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University of North Carolina School of Public Health, Chapel Hill, NC 27955
2 To whom correspondence should be addressed. E-mail: LenoreA{at}unc.edu.
| ABSTRACT |
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KEY WORDS: biomarkers diet assessment epidemiology fat intake fatty acids nutrition
| Biomarkers of total fat intake |
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The tremendous interest in dietary fat intake and the controversy surrounding the effect of fat intake on chronic diseases and cancer, has heightened the desire for a biomarker that would closely reflect the fat intake of an individual. In addition to being so widely and massively dispersed throughout the diet, fat is also one of the most difficult dietary components to assess through traditional methods for several reasons. Fat is sometimes very difficult for an individual to recognize and quantify. For instance, fat used in food preparationfor frying and cooking or as sauces and dressingsis often added by someone other than the individual under study, making it nearly impossible to identify the source and brand of fat. Even if this were known, it would be particularly tedious to report in detail. In addition, the accuracy of reporting fat is especially prone to bias. Underreporting of fat intake is greater among individuals that are overweight because of social implications (1).
Despite calls for proposals to develop and validate dietary fat biomarkers, a biomarker of the absolute amount of fat consumed remains elusive. However, there are biomarkers that can be used to quantify circulation change in fat intake, as well as biomarkers that reflect the consumption of essential and nonessential exogenously produced fatty acids. Interpreting these biomarkers requires an understanding of fatty acid metabolism, exogenous factors and the contributions of various body pools.
| Fatty acid metabolism |
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The third major alteration of fatty acids within the body is through desaturation, resulting in the formulation of a double bond. The mammalian lack of a
12 desaturase prevents conversion of oleic acid into linoleic acid [(n-9) to (n-6) conversion]. Lack of the
15 desaturase prevents the conversion of linoleic into
-linolenic acid or the interconversion of (n-6) and (n-3) fatty acids in man. Plants can perform both of the conversions. Therefore dietary sources of these families of (n-6) and (n-3) fatty acids are the sole contributors to stores in man.
| Exogenously produced fatty acids |
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-linolenate, arachidonate or eicosapentanoate. The precursor fatty acid determines the product as seen in Figure 2.
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-linolenate and eicosapentanoate are the most prevalent in human tissues. After digestion, metabolism and selective storage affect fat tissue levels, the profile of adult body fat reflects the profile of these dietary fats. The factors influencing fatty acid profiles in adipose tissue are presented in Table 2 and discussed below.
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Half-lives of individual fatty acids in adipose tissue may differ. At best, one can judge from the few studies of turnover of linoleic acid in adipose tissue that the average half-life of fatty acids reflects an integrated measure over 12 y of intake (9). The degree to which adipose tissue levels of fatty acids correlate with reported dietary intakes can be seen in Table 3. With the strongest dietary assessment tools after deattenuation, the correlation coefficients are as low as 0.26 for monounsaturated fats and as high as 0.80 for DHA, a metabolite of EPA. Direct comparability, as expressed by correlation coefficients close to one, cannot be expected for a number of reasons. One reason is that the biomarker is subject to absorption, metabolism and all of the factors that have an impact on metabolic efficiency. The medium being sampled is not necessarily a storage site for the nutrient, and the nutrient may have been utilized before reaching storage (as is the case of the circulating ß-carotene levels of smokers). Sampling, handling, storage and lab measurement contribute to some extent. Other discrepancies may be caused in part by measurement errors in reported dietary intakes of the daily and seasonal variations of habitual intake and sources of the adipose tissue and differences in utilization. The measurement error associated with dietary intake reports often includes difficulty in identifying fat sources, particularly for foods not prepared at home. Also included is error in the inference of fat composition of reported foods based on database values of food composition that generally exceed the measurement error of biomarkers. As seen in Table 3, the exogenously produced fatty acid biomarkers are more closely associated with dietary reports than are the groups of fats (e.g., saturated fatty acids), which can be synthesized endogenously.
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| Short-, medium-, and long-chain fatty acids |
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| Trans fatty acids |
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5% of total fat stores. Mean adipose tissue levels are lower in many European countries than in the U.S. (11). The most commonly found trans fat is the 18:1(n-9): elaidic acid. Trans fats are roughly similar to saturated fats in their three-dimensional spatial configuration but are not as precisely aligned. Their biological activity may stem from their effective competition with other fatty acids for desaturase enzymes. | Monounsaturated fats |
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Most of the studies of monounsaturated fats are based upon intake of olive oila rich source of oleic acid and the principal monounsaturated fatty acid in the Western diet. Canola oil is also a rich dietary source of this fat. When biomarkers of oleic acid are studied, the results are not consistent with an oleic acid effect independent of olive oil as a dietary source (12).
| Polyunsaturated fats |
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| Omega-6 (n-6) fatty acids/arachidonic acid |
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-linolenic acid [(18:3(n-6)].
Arachidonic acid is stored in cell membranes and can be mobilized by phospholipids. It can be released in response to injury. Arachidonic acid is regulated well within the body and is the principle precursor in eicosanoid synthesis (3). Eicosanoids are fast-acting, high-potency hormones that are produced locally from free fatty acids and serve as second messengers. Seminal fluid is particularly rich in eicosanoids, 20-carbon metabolites of arachidonic acid, dihomo-
-linolenic acid or eicosapentanoic acid, which have been synthesized via cyclo-oxygenase or lipooxygenase pathways in microsomes. They are very complex in their activity because they can demonstrate biphasic responses depending upon concentrations. In addition, different eicosanoids arising from the same precursor fatty acid can have opposing actions. Prostacyclin and thromboxane A2 are examples of this because the former inhibits platelet aggregations and the latter stimulates platelet aggregation. Eicosanoids from different precursor fatty acids also tend to express contradictory effects, such as in the case of prostaglandin E1 and E2 effects described below. An overabundance of one precursor can drive down production of the products of another.
| Omega-3 (n-3) fatty acids |
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| Conjugated linoleic acid |
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| Measurement of fatty acid |
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Thin layer chromatography or silica cartridges are used to separate the lipid fractions. Then either GC, HPLC or gas liquid chromatography (GLC) are used to separate the individual fatty acids. This choice depends on the need for precise quantitative analyses of small proportions of the total fat, the volatility of the fatty acid, the comparison in mass between fatty acids of interest and the polarity of the compound availability of equipment and cost. Due to equipment and running costs of HPLC, GLCwhen performed in open-tubular columns of fused silicais less expensive (15). However, for isolation and separation of particular fatty acids, HPLC is preferred (15). HPLC is also carried out at ambient temperatures, which prevents the heat-related rearrangement of fatty acids with labile moieties (15). Most importantly these analyses must be carried out with the intent to minimize autooxidation of the samples (15). For this, blanketing with nitrogen is often chosen (15).
The identification of peaks through elution order is commonly based on relative retention times and equivalent chain lengths. This does not however allow for identification of unknown peaks. Flame ionization detectors (FIO) are used to ionize carbon-containing compounds and quantify the ions as they pass through the collector. Mass spectrometry (GC/MS) with a mass ion detector is more precise and can identify compounds based on their total mass; however it is still prohibitively expensive for use in large studies. GC works well for simple, shorter and volatile fatty acid mixtures. In addition, GC can afford the epidemiologist a total fatty acid profile in a single run by separating based on the fatty acid chain length, the number of double bonds and the positioning of these bonds. Polyunsaturated fatty acids are more effectively separated with HPLC (19).
The most challenging separations are those involving identification of individual cis- and trans-isomers of fatty acids and small peaks such as those from conjugated linoleic acid. These families of fatty acids are either of equivalent molecular weight or are present in very small fractions that call for longer columns and run times. Therefore, the choice of an analytic method depends on the need for precise quantitative analyses of small proportions of the total fat, the volatility of the fatty acid, the comparison in mass between fatty acids of interest and the polarity of the compound availability of equipment and cost.
Quantitation of the weight of specific fatty acids depends upon the addition of internal standards in known weights early in the analysis. These standards need to be similar in composition to the experimental sample.
| Factors influencing fatty acid measurements |
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Other factors, summarized in Table 2, can play a role in the inaccuracy of fatty acid measurement. Some functions occur before arrival of the sample for laboratory analysis. These include the sampling techniques and the handling and storage of the sample (20). For example, larger samples of adipose fat derived from surgery or punch biopsy are not as susceptible to the problems of detection limits. Inappropriate handling of the sample can result in oxidation of the polyunsaturated fatty acids through air exposure or contact with iron from erythrocytes. Samples stored for long periods of time before analysis, especially in a large study in which the samples are being run in a single laboratory, may suffer degeneration or the consequences of refrigeration loss (21). Long storage periods, resulting from a cohort or nested case-control design or simply from a backlog of samples to be analyzed, can result in changes in the profiles of the polyunsaturated fats, because these are temperature and oxygen sensitive. Careful storage under nitrogen gas and at -80°C will minimize this loss. The throughput for these analyses can be a limiting factor in sample turnover causing analyses in many cases to take months or even years to be completed. The tissue-sampling site can also have an impact on the values derived. For example, a comparison of fatty acid profiles from a deep-seated site (perirenal) and two subcutaneous sites (abdominal and buttocks) from autopsies of a racially mixed group of adults showed the proportion of saturated fatty acids to be highest in the perirenal adipose tissue and lowest in the buttock. Monounsaturated fatty acids were highest in the buttock (22). Abdominal tissue was more heavily saturated than the gluteal fat. The extremes of difference were as great as 40%. Polyunsaturated fatty acid profiles however were not significantly different across these three sites, which fortunately allows a choice of the most convenient sampling site. Another study comparing abdominal fat with fat from the inner and outer thigh showed higher levels of saturated fatty acid in the abdominal fat (23). In this study the polyunsaturated fat levels differed; the highest levels were in the outer thigh, the lowest levels were in the abdomen and in-between levels were in the inner thigh. These differences were as great as 30% for saturated fatty acids and 17% for the polyunsaturates.
Even if there were consistent and comparable mean levels of individual fatty acids across sites, it would be unwise to mix sites within a study. Nutritional status can also adversely influence the fatty acid profiles of the dietary fat intakes of individuals. Because the desaturases are metaloenzymes, adequate amounts of iron, zinc, copper and magnesium may be required for fatty acid metabolism to function normally.
| Interpretation of fatty acid concentrations |
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When adipose tissue concentrations are used, an extrapolation of total body stores (based upon measurement or estimation of total body fat) might be appropriate if the biomarker is to reflect total stores as a measure of prior intakes. Height and weight can be used to extrapolate the body fat pool using the formulas derived by Womersley (24). Multiplication of the concentration in adipose tissue by the estimated total body fat should result in an estimate of the total body burden of that fatty acid. This type of extrapolation is not possible with serum fatty acid measurement. Serum reflects recent intake, not long-term stores, and is poorly correlated with adipose tissue levels in most individuals (19,25).
| Fasting and weight gain |
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| Choice of a medium for biomarker-based measures of fatty acids |
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The shortest-term markers of fat intake are proportions of fatty acids in chylomicrons. These reflect the dietary fat intakes that enter the enterohepatic circulation directly after a meal. Other serum or plasma measures reflect the dietary intakes of the past few hours (triglyceride) or the past few days (cholesterol ester and phospholipid fatty acids) (28). Free fatty acids are bound to albumin and released from adipose when insulin and glucose are low. The plasma nonesterified fatty acid (NEFA) levels are largely determined by their rate of liberation from adipose tissue. Serum triglycerides are bound to apolipoproteins, and the rate of very low density lipoprotein secretion from the liver also influences circulating NEFA levels. Postprandially, these fatty acids are cleared to the adipose tissue under the action of lipoprotein lipase. Mobilization of adipose-tissue fatty acids is affected by hormone-sensitive lipase, lipoprotein lipase and fatty acid esterification (29).
The next most immediate biomarker medium is the serum or plasma levels of individual fatty acids, which can reflect intake over the last few days or meals. Serum fatty acids levels were shown to be sensitive indicators of changes in the polyunsaturated fat intakes of the diet (30,31). However serum triglyceride levels fluctuate greatly, with coefficients of variation of 1230% and with laboratory error accounting for less than 5% of the total variance (32,33). A single triglyceride measure, based on the experience of lipid research clinics, is likely to be only within 40% of the true average value for triglycerides, compared with 13% for cholesterol. Serum triglycerides may need an average of 10 baseline values to approach a coefficient of variance of 13% (28).
Red cell membranes and platelets are of interest as the biomarker media for fatty acid analyses because they reflect longer-term intake than circulating triglycerides but are still accessible through phlebotomy. Red cell membranes, for example, reflect intake aggregated over the lifespan of erythrocytes, or
120 d, the half-life of erythrocytes. Membrane lipids differ from storage lipids in that they contain a high proportion of long-chain polyunsaturated fatty acids and rarely include triglycerides. Red blood cells provide a marker reflecting the last month and offer a more aggregated time period than does serum. The method requires pretreatment (lysis), protection against oxidation and centrifuging before storage until the final gas chromatographic analyses can be undertaken. For the use of this medium, whole blood specimens that contain red blood cells are collected, suspended in phosphate buffer and centrifuged. After removal of plasma and buffer coat, the packed red cells are resuspended in buffer, and hematocrit is measured and recorded. The red blood cells may then be stored in a -80°C freezer where they can remain stable for upwards of 5 y (34,35). Red blood cell membrane phospholipids reflect fatty acid profiles of serum for saturated and monounsaturated fats but may contain lower levels of (n-3) and (n-6) fatty acids (19). The need for immediate and appropriate handling of this medium (membrane lysis and isolation) at the time of phlebotomy is a limitation (19,21,24,3639).
Adipose tissue is a preferred medium for the measurement of fatty acids as a reflection of long-term dietary intakes when no severe weight loss has occurred. Adipose tissue, be it gluteal, abdominal, subscapular, pectoral or from another site, reflects long-term storage of fats under homeostatic conditions. This is because of the oxidative, low fuel requirements of adipocytes and the large energy content. White adipose tissue is metabolically active. It controls the release of nonesterified fatty acids into the circulation and the uptake of dietary fatty acids into the adipocyte via lipoprotein lipase. However, because most populations studied are adequately to overly nourished, these influences do not have a strong impact on the stored fat profile.
The collection of adipose tissue, although still relatively unusual in the U.S., represents a safe and simple method of sample collection that is comparable to phlebotomy (8). Because there is no need for intact adipocytes, the tissue can be collected by aspiration using a 15-gauge needle with or without the use of local anesthesia (40). Training videos and complete methodologies on this are available from the author.
Fatty acid stores, both polyunsaturated and saturated, are likely to reflect more accurate dietary intakes under conditions of adequate nutrition or over-nutrition, lack of weight swings and good health. To some extent, age of the subject is relevant to the use of adipose tissue as a biomarker of exposure. Fat storage and release at birth and in early life (or adolescence) differ from later stages of development and adulthood. Pregnancy can also affect the fatty acid profiles of the mother, because deposition of fat is initially enhanced (40,41).
| Effects of disease on fatty acid profiles |
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More obvious are the effects of diseases, such as cystic fibrosis involving pancreatic insufficiency, malabsorption of fats and cirrhosis of the liver, which will affect lipoprotein production (44). Similarly, patients with other lipid metabolism disorders such as Zellweger Syndrome, where synthesis of DHA is impaired, would also have biomarker profiles biased by these diseases (43).
| Change in fat intake |
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Keys found that
y = 1.35(2
S -
P) + 1.5
Z where
S and P are the changes in saturated and polyunsaturated fatty acids as percentages of calories and
y is the change in plasma cholesterol in mg/dl (45). This can be rearranged to predict the change in saturated fat intake or polyunsaturated fat in an individual's diet based on knowledge of change in serum cholesterol assuming either that the other fats did not change or their amount of change is known. These formulas are then
S =
y - 1.5
z + 1.35
p/2.7 and
P = (2.7
S -
y + 1.5
z)/1.35. Similarly, Hegsted reported the change in serum cholesterol to be equal to 2.16
S - 1.65
P + 0.176
C where C = mg change in cholesterol per 1000 kcal (46). This rearranges to
S = (
y + 1.65
P - 0.176
C)/2.16 and
P = (2.16
S + 0.176
C -
Y)/1.65. It can therefore predict either the change in
S and
P as a function of other dietary change or the effect of change in individual fats on serum cholesterol as a marker of change. More recently Mensink (47) and Kris-Etherton (48) published formulas that present more precision by adding changes in monounsaturated fat intakes and by taking into account the chain length of the polyunsaturated fat source. Because these formulas are so robust, changes in serum cholesterol levelsunder otherwise homeostatic conditions with regard to weight statusand intakes of other fats and dietary cholesterol could be used as a biomarker of change in fat intake. These formulas were recently refined to be more specific with regard to individual fatty acids. The estimates from these authors are presented in Table 4.
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| Biomarkers of food intake |
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Stearic acid levels are high in chocolate (
30%) (51,53). However, the utility of this fatty acid as a biomarker of chocolate consumption is limited by its conversion in the liver to oleic acid after desaturation (51). In some populations, the levels of oleic acid are taken as an indicator of the consumption of olive oil. All of this presumes that the individual is not using the fat for energy generation and that the intakes of other fats are relatively homogeneous.
| CONCLUSIONS |
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| FOOTNOTES |
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3 Abbreviations used: CLA, conjugated linoleic acid; DHA, decosahexanoic acid; EPA, eicosapentanoic acid; FIO, flame ionization detectors; GC, gas chromatography; GCMS, gas chromatography and mass spectrometry; HPLC, high performance liquid chromatography; NEFA, nonesterified fatty acid. ![]()
| LITERATURE CITED |
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1. Lichtman, S. W., Pisarska, K., Berman, E. R., Pestone, M., Dowling, H., Offenbacher, E., Weisel, H., Heshka, S., Matthews, D. E. & Heymsfield, S. B. (1992) Discrepancy between self-reported and actual caloric intake and exercise in obese subjects. N. Engl. J. Med. 327: 18931898.[Abstract]
2. Wood, D. A., Riemersma, R. A., Butler, S., Thomson, M., Macintyre, C., Elton, R. A. & Oliver, M. F. (1987) Linoleic and eicosapentaenoic acids in adipose tissue and platelets and risk of coronary heart disease. Lancet 1: 177183.[Medline]
3. Chilton, F. H., Fonteh, A. N., Surette, M. E., Triggiani, M. & Winkler, J. D. (1996) Control of arachidonate levels within inflammatory cells. Biochim. Biophys. Acta 1299: 115.[Medline]
4. Hellerstein, M. K. (1999) De novo lipogenesis in humans: metabolic and regulatory aspects. Eur. J. Clin. Nutr. 53(suppl 1): 553565.
5. Cinti, D. L., Cook, L., Nagi, M. N. & Suneja, S. K. (1992) The fatty acid chain elongation system of mammalian endoplasmic reticulum. Prog. Lipid Res. 31: 151.[Medline]
6. Burr, G. O. & Burr, M. M. (1930) On the nature and role of the fatty acids essential in nutrition. J. Biol. Chem. 86: 587621.
7. Hirsch, J., Farquhar, J. W., Ahrens, E. H., Peterson, M. L. & Stoffel, W. (1960) Studies of adipose tissue in man. Am. J. Clin. Nutr. 8: 499511.
8. Kohlmeier, L. & Kohlmeier, M. (1995) Adipose tissue as a medium for epidemiologic exposure assessment. Environ. Health Perspect. 103(Suppl 3): 99106.
9. Beynen, A. C., Hermus, R. J. & Hautvast, J. G. (1980) A mathematical relationship between the fatty acid composition of the diet and that of the adipose tissue in man. Am. J. Clin. Nutr. 33: 8185.
10. Kritchevsky, D. (1990) Trans unsaturated fat in nutrition and health. In: Edible Fats and Oils Processing: Basic Principles and Modern Practices (Erickson, E.R., ed.), pp 158165. American Oil and Chemistry Society, Champaign, IL.
11. Kohlmeier, L., Simonsen, N., van't Veer, P., Strain, J. J., Martin-Moreno, J. M., Margolin, B., Huttunen, M. K., Fernandez-Crehuet Navajas, J., Martin, B. C., Thamm, M., Kardinaal, A. F. & Kok, F. J. (1997) Adipose tissue trans fatty acids and breast cancer in the European community multicenter study on antioxidants, myocardial infarction, and breast cancer. Cancer Epidemiol. Biomarkers Prev. 6: 705710.
12. Simonsen, N. R., Fernandez-Crehuet Navajas, J., Martin-Moreno, J. M., Strain, J. J., Huttunen, K., Martin, B. C., Thamm, M., Kardinaal, A. F., van't Veer, P., Kok, F. J. & Kohlmeier, L. (1998) Tissue stores of individual monounsaturated fatty acids and breast cancer: the EURAMIC study. European community multicenter study on antioxidants, myocardial infarction, and breast cancer. Am. J. Clin. Nutr. 68: 134141.[Abstract]
13. Horrobin, D. F. (1992) Nutritional and medical importance of gamma-linoleic acid. Prog. Lipid Res. 31: 163194.[Medline]
14. Ip, C., Singh, M., Thompson, H. J. & Scimeca, J. A. (1994) Conjugated linoleic acid suppresses mammary carcinogenesis and proliferative activity of the mammary gland in the rat. Cancer Res. 54: 12121215.
15. Banni, S., Angioni, E., Casu, V., Melis, M. P., Carta, G., Corongiu, F. P., Thompson, H. & Ip, C. (1999) Decrease in linoleic acid metabolites as a potential mechanism in cancer risk reduction by conjugated linoleic acid. Carcinogenesis 20: 10191024.
16. Christie, W. W. (1987) High-Performance Liquid Chromatography and Lipids: A Practical Guide. pp. 133168. Pergamon Press, Oxford, England.
17. Ackman, R. G. (1972) The analysis of fatty acids and related materials by gas-liquid chromatography. In: Progress in the Chemistry of Fats and Other Lipids (Holman, R. T., ed.), vol. 12, p. 165.
18. Kuksis, A. (1972) Newer developments in determination of structure of glycerides and phosphoglycerides. In: Progress in the Chemistry of Fats and Other Lipids (Holman, R. T., ed.) vol. 12, p 1.
19. Bates, C. J., Thurman, D. I., Bingham, S. A., Margetts, B. M. & Nelson, M. (1997) Biochemical markers of nutrient intake. In: Design Concepts in Nutritional Epidemiology (Margetts, B. M. & Nelson, M., eds.), pp 170240, Oxford University Press, Oxford, UK.
20. Kohlmeier, L. (1991) What you should know about your marker. In: Biomarkers of Dietary Exposure. Proceedings of the 3rd Meeting on Nutritional Epidemiology (Kok, F. J. & van't Veer, P., eds.), pp. 1525.
21. Zeleniuch-Jacquotte, A., Chajes, V., Van Kappel, A. L., Riboli, E. & Toniolo, P. (2000) Reliability of fatty acid composition in human serum phospholipids. Eur. J. Clin. Nutr. 54: 367372.[Medline]
22. Malcom, G. T., Bhattacharyya, A. K., Velez-Duran, M., Guzman, M. A., Oalmann, M. C. & Strong, J. P. (1989) Fatty acid composition of adipose tissue in humans: differences between subcutaneous sites. Am. J. Clin. Nutr. 50: 288291.
23. Phinney, S. D., Stern, J. S., Burke, K. E., Tang, A. B., Miller, G. & Holman, R. T. (1994) Human subcutaneous adipose tissue shows site-specific differences in fatty acid composition. Am. J. Clin. Nutr. 60: 725729.
24. Womersley, J. (1977) A comparison of the skinfold method with extent of overweight and various weight-height relationships in the assessment of obesity. Br. J. Nutr. 38: 271284.[Medline]
25. Berry, E. M., Hirsch, J., Most, J., McNamara, D. J. & Thornton, J. (1986) The relationship of dietary fat to plasma lipid levels as studied by factor analysis of adipose tissue fatty acid composition in a free-living population of middle-aged American men. Am. J. Clin. Nutr. 44: 220231.
26. Dayton, S., Hashimoto, S., Dixon, W. & Pearce, M. L. (1966) Composition of lipids in human serum and adipose tissue during prolonged feeding of a diet high in unsaturated fat. J. Lipid Res. 7: 103111.[Abstract]
27. Hudgins, L. C. & Hirsch, J. (1991) Changes in abdominal and gluteal adipose-tissue fatty acid compositions in obese subjects after weight gain and weight loss. Am. J. Clin. Nutr. 53: 13721377.
28. Kohlmeier, L. (1995) Future of dietary exposure assessment. Am. J. Clin. Nutr. 61(Suppl): 702S709S.
29. Frayn, K. N., Shadid, S., Hamlani, R., Humphreys, S. M., Clark, M. L., Fielding, B. A., Boland, O. & Coppack, S. W. (1994) Regulation of fatty acid movement in human adipose tissue in the postabsorptive-to-postprandial transition. Am. J. Physiol. 266: E308E317.
30. Corrocher, R., Pagnan, A., Ambrosio, G. B., Ferrari, S., Olivieri, O., Guarini, P., Bassi, A., Piccolo, D., Gandini, A. & Girelli, D. (1992) Effects induced by olive oil-rich diet on erythrocytes membrane lipids and sodium-potassium transports in postmenopausal hypertensive women. J. Endocrinol. Invest. 15: 369376.[Medline]
31. Dougherty, R. M., Galli, C., Ferro-Luzzi, A. & Iacono, J. M. (1987) Lipid and phospholipid fatty acid composition of plasma, red blood cells, and platelets and how they are affected by dietary lipids: a study of normal subjects from Italy, Finland, and the USA. Am. J. Clin. Nutr. 45: 443455.
32. Jacobs, D. R., Jr. & Barrett-Connor, E. (1982) Retest reliability of plasma cholesterol and triglyceride. The Lipid Research Clinics Prevalence Study. Am. J. Epidemiol. 116: 878885.
33. Mjos, O. D., Rao, S. N., Bjoru, L., Henden, T., Thelle, D. S., Forde, O. H. & Miller, N. E. (1979) A longitudinal study of the biological variability of plasma lipoproteins in healthy young adults. Atherosclerosis 34: 7581.[Medline]
34. Bligh, E. & Dyer, W. (1959) A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37: 911917.
35. Folch, J., Lees, M. & Sloan-Stanley, G. (1957) A simple method for the isolation and purification of total lipids from animal tissues. J. Biol. Chem. 226: 497509.
36. Prisco, D., Filippini, M., Francalanci, I., Paniccia, R., Gensini, G. F., Abbate, R. & Serneri, G. G. N. (1996) Effect of n-3 polyunsaturated fatty acid intake on phospholipid fatty acid composition in plasma and erythrocytes. Am. J. Clin. Nutr. 63: 925932.
37. Mulchert, H. U., Limsathayourat, N., Mihajlovic, H., Eichberg, J., Thefeld, W. & Rotka, H. (1987) Fatty acid patterns in triglycerides, diglycerides, free fatty acids, cholesteryl esters and phosphatidylcholine in serum from vegetarians and non-vegetarians. Atherosclerosis 65: 159166.[Medline]
38. Kardinaal, A. F. M., van't Veer, P., Brants, H. A. M., van den Berg, H., van Schoonhoven, J. & Hermus, R. J. J. (1995) Relations between antioxidant vitamins in adipose tissue, plasma, and diet. Am. J. Epidemiol. 141: 440450.
39. van Staveren, W. A., Deurenberg, P., Katan, M. B., Burema, J., de Groot, L. C. P. G. M. & Hoffmans, M. D. A. F. (1986) Validity of the fatty acid composition of subcutaneous fat tissue microbiopsies as an estimate of the long-term average fatty acid composition of the diet of separate individuals. Am. J. Epidemiol. 123: 455463.
40. Handelman, G. J., Epstein, W. L., Machlin, L. J., van Kuijk, F. J. & Dratz, E. A. (1988) Biopsy method for human adipose with vitamin E and lipid measurements. Lipids 23: 598604.[Medline]
41. Otto, S. J., van Houwelingen, A. C., Badart-Smook, A. & Hornstra, G. (2001) Comparison of the peripartum and postpartum phospholipid polyunsaturated fatty acid profiles of lactating and nonlactating women. Am. J. Clin. Nutr. 73: 10741079.
42. Sarnelli, R. & Squartini, F. (1983) The microenvironment of human breast with clinical cancer. Appl. Pathol. 1: 323332.[Medline]
43. Rautalahti, M., Hyvonen, L., Albanes, D., Lampi, A. M., Koivistoinen, P. & Virtamo, J. (1990) Effect of sampling site on fatty acid composition of human breast adipose tissue. Nutr. Cancer 14: 247251.[Medline]
44. Wanders, R. J. (2000) Peroxisomes, lipid metabolism, and human disease. Cell Biochem. Biophys. 32: 89106.
45. Keys, A., Andersen, J. T. & Grande, F. (1965) Serum cholesterol response to changes in the diet. IV. Particular saturated fats in the diet. Metabolism 14: 376387.
46. Hegsted, D. M., McGandy, R. B., Myers, M. L. & Stare, F. J. (1965) Quantitative effects of dietary fat on serum cholesterol in man. Am. J. Clin. Nutr. 17: 281295.[Medline]
47. Mensink, R. P., Temme, E. H. & Hornstra, G. (1994) Dietary saturated and trans fatty acids and lipoprotein metabolism. Ann. Med. 26: 461464.[Medline]
48. Kris-Etherton, P. M. & Yu, S. (1997) Individual fatty acid effects on plasma lipids and lipoproteins: human studies. Am. J. Clin. Nutr. 65(Suppl): 1628S1644S.
49. Wolk, A., Vessby, B., Ljung, H. & Barrefors, P. (1998) Evaluation of a biological marker of dairy fat intake. Am. J. Clin. Nutr. 68: 291295.[Abstract]
50. Hjartaker, J., Lund, E. & Bjerve, K. S. (1997) Serum phospholipid fatty acid composition and habitual intake of marine foods registered by a semi-quantitative food frequency questionnaire. Eur. J. Clin. Nutr. 51: 736742.[Medline]
51. Kobayashi, M., Sasaki, S., Kawabata, T., Hasegawa, K., Akabane, M. & Tsugane, S. (2001) Single measurement of serum phospholipid fatty acid as a biomarker of specific fatty acid intake in middle-aged Japanese men. Eur. J. Clin. Nutr. 55: 643650.[Medline]
52. Godley, P. A., Campbell, M. K., Miller, C., Gallagher, P., Martinson, F. E., Mohler, J. L. & Sandler, R. S. (1996) Correlation between biomarkers of omega-3 fatty acid consumption and questionnaire data in African American and Caucasian United States males with and without prostatic carcinoma. Cancer Epidemiol. Biomarkers Prev. 5: 115119.
53. Connor, W. E. (1999) Harbingers of coronary heart disease: dietary saturated fatty acids and cholesterol. Is chocolate benign because of its stearic acid content? Am. J. Clin. Nutr. 70: 951952.
54. Hunter, D. J., Rimm, E. B., Sacks, F. M., Stampfer, M. J., Colditz, G. A., Litin, L. B. & Willett, W. C. (1992) Comparison of measures of fatty acid intake by subcutaneous fat aspirate, food frequency questionnaire, and diet records in a free-living population of US men. Am. J. Epidemiol. 135: 418427.
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