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. 2021 Apr 22;16(4):e0250864. doi: 10.1371/journal.pone.0250864

Correction: Charged metabolite biomarkers of food intake assessed via plasma metabolomics in a population-based observational study in Japan

Eriko Shibutami, Ryota Ishii, Sei Harada, Ayako Kurihara, Kazuyo Kuwabara, Suzuka Kato, Miho Iida, Miki Akiyama, Daisuke Sugiyama, Akiyoshi Hirayama, Asako Sato, Kaori Amano, Masahiro Sugimoto, Tomoyoshi Soga, Masaru Tomita, Toru Takebayashi
PMCID: PMC8062029  PMID: 33886678

In Table 2, the mean (10th-90th range)a of Rice for Male should be (250–680). Please see the correct Table 2 here.

Table 2. Food classification and population intake status.

Food group Food item on FFQ Mean (10th-90th range)a
All Male Female
n = 7,012 n = 3,198 n = 3,814
Energy-giving foods
Rice Rice g/d 394 (188-600) 485 (250-680) 317 (165-450)
Other grains/potatoes Bread, noodles, soba, potatoes g/d 129 (72-204) 131 (68-215) 127 (72-195)
Confectionery Cake, Japanese traditional sweets g/d 21 (7-42) 18 (7-28) 24 (10-47)
Oil Butter, margarine, mayonnaise, oil for deep fried/stir fried g/d 14 (6-24) 12 (5-22) 15 (6-25)
Protein-rich foods
Meat Beef/pork, chicken, liver, ham/sausage g/d 41 (17-69) 39 (17-69) 42 (17-70)
Fish/seafood Fish, shellfish, squid/shrimp/crab/octopus, fish roe, processed fish food, canned tuna g/d 62 (28-98) 62 (28-100) 62 (27-97)
Eggs Eggs g/d 19 (4-40) 18 (4-40) 19 (8-40)
Dairy products Milk, yogurt g/d 122 (13-255) 99 (13-210) 142 (26-255)
Soy products Soybeans, tofu, fermented soy food, fried soy product g/d 112 (41-195) 111 (41-195) 113 (42-194)
Fruits/vegetables
Carotenoid-rich vegetables Pumpkin, carrot, broccoli, green leafy vegetables, other carotenoid-rich vegetables g/d 78 (27-146) 63 (22-116) 92 (34-166)
Other vegetables Cabbage, Japanese radish, dried radish, burdock, other light vegetables, mushroom g/d 78 (28-140) 61 (24-111) 93 (35-157)
Seaweed Seaweed g/d 2 (1-4) 2 (1-4) 2 (1-5)
Fruits Mandarin/orange/grapefruit, other fruits g/d 55 (13-125) 41 (13-89) 66 (17-136)
Seeds Peanuts/almond g/d 3 (1-4) 3 (1-4) 3 (1-4)
Beverages
Green tea Green tea g/d 230 (11-600) 220 (11-660) 239 (10-600)
Coffee Coffee g/d 146 (10-300) 134 (10-300) 156 (10-300)
Alcoholb Sake, beer, whiskey, wine, shochu, chuhai g/d 106 (0-377) 199 (0-480) 29 (0-93)

FFQ, food frequency questionnaire.

a Values are presented as mean and 10th-90th percentiles in parentheses.

b Values are calculated according to the percentage of ethanol and shown in comparison to sake.

In Table 3, the Q2cumc for Eggs should be (0.02). Please see the correct Table 3 here.

Table 3. Promising food biomarker candidates (n = 7,012).

Food group Metabolite Sub Classa PLS-Rb rsd
VIP Coeff Q2cumc
    Meat
  Hydroxyproline AA 2.66 0.07 0.07 0.09
  3-Methylhistidine AA 2.11 0.06 0.08
  beta-Alanine AA 2.05 0.05 0.04
  2-Aminobutyrate AA 2.01 0.05 0.05
  Creatine AA 1.99 0.06 0.05
  Carnitine AA 1.70 0.04 0.03
    Fish/seafood
  Creatine AA 3.19 0.10 0.21 0.18
  Trimethylamine-N-oxide AO 2.63 0.09 0.15
  Cystine AA 2.26 0.07 0.12
  2-Hydroxybutyrate AA 1.73 0.04 0.11
  Isethionate AHA 1.55 0.03 0.08
  Glucuronate CHO 1.43 0.04 0.13
  2-Aminobutyrate AA 1.36 0.03 0.07
  Uridine PN 1.32 0.03 0.06
  Guanidinosuccinate AA 1.21 0.02 0.07
    Eggs
  Choline QA 2.88 0.05 0.01 (0.02) 0.06
  2-Aminobutyrate AA 2.40 0.04 0.04
  Betaine AA 2.14 0.04 0.05
  Asparagine AA 1.66 0.02 0.02
    Dairy
  Galactarate CHO 2.14 0.08 0.33 0.09
  Threonate CHO 1.97 0.07 0.09
  Phenylalanine AA 1.95 0.08 0.08
  Lysine AA 1.60 0.04 0.05
  Tyrosine AA 1.53 0.04 0.02
  Citrate TCA 1.47 0.07 0.07
  Tryptophan AA 1.44 0.02 0.03
  2-Aminobutyrate AA 1.31 0.05 0.07
  Hippurate BA 1.27 0.05 0.08
  Creatine AA 1.24 0.03 0.02
    Soy products
  Cystine AA 1.73 0.07 0.23 0.08
  Betaine AA 1.53 0.06 0.07
  Isethionate TCA 1.34 0.02 0.09
  Creatine AA 1.34 0.05 0.08
  Uridine PN 1.30 0.04 0.06
  Citrate AA 1.25 0.04 0.06
  Phenylalanine AA 1.25 0.03 -0.02
  Glutamine AA 1.25 0.04 0.05
    Carotenoid-rich vegetables
  Threonate CHO 2.23 0.07 0.28 0.09
  Galactarate CHO 2.06 0.06 0.07
  Creatine AA 1.80 0.06 0.05
  Lysine AA 1.44 0.02 0.03
  Cystine AA 1.40 0.04 0.07
  Citrate TCA 1.33 0.04 0.06
  Hippurate BA 1.29 0.04 0.07
    Other vegetables
  Creatine AA 2.00 0.07 0.31 0.05
  Threonate CH 1.85 0.05 0.06
  Galactarate CH 1.51 0.04 0.02
  Cystine AA 1.40 0.04 0.06
    Fruits
  Proline betaine AA 3.80 0.23 0.47 0.27
  Threonate CHO 2.30 0.09 0.15
  Galactarate CHO 1.95 0.07 0.11
  Tyrosine AA 1.49 0.03 0.00
  Lysine AA 1.43 0.02 0.03
  Cystine AA 1.29 0.04 0.06
  Creatine AA 1.29 0.06 0.04
  Citrate TCA 1.21 0.05 0.06
    Green tea
  Threonate CHO 3.54 0.06 0.05 0.11
  Galactarate CHO 3.15 0.06 0.08
  Cystine AA 1.93 0.04 0.07
  Creatine AA 1.87 0.03 0.06
  2-Aminobutyrate AA 1.74 0.03 0.06
  Trimethylamine-N-oxide AO 1.71 0.03 0.07
  Proline betaine AA 1.68 0.03 0.05
  2-Hydroxybutyrate AA 1.29 0.02 0.06
    Coffee
  Quinate ALC 4.59 0.29 0.55 0.39
  Trigonelline AL 3.13 0.17 0.28
  Hippurate BA 1.88 0.07 0.17
  Leucine AA 1.34 0.02 0.01
    Alcohole
  Pipecolate AA 2.78 0.17 0.53 0.26
  2-Aminobutyrate AA 1.92 0.12 0.17
  Choline QA 1.87 0.09 0.15
  Threonine AA 1.65 0.09 0.10
  Carnitine AA 1.41 0.07 0.09
  Tyrosine AA 1.34 0.06 0.08
  Malate BHA 1.30 0.08 0.14
  Creatine AA 1.24 0.04 0.09

PLS-R, partial least square regression; VIP, variable importance in projection; AA, amino acids, peptides, and analogs; CHO, carbohydrates and carbohydrate conjugates; AO, aminoxides; AHA, alpha-hydroxy acids and derivatives; PN, pyrimidine nucleosides; QA, quaternary ammonium salts; TCA, tricarboxylic acids and derivatives; BA, benzoic acids and derivatives; ALC, alcohols and polyols, and polyols; BHA, beta-hydroxy acids and derivatives.

a Reference: The Human Metabolome Database (https://hmdb.ca)

b Metabolites which indicate VIP scores ≥ 1.2 and positive PLS coefficients ≥ 0.02 are shown.

c Cumulative predicted variation in the Y matrix for optimal factor numbers, calculated as 1 –(the cumulative predicted residual sum of squares / the cumulative sum of squares). The value indicates the predictive performance of the model. For cases with an optimal factor number of less than two, the factor number was set to two and the result was shown in parentheses.

d Partial rank-order Spearman’s correlation coefficients between food consumption and metabolite concentration, controlling for sex, smoking, and physical activity levels.

e Data of male drinkers (n = 2,449) were used in the analysis.

Reference

  • 1.Shibutami E, Ishii R, Harada S, Kurihara A, Kuwabara K, Kato S, et al. (2021) Charged metabolite biomarkers of food intake assessed via plasma metabolomics in a population-based observational study in Japan. PLoS ONE 16(2): e0246456. 10.1371/journal.pone.0246456 [DOI] [PMC free article] [PubMed] [Google Scholar]

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