Impact of Metabolic Syndrome on Flu Vaccine Efficacy

Metabolic syndrome (MetS) is a cluster of metabolic conditions associated with obesity that predispose individuals to coronary heart diseases and diabetes but obesity has been shown to increase the risks of other diseases like cancer and asthma. Studies have also shown that obesity increases the risk of severe influenza infection and associated death and reduces the efficacy of influenza vaccine in the obese population but yet, the molecular mechanisms have not been described. The investigators are thus hypothesizing that differences in the innate immune responses between individual with or without metabolic syndrome impact viral infection and vaccine outcome. The investigators will perform seasonal influenza vaccination in people with or without metabolic syndrome to determine if the late adaptive response assessed by antibodies titers is different between the two groups and correlates with the early immune response assessed by gene expression profile in whole blood cells. The project proposed by the investigators will contribute to a better understanding of the inflammatory phenotype associated with metabolic syndrome and establish for the first time if it affects the immune protection against infectious diseases and particularly against influenza virus infection. The results will be important to determine if the population affected by metabolic syndrome should receive anti-influenza treatment in priority in the context of a severe influenza epidemic.

Study Overview

• Status: Terminated
• Conditions: Metabolic Syndrome; Immune Deficiency
• Intervention / Treatment: Biological: Influenza vaccine

Detailed Description

The development of industrialization with increased food consumption and sedentarity has given rise to an obesity pandemic, which affects up to 30% of the population in countries like US, these populations being at greater risk for cardiovascular diseases, and diabetes. More than obesity per se, visceral obesity is associated with metabolic diseases that cluster together and clinically defined metabolic syndrome. MetS comprises individuals with at least three of the 5 of the following factors: abdominal obesity, high blood triglycerides, low HDL ("good cholesterol"), high blood pressure and elevated fasting glucose. Metabolic syndrome is associated with a low-grade inflammation characterized by an infiltration of immune cells particularly in the adipose tissue, the liver and the pancreas that is thought to be responsible for the induction of insulin resistance. It is thought that obesity predisposes to other diseases such as cancer, asthma but only little attention has been given to infectious diseases. Studies have shown that obesity increases the risk of severe influenza infection and associated death and reduces the efficacy of influenza vaccine in the obese population but yet, the molecular mechanisms have not been described. Immune dysfunctions associated with obesity are suspected to play a major role but obesity is often associated with respiratory disorders that could directly explain the increased susceptibility to influenza infection. Also, metabolically healthy obesity is less associated with inflammation. Therefore, the investigators would like to focus particularly on metabolic syndrome, and determine how it influences immune response to viruses.

The investigators are thus hypothesizing that differences in the innate immune responses between individual with or without metabolic syndrome impact viral infection and vaccine outcome. Recent studies involving complex biological analysis and computational modeling have shown that the ability of an individual to positively respond to influenza vaccine can be molecularly predicted by looking at markers in the blood cells. The investigators will perform seasonal influenza vaccination in people with or without metabolic syndrome to determine if the late adaptive response assessed by antibodies titers is different between the two groups and correlates with the early immune response assessed by gene expression profile in whole blood cells.

Healthy nutritional habits along with increased physical activities should be best at preventing the development of metabolic syndrome but socio-economical issues are slowing the implementation of these changes. Therefore, as metabolic syndrome is raising public health concerns, it is important to understand why the metabolic syndrome affects susceptibility to diseases.

• Study Type: Interventional
• Enrollment (Actual): 17
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • New York
    • New York, New York, United States, 10065
      • Rockefeller University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 65 years (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

Description

Inclusion criteria for the METABOLIC SYNDROME COHORT( Participants must have 3 or more of the following 5 risk factors):

• Abdominal Obesity, given as a waist circumference: Men >102 cm (>40 in) Women > 88 cm (>35 in)
• Triglycerides >150 mg/dl
• HDL Cholesterol: Men < 40 mg/dl Women < 50 mg/dl
• Blood Pressure >130/ >85 mm Hg - or controlled on antihypertensive medication
• Fasting Glucose > 100 mg/dl

Inclusion criteria for the HEALTHY CONTROLS (Participants must have all of the requirements below) :

• body mass index 18.5 - 25 kg/m2
• HDL female > 50 mg/dL, male > 40 mg/dL
• fasting glucose < 100 mg/dL
• triglycerides <150 mg/dL,
• waist circumference of a female < 88 cm, male < 102 cm)
• - Blood pressure < or = to 120/80 (based on an average of 3 readings taken 5 minutes apart after the consent form has been signed)

Exclusion criteria :

• Currently undergoing treatment for the metabolic syndrome
• The average of 2 BP readings > 150/90 (based on 2 B/Ps taken at screening visit 1).
• Hepatitis A, B and C
• NSAIDs and/or Aspirin ingestion within the last 14 days
• Self-reported history of any active autoimmune diseases
• Self-reported ingestion of statins within the last 3 months
• Self-reported antibiotic use within the last 3 months
• Anti-inflammatory drugs including biologics and corticosteroids within last 3 months( nasal spray and topical applications are OK)or Omega 3 Fatty Acids.
• Self-reported hx of cancer treatment within the last year
• Allergy to eggs
• History of Guillain-Barre syndrome
• Pregnant ( determined by point of care testing at screening visit 1).
• HIV positive
• Self-reported history of flu vaccination within the past 3 months.
• Any self-reported infection in the week of the visit except the first two visits (Screening visit 1 and Screening visit 2) and the last visit (Study visit #5) that could be rescheduled.
• Any medical, psychological or social condition that, in the opinion of the Investigator, would jeopardize the health or well-being of the participant during any study procedures or the integrity of the data.

Study Population Description The population from which the groups will be selected are resident of New York City.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Basic Science
• Allocation: Non-Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Influenza vaccine in metabolic syndrome; Influenza vaccine	Biological: Influenza vaccine; Influenza vaccine administered intramuscularly (IM), 1 time only, on visit 3
Experimental: Influenza vaccine in healthy controls; Influenza vaccine	Biological: Influenza vaccine; Influenza vaccine administered intramuscularly (IM), 1 time only, on visit 3

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Antibody Response D28	Measured by hemagglutination inhibition assay	28 days after vaccination compare to baseline (screening visit 1) pre-vaccination

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Gene Expression Profiling D1	Analyze by RNA-seq	1 day post-vaccination compare to baseline (gene expression screening visit #1 and study visit #1 D0 of vaccination)
Gene Expression Profiling D28	Analyze by RNA-seq	28 days post-vaccination compare to baseline (gene expression screening visit #1 and study visit #1 D0 of vaccination)
Gene Expression Profiling D90	Analyze by RNA-seq	90 days post-vaccination compare to baseline (gene expression screening visit #1 and study visit #1 D0 of vaccination)
Antibody Response D90	Measured by hemagglutination inhibition assay	90 days after vaccination compare to day 28

Collaborators and Investigators

• Sponsor: Rockefeller University
• Investigators: Principal Investigator: Ursula Andreo, PhD, The Rockefeller University Center for Clinical and Translational

Study record dates

Study Major Dates

• Study Start: January 1, 2016
• Primary Completion (Actual): March 1, 2017
• Study Completion (Actual): March 1, 2017

Study Registration Dates

• First Submitted: January 8, 2016
• First Submitted That Met QC Criteria: January 8, 2016
• First Posted (Estimate): January 12, 2016

Study Record Updates

• Last Update Posted (Actual): September 28, 2017
• Last Update Submitted That Met QC Criteria: September 1, 2017
• Last Verified: September 1, 2017

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Glucose Metabolism Disorders; Metabolic Diseases; Immune System Diseases; Disease; Insulin Resistance; Hyperinsulinism; Syndrome; Metabolic Syndrome; Immunologic Deficiency Syndromes
• Other Study ID Numbers: UAN-0891

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO