Methods

All study participants provided written informed consent. The ethics committee of the medical faculty of Lund University approved the studies. Procedures were in accord with institutional guidelines.

The study population was derived from the Malmö Diet and Cancer Study (MDC). BP and other cardiovascular risk factors were measured in a subsample of the MDC study, referred to as the MDC cardiovascular arm (MDC-CVA; n = 6,103). Successfully extracted genomic DNA was available from 5,763 participants in the MDC-CVA. Complete data for components of MetS (defined later) and the CDH13 rs11646213 genotype were available for 4,942. In analyses of the European Group for the Study of Insulin Resistance definition, 500 patients (with diabetes and/or without data on fasting insulin concentration in plasma) were excluded from the cohort, leaving 4,442 subjects for analysis.

In the Malmö Preventive Project (MPP) 33,346 Swedish participants (22,444 men and 10,902 women, mean age 49 years) from the city of Malmö in southern Sweden participated in health screening from 1974 through 1992 (attendance rate 71%). All subjects underwent physical examination and measurements of fasting blood glucose and triglyceride concentrations were performed. Information on lifestyle factors and medical history was obtained from a questionnaire. Of subjects participating in the initial screening 4,931 died and 551 were lost during follow-up for other reasons. Of eligible subjects 25,000 were invited to a rescreening visit from 2002 through 2006 including physical examination and fasting blood samples for measurements of glucose, triglyceride, and high-density lipoprotein (HDL) cholesterol concentrations. Of the invited subjects 18,240 participated in the rescreening; 565 were excluded from the present study because of lack of DNA or crucial clinical information. Thus 17,675 participants were included in the follow-up study.

Waist circumference was measured at the umbilicus level with the patient standing. Body mass index was calculated as the ratio of weight in kilograms to the square of height in meters. Obesity was defined as a body mass index ≥30 kg/m ² . BP was measured by specially trained nurses in the right brachial artery with some differences between studies (see supplementary methods available online). Increased BP was defined as systolic BP ≥130 mm Hg or diastolic BP ≥85 mm Hg or treatment by antihypertensive drugs according to MetS criteria definitions (provided later).

Details of the measurement of serum lipids, serum insulin, and whole blood glucose have been published elsewhere. Diabetes was defined as fasting blood glucose ≥6.1 mmol/L (MDC-CVA and MPP at baseline) or ≥7.0 mmol/L (MPP at reinvestigation) or long-term therapy with antidiabetic drugs or self-reported history of diabetes.

When continuous traits were analyzed, to adjust for use of specific medications that could interfere with recorded values, we added 1 SD to the standardized age- and gender-adjusted residuals when data were available. Thus we added 1 SD to subjects with long-term antihypertensive treatments (n = 814 in MDC-CVA, n = 774 in MPP at baseline, n = 6,666 in MPP at reinvestigation), glucose-lowering agents (n = 68 in MDC-CVA, n = 1,207 in MPP at reinvestigation), and specific triglyceride-lowering drugs (n = 109 in MDC-CVA, n = 162 in MPP at reinvestigation).

Data about menopause status and hormone-replacement therapy were recorded from the standardized questionnaire and the “7-day book menu,” which subjects participating in the 2 cohorts were asked to fill out. Women who confirmed that their menstruation had ceased or who used hormone-replacement therapy because of menopausal problems were classified as postmenopausal.

MetS was defined according to National Cholesterol Education Program/Adult Treatment Panel III criteria, the International Diabetes Federation definition, the European Group for the Study of Insulin Resistance definition (subjects without diabetes only), and the most recent American Heart Association/National Heart, Lung, and Blood Institute definition (see supplementary methods for details).

For the European Group for the Study of Insulin Resistance definition it is necessary to detect insulin resistance. We defined insulin resistance as homeostasis model assessment values >75th percentile (i.e., >1.98 mmol/mU/L ² in MDC-CVA) based on the distribution of all subjects without diabetes included in the present studies.

In the MPP at baseline, because waist and HDL cholesterol measurements were not available for most participants, we were unable to construct the definitions of MetS according to any of the common definitions and therefore defined the components of the MetS as (1) a body mass index ≥30 kg/m ² , (2) triglycerides ≥1.7 mmol/L and/or lipid-lowering treatment, (3) BP ≥130/85 mm Hg and/or antihypertensive medication, and (4) fasting plasma glucose ≥5.6 mmol/L and/or overt diabetes. Presence of ≥3 of these components defined MetS.

In the MDC-CVA and MPP at reinvestigation we constructed a MetS score to analyze MetS as a quantitative trait. First, we adjusted each variable included in the MetS definitions for gender and age. Second, residuals from these linear regression analyses were standardized by subtracting age- and gender-specific means and dividing by age- and gender-specific standard deviation (SD). Because resultant residuals were approximately normally distributed, the standardization process yielded trait values that followed an n ∼ (0,1) distribution. Because many subjects were using antihypertensive, antilipemic, or antidiabetic medications, we added 1 SD if a patient was treated. Outliers for each trait were handled as follows: subjects with values ±>3 SD were set as ±3 SD. To generate the MetS score for each subject’s available observations, we combined standardized residuals for each component trait as follows: MetS score = mean BP plus triglycerides plus glucose plus waist circumference minus HDL. HDL was subtracted from the score because it is protective against cardiovascular diseases and tends to be inversely correlated with the other component traits; thus lower HDL values correspond to a higher MetS score.

Genotypes of the CDH13 rs11646213 T > A polymorphism (db single-nucleotide polymorphism accession number rs11646213) were determined by end-point fluorescent measurements.

All data except for the power analysis were analyzed with SPSS 18.0 (SPSS, Inc., Chicago, Illinois). Power calculation was performed using Power and Sample Size Calculator 2/1/31 (Vanderbilt University Medical Center, Nashville, Tennessee). Continuous variables are presented as mean ± SD. Pearson chi-square test was used to compare group frequencies and to test for deviations from the Hardy–Weinberg equilibrium. Multiple logistic and linear regression analyses were used in multivariate models with MetS status, individual MetS components, and/or MetS score as dependent variables and genotype, age, and gender as independent variables. For variables with skewed distributions such as triglycerides, log-normalized values were used in the analysis. All tests were 2-sided and p values <0.05 were considered statistically significant.

Results

Genotyping success rates in subsamples with complete data for components of MetS were 97.3% in MDC-CVA and 96.9% in MPP. In MDC-CVA there were 1,818 CDH13 rs11646213 TT homozygotes (36.8%), 2,367 CDH13 rs11646213 TA heterozygotes (47.9%), and 757 CDH13 rs11646213 AA homozygotes (15.3%); in MPP there were 6,381 CDH13 rs11646213 TT homozygotes (36.1%), 8,441 CDH13 rs11646213 TA heterozygotes (47.8%), and 2,853 CDH13 rs11646213 AA homozygotes (16.1%).

Genotype distributions did not deviate from Hardy–Weinberg equilibrium in all samples (predicted heterozygosity 0.476, observed heterozygosity 0.480, p = 0.54 in MDC-CVA; predicted heterozygosity 0.480, observed heterozygosity 0.478, p = 0.56 in MPP). Clinical characteristics of all participants are presented in Table 1 . Detailed analyses about statistical power are reported in supplementary Table S1 (available online). Based on preliminary analyses of the data we focused our attention especially on the autosomal recessive genetic model, which is presented in the main report; data about autosomal dominant and additive genetic models are presented in the supplementary material . In the MDC-CVA as a whole, when adjusted for medication use, none of the individual MetS components resulted in statistical differences among CDH13 rs11646213 genotypes regardless of genetic model ( Table 2 and complementary Table C1, available online). However, when stratifying the population by gender, MetS score showed significant increases in CDH13 rs11646213 AA homozygotic women but not men compared to carriers of the G-allele, a result driven especially by a tendency toward higher triglycerides and systolic BP and lower HDL cholesterol, even if none of those attained formal statistical significance ( Table 2 ). In the MPP at reinvestigation CDH13 rs11646213 AA homozygotes had higher MetS scores compared to carriers of the G-allele only in women. Similarly to the MDC-CVA, HDL cholesterol showed a nonsignificant tendency toward a lower level in AA homozygotes compared to G-carriers.

Table 2

Beta coefficient ± SE for CDH13 rs11646213 T → A polymorphism tested by linear regression according to autosomal recessive genetic model and after stratification for gender

Variables (individual MetS components)	Entire Population	p Value	Women	p Value	Men	p Value
Malmö Diet and Cancer Study cardiovascular arm
Systolic blood pressure (mm Hg)	0.080 ± 0.045	0.074	0.099 ± 0.059	0.09	0.055 ± 0.069	0.43
Diastolic blood pressure (mm Hg)	0.064 ± 0.045	0.16	0.087 ± 0.058	0.13	0.033 ± 0.072	0.65
Waist circumference (cm)	0.043 ± 0.40	0.28	0.087 ± 0.053	0.10	−0.014 ± 0.060	0.81
Body mass index (kg/m 2 )	0.165 ± 0.154	0.29	0.292 ± 0.219	0.18	−0.011 ± 0.209	0.96
Triglycerides (mmol/L)	0.043 ± 0.040	0.29	0.098 ± 0.050	0.052	−0.030 ± 0.064	0.64
Glucose (mmol/L)	−0.031 ± 0.042	0.46	−0.023 ± 0.051	0.66	−0.042 ± 0.070	0.54
High-density lipoprotein cholesterol (mmol/L)	−0.048 ± 0.039	0.22	0.101 ± 0.052	0.054	0.020 ± 0.060	0.74
Metabolic syndrome score	0.207 ± 0.128	0.10	0.382 ± 0.168	0.023	−0.022 ± 0.197	0.91
Malmö Preventive Project at baseline
Systolic blood pressure (mm Hg)	0.008 ± 0.022	0.71	0.006 ± 0.041	0.88	0.010 ± 0.025	0.70
Diastolic blood pressure (mm Hg)	0.016 ± 0.022	0.48	0.022 ± 0.038	0.56	0.013 ± 0.027	0.63
Body mass index (kg/m 2 )	0.067 ± 0.067	0.32	0.064 ± 0.036	0.07	−0.008 ± 0.023	0.74
Triglycerides (mmol/L)	0.015 ± 0.020	0.46	0.002 ± 0.031	0.95	0.022 ± 0.026	0.39
Glucose (mmol/L)	0.019 ± 0.019	0.32	0.029 ± 0.032	0.38	0.013 ± 0.022	0.56
Malmö Preventive Project reinvestigation
Systolic blood pressure (mm Hg)	0.011 ± 0.024	0.64	0.010 ± 0.041	0.81	0.012 ± 0.029	0.69
Diastolic blood pressure (mm Hg)	0.032 ± 0.023	0.17	0.046 ± 0.039	0.23	0.023 ± 0.029	0.42
Waist circumference (cm)	0.005 ± 0.020	0.81	0.062 ± 0.037	0.09	−0.027 ± 0.024	0.26
Body mass index (kg/m 2 )	0.009 ± 0.020	0.65	0.075 ± 0.038	0.051	0.09 ± 0.020	0.65
Triglycerides (mmol/L)	0.017 ± 0.021	0.40	0.050 ± 0.032	0.12	−0.001 ± 0.027	0.98
Glucose (mmol/L)	0.016 ± 0.024	0.51	0.030 ± 0.036	0.41	0.007 ± 0.031	0.81
High-density lipoprotein cholesterol (mmol/L)	−0.023 ± 0.020	0.25	−0.070 ± 0.038	0.07	0.003 ± 0.024	0.91
Metabolic syndrome score	0.109 ± 0.078	0.16	0.271 ± 0.134	0.043	0.015 ± 0.096	0.88

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