title: CD14dimCD16+ and CD14+CD16+ monocytes in obesity and during weight loss: relationships with fat mass and subclinical atherosclerosis.
abstract: OBJECTIVE
  Studies suggest the implication of CD16(+) subpopulations (CD14(+)CD16(+), CD14(dim)CD16(+)) in inflammatory diseases. We aimed to determine the frequency of these subpopulations during weight loss in obesity and diabetes, conditions associated with changes in systemic inflammation, and we tested the link with subclinical atherosclerosis.
  
  
  RESULTS
  CD14(dim)CD16(+) and CD14(+)CD16(+) frequencies were measured by flow cytometry in lean subjects, obese subjects before and after a hypocaloric diet or gastric surgery, and obese diabetic subjects before and after gastric surgery. Both monocyte subsets were increased in obese subjects, with a significant enrichment of the CD14(dim)CD16(+) subpopulation in obese diabetic patients. Multivariate analysis demonstrated a link between the percentages of CD14(dim)CD16(+) monocytes and glycemia, independent of fat mass. Drastic weight loss led to a sharp decrease of this subset, the variations of which were strongly related to fat mass changes. A reduction of at least 5% of fat mass was sufficient to observe a significant decrease of CD14(dim)CD16(+) monocytes. A diminution of the CD14(+)CD16(+) subset was also observed during weight loss and was associated with a decrease in intima-media thickness.
  
  
  CONCLUSIONS
  This work demonstrates a major impact of fat mass variations on CD14(dim)CD16(+) monocyte subsets and that the decrease in the CD14(+)CD16(+) subpopulation is linked to a reduction of subclinical atherosclerosis.
  
  
  BACKGROUND
  URL: http://clinicaltrials.gov. Unique identifier: NCT00476658.
authors.affiliation: Institut National de la Santé et de la Recherche Médicale, U, Cordeliers Research Center, Paris, France. bernert@psl.aphp.fr
authors.forename: Christine
authors.initials: C
authors.lastname: Poitou
authors.forename: Elise
authors.initials: E
authors.lastname: Dalmas
authors.forename: Mariana
authors.initials: M
authors.lastname: Renovato
authors.forename: Vanessa
authors.initials: V
authors.lastname: Benhamo
authors.forename: Froogh
authors.initials: F
authors.lastname: Hajduch
authors.forename: Meriem
authors.initials: M
authors.lastname: Abdennour
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Kahn
authors.forename: Nicolas
authors.initials: N
authors.lastname: Veyrie
authors.forename: Salwa
authors.initials: S
authors.lastname: Rizkalla
authors.forename: Wolf-Hervé
authors.initials: WH
authors.lastname: Fridman
authors.forename: Catherine
authors.initials: C
authors.lastname: Sautès-Fridman
authors.forename: Karine
authors.initials: K
authors.lastname: Clément
authors.forename: Isabelle
authors.initials: I
authors.lastname: Cremer
mesh_terms: D015502:Absorptiometry, Photon; D050154:Adiposity; D000328:Adult; D000704:Analysis of Variance; D058070:Asymptomatic Diseases; D050197:Atherosclerosis / Q000000981:diagnostic imaging / Q000188:drug therapy / Q000276:immunology*; D031204:Caloric Restriction; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000188:drug therapy / Q000276:immunology*; D005260:Female; D005434:Flow Cytometry; D005602:France; D058851:GPI-Linked Proteins / Q000097:blood; D015390:Gastric Bypass; D006801:Humans; D018950:Lipopolysaccharide Receptors / Q000097:blood*; D008297:Male; D008875:Middle Aged; D009000:Monocytes / Q000276:immunology*; D009765:Obesity / Q000276:immunology / Q000503:physiopathology / Q000628:therapy*; D011446:Prospective Studies; D017452:Receptors, IgG / Q000097:blood*; D012044:Regression Analysis; D013997:Time Factors; D016896:Treatment Outcome; D014463:Ultrasonography; D015431:Weight Loss
chemical_list: C428200:FCGR3B protein, human; D058851:GPI-Linked Proteins; D018950:Lipopolysaccharide Receptors; D017452:Receptors, IgG