Validating the NIH LDL-C equation for provincial implementation in Alberta.

BACKGROUND: LDL-C, a cardiovascular disease risk assessment biomarker, is commonly calculated using the Friedewald equation. The NIH equation overcomes several limitations of the Friedewald equation. Consistent with the Canadian Society of Clinical Chemists (CSCC) lipid reporting recommendations, we assessed the NIH LDL-C equation in Alberta prior to its provincial implementation. METHODS: 1-year (01/01/2021-12/31/2021) of lipid results (n = 1,486,584 after data cleaning) were obtained from five analytical instrument groups used across Alberta. Analyses were performed on all data and after separating by age, analytical instrument group, and fasting status. The correlation between Friedewald- and NIH-calculated LDL-C and between Friedewald- and NIH-calculated LDL-C difference and each lipid parameter, was determined. The frequency of unreportable/inaccurate LDL-C results was compared between the two equations. The concordance between the two equations and with non-HDL-C was determined at LDL-C thresholds. Lastly, LDL-C calculated by Friedewald, NIH, and Martin-Hopkins equations was compared to density-gradient ultracentrifugation. RESULTS: Friedewald- and NIH-calculated LDL-C exhibit the strongest correlation when triglycerides ≤ 4.52 mmol/L. The difference between Friedewald- and NIH-calculated LDL-C increases with decreasing LDL-C concentration. The NIH equation yields fewer inaccurate results (0.35 % vs. 22.0 %). The percent agreement between equations was > 96 % at all LDL-C thresholds, suggesting most patients will not require treatment changes. NIH-calculated LDL-C exhibited better agreement with non-HDL-C when triglycerides ≤ 9.04 mmol/L and better correlated with LDL-C measured by ultracentrifugation (r2 = 0.926 vs. 0.775 (Friedewald) and 0.863 (Martin-Hopkins)). Results were consistent across age, analytical instrument group, and fasting status. CONCLUSIONS: Our findings demonstrate the benefits of implementing the NIH equation across Alberta.

Development of Direct LDL Measurement by LDL Precipitation Combined with Sandwich ELISA Using In-House-Generated mAbs.

One of the major risk factors for the progression of cardiovascular diseases is a high blood level of low-density lipoprotein (LDL), so progression of the disease may be prevented by lowering the plasma LDL. Evaluation and monitoring of LDL concentrations are therefore necessary. Friedewald's equation is a calculation method that is currently used routinely to estimate plasma LDL concentrations in hospital laboratories. However, this method cannot be applied to samples with a high concentration of triglyceride (TG). To overcome this limitation, this study aimed to develop direct LDL measurements using in-house generated monoclonal antibodies against human LDL in combination with LDL precipitation using heparin-containing citrate buffer pH 5.04. The method was applied to measure the LDL concentration in 208 randomized samples from Suranaree University of Technology Hospital. The mean values obtained from the developed method and the hospital laboratory were 126.6 ± 43.1 mg/dL and 123.2 ± 42.3 mg/dL, respectively. Linear regression analysis showed a high correlation between these two methods (r = 0.8491, p < 0.0001). High concentrations of TG, total cholesterol, and HDL have no influence on the LDL values obtained by this method. In this study, we offer an alternative technique for the direct measurement of plasma LDL. Further development for more convenient and easy use can now be undertaken.

Urban particulate air pollution linked to dyslipidemia by modification innate immune cells.

Air particulate matter (PM) is an essential risk factor for lipid metabolism disorders. However, the underlying mechanism remains unclear. In this cross-sectional study, 216 healthcare workers were recruited to estimate the associations among the daily exposure dose (DED) of air PM, innate immune cells, and plasma lipid levels. All participants were divided into two groups according to the air particulate combined DED (DED-PMC). The peripheral white blood cell counts, lymphocyte counts, and monocyte counts and percentages were higher in the higher-exposure group (HEG) than in the lower-exposure group (LEG), whereas the percentage of natural-killer cells was lower in the HEG than in the LEG. The plasma concentrations of the total cholesterol, triglycerides, LDL-C, and apolipoprotein B were higher in the HEG than in the LEG, whereas the HDL-C and apolipoprotein A1 were lower in the HEG than in the LEG. A dose-effect analysis indicated that when the DED of the air PM increased, there were increased peripheral monocyte counts and percentages, a decreased NK cell percentage, elevated plasma concentrations of total cholesterol, triglycerides, LDL-C, and apolipoprotein B, and reduced plasma levels of HDL-C and apolipoprotein A1. In addition, the modification of the innate immune cells was accompanied by alterations in the plasma lipid levels in a dose-dependent manner. Mediation effect analysis suggested innate immune cells were the potential mediators for the associations among air PM exposure on abnormal lipid metabolism. These results indicated that chronic exposure to air PM may disturb lipid metabolism by altering the distribution of innate immune cells in the peripheral blood, ultimately advancing cardiovascular disease risk.

Validation of low-density lipoprotein cholesterol equations in pediatric population.

Several studies have shown a high prevalence of dyslipidemia in children. Since childhood lipid concentrations continue into adulthood, recognition of lipid abnormalities in the early period is crucial to prevent the development of future coronary heart disease (CHD). Low density lipoprotein cholesterol (LDL-C) is one of the most used parameters in the initiation and follow-up of treatment in patients with dyslipidemia. It is a well known fact that LDL-C lowering therapy reduces the risk of future CHD. Therefore, accurate determination of the LDL-C levels is so important for the management of lipid abnormalities. This study aimed to validate different LDL-C estimating equations in the Turkish population, composed of children and adolescents. A total of 3,908 children below 18 years old at Sivas Cumhuriyet University Hospital (Sivas, Turkey) were included in this study. LDL-C was directly measured by direct homogeneous assays, i.e., Roche, Beckman, Siemens and estimated by Friedewald's, Martin/Hopkins', extended Martin-Hopkins' and Sampson's formulas. The concordances between the estimations obtained by the formulas and the direct measurements were evaluated both overall and separately for the LDL-C, triglycerides (TG) and non-high-density lipoprotein cholesterol (non-HDL-C) sublevels. Linear regression analysis was performed and residual error plots were generated between each estimation and direct measurement method. Coefficient of determination (R 2) and mean absolute deviations were also evaluated. The overall concordance of Friedewald, Sampson, Martin-Hopkins and the extended Martin-Hopkins formula were 64.6%, 69.9%, 69.4%, and 84.3% for the Roche direct assay, 69.8%, 71.6%, 73.6% and 80.4% for the Siemens direct assay, 66.5%, 68.8%, 68.9% and 82.1% for the Beckman direct assay, respectively. The extended Martin-Hopkins formula had the highest concordance coefficient in both overall and all sublevels of LDL-C, non-HDL-C, and TG. When estimating the LDL-C categories, the highest underestimation degrees were obtained with the Friedewald formula. Our analysis, conducted in a large pediatric population, showed that the extended Martin-Hopkins equation gives more reliable results in estimation of LDL-C compared to other equations.

Lipoprotein(a) levels in children with suspected familial hypercholesterolaemia: a cross-sectional study.

AIMS: Familial hypercholesterolaemia (FH) predisposes children to the early initiation of atherosclerosis and is preferably diagnosed by DNA analysis. Yet, in many children with a clinical presentation of FH, no mutation is found. Adult data show that high levels of lipoprotein(a) [Lp(a)] may underlie a clinical presentation of FH, as the cholesterol content of Lp(a) is included in conventional LDL cholesterol measurements. As this is limited to adult data, Lp(a) levels in children with and without (clinical) FH were evaluated. METHODS AND RESULTS: Children were eligible if they visited the paediatric lipid clinic (1989-2020) and if Lp(a) measurement and DNA analysis were performed. In total, 2721 children (mean age: 10.3 years) were included and divided into four groups: 1931 children with definite FH (mutation detected), 290 unaffected siblings/normolipidaemic controls (mutation excluded), 108 children with probable FH (clinical presentation, mutation not detected), and 392 children with probable non-FH (no clinical presentation, mutation not excluded). In children with probable FH, 32% were found to have high Lp(a) [geometric mean (95% confidence interval) of 15.9 (12.3-20.6) mg/dL] compared with 10 and 10% [geometric means (95% confidence interval) of 11.5 (10.9-12.1) mg/dL and 9.8 (8.4-11.3) mg/dL] in children with definite FH (P = 0.017) and unaffected siblings (P = 0.002), respectively. CONCLUSION: Lp(a) was significantly higher and more frequently elevated in children with probable FH compared with children with definite FH and unaffected siblings, suggesting that high Lp(a) may underlie the clinical presentation of FH when no FH-causing mutation is found. Performing both DNA analysis and measuring Lp(a) in all children suspected of FH is recommended to assess possible LDL cholesterol overestimation related to increased Lp(a).

[Association of small dense low-density lipoprotein cholesterol with H-type hypertension and MTHFR gene polymorphism].

To investigate the expression of small dense low-density lipoprotein cholesterol (sdLDL-C) in patients with H-type hypertension and its association with H-type hypertension and methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms. The retrospective study method was used,and a total of 207 hospitalized hypertensive patients (76 males and 131 females, aged 40-82 years, median age 66 years) admitted to the Zibo First Hospital from March 2021 to March 2022 were enrolled in this study. The levels of homocysteine (Hcy), sdLDL-C, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), triglyceride (TG) and lipoprotein (a) [Lp(a)] were measured. The patients were divided into H-type hypertensive group (n=105, 40 males and 65 females) and non-H-type hypertensive group (n=102, 36 males and 66 females) according to Hcy levels. The C677T polymorphism of methylenetetrahydrofolate reductase (MTHFR) gene was detected in each group. Logistic regression analysis was performed for the related factors of H-type hypertension. The serum sdLDL-C levels were (0.92±0.31) and (0.65±0.28) mmol/L in H-type hypertension group and non-H-type hypertension group, respectively. The sdLDL-C levels in H-type hypertension group were significantly higher than those in non-H-type hypertension group (t=6.500, P<0.01). There was no significant difference in the serum sdLDL-C levels between males and females in H-type hypertension group (t=-1.543, P=0.129). The CC, CT, TT genotypes and C and T allele frequencies of MTHFR C677T in H-type hypertension group were significantly different from those in non-H-type hypertension group (P<0.05). The Hcy and sdLDL-C levels in different genotypes of MTHFR in H-type hypertension group were significantly different (H=12.742, P=0.002; F=3.345, P=0.042). Among them, Hcy levels were higher in TT genotype than in CT and CC genotypes, respectively (Z=-28.099, P=0.003; Z=-16.112, P=0.040), and sdLDL-C levels were higher in TT genotype than in CC genotype (t=-2.587, P=0.012). Logistic regression analysis showed that age, sdLDL-C, and MTHFRC677T TT genotypes were associated with the development for H-type hypertension. In conclusion, the level of sdLDL-C is associated with MTHFR gene polymorphisms and may be associated with the development of H-type hypertension.

Estimation of low-density lipoprotein cholesterol levels using machine learning.

BACKGROUND: Low-density lipoprotein-cholesterol (LDL-C) is used as a threshold and target for treating dyslipidemia. Although the Friedewald equation is widely used to estimate LDL-C, it has been known to be inaccurate in the case of high triglycerides (TG) or non-fasting states. We aimed to propose a novel method to estimate LDL-C using machine learning. METHODS: Using a large, single-center electronic health record database, we derived a ML algorithm to estimate LDL-C from standard lipid profiles. From 1,029,572 cases with both standard lipid profiles (total cholesterol, high-density lipoprotein-cholesterol, and TG) and direct LDL-C measurements, 823,657 tests were used to derive LDL-C estimation models. Patient characteristics such as sex, age, height, weight, and other laboratory values were additionally used to create separate data sets and algorithms. RESULTS: Machine learning with gradient boosting (LDL-CX) and neural network (LDL-CN) showed better correlation with directly measured LDL-C, compared with conventional methods (r = 0.9662, 0.9668, 0.9563, 0.9585; for LDL-CX, LDL-CN, Friedewald [LDL-CF], and Martin [LDL-CM] equations, respectively). The overall bias of LDL-CX (-0.27 mg/dL, 95% CI -0.30 to -0.23) and LDL-CN (-0.01 mg/dL, 95% CI -0.04-0.03) were significantly smaller compared with both LDL-CF (-3.80 mg/dL, 95% CI -3.80 to -3.60) or LDL-CM (-2.00 mg/dL, 95% CI -2.00 to -1.94), especially at high TG levels. CONCLUSIONS: Machine learning algorithms were superior in estimating LDL-C compared with the conventional Friedewald or the more contemporary Martin equations. Through external validation and modification, machine learning could be incorporated into electronic health records to substitute LDL-C estimation.

Novel biomarker panel measuring endothelial injury identifies patients at risk of coronary artery syndrome and discordance with low-density lipoprotein cholesterol.

BACKGROUND: Individuals with no history of coronary artery disease can develop acute coronary syndrome (ACS), often in the absence of major risk factors including low-density lipoprotein cholesterol (LDL-C). We identified risk factors and biomarkers that can help identify those at discordantly high risk of ACS with normal LDL-C using a novel validated coronary artery disease predictive algorithm (CADPA) incorporating biomarkers of endothelial injury. METHODS: Five-year predicted ACS risk was calculated for 6392 persons using CADPA. Persons were classified as low (<3.5%), intermediate (3.5-<7.5%) or high (≥7.5%) CADPA risk and by LDL-C levels <130 mg/dL (low) and ≥130 mg/dL (high) and whether in the discordantly low LDL-C (but high CADPA risk) or high LDL-C (but low/intermediate CADPA risk) group. Multiple logistic regression identified risk factors and biomarkers that predicted discordance. RESULTS: 31% were classified as low (<3.5%), 27% at intermediate (3.5-<7.5%) and 42% were at high risk (≥7.5%). 28% of subjects were identified in the low LDL discordant risk group (LDL-C< 130 mg/dL but 5-year CADPA predicted risk ≥7.5%) and 19% in the high LDL discordant risk group (LDL-C ≥ 130 mg/dL but 5-year CADPA risk of <7.5%). Diabetes (odds ratio [OR], 2.84 [2.21-3.66]), male sex (OR, 2.83 [2.40-3.35]), family history (OR, 2.23 [1.88-2.64]) and active smoking (OR, 1.99 [1.50-2.62]) predicted low LDL risk discordance more than other risk factors (all P < 0.01). Increased serum soluble FAS, hemoglobin A1c and interleukin-16 were the biomarkers most independently associated with increased risk. CONCLUSIONS: Discordance between LDL-C levels and ACS risk is common. Males with diabetes and a family history of myocardial infarction who are actively smoking may be at highest risk of developing ACS despite controlled LDL-C. Future studies should examine whether using the CADPA can help identify individuals that could benefit from earlier targeting of risk factor modification for the prevention of ACS.

Genetically Predicted Insomnia in Relation to 14 Cardiovascular Conditions and 17 Cardiometabolic Risk Factors: A Mendelian Randomization Study.

Background This Mendelian randomization study aims to investigate causal associations between genetically predicted insomnia and 14 cardiovascular diseases (CVDs) as well as the potential mediator role of 17 cardiometabolic risk factors. Methods and Results Using genetic association estimates from large genome-wide association studies and UK Biobank, we performed a 2-sample Mendelian randomization analysis to estimate the associations of insomnia with 14 CVD conditions in the primary analysis. Then mediation analysis was conducted to explore the potential mediator role of 17 cardiometabolic risk factors using a network Mendelian randomization design. After correcting for multiple testing, genetically predicted insomnia was consistent significantly positively associated with 9 of 14 CVDs, those odds ratios ranged from 1.13 (95% CI, 1.08-1.18) for atrial fibrillation to 1.24 (95% CI, 1.16-1.32) for heart failure. Moreover, genetically predicted insomnia was consistently associated with higher body mass index, triglycerides, and lower high-density lipoprotein cholesterol, each of which may act as a mediator in the causal pathway from insomnia to several CVD outcomes. Additionally, we found very little evidence to support a causal link between insomnia with abdominal aortic aneurysm, thoracic aortic aneurysm, total cholesterol, low-density lipoprotein cholesterol, glycemic traits, renal function, and heart rate increase during exercise. Finally, we found no evidence of causal associations of genetically predicted body mass index, high-density lipoprotein cholesterol, or triglycerides on insomnia. Conclusions This study provides evidence that insomnia is associated with 9 of 14 CVD outcomes, some of which may be partially mediated by 1 or more of higher body mass index, triglycerides, and lower high-density lipoprotein cholesterol.

Proprotein Convertase Subtilisin Kexin Type 9 Inhibitors Reduce Platelet Activation Modulating ox-LDL Pathways.

Background: Proprotein convertase subtilisin kexin type 9 inhibitors (PCSK9i) lower LDL-cholesterol and slow atherosclerosis preventing cardiovascular events. While it is known that circulating PCSK9 enhances platelet activation (PA) and that PCSK9i reduce it, the underlying mechanism is not still clarified. Methods: In a multicenter before-after study in 80 heterozygous familial hypercholesterolemia (HeFH) patients on treatment with maximum tolerated statin dose ± ezetimibe, PA, soluble-NOX2-derived peptide (sNOX2-dp), and oxidized-LDL (ox-LDL) were measured before and after six months of PCSK9i treatment. In vitro study investigates the effects of plasma from HeFH patients before and after PCK9i on PA in washed platelets (wPLTs) from healthy subjects. Results: Compared to baseline, PCSK9i reduced the serum levels of LDL-c, ox-LDL, Thromboxane (Tx) B2, sNOX2-dp, and PCSK9 (p < 0.001). The decrease of TxB2 correlates with that of ox-LDL, while ox-LDL reduction correlated with PCSK9 and sNOX2-dp delta. In vitro study demonstrated that wPLTs resuspended in plasma from HeFH after PCSK9i treatment induced lower PA and sNOX2-dp release than those obtained using plasma before PCSK9i treatment. This reduction was vanished by adding ox-LDL. ox-LDL-induced PA was blunted by CD36, LOX1, and NOX2 inhibition. Conclusions: PCSK9i treatment reduces PA modulating NOX2 activity and in turn ox-LDL formation in HeFH patients.

Baseline cardiometabolic profiles and SARS-CoV-2 infection in the UK Biobank.

BACKGROUND: SARS-CoV-2 is a rapidly spreading coronavirus responsible for the Covid-19 pandemic, which is characterized by severe respiratory infection. Many factors have been identified as risk factors for SARS-CoV-2, with much early attention being paid to body mass index (BMI), which is a well-known cardiometabolic risk factor. OBJECTIVE: This study seeks to examine the impact of additional baseline cardiometabolic risk factors including high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), Apolipoprotein A-I (ApoA-I), Apolipoprotein B (ApoB), triglycerides, hemoglobin A1c (HbA1c) and diabetes on the odds of testing positive for SARS-CoV-2 in UK Biobank (UKB) study participants. METHODS: We examined the effect of BMI, lipid profiles, diabetes and alcohol intake on the odds of testing positive for SARS-Cov-2 among 9,005 UKB participants tested for SARS-CoV-2 from March 16 through July 14, 2020. Odds ratios and 95% confidence intervals were computed using logistic regression adjusted for age, sex and ancestry. RESULTS: Higher BMI, Type II diabetes and HbA1c were associated with increased SARS-CoV-2 odds (p < 0.05) while HDL-C and ApoA-I were associated with decreased odds (p < 0.001). Though the effect of BMI, Type II diabetes and HbA1c were eliminated when HDL-C was controlled, the effect of HDL-C remained significant when BMI was controlled for. LDL-C, ApoB and triglyceride levels were not found to be significantly associated with increased odds. CONCLUSION: Elevated HDL-C and ApoA-I levels were associated with reduced odds of testing positive for SARS-CoV-2, while higher BMI, type II diabetes and HbA1c were associated with increased odds. The effects of BMI, type II diabetes and HbA1c levels were no longer significant after controlling for HDL-C, suggesting that these effects may be mediated in part through regulation of HDL-C levels. In summary, our study suggests that baseline HDL-C level may be useful for stratifying SARS-CoV-2 infection risk and corroborates the emerging picture that HDL-C may confer protection against sepsis in general and SARS-CoV-2 in particular.

Residual Cardiovascular Risk at Low LDL: Remnants, Lipoprotein(a), and Inflammation.

BACKGROUND: Current guidelines target low-density lipoprotein cholesterol (LDL-C) concentrations to reduce atherosclerotic cardiovascular disease (ASCVD) risk, and yet clinical trials demonstrate persistent residual ASCVD risk despite aggressive LDL-C lowering. CONTENT: Non-LDL-C lipid parameters, most notably triglycerides, triglyceride-rich lipoproteins (TGRLs), and lipoprotein(a), and C-reactive protein as a measure of inflammation are increasingly recognized as associated with residual risk after LDL-C lowering. Eicosapentaenoic acid in statin-treated patients with high triglycerides reduced both triglycerides and ASCVD events. Reducing TGRLs is believed to have beneficial effects on inflammation and atherosclerosis. High lipoprotein(a) concentrations increase ASCVD risk even in individuals with LDL-C < 70 mg/dL. Although statins do not generally lower lipoprotein(a), proprotein convertase subtilisin/kexin type 9 inhibitors reduce lipoprotein(a) and cardiovascular outcomes, and newer approaches are in development. Persistent increases in C-reactive protein after intensive lipid therapy have been consistently associated with increased risk for ASCVD events. SUMMARY: We review the evidence that biochemical assays to measure TGRLs, lipoprotein(a), and C-reactive protein are associated with residual risk in patients treated to low concentrations of LDL-C. Growing evidence supports a causal role for TGRLs, lipoprotein(a), and inflammation in ASCVD; novel therapies that target TGRLs, lipoprotein(a), and inflammation are in development to reduce residual ASCVD risk.

Assessment of Low LDL Cholesterol in Patients Treated by PCSK9 Inhibition: Comparison of Martin/Hopkins and Friedewald Estimations.

PURPOSE: Recent guidelines recommend further reduction of low-density lipoprotein cholesterol (LDL-C) in high-risk populations. The use of proprotein convertase subtilisin/kexin type-9 inhibitors (PCSK9i) enables many patients to achieve profound reduction in LDL-C. However, in patients with low cholesterol, the commonly used Friedewald equation tends to underestimate LDL-C, which may result in undertreatment. We aimed to compare Friedewald LDL-C estimation with the more novel Martin/Hopkins method in PCSK9i-treated patients achieving low LDL-C. METHODS: We investigated high-risk patients treated by PCSK9i in whom Friedewald LDL-C levels were < 70 mg/dL and triglycerides ≤ 300 mg/dL. LDL-C was additionally assessed by the Martin/Hopkins method. The compatibility between estimations was evaluated using methods of concordance and reclassification between LDL-C categories (< 25, 25-40, 40-55, 55-70 mg/dL) and according to triglyceride strata. RESULTS: Mean age was 65 ± 10 years. The correlation coefficient between LDL-C estimations was r = 0.898. Martin/Hopkins reclassified 269 of the 608 patients (44%) to a higher LDL-C category, with 14% of the patients reaching LDL-C > 70 mg/dL. Of the 390 patients achieving Friedewald LDL-C < 55 mg/dL, 113 (29%) were estimated to have LDL-C ≥ 55 mg/dL by the Martin/Hopkins equation. The magnitude of discordance between LDL-C estimates was more pronounced in hypertriglyceridemic patients in whom LDL-C reclassification from < 55 to ≥ 55 mg/dL was observed in 48%. CONCLUSIONS: In real-world practice of high-risk patients achieving low LDL-C under PCSK9i, Martin/Hopkins algorithm displayed significant proportion of LDL-C upward discordance compared to the Friedewald equation, particularly observed in patients with elevated triglycerides, identifying patients that may need treatment intensification.

Association of small, dense LDL-cholesterol concentration and lipoprotein particle characteristics with coronary heart disease: A systematic review and meta-analysis.

OBJECTIVES: The aim of this study was to systematically collate and appraise the available evidence regarding the associations between small, dense low-density lipoprotein (sdLDL) and incident coronary heart disease (CHD), focusing on cholesterol concentration (sdLDL-C) and sdLDL particle characteristics (presence, density, and size). BACKGROUND: Coronary heart disease (CHD) is the leading cause of death worldwide. Small, dense low-density lipoprotein (sdLDL) has been hypothesized to induce atherosclerosis and subsequent coronary heart disease (CHD). However, the etiological relevance of lipoprotein particle size (sdLDL) versus cholesterol content (sdLDL-C) remains unclear. METHODS: PubMed, MEDLINE, Web of Science, and EMBASE were systematically searched for studies published before February 2020. CHD associations were based on quartile comparisons in eight studies of sdLDL-C and were based on binary categorization in fourteen studies of sdLDL particle size. Reported hazards ratios (HR) and odds ratios (OR) with 95% confidence interval (CI) were standardized and pooled using a random-effects meta-analysis model. RESULTS: Data were collated from 21 studies with a total of 30,628 subjects and 5,693 incident CHD events. The average age was 67 years, and 53% were men. Higher sdLDL and sdLDL-C levels were both significantly associated with higher risk of CHD. The pooled estimate for the high vs. low categorization of sdLDL was 1.36 (95% CI: 1.21, 1.52) and 1.07 (95% CI: 1.01, 1.12) for comparing the top quartiles versus the bottom of sdLDL-C. Several studies suggested a dose response relationship. CONCLUSIONS: The findings show a positive association between sdLDL or sdLDL-C levels and CHD, which is supported by an increasing body of genetic evidence in favor of its causality as an etiological risk factor. Thus, the results support sdLDL and sdLDL-C as a risk marker, but further research is required to establish sdLDL or sdLDL-C as a potential therapeutic marker for incident CHD risk reduction.

Elevated expression of FABP4 is associated with disease activity in rheumatoid arthritis patients.

Aim: Data from 124 rheumatoid arthritis (RA) patients and 69 healthy controls were collected. Materials & methods: ELISA was performed to detect serum FABP4 levels. Results: FABP4 level was elevated in RA patients and positively associated with 28-joint disease activity score, high-sensitivity C-reactive protein, erythrocyte sedimentation rate, total cholesterol, triglyceride and low-density lipoprotein cholesterol. Additionally, the area under the receiver operating characteristic curve for FABP4 was 0.685 for RA patients versus healthy controls (p = 0.001). RA patients were separated into low, moderate and high disease activity based on 28-joint disease activity score. The area under the receiver operating characteristic value was 0.877 for RA patients with high disease activity versus healthy controls (p < 0.001). Conclusion: FABP4 was associated with disease activity in RA patients.

Role of the Metabolic Profile in Mediating the Relationship Between Body Mass Index and Left Ventricular Mass in Adolescents: Analysis of a Prospective Cohort Study.

Background We aimed to quantify the role of the plasma metabolic profile in explaining the effect of adiposity on cardiac structure. Methods and Results Body mass index (BMI) was measured at age 11 in the Avon Longitudinal Study of Parents and Children. Left ventricular mass indexed to height2.7 (LVMI) was assessed by echocardiography at age 17. The metabolic profile was quantified via 1H-nuclear magnetic resonance spectroscopy at age 15. Multivariable confounder (maternal age, parity, highest qualification, maternal smoking, prepregnancy BMI, prepregnancy height, household social class, adolescent birthweight, adolescent smoking, fruit and vegetable consumption, and physical activity)-adjusted linear regression estimated the association of BMI with LVMI and mediation by metabolic traits. We considered 156 metabolomic traits individually and jointly as principal components explaining 95% of the variance in the nuclear magnetic resonance platform and assessed whether the principal components for the metabolic traits added to the proportion of the association explained by putative cardiovascular risk factors (systolic and diastolic blood pressures, insulin, triglycerides, low-density lipoprotein cholesterol, and glucose). A 1 kg/m2 higher BMI was associated with a 0.70 g/m2.7 (95% CI, 0.53-0.88 g/m2.7) and 0.66 g/m2.7 (95% CI, 0.53-0.79 g/m2.7) higher LVMI in males (n=437) and females (n=536), respectively. Putative risk factors explained 3% (95% CI, 2%-5%) of this association in males, increasing to 10% (95% CI, 8%-13%) when including metabolic principal components. In females, the standard risk factors explained 3% (95% CI, 2%-5%) of the association and did not increase when including the metabolic principal components. Conclusions The addition of the nuclear magnetic resonance-measured metabolic traits appears to mediate more of the association of BMI on LVMI than the putative risk factors alone in adolescent males, but not females.

Investigation of Lipid Profile and Clinical Manifestations in SCA Children.

INTRODUCTION: Clinical complications in sickle cell anemia (SCA) are heterogeneous and involve several molecules. It has been suggested that SCA individuals present a dyslipidemic phenotype and that lipid parameters are associated with severe clinical complications, such as pulmonary hypertension. We sought to investigate associations between lipid parameters and clinical manifestations, as well as other laboratory parameters in a population of pediatric SCA patients. METHODS: Our cross-sectional evaluation included 126 SCA patients in steady state and who were not undergoing lipid-lowering therapy. Hematological and biochemical parameters were characterized, and previous clinical manifestations were investigated. RESULTS: Total cholesterol and low-density lipoprotein cholesterol (LDL-C) levels were increased in patients with a previous history of pneumonia, which also positively correlated with HbS levels. Decreased LDL-C levels were also associated with leg ulcers and anemia. Elevated high-density lipoprotein cholesterol (HDL-C) levels were associated with pain crises, increased viscosity, and decreased hemolysis. Several studies have determined that lipids play a role in the vascular impairment seen in SCA, which was corroborated by our findings. CONCLUSIONS: In sum, our results suggest that total cholesterol, HDL-C, and LDL-C levels are associated with hemolysis and anemia markers and, most importantly, with clinical complications related to vasculopathy in SCA.