Adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men

TY - JOUR

T1 - Adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men

AU - Rawshani, Aidin

AU - Eliasson, Björn

AU - Rawshani, Araz

AU - Henninger, Josefin

AU - Mardinoglu, Adil

AU - Carlsson, Åsa

AU - Sohlin, Maja

AU - Ljungberg, Maria

AU - Hammarstedt, Ann

AU - Rosengren, Annika

AU - Smith, Ulf

PY - 2020/12/1

Y1 - 2020/12/1

N2 - We evaluated the importance of body composition, amount of subcutaneous and visceral fat, liver and heart ectopic fat, adipose tissue distribution and cell size as predictors of cardio-metabolic risk in 53 non-obese male individuals. Known family history of type 2 diabetes was identified in 25 individuals. The participants also underwent extensive phenotyping together with measuring different biomarkers and non-targeted serum metabolomics. We used ensemble learning and other machine learning approaches to identify predictors with considerable relative importance and their intricate interactions. Visceral fat and age were strong individual predictors of ectopic fat accumulation in liver and heart along with markers of lipid oxidation and reduced glucose tolerance. Subcutaneous adipose cell size was the strongest individual predictor of whole-body insulin sensitivity and also a marker of visceral and ectopic fat accumulation. The metabolite 3-MOB along with related branched-chain amino acids demonstrated strong predictability for family history of type 2 diabetes.

AB - We evaluated the importance of body composition, amount of subcutaneous and visceral fat, liver and heart ectopic fat, adipose tissue distribution and cell size as predictors of cardio-metabolic risk in 53 non-obese male individuals. Known family history of type 2 diabetes was identified in 25 individuals. The participants also underwent extensive phenotyping together with measuring different biomarkers and non-targeted serum metabolomics. We used ensemble learning and other machine learning approaches to identify predictors with considerable relative importance and their intricate interactions. Visceral fat and age were strong individual predictors of ectopic fat accumulation in liver and heart along with markers of lipid oxidation and reduced glucose tolerance. Subcutaneous adipose cell size was the strongest individual predictor of whole-body insulin sensitivity and also a marker of visceral and ectopic fat accumulation. The metabolite 3-MOB along with related branched-chain amino acids demonstrated strong predictability for family history of type 2 diabetes.

UR - http://www.scopus.com/inward/record.url?scp=85086674850&partnerID=8YFLogxK

U2 - 10.1038/s41598-020-66199-z

DO - 10.1038/s41598-020-66199-z

M3 - Article

C2 - 32561768

AN - SCOPUS:85086674850

SN - 2045-2322

VL - 10

JO - Scientific Reports

JF - Scientific Reports

IS - 1

M1 - 9973

ER -