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Interaction between Cholesterol Crystals and Bacteria: Implications for Atherosclerosis *
346
Journal of Clinical Lipidology, Vol 8, No 3, June 2014
Table 1 Correlation of LpPLA2 with other risk factors in retired NFL players LpPLA2 Variables
r
P value
Age LDL-C HDL-C Triglycerides hs-CRP LDL-P LDL size BMI
0.12 0.14 0.23 -0.23 0.02 -0.16 0.24 -0.19
0.006 ,0.001 ,0.001 ,0.001 0.550 ,0.001 ,0.001 ,0.001
Data expressed as Spearman’s correlation coefficient (r) and associated p value between Lp-PLA2 and covariates. LpPLA2: lipoprotein associated phospholipase A2, NFL: national football league, LDLC: low-density lipoprotein cholesterol, HDL-C: high-density lipoprotein cholesterol, hs-CRP: high sensitivity C-reactive protein, LDL-P: lowdensity lipoprotein particle, non HDL-C: non high-density lipoprotein cholesterol, BMI: body mass index, WC: waist circumference, BP: blood pressure
Table 2 Association between LpPLA2 and presence of subclinical atherosclerosis (CAC or CAP) in retired NFL players Outcome
Model 1 (OR*, 95% CI)
Model 2 (OR*, 95% CI)
CAC CAP
0.89 (0.76-1.04) 0.93 (0.79-1.10)
0.85 (0.71-1.02) 0.90 (0.75-1.08)
Model 1: Adjusted for age, race, systolic blood pressure, fasting blood sugar, body mass index Model 2: Adjusted for model 1 plus high density lipoprotein cholesterol, low density lipoprotein cholesterol, triglycerides, highsensitivity C reactive protein *OR from logistic regression model per standard deviation increase in LpPLA2 (80 ng/mL) LpPLA2: Lipoprotein associated phospholipase A2, CAC: coronary artery calcium, CAP: carotid artery plaque, NFL: national football league, OR: odds ratio, CI: confidence interval
Table 3
LpPLA2 and burden of CAC in retired NFL players
Model 1 (*b Coeff, 95% CI)
Model 2 (*b Coeff, 95% CI)
0.15 (-0.02 to 0.33)
0.13 (-0.06 to 0.33)
Model 1: Adjusted for age, race, systolic blood pressure, fasting blood sugar, body mass index Model 2: Adjusted for model 1 plus high density lipoprotein cholesterol, low density lipoprotein cholesterol, triglycerides, highsensitivity C reactive protein *(b Coeff, 95% CI) is based on linear regression with ln (CAC + 1) as a dependent variable amongst those with CAC.0 per standard deviation increase in LpPLA2 (80 ng/mL) LpPLA2: Lipoprotein associated phospholipase A2, CAC: coronary artery calcium, NFL: national football league, CI: confidence interval
0.71-1.02) or CAP (HR 0.90, 95% CI 0.75-1.08) (Table 2). Similar results were obtained when participants in the highest LpPLA2 tertile were compared to the lowest tertile. LpPLA2 was also not associated with the burden of CAC in
those with CAC.0 (Table 3). Results were similar when analyzed by position played (lineman vs. non-lineman). Conclusion: In this group of retired NFL players, LpPLA2 mass was not associated with coronary or carotid subclinical atherosclerosis. 166 A Novel Total Lipoprotein Electronegativity Index for Predicting Cardiometabolic Risk* Maekal Elyasi, Steven Shayani, MD, (Great Neck, NY)
Lead Author’s Financial Disclosures: None Study Funding: None Background/Synopsis: The most electronegative subfractions of chromatographically resolved low-density lipoprotein (LDL) and very-low-density lipoprotein (VLDL), L5 and V5, are highly atherogenic. High-density lipoprotein (HDL) can similarly be resolved into subfractions; H5 exhibits reduced cholesterol efflux capacity and appears dysfunctional. Objective/Purpose: We examined the clinical implications of lipoprotein electronegativity by analyzing plasma H5, L5, and V5 levels in 33 asymptomatic subjects with cardiometabolic risk factors. Methods: pending Results: H5, L5, and V5 concentrations were 18.410.6, 19.618.9, and 10.57.6 mg/dL, respectively. The Jonckheere’s trend test revealed that the total lipoprotein electronegativity index (H5+L5+V5) increased with the number of metabolic syndrome criteria (P,0.001). When total cholesterol (TC) and age were also included in the analyses, the index was significantly (P,0.05) associated with age (Spearman’s rho, 0.41), waist circumference (0.44), systolic blood pressure (0.40), and levels of fasting glucose (0.49), TC (0.52), and triglyceride (0.49). Stepwise regression analysis revealed that fasting glucose (FG) and TC levels contributed to 40% of index variance; thus, we derived the following formula for predicting plasma total lipoprotein electronegativity: ([0.36 ! FG] + [0.23 ! TC] – 34). Conclusion: The total lipoprotein electronegativity index(H5+L5+V5) increases with the number of metabolic syndrome criteria.FG and TC could be used to predict total plasma lipoprotein electronegativity using a formula. Large-scale clinical trials are warranted to test the reliability of this formula and the clinical importance of the total lipoprotein electronegativity index. 167 Interaction between Cholesterol Crystals and Bacteria: Implications for Atherosclerosis * Manjunath Raju, MD, Apoorv Kalra, MD, Joseph Gardiner, PhD, Abed Janoudi, PhD, George Abela, MD, (East Lansing, MI)
Abstracts
Lead Author’s Financial Disclosures: None Study Funding: None Background/Synopsis: The presence of bacteria in atherosclerotic plaque has been reported but their role in atherosclerosis is unclear. It has already been established by histology that cholesterol crystals are abundantly present in atherosclerotic plaque. Objective/Purpose: We hypothesized that bacteria utilize cholesterol crystals (CC) in plaques as a nutrient. To study this phenomenon, we evaluated the growth characteristics and adherence of Staphylococcus aureus (SA) to CC. Methods: Cholesterol crystals were synthesized by dissolving cholesterol powder in methanol and then evaporating. Also, in order to demonstrate that SA-CC adherence was not related to the shape and hardness of CC, we used ground glass shards and plastic microspheres (250 mm) as controls. All particulates (CC, glass shards, microspheres) were attached to glass coverslips covered with glue which was also tested independently. Coverslips were then incubated with SA in broth for 1, 2, 3 and 4 h and bacterial colony counts obtained at each interval. After incubation, coverslips were examined for bacterial presence by scanning electron microscopy (SEM). Results: CC had the highest bacterial count present compared to those tubes with glass shards, microspheres and glue (Figure). After Box-Cox transformation of bacterial count significant differences were found (p,0.0001) between groups except for the glass and microsphere pair. By quantitative SA culture, there was significantly greater bacterial adhesion with CC for each time interval compared to controls. There was a 45% increase in bacterial growth with CC. SEM demonstrated SA attached to CC and were also found to be dissolving CC. Conclusion: These data suggest that bacteria have higher adherence to CC when compared to other particulates of comparable size and hardness. Thus, the availability of CC as a nutrient could explain the accumulation of bacteria in atherosclerotic plaque.
Figure
347 168 Dyslipidemia and Insulin Resistance in Nondiabetic Subjects with Fatty Liver Disease Kathleen L. Wyne, MD, Yi-Ting S. Shen, Leah C. Folb, MD, Howard P. Monsour, MD, Willa A. Hsueh, MD, (Houston, TX)
Lead Author’s Financial Disclosures: None Study Funding: None Background/Synopsis: The growing epidemic of fatty liver disease parallels the global epidemic of diabetes. Patients with nonalcoholic fatty liver disease (NAFLD) have an increased risk of cardiovascular disease as well as type 2 diabetes (T2DM). Insulin resistance (IR), a precursor to diabetes, has been described in people with fatty liver disease including steatosis with inflammation (nonalcoholic steatohepatitis or NASH). However not all patients with NAFLD have IR thus markers are needed to identify patients for investigation of their glucoregulatory status. The ‘‘diabetic dyslipidemia’’ of high triglycerides and low HDL has been demonstrated to be a marker of IR in the Metabolic Syndrome. If this characteristic ‘‘diabetic dyslipidemia’’ is present in NAFLD it could be used as a marker to identify people who have IR and hyperinsulinemia thereby facilitating early diagnosis of prediabetes in this population leading to an opportunity to prevent the progression to T2DM. Objective/Purpose: Evaluate the components of the lipid profile for correlation to metabolic parameters in NAFLD/NASH patients without diabetes. Methods: Charts were reviewed retrospectively from 154 consecutive patients in the metabolic liver clinic. After excluding those who met criteria for diabetes (whether known or newly diagnosed) and incomplete metabolic data, we assessed correlations with total cholesterol, LDL-C, triglycerides, HDL-C, fasting insulin, IR, as measured by HOMA-IR, pancreatic b-cell function, as measured by HOMA-b and NASH FibroSUREÒ. Spearman correlation coefficient was used to measure the association between metabolic parameters. Results: In this population of nondiabetic fatty liver disease patients there is a negative statistical significant correlation between HDL and fasting insulin level (p 50.0079). This correlation was significant in men but not in women. However, neither HDL nor insulin level correlated to BMI in men. There was no correlation between fasting plasma glucose and lipid parameters. We found a significant negative correlation between HDL and triglycerides in both men and women (p,0.0001). Conclusion: These data show that low HDL identifies a subset of men, but not women, with NAFLD who should undergo further evaluation for IR, hyperinsulinemia and prediabetes with a goal of preventing both cardiovascular disease and T2DM. Triglyceride-to-HDL ratio, but not HDL alone, can be used in women with NAFLD as a marker to identify individuals who should undergo more extensive evaluation for prediabetes and T2DM. Studies are ongoing in this population
Journal of Clinical Lipidology, Vol 8, No 3, June 2014
Table 1 Correlation of LpPLA2 with other risk factors in retired NFL players LpPLA2 Variables
r
P value
Age LDL-C HDL-C Triglycerides hs-CRP LDL-P LDL size BMI
0.12 0.14 0.23 -0.23 0.02 -0.16 0.24 -0.19
0.006 ,0.001 ,0.001 ,0.001 0.550 ,0.001 ,0.001 ,0.001
Data expressed as Spearman’s correlation coefficient (r) and associated p value between Lp-PLA2 and covariates. LpPLA2: lipoprotein associated phospholipase A2, NFL: national football league, LDLC: low-density lipoprotein cholesterol, HDL-C: high-density lipoprotein cholesterol, hs-CRP: high sensitivity C-reactive protein, LDL-P: lowdensity lipoprotein particle, non HDL-C: non high-density lipoprotein cholesterol, BMI: body mass index, WC: waist circumference, BP: blood pressure
Table 2 Association between LpPLA2 and presence of subclinical atherosclerosis (CAC or CAP) in retired NFL players Outcome
Model 1 (OR*, 95% CI)
Model 2 (OR*, 95% CI)
CAC CAP
0.89 (0.76-1.04) 0.93 (0.79-1.10)
0.85 (0.71-1.02) 0.90 (0.75-1.08)
Model 1: Adjusted for age, race, systolic blood pressure, fasting blood sugar, body mass index Model 2: Adjusted for model 1 plus high density lipoprotein cholesterol, low density lipoprotein cholesterol, triglycerides, highsensitivity C reactive protein *OR from logistic regression model per standard deviation increase in LpPLA2 (80 ng/mL) LpPLA2: Lipoprotein associated phospholipase A2, CAC: coronary artery calcium, CAP: carotid artery plaque, NFL: national football league, OR: odds ratio, CI: confidence interval
Table 3
LpPLA2 and burden of CAC in retired NFL players
Model 1 (*b Coeff, 95% CI)
Model 2 (*b Coeff, 95% CI)
0.15 (-0.02 to 0.33)
0.13 (-0.06 to 0.33)
Model 1: Adjusted for age, race, systolic blood pressure, fasting blood sugar, body mass index Model 2: Adjusted for model 1 plus high density lipoprotein cholesterol, low density lipoprotein cholesterol, triglycerides, highsensitivity C reactive protein *(b Coeff, 95% CI) is based on linear regression with ln (CAC + 1) as a dependent variable amongst those with CAC.0 per standard deviation increase in LpPLA2 (80 ng/mL) LpPLA2: Lipoprotein associated phospholipase A2, CAC: coronary artery calcium, NFL: national football league, CI: confidence interval
0.71-1.02) or CAP (HR 0.90, 95% CI 0.75-1.08) (Table 2). Similar results were obtained when participants in the highest LpPLA2 tertile were compared to the lowest tertile. LpPLA2 was also not associated with the burden of CAC in
those with CAC.0 (Table 3). Results were similar when analyzed by position played (lineman vs. non-lineman). Conclusion: In this group of retired NFL players, LpPLA2 mass was not associated with coronary or carotid subclinical atherosclerosis. 166 A Novel Total Lipoprotein Electronegativity Index for Predicting Cardiometabolic Risk* Maekal Elyasi, Steven Shayani, MD, (Great Neck, NY)
Lead Author’s Financial Disclosures: None Study Funding: None Background/Synopsis: The most electronegative subfractions of chromatographically resolved low-density lipoprotein (LDL) and very-low-density lipoprotein (VLDL), L5 and V5, are highly atherogenic. High-density lipoprotein (HDL) can similarly be resolved into subfractions; H5 exhibits reduced cholesterol efflux capacity and appears dysfunctional. Objective/Purpose: We examined the clinical implications of lipoprotein electronegativity by analyzing plasma H5, L5, and V5 levels in 33 asymptomatic subjects with cardiometabolic risk factors. Methods: pending Results: H5, L5, and V5 concentrations were 18.410.6, 19.618.9, and 10.57.6 mg/dL, respectively. The Jonckheere’s trend test revealed that the total lipoprotein electronegativity index (H5+L5+V5) increased with the number of metabolic syndrome criteria (P,0.001). When total cholesterol (TC) and age were also included in the analyses, the index was significantly (P,0.05) associated with age (Spearman’s rho, 0.41), waist circumference (0.44), systolic blood pressure (0.40), and levels of fasting glucose (0.49), TC (0.52), and triglyceride (0.49). Stepwise regression analysis revealed that fasting glucose (FG) and TC levels contributed to 40% of index variance; thus, we derived the following formula for predicting plasma total lipoprotein electronegativity: ([0.36 ! FG] + [0.23 ! TC] – 34). Conclusion: The total lipoprotein electronegativity index(H5+L5+V5) increases with the number of metabolic syndrome criteria.FG and TC could be used to predict total plasma lipoprotein electronegativity using a formula. Large-scale clinical trials are warranted to test the reliability of this formula and the clinical importance of the total lipoprotein electronegativity index. 167 Interaction between Cholesterol Crystals and Bacteria: Implications for Atherosclerosis * Manjunath Raju, MD, Apoorv Kalra, MD, Joseph Gardiner, PhD, Abed Janoudi, PhD, George Abela, MD, (East Lansing, MI)
Abstracts
Lead Author’s Financial Disclosures: None Study Funding: None Background/Synopsis: The presence of bacteria in atherosclerotic plaque has been reported but their role in atherosclerosis is unclear. It has already been established by histology that cholesterol crystals are abundantly present in atherosclerotic plaque. Objective/Purpose: We hypothesized that bacteria utilize cholesterol crystals (CC) in plaques as a nutrient. To study this phenomenon, we evaluated the growth characteristics and adherence of Staphylococcus aureus (SA) to CC. Methods: Cholesterol crystals were synthesized by dissolving cholesterol powder in methanol and then evaporating. Also, in order to demonstrate that SA-CC adherence was not related to the shape and hardness of CC, we used ground glass shards and plastic microspheres (250 mm) as controls. All particulates (CC, glass shards, microspheres) were attached to glass coverslips covered with glue which was also tested independently. Coverslips were then incubated with SA in broth for 1, 2, 3 and 4 h and bacterial colony counts obtained at each interval. After incubation, coverslips were examined for bacterial presence by scanning electron microscopy (SEM). Results: CC had the highest bacterial count present compared to those tubes with glass shards, microspheres and glue (Figure). After Box-Cox transformation of bacterial count significant differences were found (p,0.0001) between groups except for the glass and microsphere pair. By quantitative SA culture, there was significantly greater bacterial adhesion with CC for each time interval compared to controls. There was a 45% increase in bacterial growth with CC. SEM demonstrated SA attached to CC and were also found to be dissolving CC. Conclusion: These data suggest that bacteria have higher adherence to CC when compared to other particulates of comparable size and hardness. Thus, the availability of CC as a nutrient could explain the accumulation of bacteria in atherosclerotic plaque.
Figure
347 168 Dyslipidemia and Insulin Resistance in Nondiabetic Subjects with Fatty Liver Disease Kathleen L. Wyne, MD, Yi-Ting S. Shen, Leah C. Folb, MD, Howard P. Monsour, MD, Willa A. Hsueh, MD, (Houston, TX)
Lead Author’s Financial Disclosures: None Study Funding: None Background/Synopsis: The growing epidemic of fatty liver disease parallels the global epidemic of diabetes. Patients with nonalcoholic fatty liver disease (NAFLD) have an increased risk of cardiovascular disease as well as type 2 diabetes (T2DM). Insulin resistance (IR), a precursor to diabetes, has been described in people with fatty liver disease including steatosis with inflammation (nonalcoholic steatohepatitis or NASH). However not all patients with NAFLD have IR thus markers are needed to identify patients for investigation of their glucoregulatory status. The ‘‘diabetic dyslipidemia’’ of high triglycerides and low HDL has been demonstrated to be a marker of IR in the Metabolic Syndrome. If this characteristic ‘‘diabetic dyslipidemia’’ is present in NAFLD it could be used as a marker to identify people who have IR and hyperinsulinemia thereby facilitating early diagnosis of prediabetes in this population leading to an opportunity to prevent the progression to T2DM. Objective/Purpose: Evaluate the components of the lipid profile for correlation to metabolic parameters in NAFLD/NASH patients without diabetes. Methods: Charts were reviewed retrospectively from 154 consecutive patients in the metabolic liver clinic. After excluding those who met criteria for diabetes (whether known or newly diagnosed) and incomplete metabolic data, we assessed correlations with total cholesterol, LDL-C, triglycerides, HDL-C, fasting insulin, IR, as measured by HOMA-IR, pancreatic b-cell function, as measured by HOMA-b and NASH FibroSUREÒ. Spearman correlation coefficient was used to measure the association between metabolic parameters. Results: In this population of nondiabetic fatty liver disease patients there is a negative statistical significant correlation between HDL and fasting insulin level (p 50.0079). This correlation was significant in men but not in women. However, neither HDL nor insulin level correlated to BMI in men. There was no correlation between fasting plasma glucose and lipid parameters. We found a significant negative correlation between HDL and triglycerides in both men and women (p,0.0001). Conclusion: These data show that low HDL identifies a subset of men, but not women, with NAFLD who should undergo further evaluation for IR, hyperinsulinemia and prediabetes with a goal of preventing both cardiovascular disease and T2DM. Triglyceride-to-HDL ratio, but not HDL alone, can be used in women with NAFLD as a marker to identify individuals who should undergo more extensive evaluation for prediabetes and T2DM. Studies are ongoing in this population