title: Improved weight management using genetic information to personalize a calorie controlled diet.
abstract: BACKGROUND
  Gene-environment studies demonstrate variability in nutrient requirements depending upon individual variations in genes affecting nutrient metabolism and transport. This study investigated whether the inclusion of genetic information to personalize a patient's diet (nutrigenetics) could improve long term weight management.
  
  
  METHODS
  Patients with a history of failures at weight loss were offered a nutrigenetic test screening 24 variants in 19 genes involved in metabolism. 50 patients were in the nutrigenetic group and 43 patients attending the same clinic were selected for comparison using algorithms to match the characteristics: age, sex, frequency of clinical visits and BMI at initial clinic visit. The second group of 43 patients did not receive a nutrigenetic test. BMI reduction at 100 and > 300 days and blood fasting glucose were measured.
  
  
  RESULTS
  After 300 days of follow-up individuals in the nutrigenetic group were more likely to have maintained some weight loss (73%) than those in the comparison group (32%), resulting in an age and gender adjusted OR of 5.74 (95% CI 1.74-22.52). Average BMI reduction in the nutrigenetic group was 1.93 kg/m2(5.6% loss) vs. an average BMI gain of 0.51 kg/m2(2.2% gain) (p < 0.023). Among patients with a starting blood fasting glucose of > 100 mg/dL, 57% (17/30) of the nutrigenetic group but only 25% (4/16) of the non-tested group had levels reduced to < 100 mg/dL after > 90 days of weight management therapy (OR for lowering glucose to < 100 mg/dL due to diet = 1.98 95%CI 1.01, 3.87, p < 0.046).
  
  
  CONCLUSIONS
  Addition of nutrigenetically tailored diets resulted in better compliance, longer-term BMI reduction and improvements in blood glucose levels.
authors.affiliation: Sciona Inc, Boulder, 80302, Colorado, USA. idc.diet@eexi.gr
authors.forename: Ioannis
authors.initials: I
authors.lastname: Arkadianos
authors.forename: Ana M
authors.initials: AM
authors.lastname: Valdes
authors.forename: Efstathios
authors.initials: E
authors.lastname: Marinos
authors.forename: Anna
authors.initials: A
authors.lastname: Florou
authors.forename: Rosalynn D
authors.initials: RD
authors.lastname: Gill
authors.forename: Keith A
authors.initials: KA
authors.lastname: Grimaldi
mesh_terms: D000328:Adult; D000704:Analysis of Variance; D001786:Blood Glucose / Q000032:analysis / Q000378:metabolism*; D015992:Body Mass Index; D038441:Diet, Mediterranean; D004038:Diet, Reducing; D015444:Exercise / Q000502:physiology; D005260:Female; D020022:Genetic Predisposition to Disease; D005838:Genotype; D038321:Glycemic Index; D006801:Humans; D008297:Male; D008875:Middle Aged; D054647:Nutrigenomics / Q000379:methods*; D009751:Nutritional Requirements; D009765:Obesity / Q000178:diet therapy* / Q000235:genetics*; D010349:Patient Compliance; D013997:Time Factors; D016896:Treatment Outcome; D015431:Weight Loss
chemical_list: D001786:Blood Glucose