Individuals suffering from ATH (adult-type hypolactasia), defined by the LCT (gene encoding lactase-phlorizin hydrolase) C/C−13910 genotype (rs4988235), use less milk and dairy products and may have higher plasma HDL (high-density lipoprotein) and lower triacylglycerol (triglyceride) concentrations than their counterparts without ATH. To investigate the effects of ATH status on the early markers of atherosclerosis, we examined its association with CIMT (carotid intima-media thickness), CAC (carotid artery compliance) and brachial artery FMD (flow-mediated dilation) in a young population-based cohort of otherwise healthy individuals. As part of the Cardiovascular Risk in Young Finns Study, we performed CIMT, CAC and FMD analyses, LCT C/T−13910 genotyping and risk factor determination in 2109 young subjects 24–39 years of age (45% males) at the time of the examination. The consumption of both milk and dairy products was lowest and the consumption of alcohol highest in subjects with the C/C−13910 genotype (P<0.001 for all) in comparison with subjects without ATH (TT+CT). In multivariate analysis, no significant association between ATH status and CIMT, CAC or brachial artery FMD was found after adjustment for the use of alcohol, dairy products and all other major risk factors of coronary artery disease. In otherwise similar statistical analysis, the results remained non-significant when females and males were analysed in their own groups. In conclusion, the finding does not support the involvement of ATH in the pathogenesis of early atherosclerosis.

INTRODUCTION

ATH (adult-type hypolactasia), also known as lactase deficiency or lactase persistence/non-persistence [see OMIM (Online Medelian Inheritance in Man) website at http://www.ncbi.nlm.nih.gov/sites/entrez], is a genetically defined condition affecting approximately half of the world's population [14]. Today, ATH can be diagnosed by using a simple genetic test [SNP (single nucleotide polymorphism) rs4988235] [47].

The C/T−13910 SNP (rs4988235) in the LCT gene (gene encoding lactase-phlorizin hydrolase) on chromosome 2 defines ATH status, leading to a several times higher expression of lactase-phlorizin hydrolase in T/T homozygotes than is found in subjects with the C/C genotype [8,9]. LCT C/T−13910 heterozygotes have intermediate levels of lactase, as measured by enzyme activity [10] and mRNA levels, but they still produce enough lactase to be asymptomatic when given a 50 g dose of lactose in connection with a standard physiological test for lactose tolerance. Enattah et al. [5] reported that the C/T−13910 polymorphism completely associates with biochemically verified lactase non-persistence in Finnish families and a sample set of 236 individuals from four different populations. After the original discovery of the ATH-causing LCT C/T−13910 genotype, molecular epidemiological studies in more than 40 countries have confirmed that the prevalence of the C/C−13910 genotype is consistent with epidemiological data on ATH published previously [4,7,11,12]. Therefore ATH persistence (genotypes TT and CT) and non-persistence (CC genotype) status can be reliably defined by this genetic test.

Over the last few decades, the consumption of milk has decreased while that of the other milk products, such as cheese and yoghurt, has increased in the general Finnish population [13,14]. However, ATH defined by the C/C−13910 genotype limits the use of dairy products, in addition to regulating the intake of dietary fat and calcium in Finnish subjects and in subjects from several other populations [6,7,11,12,15]. Moreover, some previous studies have shown that, in subjects with ATH, serum levels of insulin, glucose and triacylglycerols (triglycerides) are lower and HDL (high-density lipoprotein)-cholesterol levels are higher than in subjects who do not have ATH [16,17]. It is not known whether these biochemical differences in subjects with and without ATH [16,17] might eventually lead to differences in the early markers of atherosclerosis.

CIMT (carotid intima-media thickness), CAC (carotid artery compliance) and brachial artery FMD (flow-mediated dilation) are all accurately quantifiable and reproducible markers of early atherosclerosis [1828]. Of these markers, increased CIMT correlates with cardiovascular risk factors [26], as well as the severity of coronary atherosclerosis [19], and predicts cardiovascular events in population groups [24]. FMD, as well as CAC, offers a new means to study early functional changes caused by atherosclerosis [20,25,29]. Impaired FMD is a marker of endothelial dysfunction, which also relates to the prevalence and extent of coronary atherosclerosis and predicts cardiovascular events in patient groups [21,22].

Given the established relationship between ATH and dietary intake of milk and dairy products and thus dietary fat and calcium, it may be hypothesized that variation at the LCT gene locus (rs4988235) directly, or indirectly by modifying biochemical risk factors, translates into differences in the early markers of atherosclerosis. Therefore, in the present study, we investigated the association between ATH status and early markers of atherosclerosis in a young population-based cohort of otherwise healthy individuals participating in the Cardiovascular Risk in Young Finns Study [26].

MATERIALS AND METHODS

Subjects

The Cardiovascular Risk in Young Finns Study (http://vanha.med.utu.fi/cardio/youngfinnsstudy) is an on-going follow-up study of the precursors of atherosclerosis in Finnish children and adolescents. The first cross-sectional survey was conducted in 1980 when 3596 participants aged 3, 6, 9, 12, 15 and 18 years were randomly chosen from the national population register to represent each (geographical) area in Finland [30]. The sample was representative of the entire Finnish population. In 2001, we re-examined 2283 of these individuals, now 24–39 years of age. Complete data on the LCT gene C/T−13910 polymorphism as well as carotid and brachial artery ultrasound examinations were available for 2109 subjects [23,26].

The study was carried out in accordance with the Declaration of Helsinki 2000 of the World Medical Association and approved by local Ethics committees, and all subjects gave their written informed consent.

Clinical characteristics and risk factors

Height and weight were measured, and BMI (body mass index) was calculated [31]. In 2001, a random zero sphygmomanometer was used for BP (blood pressure) measurements. The average of three measurements was used in the analysis. In adults, smoking habits and history of diabetes were assessed using a questionnaire. The physical activity index was calculated as described previously [32].

For the determination of serum lipoprotein levels, venous blood samples were drawn after an overnight fast. Lipid concentrations were measured using standard methods [31,33]. LDL (low-density lipoprotein)-cholesterol concentrations were calculated using the Friedewald formula. The fasting plasma high-sensitive CRP (C-reactive protein) concentrations were analysed using a latex turbidometric immunoassay (Wako Chemicals). The lower detection limit reported for the assay was 0.06 mg/l, and the CV (coefficient of variation) in repeated measurements was 3.3%. Plasma glucose concentrations were analysed enzymatically (Olympus). Serum insulin concentrations were measured with microparticle enzyme immunoassay kits (Abbott Laboratories).

Assessment of dietary variables

Food consumption was assessed with dietary questionnaires on habitual eating behaviour and food choices, including questions on the habitual frequency of the consumption of selected foods and food groups. On the basis of these data, we also constructed an index variable representing the subjects' usual daily consumption of milk and other dairy products, such as cheese, sour milk, yoghurt and ice cream. Similarly, we calculated the daily consumption of fresh vegetables and the weekly consumption of fish. The consumption of alcohol is presented as a sum of weekly portions of beer, wine and hard liquor (g/week). The details of the dietary study included in the project have been described previously [34,35].

Ultrasound measurements

Ultrasound examinations were performed using Sequoia 512 ultrasound mainframes (Acuson) with a 13.0 MHz linear array transducer, as described previously [26]. In brief, the image in the CIMT measurements was focused on the posterior (far) wall of the left carotid artery. A magnified image was recorded from the angle showing the greatest distance between the lumen–intima interface and the media–adventitia interface. A minimum of four measurements of the common carotid far wall were taken 10 mm proximally to the bifurcation in order to derive mean CIMT. The between-visit (two visits 3 months apart) CV for CIMT measurements was 6.4% [26].

For CAC measurements, the left carotid artery was scanned by physicians and ultrasound technicians following standard protocols [23]. In brief, several 5-s moving image clips of the beginning of the carotid bifurcation and the common carotid artery were acquired and stored in digital format on optical discs for subsequent off-line analysis. All digitally stored ultrasound scans were analysed manually by a single reader blinded to the subjects' details. The analyses were performed using ultrasonic callipers. From the 5-s clips, the best-quality cardiac cycle was selected. The carotid diameter was measured at least twice in end-diastole and end-systole respectively. The mean of the measurements was used as the end-diastolic or end-systolic diameter. BP was measured during the ultrasound study with an automated sphygmomanometer (Omron M4; Omron Matsusaka) from the non-dominant brachial artery. The mean of two measurements was used in the analysis. CAC (%/10 mmHg) was calculated using the equation: ([DsDd]/Dd)/(PsPd), where Dd represents the diastolic diameter, Ds the systolic diameter, Ps the systolic BP and Pd the diastolic BP. To assess the reproducibility of the CAC measurements, we re-examined 60 subjects 3 months after the initial visit (2.5% random sample). The between-visit CV for the end-diastolic carotid diameter was 2.7% and for carotid diameter change was 13.1% [23].

To assess brachial artery FMD, the left brachial artery diameter was measured both at rest and during reactive hyperaemia, as described previously [23]. In brief, increased flow was induced by inflation of a pneumatic tourniquet placed around the forearm to a pressure of 250 mmHg for 4.5 min, followed by release. Three measurements of arterial diameter were performed at end-diastole at a fixed distance from an anatomic marker at rest as well as 40, 60 and 80 s after cuff release. The vessel diameter in scans after reactive hyperaemia was expressed as a percentage relative to the resting scan (100%). The average of three measurements at each point in time was used to derive maximum FMD (the greatest value was between 40 and 80 s). We have reported previously a short-term (2-h) between-study CV of 9% for FMD measurements [36]. The long-term between-visit CVs of brachial measurements, achieved through re-examining 57 subjects 3 months after the initial visit (2.5% random sample), were 3.2% for brachial artery diameter measurements and 26.0% for FMD measurements.

Lactase-phlorizin hydrolase genotyping

The LCT C/T−13910 SNP (rs4988235) was measured in 2281 participants in 2001. Genomic DNA was extracted from peripheral blood leucocytes using a commercially available kit (Qiagen). LCT C/T−13910 genotyping was performed by employing the 5′-nuclease assay with fluorogenic allele-specific TaqMan probes and primers [7,37], using the ABI Prism 7000 Sequence Detection System (Applied Biosystems). As a quality control, we used known control samples which were run in parallel with unknown DNA samples and random-blind duplicates.

Statistical analysis

Statistical analyses were carried out using SPSS version 14.0 for Windows software.

The levels of continuous (normally distributed) variables were compared between the ATH status groups (no/yes) using a Student's t test. These analyses were performed separately for males and females. The compliance of genotype data with the Hardy–Weinberg equilibrium was assessed using a χ2 test.

In multivariate linear regression analysis, we used the vascular end points, i.e. CIMT, CAC or FMD, as the outcome variable, one at a time. The predictors (independent variables) in the model were ATH status (no/yes), age, gender, BMI, smoking (pack years), physical activity index [32], use of alcohol (portions/week), glasses of milk/day, HDL-cholesterol, LDL-cholesterol [due to alternatively apoB (apolipoprotein B) or total cholesterol], triacylglycerols, glucose, systolic BP and high-sensitive CRP. The linear regression analysis for the above-mentioned outcome variables was performed by applying three different models: model 1 using ATH status as a predictor, model 2 adding age and lifestyle factors to model 1, and model 3 adding gender and the remaining major CAD (coronary artery disease) risk factors as predictors to model 2. Owing to high intercorrelations between apoB, LDL-cholesterol and total cholesterol, these were not used simultaneously as predictors in the same statistical model. Owing to skewed distributions, the values for triacylglycerols, insulin and CRP were log-transformed prior to the analyses. For glucose and the consumption of milk and cheese, the distribution remained too skewed after log-transformation; consequently, the Kruskal–Wallis test was employed.

The distributions of categorical variables among ATH groups were compared with the χ2 test. A P value <0.05 was considered significant.

RESULTS

The prevalence of LCT C/T−13910 genotypes C/C, C/T and T/T in our population were as follows: 17.6% (401 out of 2281), 48.9% (1116 out of 2281) and 33.5% (764 out of 2281) respectively.

Association of ATH status with CAD risk factors

The relationship between ATH status, as defined by the C/T−13910 polymorphism (rs4988235), with CAD risk factors and dietary factors as well as indices of early atherosclerosis is shown in Table 1. The consumption of alcohol was highest among subjects with the C/C−13910 genotype (P=0.001) when compared with subjects without ATH (T/T+C/T). The overall consumption of dairy products (dairy product index in Table 1) was lower among subjects with ATH (P<0.001). The difference is explained by the differential consumption of milk (P<0.001), as the consumption of the other dairy products was alike in the two groups (P=0.953). However, neither the total fat intake (g/day) nor the total intake of saturated fat differed in the groups studied (P=0.80 and P=0.99 respectively).

Table 1
Association of ATH status defined by the LCT C/T−13910 genotype (rs4988235) with risk and dietary factors as well as preclinical indicators of atherosclerosis

Values are means±S.D. The values in parentheses are the number of subjects studied for the variable. *The physical activity index was calculated on the basis of a questionnaire; †dairy products (index) represent subjects' habitual consumption of milk and dairy products as portions/day and were assessed with a dietary questionnaire on habitual eating behaviour and food choices; ‡a χ2 test was used for categorical variables, whereas an independent Student's t test was used for continuous variables. Owing to the skewed distribution, the data for dairy products, triacylglycerols, CRP and insulin were log-transformed before analysis; §the distribution remained too skewed after log-transformation and, as a consequence, the Mann–Whitney U test was used.

ATH status
VariableNo (T/T+C/T)Yes (C/C)P value‡
Age (years) 31.7±5.0 (1880) 31.9±4.9 (401) 0.512 
Male gender (%) 44.6 (1880) 46.4 (401) 0.543 
Height (cm) 172.1±9.2 (1867) 172.1±8.9 (398) 0.780 
Weight (kg) 74.5±15.9 (1866) 74.8±16.0 (398) 0.739 
BMI (kg/m225.1±4.4 (1865) 25.1±4.61 (401) 0.763 
Smoking (pack years) 2.96±5.67 (1748) 3.30±6.13 (369) 0.314 
Physical activity index* 9.96±2.36 (1755) 9.75±2.36 (368) 0.120 
Dairy product index (portions/day)† 3.03±1.86 (1754) 2.39±1.54 (369) <0.001 
Milk consumption (glasses/day)§ 1.79±1.84 (1818) 1.12±1.50 (386) <0.001 
Dairy products without milk (portions/day) 1.25±0.60 (1754) 1.25±0.56 (369) 0.953 
Alcohol consumption (g/week) 67.4±96.1 (1852) 85.9±120.5 (396) 0.001 
Systolic BP (mmHg) 116.6±13.1 (1862) 117.2±13.1 (395) 0.374 
Diastolic BP (mmHg) 70.7±10.9 (1862) 70.9±10.4 (395) 0.768 
Total cholesterol (mmol/l) 5.16±0.98 (1880) 5.17±0.99 (401) 0.803 
LDL-cholesterol (mmol/l) 3.28±0.85 (1855) 3.27±0.83 (394) 0.923 
HDL-cholesterol (mmol/l) 1.29±0.31 (1878) 1.31±0.35 (401) 0.120 
Triacylglycerols (mmol/l) 1.34±0.86 (1880) 1.35±0.84 (401) 0.769 
CRP (mg/l) 1.94±3.99 (1880) 1.86±3.73 (401) 0.707 
Glucose (mmol/l)§ 5.06±0.89 (1880) 5.02±0.48 (401) 0.374 
CIMT (mm) 0.581±0.092 (1860) 0.583±0.096 (395) 0.657 
CAC (%/10 mmHg) 2.18±0.74 (1852) 2.16±0.75 (393) 0.752 
FMD (%) 8.00±4.41 (1723) 7.98±4.4 6 (376) 0.944 
ATH status
VariableNo (T/T+C/T)Yes (C/C)P value‡
Age (years) 31.7±5.0 (1880) 31.9±4.9 (401) 0.512 
Male gender (%) 44.6 (1880) 46.4 (401) 0.543 
Height (cm) 172.1±9.2 (1867) 172.1±8.9 (398) 0.780 
Weight (kg) 74.5±15.9 (1866) 74.8±16.0 (398) 0.739 
BMI (kg/m225.1±4.4 (1865) 25.1±4.61 (401) 0.763 
Smoking (pack years) 2.96±5.67 (1748) 3.30±6.13 (369) 0.314 
Physical activity index* 9.96±2.36 (1755) 9.75±2.36 (368) 0.120 
Dairy product index (portions/day)† 3.03±1.86 (1754) 2.39±1.54 (369) <0.001 
Milk consumption (glasses/day)§ 1.79±1.84 (1818) 1.12±1.50 (386) <0.001 
Dairy products without milk (portions/day) 1.25±0.60 (1754) 1.25±0.56 (369) 0.953 
Alcohol consumption (g/week) 67.4±96.1 (1852) 85.9±120.5 (396) 0.001 
Systolic BP (mmHg) 116.6±13.1 (1862) 117.2±13.1 (395) 0.374 
Diastolic BP (mmHg) 70.7±10.9 (1862) 70.9±10.4 (395) 0.768 
Total cholesterol (mmol/l) 5.16±0.98 (1880) 5.17±0.99 (401) 0.803 
LDL-cholesterol (mmol/l) 3.28±0.85 (1855) 3.27±0.83 (394) 0.923 
HDL-cholesterol (mmol/l) 1.29±0.31 (1878) 1.31±0.35 (401) 0.120 
Triacylglycerols (mmol/l) 1.34±0.86 (1880) 1.35±0.84 (401) 0.769 
CRP (mg/l) 1.94±3.99 (1880) 1.86±3.73 (401) 0.707 
Glucose (mmol/l)§ 5.06±0.89 (1880) 5.02±0.48 (401) 0.374 
CIMT (mm) 0.581±0.092 (1860) 0.583±0.096 (395) 0.657 
CAC (%/10 mmHg) 2.18±0.74 (1852) 2.16±0.75 (393) 0.752 
FMD (%) 8.00±4.41 (1723) 7.98±4.4 6 (376) 0.944 

Association of ATH status and the LCT C/T−13910 genotype with markers of early atherosclerosis

In univariate analysis, no significant association between LCT C/T−13910 genotype-defined ATH status and CIMT, CAC or brachial artery FMD was found among the entire study population (Table 1), or among females or males (P=not significant for all groups).

The differently adjusted regression analyses, i.e. the unadjusted model 1, model 2 adjusted with age and lifestyle factors, and the fully adjusted model 3 also adding gender and CAD risk factors as predictors, gave essentially the same results for all major vascular end points, namely CIMT, CAC and FMD. Therefore the numerical results from only the fully adjusted regression model are shown in Table 2. In multiple linear regression analyses, after adjustment for all major covariates, there were no statistically significant associations between ATH status and CIMT, CAC or FMD among all of the subjects (Table 2) or when males and females were analysed separately (results not shown). No significant association between LCT C/T−13910 genotypes and CIMT, CAC or brachial artery FMD was found among the entire study population or in females and males separately (results not shown).

Table 2
Multiple linear regression analysis for predicting CIMT, CAC and FMD in all subjects

Values are non-standardized regression coefficients (β), indicating the magnitude of change which one unit change of predictor value causes in a dependent variable unit. Owing to the skewed distribution, the data on milk consumption and triacylglycerols were log-transformed before analysis, but the values are shown as crude values. *ATH status was defined using a genetic test (rs4988235); †a physical activity index was calculated on the basis of a questionnaire. R2, explanatory portion of the model.

Dependent variable
CIMT (n=1977)CAC (n=1969)FMD (n=1835)
Predictor (entered to the model)βS.E.P valueβS.E.P valueβS.E.P value
ATH (no T/T+C/T; yes=C/C)* 0.005 0.005 0.341 −0.020 0.039 0.599 −0.105 0.262 0.689 
Age (years) 0.005 0.000 0.000 −0.035 0.003 0.000 0.009 0.021 0.656 
Gender (female/male) 0.005 0.005 0.328 −0.181 0.037 0.000 −1.564 0.251 0.000 
BMI (kg/m20.005 0.001 0.000 −0.013 0.004 0.001 0.135 0.027 0.000 
Smoking (pack years) 2.65×10−5 0.000 0.210 0.000 0.000 0.225 −0.001 0.001 0.581 
Physical activity index† 0.001 0.001 0.216 0.016 0.006 0.013 −0.135 0.043 0.002 
Alcohol consumption (g/week) 0.000 0.000 0.586 0.005 0.002 0.005 −0.019 0.014 0.157 
Milk consumption (glasses/day) 0.000 0.001 0.796 −0.005 0.008 0.578 0.127 0.059 0.031 
Systolic BP (mmHg) 0.001 0.000 0.000 −0.017 0.001 0.000 −0.024 0.009 0.005 
LDL-cholesterol (mmol/l) 0.004 0.002 0.106 −0.028 0.019 0.128 0.003 0.128 0.983 
HDL-cholesterol (mmol/l) −0.002 0.007 0.798 −0.056 0.054 0.302 0.839 0.372 0.024 
Triacylglycerols (mmol/l) −0.001 0.003 0.803 −0.064 0.025 0.012 0.243 0.173 0.161 
Glucose (mmol/l) 0.001 0.002 0.661 0.015 0.019 0.418 −0.159 0.118 0.178 
CRP (mg/l) 0.000 0.000 0.839 −0.004 0.004 0.240 −0.002 0.026 0.937 
Adjusted R2 0.141 0.086 0.000 0.246 0.642 0.000 0.066 4.230 0.000 
Dependent variable
CIMT (n=1977)CAC (n=1969)FMD (n=1835)
Predictor (entered to the model)βS.E.P valueβS.E.P valueβS.E.P value
ATH (no T/T+C/T; yes=C/C)* 0.005 0.005 0.341 −0.020 0.039 0.599 −0.105 0.262 0.689 
Age (years) 0.005 0.000 0.000 −0.035 0.003 0.000 0.009 0.021 0.656 
Gender (female/male) 0.005 0.005 0.328 −0.181 0.037 0.000 −1.564 0.251 0.000 
BMI (kg/m20.005 0.001 0.000 −0.013 0.004 0.001 0.135 0.027 0.000 
Smoking (pack years) 2.65×10−5 0.000 0.210 0.000 0.000 0.225 −0.001 0.001 0.581 
Physical activity index† 0.001 0.001 0.216 0.016 0.006 0.013 −0.135 0.043 0.002 
Alcohol consumption (g/week) 0.000 0.000 0.586 0.005 0.002 0.005 −0.019 0.014 0.157 
Milk consumption (glasses/day) 0.000 0.001 0.796 −0.005 0.008 0.578 0.127 0.059 0.031 
Systolic BP (mmHg) 0.001 0.000 0.000 −0.017 0.001 0.000 −0.024 0.009 0.005 
LDL-cholesterol (mmol/l) 0.004 0.002 0.106 −0.028 0.019 0.128 0.003 0.128 0.983 
HDL-cholesterol (mmol/l) −0.002 0.007 0.798 −0.056 0.054 0.302 0.839 0.372 0.024 
Triacylglycerols (mmol/l) −0.001 0.003 0.803 −0.064 0.025 0.012 0.243 0.173 0.161 
Glucose (mmol/l) 0.001 0.002 0.661 0.015 0.019 0.418 −0.159 0.118 0.178 
CRP (mg/l) 0.000 0.000 0.839 −0.004 0.004 0.240 −0.002 0.026 0.937 
Adjusted R2 0.141 0.086 0.000 0.246 0.642 0.000 0.066 4.230 0.000 

DISCUSSION

This is the first general-population-based study suggesting that the genetic locus which causes ATH has no clinically significant effects on the early functional or structural markers of asymptomatic atherosclerosis in young Finns.

There is little data published previously on the effect of ATH on serum lipid concentrations [16,17]. In one earlier study, serum levels of insulin and glucose were found to be lower and HDL-cholesterol levels higher in subjects with ATH compared with others [17]. In our population-based study, we were not able to find any differences in serum levels of insulin and glucose between subjects with and without ATH. Instead, the LCT C/C−13910 genotype was associated with HDL-cholesterol in that it tended to be higher in subjects carrying the C/C−13910 genotype when the population was stratified according to ATH status; however, the difference in HDL-cholesterol remained statistically insignificant. Although the overall consumption of dairy products was lower in subjects with the ATH, serum total cholesterol or LDL-cholesterol, insulin, glucose, high-sensitive CRP or homocysteine concentrations did not differ between subjects with or without ATH. Therefore our findings do not support the suggestion that differences in the dietary intakes between subjects with and without ATH are translated into differences in early atherosclerotic changes through an association with serum lipid levels.

The lower consumption of dairy products among the subjects with ATH is in line with earlier results from Finnish, Estonian and Austrian populations [7,12,15,38]. In addition, ATH was associated with a higher consumption of alcoholic beverages among men, a new finding requiring confirmation in subsequent investigations.

In epidemiological studies, the dietary consumption of milk [39,40] and calcium [4143], both of which are altered in connection with ATH, have been implicated as risk factors for CAD. On the other hand, as a balancing view to these earlier epidemiological results, several studies have also indicated that milk and dairy products may yield some beneficial effect in relation to CAD risk factors, such as BP and body weight control [4448]. Therefore our present study, which shows that ATH, a quite common condition, is not related to CIMT, carotid elasticity or an indicator of endothelial function, i.e. brachial artery FMD, makes an important contribution to the literature in this field. Our findings do not support either the suggestion that differences in the dietary intakes between subjects with and without ATH are translated into differences in early atherosclerotic changes directly without the effect on serum lipid levels.

However, it is possible that the LCT loci affect CAD risk through mechanisms not reflected in CIMT or that the relatively young age range of the present cohort precludes the ability to detect an effect which may become discernible in older individuals. These possibilities require further investigation, and our results do not exclude the possibility that the LCT C/T−13910 genotype or ATH status could be associated with more advanced clinically symptomatic atherosclerotic changes, i.e. CAD or myocardial infarction, developing 20–30 years later.

The major limitation of our present study traces back to our dietary questionnaire which only counts the number of milk and dairy product portions and does not account for the actual portion size. It therefore does not measure the true quantity of dairy product consumption. Although the sample size is seemingly large, the numbers and thus the statistical power may still be insufficient to formally exclude the association with BP or vascular risk markers.

In conclusion, our results do not provide further evidence for the involvement of ATH, as defined by the LCT gene locus rs4988235, in determining early atherosclerosis risk in a large cohort of young Finnish individuals.

Abbreviations

     
  • apoB

    apolipoprotein B

  •  
  • ATH

    adult-type hypolactasia

  •  
  • BMI

    body mass index

  •  
  • BP

    blood pressure

  •  
  • CAC

    carotid artery compliance

  •  
  • CAD

    coronary artery disease

  •  
  • CIMT

    carotid intima-media thickness

  •  
  • CRP

    C-reactive protein

  •  
  • CV

    coefficient of variation

  •  
  • FMD

    flow-mediated dilation

  •  
  • HDL

    high-density lipoprotein

  •  
  • LCT

    gene encoding lactase-phlorizin hydrolase

  •  
  • LDL

    low-density lipoprotein

  •  
  • SNP

    single nucleotide polymorphism

This study was supported financially by the Emil Aaltonen Foundation (to T. L.), the Academy of Finland (grant numbers 77841, 210283 and 117941), the Social Insurance Institution of Finland, the Turku University Foundation, the Juho Vainio Foundation, the Finnish Foundation of Cardiovascular Research, the Finnish Cultural Foundation, and the Tampere and Turku University Central Hospital Medical Funds.

References

References
1
Sahi
 
T.
Isokoski
 
M.
Jussila
 
J.
Launiala
 
K.
Pyörälä
 
K.
 
Recessive inheritance of adult-type lactose malabsorption
Lancet
1973
, vol. 
ii
 (pg. 
823
-
826
)
2
Jussila
 
J.
Isokoski
 
M.
Launiala
 
K.
 
Prevalence of lactose malabsorption in a Finnish rural population
Scand. J. Gastroenterol.
1970
, vol. 
5
 (pg. 
49
-
56
)
3
Sahi
 
T.
Isokoski
 
M.
Jussila
 
J.
Launiala
 
K.
 
Lactose malabsorption in Finnish children of school age
Acta Paediatr. Scand.
1972
, vol. 
61
 (pg. 
11
-
16
)
4
Rasinperö
 
H.
Savilahti
 
E.
Enattah
 
N. S.
, et al 
A genetic test which can be used to diagnose adult-type hypolactasia in children
Gut
2004
, vol. 
53
 (pg. 
1571
-
1576
)
5
Enattah
 
N. S.
Sahi
 
T.
Savilahti
 
E.
Terwilliger
 
J. D.
Peltonen
 
L.
Järvelä
 
I.
 
Identification of a variant associated with adult-type hypolactasia
Nat. Genet.
2002
, vol. 
30
 (pg. 
233
-
237
)
6
Enattah
 
N. S.
Sulkava
 
R.
Halonen
 
P.
Kontula
 
K.
Järvelä
 
I.
 
Genetic variant of lactase-persistent C/T−13910 is associated with bone fractures in very old age
J. Am. Geriatr. Soc.
2005
, vol. 
53
 (pg. 
79
-
82
)
7
Lehtimäki
 
T.
Hemminki
 
J.
Rontu
 
R.
, et al 
The effects of adult-type hypolactasia on body height growth and dietary calcium intake from childhood into young adulthood: a 21-year follow-up study: the Cardiovascular Risk in Young Finns Study
Pediatrics
2006
, vol. 
118
 (pg. 
1553
-
1559
)
8
Kuokkanen
 
M.
Enattah
 
N. S.
Oksanen
 
A.
Savilahti
 
E.
Orpana
 
A.
Järvelä
 
I.
 
Transcriptional regulation of the lactase-phlorizin hydrolase gene by polymorphisms associated with adult-type hypolactasia
Gut
2003
, vol. 
52
 (pg. 
647
-
652
)
9
Olds
 
L. C.
Sibley
 
E.
 
Lactase persistence DNA variant enhances lactase promoter activity in vitro: functional role as a cis regulatory element
Hum. Mol. Genet.
2003
, vol. 
12
 (pg. 
2333
-
2340
)
10
Enattah
 
N. S.
Kuokkanen
 
M.
Forsblom
 
C.
, et al 
Correlation of intestinal disaccharidase activities with the C/T−13910 variant and age
World J. Gastroenterol.
2007
, vol. 
13
 (pg. 
3508
-
3512
)
11
Lember
 
M.
Torniainen
 
S.
Kull
 
M.
, et al 
Lactase non-persistence and milk consumption in Estonia
World J. Gastroenterol.
2006
, vol. 
12
 (pg. 
7329
-
7331
)
12
Anthoni
 
S. R.
Rasinperä
 
H. A.
Kotamies
 
A. J.
, et al 
Molecularly defined adult-type hypolactasia among working age people with reference to milk consumption and gastrointestinal symptoms
World J. Gastroenterol.
2007
, vol. 
13
 (pg. 
1230
-
1235
)
13
Männistö
 
S.
Ovaskainen
 
M.
Valsta
 
L.
 
The National Findiet 2002 study, Series B B3
2003
Helsinki, Finland
Publications of National Public Health Institute
14
Kleemola
 
P.
Virtanen
 
M.
Pietinen
 
P.
 
The 1992 Dietary Survey of Finnish Adults, Series B B2
1994
Helsinki, Finland
Publications of the National Public Health Institute
15
Obermayer-Pietsch
 
B. M.
Bonelli
 
C. M.
Walter
 
D. E.
, et al 
Genetic predisposition for adult lactose intolerance and relation to diet, bone density, and bone fractures
J. Bone Miner. Res.
2004
, vol. 
19
 (pg. 
42
-
47
)
16
Sahi
 
T.
Jussila
 
J.
Penttila
 
I. M.
Sarna
 
S.
Isokoski
 
M.
 
Serum lipids and proteins in lactose malabsorption
Am. J. Clin. Nutr.
1977
, vol. 
30
 (pg. 
476
-
481
)
17
Russo
 
F.
De Carne
 
M.
Buonsante
 
A.
, et al 
Hypolactasia and metabolic changes in post-menopausal women
Maturitas
1997
, vol. 
26
 (pg. 
193
-
202
)
18
Blacher
 
J.
Pannier
 
B.
Guerin
 
A. P.
Marchais
 
S. J.
Safar
 
M. E.
London
 
G. M.
 
Carotid arterial stiffness as a predictor of cardiovascular and all-cause mortality in end-stage renal disease
Hypertension
1998
, vol. 
32
 (pg. 
570
-
574
)
19
Burke
 
G. L.
Evans
 
G. W.
Riley
 
W. A.
, et al 
Arterial wall thickness is associated with prevalent cardiovascular disease in middle-aged adults. The Atherosclerosis Risk in Communities (ARIC) Study
Stroke
1995
, vol. 
26
 (pg. 
386
-
391
)
20
Celermajer
 
D. S.
Sorensen
 
K. E.
Gooch
 
V. M.
, et al 
Non-invasive detection of endothelial dysfunction in children and adults at risk of atherosclerosis
Lancet
1992
, vol. 
340
 (pg. 
1111
-
1115
)
21
Chan
 
S. Y.
Mancini
 
G. B.
Kuramoto
 
L.
Schulzer
 
M.
Frohlich
 
J.
Ignaszewski
 
A.
 
The prognostic importance of endothelial dysfunction and carotid atheroma burden in patients with coronary artery disease
J. Am. Coll. Cardiol.
2003
, vol. 
42
 (pg. 
1037
-
1043
)
22
Gokce
 
N.
Keaney
 
J. F.
Hunter
 
L. M.
Watkins
 
M. T.
Menzoian
 
J. O.
Vita
 
J. A.
 
Risk stratification for postoperative cardiovascular events via noninvasive assessment of endothelial function: a prospective study
Circulation
2002
, vol. 
105
 (pg. 
1567
-
1572
)
23
Juonala
 
M.
Viikari
 
J. S.
Kähönen
 
M.
, et al 
Geographic origin as a determinant of carotid artery intima-media thickness and brachial artery flow-mediated dilation: the Cardiovascular Risk in Young Finns study
Arterioscler. Thromb. Vasc. Biol.
2005
, vol. 
25
 (pg. 
392
-
398
)
24
O'Leary
 
D. H.
Polak
 
J. F.
Kronmal
 
R. A.
Manolio
 
T. A.
Burke
 
G. L.
Wolfson
 
S. K.
 
Carotid-artery intima and media thickness as a risk factor for myocardial infarction and stroke in older adults. Cardiovascular Health Study Collaborative Research Group
N. Engl. J. Med.
1999
, vol. 
340
 (pg. 
14
-
22
)
25
Oliver
 
J. J.
Webb
 
D. J.
 
Noninvasive assessment of arterial stiffness and risk of atherosclerotic events
Arterioscler. Thromb. Vasc. Biol.
2003
, vol. 
23
 (pg. 
554
-
566
)
26
Raitakari
 
O. T.
Juonala
 
M.
Kähönen
 
M.
, et al 
Cardiovascular risk factors in childhood and carotid artery intima-media thickness in adulthood: the Cardiovascular Risk in Young Finns Study
JAMA, J. Am. Med. Assoc.
2003
, vol. 
290
 (pg. 
2277
-
2283
)
27
Tounian
 
P.
Aggoun
 
Y.
Dubern
 
B.
, et al 
Presence of increased stiffness of the common carotid artery and endothelial dysfunction in severely obese children: a prospective study
Lancet
2001
, vol. 
358
 (pg. 
1400
-
1404
)
28
Yufu
 
K.
Takahashi
 
N.
Anan
 
F.
Hara
 
M.
Yoshimatsu
 
H.
Saikawa
 
T.
 
Brachial arterial stiffness predicts coronary atherosclerosis in patients at risk for cardiovascular diseases
Jpn Heart J.
2004
, vol. 
45
 (pg. 
231
-
242
)
29
Corretti
 
M. C.
Anderson
 
T. J.
Benjamin
 
E. J.
, et al 
Guidelines for the ultrasound assessment of endothelial-dependent flow-mediated vasodilation of the brachial artery: a report of the International Brachial Artery Reactivity Task Force
J. Am. Coll. Cardiol.
2002
, vol. 
39
 (pg. 
257
-
265
)
30
Akerblom
 
H. K.
Viikari
 
J.
Uhari
 
M.
, et al 
Atherosclerosis precursors in Finnish children and adolescents. I. General description of the cross-sectional study of 1980, and an account of the children's and families' state of health
Acta Paediatr. Scand. Suppl.
1985
, vol. 
318
 (pg. 
49
-
63
)
31
Juonala
 
M.
Viikari
 
J. S.
Hutri-Kähönen
 
N.
, et al 
The 21-year follow-up of the Cardiovascular Risk in Young Finns Study: risk factor levels, secular trends and east-west difference
J. Intern. Med.
2004
, vol. 
255
 (pg. 
457
-
468
)
32
Telama
 
R.
Yang
 
X.
Viikari
 
J.
Välimäki
 
I.
Wanne
 
O.
Raitakari
 
O.
 
Physical activity from childhood to adulthood: a 21-year tracking study
Am. J. Prev. Med.
2005
, vol. 
28
 (pg. 
267
-
273
)
33
Lehtimäki
 
T.
Moilanen
 
T.
Viikari
 
J.
, et al 
Apolipoprotein E phenotypes in Finnish youths: a cross-sectional and 6-year follow-up study
J. Lipid Res.
1990
, vol. 
31
 (pg. 
487
-
495
)
34
Mikkila
 
V.
Räsänen
 
L.
Raitakari
 
O. T.
Pietinen
 
P.
Viikari
 
J.
 
Longitudinal changes in diet from childhood into adulthood with respect to risk of cardiovascular diseases: the Cardiovascular Risk in Young Finns Study
Eur. J. Clin. Nutr.
2004
, vol. 
58
 (pg. 
1038
-
1045
)
35
Mikkila
 
V.
Räsänen
 
L.
Raitakari
 
O. T.
Pietinen
 
P.
Viikari
 
J.
 
Consistent dietary patterns identified from childhood to adulthood: the cardiovascular risk in Young Finns Study
Br. J. Nutr.
2005
, vol. 
93
 (pg. 
923
-
931
)
36
Järvisalo
 
M. J.
Jartti
 
L.
Karvonen
 
M. K.
, et al 
Enhanced endothelium-dependent vasodilation in subjects with Proline7 substitution in the signal peptide of neuropeptide Y
Atherosclerosis
2003
, vol. 
167
 (pg. 
319
-
326
)
37
Livak
 
K. J.
 
Allelic discrimination using fluorogenic probes and the 5′ nuclease assay
Genet. Anal.
1999
, vol. 
14
 (pg. 
143
-
149
)
38
Obermayer-Pietsch
 
B. M.
Gugatschka
 
M.
Reitter
 
S.
, et al 
Adult-type hypolactasia and calcium availability: decreased calcium intake or impaired calcium absorption?
Osteoporosis Int.
2007
, vol. 
18
 (pg. 
445
-
451
)
39
Elwood
 
P.
 
Milk, coronary disease and mortality
J. Epidemiol. Community Health
2001
, vol. 
55
 pg. 
375
 
40
Strain
 
J. J.
 
Milk consumption, lactose and copper in the aetiology of ischaemic heart disease
Med. Hypotheses
1988
, vol. 
25
 (pg. 
99
-
101
)
41
Leskinen
 
Y.
Salenius
 
J. P.
Lehtimäki
 
T.
Huhtala
 
H.
Saha
 
H.
 
The prevalence of peripheral arterial disease and medial arterial calcification in patients with chronic renal failure: requirements for diagnostics
Am. J. Kidney Dis.
2002
, vol. 
40
 (pg. 
472
-
479
)
42
Goldsmith
 
D.
Ritz
 
E.
Covic
 
A.
 
Vascular calcification: a stiff challenge for the nephrologist: does preventing bone disease cause arterial disease?
Kidney Int.
2004
, vol. 
66
 (pg. 
1315
-
1333
)
43
Seely
 
S.
 
Possible connection between milk and coronary heart disease: the calcium hypothesis
Med. Hypotheses
2000
, vol. 
54
 (pg. 
701
-
703
)
44
Pfeuffer
 
M.
Schrezenmeir
 
J.
 
Milk and the metabolic syndrome
Obes. Rev.
2007
, vol. 
8
 (pg. 
109
-
118
)
45
Alvarez-Leon
 
E. E.
Roman-Vinas
 
B.
Serra-Majem
 
L.
 
Dairy products and health: a review of the epidemiological evidence
Br. J. Nutr.
2006
, vol. 
96
 
Suppl. 1
S94
S99
46
Al-Delaimy
 
W. K.
Rimm
 
E.
Willett
 
W. C.
Stampfer
 
M. J.
Hu
 
F. B.
 
A prospective study of calcium intake from diet and supplements and risk of ischemic heart disease among men
Am. J. Clin. Nutr.
2003
, vol. 
77
 (pg. 
814
-
818
)
47
Hajjar
 
I. M.
Grim
 
C. E.
Kotchen
 
T. A.
 
Dietary calcium lowers the age-related rise in blood pressure in the United States: the NHANES III survey
J. Clin. Hypertens.
2003
, vol. 
5
 (pg. 
122
-
126
)
48
Pereira
 
M. A.
Jacobs
 
D. R.
Van Horn
 
L.
Slattery
 
M. L.
Kartashov
 
A. I.
Ludwig
 
D. S.
 
Dairy consumption, obesity, and the insulin resistance syndrome in young adults: the CARDIA Study
JAMA, J. Am. Med. Assoc.
2002
, vol. 
287
 (pg. 
2081
-
2089
)