The Impact of Almond Nut Consumption on Markers of CVD & Metabolic Health

King's College London108 enrolled

Overview

The purpose of this study is to investigate the cardio-metabolic health effects of consuming almond nuts in place of habitual (usual) snack products in adults at moderate risk of developing cardiovascular disease

Tree nuts are recommended in the prevention and management of cardiovascular disease (CVD) largely based on their LDL (low density lipoprotein) lowering effects, but the CVD risk reduction observed with tree nut consumption is greater than that predicted by their hypocholesterolemic effects alone. Other health benefits have also been noted by our group, such as moderation of postprandial lipemia , as well as by others such as modified postprandial glycemia , decreased blood pressure (BP) , improvement in oxidant status and weight loss. Robust evidence for the protective cardio-metabolic effects of nuts from the PREDIMED study has highlighted the association between nut consumption and decreased risk of cardiovascular events, obesity, metabolic syndrome and type 2 diabetes (T2DM). However, there is a paucity of evidence on the effects of almonds on vascular function in humans (BP and endothelium-dependent vasodilation (EDV)), although there is evidence that almonds promote nitric oxide (NO) release in animals consuming high-fat diets. Fundamental to vascular health is a well-functioning liver and there is increasing evidence to demonstrate that the accumulation of liver fat is a causative factor in the development of cardio-metabolic disorders. Non-alcoholic fatty liver disease (NAFLD) is now considered the hepatic manifestation of the metabolic syndrome (MetS); recent data has shown that it is linked to increased CVD risk via direct effects on vascular function (and EDV) independently of obesity and MetS . NAFLD is thought to affect 30% of the population in developed countries, and up to two-thirds of people with obesity and 50% of people with hyperlipidemia. Development of fatty liver, mainly attributable to obesity and elevated postprandial lipemia, is associated with increased inflammation, oxidative stress, insulin resistance, dyslipidemia and impaired EDV, and predicts risk of CVD and T2DM . Therefore, the long-term goal of this research is to understand the mechanisms underpinning how dietary change can drive favourable modification of CVD disease risk and to identify patterns in population food choices, specifically almond consumption, that tend to correlate with reduced CVD disease risk. The primary aim of this proposal is to investigate, in a randomised controlled, parallel arm, 6-wk dietary intervention (n=100) whether replacing snacks based on refined carbohydrates and poor in micronutrients/non-nutrient bioactives (NNB) with nutrient/NNB-dense, whole almond snacks can influence liver fat content (a key metabolic driver of insulin resistance and vascular dysfunction, and a hallmark of metabolic syndrome) and EDV (brachial FMD being an independent predictor of CVD events, in addition to related biomarkers of cardio-metabolic disease risk. The snacks products provide participants with 20% of their energy requirements via either whole almonds or as muffins/crackers that have been designed to mimic the average UK snack.

Study Type

INTERVENTIONAL

Allocation

RANDOMIZED

Purpose

DIAGNOSTIC

Masking

SINGLE

Enrollment

108

Conditions

Cardiovascular Disease

Interventions

AlmondsDIETARY_SUPPLEMENT

Participants to consume almonds as snacks to contribute to 20% of their energy requirements daily for 4 weeks

Muffins/CrackersDIETARY_SUPPLEMENT

Participants to consume muffins/crackers as snacks to contribute to 20% of their energy requirements daily for 4 weeks NB all participants will have a run in period for 2 weeks whereby muffins are consumed, this is prior to randomisation.

Eligibility

Sex: ALLMin age: 30 YearsMax age: 70 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: Subjects will be male or female, aged between 30-70 years who regularly consume ≥2 snack products a day. A principal aim is to identify and recruit subjects with increased risk of CVD, in order to increase the sensitivity of the study subjects to dietary change. Subjects who are at above average risk for developing CVD (relative risk \>1.5) will be selected using a metabolic scoring system (scoring ≥2 points), adapted from the Framingham risk score system, as used previously by Chong et al. 2012. Subjects will give their own written informed consent. Exclusion Criteria: 1. Non-snack consumers (assessed as subjects consuming \<2 snack products per day by a specific FFQ (food frequency questionnaire) at screening, adapted from the short Health Survey for England (2007) Eating Habits Questionnaire). 2. A reported history of myocardial infarction or cancer. 3. Being fitted with a heart pacemaker. 4. Presence of metal inside the body (implants, devices, shrapnel, metal particles in eyes from welding etc.). History of black-outs/epilepsy. 5. Diabetes mellitus (fasting plasma glucose \>7 mmol/L). 6. Chronic coronary, renal or bowel disease or history of cholestatic liver disease or pancreatitis. 7. Presence of gastrointestinal disorder or use of a drug, which is likely to alter gastrointestinal motility or nutrient absorption. 8. History of substance abuse or alcoholism (past history of alcohol intake \>60 units/men or 50 units/women). 9. Currently pregnant, planning pregnancy, breastfeeding or having had a baby in the last 12 months. 10. Allergy or intolerance to nuts. 11. Unwilling to follow the protocol and/or give informed consent. 12. Weight change of \> 3 kg in preceding 2 months. BMI \<18 kg/m2 (underweight) or \>40 kg/m2 (morbidly obese due to potential technical difficulties making FMD and ambulatory blood pressure (ABP) measurements). 13. Current smokers or individuals who quit smoking within the last 6 months. 14. Participation in other research trials involving dietary or drug intervention and/ or blood collection in the past 3 months. 15. Unable or unwilling to comply with study protocol. 16. The above criteria will be measured using the screening questionnaires and from physical (blood pressure, weight, height) and biochemical measurements (full lipid count, liver function test, full blood count, glucose and insulin) made during the screening visit. Participant eligibility will be assessed against the inclusion/exclusion criteria and 'fitness' to participate will be assessed and signed off by a clinician.

Locations (1)

King's College London, Diabetes and Nutritional Sciences Division

London, United Kingdom

Outcomes

Primary Outcomes

Endothelium-dependent vasodilation

Measured via flow mediated dilation (FMD)

Time frame: Baseline (week 2)

Endothelium-dependent vasodilation

Measured via flow mediated dilation (FMD)

Time frame: Week 8 (after 2 week run in)

Liver fat %

Via MRI and magnetic resonance spectroscopy (MRS) analysis. Only a subset of 48 participants with aim of 20 per each arm to complete

Time frame: Baseline (week 2)

Liver fat %

Via MRI and MRS analysis. Only a subset of 48 participants with aim of 20 per each arm to complete

Time frame: Week 8 (after 2 week run in)

Secondary Outcomes

Pancreatic fat

Via body MRI. Only a subset of 48 participants with aim of 20 per each arm to complete.

Time frame: Baseline (week 2)

Abdominal fat

Via body MRI. Only a subset of 48 participants with aim of 20 per each arm to complete.

Time frame: Baseline (week 2)

Muscle fat

Single measurement via body MRI. Only a subset of 48 participants with aim of 20 per each arm to complete.Muscle fat will be measured in the soleus muscle in the lower calf.

Time frame: Baseline (week 2)

Pancreatic fat

Single measurement via body MRI. Only a subset of 48 participants with aim of 20 per each arm to complete.

Data from ClinicalTrials.gov

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