Variation in Fasting and Non-Fasting Serum Enterolactone Concentrations in Women of the Malmo¨ Diet and Cancer Cohort

ORIGINAL ARTICLE Variation in fasting and non-fasting serum enterolactone concentrations in women of the Malmo¨ Diet and Cancer cohort

E Sonestedt1, U Ericson1, B Gullberg1, JL Pen˜alvo2, H Adlercreutz2 and E Wirfa¨lt1

1Department of Clinical Sciences, Lund University, Malmo¨, Sweden and 2Institute for Preventive Medicine, Nutrition and Cancer, Folkha¨lsan Research Center and Division of Clinical Chemistry, University of Helsinki, Helsinki, Finland

Objectives: The aim of this study was to examine the variation of enterolactone from fasting and non-fasting blood of middle- aged healthy women eating a normal diet to determine the usefulness of a single sample in epidemiological studies. Subjects and methods: Twenty-six women born between 1940 and 1950 were recruited within the Malmo¨ Diet and Cancer cohort. Three non-fasting and two overnight fasting samples were collected from each individual during a 5-week period. Twenty-one participated in all measurements. Enterolactone concentrations were analyzed by time-resolved fluoroimmunoassay. Results: The within-subject and between-subject variations (coefficient of variations, CV) were estimated to 59 and 89% respectively for fasting samples and 71 and 67% for non-fasting samples. The intraclass correlation coefficients (ICC) were estimated to 0.66 (95% confidence interval (CI) 0.35–0.84) for fasting and 0.48 (95% CI, 0.22–0.72) for non-fasting samples. Conclusions: Although the estimated ICC for blood samples was moderate, it indicates that enterolactone levels of both fasting and non-fasting blood samples should be useful in future projects within the Malmo¨ Diet and Cancer cohort. European Journal of Clinical Nutrition (2008) 62, 1005–1009; doi:10.1038/sj.ejcn.1602811; published online 30 May 2007

Keywords: enterolactone; serum; lignans; biomarker; time-resolved fluoroimmunoassay

Introduction value as a marker of dietary lignan intake, because complete information of the lignan content in foods is not available in Lignans, found in seeds, legumes, berries and cereals (Milder food databases, making it difficult to estimate the individual et al., 2005; Penalvo et al., 2005a), may have health benefits intake of lignans by dietary assessment (Lampe, 2003). Because and possibly protect, or indicate protection against chronic many large-scale epidemiological studies are only able to diseases such as breast and prostate cancer and cardio- collect single blood samples, is it also important to examine vascular disease (Vanharanta et al., 1999, 2003; Adlercreutz, carefully the reliability of using one sample when classifying 2002). The mammalian intestinal micro flora converts plant individuals according to their blood concentrations. More- lignans into enterolignans, mainly enterolactone (ENL) over, it is important to estimate the variability of biomarkers in (Heinonen et al., 2001). each study population, where an epidemiological study will be Biomarkers are objective assessments of exposure and performed, because the variability across studies is not always therefore valuable measures of internal exposure in chronic comparable. The reliability can be estimated by the intraclass disease epidemiology. The blood level of ENL is of specific correlation coefficient (ICC), which is defined as the ratio of the between-person to total variability. Biomarkers with low Correspondence: E Wirfa¨lt, Department of Clinical Sciences, Malmo, ICC often result in attenuation of the relation between the Nutritional Epidemiology, Lund University, UMAS CRC entrance 72, Building 60, Floor 13, SE-205 02 Malmo¨, Sweden. exposure and disease (Vineis, 1997). However, if the ICC in a E-mail: [email protected] population is known, this estimate can be used in multivariate Contributors: ES, UE, EW and BG contributed to study design. ES conducted analysis to control risk estimates for random within-person the analysis of data, and wrote most of the manuscript. All authors reviewed measurement error (Rosner et al., 1992). the final manuscript. Received 17 November 2006; revised 17 April 2007; accepted 18 April 2007; The aim of this study was to examine the variation of published online 30 May 2007 fasting and non-fasting ENL concentrations in serum of a Variation in serum enterolactone concentrations E Sonestedt et al 1006 sample of middle-aged healthy woman eating a normal diet fasting and non-fasting samples. Estimates of between- 2 2 to determine the usefulness of one sample for use in subject (sB), within-subject (sW), total variances as well as epidemiological studies. ICCs with 95% CIs were obtained by SPSS (version 11.5; SPSS Inc.; Chicago, IL, USA) using reliability analysis. The Person correlation coefficients between within-subject variances Subjects and methods and the number of days between first and last non-fasting blood collections were examined. The number of repeated Study population measurements (in different weeks) needed to estimate the One hundred women born between 1940 and 1950 were individual underlying within-month ENL mean concentra- randomly selected from the Malmo¨ Diet and Cancer cohort, tion was calculated to within 750% with 80% CI. a prospective cohort study (n ¼ 28 098) with baseline examinations from 1991 to 1996 (Berglund et al., 1993). The participants were recruited by mail and telephone to Results reach the goal of 25 individuals. Limited Swedish language skills, mental incapacity and carrier of any serious disease Out of 100 invited women randomly selected from the were the only exclusion criteria. cohort, 26 women without any serious disease were recruited The study was performed after approval by the Regional into this study and 21 women participated in all five blood Ethical Review Board in Lund and informed consent was collections. The main reason for not completing all blood obtained from each subject. Study participants came for measurements was lack of time. The median interval blood collection five times during May–June 2005 (three between the first and the last blood collection (i.e., non-fasting and two fasting samples). For the fasting samples, non-fasting samples) was 33 days (range 19–46 days), with the participants had to be fasting from 2400 the day before. a median of 7 days (range 4–23 days) between the two fasting The ‘usual dietary intake’ was assessed with a modified diet measurements. Figure 1 illustrates ENL concentrations for history methodology combining a diet history questionnaire the first and last blood collection for the 21 individuals covering usual intake of regularly eaten foods the last year according to the number of days between measurements with a 7-day menu book for registration of cold beverages, (19–46 days). The correlation analysis did not indicate that lunch and dinner meals and nutrient supplements, and a 1 h the number of days between the first and last non-fasting dietary interview. The information on food intake was blood collections influenced the within-subject variation converted to nutrient intake data using a database from the (r ¼ 0.12, P ¼ 0.61). The overall median ENL concentration Swedish National Food Administration (PC KOST2-93). was 19 nmol/l with a range of 0.5–65 nmol/l for fasting A questionnaire collected information on lifestyle factors and regular drug use and occasional drug use during the last 3 months. Current use of drugs was recorded in the menu book. 100,00

Laboratory analyses The blood samples were processed and separated for serum. The samples were stored at À201C until analysis. Serum ENL concentrations were determined by time-resolved fluoroimmunoassay as reported previously (Adlercreutz et al., 1998; Stumpf et al., 2000). In brief, samples were incubated overnight with a mixture sulphatase and b-glucuronidase and unconjugated ENL was extracted with diethyl ether. 10,00 Sample extracts were then diluted in assay buffer, added with antiserum and europium-labeled and placed in prewashed goat anti-rabbit IgG microstrips to be analyzed by Auto- 3

DELFIA 1235 Automatic Immunoassay System. H-estradiol Enterolactone concentration (nmol/L) glucuronide was used as internal standard.

1,00 Statistical analyses

All calculations were performed on loge transformed ENL 19 20 23 26 26 28 28 28 29 33 33 34 34 34 35 38 40 41 41 42 46 concentrations. Median ENL concentrations and the number Difference between first and last observation (days) and range of days between blood collections were deter- Figure 1 Enterolactone (ENL) concentrations for the first and last mined separately for fasting and non-fasting blood samples. blood collection for the individuals according to the number of days Pearson correlation coefficients were determined within between measurements (19–46 days).

European Journal of Clinical Nutrition Variation in serum enterolactone concentrations E Sonestedt et al 1007 samples and 1.3–82 nmol/l for non-fasting samples (Table 1). either fasting or non-fasting blood. Also, the participants One individual had the lowest ENL concentrations in both represent a relative homogenous group; women aged 55–65 the fasting and the non-fasting samples on two consecutive years. Other studies have included younger participants collections points. The correlations of ENL for fasting (Stumpf and Adlercreutz, 2003). and non-fasting samples are presented in Table 2. A higher Another advantage of this study is that we (unlike many Pearson correlation coefficient was estimated between fast- other studies) collected blood samples and dietary informa- ing blood samples (0.74) than for non-fasting samples (0.62 tion concurrently and are therefore able to explain extremely for the first and second non-fasting sample and 0.42 for the high values. Lignans occur frequently in plant foods, first and last non-fasting samples). The fasting samples also however, diets enriched with flax and sesame seeds (contain- showed a slightly higher ICC than the non-fasting samples ing very high concentrations of plant lignans) have been (0.66 vs 0.48), with a slightly lower within-subject coefficient observed to duplicate concentration of ENL in serum (Tarpila of variations (CV) (59 vs 71%). The estimated ICC was 0.88 et al., 2002; Penalvo et al., 2005b). No subject reported flax for fasting and 0.53 for non-fasting when the individual seed consumption, but two subjects with the highest ENL with lowest ENL concentrations was excluded. Three days levels reported that they might have consumed flax seeds in for fasting and 4 days for non-fasting would be required to bread. The correlation between fiber and ENL became estimate the mean within-month concentration (to within positive (r ¼ 0.36) when excluding four subjects with the 750% with 80% CI) for individuals in this population. highest ENL levels, indicating high intakes of low-fiber lignan-rich foods (for example, flax seed) among these subjects. The range in ENL concentration is largely explained by Discussion differences in dietary intakes (Adlercreutz et al., 1987, 1993, 1994). The range of ENL concentrations is 0.5–82 nmol/l in This study of variation of ENL in blood during 1 month the present study. Stumpf and Adlercreutz (2003), observed indicates a large variation in both fasting and non-fasting ENL serum concentrations of 0 to 130 nmol/l in 20 Finnish samples. individuals during 1 month and a range of 0–655 nmol/l The uniqueness of this study is that it simultaneously were measured in serum samples collected at 3 yearly visits examines the variation of ENL from fasting and non-fasting in 60 American women (Zeleniuch-Jacquotte et al., 1998). blood. Other studies have examined variation of ENL in Smoking, body mass index and constipation are other factors that can influence serum concentration of ENL (Kilkkinen Table 1 Median concentrations, coefficients of variation, ICC and et al., 2001; Johnsen et al., 2004). The capacity of the gut number of days to estimate mean levels of ENL in serum in microflora is also a very influential factor (Bowey et al., postmenopausal women 2003). The use of antibiotics is known to reduce the amount Variables Non-fasting Fasting of colonic bacteria and subsequently concentrations of ENL in serum (Kilkkinen et al., 2002). No participant reported use Number of subjects 21 21 of antibiotics during 3 months before the present study Number of measurements 3 2 started. Other factors (for example, fermented milk) may Median 18 22 CV (within-subject) 71% 59% potentially influence the ability of colon bacteria to convert CV (between-subject) 67% 89% plant lignans to mammalian lignans. We did not analyze ICC (95% CI) 0.48 (0.22–0.72) 0.66 (0.35–0.84) entrodiol (END), another mammalian lignan that also is a Number of samples 43biological active. Different bacteria are needed for the Abbreviations: CI, confidence interval; CV, coefficient of variation; ENL, conversion of plant lignans into END and ENL (Clavel enterolactone; ICC, intraclass correlation coefficient. et al., 2005). ENL is generally the lignan with highest aThe number of samples required to estimate individual mean level of ENL concentration in blood (Adlercreutz et al., 1993) and also concentration within 50% of the true mean and with 80% CI. the lignan that mostly have been examined in epidemiological studies. We concluded that four non-fasting or three fasting Table 2 Number of days and correlation between blood collections in samples were needed to estimate the mean serum concen- postmenopausal women tration in individuals within 750% with 80% confidence interval (CI). These results are in agreement with a Finnish Blood samples Median Range Correlationa study with 20 university students using a comparable study Fasting 7 4–23 0.74 design, which concluded that three fasting samples were needed to estimate serum concentration within 750% with Non-fasting 80% CI (Stumpf and Adlercreutz, 2003). However, the Between first and second 14 9–33 0.62 purpose in epidemiological studies is to rank individuals Between first and last 33 19–46 0.42 (i.e., classify individuals into percentiles) according to aPearson correlation coefficient. their blood concentrations, not to estimate mean blood

European Journal of Clinical Nutrition Variation in serum enterolactone concentrations E Sonestedt et al 1008 concentrations of single individuals. Therefore, high within- (Missmer et al., 2006), and should be advantageous in future person variability may be a minor problem if the biomarker studies of the Malmo¨ Diet and Cancer cohort assessing ENL also shows high between-person variability (Li et al., 2001). blood concentration in relation to risk of breast cancer ICC provides an estimate of the proportion of the (Tworoger and Hankinson, 2006). variation in the exposure explained by the variation between groups relative to the total variation. A reliable biomarker, useful for epidemiological studies, are characterized by Acknowledgements high ICC, while a low ICC (close to zero) means either low between-person variability or high within-person variability. This study was sponsored by Swedish Council for Working ENL concentrations in this study are characterized by a Life and Social Research, Albert Pa˚hlsson Foundation, relatively high between-person variation as well as high Johanna Andersson Foundation, Swedish Research Council, within-person variation with ICC estimated to 0.66 for Swedish Cancer Society, Regional Government of Ska˚ne. fasting samples. The comparable study with fasting blood collections once a week for 3 weeks among 20 university students in Finland estimated ICC to 0.77 for ENL (Stumpf References and Adlercreutz, 2003). Our narrower range and smaller between-subject variations may be due to a more homo- Adlercreutz H (2002). Phyto-oestrogens and cancer. Lancet Oncol 3, genous study sample and a different age category. We 364–373. Adlercreutz H, Fotsis T, Lampe J, Wahala K, Makela T, Brunow G et al. estimated ICC for non-fasting sample to 0.48. In epidemio- (1993). 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