Beet the cold: Beetroot juice supplementation improves peripheral blood flow, endothelial function and anti-inflammatory status in individuals with Raynaud’s phenomenon.

Raynaud’s phenomenon (RP) is characterised by recurrent transient peripheral vasospasm and lower nitric oxide (NO) bioavailability in the cold. We investigated the effect of nitrate-rich beetroot juice (BJ) supplementation on i) NO-mediated vasodilation, ii) cutaneous vascular conductance (CVC) and skin temperature (Tsk) following local cooling and iii) systemic anti-inflammatory status. Following baseline testing, twenty-three individuals with RP attended four times, in a double-blind, randomized crossover design, following acute and chronic (14 days) BJ and nitrate-depleted beetroot juice (NDBJ) supplementation. Peripheral Tsk and CVC were measured during and after mild hand and foot cooling, and during transdermal delivery of acetylcholine and sodium nitroprusside. Markers of anti-inflammatory status were also measured. Plasma [nitrite] was increased in the BJ conditions (P 0.05). Plasma [interleukin-10] was greater, pan endothelin and systolic and diastolic blood pressure (BP) were reduced, and forearm endothelial function was improved ,by both BR and NDBJ supplementation (P < 0.05). Acute and chronic BJ and NDBJ supplementation improved anti-inflammatory status, endothelial function and BP. CVC following cooling increased post chronic-BJ and chronic-NDBJ supplementation, but no effect on Tsk was observed

A workflow of the gene expression analysis.

<p>The gene expression data were analysed to produce a list of fatigue-related features which were used as inputs for a support vector machine classifier of fatigue. 1. Differentially expressed genes were identified between fatigue groups. 2. Linear regression was used to analyse fatigue as a continuous variable. 3. The interferon type I signature was calculated for all the patients and compared to fatigue levels. 4. Gene set enrichment analysis was carried out using the high and low fatigue groups. 5. A support vector machine classifier was created using fatigue-related features as inputs and its performance assessed using receiver-operator characteristic (ROC) curves.</p

Interferon type I signature and fatigue.

<p>(A) The IFN score ranges for the 133 patients. (B) The Fatigue VAS scores for the IFN-active and IFN-inactive groups. (C) The ESSDAI scores for the IFN-active and IFN-inactive groups.</p

Correction for other clinical factors.

<p>Volcano plots for the Fatigue VAS fatigue groups corrected for clinical factors: (A) Age at UKPSSR cohort recruitment. (B) Disease activity measured using the EULAR Sjögren’s Syndrome Disease Activity Index. (C) Disease damage measured using the Sjögren’s Syndrome Disease Damage Index. (D) The EULAR Sjögren’s Syndrome Patient Reported Index dryness sub-domain. (E) The EULAR Sjögren’s Syndrome Patient Reported Index pain sub-domain. (F) Anxiety measured using the Hospital Anxiety and Depression scale. (G) Depression measured using the Hospital Anxiety and Depression scale. (H) Pain and depression (E & G). (I) Pain, depression, dryness and anxiety (D-G). (J) All seven factors (A-G). No significantly differentially expressed genes were identified following any correction.</p

Support vector machine (SVM) classification of fatigue groups.

<p>The receiver operator characteristic curves for the SVM output. Ten curves are shown on each plot. The area under the curve (AUC) is calculated as the mean over the ten curves. (A) All 181 enriched pathway genes as input. (B) The 55 leading edge genes as input.</p

The characteristics of the patients.

<p>A heatmap of the clinical scores for the 133 patients included in this study. The values have been scaled between zero (absent) and one (worst). ESSDAI = EULAR Sjögren’s Syndrome Disease Activity Index, SSDDI = Sjögren’s Syndrome Disease Damage Index, ESSPRI = EULAR Sjögren’s Syndrome Patient Reported Index, HAD = Hospital Anxiety and Depression, PROFAD = Profile of Fatigue and Discomfort, VAS = Visual Analogue Scale.</p