Dyslipidemia and aortic valve disease

Independent association of aortic stenosis with many known cardiovascular risk factors and many inflammatory diseases

BACKGROUND

Aortic valve stenosis is associated with age, rheumatic fever and bicuspid aortic valve, but its association with other co-morbidities, such as inflammatory disease and race/ethnicity, is less known.

AIM

To investigate any association between aortic stenosis and many co-morbidities.

METHODS

We used the large Nationwide Inpatient Sample database to evaluate any association between aortic stenosis and risk factors. We performed univariate and multivariable analyses, adjusting for co-morbid conditions.

RESULTS

Data were extracted from the first available database that used the International Classification of Diseases, Tenth Revision codes specifically coding for aortic stenosis alone, spanning from 2016 to 2020 (n=112,982,565). A total of 2,322,649 patients had aortic stenosis; the remaining 110,659,916 served as controls. We found a strong and independent significant association between aortic stenosis and coronary artery disease (odds ratio [OR]: 2.11, 95% confidence interval [CI]: 2.09-2.13), smoking (OR: 1.08, 95% CI: 1.07-1.08), diabetes mellitus (OR: 1.15, 95% CI: 1.14-1.16), hypertension (OR: 1.41, 95% CI: 1.4-1.42), hyperlipidaemia (OR: 1.31, 95% CI: 1.3-1.32), renal disease (OR: 1.3, 95% CI: 1.29-1.31), chronic obstructive pulmonary disease (OR: 1.05, 95% CI: 1.04-1.05), obesity (OR: 1.3, 95% CI: 1.29-1.32), white race/ethnicity (OR: 1.47, 95% CI: 1.42-1.52), rheumatoid arthritis (OR: 1.13, 95% CI: 1.11-1.15), scleroderma (OR: 1.93, 95% CI: 1.79-2.09), systemic connective tissue disease (OR: 1.24, 95% CI: 1.2-1.27), polyarteritis nodosa (OR: 1.5, CI: 1.24-1.81) and Raynaud's syndrome (OR: 1.16, 95% CI: 1.09-1.24) (all P<0.001), in addition to known factors, such as age, male sex and bicuspid aortic valve.

CONCLUSION

Using a very large database, we found many new associations with aortic valve stenosis, including race/ethnicity, renal disease, several inflammatory diseases, chronic obstructive pulmonary disease and obesity, in addition to many other known cardiovascular risk factors.

Mediation Effect of Body Mass Index on the Association of Urinary Nickel Exposure with Serum Lipid Profiles

The objective of this study was to determine the relationship of urinary nickel (U-Ni) exposure to serum lipid profiles and the mediation effect of body mass index (BMI) in a US general population. We analyzed the cross-sectional data from 3517 participants in the National Health and Nutrition Examination Survey (NHANES) (2017-March 2020). Multivariable linear regression and restricted cubic spline (RCS) regression were conducted to explore the association of U-Ni with four serum lipids and four lipids-derived indicators. Mediation analysis was performed to examine the effect of BMI on the relationship between U-Ni levels and serum lipid profiles. Compared with the lowest quartile, the β with 95% confidence intervals (CIs) in the highest quartile were - 12.83 (- 19.42, - 6.25) for total cholesterol (TC) (P for trend < 0.001), - 12.76 (- 19.78, - 5.74) for non-high-density lipoprotein cholesterol (non-HDL-C) (P for trend = 0.001) and - 0.29 (- 0.51, - 0.07) for TC/HDL-C (P for trend = 0.007) in the fully adjusted model. RCS plots showed the linear association of log₂-transformed U-Ni levels with TC, non-HDL-C and TC/HDL-C (P for nonlinearity = 0.294, 0.152, and 0.087, respectively). Besides, BMI decreased monotonically in correlation with increasing U-Ni levels (P for trend < 0.001). Mediation analysis revealed that BMI significantly mediated the relationship of U-Ni to TC, non-HDL-C and TC/HDL-C with mediated proportions of 11.17%, 22.20% and 36.44%, respectively. In summary, our findings suggest that BMI mediates the negative association of U-Ni with TC, non-HDL-C, and TC/HDL-C in the US general population.

Risk factors for cardiovascular events in patients with heterozygous familial hypercholesterolaemia: protocol for a systematic review

INTRODUCTION

Heterozygous familial hypercholesterolaemia (heFH) is the most common monogenic cause of premature atherosclerotic cardiovascular disease. The precise diagnosis of heFH is established by genetic testing. This systematic review will investigate the risk factors that predict cardiovascular events in patients with a genetic diagnosis of heFH.

METHODS AND ANALYSIS

Our literature search will cover publications from database inception until June 2023. We will undertake a search of CINAHL (trial), clinicalKey, Cochrane Library, DynaMed, Embase, Espacenet, Experiments (trial), Fisterra, ÍnDICEs CSIC, LILACS, LISTA, Medline, Micromedex, NEJM Resident 360, OpenDissertations, PEDro, Trip Database, PubPsych, Scopus, TESEO, UpToDate, Web of Science and the grey literature for eligible studies. We will screen the title, abstract and full-text papers for potential inclusion and assess the risk of bias. We will employ the Cochrane tool for randomised controlled trials and non-randomised clinical studies and the Newcastle-Ottawa Scale for assessing the risk of bias in observational studies. We will include full-text peer-reviewed publications, reports of a cohort/registry, case-control and cross-sectional studies, case report/series and surveys related to adults (≥18 years of age) with a genetic diagnostic heFH. The language of the searched studies will be restricted to English or Spanish. The Grading of Recommendations, Assessment, Development and Evaluation approach will be used to assess the quality of the evidence. Based on the data available, the authors will determine whether the data can be pooled in meta-analyses.

ETHICS AND DISSEMINATION

All data will be extracted from published literature. Hence, ethical approval and patient informed consent are not required. The findings of the systematic review will be submitted for publication in a peer-reviewed journal and presentation at international conferences.

PROSPERO REGISTRATION NUMBER

CRD42022304273.

Associations of thiocyanate, nitrate, and perchlorate exposure with dyslipidemia: a cross-sectional, population-based analysis

The aim of this study was to assess the associations of urinary thiocyanate, nitrate, and perchlorate concentrations with dyslipidemia, individually and in combination, which has not previously been studied. Data from the 2001-2002 and 2005-2016 National Health and Nutrition Examination Surveys (NHANES) were analyzed in this cross-sectional study. The dependent variables were continuous serum lipid variables (triglycerides [TG], total cholesterol [TC], low-density lipoprotein cholesterol [LDL-C], high-density lipoprotein cholesterol [HDL-C], non-HDL-C, and apolipoprotein B [Apo B]) and binary serum lipid variables, with the latter reflecting dyslipidemia (elevated TG, ≥ 150 mg/dL; elevated TC, ≥ 200 mg/dL; elevated LDL-C, ≥ 130 mg/dL; lowered HDL-C, < 40 mg/dL in men and < 5 0 mg/dL in women; elevated non-HDL-C, ≥ 160 mg/dL; and elevated Apo B, ≥ 130 mg/dL). Multivariate logistic, linear, and weighted quantile sum (WQS) regression analyses were used to explore the associations of thiocyanate, nitrate, and perchlorate with the continuous and binary serum lipid variables. The linearity of the associations with the binary serum lipid variables was assessed using restricted cubic spline (RCS) regression. A total of 15,563 adults were included in the analysis. The multivariate linear and logistic regression analyses showed that thiocyanate was positively associated with multiple continuous (TG, TC, LDL-C, non-HDL-C, and Apo B, but not HDL-C) and binary (elevated TG, TC, LDL-C, and non-HDL-C) serum lipid variables, whereas perchlorate was negatively associated with elevated LDL-C. Multivariate RCS logistic regression revealed a linear dose-response relationship between thiocyanate and elevated TG, TC, LDL-C, non-HDL-C, and Apo B, but a nonlinear relationship with lowered HDL-C (inflection point = 1.622 mg/L). WQS regression showed that a mixture of thiocyanate, nitrate, and perchlorate was positively associated with all binary serum lipid variables except for Apo B. Our findings indicate that urinary thiocyanate, nitrate, and perchlorate concentrations, individually and in combination, were associated with dyslipidemia.

Blood ethylene oxide, systemic inflammation, and serum lipid profiles: Results from NHANES 2013-2016

BACKGROUND

Using data from the National Health and Nutrition Examination Survey (NHANES), this study aimed to explore the relationship between ethylene oxide (EO) exposure and serum lipid profiles as well as the mediation effect of systemic inflammation among the general adult population.

METHODS

This cross-sectional study analyzed NHANES data from 2013 to 2016, examining a total of 2721 participants. The EO biomarker (hemoglobin adduct of EO [HbEO]) was quantified in blood using a high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method. The association among HbEO levels, inflammatory biomarkers, and four serum lipids was evaluated using a multivariable linear regression model. Mediating analysis was performed to examine the effect of inflammatory biomarkers on the relationship between HbEO levels and serum lipid profiles.

RESULTS

As the quartiles of HbEO increased, high-density lipoprotein cholesterol (HDL-C) monotonically decreased (p for trend <0.001). Using the lowest quartile of HbEO as a reference, the percent change for HDL-C was 6.30% (95% CI: 3.89%, 8.71%) in the highest quartile of HbEO. HbEO levels were dose-dependently associated with triglycerides (TG) (p for trend = 0.001). The percent change in TG in the fourth quartile of HbEO was 17.24% (95% CI: 2.01%, 32.48%) compared to the first quartile. Overall, inflammatory biomarkers (hs-CRP, alkaline phosphatase, white blood cell count, neutrophil count, and lymphocyte count) increased monotonically in correlation with increasing HbEO levels (all p for trend <0.01); were positively correlated with total cholesterol (TC), TG, and low-density lipoprotein cholesterol (LDL-C); and were negatively associated with HDL-C. Additionally, inflammatory biomarkers strongly mediated the relationships between HbEO and HDL-C and TG with maximum mediated proportions of 21.40% and 33.40%, respectively.

CONCLUSIONS

These findings suggest that HbEO is closely linked to serum lipid profiles and that systemic inflammation may be a key mediator of this association.

Familial Hypercholesterolemia and Elevated Lipoprotein(a): Cascade Testing and Other Implications for Contextual Models of Care

Elevated lipoprotein(a) [Lp(a)], a predominantly genetic disorder, is a causal risk factor for atherosclerotic cardiovascular disease (ASCVD) and calcific aortic valvular disease, particularly in patients with familial hypercholesterolemia (FH), a Tier I genomic condition. The combination from birth of the cumulative exposure to elevated plasma concentrations of both Lp(a) and low-density lipoprotein is particularly detrimental and explains the enhanced morbidity and mortality risk observed in patients with both conditions. An excellent opportunity to identify at-risk patients with hyper-Lp(a) at increased risk of ASCVD is to test for hyper-Lp(a) during cascade testing for FH. With probands having FH and hyper-Lp(a), the yield of detection of hyper-Lp(a) is 1 individual for every 2.1-2.4 relatives tested, whereas the yield of detection of both conditions is 1 individual for every 3-3.4 relatives tested. In this article, we discuss the incorporation of assessment of Lp(a) in the cascade testing in FH as a feasible and crucial part of models of care for FH. We also propose a simple management tool to help physicians identify and manage elevated Lp(a) in FH, with implications for the care of Lp(a) beyond FH, noting that the clinical use of RNA therapeutics for specifically targeting the overproduction of Lp(a) in at risk patients is still under investigation.

Familial Hypercholesterolemia and Lipoprotein(a): Two Partners in Crime?

PURPOSE OF REVIEW

Familial hypercholesterolemia is a high cardiovascular risk disorder. We will review the role of lipoprotein(a) in cardiovascular risk and in aortic valve stenosis in familial hypercholesterolemia, as well as its association with their phenotype, and strategies to identify this high-risk population.

RECENT FINDINGS

Patients with familial hypercholesterolemia have higher lipoprotein(a) levels mainly due to an increased frequency of LPA variants, and the cardiovascular risk is increased twofolds when both conditions coexist. Also, an increased risk for aortic valve stenosis and valve replacement has been observed with high lipoprotein(a) levels. Assessment of lipoprotein(a) during the cascade screening for familial hypercholesterolemia is a good opportunity to identify this high-risk population. High cardiovascular risk in familial hypercholesterolemia is increased even more when lipoprotein(a) is also elevated. Measurement of lipoprotein(a) in these patients is crucial to identify those subjects who need to intensify LDL-cholesterol reduction pending availability of lipoprotein(a)-specific treatments.