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Comparative Study
. 2021 Sep 21;11(1):18748.
doi: 10.1038/s41598-021-97349-6.

Comparison of dimension reduction methods on fatty acids food source study

Yifan Chen  1 , Yusuke Miura  2 , Toshihiro Sakurai  1 , Zhen Chen  1 , Rojeet Shrestha  3 , Sota Kato  1 , Emiko Okada  4 , Shigekazu Ukawa  5 , Takafumi Nakagawa  6 , Koshi Nakamura  7 , Akiko Tamakoshi  8 , Hitoshi Chiba  9 , Hideyuki Imai  10 , Hiroyuki Minami  11 , Masahiro Mizuta  11 , Shu-Ping Hui  12
Affiliations
Comparative Study

Comparison of dimension reduction methods on fatty acids food source study

Yifan Chen et al. Sci Rep. .

Abstract

Serum fatty acids (FAs) exist in the four lipid fractions of triglycerides (TGs), phospholipids (PLs), cholesteryl esters (CEs) and free fatty acids (FFAs). Total fatty acids (TFAs) indicate the sum of FAs in them. In this study, four statistical analysis methods, which are independent component analysis (ICA), factor analysis, common principal component analysis (CPCA) and principal component analysis (PCA), were conducted to uncover food sources of FAs among the four lipid fractions (CE, FFA, and TG + PL). Among the methods, ICA provided the most suggestive results. To distinguish the animal fat intake from endogenous fatty acids, FFA variables in ICA and factor analysis were studied. ICA provided more distinct suggestions of FA food sources (endogenous, plant oil intake, animal fat intake, and fish oil intake) than factor analysis. Moreover, ICA was discovered as a new approach to distinguish animal FAs from endogenous FAs, which will have an impact on epidemiological studies. In addition, the correlation coefficients between a published dataset of food FA compositions and the loading values obtained in the present ICA study suggested specific foods as serum FA sources. In conclusion, we found that ICA is a useful tool to uncover food sources of serum FAs.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Histograms of independent component analysis results, including (A) IC 1, (B) variance of variables, (C) IC 2, (D) IC 3, (E) IC 4, and (F) IC 5. The omega groups of FAs were omitted.
Figure 2
Figure 2
Histograms of factor analysis results, including (A) Factor 1, (B) Factor 2, (C) Factor 3, (D) Factor 4, (E) Factor 5, and (F) Factor 6.
Figure 3
Figure 3
Histograms of CPCA results, including (A) CPC1, (B) CPC2, (C) CPC3, and (D) CPC4.
Figure 4
Figure 4
Histograms of PCA results, including (A) PC1, (B) PC2, (C) PC3, and (D) PC4.
Figure 5
Figure 5
Diagram of suggested food sources. We calculated the correlation coefficients (CCs) between the loading values in the ICA results and the published FA composition in foods. Then, we selected the foods with the top 10 highest CCs in four major food sources of animal meats (A), plants (B), dairy products (C), and marine foods (D).
See this image and copyright information in PMC

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