Association of lipoprotein (a) with coronary artery disease in a South Asian population: A case-control study.

INTRODUCTION: Coronary artery disease (CAD), the leading cause of mortality worldwide, is characterised by an earlier onset and more severe disease in South Asians as compared to Western populations.
METHODS: This is an observational study on 928 individuals who attended three tertiary care centres in Kerala, India from 2014-to 2017. The demographic, anthropometric, behavioural factors and the lipoprotein (Lp(a)) and cholesterol values were compared between the two groups and across disease severity. The Chi-square test was used to compare the categorical variables and independent sample t-test for the continuous variables. Multivariable logistic regression was performed to investigate the association of demographic, clinical and behavioural factors with the disease. Odds ratios are presented with a 95% confidence interval. In individuals below 50 years, two logistic regression models were compared to investigate the improvement in modelling the association of the independent factors and Lp(a) with the occurrence of the disease.
RESULTS: We included 682 patients in the diseased group and 246 patients treated for non-coronary conditions in the control group. Those in the control group were significantly younger than in the diseased group(p<0.002). Significantly more patients were diabetic, hypertensive, tobacco users and consumers of alcohol in the diseased group. Multivariable logistic regression on data from all age groups showed that age (OR = 2.55, 95% CI 1.51-4.33, p = 0.01), diabetes (OR = 3.71, 95% CI 2.42-5.70, p = 0.01), hypertension (OR = 3.03, 95% CI 2.12-4.34, p = 0.01) and tobacco use (OR = 5.44, 95% CI 3.39-8.75, p = 0.01) are significantly associated with the disease. Lp(a) (OR = 1.22, 95% CI 0.87-1.72) increased the odds of the disease by 22% but was not statistically significant. In individuals below 50 years, Lp(a) significantly increased the likelihood of CAD (OR = 3.52, 95% CI 1.63-7.57, p = 0.01). Those with diabetes were seven times more likely to be diseased (OR = 7.06, 95% CI 2.59-19.21, p = 0.01) and the tobacco users had six times the likelihood of disease occurrence (OR = 6.38, 95% CI 2.62-15.54, p = 0.01). The median Lp(a) values showed a statistically significant increasing trend with the extent/severity of the disease in those below 50 years.
CONCLUSION: Age, diabetes, hypertension and tobacco use appear to be associated more with the occurrence of coronary artery disease in adults of all ages. Lipoprotein(a), cholesterol and BMI categories do not seem to be related to disease status in all ages. However, in individuals below 50 years, diabetes, tobacco use and lipoprotein (a) are significantly associated with the occurrence of the disease.

Background

Hyperlipidaemia is one of the major risk factors for ASCVD (atherosclerotic CVD), with elevated levels of low-density lipoprotein cholesterol (LDL-C) being a major contributor to subsequent CVD events [1, 2]. Despite numerous clinical trials have shown that reducing LDL-C levels, substantially reduces the risk of CVD suggesting a strong causality, individuals continue to have residual CVD risk and suffer from CVD events despite significant LDL-C lowering in addition to the fact that many individuals have ASCVD despite normal lipid values [3]. There are very likely other factors influencing atherosclerosis of which lipoprotein (a)- [Lp(a)], is a likely candidate, especially in the young coronary artery disease (CAD) subset of patients defined as males below 55 years and females below 65 years of age with CAD [4-6].

Previous studies have published a robust association between Lp(a) and CVD outcomes in the general population. A wealth of current evidence suggests that an increased Lp(a) level is associated with a modest increase in the risk of future CVD events in both general and high-risk populations. Such an association of Lp(a) with CVD, is independent of LDL, reduced high-density lipoproteins (HDL), and other traditional CVD risk factors [7, 8].

Lp(a) is uninfluenced by age, sex, diet, or environmental factors, with stable lifelong levels being attained by age of two [9-11]. Lp(a) levels have shown worldwide ethnic variation with different levels associated with CAD in different populations [12]. Over the last 50 years from when it was first discovered by Norwegian physician Kaare Berg, Lp(a) has evolved from an antigenic determinant in blood type to the strongest genetically determined risk factor for coronary artery disease [12].

The Emerging Risk Factor Collaboration reported a positive association between high Lp(a) levels and cardiovascular, but not all-cause, mortality in a meta-analysis of 24 long-term, prospective studies [13, 14]. Further 2 Danish prospective population studies (Copenhagen City Heart Study and Copenhagen General Population Study) also suggested a possible association between high levels of Lp(a) and all-cause and cardiovascular mortality in the general population. The Danish studies reported that, compared with participants in the bottom 50th percentile of the Lp(a) level distribution (all-cause mortality event rate of 14.2% and cardiovascular mortality event rate of 3.6%), participants with Lp(a) levels above the 95th percentile had a hazard ratio (HR) for all-cause mortality of 1.20 (95% CI, 1.10–1.30; event rate, 16.5%) and an HR for cardiovascular mortality of 1.50 (95% CI, 1.28–1.76; eventrate5.0%) [15, 16].

The Mendelian Randomisation analysis revealed that Lp(a) levels were associated with an increased long-term risk of all-cause and cardiovascular mortality in 18720 participants of the EPIC-Norfolk prospective population study followed up for a mean of 20 years, in which the mortality risk for those with Lp(a) levels equal to or above the 95th percentile was equivalent to being 1.5 years older in chronologic age [17].

Malignant coronary artery disease (CAD) refers to a severe and extensive atherosclerotic process involving multiple coronary arteries in young individuals (aged <45 years in men and <50 years in women) with a low or no burden of established risk factors. South Asians, in general, develop acute myocardial infarction (AMI) about 10 years earlier and have rates that are three to fivefold higher than in other populations. Although established CAD risk factors have a predictive value, they do not fully account for the excessive burden of CAD in young South Asians. Lp(a) is increasingly recognized as the strongest known genetic risk factor for premature CAD, with high levels observed in South Asians with malignant CAD [18].

The purpose of this analysis was to examine the association of demographic, behavioural and clinical factors including Lp(a) with disease occurrence. The findings from this retrospective analysis would help generate public health evidence for early prediction and risk stratification of CAD, especially in younger adults.

Methods

Setting and case definition

Cases included consecutive patients admitted with an Acute Coronary Syndrome (ACS) at the Departments of Cardiology, MAGJ and Lisie hospitals, between 2014–2017. The diagnosis of ACS included an acute ST-Elevation Myocardial Infarction (STEMI), Non-ST Elevation Myocardial Infarction (NSTEMI) and Unstable Angina (UA) as per the Fourth Universal definition of myocardial infarction. Cases also included patients with documented reversible ischaemia on exercise testing, angiographically proven coronary artery disease or a history of re-vascularisation procedures- bypass graft or percutaneous coronary intervention. Obstructive CAD as per the angiogram was defined as a more than 50% obstruction of any one or more of the epicardial coronary arteries. The controls were patients admitted and treated for non-coronary conditions including supraventricular tachycardia (SVT), atrial fibrillation, atypical chest pain with a normal coronary angiogram or who presented as an outpatient for comprehensive health check-ups, with normal results for ischaemia but with one or more identified major risk factors for CAD from diabetes mellitus, hypertension, dyslipidaemia, tobacco use or a family history of CAD. The biochemical analysis included fasting plasma glucose (FBS) and lipid profile. Lp(a) was assessed using the immuno-turbidimetric method using the same test kit (Randox) at both hospitals, FBS by the glucose oxidase method and lipid profile by the CHOD-PAP method. The range of normal for Lp(a) is between 5–30 mg/dl. All tests were done on a HITACH 902 autoanalyzer.

Data collection

Details of individuals evaluated either as an inpatient or an outpatient were entered on an Excel datasheet which included anthropometric, laboratory parameters, medical conditions, socio-demographic and behavioural factors. Parameters entered included age, sex, body mass index (BMI), waist-hip ratio, disease status vis a vis acute coronary syndrome (ACS), history of diabetes, dyslipidaemia or hypertension, family history of CAD, socio-behavioural habits including tobacco and alcohol use, exercise stress test report, LV function by echocardiography, coronary angiogram report and revascularization procedure, either percutaneous intervention or coronary bypass graft. Current alcohol user was defined as having had one or more alcoholic drinks over the past 1 year and abstinence as having had no alcoholic drinks over the past 1 year. An Lp(a) value of ≤50mg/dl was considered as normal while values above 50mg/dl were taken as high/elevated.

Statistical analysis

Bivariate analysis was performed to examine the independent association of the disease with age, sex, diabetes, hypertension, standard BMI categories as defined by the WHO (Underweight (<18.5 Kg/m2); Normal (18.5–24.9 Kg/m2); Overweight and Obese (>= 25 Kg/m2), elevated lipoprotein (>50mg/dl), Dyslipidaemia (LDL>= 130 or HDL<35 or TGL>= 200) tobacco and alcohol use. Continuous variables were presented as mean with standard deviation (SD) and categorical variables were presented as frequencies and percentages. A Chi-square test was used to compare the categorical variables and an independent sample t-test was used to compare the continuous variables. For comparison of median, the Moods median test was used. Multivariable logistic regression analysis was done to investigate the association of demographic, clinical and behavioural factors on the occurrence of disease. All independent factors including Lp(a) that were statistically significant with a p-value of <0.15 in the bivariate analysis were included in the multivariable analysis. Odds ratio with 95% Confidence interval (95% CI) were reported. Two logistic regression models were developed; Model 1 without Lp(a) and Model 2 with Lp(a) to investigate the improvement in the model. A statistically significant (p<0.05) deviance (D = -2logLModel1+2logLModel2) indicated that the model with more independent variables was a better model to study the association of the factors with the occurrence of the disease. The analysis was performed using SPSS version 20.0.

Ethics statement

The study was exempted from a review by the IEC, MAGJ hospital since it was a retrospective data analysis using de-identified data from the medical records.

Results

Data from 928 individuals was included in this study of which 682 had CAD (diseased/cases) and 246 did not have CAD (non-diseased/controls). Of these 169 patients 18.2% had undergone coronary angioplasty of which majority 71.6% were above 50 years of age. The comparison of clinical and demographic characteristics between the cases and controls is shown in Table 1. 67.9% of the cases were above the age of 50 years as compared to 84.3% in the controls. Males were proportionately more in the cases as compared to the controls (75.4% vs 64.5%, p = 0.001). The cases had significantly higher proportion of hypertensives (64.1% vs 32.9, p<0.001), more underweight and normal BMI categories (p = 0.01), more tobacco users (48.7% vs 15.9% p = 0.001) and more alcohol users (29.0% vs 13.4% p<0.001) as compared to the controls. Of those who reported using tobacco (n = 371), 95% (n = 353) were smokers. The mean LDL cholesterol, waist-hip ratio, dyslipidaemia and Lp(a) levels were not significant between the two groups.

Table 1

Comparison of the demographic, clinical and behavioural characteristics between the cases and the controls.

Characteristics	All individualsN = 928			Individuals below 50 yearsN = 186
	ControlsN = 246	CasesN = 682	p-value	ControlsN = 79	CasesN = 107	p-value
Age group
<= 50 years	79(32.1)	107(15.7)	0.0001	-	-	-
>50 years	167(67.9)	575(84.3)
Sex
Female	87 (35.4)	168 (24.6)	0.0015	15 (19.0)	7 (6.5)	0.009
Male	159 (64.6)	514 (75.4)		64 (81.0)	100 (93.5)
Diabetes	33 (13.4)	273 (40.0)	0.001	7 (8.9)	38 (35.5)	0.001
Hypertension	81 (32.9)	437 (64.1)	0.001	21 (26.6)	45 (42.1)	0.03
BMI categories
Underweight	16 (11.9)	102 (16.7)		4 (7.1)	13 (12.5)
Normal	80 (59.3)	399 (65.4)	0.01	32(58.2)	66 (63.5)	0.39
Overweight and Obese	39 (28.9)	109 (17.9)		19 (34.5)	25 (24.0)
Waist-Hip ratio (Mean ± SD)	0.92±0.09	0.94±0.06	0.09	0.91±0.14	0.93±0.07	0.30
Elevated Lp(a)	71 (28.9)	218 (32.0)	0.37	15 (19.0)	42(39.3)	0.03
LDL Cholesterol (Mean ±S D)	142.3±50.6	139.6±44.9	0.44	138.5±46.5	129.6±39.5	0.17
Dyslipidaemia	68 (28.1)	217 (32.4)	0.21	56 (72.7)	76 (71.0)	0.80
Tobacco use	39 (15.9)	332 (48.7)	0.001	16 (20.3)	64 (59.8)	<0.001
Alcohol consumption	33 (13.4)	198 (29.0)	0.001	12 (15.2)	45 (42.1)	<0.001

Figures in parenthesis indicate percentages.

Next, we compared the demographic, clinical and behavioural factors between cases and controls in individuals below 50 years. In cases, 39.3% had higher levels of Lp(a) as compared to 19% in controls and this was statistically significant (p = 0.03) In this age group, sex, presence of diabetes, hypertension, tobacco use in any form and alcohol consumption were significantly different between the cases and controls (Table 1).

We performed a multivariable logistic regression to examine the relationship between independent variables and the disease status (Table 2). Compared to individuals below 45 years, those in the higher age group were more likely to be diseased. Presence of diabetes (OR = 3.71, 95% CI 2.42–5.70, p<0.01), hypertension (OR = 3.03, 95% CI 2.12–4.34, p<0.01) and tobacco use (OR = 5.44, 95% CI 3.39–8.75, p<0.01) increased the odds of disease. Higher Lp(a) levels increased the odds of the disease by 22% (OR = 1.22, 95% CI 0.87–1.72) but this was not statistically significant. Sex and alcohol use did not increase the likelihood of the disease.

Table 2

Multivariable logistic regression to study the association of demographic, clinical and behavioural factors.

Characteristics	All ages	Below 50 years
		Model 1	Model 2
Age group
46–60 years	2.55(1.51–4.33)**
>60 years	2.54(1.51–4.29)**
Males	1.33(0.89–2.0)	1.44(0.49–4.25)	1.65(0.53–5.07)
Diabetes	3.71 (2.42–5.70)**	6.02(2.33–15.58) **	7.06(2.59–19.21) **
Hypertension	3.03(2.12–4.34)**	1.55(0.73–3.28)	1.75(0.80–3.84)
Elevated LPa	1.22(0.87–1.72)		3.52(1.63–7.57) **
Tobacco use	5.44(3.39–8.75)**	5.1(2.22–11.73) **	6.38(2.62–15.54) **
Alcohol consumption	0.96(0.57–1.61)	1.24(0.49–3.15)	1.04(0.39–2.76)

**p<0.01.

For the data from individuals below 50 years, two multivariable logistic regression models were developed; Model 1 regressed all independent factors excluding Lp(a)) with the disease and Model 2 included Lp (a) with other independent factors (Table 2).

Model 1 showed that the presence of diabetes increased the odds of occurrence of the disease by six times (OR = 6.02, 95% CI 2.33–15.58, p<0.01) and tobacco use increased the likelihood of disease by 5 times (OR = 5.1, 95% CI 2.22–11.73, p<0.01). Being a male, presence of hypertension or consumption of alcohol did not increase the odds of the disease significantly.

Model 2 that included LP(a) showed that diabetes increased the odds of disease by more than seven times (OR = 7.06, 95% CI 2.59–19.21, p<0.01) while the use of tobacco increased the odds of disease by more than six times (OR = 6.38, 95% CI 2.62–15.54, p<0.01) and Lp(a) increased the odds of disease by more than 3 times (OR = 3.52, 95% CI 1.63–7.57, p<0.01). The deviance between Model 1 and Model 2 was 9.82 which was statistically significant at p<0.05 when compared with χ2 with 1 d.f. Thus, Model 2 with Lp(a) is a better logistic regression model for studying the association of the various factors and the disease.

To examine whether Lp(a) varied across the extent of the disease in those below 50 years, we found that the median Lp(a) values increased with severity of the disease and this was statistically significantly (Moods median test, p-value<0.03) (Table 3).

Table 3

Comparison of median Lp(a) with the severity of the disease in individuals below 50 years.

Coronary Artery Status	Number of individuals (n = 48)	Median Lp(a) (IQR)
Normal	5	37.0(12.5–68.0)
Single vessel disease	23	43.0(28–68.7)
Double vessel disease	11	63.7(22–112.0)
Triple vessel disease	9	61(45.8–99.0)

Discussion

This study was conducted on patients with and without coronary artery disease in three tertiary care centres of Kerala in India. Although we studied the association of known factors with the disease viz. Diabetes, hypertension, tobacco and alcohol use, the primary aim was to investigate the effect of raised Lp(a) on the occurrence of the disease. In particular, we investigated the association of Lp(a) as an independent factor in individuals below 50 years. The findings suggest that elevated Lp(a) increased the odds of occurrence of the disease by more than three times in this age group. Sex, BMI, Waist hip ratio and dyslipidemia do not seem to be associated with the disease.

Zampoulakis et al. (2000) studied the relationship of Lp(a) with the extent and severity of atherosclerosis in CAD patients and found that high Lp(a) was associated with more diffuse lesions covering a larger part of the coronary vasculature [19]. Lp(a) levels were also observed to be correlated with the length of coronary lesions as well as the number of diseased vessels especially those with total occlusions [20-23].

A study on 151 patients in South India showed that Lp(a) >25 mg/dl increases the risk of CAD by about two-fold [24]. In another study on 71 subjects in North India, Lp(a) concentration of 20–30 mg/dl failed to show a statistically significant association with CAD [7]. Mohan et al. reported a strong association between Lp(a) levels and Intima-Media Thickness (IMT) of the carotid arteries in Type 2 diabetic patients [25]. Angeline et al., tested the Lp(a) levels in 65 patients of myocardial infarction below 45 years old, which when compared to age-matched controls was seen to be significantly higher [26]. Yusuf et al., compared the estimated Lp(a) by immunoturbidimetry in 150 patients each of single-vessel disease (SVD), double vessel disease (DVD) and triple vessel disease (TVD) with a control of 150 healthy volunteers [5]. They found the median Lp(a) levels were significantly raised in cases as compared to controls (median 30.3 vs. 20 mg/dl, p <0.001). Ashfaq et al. [27] reported higher Lp(a) values in 270 patients of CAD as compared to 90 controls without CAD. Lipoprotein (a) 21.0 mg/dL was associated with the presence of coronary lesions (P = 0.0001). Statistically significant differences were seen between patients with normal coronaries as compared with those with SVD, DVD or TVD in this study.

There have been several studies on Lp(a) from various sites in India most of which point towards a positive correlation with atherosclerotic CAD with our series being the largest in India till date comparing the diseased and non-diseased [28, 29]. The baseline values of Lp(a) in our study are higher than most other studies [5, 7, 14, 21]. Importantly, Lp(a) was significantly higher in cases when compared to controls in the age group ≤50 years as also there was a correlation between severity and extent of disease with median Lp(a) values in this age group. In addition, individuals who needed revascularisation, through bypass grafting or percutaneous interventions had higher values than controls. By comparison, in a study by Gupta et al. the mean values of Lp(a) were not different between young myocardial infarctions (MI)< age 35, (Mean Lp(a)37.26 ± 4.06) and old MI (age 36–80) (Mean Lp(a)36.67 ± 4.00) [30]. In another study by Govindaraju et al. in patients of CAD, there were no significant difference in mean Lp(a) values between cases and controls [31]. Lp(a) was studied in 40 patients of myocardial infarction less than age 45 and compared with age-matched controls by Wadhwa et al., who showed that mean Lp(a) in cases (MI < 45 years) was significantly higher as compared with age-matched controls (38.74 +/- 26.15 mg/dl vs 20.54 +/- 16.27 mg/dl) [32]. A similar conclusion was drawn by Bansal et al. [33] from a study in young patients of CAD and the same was corroborated in another study by Ramesh et al. in which Lp(a) was 33.84 ± 23.69 mg/dl in cases (MI age <45 years) and 19.68 ± 10.39 mg/dl in controls [34].

The ESC Guidelines [35] does not recommend plasma Lp(a) for routine risk screening in the general population; however, Lp(a) measurement should be considered in people with high CVD risk or a strong family history of premature atherothrombotic disease. Lp(a) measurement should be considered at least once in each adult person’s lifetime to help identify those with very high inherited Lp(a) levels >180 mg/dL (>430 nmol/L) who may have a lifetime risk of ASCVD equivalent to the risk associated with heterozygous familial hypercholesterolaemia [36]. Lp(a) should be considered in selected patients with a family history of premature CVD and for reclassification in people who are borderline between moderate and high-risk [19, 37].

In the light of the current study, we believe Lp(a) to be strongly associated with coronary artery disease in Asian-Indians especially in individuals below fifty years with the disease. Given that Lp(a) values are stable from the first decade of life and considering that Lp(a) values are genetically determined, Lp(a) is found to be strong indicator of premature CAD.

Limitations of the study

Since the study was carried out at two tertiary care centres in Kerala the results cannot be generalised to the country. The number of diseased was more than 2.5 times the number of non-diseased which does not make for an ideal comparison. The study was carried out in the setting of a hospital in individuals with disease or at risk for disease, the findings of which cannot be generalised to the population. The study is a secondary data analysis that carries all the drawbacks of the same in that the comparator groups are not balanced for common prognostic factors.

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27 Oct 2021

Lipoprotein(a) as a risk factor for cardiovascular disease in a South Indian population: A case control study

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Reviewer #1: PONE-D-21-20756

General comments:

1. This is a good study question and I would encourage the authors to make the presentation better.

2. I believe that South Asians is better than Asian Indians. Most of the global studies use data from South Asia and not India alone.

3. The basic limitation in the study is use of mean levels of lipoprotein(a). Lp(a) typically has a skewed distribution and I would recommend that the authors use median values with 25-75 interquartile intervals (IQR) or data presentation. Similarly intergroup comparisons should be performed with non-parametric statistics (Kruskall-Wallis or other tests). An expert opinion from a statistician should be obtained. In the current form the data are not understandable, SD’s are more than the mean values. I am skeptical for use of other parametric tests in the statistics.

4. The article is too lengthy. Especially the introduction and discussion sections.

Specific comments:

Abstract:

5. The Background statement is lengthy. Please make it a one liner.

6. Please describe the method of identifying controls here.

7. All the results could change after the change in statistical methodology highlighted in point no. 3 above.

Introduction:

8. Please describe the evolution of Lp(a) as a risk factor especially focusing on Emerging Risk Factors Collaboration, Danish studies and Mendelian Randomization studies. To be identified it is essential that the factor follows all the Bradford-Hill criteria.

9. Remove the redundant and duplicate statements from this section. Paragraphs 1, 3, 4, 5, 6, and 7 could be deleted/shortened. Previous studies should be could be referenced and details could be discussed in Discussion. No need to provide details of Lp(a) structure.

10. I agree that this is a large study. However, this is not the largest study, INTERHEART study Lp(a) data have been published with more cases/controls than the present one.

11. The literature review is incomplete.

12. Objectives are not defined at all.

Methods:

13. Ethics clearance should be in the first paragraph.

14. Too many abbreviations make for a tough reading. The language needs major improvement so as to improve understanding.

15. I would not include individuals with less than 50% obstructive lesions as controls. These are the persons in whom acute coronary events happen, especially in the young and should be included in CAD group.

16. Most of the guidelines, including latest European and North American, recommend a cut-off of >50 mg/dl and high Lp(a). This cut off should be used. >30mg/dl could be a secondary cut-off.

17. Statistical analyses need major revision. Highlighted in point no. 3 supra. Why adjust for age, when age is the defining characteristics and age-stratified analyses have ben done?

Results:

18. Please describe the characteristics of non-CAD patients.

19. In Table 1, there are too many data. Anyway, this should be revised after exclusion of controls with any evidence of CAD on coronary angio.

20. Dyslipidemia is a wrong word. Please specify the hyperlipidemias as, LDL >=130, non-HDL >=160, and TG >=150. Similarly low HDL should be better defined according to international guidelines. Arbitrary cut-offs are not recommended.

21. Alcohol intake Y/N is also wrong. Please specify the alcohol intake cut-off used in international studies.

22. Age-stratified data on Table 2 should be reduced or combined in Table 1.

23. Presentation of statistical analyses are not understandable at all. The problem with the currently available statistical packages is that they produce too many outputs which are not relevant to the study question. Please take guidance from an expert to create more useful statistics.

24. Figure 1 should be a bar graph and not a line graph.

25. Discussion:

26. The first paragraph should report principal conclusions of the study.

27. Too much space has been taken up by pathophysiology of Lp(a). This must be deleted.

28. Review of Indian studies is incomplete. Also include some studies from other South Asian countries.

29. The current guidelines recommend measurement of Lp(a) in every individual, at least once in lifetime. In Indian context it could be more than once, given the varies of laboratory variations.

30. Limitations should be more specific. This is not a prospective study, sample size is small (although larger than most Indian studies), control population could be better selected as age-matching is uneven (more young patients than controls), etc.

31. Too much repetition.

32. The length of the Discussion section should be less.

Reviewer #2: Manuscript Number: PONE-D-21-20756

Lipoprotein(a) as a risk factor for cardiovascular disease in a South Indian population: A case control study

PLOS ONE

Thank you for the opportunity to review this manuscript. The manuscript identified lipoprotein(a) as a risk factor (predictor?) for CVD, particularly those aged below 50 years. Overall, the manuscript is good in its concept and will be of interest to those involved in CVD prevention and management. However, I have major issues in the novelty of the study, methodological issues and results that need to be addressed critically. Specific comments and questions are provided below.

General

1. The present manuscript reported on a topic that has been studied previously in India as well as other parts of the world. Many studies, both predictive and causal, have already been published on this topic and found somewhat similar results, indicating LP (a) is an independent risk factor of CAD. On paragraph 6 of the background, several studies have been mentioned from India, which showed more or less consistent results. However, with the abundance of such studies, the motivation to conduct this study is not well justified. What makes this study different from the others in terms of study population, methodology, approach, or context other than a bit larger sample? The authors need to explain why their study was necessary, and what it adds to common knowledge.

2. It is essential to clearly state whether this is a ‘prediction’ study that identifies predictors of CAD or ‘causal’ which needs controlling for confounding and adjustment for selection biases. Based on the description from the introduction and method section, the aim of this study looks more of causal, i.e., means to identify the role of LP (a) as a risk for CAD. However, in the analysis and result section, the authors described the ROC curve, which is completely prediction (discriminatory potential) of LP(a) for CAD, means…confounding is not an issue (Grobbee and Hoes 2014). Moreover, in paragraph 4 of the discussion, the authors emphasize LP(a) to be considered to reclassify patients, which is completely prediction in nature. Thus, the authors should explicitly describe whether the aim is prediction or causal and descriptions should be consistent throughout the manuscript. In addition, if the aim is causal, there are several biochemical parameters (lipid profile) that need to be controlled to claim that LP(a) is an independent risk factor of CAD.

Title

3. The title refers to cardiovascular diseases, which includes several categories, which is not limited to coronary artery diseases (CAD). However, the study is specifically for CAD. There are several risk factors which are limited to specific CVD types. If the outcome is CVD, controls are also CVD patients other than CAD. Thus, I would suggest limiting the title specific to CAD, which is the focus of this study.

Background

4. Introduction, paragraph 4: the first two descriptions do not have references.

5. The role of paragraph 7 of the background is not clear or not well placed in the background.

Methods

6. How the number of cases and control (the ratio) was determined? It is an unbalanced case to control ratio.

7. Controls were supraventricular tachycardia (SVT), atrial fibrillation, atypical chest pain with a normal coronary angiogram. First, these cardiac conditions might be related to the main exposure of interest, i.e. LP(a). This may underestimate the association between LP(a) and CAD. The study would have benefited from multiple control groups. Would it have been better to compare the cases with healthy counterparts in addition to these cases?

8. Ethics statement: It is not clear how this study is exempted from ethical review. It is acceptable that consent might not be required as it is a hospital record. However, it doesn’t necessarily mean ethical review is not required.

Analysis

9. In the analysis section, the authors described that Lp(a) is not normally distributed. However, in the result section of the abstract and the main document, LP(a) is described using mean (SD). This is evidenced by table 4 of the result section, which indicates huge variation in mean and median. The authors described that they used log-transformation. Nevertheless, throughout the manuscript, raw values of LP(a) are reported. Thus, the authors should revise the analysis and results accordingly.

10. Receiver operating characteristic curve (ROC) analysis was used to obtain the predictive accuracy of Lp(a) by disease status. What is the importance of ROC…if the study aim is causal.

11. LP(a) is continuous variable and treated as continuous in one occasion and as categorical in another place. It is better to make it consistent based on the prior hypothesis.

12. Table 1 and 2: ‘lipoprotein’, which specific type of lipoprotein?

13. It is puzzling that the main exposure of interest (Lipoprotein) is not included in the multivariable analysis for ‘all ages’.

Results

14. The authors described that “We found that Lp(a) was able to prediction accuracy of Lp(a) was 57% as compared to 62% for diabetes and 70% for tobacco use (Table 5). The ROC curve drawn with these variables in the model gives a predictive probability of about 80%”. This indicates that the predictive capacity of LP(a) is very low…only 7% over just tossing a coin. It would be better to see the added value of LP(a) apart from other predictors including, tobacco, diabetes, BP, BMI, etc.…

Discussion

15. Last paragraph of the discussion section: “Given that Lp(a) values are stable from the first decade of life and considering that Lp(a) values are genetically determined, Lp(a) should be considered for risk stratification in families with premature CAD and or with high Lp(a) levels in the family”. Based on this description, the aim of this study is prognostication in its nature, i.e. to evaluate the prognostic performance of LP(a) in predicting CAD. If so, the AUC is only 57%, which is very low, a bit higher than chance. If the aim is not to see the causal role of LP(a) so as to guide preventive interventions, I would suggest restructuring the whole manuscript as a prognostic research. The theoretical design and approach to statistical analysis is different for causal and prediction research.

Minor issues

• In general, the manuscript doesn’t have page and line numbers, which make the review process difficult to refer to specific descriptions.

• Be consistent in the use of decimal points

References

Grobbee, D. E. and A. W. Hoes (2014). Clinical epidemiology: principles, methods, and applications for clinical research, Jones & Bartlett Publishers.

**********

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Reviewer #1: No

Reviewer #2: Yes: Hamid Yimam Hassen

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Submitted filename: Comment_HYH.docx

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16 Dec 2021

I thought both the reviewers comments were excellent and helped us to give the manuscript a better form.

Reviewer #1: PONE-D-21-20756

General comments:

Comment 1. This is a good study question and I would encourage the authors to make the presentation better.

Response: We thank the reviewer for appreciating the idea. We have incorporated each of the comments made by the reviewer in the revised manuscript.

Comment 2. I believe that South Asians is better than Asian Indians. Most of the global studies use data from South Asia and not India alone.

Response: Asian-Indians has been replaced by South Asians as suggested

Comment 3. The basic limitation in the study is use of mean levels of lipoprotein(a). Lp(a) typically has a skewed distribution and I would recommend that the authors use median values with 25-75 interquartile intervals (IQR) or data presentation. Similarly intergroup comparisons should be performed with non-parametric statistics (Kruskall-Wallis or other tests). An expert opinion from a statistician should be obtained. In the current form the data are not understandable, SD’s are more than the mean values. I am skeptical for use of other parametric tests in the statistics.

Response. We thank the reviewer for the observations. The Lp(a) median values (IQR) has been compared between the disease categories using Mood’ s median test. This has been presented in Table 3 in the revised manuscript.

Comment 4. The article is too lengthy. Especially the introduction and discussion sections.

Response The introduction and the discussion section has been shortened considerably.

Specific comments:

Abstract:

Comment 5. The Background statement is lengthy. Please make it a one liner.

Response: The background statement has been shortened to a single sentence as suggested

Comment 6. Please describe the method of identifying controls here.

Response: As mentioned in the methods section controls were patients admitted and treated for non-coronary conditions including supraventricular tachycardia (SVT), atrial fibrillation, atypical chest pain with a normal coronary angiogram or who presented as an outpatient for comprehensive health check-ups, with normal results for ischaemia but with one or more identified major risk factors for CAD including diabetes mellitus, hypertension, dyslipidaemia, tobacco use or a family history of CAD.

Comment 7. All the results could change after the change in statistical methodology highlighted in point no. 3 above.

Response: The results are incorporated in the revised manuscript using Median and IQR as suggested.

Introduction:

8. Please describe the evolution of Lp(a) as a risk factor especially focusing on Emerging Risk Factors Collaboration, Danish studies and Mendelian Randomization studies. To be identified it is essential that the factor follows all the Bradford-Hill criteria.

Response: The mentioned studies have been incorporated into the Introduction section.

9. Remove the redundant and duplicate statements from this section. Paragraphs 1, 3, 4, 5, 6, and 7 could be deleted/shortened. Previous studies should be could be referenced and details could be discussed in Discussion. No need to provide details of Lp(a) structure.

Response: Changes as suggested have been made and the section on Lp(a) structure has been deleted in its entirety.

10. I agree that this is a large study. However, this is not the largest study, INTERHEART study Lp(a) data have been published with more cases/controls than the present one

Response: The total number of subjects in whom Lp(a) was tested as a part of the INTERHEART study from South Asia (India, Pakistan, Bangladesh and Nepal was 1818, which most likely makes the present study probably larger than the INTERHEART as far as sampling for Lp(a) were concerned.

11. The literature review is incomplete.

Response: The mentioned trials from Denmark, the Risk factor Collaboration and the Mendelian Randomisation have been added.

12. Objectives are not defined at all.

Response: The last paragraph of the Introduction defines the Objectives and has been labelled so in the revised version.

Methods:

13. Ethics clearance should be in the first paragraph.

Response: Ethics clearance has been now included as the first paragraph as suggested.

14. Too many abbreviations make for a tough reading. The language needs major improvement so as to improve understanding.

Response: We have modified the manuscript to make for a better read.

15. I would not include individuals with less than 50% obstructive lesions as controls. These are the persons in whom acute coronary events happen, especially in the young and should be included in CAD group.

Response: Individuals with minor CAD have been included in the patient arm as suggested while those with normal epicardial coronaries were in the control arm.

16. Most of the guidelines, including latest European and North American, recommend a cut-off of >50 mg/dl and high Lp(a). This cut off should be used. >30mg/dl could be a secondary cut-off.

Response: Modification to the manuscript have been made taking a cut-off of > 50 mg/dl to denote high Lp(a) as suggested.

17. Statistical analyses need major revision. Highlighted in point no. 3 supra. Why adjust for age, when age is the defining characteristics and age-stratified analyses have been done?

Results: The reviewers point on statistical analysis has been taken. The binary logistic regression on all ages has age as a predictor variable and has been adjusted for age. However the logistic regression analysis on persons below the age of 50 years is not adjusted for age.

18. Please describe the characteristics of non-CAD patients.

Response: The characteristics of non-CAD patients (non-diseased) is described in table 1.

19. In Table 1, there are too many data. Anyway, this should be revised after exclusion of controls with any evidence of CAD on coronary angio.

Response: Table 1 and 2 have been combined into one table giving the patient characteristics.

20. Dyslipidemia is a wrong word. Please specify the hyperlipidemias as, LDL >=130, non-HDL >=160, and TG >=150. Similarly low HDL should be better defined according to international guidelines. Arbitrary cut-offs are not recommended.

Response: The suggested modifications have been made

21. Alcohol intake Y/N is also wrong. Please specify the alcohol intake cut-off used in international studies.

Response: The intake cut-off used are as per international studies and has been re-written. Current drinking was defined as having had one or more alcoholic drinks over the past 1 year and abstinence as having had no alcoholic drinks over the past 1 year

22. Age-stratified data on Table 2 should be reduced or combined in Table 1.

Response: Table 1 and 2 have now been combined into a single table.

23. Presentation of statistical analyses are not understandable at all. The problem with the currently available statistical packages is that they produce too many outputs which are not relevant to the study question. Please take guidance from an expert to create more useful statistics.

Response: The authors have interpreted the logistic regression analysis in a way that is easily understood by the clinicians. This is the standard way of reporting the results.

24. Figure 1 should be a bar graph and not a line graph.

Response: We have removed the figure in the revised manuscript

25. Discussion:

26. The first paragraph should report principal conclusions of the study.

Response: Principal conclusions of the study have been included in the first paragraph as suggested.

27. Too much space has been taken up by pathophysiology of Lp(a). This must be deleted.

Response: Pathophysiology has been deleted.

28. Review of Indian studies is incomplete. Also include some studies from other South Asian countries.

Response: Not aware of any other Indian studies.

29. The current guidelines recommend measurement of Lp(a) in every individual, at least once in lifetime. In Indian context it could be more than once, given the varies of laboratory variations.

Response: Agree with the reviewer.

30. Limitations should be more specific. This is not a prospective study, sample size is small (although larger than most Indian studies), control population could be better selected as age-matching is uneven (more young patients than controls), etc.

Response: The above mentioned have been incorporated into the revised manuscript.

31. Too much repetition.

Response: Necessary deletions made.

32. The length of the Discussion section should be less.

Response: Discussion has been shortened.

Reviewer #2: Manuscript Number: PONE-D-21-20756

Lipoprotein(a) as a risk factor for cardiovascular disease in a South Indian population: A case control study

PLOS ONE

Thank you for the opportunity to review this manuscript. The manuscript identified lipoprotein(a) as a risk factor (predictor?) for CVD, particularly those aged below 50 years. Overall, the manuscript is good in its concept and will be of interest to those involved in CVD prevention and management. However, I have major issues in the novelty of the study, methodological issues and results that need to be addressed critically. Specific comments and questions are provided below.

General

1. The present manuscript reported on a topic that has been studied previously in India as well as other parts of the world. Many studies, both predictive and causal, have already been published on this topic and found somewhat similar results, indicating LP (a) is an independent risk factor of CAD. On paragraph 6 of the background, several studies have been mentioned from India, which showed more or less consistent results. However, with the abundance of such studies, the motivation to conduct this study is not well justified. What makes this study different from the others in terms of study population, methodology, approach, or context other than a bit larger sample? The authors need to explain why their study was necessary, and what it adds to common knowledge.

Response: Thanks for your review and the clarity you have brought into the review;

Other than for being the largest in India by number, we have compared Lp(a) levels between patients and controls in the ≤50 years age and compared Lp(a) with other risk factors for disease as predictor for CAD in that age group. This because a number of the younger age patients with coronary heart disease (CHD) do not have any of the conventional risk factors for CHD. Our study was an attempt to assess as to how predictive Lp(a) is especially in the age group < 50 years.

2. It is essential to clearly state whether this is a ‘prediction’ study that identifies predictors of CAD or ‘causal’ which needs controlling for confounding and adjustment for selection biases. Based on the description from the introduction and method section, the aim of this study looks more of causal, i.e., means to identify the role of LP (a) as a risk for CAD. However, in the analysis and result section, the authors described the ROC curve, which is completely prediction (discriminatory potential) of LP(a) for CAD, means…confounding is not an issue (Grobbee and Hoes 2014). Moreover, in paragraph 4 of the discussion, the authors emphasize LP(a) to be considered to reclassify patients, which is completely prediction in nature. Thus, the authors should explicitly describe whether the aim is prediction or causal and descriptions should be consistent throughout the manuscript. In addition, if the aim is causal, there are several biochemical parameters (lipid profile) that need to be controlled to claim that LP(a) is an independent risk factor of CAD.

Response: The study is more predictive than causal and in the revised version we have addressed the concerns stated.

Title

3. The title refers to cardiovascular diseases, which includes several categories, which is not limited to coronary artery diseases (CAD). However, the study is specifically for CAD. There are several risk factors which are limited to specific CVD types. If the outcome is CVD, controls are also CVD patients other than CAD. Thus, I would suggest limiting the title specific to CAD, which is the focus of this study.

Response: Thank you, we have changed the title as suggested to coronary artery disease (CAD).

Background

4. Introduction, paragraph 4: the first two descriptions do not have references.

Response: The reference for the section on “malignant CAD” is 18- Enas K Enas et al.

5. The role of paragraph 7 of the background is not clear or not well placed in the background.

Response: Lp(a) is not routinely assessed in patients with an ACS in most parts of India due to multiple reasons one of which being the lack of any treatment for lowering Lp(a). There are a number of molecules currently being tested which have shown benefit in lowering Lp(a) and hence this paragraph was incorporated.

It has been removed and is placed in the Discussion section

Methods

6. How the number of cases and control (the ratio) was determined? It is an unbalanced case to control ratio.

Response: The cases and controls comprised of patients of CAD as defined in the text as cases to controls of patients admitted and treated for non-ischaemic cardiac conditions or in those who for whom it was done as a part of a comprehensive health check-up provided that the individual had one or more of the 5 risk factors for CAD- diabetes, HTN, dyslipidaemia, tobacco use or a family history of CAD.

7. Controls were supraventricular tachycardia (SVT), atrial fibrillation, atypical chest pain with a normal coronary angiogram. First, these cardiac conditions might be related to the main exposure of interest, i.e. LP(a). This may underestimate the association between LP(a) and CAD. The study would have benefited from multiple control groups. Would it have been better to compare the cases with healthy counterparts in addition to these cases?

Response: That is a very good suggestion which we hope we will be able to take up in the future.

8. Ethics statement: It is not clear how this study is exempted from ethical review. It is acceptable that consent might not be required as it is a hospital record. However, it doesn’t necessarily mean ethical review is not required.

Response: The study was exempted from a ethical review process since it was a secondary data analysis.

Analysis

9. In the analysis section, the authors described that Lp(a) is not normally distributed. However, in the result section of the abstract and the main document, LP(a) is described using mean (SD). This is evidenced by table 4 of the result section, which indicates huge variation in mean and median. The authors described that they used log-transformation. Nevertheless, throughout the manuscript, raw values of LP(a) are reported. Thus, the authors should revise the analysis and results accordingly.

Response: Thanks for the suggestion which has been taken and necessary changes made.

10. Receiver operating characteristic curve (ROC) analysis was used to obtain the predictive accuracy of Lp(a) by disease status. What is the importance of ROC…if the study aim is causal.

Response: The study looks at the predictive accuracy of Lp(a). The ROC analysis was done to determine the predictive accuracy of Lp(a) as compared to other established risk factors for CAD.

11. LP(a) is continuous variable and treated as continuous in one occasion and as categorical in another place. It is better to make it consistent based on the prior hypothesis.

Response: It is now primarily treated as a categorical variable.

12. Table 1 and 2: ‘lipoprotein’, which specific type of lipoprotein?

Response: Thanks, has been labelled as Lp(a)

13. It is puzzling that the main exposure of interest (Lipoprotein) is not included in the multivariable analysis for ‘all ages’.

Response: Lp(a) was not included in the multiple logistic regression because it did not show statistical significance between the diseased and non-diseased groups in the univariate analysis, however in < 50 age group it was included in the regression analysis as it was significant in the univariate analysis.

Results

14. The authors described that “We found that Lp(a) was able to prediction accuracy of Lp(a) was 57% as compared to 62% for diabetes and 70% for tobacco use (Table 15). The ROC curve drawn with these variables in the model gives a predictive probability of about 80%”. This indicates that the predictive capacity of LP(a) is very low…only 7% over just tossing a coin. It would be better to see the added value of LP(a) apart from other predictors including, tobacco, diabetes, BP, BMI, etc.…

Response: The authors appreciate the remarks of the reviewer, the ROC analysis with a cut-off of 50mg% as high Lp(a) yields a predictive accuracy of 60% which is statistically significant. This is almost as good as diabetes which has an accuracy of 62%. The logistic regression analysis in ≤50 years shows the added value of Lp(a) with the other known predictors.

Discussion

15. Last paragraph of the discussion section: “Given that Lp(a) values are stable from the first decade of life and considering that Lp(a) values are genetically determined, Lp(a) should be considered for risk stratification in families with premature CAD and or with high Lp(a) levels in the family”. Based on this description, the aim of this study is prognostication in its nature, i.e. to evaluate the prognostic performance of LP(a) in predicting CAD. If so, the AUC is only 57%, which is very low, a bit higher than chance. If the aim is not to see the causal role of LP(a) so as to guide preventive interventions, I would suggest restructuring the whole manuscript as a prognostic research. The theoretical design and approach to statistical analysis is different for causal and prediction research.

Response: Thanks, the manuscript has been restructured towards predictive research as suggested.

Minor issues

• In general, the manuscript doesn’t have page and line numbers, which make the review process difficult to refer to specific descriptions.

• Be consistent in the use of decimal points

Has been rectified

References

Grobbee, D. E. and A. W. Hoes (2014). Clinical epidemiology: principles, methods, and applications for clinical research, Jones & Bartlett Publishers.

________________________________________

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Hamid Yimam Hassen

Submitted filename: Reviewer.docx

Click here for additional data file.

26 Jan 2022

Submitted filename: Table 7.docx

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4 Feb 2022

Reviewer #1: Thanks for submitting a revised version of this article. The manuscript is now much better, but some deficiencies remain.

Response: We thank the reviewer for his encouraging remarks.

Comment 1. The authors have log transformed the Lp(a) values and then performed the quantitative analyses. This is also an appropriate method, although I believe that using non-parametric comparisons such as median test for 2 group and Kruskal-Wallis test for multiple group comparisons are better methods. This should be discussed in the limitation sections of the article.

Response: We have reported the median Lp(a) values and used the median test for comparison in the revised version of the manuscript. (Line 23-26, page 3 and Table 4 page 11)

Comment 2. The interquartile ranges are typically presented as median (25-75 interquartile range, IQR), e.g. 55 (40-70). Nowhere the authors have presented data in this format. Moreover, the authors have reported mean levels of Lp(a) without any measurement of dispersion in the abstract, text and tables. All these should be revised.

Response: We have reported the (25-75 IQR) in table 4 page 11 of the revised manuscript.

Comment 3. The discussion section is still too long and instead of discussing the findings of the article and comparing these with previous Indian and international studies, the authors focus on implications of the findings. Please modify.

Response: The discussion section has been suitably altered comparing between previous studies and the present one. The implications of our study have been removed from the section.

4. Studies on Lp(a) from India are listed below. There are many such studies and should be referenced.

Response: Thank you very much, all the references have been included and cited.

Reviewer #2: Manuscript Number: PONE-D-21-20756R1

Lipoprotein(a) as a risk factor for coronary artery disease in a South Asian population: A case control study

PLOS ONE

Thank you again for the opportunity to review this manuscript. However, I still have major issues that need to be addressed critically. Specific comments and questions are provided below.

Response: We thank the reviewer for his comments. We have responded to each one of his comments in the revised manuscript

Comment 1. The authors claim that it is a prediction study not causal or risk factor analysis. However, the title still reads as “…as a risk factor….”. The theoretical design, the approach to data analysis and interpretation of the study varies significantly for prediction and causal research. The description in the abstract and the whole body of the manuscript still reads as ‘…risk factor.’. In prediction, individual ORs do not have interpretive value. Prediction is not necessarily risk factor identification.

Response: Thanks for the detailed observation. We have studied the association of Lp(a) with CAD in the presence of other known factors. We have changed the title of the manuscript now.

Comment 2. I still suggest authors consider evaluating the added value of LP(a) in predicting CAD along with other predictors such as tobacco, DM, etc.…. Whether statistically significant or not, AUC of 60% has minimal clinical importance. It is better to develop a multivariable prediction model with and without LP(a) and assess the added value.

Response: We thank the reviewer for his valuable suggestions. We have now added another table for logistic regression for individuals below 50 years(Table 3) in the revised manuscript in page 10. Two models Model 1 and Model 2 have been developed. Model 1 has CAD has the dependent variable and gender(female/male), diabetes(yes/no), hypertension(yes/no), tobacco use (yes/no), alcohol use (yes/no) as predictor variables and Model 2 has CAD has the dependent variable and gender(female/male), diabetes(yes/no), hypertension(yes/no), tobacco use (yes/no), alcohol use (yes/no) and Lp(a)(<50 and >=50) as predictors. The deviance between Model 1 and Model 2 was 9.82 which is statistically significant at p<0.05 when compared with �  2 with 1 d.f. Thus, Model 2 with Lp(a) is a better predictor model for the disease as compared to Model 1 without it, indicating that Lp(a) is an independent predictor for the disease in addition to the established risk factors viz. presence of diabetes and tobacco use

Comment 3. Although LP(a) is not normally distributed, using mean with SD is not justified enough.

Response: We have not reported mean Lp(a) anywhere in the revised manuscript now.

Comment 4. Whether significant or not on the univariable analysis, the main predictor of interest (LP (a)) should be included in the multivariable analysis.

Response: We have now revised Table 1 for all individuals after including Lp(a) as a predictor in the multivariable analysis.

Comment 5. I commend the authors for uploading the data used to produce this manuscript. It helps for open science. Looking in to the supporting information (Data), there are lots of missing values. However, there is no description on the missing data. Did the authors check for the missingness pattern? How did they manage it?

Response: We had uploaded a revised data sheet with the variables used for the analysis.

Comment6. In addition, the outcome variable and predictors are not clearly labeled in the data. I suggest authors make it more clear and transparent.

Response: A revised data sheet is being uploaded with clear labels

Comment 7. In spite of the comment in round 1 to add for line numbers, the manuscript still doesn’t have page and line numbers, which make the review process difficult to refer to specific descriptions. As far as I understand, the author guideline requests to put line numbers to ease the review process.

Response: Thanks for the suggestions. We have now inserted the page numbers and the line numbers now in the revised manuscript.

Submitted filename: Response to the reviewers comments2.docx

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8 Mar 2022

16 Mar 2022

Sub: Reply to the editor’s and reviewers’ comments on the paper number PONE-D-21-20756R2

Dear Editor,

We appreciate the comments from the honourable Editor and the Reviewers. We are highly obliged to the journal for providing us the opportunity to revise the manuscript entitled “Association of lipoprotein (a) with coronary artery disease in a South Asian population: A case control study” and retain the opportunity to get our work published with PLOS ONE. We must mention that the comments have been very useful to improve the quality of our paper.

We have modified the manuscript as per the journals requirements. Our response to each and every point raised by the two reviewers is also being uploaded and incorporated in the revised version of the manuscript. We also request you, to notify us if any more corrections are needed.

Thanking you in advance for your sincere efforts and support.

Author’s response to the Editor’s comments

Comment: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labelled 'Response to Reviewers_R3'.

Response: Rebuttal letter uploaded as a separate file

Comment: A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labelled 'Revised Manuscript with Track Changes_R3'.

Response: A marked up copy of the manuscript “PONE-D-21-20756R3_marked up” uploaded

Comment: An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labelled 'Manuscript'

Response: An unmarked version of the manuscript” Manuscript_R3” uploaded

Yours sincerely,

Dr Geetha R Menon

Authors Response to the reviewers comments

Reviewer #1:

1. The Tables are very lengthy and provide unnecessary information.

Response: We appreciate the reviewer’s suggestion. The tables have been reduced after removing unnecessary information

2. I would suggest that in each row, in Tables 1 and 2, the authors only retain the Yes (risk factor, positive findings) row and delete the No row. This would make the Tables less cluttered and easier to comprehend.

Response:. We have reduced the ‘No’ categories for each variable. The information in tables 2 and 3 has now been combined into one table.

Reviewer #2: Manuscript Number: PONE-D-21-20756R2 Association of lipoprotein (a) with coronary artery disease in a South Asian population: A case control study

PLOS ONE

Thank you once more. The authors addressed most of my concerns. However, I still have issues that need to be addressed. Specific comments and questions are provided below.

Response: We are glad that we have been able to address many of the reviewers concern.

1. The authors’ focus shifted from a kind of prediction research to “Association of lipoprotein (a) with coronary artery disease”. Thus, the study approach, statistical analysis and interpretation of results would also change. There are descriptions in the manuscript that seem for prediction type of research. Here are some of the descriptions in the manuscript that confused risk factor identification research to prediction…

•First sentence of the discussion section still reads as “The study results suggest that Lp(a) has a modest predictive accuracy for CAD especially in subjects ≤50 years of age.”

Response: We have now rewritten the first paragraph of the discussion section

•The first sentence of summary (page 13, line 13-14) also phrased as “In summary our study suggests that Lp(a) is an important predictor for CAD especially in the age group < 50 years.”

Response: We have rewritten the first sentence of the summary section

•The conclusion section of the abstract.

Response: Response: We have rewritten the conclusion section of the abstract.

•Abstract line 13

Response: We have rewritten the abstract line 13

•Analysis section, page 7 line 3 to 8. This description of analysis is still on prediction.

Response: The analysis section has been rewritten as an association study

•Result page 10, lines 5 to 9: these descriptions are for prediction type of research.

Response: The results section has been rewritten as an association study

Submitted filename: Authors Response to the reviewers comments_R3.docx

Click here for additional data file.

18 Apr 2022

Association of lipoprotein(a) with coronary artery disease in a South Asian population: A case control study

PONE-D-21-20756R3

Dear Dr. Ravindran ,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Geofrey Musinguzi, MPH, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: No comments.

Thanks for submitting the revised version. All the comments have been incorporated in the manuscript.

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Reviewer #1: No

22 Apr 2022

PONE-D-21-20756R3

Association of lipoprotein (a) with  coronary artery disease in a South Asian population: a case-control study

Dear Dr. Menon:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Geofrey Musinguzi

Academic Editor

PLOS ONE