp(a) resembles both LDL and plasminogen, it could possibly act as a link between atherosclerosis and thrombosis. [14]

Lp(a) levels provide additional information on cardiovascular risk and is today an important component of the lipid profile test. An independent and continuous association between Lp(a) and risk of CAD has been firmly established by a number of studies. Lp(a) is highly stable in individuals across many years and is only weakly correlated with known risk factors. Though the exact mechanism of action is still not clear, it is now suggested that due to the presence of both LDL and plasminogen like moiety, Lp(a) may form a link between atherosclerosis and thrombosis. [7]

The number of people for whom lipid management is potentially indicated therefore increases with aging. This is especially the case for secondary prevention and for people aged 65-75 years for whom there is also evidence of benefit from primary prevention. Many people in this age group are not treated with lipid-lowering drugs, however. Even those with CVD may be suboptimally treated, with one study showing treatment rates to fall from ∼60% in those aged < 50 years to < 15% for those aged 85+ years. [11] This study can be conclude that Lp(a) check together with lipid profile and blood pressure can be useful to screening of CAD with more accuracy especially in subclinical group. However, these recent studies were lacking medical histories of elderly volunteers, especially lipid-lowering drug usage. The further study may focus on the relation of Lp(a) and appropriate dose lipid-lowering drug on different age ranges on Thai elderly and Lp(a) can be clearly use for CAD screening as epidemiological study, which might be done on large population.

Acknowledgement

Author is grateful to Suan Sunandha Rajabhat University, Bangkok, Thailand for grant support. I also would like to sincerely thank to all volunteers from Amphawa district, Samut Songkhram province, Thailand for providing useful anthropometric data. I am also grateful to my colleagues from local clinical laboratory (in Bangkok) for providing automatic analyzers, which determined biochemical parameters in this research.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/1755-6783.188494

Tables

[Table 1], [Table 2], [Table 3], [Table 4]

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