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BackgroundThe response in levels of very-low-density (VLDL) and low-density (LDL) lipoproteins varies substantially among hyperlipidemic patients during treatment with HMGCoA reductase inhibitors. Apolipoprotein E genotype and gender are known to contribute to the regulation of steady state levels of plasma lipoproteins. This study explores the effect of these and other potential determinants of the response of VLDL and LDL to treatment with reductase inhibitors.MethodsUsing mixed linear statistical models, the response of lipoprotein lipid values was studied in 142 hyperlipidemic individuals who were treated with reductase inhibitors. Patients received one or more of the following drugs individually for a total of 623 treatment observations: lovastatin, pravastatin, simvastatin, or atorvastatin. For evaluation of the effects of treatment in the aggregate, actual doses were expressed as equivalent doses of atorvastatin, using factors based on random assignment comparisons in 16 reported studies. The analysis factors considered were apolipoprotein E genotype, baseline average triglycerides >170 mg/dL (vs less), and gender.ResultsPresence of an apo epsilon4 allele was associated with a trend toward greater reduction of triglyceride levels and a diminished ability of the reductase inhibitors to reduce LDL cholesterol levels. Gender had only minimal effect on the response of either LDL cholesterol or triglycerides. However, the effect of elevated baseline triglycerides on the response of both triglycerides and LDL cholesterol was striking and was exerted in opposite directions. The triglyceride-lowering effect of reductase inhibitors was greater in patients with initial triglyceride levels above 170 mg/dL (P=0.0001). The effect was even greater in patients with initial triglyceride levels over 250 mg/dL (P=0.015). Conversely, for LDL cholesterol levels, elevated baseline triglycerides were associated with a significantly decreased response to the drugs (P=0.0015).ConclusionsThese findings indicate that baseline triglyceride levels are an important predictor of response of plasma lipoproteins to HMGCoA reductase inhibitors, perhaps reflecting fundamental differences in mechanism underlying the hyperlipidemic phenotype.

Triglyceride-rich lipoproteins bind and inactive bacterial endotoxin in vitro and prevent death when given before a lethal dose of endotoxin in animals. However, lipoproteins have not yet been demonstrated to improve survival in polymicrobial gram-negative sepsis. We therefore tested the ability of triglyceride-rich lipoproteins to prevent death after cecal ligation and puncture (CLP) in rats. Animals were given bolus infusions of either chylomicrons (1 g triglyceride/kg per 4 h) or an equal volume of saline for 28 h after CLP. Chylomicron infusions significantly improved survival (measured at 96 h) compared with saline controls (80 vs 27%, P < or = 0.03). Chylomicron infusions also reduced serum levels of endotoxin, measured 90 min (26 +/- 3 vs 136 +/- 51 pg/ml, mean +/- SEM, P < or = 0.03) and 6 h (121 +/- 54 vs 1,026 +/- 459 pg/ml, P < or = 0.05) after CLP. The reduction in serum endotoxin correlated with a reduction in serum tumor necrosis factor, measured 6 h after CLP (0 +/- 0 vs 58 +/- 24 pg/ml, P < or = 0.03), suggesting that chylomicrons improve survival in this model by limiting macrophage exposure to endotoxin and thereby reducing secretion of inflammatory cytokines. Infusions of a synthetic triglyceride-rich lipid emulsion (Intralipid; KabiVitrum, Inc., Alameda, CA) (1 g triglyceride/kg) also significantly improved survival compared with saline controls (71 vs 27%, P < or = 0.03). These data demonstrate that triglyceride-rich lipoproteins can protect animals from lethal polymicrobial gram-negative sepsis.

Lipoproteins isolated from normal human plasma can bind and neutralize bacterial lipopolysaccharide (LPS) and may represent an important mechanism in host defense against gram-negative septic shock. Recent studies have shown that experimentally elevating the levels of circulating high-density lipoproteins (HDL) provides protection against death in animal models of endotoxic shock. We sought to define the components of HDL that are required for neutralization of LPS. To accomplish this we have studied the functional neutralization of LPS by native and reconstituted HDL using a rapid assay that measures the CD14-dependent activation of leukocyte integrins on human neutrophils. We report here that reconstituted HDL particles (R-HDL), prepared from purified apolipoprotein A-I (apoA-I) combined with phospholipid and free cholesterol, are not sufficient to neutralize the biologic activity of LPS. However, addition of recombinant LPS binding protein (LBP), a protein known to transfer LPS to CD14 and enhance responses of cells to LPS, enabled prompt binding and neutralization of LPS by R-HDL. Thus, LBP appears capable of transferring LPS not only to CD14 but also to lipoprotein particles. In contrast with R-HDL, apoA-I containing lipoproteins (LpA-I) isolated from plasma by selected affinity immunosorption (SAIS) on an anti-apoA-I column, neutralized LPS without addition of exogenous LBP. Several lines of evidence demonstrated that LBP is a constituent of LpA-I in plasma. Passage of plasma over an anti-apoA-I column removed more than 99% of the LBP detectable by ELISA, whereas 31% of the LBP was recovered by elution of the column. Similarly, the ability of plasma to enable activation of neutrophils by LPS (LBP/Septin activity) was depleted and recovered by the same process. Furthermore, an immobilized anti-LBP monoclonal antibody coprecipitated apoA-I. The results described here suggest that in addition to its ability to transfer LPS to CD14, LBP may also transfer LPS to lipoproteins. Since LBP appears to be physically associated with lipoproteins in plasma, it is positioned to play an important role in the neutralization of LPS.

Background: The genetic basis of hypertriglyceridemia (HTG) is complex and includes variants in Lipase Maturation Factor 1 (LMF1), an endoplasmic reticulum (ER)-chaperone involved in the post-translational activation of lipoprotein lipase (LPL)., Objective: The objective of this study was to identify and functionally characterize biallelic LMF1 variants in patients with HTG., Methods: Genomic DNA sequencing was used to identify biallelic LMF1 variants in HTG patients without deleterious variants in LPL, apolipoprotein C-II (APOC2), glycosylphosphatidylinositol-anchored high-density lipoprotein binding protein 1 (GPIHBP1) or apolipoprotein A-V (APOA5). LMF1 variants were functionally evaluated by in silico analyses and assessing their impact on LPL activity, LMF1 protein expression and specific activity in transiently transfected HEK293 cells., Results: We identified four homozygous LMF1 variants in patients with severe HTG: two novel rare variants (p.Asn147Lys and p.Pro246Arg) and two low-frequency variants (p.Arg354Trp and p.Arg364Gln) previously reported at heterozygosity. We demonstrate that all four variants reduce the secretion of enzymatically active LPL by impairing the specific activity of LMF1, whereas p.Asn147Lys also diminishes LMF1 protein expression., Conclusion: This study extends the role of LMF1 as a genetic determinant in severe HTG and demonstrates that rare and low-frequency LMF1 variants can underlie this condition through distinct molecular mechanisms. The clinical phenotype of patients affected by partial loss of LMF1 function is consistent with Multifactorial Chylomicronemia Syndrome (MCS) and suggests that secondary factors and additional genetic determinants contribute to HTG in these subjects., Competing Interests: Conflict of Interest None., (Copyright © 2024. Published by Elsevier Inc.)

Objectives: With the legalization of cannabis in New Jersey on April 21, 2022, including the licensing of cannabis dispensaries, concerns have arisen about potential adverse events related to cannabis use. Here, we explore temporal trends and risk factors for cannabis-related harm in both adult and pediatric cannabis-related visits at a tertiary care academic institution., Methods: We performed a retrospective chart review and temporal trend analysis via the electronic health record from May 1, 2019 to October 31, 2022, covering 2 years before, and 6 months after, cannabis legalization in New Jersey. The pediatric charts identified were analyzed for root causes of adverse events, and changes in the frequency of specific unsafe practices since cannabis legalization were tracked., Results: We found that adult cannabis ED-related visits significantly increased during the COVID-19 pandemic and remained higher than pre-pandemic levels for the remainder of the study periods, without a significant change upon legalization. Pediatric rates of cannabis-related ED visits did not vary significantly during the study period. The vast majority of visits for children aged 0-12 years were related to accidental cannabis exposures-often a household member's edibles-whereas most visits for older children stemmed from intentional cannabis use., Conclusion: This project highlights the unintended consequences of wider cannabis access in New Jersey. Notably, cannabis use increased even before its legalization, presumably in response to the COVID-19 pandemic and its attendant mental health effects. Rates of cannabis use disorder and its highlight of other concurrent psychiatric disorders are important topics for both clinicians and lawmakers to consider., Competing Interests: The authors declare no conflicts of interset., (© 2024 The Authors. Journal of the American College of Emergency Physicians Open published by Wiley Periodicals LLC on behalf of American College of Emergency Physicians.)

Background: Substantial data support a heritable basis for supraventricular tachycardias, but the genetic determinants and molecular mechanisms of these arrhythmias are poorly understood. We sought to identify genetic loci associated with atrioventricular nodal reentrant tachycardia (AVNRT) and atrioventricular accessory pathways or atrioventricular reciprocating tachycardia (AVAPs/AVRT)., Methods: We performed multiancestry meta-analyses of genome-wide association studies to identify genetic loci for AVNRT (4 studies) and AVAP/AVRT (7 studies). We assessed evidence supporting the potential causal effects of candidate genes by analyzing relations between associated variants and cardiac gene expression, performing transcriptome-wide analyses, and examining prior genome-wide association studies., Results: Analyses comprised 2384 AVNRT cases and 106 489 referents, and 2811 AVAP/AVRT cases and 1,483 093 referents. We identified 2 significant loci for AVNRT, which implicate NKX2-5 and TTN as disease susceptibility genes. A transcriptome-wide association analysis supported an association between reduced predicted cardiac expression of NKX2-5 and AVNRT. We identified 3 significant loci for AVAP/AVRT, which implicate SCN5A , SCN10A , and TTN/CCDC141 . Variant associations at several loci have been previously reported for cardiac phenotypes, including atrial fibrillation, stroke, Brugada syndrome, and electrocardiographic intervals., Conclusions: Our findings highlight gene regions associated with ion channel function (AVAP/AVRT), as well as cardiac development and the sarcomere (AVAP/AVRT and AVNRT) as important potential effectors of supraventricular tachycardia susceptibility., Competing Interests: Disclosures Dr Lubitz is a full-time employee of Novartis as of July 2022. Previously, Dr Lubitz received research support from Bristol Myers Squibb/Pfizer, Bayer AG, Boehringer Ingelheim, Fitbit, IBM, Medtronic, and Premier, Inc, and consulted for Bristol Myers Squibb/Pfizer, Bayer AG, Blackstone Life Sciences, and Invitae. Dr Ellinor receives research support from Bayer AG, IBM, and Bristol Myers Squibb/Pfizer and has consulted for Novartis, MyoKardia, and Bayer AG. Dr Damrauer receives research support for RenalytixAI and has consulted for Calico Labs. Dr Svendsen is a member of Medtronic advisory boards and has received speaker honoraria and research grants from Medtronic outside this work. Dr Cutler has consulted for Janssen Scientific. Dr Roselli is supported by a grant from Bayer AG to the Broad Institute focused on the development of therapeutics for cardiovascular disease. The other authors report no conflicts.

Background: African American smokers have 2.5 times higher risk for stroke compared with nonsmokers (higher than other races). About 50% of the African American population carry 1 or 2 genetic variants (G1 and G2; rare in other races) of the apolipoprotein L1 gene ( APOL1 ). Studies showed these variants may be associated with stroke. However, the role of the APOL1 risk variants in tobacco-related stroke is unknown., Methods and Results: In a cross-sectional study, we examined whether APOL1 risk variants modified the relationship between tobacco smoking and stroke prevalence in 513 African American adults recruited at University of California, San Francisco. Using DNA, plasma, and questionnaires we determined APOL1 variants, smoking status, and stroke prevalence. Using logistic regression models, we examined the association between smoking ( ever versus never smokers) and stroke overall, and among carriers of APOL1 risk variants (1 or 2 risk alleles), and noncarriers, separately. Among participants, 41% were ever ( current and past ) smokers, 54% were carriers of the APOL1 risk variants, and 41 had a history of stroke. The association between smoking and stroke differed by APOL1 genotype ( P interaction term =0.014). Among carriers, ever versus never smokers had odds ratio (OR) 2.46 (95% CI, 1.08-5.59) for stroke ( P =0.034); OR 2.00 (95% CI, 0.81-4.96) among carriers of 1 risk allele, and OR 4.72 (95% CI, 0.62-36.02) for 2 risk alleles. Among noncarriers, smoking was not associated with a stroke., Conclusions: Current and past smokers who carry APOL1 G1 and/or G2 risk variants may be more susceptible to stroke among the African American population.

Cigarette smoking is a preventable epidemic that is a leading cause of death. It increases the risk of coronary heart disease, stroke, lung cancer, chronic obstructive lung diseases etc., multifold. Smoking tobacco is not only injurious to oneself but also to those who are exposed second hand. Smoking induces endothelial dysfunction via inflammatory cytokines that can be quantified precisely. Cytokines can be leveraged as powerful predictive biomarkers for identifying risk of potential diseases. Current advances in biomarker research are providing substantive evidence of the roles of cytokines in disease. This is driving precision-based diagnosis and translational therapeutic interventions. Innovative machine algorithms (ML) are pioneering transformative changes in the field of medical research. This research implements the Neural Networks (NN) algorithm to classify smokers versus non-smokers using 63 cytokines as predictor features. In addition to the fact that NN is a generative algorithm, which makes it a very powerful tool to achieve the objective of this differentiation, techniques like cross validation and hyperparameter tuning improve the efficacy of the algorithm. The study identified the 10 most impactful predictor features that contributed to the classification and then used these to characterize smokers versus non-smokers. Primarily, the study constructed and investigated two classifiers, of which the first implemented NN using the entire set of 63 cytokines and the second using 10 most informative cytokines. The performance of the first classifier, implemented using 63 cytokines, evaluated by area under receiver operating characteristic (AUROC), was extremely good with an AUROC score of .949 and 95% Confidence Interval (CI) (.923,.974). The second classifier that used the 10 most impactful cytokines with regard to the classification, demonstrated an exemplary performance, with an AUROC score of .995 and a 95% CI (.991,1). The 10 most impactful cytokines from the aspect of smoker versus non-smoker differentiation, listed in order of importance, include: I-TAC, IL-22, IL-2R, IL-3, HGF, IL-18, G-CSF-CSF-3, MIF, SDF-1alpha, MMP-1. To gain a deeper understanding of the effect of smoking on cytokine levels, a 2-sample independent t test was performed, ascertaining the statistical significance of the 63 cytokine levels in smokers versus non-smokers. Machine Learning using biomarkers such as cytokines will enhance the ability to predict the advent of a disease and its outcome, and lead to novel treatment strategies., Competing Interests: Competing interests The authors report no conflicts of interest.

Coronary artery disease (CAD) is a leading cause of mortality in the world. It is important to be able to proactively assess the risk of the disease, using novel biomarkers like cytokines that are indicators of inflammation in addition to traditional predictors of risk. Atherosclerosis, the primary cause of CAD, is an inflammatory disease involving cytokines. Identifying which cytokines are specifically altered can advance diagnosis and personalized treatment. Emerging research demonstrates that cytokines are transported on high density lipoproteins (HDL). Therefore, it is important to explore the roles of HDL-associated cytokines in vascular inflammation. Machine Learning (ML) algorithms are enhancing pioneering research from the standpoint of precision medicine. This technology can materially enable the translation of scientific research to clinical practice. In this study we implemented logistic regression and the derived regularized techniques using age and multidimensional cytokine biomarkers with the objective of identification of individuals "At Risk" for CAD. These techniques were further empowered by k-fold cross validation and hyper parameter tuning. Of the numerous algorithms investigated, the three most prominent ones, assessed based on area under receiver operating characteristic (AUROC) score are as follows: logistic regression, least absolute shrinkage, and selection operator (LASSO) regression with feature selection and ridge regression with feature selection. Logistic regression demonstrated an AUROC score of .85 with a 95% Confidence Interval CI (.804, .897), LASSO regression achieved a better AUROC score of .875 with a 95% CI (.832, .917) and finally ridge regression with feature selection exhibited the highest AUROC score of .878 with a 95% CI (.837, .92). The 2-sample independent t test proved that the three techniques were statistically significantly different from each other. With regard to the best classification demonstrated by ridge regression with feature selection, the most prominent biomarkers identified for the best classification achieved by ridge regression by feature selection, in the order of importance are as follows: Age, IL-7, RANTES, IFN-gamma, IL-3, GM-CSF, IL-15, IP-10, GCSF, IL-12. The identification and quantification of cytokines transported by HDL provide novel mechanistic insights that can inform the assessment of risk and therapeutic intervention in CAD., Competing Interests: Competing interests The authors report no conflicts of interest.

Smoking is a major cause of premature and preventable death. Tobacco exposure has a detrimental effect on many organs and contributes to multiple diseases including chronic obstructive pulmonary disease (COPD), cardiovascular disease, cancer, and diabetes. Cytokines are inflammatory biomarkers that are mechanistically associated with smoking. Machine Learning algorithms allow for the quantitative assessment of the contributions of individual cytokines to tobacco-related diseases. The mapping of cytokines to disease can facilitate and direct treatment modalities. By the application of k Nearest Neighbor (k-NN) and Random Forest machine learning algorithms on 63 plasma cytokines we have demonstrated the classification of smoking. To ensure optimal results, performance improvement techniques such as k-fold cross validation and hyper parameter tuning are employed. Separability efficiency achieved by the models is evaluated using the Area Under the Receiver Operating Characteristic (AUROC) metric. The most significant cytokines that enabled the classification are identified and presented. The statistically significant difference for AUROC score of k-NN and Random Forest has been ascertained using the 2-sample independent t test. A reasonably good classification performance was achieved by k-NN algorithm with an AUROC metric of .87, and a 95% CI of (.823,.917). Random forest exceeded k-NN algorithm's performance, with a perfect AUROC score of 1 and a 95% CI of (1,1). From among the ten most prominent cytokines that contributed to the classification, the ones common to both algorithms are: LIF, IL22, G-CSF/CSF-3, TRAIL. AUROC scores for k-NN and Random Forest are significantly different (p-value = 5.105e-16). The discovery and transference of biomarkers such as cytokines from the platform of molecular investigation to clinical practice, can facilitate precision medicine-based therapeutic interventions., Competing Interests: Competing interests The authors report no conflicts of interest.

Background: Dementia with Lewy bodies (DLB) is an important cause of dementia with a range of clinical manifestations, including motor, neuropsychiatric, and autonomic symptoms. Compared with more common forms of dementia such as Alzheimer's disease, DLB has been the focus of significantly fewer treatment studies, often with diverse outcome measures, making comparison and clinical implementation difficult. A core outcome set (COS) can address this by ensuring that data are comparable, relevant, useful, and usable for making the best healthcare decisions. Methods: Using a multi-stage approach, development of the DLB-COS will include the following stages: (1) A systematic review, following PRISMA guidelines to create an initial long list of outcomes; (2) A two-round online Delphi including clinicians, scientists, policymakers, and individuals with lived experience of DLB and their representatives; (3) An online consensus meeting to agree on the final core list of outcomes (the final DLB-COS) for use in research and clinical practice; (4) A systematic review to identify appropriate measurement instruments for the DLB-COS outcomes; (5) A final consensus meeting of the professional stakeholders who attended the online consensus meeting to agree on the instruments that should be used to measure the outcomes in the DLB-COS; and (6) Global dissemination. Discussion: This is a multi-stage project to develop a COS to be used in treatment trials for DLB. A DLB-COS will ensure the selection of relevant outcomes and will identify the instruments to be used to measure DLB globally. Keywords : Dementia, Dementia with Lewy Bodies, Core Outcome Set, Delphi, Systematic Review, Ageing, Cognition, Memory., Competing Interests: No competing interests were disclosed., (Copyright: © 2023 Grycuk E et al.)

Introduction: Operationalized research criteria for mild cognitive impairment with Lewy bodies (MCI-LB) were published in 2020. The aim of this systematic review and meta-analysis was to review the evidence for the diagnostic clinical features and biomarkers in MCI-LB set out in the criteria., Methods: MEDLINE, PubMed, and Embase were searched on 9/28/22 for relevant articles. Articles were included if they presented original data reporting the rates of diagnostic features in MCI-LB., Results: Fifty-seven articles were included. The meta-analysis supported the inclusion of the current clinical features in the diagnostic criteria. Evidence for striatal dopaminergic imaging and meta-iodobenzylguanidine cardiac scintigraphy, though limited, supports their inclusion. Quantitative electroencephalogram (EEG) and fluorodeoxyglucose positron emission tomography (PET) show promise as diagnostic biomarkers., Discussion: The available evidence largely supports the current diagnostic criteria for MCI-LB. Further evidence will help refine the diagnostic criteria and understand how best to apply them in clinical practice and research., Highlights: A meta-analysis of the diagnostic features of MCI-LB was carried out. The four core clinical features were more common in MCI-LB than MCI-AD/stable MCI. Neuropsychiatric and autonomic features were also more common in MCI-LB. More evidence is needed for the proposed biomarkers. FDG-PET and quantitative EEG show promise as diagnostic biomarkers in MCI-LB., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background Homozygous familial hypercholesterolemia (HoFH) is a rare, treatment-resistant disorder characterized by early-onset atherosclerotic and aortic valvular cardiovascular disease if left untreated. Contemporary information on HoFH in the United States is lacking, and the extent of underdiagnosis and undertreatment is uncertain. Methods and Results Data were analyzed from 67 children and adults with clinically diagnosed HoFH from the CASCADE (Cascade Screening for Awareness and Detection) FH Registry. Genetic diagnosis was confirmed in 43 patients. We used the clinical characteristics of genetically confirmed patients with HoFH to query the Family Heart Database, a US anonymized payer health database, to estimate the number of patients with similar lipid profiles in a "real-world" setting. Untreated low-density lipoprotein cholesterol levels were lower in adults than children (533 versus 776 mg/dL; P =0.001). At enrollment, atherosclerotic cardiovascular disease and supravalvular and aortic valve stenosis were present in 78.4% and 43.8% and 25.5% and 18.8% of adults and children, respectively. At most recent follow-up, despite multiple lipid-lowering treatment, low-density lipoprotein cholesterol goals were achieved in only a minority of adults and children. Query of the Family Heart Database identified 277 individuals with profiles similar to patients with genetically confirmed HoFH. Advanced lipid-lowering treatments were prescribed for 18%; 40% were on no lipid-lowering treatment; atherosclerotic cardiovascular disease was reported in 20%; familial hypercholesterolemia diagnosis was uncommon. Conclusions Only patients with the most severe HoFH phenotypes are diagnosed early. HoFH remains challenging to treat. Results from the Family Heart Database indicate HoFH is systemically underdiagnosed and undertreated. Earlier screening, aggressive lipid-lowering treatments, and guideline implementation are required to reduce disease burden in HoFH.

Mutations in a diverse set of driver genes increase the fitness of haematopoietic stem cells (HSCs), leading to clonal haematopoiesis 1 . These lesions are precursors for blood cancers 2-6 , but the basis of their fitness advantage remains largely unknown, partly owing to a paucity of large cohorts in which the clonal expansion rate has been assessed by longitudinal sampling. Here, to circumvent this limitation, we developed a method to infer the expansion rate from data from a single time point. We applied this method to 5,071 people with clonal haematopoiesis. A genome-wide association study revealed that a common inherited polymorphism in the TCL1A promoter was associated with a slower expansion rate in clonal haematopoiesis overall, but the effect varied by driver gene. Those carrying this protective allele exhibited markedly reduced growth rates or prevalence of clones with driver mutations in TET2, ASXL1, SF3B1 and SRSF2, but this effect was not seen in clones with driver mutations in DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 led to the expression of TCL1A protein and the expansion of HSCs in vitro. The protective allele restricted TCL1A expression and expansion of mutant HSCs, as did experimental knockdown of TCL1A expression. Forced expression of TCL1A promoted the expansion of human HSCs in vitro and mouse HSCs in vivo. Our results indicate that the fitness advantage of several commonly mutated driver genes in clonal haematopoiesis may be mediated by TCL1A activation., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: Dementia with Lewy bodies (DLB) is an important cause of dementia with a range of clinical manifestations, including motor, neuropsychiatric, and autonomic symptoms. Compared with more common forms of dementia such as Alzheimer's disease, DLB has been the focus of significantly fewer treatment studies, often with diverse outcome measures, making comparison and clinical implementation difficult. A core outcome set (COS) can address this by ensuring that data are comparable, relevant, useful, and usable for making the best healthcare decisions. Methods: Using a multi-stage approach, development of the DLB-COS will include the following stages: (1) A systematic review, following PRISMA guidelines to create an initial long list of outcomes; (2) A two-round online Delphi including clinicians, scientists, policymakers, and individuals with lived experience of DLB and their representatives; (3) An online consensus meeting to agree on the final core list of outcomes (the final DLB-COS) for use in research and clinical practice; (4) A literature search to identify appropriate measurement instruments for the DLB-COS outcomes; (5) A final consensus meeting of the professional stakeholders who attended the online consensus meeting to agree on the instruments that should be used to measure the outcomes in the DLB-COS; and (6) Global dissemination. Discussion: This is a multi-stage project to develop a COS to be used in treatment trials for DLB. A DLB-COS will ensure the selection of relevant outcomes and will identify the instruments to be used to measure DLB globally., Competing Interests: No competing interests were disclosed., (Copyright: © 2022 Grycuk E et al.)

Background: Prolonged past exposure to secondhand tobacco smoke (SHS) in never-smokers is associated with abnormal lung function and reduced diffusing capacity suggestive of an associated lung tissue injury and damage. The mechanisms by which past SHS exposure may contribute to lung tissue damage are unknown. Elastin is a major constituent of extracellular matrix in lung parenchyma., Objective: To determine whether past exposure to SHS is associated with ongoing lung tissue damage as indicated by elevated elastin degradation products that are linked to lung function., Methods: We measured the plasma levels of elastin degradation markers (EDM) from 193 never-smoking flight attendants with a history of remote SHS exposure in aircraft cabins and 103 nonsmoking flight attendants or sea-level control participants without such history of cabin SHS exposure and examined those levels versus their lung function with adjustment for covariates. The cabin SHS exposure was estimated based on airline employment history and years of the smoking ban enactment., Results: The median [interquartile range] plasma EDM level for all participants was 0.30 [0.24-0.36] ng/mL with a total range of 0.16-0.65 ng/mL. Plasma EDM levels were elevated in those with a history of exposure to cabin SHS compared to those not exposed (0.33±0.08 versus 0.26±0.06 ng/mL; age- and sex-adjusted P <0.001). In those with a history of cabin SHS exposure, higher EDM levels were associated with a lower diffusing capacity (parameter estimate [PE] 95% [confidence interval(CI)]=4.2 [0.4-8.0] %predicted decrease per 0.1 ng/mL increase in EDM; P =0.030). Furthermore, EDM levels were inversely associated with forced expiratory volume in 1 second (FEV 1 ), FEV 1 to forced vital capacity (FVC) ratio , and forced expiratory flow rate between 25% and 75% ( FEF 25%-75% ) (PE [95%CI]=5.8 [2.1-9.4], 4.0 [2.2-5.7], and 12.5 [5.8-19.2] %predicted decrease per 0.1 ng/mL increase in EDM, respectively; P <0.001). Plasma EDM mediated a substantial fraction of the association of SHS with FEV 1 , FVC, and FEF 25%-75% ( P <0.05)., Conclusions: Long after past exposure to SHS, there is ongoing elastin degradation beyond what is expected from the aging process, which likely contributes to lower lung function and a reduced pulmonary capillary bed as seen in chronic obstructive pulmonary disease (COPD)., (JCOPDF © 2022.)

Low levels of high density lipoprotein-cholesterol (HDL-C) are associated with an elevated risk of arteriosclerotic coronary heart disease. Heritability of HDL-C levels is high. In this research discovery study, we used whole-exome sequencing to identify damaging gene variants that may play significant roles in determining HDL-C levels. We studied 204 individuals with a mean HDL-C level of 27.8 ± 6.4 mg/dl (range: 4-36 mg/dl). Data were analyzed by statistical gene burden testing and by filtering against candidate gene lists. We found 120 occurrences of probably damaging variants (116 heterozygous; four homozygous) among 45 of 104 recognized HDL candidate genes. Those with the highest prevalence of damaging variants were ABCA1 (n = 20), STAB1 (n = 9), OSBPL1A (n = 8), CPS1 (n = 8), CD36 (n = 7), LRP1 (n = 6), ABCA8 (n = 6), GOT2 (n = 5), AMPD3 (n = 5), WWOX (n = 4), and IRS1 (n = 4). Binomial analysis for damaging missense or loss-of-function variants identified the ABCA1 and LDLR genes at genome-wide significance. In conclusion, whole-exome sequencing of individuals with low HDL-C showed the burden of damaging rare variants in the ABCA1 and LDLR genes is particularly high and revealed numerous occurrences in HDL candidate genes, including many genes identified in genome-wide association study reports. Many of these genes are involved in cancer biology, which accords with epidemiologic findings of the association of HDL deficiency with increased risk of cancer, thus presenting a new area of interest in HDL genomics., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Smoking is a major cause of cardiac and pulmonary disease, cancer, and other inflammation related diseases. Smoking impairs lipid and lipoprotein metabolism. The observed modification and reduction in levels of HDL in smokers has adverse effects on atheroprotective properties. It has been hypothesized that HDL transports inflammatory cytokines which accelerate tobacco-related diseases. To investigate the role of HDL in the transport of inflammatory cytokines and their detrimental effects on the immune response, it is paramount to compare cytokine levels in HDL for Smoker versus Nonsmoker groups. We isolated HDL from plasma using selected affinity immunosorption of apolipoprotein A-I-bearing lipoproteins, followed by quantitative ELISA of cytokines. We implemented a powerful stacked ensemble Machine Learning algorithm, namely Super Learner (SL) with base-learners: Decision Tree classifier, AdaBoost classifier, Bagging classifier, Extra Tree classifier, Logistic Regression and Random Forest classifier and meta learner: Logistic Regression. Prediction Accuracy metric was used to ascertain the separability efficacy of Smoker versus Nonsmoker based on cytokine levels. Super Learner composed of a Logistic Regression meta learner, achieved a 100% prediction accuracy, outperforming all the base learners. Machine learning-enabled Precision Medicine allows the investigation of the role of novel biomarkers such as HDL-transported cytokines which have a potential to generate valuable molecular insights. The discovery that cytokines are transported by HDL presents a new dimension in understanding inflammatory disorders and the potential for therapeutic intervention. The outstanding classification and prediction performance of Ensemble learning can be leveraged to revolutionize the biomarker discoveries, enabling insight that can lead to novel treatment modalities., Competing Interests: Competing interests The authors report no conflicts of interest.

Presently, the role of cytokines in severe illness like COPD, cancer, cardiac disease associated with smoking is being explored to enable preemptive diagnosis and delivery of treatment interventions. We are investigating the connection between the elevation of inflammatory plasma cytokine in smokers versus nonsmokers. Disease indicator cytokines can be used to monitor the progression of disease which can help in the crucial task of prognosis and definitive diagnosis. Powerful and versatile Machine Learning algorithms can be leveraged to extract insights that cannot be obtained manually. We have applied Support Vector Machine (SVM) on 65 plasma cytokines and other traditional biomarkers to differentiate smokers and nonsmokers. To optimize the classification separability, we have used the following techniques: Principal component analysis (PCA), 10-fold cross validation and variable importance. The primary metric of evaluation is Area Under Receiver Operating Curve (AUROC), though we have additionally recorded and compared prediction accuracy across classifiers. The results are very promising. The AUROC classification accuracy achieved by SVM using the selected predictor feature variables is 89.2% with a 95%CI (85.4%,93.1%). The most prominent cytokines, contributing to the classification, in the order of importance are: I-TAC, Age, TG, G-CSF-CSF-3, MDC-CCL22, Eotaxin-3, LIF, IL-2, Eotaxin-2, MIP-3alpha. The AUROC classification accuracy improved to 93% with a 95% CI (90.1%,99.5%) upon choosing the five most prominent cytokines. The versatile prowess of Machine Learning algorithms such as Support Vector Machine can translate pioneering molecular discoveries into actionable insights that can be applied in the field of translational and precision medicine to save life., Competing Interests: Competing interests The authors report no conflicts of interest.

Diabetes mellitus is a complex disease. We are increasingly gaining a better understanding of its mechanisms at the molecular level. From these new insights, better therapeutic approaches should emerge. Diabetes mellitus is a syndrome with many associated subphenotypes. These include mitochondrial disorders, lipodystrophies, and inflammatory disorders involving cytokines. Levels of sphingosine-1-phosphate, which has recently been shown to play a role in glucose homeostasis, are low in diabetics, whereas levels of ceramides are increased. Major phenotypes associated with diabetes mellitus are dyslipidemias, notably hypertriglyceridemia and low high-density lipoprotein cholesterol levels. Both diabetes and dyslipidemia are strongly associated with increased risk for atherosclerotic vascular disease., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: As per the 2017 WHO fact sheet, Coronary Artery Disease (CAD) is the primary cause of death in the world, and accounts for 31% of total fatalities. The unprecedented 17.6 million deaths caused by CAD in 2016 underscores the urgent need to facilitate proactive and accelerated pre-emptive diagnosis. The innovative and emerging Machine Learning (ML) techniques can be leveraged to facilitate early detection of CAD which is a crucial factor in saving lives. The standard techniques like angiography, that provide reliable evidence are invasive and typically expensive and risky. In contrast, ML model generated diagnosis is non-invasive, fast, accurate and affordable. Therefore, ML algorithms can be used as a supplement or precursor to the conventional methods. This research demonstrates the implementation and comparative analysis of K Nearest Neighbor (k-NN) and Random Forest ML algorithms to achieve a targeted "At Risk" CAD classification using an emerging set of 35 cytokine biomarkers that are strongly indicative predictive variables that can be potential targets for therapy. To ensure better generalizability, mechanisms such as data balancing, repeated k-fold cross validation for hyperparameter tuning, were integrated within the models. To determine the separability efficacy of "At Risk" CAD versus Control achieved by the models, Area under Receiver Operating Characteristic (AUROC) metric is used which discriminates the classes by exhibiting tradeoff between the false positive and true positive rates., Results: A total of 2 classifiers were developed, both built using 35 cytokine predictive features. The best AUROC score of .99 with a 95% Confidence Interval (CI) (.982,.999) was achieved by the Random Forest classifier using 35 cytokine biomarkers. The second-best AUROC score of .954 with a 95% Confidence Interval (.929,.979) was achieved by the k-NN model using 35 cytokines. A p-value of less than 7.481e-10 obtained by an independent t-test validated that Random Forest classifier was significantly better than the k-NN classifier with regards to the AUROC score. Presently, as large-scale efforts are gaining momentum to enable early, fast, reliable, affordable, and accessible detection of individuals at risk for CAD, the application of powerful ML algorithms can be leveraged as a supplement to conventional methods such as angiography. Early detection can be further improved by incorporating 65 novel and sensitive cytokine biomarkers. Investigation of the emerging role of cytokines in CAD can materially enhance the detection of risk and the discovery of mechanisms of disease that can lead to new therapeutic modalities.

Background We previously showed that levels of prebeta-1 high-density lipoprotein (HDL), the principal acceptor of cholesterol effluxed from cells, including artery wall macrophages, are positively associated with coronary heart disease (CHD) and myocardial infarction (MI) risk. Methods and Results In a multiethnic follow-up cohort of 1249 individuals from University of California-San Francisco clinics, we determined the degree to which prebeta-1 HDL levels, both absolute and percentage of apolipoprotein AI, are associated with CHD and history of MI. Independent, strong, positive associations were found. Meta-analysis revealed for the absolute prebeta-1 HDL for the top tertile versus the lowest, unadjusted odds ratios of 1.90 (95% CI, 1.40-2.58) for CHD and 1.79 (95% CI, 1.35-2.36) for MI. For CHD, adjusting for established risk factors, the top versus bottom tertiles, quintiles, and deciles yielded sizable odds ratios of 2.37 (95% CI, 1.74-3.25, P <0.001), 3.20 (95% CI, 2.07-4.94, P <0.001), and 4.00 (95% CI, 2.11-7.58, P <0.001), respectively. Men and women were analyzed separately in a combined data set of 2507 individuals. The odds ratios for CHD and MI risk were similar. Higher levels of prebeta-1 HDL were associated with all 5 metabolic syndrome features. Addition of prebeta-1 HDL to these 5 features resulted in significant improvements in risk-prediction models. Conclusions Analysis of 2507 subjects showed conclusively that levels of prebeta-1 HDL are strongly associated with a history of CHD or MI, independently of traditional risk factors. Addition of prebeta-1 HDL can significantly improve clinical assessment of risk of CHD and MI.

Background: Susceptibility to severe hypertriglyceridemia (HTG), defined as plasma triglyceride (TG) levels ≥10 mmol/L (880 mg/dL), is conferred by both heterozygous rare variants in five genes involved in TG metabolism and numerous common single-nucleotide polymorphisms (SNPs) associated with TG levels., Objective: To date, these genetic susceptibility factors have been comprehensively assessed primarily in severe HTG patients of European ancestry. Here, we expand our analysis to HTG patients of East Asian and Hispanic ancestry., Methods: The genomic DNA of 336, 63 and 199 severe HTG patients of European, East Asian and Hispanic ancestry, respectively, was evaluated using a targeted next-generation sequencing panel to screen for: 1) rare variants in LPL, APOA5, APOC2, GPIHBP1 and LMF1; 2) common, small-to-moderate effect SNPs, quantified using a polygenic score; and 3) common, large-effect polymorphisms, APOA5 p.G185C and p.S19W., Results: While the proportion of individuals with high polygenic scores was similar, frequency of rare variant carriers varied across ancestries. Compared with ancestry-matched controls, Hispanic patients were the most likely to have a rare variant (OR = 5.02; 95% CI 3.07-8.21; p < 0.001), while European patients were the least likely (OR = 2.56; 95% CI 1.58-4.13; p < 0.001). The APOA5 p.G185C polymorphism, exclusive to East Asians, was significantly enriched in patients compared with controls (OR = 10.1; 95% CI 5.6-18.3; p < 0.001), showing the highest enrichment among the measured genetic factors., Conclusion: While TG-associated rare variants and common SNPs are both found in statistical excess in severe HTG patients of different ancestral backgrounds, the overall genetic profiles of each ancestry group were distinct., (Copyright © 2020 National Lipid Association. Published by Elsevier Inc. All rights reserved.)

Objective: Genetic determinants of severe hypertriglyceridemia include both common variants with small effects (assessed using polygenic risk scores) plus heterozygous and homozygous rare variants in canonical genes directly affecting triglyceride metabolism. Here, we broadened our scope to detect associations with rare loss-of-function variants in genes affecting noncanonical pathways, including those known to affect triglyceride metabolism indirectly. Approach and Results: From targeted next-generation sequencing of 69 metabolism-related genes in 265 patients of European descent with severe hypertriglyceridemia (≥10 mmol/L or ≥885 mg/dL) and 477 normolipidemic controls, we focused on the association of rare heterozygous loss-of-function variants in individual genes. We observed that compared with controls, severe hypertriglyceridemia patients were 20.2× (95% CI, 1.11-366.1; P =0.03) more likely than controls to carry a rare loss-of-function variant in CREB3L3 , which encodes a transcription factor that regulates several target genes with roles in triglyceride metabolism., Conclusions: Our findings indicate that rare variants in a noncanonical gene for triglyceride metabolism, namely CREB3L3 , contribute significantly to severe hypertriglyceridemia. Secondary genes and pathways should be considered when evaluating the genetic architecture of this complex trait.

Elevated levels of triglyceride-rich lipoproteins (TRLs), both fasting and postprandial, are associated with increased risk for atherosclerosis. However, guidelines for treatment are defined solely by fasting lipid levels, even though postprandial lipids may be more informative. In the postprandial state, circulating lipids consist of dietary fat transported from the intestine in chylomicrons (CMs; containing ApoB48) and fat transported from the liver in VLDL (containing ApoB100). Research into the roles of endogenous versus dietary fat has been hindered because of the difficulty in separating these particles by ultracentrifugation. CM fractions have considerable contamination from VLDL (purity, 10%). To separate CMs from VLDL, we produced polyclonal antibodies against ApoB100 and generated immunoaffinity columns. TRLs isolated by ultracentrifugation of plasma were applied to these columns, and highly purified CMs were collected (purity, 90-94%). Overall eight healthy unmedicated adult volunteers (BMI, 27.2 ± 1.4 kg/m 2 ; fasting triacylglycerol, 102.6 ± 19.5 mg/dl) participated in a feeding study, which contained an oral stable-isotope tracer (1- 13 C acetate). We then used this technique on plasma samples freshly collected during an 8 h human feeding study from a subset of four subjects. We analyzed fractionated lipoproteins by Western blot, isolated and derivatized triacylglycerols, and calculated fractional de novo lipogenesis. The results demonstrated effective separation of postprandial lipoproteins and substantially improved purity compared with ultracentrifugation protocols, using the immunoaffinity method. This method can be used to better delineate the role of dietary sugar and fat on postprandial lipids in cardiovascular risk and explore the potential role of CM remnants in atherosclerosis., (Copyright © 2020 Jones et al.)

Background: Homozygous Familial Hypercholesterolemia (HoFH) is an inherited recessive condition associated with extremely high levels of low-density lipoprotein (LDL) cholesterol in affected individuals. It is usually caused by homozygous or compound heterozygous functional mutations in the LDL receptor (LDLR). A number of mutations causing FH have been reported in literature and such genetic heterogeneity presents great challenges for disease diagnosis., Objective: We aim to determine the likely genetic defects responsible for three cases of pediatric HoFH in two kindreds., Methods: We applied whole exome sequencing (WES) on the two probands to determine the likely functional variants among candidate FH genes. We additionally applied 10x Genomics (10xG) Linked-Reads whole genome sequencing (WGS) on one of the kindreds to identify potentially deleterious structural variants (SVs) underlying HoFH. A PCR-based screening assay was also established to detect the LDLR structural variant in a cohort of 641 patients with elevated LDL., Results: In the Caucasian kindred, the FH homozygosity can be attributed to two compound heterozygous LDLR damaging variants, an exon 12 p.G592E missense mutation and a novel 3kb exon 1 deletion. By analyzing the 10xG phased data, we ascertained that this deletion allele was most likely to have originated from a Russian ancestor. In the Mexican kindred, the strikingly elevated LDL cholesterol level can be attributed to a homozygous frameshift LDLR variant p.E113fs., Conclusions: While the application of WES can provide a cost-effective way of identifying the genetic causes of FH, it often lacks sensitivity for detecting structural variants. Our finding of the LDLR exon 1 deletion highlights the broader utility of Linked-Read WGS in detecting SVs in the clinical setting, especially when HoFH patients remain undiagnosed after WES., (© 2019 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.)

Severe hypertriglyceridemia (HTG) is a relatively common form of dyslipidemia with a complex pathophysiology and serious health complications. HTG can develop in the presence of rare genetic factors disrupting genes involved in the triglyceride (TG) metabolic pathway, including large-scale copy-number variants (CNVs). Improvements in next-generation sequencing technologies and bioinformatic analyses have better allowed assessment of CNVs as possible causes of or contributors to severe HTG. We screened targeted sequencing data of 632 patients with severe HTG and identified partial deletions of the LPL gene, encoding the central enzyme involved in the metabolism of TG-rich lipoproteins, in four individuals (0.63%). We confirmed the genomic breakpoints in each patient with Sanger sequencing. Three patients carried an identical heterozygous deletion spanning the 5' untranslated region (UTR) to LPL exon 2, and one patient carried a heterozygous deletion spanning the 5'UTR to LPL exon 1. All four heterozygous CNV carriers were determined to have multifactorial severe HTG. The predicted null nature of our identified LPL deletions may contribute to relatively higher TG levels and a more severe clinical phenotype than other forms of genetic variation associated with the disease, particularly in the polygenic state. The identification of novel CNVs in patients with severe HTG suggests that methods for CNV detection should be included in the diagnostic workup and molecular genetic evaluation of patients with high TG levels., (Copyright © 2019 Dron et al.)

Background: Hypertriglyceridemia (HTG) is a complex trait defined by elevated plasma triglyceride levels. Genetic determinants of HTG have so far been examined in a piecemeal manner; understanding of its molecular basis, both monogenic and polygenic, is thus incomplete., Objective: The objective of this study was to characterize genetic profiles of patients with severe HTG, and quantify the genetic determinants and molecular contributors., Methods: We concurrently assessed rare and common variants in two independent cohorts of 251 and 312 Caucasian patients with severe HTG. DNA was subjected to targeted next-generation sequencing of 73 genes and 185 SNPs associated with dyslipidemia. LPL, APOC2, GPIHBP1, APOA5, and LMF1 genes were screened for rare variants, and a polygenic risk score was used to assess the accumulation of common variants., Results: As there were no significant differences in the prevalence of genetic determinants between cohorts, data were combined for all 563 patients: 1.1% had biallelic (homozygous or compound heterozygous) rare variants, 14.4% had heterozygous rare variants, 32.0% had an extreme accumulation of common variants (ie, high polygenic risk), and 52.6% remained genetically undefined. Patients with HTG were 5.77 times (95% CI [4.26-7.82]; P < .0001) more likely to carry one of these types of genetic susceptibility compared with controls., Conclusions: We report the most in-depth, systematic evaluation of genetic determinants of severe HTG to date. The predominant feature was an extreme accumulation of common variants (high polygenic risk score), whereas a substantial proportion of patients also carried heterozygous rare variants. Overall, 46.3% of patients had polygenic HTG, whereas only 1.1% had biallelic or homozygous monogenic HTG., (Copyright © 2018 National Lipid Association. Published by Elsevier Inc. All rights reserved.)

Atrial fibrillation (AF) affects more than 33 million individuals worldwide 1 and has a complex heritability 2 . We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.

Background: Prebeta-1 high-density lipoprotein (HDL) is a small subspecies of HDL that functions as the HDL quantum particle and is the principal acceptor of cholesterol effluxed from macrophages through the ATP-binding cassette transporter, ABCA1. High levels of prebeta-1 HDL are associated with increased risk of structural coronary artery disease and myocardial infarction., Objective: We aimed to compare prebeta-1 HDL levels in normal subjects and in 3 phenotypes of dyslipidemia., Methods: We studied 2435 individuals (1388 women; 1047 men). Of these, 2018 were not taking lipid-lowering medication when enrolled: 392 were normolipidemic controls; 713 had elevated levels of low-density lipoprotein cholesterol; 623 had combined hyperlipidemia; and 290 had hypertriglyceridemia., Results: Relative to controls, prebeta-1 HDL levels were increased in all 3 dyslipidemic phenotypes, particularly the combined and hypertriglyceridemia groups. This increase possibly reflects increased acceptor capacity of apolipoprotein B-100 containing lipoproteins for entropically driven transfer of cholesteryl esters from HDL via cholesteryl ester transfer protein. Multiple regression analysis revealed that the main predictor variables significantly associated with prebeta-1 HDL levels were apolipoprotein A-I (apoA-1) (β = 0.500), triglyceride (β = 0.285), HDL-C (β = -0.237), and age (β = -0.169). There was an interaction between apoA-1 and sex (female vs male; β = -0.110). Among postmenopausal women, estrogenized subjects had a similar level of prebeta-1 HDL compared to those not receiving estrogens., Conclusions: Prebeta-1 HDL levels are elevated in the 3 most common types of hyperlipidemia and are most strongly influenced by the levels of apoA-1, triglyceride, and HDL-C., (Copyright © 2017 National Lipid Association. Published by Elsevier Inc. All rights reserved.)

Background: Elevated plasma levels of prebeta-1 high-density lipoprotein (HDL), the principal acceptor of cholesterol effluxed from macrophages, are associated with increased risk of atherosclerotic coronary heart disease and myocardial infarction., Objective: The objective of the study was to assess the effects on prebeta-1 HDL levels of 6-week moderate-dose statin treatment., Methods: We studied 101 patients (mean age 52.7 years; 53.5% female; 63 with primary hypercholesterolemia; 38 with combined hyperlipidemia) before and after treatment with statins. Mean atorvastatin potency equivalence was 23.6 mg/d. Prebeta-1 HDL plasma levels were measured by immunofixation of agarose gels using anti-apolipoprotein A-1 antibody., Results: We observed a 42.0% reduction of low-density lipoprotein cholesterol (181 ± 56 vs 105 mg/dL, P < .001). Triglyceride (TG) levels decreased by 22.3% (157 vs 122 mg/dL, P < .001), HDL cholesterol levels remained similar (56.0 vs 57.1, P = NS). Levels of prebeta-1 HDL were significantly reduced by 17.9% after statin treatment (mean 11.4 vs 9.4 mg apoA-1/dL, P < .001). The magnitude of this decrease was similar with each of 3 statins (atorvastatin, simvastatin, and rosuvastatin). The decrease in prebeta-1 HDL was strongly associated with the decline in TG, but not with the decline in low-density lipoprotein cholesterol., Conclusions: The association of high prebeta-1 HDL with coronary heart disease identifies it as an inferential measure of the rate of cholesterol efflux from the artery wall. Our observations demonstrate a reduction of prebeta-1 HDL with statin therapy, partially reflecting the reduced TGs, and probably reflecting a direct beneficial impact on cholesterol efflux., (Copyright © 2017 National Lipid Association. Published by Elsevier Inc. All rights reserved.)

Lipoprotein lipase (LPL) is responsible for the hydrolysis of triglycerides from circulating lipoproteins. Whereas most identified mutations in the LPL gene are deleterious, one mutation, LPL S447X , causes a gain of function. This mutation truncates two amino acids from LPL's C-terminus. Carriers of LPL S447X have decreased VLDL levels and increased HDL levels, a cardioprotective phenotype. LPL S447X is used in Alipogene tiparvovec, the gene therapy product for individuals with familial LPL deficiency. It is unclear why LPL S447X results in a serum lipid profile more favorable than that of LPL. In vitro reports vary as to whether LPL S447X is more active than LPL. We report a comprehensive, biochemical comparison of purified LPL S447X and LPL dimers. We found no difference in specific activity on synthetic and natural substrates. We also did not observe a difference in the K i for ANGPTL4 inhibition of LPL S447X relative to that of LPL. Finally, we analyzed LPL-mediated uptake of fluorescently labeled lipoprotein particles and found that LPL S447X enhanced lipoprotein uptake to a greater degree than LPL did. An LPL structural model suggests that the LPL S447X truncation exposes residues implicated in LPL binding to uptake receptors.

Background: Coronary heart disease (CHD) risk inversely associates with levels of high-density lipoprotein cholesterol (HDL-C). The protective effect of HDL is thought to depend on its functionality, such as its ability to induce cholesterol efflux., Materials and Methods: We compared plasma cholesterol efflux capacity between male familial hypercholesterolaemia (FH) patients with and without CHD relative to their non-FH brothers, and examined HDL constituents including sphingosine-1-phosphate (S1P) and its carrier apolipoprotein M (apoM)., Results: Seven FH patients were asymptomatic and six had experienced a cardiac event at a mean age of 39 years. Compared to their non-FH brothers, cholesterol efflux from macrophages to plasma from the FH patients without CHD was 16 ± 22% (mean ± SD) higher and to plasma from the FH patients with CHD was 7 ± 8% lower (P = 0·03, CHD vs. non-CHD). Compared to their non-FH brothers, FH patients without CHD displayed significantly higher levels of HDL-cholesterol, HDL-S1P and apoM, while FH patients with CHD displayed lower levels than their non-FH brothers., Conclusions: A higher plasma cholesterol efflux capacity and higher S1P and apoM content of HDL in asymptomatic FH patients may play a role in their apparent protection from premature CHD., (© 2016 The Authors. European Journal of Clinical Investigation published by John Wiley & Sons Ltd on behalf of Stichting European Society for Clinical Investigation Journal Foundation.)

Background: Potent cholesteryl ester transfer protein (CETP) inhibitors have been shown to substantially increase high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A-I levels as monotherapy and combined with statins. However, data on the effects of this class of drugs on macrophage cholesterol efflux capacity (CEC), a functional assay that characterizes a key step in the process of reverse cholesterol transport, are limited., Objectives: This study assessed the impact of evacetrapib, statins, or combination therapy on CEC., Methods: We analyzed samples from 377 subjects with elevated low-density lipoprotein cholesterol (LDL-C) or low HDL-C levels who were enrolled in a phase 2 trial of evacetrapib. Percent changes from baseline in CEC (total, non-ABCA1-, and ABCA1-specific) and HDL subpopulations were evaluated after 12 weeks of treatment with placebo, statin monotherapy, evacetrapib monotherapy, or evacetrapib combined with statins. Pre-beta-1 HDL levels were quantified by immunofixation and nondenaturing 2-dimensional gel electrophoresis (2DGE)., Results: Relative to placebo, evacetrapib monotherapy increased dose-dependent total and non-ABCA1-specific CEC up to 34% and 47%, respectively. Evacetrapib monotherapy also increased ABCA1-specific CEC up to 26%. Relative to statin monotherapy, evacetrapib with statins also increased total, non-ABCA1-, and ABCA1-specific CEC by 21%, 27%, and 15%, respectively. In contrast, rosuvastatin and simvastatin significantly reduced total and ABCA1-specific CEC, whereas atorvastatin had no significant effect. Consistent with ABCA1-specific CEC, evacetrapib monotherapy and evacetrapib combined with statins significantly increased pre-beta-1 HDL levels as measured by either method., Conclusions: Evacetrapib, as monotherapy and combined with statins, not only increased total CEC, but also increased ABCA1-specific CEC and pre-beta-1 HDL. The mechanisms by which potent CETP inhibition increases ABCA1-specific CEC and pre-beta-1 HDL require further study. (A Study of LY2484595 in Patients With High LDL-C or Low HDL-C; NCT01105975)., (Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)