Background

Tuberculosis (TB) remains the leading infectious cause of mortality globally [1]. Moreover, individuals with active TB face a significantly high risk of major adverse cardiovascular events, estimated at 51% greater than those without TB [2]. This translates to increased incidence of ischemic stroke, peripheral artery disease, and myocardial infarction in patients with TB [3,39]. Beyond its traditional role, emerging research links elevated MCV with endothelial dysfunction, increased severity of coronary artery disease, arterial stiffness, and a higher likelihood of major adverse cardiovascular events [40,41,42,43,44,45]. The current study delineates a nuanced relationship between MCV and dyslipidemia, revealing an inverse association with low HDL-c and a positive association with hypertriglyceridemia. Specifically, the study found that an elevated MCV corresponds to higher levels of both HDL-c and triglycerides. Though hypertriglyceridemia is a known culprit in CVD, it’s crucial to remember that high HDL-c, while often deemed protective, can be a double-edged sword. In fact, HDL-c levels exceeding 80 mg/100 ml have been associated with an increased risk of mortality, challenging the conventional understanding of its protective role in CVD [46].

The observation of an association between high MCV and elevated HDL-c levels, mirrors results from the National Health and Nutrition Examination Survey 2005–2006 [47] and studies involving overweight/obese individuals in Iran and non-anemic elderly populations [48, 49]. One plausible explanation is the role of plasma HDL-c as a cholesterol source for red blood cell membranes, leading to changes in red cell membrane cholesterol content and diameter. Such alterations can decrease red cell fluidity, stiffen the lipid shell, increase membrane density, and modify red cell morphology [50]. The potential role of the HDL-c on red cell membrane cholesterol is also supported by the positive association of the RDW, a measure of red cell size variability, and low HDL-c in the bivariate analysis [51]. The RDW has been associated with myocardial infarction, heart failure, stroke, atrial fibrillation, coronary artery disease, peripheral artery disease and hypertension [52]. The observed association between elevated RDW and HDL-c in coronary artery disease patients could be indicative of chronic inflammation and oxidative stress as well [53]. The results from this study collectively suggest that alterations in HDL-c levels can significantly impact red cell membrane characteristics, potentially affecting blood rheology and predisposing individuals to CVD. Although patients with dyslipidemia had significantly elevated platelet counts than those without, further investigation is needed to determine if this, along with red blood cell membrane alterations, contributes to a pro-thrombotic state in this population.

Study strengths and weaknesses

The merits of the study lie in the multi-center nature of the study and the use of readily available markers of inflammation. Despite its valuable insights, the current study has limitations that warrant consideration. Due to its snapshot nature, changes in blood lipids and inflammation markers over time could not be assessed, particularly regarding the influence of TB treatment. This limits the understanding of any dynamic interplay between these factors and their long-term implications. Although some studies suggest HDL-c and total cholesterol remain stable during TB treatment [54], the participants in the current study had been on TB treatment for a median of 6 months. This raises the possibility that baseline lipid and inflammation marker levels may have differed from those at study entry, potentially affecting the observations. Longitudinal studies would be better suited to capture these dynamics over time. Another concern is the generalizability of the results. The research focused exclusively on patients with DR-TB, raising questions about the applicability of the findings to patients with drug-susceptible TB. While the prevalence of traditional CVD risk factors is reportedly similar in both DR-TB and drug-susceptible TB populations [7], it remains unclear whether the interplay between lipids and biomarkers of inflammation would differ according to TB drug resistance status. Genetically diverse strains of Mycobacterium tuberculosis exhibit varied propensity to metabolize host cholesterol but the effect on overall lipid levels of the host is unclear [55]. This aspect warrants further investigation. While the study evaluated readily available markers on a full haemogram known to predict CVD, we did not investigate the interaction of blood lipids with established inflammatory biomarkers such as C-reactive protein, erythrocyte sedimentation rate, interleukin-6, and tumor necrosis factor. These data were not collected from the study population. Future investigations could explore the potential synergistic effects of these inflammatory markers with blood lipids on CVD risk.

Conclusion

In conclusion, the study highlights a significant prevalence of dyslipidemia among patients with DR-TB, primarily characterized by low HDL-c levels and hypertriglyceridemia. Notably, the results showed elevated monocytes, platelets and lymphocytes among patients with dyslipidemia as well as an association between the MCV with elevated HDL-c and hypertriglyceridemia. These findings underscore the intricate interplay between lipid metabolism and hematological changes in patients with TB. Crucially, the associations with MCV suggest that dyslipidemia may influence red blood cell morphology, potentially leading to alterations in blood rheology. This observation, coupled with the noted changes in platelet count, points towards a possible pro-thrombotic state in patients with TB with dyslipidemia. Such hematological alterations could have significant implications for the cardiovascular health of these patients.

Appendix 1

Correlation between cell counts and derived cell ratios

 

Neutrophil count

NLR

Lymphocyte count

PLR

Platelet count

Monocyte count

LMR

Neutrophil count

1.000

      

NLR

0.244

1.000

     

Lymphocyte count

-0.301

-0.483

1.000

    

PLR

0.133

0.895

-0.433

1.000

   

Platelet count

-0.101

-0.046

0.294

0.070

1.000

  

Monocyte count

-0.394

-0.318

0.652

-0.286

0.4168

1.000

 

LMR

0.331

-0.113

0.192

-0.113

-0.213

-0.273

1.000

  1. NLR: Neutrophil-Lymphocyte ratio; PLR: Platelet-Lymphocyte ratio; LMR: Lymphocyte-Monocyte ratio