Predicting total, abdominal, visceral and hepatic adiposity with circulating biomarkers in Caucasian and Japanese American women.
BACKGROUND
Characterization of abdominal and intra-abdominal fat requires imaging, and thus is not feasible in large epidemiologic studies.


OBJECTIVE
We investigated whether biomarkers may complement anthropometry (body mass index [BMI], waist circumference [WC], and waist-hip ratio [WHR]) in predicting the size of the body fat compartments by analyzing blood biomarkers, including adipocytokines, insulin resistance markers, sex steroid hormones, lipids, liver enzymes and gastro-neuropeptides.


METHODS
Fasting levels of 58 blood markers were analyzed in 60 healthy, Caucasian or Japanese American postmenopausal women who underwent anthropometric measurements, dual energy X-ray absorptiometry (DXA), and abdominal magnetic resonance imaging. Total, abdominal, visceral and hepatic adiposity were predicted based on anthropometry and the biomarkers using Random Forest models.


RESULTS
Total body fat was well predicted by anthropometry alone (R(2) = 0.85), by the 5 best predictors from the biomarker model alone (leptin, leptin-adiponectin ratio [LAR], free estradiol, plasminogen activator inhibitor-1 [PAI1], alanine transaminase [ALT]; R(2) = 0.69), or by combining these 5 biomarkers with anthropometry (R(2) = 0.91). Abdominal adiposity (DXA trunk-to-periphery fat ratio) was better predicted by combining the two types of predictors (R(2) = 0.58) than by anthropometry alone (R(2) = 0.53) or the 5 best biomarkers alone (25(OH)-vitamin D(3), insulin-like growth factor binding protein-1 [IGFBP1], uric acid, soluble leptin receptor [sLEPR], Coenzyme Q10; R(2) = 0.35). Similarly, visceral fat was slightly better predicted by combining the predictors (R(2) = 0.68) than by anthropometry alone (R(2) = 0.65) or the 5 best biomarker predictors alone (leptin, C-reactive protein [CRP], LAR, lycopene, vitamin D(3); R(2) = 0.58). Percent liver fat was predicted better by the 5 best biomarker predictors (insulin, sex hormone binding globulin [SHBG], LAR, alpha-tocopherol, PAI1; R(2) = 0.42) or by combining the predictors (R(2) = 0.44) than by anthropometry alone (R(2) = 0.29).


CONCLUSIONS
The predictive ability of anthropometry for body fat distribution may be enhanced by measuring a small number of biomarkers. Studies to replicate these data in men and other ethnic groups are warranted.
Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America. ulim@cc.hawaii.edu
Unhee
U
Lim
Stephen D
SD
Turner
Adrian A
AA
Franke
Robert V
RV
Cooney
Lynne R
LR
Wilkens
Thomas
T
Ernst
Cheryl L
CL
Albright
Rachel
R
Novotny
Linda
L
Chang
Laurence N
LN
Kolonel
Suzanne P
SP
Murphy
Loïc
L
Le Marchand
D050153:Abdominal Fat / Q000378:metabolism*; D015502:Absorptiometry, Photon / Q000379:methods; D050154:Adiposity / Q000208:ethnology; D000368:Aged; D000886:Anthropometry; D001213:Asian; D015415:Biomarkers / Q000097:blood*; D015992:Body Mass Index; D015331:Cohort Studies; D005260:Female; D006254:Hawaii; D006801:Humans; D050152:Intra-Abdominal Fat / Q000378:metabolism*; D007564:Japan; D008099:Liver / Q000378:metabolism*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000097:blood / Q000175:diagnosis / Q000208:ethnology; D011237:Predictive Value of Tests; D044465:White People
D015415:Biomarkers