Low “quotient” Lp(a) Concentration Mediates Autoimmune Activation and Independently Predicts Cardiometabolic Risk

Onat, Altan; Çoban, Neslihan; Can, Giinay; Yüksel, Murat; Karagöz, Ahmet; Yüksel, Hüsniye; Ademoğlu, Evin; Erginel-Unaltuna, Nihan

doi:10.1055/s-0034-1385922

Cited by 18 publications

(26 citation statements)

References 29 publications

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“…By adjusting the Lp(a) concentration for the effects of the LPA rs10455872 A>G polymorphism, age, gender, total cholesterol, and fasting insulin, we estimated the expected Lp(a) concentration in each of the 1669 participants to determine the quotient between observed and expected Lp(a) values. Cox regression models (also comprising smoking status, systolic pressure, and serum HDL-cholesterol) disclosed that, compared with the mid-tertile, both low and high Lp(a) quotient tertiles significantly predicted incident CHD, especially in women, after 5.1 years of follow-up 20. This was consistent with the notion that ‘low’ serum Lp(a) reflects autoimmune activation 9.…”

Section: Introductionsupporting

confidence: 78%

Lipoprotein(A) Level and Mif Gene Variant Predict Incident Metabolic Syndrome and Mortality

Onat

Can

Çoban

et al. 2016

Journal of Investigative Medicine

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Owing to the scarcity of available information, we aimed to assess the association of migration inhibitory factor (MIF)-173 G/C genotypes and serum lipoprotein(Lp)(a) with incident metabolic syndrome (MetS) and all-cause mortality, respectively. In population based, middle-aged adults (n=1297), stratified by gender and presence of MetS, we used Lp(a) quintiles to identify non-linear associations with outcomes using Cox regression models, adjusted for MIF genotype, age, smoking status, high density lipoprotein cholesterol, and systolic blood pressure. After 5.2 years of follow-up, 151 cases of incident MetS and 123 deaths were recorded. For incident MetS, adjusted HRs increased in each gender across four declining quintiles, starting from the highest quintile in men and from quintile 4 in women. The MIF CC-GC genotype appeared to contribute to the risk estimates in men. Similarly adjusted models in the whole sample disclosed that all-cause mortality tended to be inversely associated with Lp(a) quintiles and yielded an HR (2.42 (95% CI 1.03 to 5.81)) in men in quintile 2, whereas the MIF genotype additively predicted mortality (HR 1.79 (95% CI 1.01 to 3.18)) only in men. Excess risk of death was additively conferred on Turkish men by the MIF CC-GC genotype and by apparently reduced circulating Lp(a) assays, supporting the notion that 'low' serum Lp(a), mediating autoimmune activation, is a major determinant of metabolic disease risk and death. Damaged MIF protein and more complex autoimmune activation in women may be responsible from lack of relationship to MetS/mortality.

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Section: Introductionsupporting

confidence: 78%

Lipoprotein(A) Level and Mif Gene Variant Predict Incident Metabolic Syndrome and Mortality

Onat

Can

Çoban

et al. 2016

Journal of Investigative Medicine

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“…If oxidation of Lp(a) is also reduced by bilirubin, the apparent Lp(a) concentration will not be decreased subsequently. Onat A et al reported that Lp(a) was positively associated with total cholesterol, and negatively associated with fasting insulin [26]. The directions of the correlation of Lp(a) with these variables seem to be in concordance with those of baseline bilirubin.…”

Section: Discussionmentioning

confidence: 78%

“…We speculate that these findings may support the idea that changes in lipoprotein[Lp](a) might be related to the underlying mechanism. Lp(a) mediates systemic inflammatory process and endothelial dysfunction, and acts as one of the cardiovascular risk factors, and it utilizes atherogenic and prothrombotic pathways [26,27]. Bilirubin exerts antioxidant activity on low-density lipoprotein [17,28,29].…”

Section: Discussionmentioning

confidence: 99%

Change in Serum Bilirubin Level as a Predictor of Incident Metabolic Syndrome

Lee

Jun

et al. 2016

PLoS ONE

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AimSerum bilirubin level was negatively associated with the prevalence of metabolic syndrome (MetS) in previous cross-sectional studies. However, bilirubin variance preceding the development of MetS has yet to be investigated. We aimed to determine the effect of change in bilirubin concentration on the risk of incident MetS in healthy Korean adults.MethodsWe conducted a retrospective longitudinal study of subjects who had undergone at least four yearly health check-ups between 2006 and 2012. Of 24,185 total individuals who received annual check-ups, 11,613 non-MetS participants with a baseline bilirubin level not exceeding 34.2 μmol/l were enrolled. We evaluated the association between percent change in bilirubin and risk of incident MetS.ResultsDuring 55,407 person-years of follow-up, 2,439 cases of incident MetS developed (21.0%). Baseline serum bilirubin level clearly showed no association with the development of MetS in men but an independent significant inverse association in women which attenuated (hence may be mediated) by elevated homeostatic model assessment index 2 for insulin resistance (HOMA2-IR). However, increased risk for incident MetS was observed in higher percent change in bilirubin quartiles, with hazard ratios of 2.415 (95% CI 2.094–2.785) in men and 2.156 (95% CI 1.738–2.675) in women in the fourth quartile, compared to the lowest quartile, after adjusting for age, smoking status, medication history, alanine aminotransferase, uric acid, estimated glomerular filtration rate, fasting glucose, baseline diabetes mellitus prevalence, systolic blood pressure, waist circumference, and body mass index. The hazard ratios per one standard deviation increase in percent change in bilirubin as a continuous variable were 1.277 (95% CI 1.229–1.326) in men and 1.366 (95% CI 1.288–1.447) in women.ConclusionsIncreases in serum bilirubin concentration were positively associated with a higher risk of incident MetS. Serum bilirubin increment might be a sensitive marker for the development of MetS.

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“…Of interest is our finding that higher baseline LDL-cholesterol levels are associated with a reduced risk for 4-year incident diabetes as other diabetes risk models have not identified LDL-cholesterol as an independent predictor of diabetes [3,6,16]. Associations between LDL-cholesterol subfractions, e.g., lipoprotein (a), and risk for diabetes have been inconsistent [17,18]. However, lipid lowering with statin medications has been associated with increased diabetes risk in both epidemiological studies [19][20][21][22] and meta-analyses of prospective clinical trials [23][24][25].…”

Section: Discussionmentioning

confidence: 99%

Updated risk factors should be used to predict development of diabetes

Bethel

Hyland

Chacra

et al. 2017

Journal of Diabetes and its Complications

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Bethel, M. A. et al. (2017) Updated risk factors should be used to predict development of diabetes. Journal of Diabetes and its Complications, (doi:10.1016/j.jdiacomp.2017.02.012) This is the author's final accepted version.There may be differences between this version and the published version. You are advised to consult the publisher's version if you wish to cite from it.http://eprints.gla.ac.uk/139102/ Authors' ContributionsMAB and KH researched the data and drafted the manuscript. ARC, PD, GRF, RRH, TJ, NSL, JJVM, and EB reviewed the manuscript. SMH reviewed/edited the manuscript and contributed to the writing. LT and JLS analyzed and researched the data and contributed to the description of the statistical methods. MAB takes responsibility for the manuscript. All authors approved the final manuscript. FundingThe NAVIGATOR trial was funded by Novartis Pharmaceuticals. The sponsor had no involvement in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication. Conclusions:Using historical clinical values to calculate diabetes risk reduces the accuracy of prediction. Diabetes risk calculations should be routinely updated to inform discussions about diabetes prevention at both the patient and population health levels.

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Low “quotient” Lp(a) Concentration Mediates Autoimmune Activation and Independently Predicts Cardiometabolic Risk

Cited by 18 publications

References 29 publications

Lipoprotein(A) Level and Mif Gene Variant Predict Incident Metabolic Syndrome and Mortality

Lipoprotein(A) Level and Mif Gene Variant Predict Incident Metabolic Syndrome and Mortality

Change in Serum Bilirubin Level as a Predictor of Incident Metabolic Syndrome

Updated risk factors should be used to predict development of diabetes

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