Non-fasting Samples Research Articles

English

English

The role of biomarkers in predicting pre-eclampsia in high-risk women.

Background There are limited data on performance of biomarkers to predict pre-eclampsia (PE) in high-risk women. This study investigated the ability of FABP4, PAPP-A, PlGF, sFlt-1 and sEng to predict PE in a high-risk group. Methods Non-fasting samples were analysed at 11 + 0–13 + 6 (V1) and 19 + 0–21 + 6 weeks (V2) ( n = 195). Logistic regression models were determined. Area under (AUC) the receiver operating characteristic (ROC) curve analysis was performed. The added value of biomarkers to clinical characteristics for PE prediction was quantified using integrated discrimination improvement (IDI) and net reclassification improvement (NRI) indices. Results Prevalence of PE was 12%. Lower concentrations of sFlt-1:PlGF (V1) and PlGF and PlGF:sEng (V2) were seen in women who developed PE. Controlling for baseline characteristics (V1), a doubling of sFlt-1 (pg/mL) (median 896.0, IQR 725.5–1097.0) and sFlt-1:PlGF (median 21.2, IQR 14.7–32.3) was associated with reduction in odds of PE (OR 0.20, 95% CI 0.06–0.65, P = 0.007 and OR 0.48, 95% CI 0.25–0.92, P = 0.04). Addition of sFlt-1 and sFlt-1:PlGF to baseline characteristics non-significantly improved AUC (0.74) (AUC 0.77, P = 0.40 and 0.76, P = 0.39). NRI and IDI analyses confirmed added clinical utility of sFlt-1 (NRI = 0.539, P = 0.01 and IDI = 0.052, P = 0.03). In V2, doubling of PlGF:sEng (median 71.9, IQR 47.0–102.8) was associated with reduction in the risk of PE (OR 0.56, 95% CI 0.35–0.98, P = 0.04). The addition of PlGF:sEng to baseline characteristics non-significantly improved AUC from 0.78 to 0.82 ( P = 0.25) and improved reclassification of cases (NRI = 0.682, P = 0.002). Conclusions Screening tests incorporating first trimester sFlt-1 and second trimester PlGF:sEng have potential to aid PE prediction in high-risk pregnancies.

Iron deficiency in healthy 18-month-old Danish children is associated with no oral iron supplementation in infancy and prolonged exclusive breast-feeding.

Fe deficiency (ID) defined as plasma ferritin <12 µg/l is associated with delayed cognitive development in early childhood and increased incidence of infections; however, the longitudinal association between early-life factors and ID in 18-month-old children in Denmark is unknown. The present study aimed to determine the prevalence of ID and to describe risk factors associated with ID in healthy 18-month-old Danish children. Blood samples, anthropometric measurements and self-reported questionnaire data had been obtained in the birth cohort, Odense Child Cohort. The questionnaires were modified from those used in the Danish National Birth Cohort. Plasma ferritin and C-reactive protein in venous, non-fasting samples were analysed in the final sample size of 370 children after exclusion of seventy-nine children due to chronic disease, acute infection, C-reactive protein >10 mg/l, twin birth or prematurity. Associations with ID were analysed by logistic regression, adjusting for sex, maternal education, duration of partial breast-feeding and current intake of milk, fish and meat. Overall, fifty-six children had ID (15·1 %). Factors associated with increased risk were exclusive breast-feeding beyond 4 months (OR 5·97; 95 % CI 1·63, 21·86) and no intake of oral Fe supplements from 6 to 12 months (OR 3·99, 95 % CI 1·33, 11·97. Duration of partial breast-feeding and current diet was not associated with ID. In conclusion, the ID prevalence was 15·1 %, and both exclusive breast-feeding beyond 4 months and no intake of oral Fe supplements from 6 to 12 months were associated with increased risk of ID in 18-month-old children.

Quantitative Analysis of Lactate and Other Organic Acids in Plasma: Preanalytical Challenges

Abstract Background and Objectives We developed a gas chromatography–mass spectrometry (GC-MS) method for the analysis of organic acids (OAs) in plasma using liquid-liquid extraction with acidified methanol. This method allows for the simultaneous analysis of several metabolites associated with energy metabolism, including lactic and pyruvic acids. Here, we evaluated the effect of different preanalytical variables (anticoagulants, delayed plasma separation, fasting vs nonfasting status) on plasma organic acid quantitation. Methods Nine organic acids (lactic, pyruvic, 3-hydroxybutyric, acetoacetic, 2-ketoisovaleric, 2-keto-3-methylvaleric, 2-ketoisocaproic, succinic, and glutaric) were extracted by deproteinizing with acidified methanol, oximated to preserve ketoacids, converted to volatile trimethylsilyl derivatives, and detected by GC-MS. Compound identification was obtained by retention time and fragmentation spectra using Agilent MassHunter software. We performed several comparison studies using blood collected from self-reported healthy participants (24-60 years of age; 14 females, 13 males). The effect of fasting/nonfasting status was evaluated in 14 participants by comparing samples collected after overnight fasting and 4 hours after meal. Paired t test was used for the statistical analysis of results. Results When compared to the preferred sample type, sodium heparin (green top) plasma EDTA plasma (purple top, n = 9) and serum (red top or serum separator tube; n = 5) displayed an unacceptable variability for several analytes. The biggest differences were observed for lactic and pyruvic acids. Lactic acid was significantly lower in EDTA plasma (9%-35% decrease; P = .0001), but higher in serum (4%-63% increase; P = .014), while pyruvic acid was significantly higher in EDTA plasma (4%-145% increase; P = .0002). The measurements of lactic and pyruvic acids were also affected by delayed separation of plasma in samples kept at room temperature. We observed a marked increase in lactate and decrease in pyruvate levels (+42% and –43% mean change, respectively) in plasma separated from whole blood after 2 hours of collection compared to samples processed within 30 minutes. Plasma separated 1 hour postcollection was acceptable. Overnight fasting (12-14 hours) did not have a significant impact on ketones (3-hydroxybutyric and acetoacetic acids) or branched-chain ketoacids (2-keto-3-methylvaleric, 2-ketoisocaproic, 2-ketoisovaleric acids). In contrast, fasting samples displayed higher lactic acid concentrations compared to nonfasting samples (24% increase on average, P = .0072), although in most fasting samples (13 out of 14), lactate concentrations were still within established normal range (600-2,600 µmol/L). Conclusions We identified several preanalytical factors influencing plasma organic acid quantitation, particularly lactic and pyruvic acids. Since those are critical analytes, suggestive of primary or secondary metabolic acidosis, appropriate steps should be taken to ensure sample quality during collection and processing.

Nuclear Magnetic Resonance (NMR)–Based Serum Metabolic Profiles: Impact of Fasting Status

Abstract Introduction Measurement of lipoprotein subclass concentration (-c), particle number (-p), and size (-s) by nuclear magnetic resonance (NMR) has gained traction recently in the clinical laboratory due to associations between smaller lipid particle sizes and atherogenic risk, especially for LDL-p. Since patients may not comply with the clinician’s recommendation of fasting before sample collection, our objective was to evaluate the impact of fasting status on NMR-based lipid and amino acid determinations. Methods Fifty self-reported healthy participants were recruited using an internal review board-approved protocol: males (n = 25; 41.3 ± 10.5 years; BMI 27.7 ± 4.6 kg/m2) and females (n = 25; 35.6 ± 9.1 years; BMI 25.3 ± 5.4 kg/m2). Blood was collected after overnight fast and 4 hours after a high-fat meal. Samples were analyzed using the AXINON lipoFIT by NMR assay (Numares) with an Avance III NMR spectrometer and Ascend 600 MHz magnet (Bruker). This assay included measurements of triglycerides, total cholesterol, IDL-c, and LDL, HDL, VLDL concentrations; particle numbers; and sizes. Additionally, NMR-based glucose, alanine, valine, leucine, and isoleucine concentrations were acquired. Conventional lipid parameters were obtained using cobas 8000 chemistry system (Roche). Fasting and postprandial results were compared for significant differences. Results As expected, mean triglycerides increased after the meal (53%, P &lt; .0001). Increases were also observed for VLDL-c (22%, P &lt; .0001) and large VLDL-p (56%, P &lt; .0001), as well as LDL-s, HDL-s, and VLDL-s (all &lt;3.5%, P &lt; .005). In contrast, LDL-p, small LDL-p, large LDL-p, HDL-p, small HDL-p, glucose, total cholesterol, and LDL, HDL, and IDL cholesterols demonstrated at most an 11% decrease (all P &lt; .002). Valine, leucine, and isoleucine also increased after the meal (31%-46%, P &lt; .0001 for all). Differences in individual lipids or amino acids were not sufficient to distinguish between fasting vs postprandial states, although incorporation of valine into a ratio with VLDL-c and LDL cholesterol (Valine*VLDL-c/LDL cholesterol) provided adequate differentiation (ROC analysis: AUC 0.91 [SD 0.03, P &lt; .0001]). A cutoff of 75 for the ratio had a sensitivity of 88.9% (95% CI, 76.0%-96.3%) and specificity of 85.4% (95% CI, 72.2%-93.9%). Interference with NMR results occurred for three participants’ postprandial samples. These individuals had significantly higher fasting triglycerides, LDL-p, small LDL-p, large VLDL-p, VLDL-s, VLDL-c, IDL-c and lower LDL-s, and HDL-s compared to other participants. Conclusions The clinical impact on results from postprandial samples warrants further evaluation prior to accepting nonfasting samples for NMR analysis. Considering a subpar compliance with fasting, algorithms to differentiate fasting and postprandial specimens may be useful in identifying suboptimal specimens.

Associations of a metabolic syndrome severity score with coronary heart disease and diabetes in fasting vs. non-fasting individuals

Background and aimsMany traditional assessments of risk for coronary heart disease (CHD) and diabetes require laboratory studies performed after an 8-h fast. We assessed whether metabolic-syndrome (MetS) severity would remain linked to future CHD and diabetes even when assessed from non-fasting samples. Methods and resultsParticipants in the Atherosclerosis Risk in Communities study were assessed at 4 visits and followed for 20-years of adjudicated CHD outcomes. We used Cox proportional-hazard models (for 20-year CHD outcomes) and logistic regression (for 9-year diabetes outcomes) to compare incident disease risk associated with a race/ethnicity-specific MetS-severity Z-score (MetS-Z) calculated in participants who were fasting (≥8 h) or non-fasting. All analyses were adjusted for sex, race, education, income and smoking. MetS Z-scores were overall similar between participants who were always fasting vs. those non-fasting at Visits 1–3 (all values −0.1 to 0.4), while MetS-Z for participants who were non-fasting at Visit-4 were higher at each visit. Baseline MetS-Z was linked to future CHD when calculated from both fasting and non-fasting measurements, with hazard ratio (HR) for fasting MetS-Z 1.53 (95% confidence interval [CI] 1.42, 1.66) and for non-fasting 1.28 (CI 1.08, 1.51). MetS-Z at Visit-1 also remained linked to future diabetes when measured from non-fasting samples, with odds ratio for fasting MetS-Z 3.10 (CI 2.88, 3.35) and for non-fasting 1.92 (CI 1.05, 3.51). ConclusionsMetS-Z remained linked to future CHD and diabetes when assessed from non-fasting samples. A score such as this may allow for identification of at-risk individuals and serve as a motivation toward interventions to reduce risk.

Lipid management for coronary heart disease patients: an appraisal of updated international guidelines applying Appraisal of Guidelines for Research and Evaluation II-clinical practice guideline appraisal for lipid management in coronary heart disease.

Clinical practice guidelines (CPGs) provide many recommendations for hyperlipidemia management, but some of them are still debatable. We applied the six-domain Appraisal of Guidelines for Research and Evaluation II (AGREE II) instrument to evaluate the quality of guidelines with lipid management recommendations for coronary heart disease (CHD), including dyslipidemia and CHD guidelines published from 2009 to 2019. Meanwhile, we synthesized and compared major recommendations and present the consistency and controversy in current dyslipidemia management. Among 19 guidelines included, ten guidelines ("strongly recommended" with AGREE scores 61-94%) performed better than the other nine (38-65% as "recommended with some modification") For blood lipid tests, most CHD guidelines simply required fasting sample while dyslipidemia guidelines preferred non-fasting sample except in high triglycerides state. Most guidelines consistently chose low-density lipoprotein cholesterol (LDL-C) as the primary lipid-lowering target (LLT), while non-high-density lipoprotein cholesterol (non-HDL-C) and apolipoprotein B were mainly selected as secondary LLTs. The specific goals of LDL-C lowering were either to lower than 70 mg/dL or with at least 50% reduction. All guidelines recommended high intensity or maximally tolerable doses of statins, while ezetimibe and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors were recommended as second-line therapy. The general quality of guidelines for lipid management is satisfactory. Consensus has been reached on the specific goal of lipid reduction and the intensity of statins therapy. Further research is needed to validate the application of non-fasting sample and non-HDL-C target, as well as the efficacy and safety of ezetimibe and PCSK9 inhibitors.

Age-specific and sex-specific reference intervals for non-fasting lipids and apolipoproteins in 7260 healthy Chinese children and adolescents measured with an Olympus AU5400 analyser: a cross-sectional study

AimsEthnic, demographic, lifestyle, genetic and environmental factors influence lipids and apolipoproteins. The aim of this study was to establish age-specific and gender-specific reference intervals for non-fasting lipids and apolipoproteins in...

Postprandial Hypertriglyceridaemia Revisited in the Era of Non-Fasting Lipid Profile Testing: A 2019 Expert Panel Statement, Main Text.

Residual vascular risk exists despite the aggressive lowering of Low-Density Lipoprotein Cholesterol (LDL-C). A contributor to this residual risk may be elevated fasting, or non-fasting, levels of Triglyceride (TG)-rich lipoproteins. Therefore, there is a need to establish whethe a standardised Oral Fat Tolerance Test (OFTT) can improve atherosclerotic Cardiovascular (CV) Disease (ASCVD) risk prediction in addition to a fasting or non-fasting lipid profile. An expert panel considered the role of postprandial hypertriglyceridaemia (as represented by an OFTT) in predicting ASCVD. The panel updated its 2011 statement by considering new studies and various patient categories. The recommendations are based on expert opinion since no strict endpoint trials have been performed. Individuals with fasting TG concentration <1 mmol/L (89 mg/dL) commonly do not have an abnormal response to an OFTT. In contrast, those with fasting TG concentration ≥2 mmol/L (175 mg/dL) or nonfasting ≥2.3 mmol/L (200 mg/dL) will usually have an abnormal response. We recommend considering postprandial hypertriglyceridaemia testing when fasting TG concentrations and non-fasting TG concentrations are 1-2 mmol/L (89-175 mg/dL) and 1.3-2.3 mmol/L (115-200 mg/dL), respectively as an additional investigation for metabolic risk prediction along with other risk factors (obesity, current tobacco abuse, metabolic syndrome, hypertension, and diabetes mellitus). The panel proposes that an abnormal TG response to an OFTT (consisting of 75 g fat, 25 g carbohydrate and 10 g proteins) is >2.5 mmol/L (220 mg/dL). Postprandial hypertriglyceridaemia is an emerging factor that may contribute to residual CV risk. This possibility requires further research. A standardised OFTT will allow comparisons between investigational studies. We acknowledge that the OFTT will be mainly used for research to further clarify the role of TG in relation to CV risk. For routine practice, there is a considerable support for the use of a single non-fasting sample.

The effect of sampling procedures and day-to-day variations in metabolomics studies of biofluids

Metabolomics analysis of biofluids is a feasible tool for disease characterization and monitoring due to its minimally invasive nature. To reduce unwanted variation in biobanks and clinical studies, it is important to determine the effect of external factors on metabolic profiles of biofluids. In this study we examined the effect of sample collection and sample processing procedures on NMR measured serum lipoproteins and small-molecule metabolites in serum and urine, using a cohort of men diagnosed with either prostate cancer or benign prostatic hyperplasia. We determined day-to-day reliability of metabolites by systematic sample collection at two different days, in both fasting and non-fasting conditions. Study participants received prostate massage the first day to assess the differences between urine with and without prostate secretions. Further, metabolic differences between first-void and mid-stream urine samples, and the effect of centrifugation of urine samples before storage were assessed. Our results show that day-to-day reliability is highly variable between metabolites in both serum and urine, while lipoprotein subfractions possess high reliability. Further, fasting status clearly influenced the metabolite concentrations, demonstrating the importance of keeping this condition constant within a study cohort. Day-to-day reliabilities were however comparable in fasting and non-fasting samples. Urine sampling procedures such as sampling of first-void or mid-stream urine, and centrifugation or not before sample storage, were shown to only have minimal effect on the overall metabolic profile, and is thus unlikely to constitute a confounder in clinical studies utilizing NMR derived metabolomics.

The association between insomnia, c-reactive protein, and chronic low back pain: cross-sectional analysis of the HUNT study, Norway.

Chronic low back pain (chronic LBP) is the number one cause for years lived with disability among 301 diseases and injuries analyzed by The Global Burden of Disease study 2013. Insomnia is highly prevalent among people with chronic LBP. To explain the sleep-pain relationship, theoretical models propose that insomnia symptoms may be associated with increased basal inflammation, operationalized as c-reactive protein (CRP) and lead to further pain and disrupted sleep. We aimed to determine the associations between insomnia, chronic LBP, and inflammation (operationalized as CRP), whilst controlling for age, body mass index, smoking, physical activity, depression, anxiety and osteoarthritis. A cross-sectional analysis of the third Nord-Trøndelag Health Study (2006-2008), a rural population survey of 50,666 participants in Norway aged 20-96 years. Insomnia (dichotomous) was defined according to the Diagnostic and Statistical Manual of Mental Disorders 5th Edition, and chronic LBP (dichotomous) as low back pain or stiffness lasting at least 3 months. Data for CRP were obtained from non-fasting serum samples and assessed via latex immunoassay methodology. We excluded participants with the following self-reported chronic somatic diseases: chronic heart failure, chronic obstructive pulmonary disease, rheumatoid arthritis, fibromyalgia or ankylosing spondylosis. Possible associations between presence of insomnia and presence of chronic LBP (dependent), and the level of CRP and presence of chronic LBP (dependent), were assessed using logistic regression models. The possible association between insomnia and CRP (dependent) was assessed using linear regression. Multivariable analyses were conducted adjusting for confounders stated in our aim that achieved p ≤ 0.2 in univariate regressions. We performed stratified analyses for participants with "Normal" (<3 mg/L) "Elevated" (3-10 mg/L) and "Very High" (>10 mg/L) levels of CRP. In our total included sample (n = 30,669, median age 52.6, 54% female), 6.1% had insomnia (n = 1,871), 21.4% had chronic LBP (n = 6,559), and 2.4% had both (n = 719). Twenty four thousand two hundred eighty-eight (79%) participants had "Normal" CRP, 5,275 (17%) had "Elevated" CRP, and 1,136 (4%) had "Very High" CRP. For participants with "Normal" levels of CRP, insomnia was associated with higher levels of CRP (adjusted B = 0.04, 95%CI [0.00-0.08], p = 0.046), but not for people with "Elevated" or "Very High" levels of CRP. There was an association between CRP and presence of chronic LBP in the total sample (adjusted OR = 1.01, [1.00-1.01], p = 0.013) and for people with "Normal" CRP (1.05, [1.00-1.10, p = 0.034]. Insomnia was associated with the presence of chronic LBP in the total sample (adjusted OR = 1.99, 95%CI [1.79-2.21], <0.001) and for people with "Normal", "Elevated" and "Very High". Individuals with insomnia have twice the odds of reporting chronic LBP. Insomnia, CRP and chronic LBP appear to be linked but the role of CRP appears to be limited. Longitudinal studies may help further explore the causal inference between insomnia chronic LBP, and inflammation. Given the strong relationship between insomnia and chronic LBP, screening and management of comorbid insomnia and chronic LBP should be considered in clinical practice. Further longitudinal studies are required to explore whether the presence of insomnia and increased inflammation affects the development of chronic LBP.

Biomarker panels associated with progression of renal disease in type 1 diabetes

Aims/hypothesisWe aimed to identify a sparse panel of biomarkers for improving the prediction of renal disease progression in type 1 diabetes.MethodsWe considered 859 individuals recruited from the Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) and 315 individuals from the Finnish Diabetic Nephropathy (FinnDiane) study. All had an entry eGFR between 30 and 75 ml min−1[1.73 m]−2, with those from FinnDiane being oversampled for albuminuria. A total of 297 circulating biomarkers (30 proteins, 121 metabolites, 146 tryptic peptides) were measured in non-fasting serum samples using the Luminex platform and LC electrospray tandem MS (LC-MS/MS). We investigated associations with final eGFR adjusted for baseline eGFR and with rapid progression (a loss of more than 3 ml min−1[1.73 m]−2 year−1) using linear and logistic regression models. Panels of biomarkers were identified using a penalised Bayesian approach, and their performance was evaluated through 10-fold cross-validation and compared with using clinical record data alone.ResultsFor final eGFR, 16 proteins and 30 metabolites or tryptic peptides showed significant association in SDRNT1BIO, and nine proteins and five metabolites or tryptic peptides in FinnDiane, beyond age, sex, diabetes duration, study day eGFR and length of follow-up (all at p < 10−4). The strongest associations were with CD27 antigen (CD27), kidney injury molecule 1 (KIM-1) and α1-microglobulin. Including the Luminex biomarkers on top of baseline covariates increased the r2 for prediction of final eGFR from 0.47 to 0.58 in SDRNT1BIO and from 0.33 to 0.48 in FinnDiane. At least 75% of the increment in r2 was attributable to CD27 and KIM-1. However, using the weighted average of historical eGFR gave similar performance to biomarkers. The LC-MS/MS platform performed less well.Conclusions/interpretationAmong a large set of associated biomarkers, a sparse panel of just CD27 and KIM-1 contains most of the predictive information for eGFR progression. The increment in prediction beyond clinical data was modest but potentially useful for oversampling individuals with rapid disease progression into clinical trials, especially where there is little information on prior eGFR trajectories.

Fasting is not required for measuring plasma lipid levels in rabbits.

Plasma lipid and glucose levels are important parameters for evaluating the onset and development of metabolic and cardiovascular diseases. In clinical and experimental studies of humans or mice, fasting is often required before testing plasma lipid and glucose levels. The rabbit is a valuable animal model for cardiovascular disease research. However, whether fasting is necessary for measuring plasma lipid and glucose levels in rabbits remains unclear. In the current study, 12 healthy Japanese white rabbits (males weighing 2.5-3.0 kg) were randomly divided into a chow diet group (n = 6) and a high cholesterol diet group (n = 6). They were fed either a standard chow diet or a chow diet supplemented with 0.5% cholesterol and 3% corn oil for 12 weeks. After 12 weeks, the plasma levels of total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol and glucose were measured before and after various fasting durations (8, 12, 16, 20 and 24 h). The results showed that there were no significant differences in lipid levels between the fasting and non-fasting samples, whereas glucose levels were lower after 8 h of fasting than in the absence of fasting. Moreover, the glucose levels were restored to normal after 8 h of refeeding. These results indicate that fasting does not affect plasma lipid values in rabbits but that fasting is important for determining the glucose level in rabbits. These findings may be helpful for future rabbit experiments and beneficial for animal welfare.

2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.

2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.

Association of Nonfasting vs Fasting Lipid Levels With Risk of Major Coronary Events in the Anglo-Scandinavian Cardiac Outcomes Trial–Lipid Lowering Arm

Recent guidelines have recommended nonfasting for routine testing of lipid levels based on comparisons of nonfasting and fasting populations. However, no previous study has examined the association of cardiovascular outcomes with fasting vs nonfasting lipid levels measured in the same individuals. To compare the association of nonfasting and fasting lipid levels with prospectively ascertained coronary and vascular outcomes and to evaluate whether a strategy of using nonfasting instead of fasting lipid level measurement would result in misclassification of risk for individuals undergoing evaluation for initiation of statin therapy. This post hoc prospective follow-up of a randomized clinical trial included 8270 of 10 305 participants from the Anglo-Scandinavian Cardiac Outcomes Trial-Lipid Lowering Arm (ASCOT-LLA) with nonfasting and fasting lipid levels measured 4 weeks apart (including 6855 participants with no prior vascular disease) (median follow-up, 3.3 years; interquartile range, 2.8-3.6 years). Data were collected from February 1, 1998, to December 31, 2002, and analyzed from February 1, 2016, to November 30, 2018. Multivariable Cox models, adjusted for cardiovascular risk factors, were calculated for 40-mg/dL (1-mmol/L) higher values of nonfasting and fasting lipids. The trial's primary end point consisted of major coronary events (nonfatal myocardial infarction [MI] and fatal coronary heart disease [212 events]). Secondary analyses examined atherosclerotic cardiovascular disease (ASCVD) events (including MI, stroke, and ASCVD death [351 events]). Among the 8270 participants (82.1% male; mean [SD] age, 63.4 [8.5] years), nonfasting samples had modestly higher triglyceride levels and similar cholesterol levels compared to fasting samples. Associations of nonfasting lipid levels with coronary events were similar to those for fasting lipid levels. For example, adjusted hazard ratios (HRs) per 40-mg/dL of low-density lipoprotein cholesterol were 1.32 (95% CI, 1.08-1.61; P = .007) for nonfasting levels and 1.28 (95% CI, 1.07-1.55; P = .008) for fasting levels. For the primary prevention group, adjusted HRs were 1.42 (95% CI, 1.13-1.78; P = .003) for nonfasting levels and 1.37 (95% CI, 1.11-1.69; P = .003) for fasting levels. Results were consistent by randomized treatment arm (atorvastatin calcium, 10 mg/d, or placebo) and similar for ASCVD events. Concordance of fasting and nonfasting lipid levels for classifying participants into appropriate ASCVD risk categories was high (94.8%). Measurement of nonfasting and fasting lipid levels yields similar results in the same individuals for association with incident coronary and ASCVD events. These results suggest that routine measurement of nonfasting lipid levels may help facilitate ASCVD risk screening and treatment, including consideration of when to initiate statin therapy.

SUN-064 Associations of a Metabolic Syndrome Severity Score with Future Coronary Heart Disease (CHD) and Diabetes in Fasting vs. Non-Fasting Individuals

BACKGROUND: Many traditional assessments of risk for coronary heart disease (CHD) and diabetes require laboratory studies performed after at least an 8-hour fast. However, obtaining fasting samples is less convenient and may result in fewer opportunities for risk assessment and targeted treatment. We hypothesized that metabolic syndrome (MetS) severity would remain linked to future CHD and diabetes even when assessed from non-fasting samples. METHODS: Participants in the Atherosclerosis Risk in Communities study were assessed at 4 visits and followed for 20-years of adjudicated CHD outcomes. We used a race/ethnicity-specific MetS severity Z-score (MetS-Z) calculated from the five traditional components of MetS: waist circumference, systolic blood pressure, HDL, triglycerides and glucose. In prior studies, this Z-score—as calculated from fasting samples—was associated with future CHD and diabetes independent of the individual MetS components. In the current analysis, we assessed risk of adjudicated CHD outcomes using Cox proportional hazard models for baseline MetS-Z calculated from a) fasting (≥8 hours) samples at Visit 1 or b) non-fasting samples at any of the 4 study visits. We assessed incident diabetes risk using logistic regression for fasting vs. non-fasting samples from Visit 1 for risk of diabetes by Visit 4. All analyses were adjusted for sex, race, education, income and current smoking. RESULTS: MetS Z-scores across visits were overall similar between fasting and non-fasting groups (all values when drawn from both fasting and non-fasting samples -0.1 - 0.4), with the exception of individuals non-fasting at Visit 4, who had higher MetS-Z values already at Visit 1. MetS-Z scores were linked to future CHD when calculated from both fasting and non-fasting measurements, with hazard ratio (HR) for fasting MetS-Z 1.53 (95% confidence interval [CI] 1.42, 1.66) and for non-fasting MetS-Z 1.28 (CI 1.08, 1.51). MetS-Z at Visit 1 also remained linked to future diabetes when measured from non-fasting samples, with HR for fasting MetS-Z 3.10 (CI 2.88, 3.35) and for non-fasting MetS-Z 1.92 (CI 1.05, 3.51). CONCLUSIONS: As a marker of long-term risk for chronic disease, MetS-Z remained linked to future CHD and diabetes when assessed from non-fasting samples. A score such as this, calculated through the electronic health record, may allow for identification of at-risk individuals and serve as a motivation toward interventions to improve risk.

The association between insomnia, high sensitive C-reactive protein, and chronic low back pain: cross-sectional analysis of the hunt study, Norway

Purpose: Chronic low back pain is the number one cause for living with disability among 301 diseases and injuries analyzed by The Global Burden of Disease study 2013. Insomnia symptoms are highly prevalent in people with chronic low back pain, with 55-59% reporting symptoms such as poor sleep quality, non-restorative sleep, waking up too early, and difficulty initiating and maintaining sleep. For people with chronic low back pain, insomnia symptoms are associated with increased pain intensity and decreased physical function. People with insomnia have 1.36 times the odds of developing chronic low back pain 17 months later, compared to those without insomnia. To explain the sleep-pain relationship, theoretical models propose that activation of inflammatory markers such as tumor necrosis factor, interleukin 6, and high sensitive C-Reactive Protein (hsCRP), could contribute to increased pain, which may also further disrupt sleep. Of these inflammatory markers hsCRP is of interest as it has been commonly assessed in large population studies for cardiovascular disease risk. The relationship between insomnia and hsCRP, and the relationship between hsCRP and presence of chronic low back pain are not clear. This is partly due to the lack of consistent insomnia and chronic low back pain diagnostic criteria, other comorbidities or associated factors may not have been adequately controlled. Moreover, no study has modelled the associations of insomnia, hsCRP and chronic low back pain within the same sample We aimed to determine the associations between insomnia, chronic low back pain, and hsCRP, whilst controlling for age, body mass index, smoking, physical activity, depression, anxiety and osteoarthritis. Methods: A cross-sectional analysis of the third Nord-Trøndelag Health Study (2006-2008), a rural population survey of 50,666 participants in Norway aged 20-96 years. A comprehensive description of the data collection methodology has been published elsewhere. Insomnia (dichotomous) was defined according to the Diagnostic and Statistical Manual of Mental Disorders 5th Edition, and chronic low back pain (dichotomous) as low back pain or stiffness lasting at least three months. Data for hsCRP was obtained from non-fasting serum samples and assessed via latex immunoassay methodology. We excluded participants with the following self-reported chronic inflammatory diseases: chronic heart failure, chronic obstructive pulmonary disease, rheumatoid arthritis, fibromyalgia or ankylosing spondylosis. This was to ensure that our results reflected the possible associations of between insomnia, hsCRP and chronic low back pain and were not masked by these chronic inflammatory diseases. We compared the median hsCRP of these chronic inflammatory conditions to confirm their suitability for exclusion. Possible associations between presence of insomnia and presence of chronic low back pain (dependent), and the level of hsCRP and presence of chronic low back pain (dependent), were assessed using univariate logistic regression models. Possible association between insomnia and hsCRP (dependent) was assessed using linear regression. Multivariable analyses were conducted adjusting for confounders stated in our aim that achieved p ≤ 0.2 in univariate regressions. We performed stratified analyses for participants with normal (<3mg/L) and elevated (≥3mg/L) levels of hsCRP. Results: In our total included sample (n=30,669, median age 52.6, 54% female), 6.1% of participants reported insomnia (n=1,871), 21.4% had chronic low back pain (n=6,559), and 2.4% had both (n=719) (Figure 1). 24,288 (79.1%) participants had normal hsCRP while 6,429 (20.9%) had elevated hsCRP. Insomnia was associated with the presence of chronic low back pain (adjusted OR=1.99, 95%CI [1.79-2.21], <0.001) (Table 2). There was an association between hsCRP and presence of chronic low back pain (adjusted OR=1.01, [1.00-1.01], p=0.016) (Table 1). For participants with normal levels of hsCRP, insomnia was associated with hsCRP (adjusted B =0.04, 95%CI [0.00-0.08], p=0.037), but not for people within elevated levels of hsCRP (Table 2). Conclusions: In our large populational study, people with insomnia have double the odds of reporting chronic low back pain, and the role of high sensitive c-reactive protein in this relationship appears to be limited. Given the strong relationship between insomnia and chronic low back pain, it may be worth targeting these comorbidities as they may lead to improvements in the other. Longitudinal studies are required to explore whether the presence of insomnia and elevated hsCRP affects the development of chronic low back pain.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Moderately elevated preconception fasting plasma total homocysteine is a risk factor for psychological problems in childhood.

We investigated the effect of maternal preconception fasting plasma total homocysteine (tHcy) on psychological problems in children aged 6 years from normal pregnancies. A longitudinal study was carried out from preconception, throughout each trimester of pregnancy, until 6 years of age in the offspring. Fasting blood samples at 2-10 weeks preconception and non-fasting samples at birth were collected. Parents completed the Child Behaviour Checklist (CBCL) and teachers the Inattention-Overactivity with Aggression (IOWA) scale for the 6-year-old children. Elevated tHcy during pregnancy has been associated with several adverse outcomes and with neurodevelopmental impairment in the offspring.ParticipantsThe initial sample consisted of 139 healthy non-pregnant women who were planning on becoming pregnant. Eighty-one mother-child dyads were followed from preconception until 6 years of age. After adjusting for covariables, multiple linear regression models showed that higher preconception tHcy was associated with higher scores in internalizing dimension (β=0·289; P=0.028), specifically in withdrawn behaviour (β=0·349; P=0·009), anxiety/depression (β=0·303; P=0·019) and social problems (β=0·372; P=0·009). Aggressive behaviour in the school setting was higher in children whose mothers had higher preconception tHcy (β=0·351; P=0·014). Moderately elevated preconception tHcy may increase the risk of psychological problems in offspring during childhood. These findings add to the evidence that maternal nutritional status, even before being pregnant, can affect later offspring health and may be important to consider when developing future public health policy.

Proteins Altered by Surgical Weight Loss Highlight Biomarkers of Insulin Resistance in the Community.

Objective- Mechanisms of early and late improvements in cardiovascular risk after bariatric surgery and applicability to larger, at-risk populations remain unclear. We aimed to identify proteins altered after bariatric surgery and their relations to metabolic syndrome and diabetes mellitus. Approach and Results- We identified 19 proteins altered in 32 nonfasting plasma samples from a study of patients undergoing bariatric surgery who were evaluated preoperatively (visit 1) versus both early (visit 2; ≈3 months) and late (visit 3; ≈12 months) postoperative follow-up using predefined protein panels (Olink). Using in silico methods and publicly available gene expression repositories, we found that genes encoding 8 out of 19 proteins had highest expression in liver relative to other assayed tissues, with the top biological and disease processes, including major obesity-related vascular diseases. Of 19 candidate proteins in the surgical cohort, 6 were previously measured in >3000 FHS (Framingham Heart Study) participants (IGFBP [insulin-like growth factor binding protein]-1, IGFBP-2, P-selectin, CD163, LDL (low-density lipoprotein)-receptor, and PAI [plasminogen activator inhibitor]-1). A higher concentration of IGFBP-2 at baseline was associated with a lower risk of incident metabolic syndrome (odds ratio per log-normal unit, 0.45; 95% CI, 0.32-0.64; P=7.7×10-6) and diabetes mellitus (odds ratio, 0.63; 95% CI, 0.49-0.79; P=0.0001) after multivariable adjustment. Conclusions- Using a directed protein quantification platform (Olink), we identified known and novel proteins altered after surgical weight loss, including IGFBP-2. Future efforts in well-defined obesity intervention settings may further define and validate novel targets for the prevention of vascular disease in obesity.

Associations of literacy with diabetes indicators in older adults

BackgroundLiteracy, the ability to access, understand and utilise information and concepts from diverse sources in ways that promote good outcomes is key to successful ageing. Domain-specific health and financial literacy...