scholarly journals The effect of a low carbohydrate high fat diet on emerging biochemical markers of cardiometabolic risk

2020 ◽  
Vol 79 (OCE2) ◽  
Author(s):  
Deaglan McCullough ◽  
Tanja Harrison ◽  
Katie Lane ◽  
Lynne Boddy ◽  
Farzad Amirabdollahian ◽  
...  
Keyword(s):  
Cardiometabolic Risk ◽  
Metabolic Adaptation ◽  
Model Assessment ◽  
High Fat ◽  
Low Carbohydrate ◽  
Homeostatic Model Assessment ◽  
Ad Libitum ◽  
Cardiometabolic Risk Markers ◽  
The Uk ◽  
The Impact

AbstractWorldwide, cardiovascular disease (CVD) is the number 1 cause of mortality and is associated with insulin resistance (IR). Emerging biomarkers such as FGF21 and adiponectin are associated with cardiometabolic risk. Low carbohydrate, high fat (LCHF) diets have been reported to reduce cardiometabolic risk markers; however, few studies have compared a LCHF diet vs. a high carbohydrate (HC), lower fat diet under ad libitum conditions on adiponectin and FGF21. The purpose of this study was to investigate the effects of an ad libitum LCHF vs. HC diet on IR, FGF21 and adiponectin in 16 healthy adults. Ethical approval: Liverpool John Moores University Research Ethics Committee (16/ELS/029); registered with ClinicalTrials.gov (Ref. NCT03257085). Participants were randomly assigned to a HC diet (n = 8, the UK Eatwell guidelines; ≥ 50% of energy from carbohydrates) or a LCHF diet (n = 8, consume < 50 g/day of carbohydrates). All provided plasma samples at 0, 4 and 8 weeks. FGF21 (R&D Systems) was analysed via ELISA and adiponectin, insulin and glucose were analysed via immunoassay technology (Randox Evidence Investigator™ Metabolic Syndrome Arrays I & II). Mann Whitney, Friedmans, Wilcoxon tests and 2×3 ANOVA (IBM SPSS 25®) were undertaken to investigate significant differences between and within groups. The homeostatic model assessment (HOMA) was used to calculate IR. FGF21 significantly (P = 0.04) decreased (Mdn, IQR:148.16, 78.51–282.02 to 99.4, 39.87–132.29 pg/ml) after 4 weeks and significantly (P = 0.02) increased (Mdn, IQR:167.38, 80.82–232.89 pg/ml) by 8 weeks vs. baseline with LCHF. No significant differences (P > 0.05) were observed between groups. Adiponectin was significantly (P = 0.03) different at week 4 only between groups. Adiponectin increased after 4 weeks (Mdn, IQR:13.44, 9.12–25.47 to 16.64, 11.96–21.51 ng/ml) but was only significantly (P = 0.03) different by 8 weeks vs. baseline in the HC group (Mdn, IQR:16, 10.8–27.43 ng/ml). Adiponectin remained unchanged (P = 0.96) in the LCHF group. HOMA significantly decreased with both diets after 8 weeks only (mean ± SD, LCHF: 2.9 ± 1.3 to 1.8 ± 0.8, HC: 2.5 ± 0.6 to 1.9 ± 0.6, P = 0.008) but was not significantly (P = 0.60) different between groups. These preliminary data reveal that while both diets improved insulin sensitivity, they may do so by different mechanisms. Future studies are warranted to investigate further, how a LCHF vs. HC diet affects FGF21 and adiponectin, and the subsequent regulation of IR. Furthermore, studies that extend these findings by determining the impact of LCHF vs. HC on peripheral metabolism to determine potential nutrition-mediated mechanisms of metabolic adaptation are warranted.

scholarly journals Differing effects of high-fat or high-carbohydrate meals on food hedonics in overweight and obese individuals

2016 ◽  
Vol 115 (10) ◽  
pp. 1875-1884 ◽  
Author(s):  
Mark Hopkins ◽  
Catherine Gibbons ◽  
Phillipa Caudwell ◽  
John E. Blundell ◽  
Graham Finlayson
Keyword(s):  
Energy Intake ◽  
High Fat ◽  
Appetite Control ◽  
Short Term ◽  
High Carbohydrate ◽  
Low Carbohydrate ◽  
Before And After ◽  
Ad Libitum ◽  
The Impact ◽  
Food Hedonics

AbstractAlthough the effects of dietary fat and carbohydrate on satiety are well documented, little is known about the impact of these macronutrients on food hedonics. We examined the effects ofad libitumand isoenergetic meals varying in fat and carbohydrate on satiety, energy intake and food hedonics. In all, sixty-five overweight and obese individuals (BMI=30·9 (sd3·8) kg/m2) completed two separate test meal days in a randomised order in which they consumed high-fat/low-carbohydrate (HFLC) or low-fat/high-carbohydrate (LFHC) foods. Satiety was measured using subjective appetite ratings to calculate the satiety quotient. Satiation was assessed by intake atad libitummeals. Hedonic measures of explicit liking (subjective ratings) and implicit wanting (speed of forced choice) for an array of HFLC and LFHC foods were also tested before and after isoenergetic HFLC and LFHC meals. The satiety quotient was greater afterad libitumand isoenergetic meals during the LFHC condition compared with the HFLC condition (P=0·006 andP=0·001, respectively), whereasad libitumenergy intake was lower in the LFHC condition (P<0·001). Importantly, the LFHC meal also reduced explicit liking (P<0·001) and implicit wanting (P=0·011) for HFLC foods compared with the isoenergetic HFLC meal, which failed to suppress the hedonic appeal of subsequent HFLC foods. Therefore, when coupled with increased satiety and lower energy intake, the greater suppression of hedonic appeal for high-fat food seen with LFHC foods provides a further mechanism for why these foods promote better short-term appetite control than HFLC foods.

HOMA-Adiponectin Closely Associates with Cardiometabolic Risk Markers in Middle-Aged Indians with Metabolic Syndrome

2020 ◽  
Author(s):  
Joyita Banerjee ◽  
Yogita Dhas ◽  
Neetu Mishra
Keyword(s):  
Insulin Resistance ◽  
Cardiometabolic Risk ◽  
Risk Indicators ◽  
Atherogenic Index ◽  
Model Assessment ◽  
Risk Markers ◽  
Middle Aged ◽  
Homeostatic Model Assessment ◽  
Hs Crp ◽  
Cardiometabolic Risk Markers

Abstract Background Unhealthy dietary habits and sedentary lifestyles have raised alarming concerns for the rising prevalence of metabolic syndrome (MetS) and associated cardiometabolic risk among Indians at an early age. Insulin resistance and adiposity are the important risk factors associated with MetS. The present study aimed to investigate the relationship between a modified marker of insulin resistance (homeostatic model assessment-adiponectin (HOMA-AD)) and cardiometabolic risk among middle-aged Indians. Methods The study comprised of 144 subjects of age-group 31–50 years, where 83 subjects were diagnosed for MetS according to the guidelines given by the International Diabetes Federation. We measured cardiometabolic risk indicators such as fasting blood glucose (FPG), fasting plasma insulin (FPI), homeostatic model assessment- insulin resistance (HOMA-IR), adiponectin, high sensitivity C-reactive protein (hs-CRP), oxidized LDL (oxLDL), monocyte chemoattractant protein-1 (MCP-1), and atherogenic index, among others. We calculated HOMA-AD by the formula: [FPG (mmol/l) × FPI (µIU/ml)] / [22.5 × Adiponectin (µg/ml)]. Results HOMA-IR and HOMA-AD were highly increased (p<0.001) in the MetS subjects than controls. Adiponectin was significantly (p<0.01) lower whereas cardiac risk markers such as atherogenic index, hs-CRP, oxLDL, and MCP-1 were significantly (p<0.01) elevated in MetS group than controls. Linear regression showed positive and significant associations (p<0.01) of HOMA-AD with all the cardiometabolic risk markers except MCP-1. HOMA-AD showed higher AUC (0.806) than HOMA-IR (0.791) for predicting MetS. Conclusion HOMA-AD could be a surrogate adipokine-based marker correlated significantly with components of MetS and cardiometabolic risk indicators. It appeared to be a better predictor of MetS among middle-aged Indians than HOMA-IR.

Abstract 13507: The Role of Weight Loss in Mediating the Effects of a 2-year Caloric Restriction Regimen on Cardiometabolic Risk Markers in Individuals Without Obesity

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
James L Dorling ◽  
Leanne Redman ◽  
Eric Ravussin ◽  
Kim Huffman ◽  
Susan B RACETTE ◽  
...  
Keyword(s):  
Weight Loss ◽  
Caloric Restriction ◽  
Cardiometabolic Risk ◽  
Density Lipoprotein ◽  
Lipoprotein Cholesterol ◽  
Model Assessment ◽  
Risk Markers ◽  
Mediation Analyses ◽  
Cardiometabolic Risk Markers ◽  
The Impact

Introduction: Caloric restriction (CR) improves cardiometabolic risk, even among individuals without obesity. However, it is unclear whether these aging-related benefits are mediated by weight loss. Mediation analyses inform mechanisms underlying relationships between an exposure and outcome. Using mediation analyses, our aim was to test if 2-year weight loss mediates the beneficial effects of CR on cardiometabolic risk markers in individuals without obesity. Methods: Participants without obesity were randomized 2:1 to CR or ad libitum (AL) as part of the 2-year trial, Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE). The CR group aimed to enact 25% CR for 2 years, while AL maintained habitual energy intake. Baseline and year 2 assessments included weight and cardiometabolic risk markers. Using the approaches of Valeri and VanderWeele, mediation was quantified as the natural indirect effect (NIE), defined as the impact of an exposure on an outcome through a mediator. Here, the NIE was the effect of CR (exposure) on cardiometabolic risk markers (outcome) that was accounted for by weight change (mediator). Results: In total, 117 and 71 participants in the CR and AL groups, respectively, completed the trial. The CR group achieved 11.9 (± 0.7)% CR and 7.6 (± 0.3) kg of weight loss ( P < 0.01 versus AL). Weight loss significantly mediated the CR-induced improvements in total cholesterol (NIE = -10.4 ± 3.5 mg/dL), low-density lipoprotein cholesterol (NIE = -8.5 ± 2.8 mg/dL), high-density lipoprotein cholesterol (NIE = 2.9 ± 1.3 mg/dL), triglycerides (NIE = -0.20 ± 0.05 log mg/dL), the homeostatic model assessment of insulin resistance (NIE = -0.22 ± 0.06), and C-reactive protein (NIE = -0.39 ± 0.15 log ug/mL) ( P ≤ 0.02). Weight loss did not mediate CR-induced reductions in systolic (NIE = -0.9 ± 1.4 mmHg) and diastolic (NIE = -1.0 ± 1.1 mmHg) blood pressure ( P ≥ 0.37). Conclusion: In individuals without obesity, CR-induced improvements in multiple cardiometabolic risk markers are driven by weight loss after 2 years. These findings emphasize that, even in individuals without obesity, weight loss after prolonged CR plays a role in improving cardiometabolic disease risk; however, some CR benefits still occur independent of weight loss.

scholarly journals Hyperandrogenism by Liquid Chromatography Tandem Mass Spectrometry in PCOS: Focus on Testosterone and Androstenedione

2020 ◽  
Vol 10 (1) ◽  
pp. 119
Author(s):  
Giorgia Grassi ◽  
Elisa Polledri ◽  
Silvia Fustinoni ◽  
Iacopo Chiodini ◽  
Ferruccio Ceriotti ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
Polycystic Ovary ◽  
Free Testosterone ◽  
Reference Intervals ◽  
Model Assessment ◽  
Homeostatic Model Assessment ◽  
Liquid Chromatography Tandem Mass ◽  
And Control ◽  
The Impact

The identification of hyperandrogenism in polycystic ovary syndrome (PCOS) is concerning because of the poor accuracy of the androgen immunoassays (IA) and controversies regarding which androgens should be measured. The aim of our study was to evaluate the impact of the assessment of testosterone (T) and androstenedione (A) by liquid chromatography in tandem with mass spectrometry (LC/MS-MS), in the diagnosis of PCOS. We evaluated 131 patients referred for suspected PCOS. Fourteen patients in total were excluded, some because of other diagnosis (n = 7) or incomplete diagnostic workup (n = 7). We measured T and A both by IA and LC-MS/MS in the 117 subjects included. We calculated free T (fT) by the Vermeulen formula and recorded clinical and metabolic data. 73 healthy females served as controls to derive immunoassays (IA) and LC-MS/MS reference intervals for T, fT and A. PCOS was confirmed in 90 subjects by IA and in 93 (+3.3%) by LC-MS/MS. The prevalence of biochemical hyperandrogenism in PCOS by LC-MS/MS increased from 81.7% to 89.2% if A was also considered. The most frequently elevated androgens were fT (73.1%) and A (64.5%) and they had similar levels of accuracy in differentiating PCOS and controls (0.34 ng/dL, Sn 91% Sp 89%; 1.16 ng/mL, Sn 91% Sp 88%, respectively). Free testosterone correlated with body mass index (BMI), homeostatic model assessment (HOMA)-index, glycated hemoglobin (HbA1c), and sex-binding globulin (SHBG). The results confirm that LC-MS/MS is slightly more sensitive than IA in the diagnosis of PCOS with LC-MS/MS detecting higher levels of fT and A. Moreover, assessment of fT and A by LC-MS/MS had a similar level of accuracy in discriminating between PCOs and control subjects. Lastly, fT by LC-MS/MS correlates with adverse metabolic parameters.

scholarly journals Adiposity and cardiometabolic risk markers among Indian children: comparison with Indian and white European children in the UK

2011 ◽  
Vol 65 (Suppl 2) ◽  
pp. A16-A16 ◽  
Author(s):  
C. Nightingale ◽  
G. Krishnaveni ◽  
A. Rudnicka ◽  
C. Owen ◽  
S. Veena ◽  
...  
Keyword(s):  
Cardiometabolic Risk ◽  
Risk Markers ◽  
Indian Children ◽  
Cardiometabolic Risk Markers ◽  
The Uk

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

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0248602 ◽  
Author(s):  
Ryan J. Scalsky ◽  
Yi-Ju Chen ◽  
Karan Desai ◽  
Jeffery R. O’Connell ◽  
James A. Perry ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type Ii Diabetes ◽  
Cardiometabolic Risk ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Lipoprotein Cholesterol ◽  
Type Ii ◽  
Uk Biobank ◽  
The Uk ◽  
The Impact

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

scholarly journals Blood glucose and meal patterns in time-blinded males, after aspartame, carbohydrate, and fat consumption, in relation to sweetness perception

1999 ◽  
Vol 82 (6) ◽  
pp. 437-446 ◽  
Author(s):  
Kathleen J. Melanson ◽  
Margriet S. Westerterp-Plantenga ◽  
L. Arthur Campfield ◽  
Wim H. M. Saris
Keyword(s):  
Blood Glucose ◽  
Meal Size ◽  
High Fat ◽  
Meal Patterns ◽  
High Carbohydrate ◽  
Fat Consumption ◽  
Ad Libitum ◽  
The Impact ◽  
Simple Carbohydrate ◽  
Healthy Males

In a study of the impact of aspartame, fat, and carbohydrate on appetite, we monitored blood glucose continuously for 431 (se 16) min. Ten healthy males (19–31 years) participated in three time-blinded visits. As blood glucose was monitored, appetite ratings were scored at randomized times. On the first meal initiation, volunteers consumed one of three isovolumetric drinks (aspartame, 1 MJ simple carbohydrate, and 1 MJ high-fat; randomized order). High-fat and high-carbohydrate foods were available ad libitum subsequently. Blood glucose patterns following the carbohydrate drink (+1·78 (se 0·28) mmol/l in 38 (se 3) min) and high-fat drink (+0·83 (se 0·28) mmol/l in 49 (se 6) min) were predictive of the next intermeal interval (R 0·64 and R 0·97 respectively). Aspartame ingestion was followed by blood glucose declines (40 % of subjects), increases (20 %), or stability (40 %). These patterns were related to the volunteers' perception of sweetness of the drink (R 0·81, P = 0·014), and were predictive of subsequent intakes (R -0·71, P = 0·048). For all drinks combined, declines in blood glucose and meal initiation were significantly associated (χ2 16·8, P < 0·001), the duration of blood glucose responses and intermeal intervals correlated significantly (R 0·715, P = 0·0001), and sweetness perception correlated negatively with hunger suppression (R -0·471, P = 0·015). Effects of fat, carbohydrate, and aspartame on meal initiation, meal size, and intermeal interval relate to blood glucose patterns. Varied blood glucose responses after aspartame support the controversy over its effects, and may relate to sweetness perception.

scholarly journals Impact of the Apolipoprotein E (epsilon) Genotype on Cardiometabolic Risk Markers and Responsiveness to Acute and Chronic Dietary Fat Manipulation

Nutrients ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 2044 ◽  
Author(s):  
Kumari M. Rathnayake ◽  
Michelle Weech ◽  
Kim G. Jackson ◽  
Julie A. Lovegrove
Keyword(s):  
Dietary Fat ◽  
Cardiometabolic Risk ◽  
Apoe Genotype ◽  
Density Lipoprotein ◽  
Lipoprotein Cholesterol ◽  
Risk Markers ◽  
Cardiometabolic Risk Markers ◽  
The Impact ◽  
Volume Pulse ◽  
Digital Volume Pulse

Apolipoprotein (APO) E (ε) genotype is considered to play an important role in lipid responses to dietary fat manipulation but the impact on novel cardiometabolic risk markers is unclear. To address this knowledge gap, we investigated the relationship between the APOE genotype and cardiometabolic risk markers in response to acute and chronic dietary fat intakes. Associations with fasting (baseline) outcome measures (n = 218) were determined using data from the chronic DIVAS (n = 191/195 adults at moderate cardiovascular disease risk) and acute DIVAS-2 (n = 27/32 postmenopausal women) studies examining the effects of diets/meals varying in saturated, polyunsaturated and monounsaturated (MUFA) fatty acid composition. Participants were retrospectively genotyped for APOE (rs429358, rs7412). For baseline cardiometabolic outcomes, E4 carriers had higher fasting total and low-density lipoprotein-cholesterol (LDL-C), total cholesterol: high-density lipoprotein-cholesterol (HDL-C) and LDL-C: HDL-C ratios, but lower C-reactive protein (CRP) than E3/E3 and E2 carriers (p ≤ 0.003). Digital volume pulse stiffness index was higher in E2 carriers than the E3/E3 group (p = 0.011). Following chronic dietary fat intake, the significant diet × genotype interaction was found for fasting triacylglycerol (p = 0.010), with indication of a differential responsiveness to MUFA intake between the E3/E3 and E4 carriers (p = 0.006). Test fat × genotype interactions were observed for the incremental area under the curve for the postprandial apolipoprotein B (apoB; p = 0.022) and digital volume pulse reflection index (DVP-RI; p = 0.030) responses after the MUFA-rich meals, with a reduction in E4 carriers and increase in the E3/E3 group for the apoB response, but an increase in E4 carriers and decrease in the E3/E3 group for the DVP-RI response. In conclusion, baseline associations between the APOE genotype and fasting lipids and CRP confirm previous findings, although a novel interaction with digital volume pulse arterial stiffness was observed in the fasted state and differential postprandial apoB and DVP-RI responses after the MUFA-rich meals. The reported differential impact of the APOE genotype on cardiometabolic markers in the acute and chronic state requires confirmation.

scholarly journals Interplay of Glycemic Index, Glycemic Load, and Dietary Antioxidant Capacity with Insulin Resistance in Subjects with a Cardiometabolic Risk Profile

2018 ◽  
Vol 19 (11) ◽  
pp. 3662 ◽  
Author(s):  
Cristina Galarregui ◽  
María Zulet ◽  
Irene Cantero ◽  
Bertha Marín-Alejandre ◽  
José Monreal ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Antioxidant Capacity ◽  
Diet Quality ◽  
Glycemic Index ◽  
Cardiometabolic Risk ◽  
Glycemic Load ◽  
Risk Profile ◽  
Model Assessment ◽  
Susceptible Population ◽  
Homeostatic Model Assessment

Background: Dietary total antioxidant capacity (TAC), glycemic index (GI), and glycemic load (GL) are accepted indicators of diet quality, which have an effect on diet–disease relationships. The aim of this study was to evaluate potential associations of dietary TAC, GI, and GL with variables related to nutritive status and insulin resistance (IR) risk in cardiometabolic subjects. Methods: A total of 112 overweight or obese adults (age: 50.8 ± 9 years old) were included in the trial. Dietary intake was assessed by a validated 137-item food frequency questionnaire (FFQ), which was also used to calculate the dietary TAC, GI, and GL. Anthropometrics, blood pressure, body composition by dual-energy X-ray absorptiometry (DXA), glycemic and lipid profiles, C-reactive protein (CRP), as well as fatty liver quantification by magnetic resonance imaging (MRI) were assessed. Results: Subjects with higher values of TAC had significantly lower circulating insulin concentration and homeostatic model assessment of insulin resistance (HOMA-IR). Participants with higher values of HOMA-IR showed significantly higher GI and GL. Correlation analyses showed relevant inverse associations of GI and GL with TAC. A regression model evidenced a relationship of HOMA-IR with TAC, GI, and GL. Conclusion: This data reinforces the concept that dietary TAC, GI, and GL are potential markers of diet quality, which have an impact on the susceptible population with a cardiometabolic risk profile.

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