Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight

Table 2

Best multiple linear regression models explaining blood lipid levels as dependent variables.

	TC		LDL-c		HDL-c		TG
Predictors		PC^2		PC^2		PC^2		PC^2
Age (years)	0.80 ± 0.19	0.06	0.58 ± 0.18	0.04	0.22 ± 0.07	0.04
Sex					4.51 ± 1.98	0.02
Energy intake (100 kcal)	0.38 ± 0.21	0.01			0.18 ± 0.12	0.009
Protein intake (%)					0.93 ± 0.30	0.04
Cholesterol intake (mg)					−0.01 ± 0.004	0.02
Alcohol					5.83 ± 2.05	0.03	−19.21 ± 9.33	0.02
TFAT (kg)							−1.14 ± 0.42	0.03
VFAT (kg)					−5.22 ± 1.05	0.09	30.95 ± 3.92	0.20
GRS_TC	6.55 ± 0.83	0.18
GRS_LDL-c			6.79 ± 0.87	0.18
GRS_HDL-c					−1.12 ± 0.27	0.06
GRS_TG							4.20 ± 0.97	0.07
Constant	93.40 ± 12.99		45.74 ± 11.43		42.72 ± 7.71		61.58 ± 17.31
	0.2578		0.2217		0.3394		0.2828
Adj.	0.2501		0.2160		0.3192		0.2715
Optimism correction coefficient for	0.0112		0.0083		0.0373		0.0211
Optimism correction coefficient for adj.	0.0113		0.0084		0.0384		0.0214
Optimism-corrected	0.2466		0.2134		0.3021		0.2617
Optimism-corrected adj.	0.2388		0.2076		0.2808		0.2501

Data are expressed as values ± standard errors. The best models for each lipid phenotype were TC (BSRP, AIC/AICC); LDL-c (BSRP, BIC); HDL (BSRP, AICC); TG (BSM). BSRP: best subset regression procedure; AIC: akaike information criterion; AICC: corrected akaike information criterion; BIC: bayesian information criterion; BSM: bootstrapping stepwise method; PC²: squared partial correlation; TC: total cholesterol; LDL-c: low-density lipoprotein cholesterol; HDL-c: high-density lipoprotein cholesterol; TG: triglycerides; TFAT: total body fat; VFAT: visceral fat; GRS_TC: genetic risk score for total cholesterol; GRS_LDL-c: genetic risk score for low-density lipoprotein cholesterol; GRS_HDL-c: genetic risk score for high-density lipoprotein cholesterol; GRS_TG: genetic risk score for triglycerides.