Circadian clocks regulate the timing of biological events including the sleep-wake cycle, energy metabolism, and secretion of hormones. The principal clock conducting the circadian system is located in the suprachiasmatic nuclei of the anterior hypothalamus. From the brain, information is sent out to regulate and reset the peripheral clocks [1]. Seasonal variations in behavior are generated by the principal clock as well [2]. Light exposures stimulate the principal clock through pathways from the retina, and the most important cues for reset of the principal circadian clock are the light-dark transitions, while the peripheral clocks are set by metabolic signals in response to feeding cycles [3]. With shortage of daylight, the metabolic cycles may take over and serve as the standard for the circadian clockwork [4]. In hibernating mammals, the metabolic futile cycle can provide the animal with those circadian signals needed for reset [5]. When there exists no light-dark transitions to reset the principal clock, reindeer living above the Arctic Circle use the metabolic cycles as the reference instead [6].

The molecular circadian clock consists of multiple positive and negative feedback loops that generate the 24-hour oscillation of target genes. In the positive loop NPAS2 (MOP4) protein [7], which plays an overlapping role with the CLOCK protein [8], pairs up with ARNTL (BMAL1 or MOP3) protein. These heterodimers activate the transcription of target genes (for review, see [9]). Downstream, PER and CRY proteins pair up and execute the negative loop. Nuclear receptor co-activators and repressors and several post-transcriptional modifications are necessary for clock precision. In addition, clockwork output molecules can provide an input to the following cycles [10].

Circadian clocks and energy metabolism are linked because the disruptions of the clockwork lead to alterations in metabolism and vice versa (for review, see [11]). Mutation in the Clock gene leads to metabolic syndrome in mice [12], and in humans Clock polymorphisms have been associated with obesity and metabolic syndrome [13,14]. Cellular metabolic states can serve as a link between stimuli from the habitat and drive for the clockwork, because the reduced forms of nicotinamide adenine dinucleotide cofactors stimulate DNA binding of the NPAS2-ARNTL [15] and CLOCK-ARNTL [16] heterodimers, whereas the oxidized forms inhibit the binding [17]. Npas2-deficient mice have reduced ability to adapt to restricted feeding [18], whereas Clock-deficient mice adapt to it even better than do wild-type mice [19], suggesting a key role of NPAS2.

Herein, we hypothesized that circadian clock polymorphisms contribute to the routine seasonal variations and to the metabolic syndrome. Our earlier finding that seasonality was associated with the metabolic syndrome [20], gave a rationale for the current study.

This study was part of a nationwide health interview and examination survey, the Health 2000 Study, which was carried out in Finland, a north-eastern (60–70°N, 20–31°E) European country with about 5 million inhabitants, from September 2000 to June 2001. The two-stage stratified cluster sampling design was planned by Statistics Finland. The sampling frame comprised adults living in mainland Finland. This frame was regionally stratified according to the five university hospital regions, or catchments areas, each containing roughly one million inhabitants. From each university hospital region, 16 health care districts were sampled as clusters (80 health care districts in the whole country, including 160 municipalities, or groups of municipalities with joint primary care). The 15 biggest health care districts in the country were all selected in the sample and their sample sizes were proportional to population size. The remaining 65 health care districts were selected by systematic probability proportional to size sampling in each stratum, and their sample sizes (ranging from 50 to 100) were equal within each university hospital region, the total number of persons drawn from a university hospital region being proportional to the corresponding population size. The 80 health care districts were the primary sampling units, and the ultimate sampling units were persons who were selected by systematic sampling from the health centre districts. From these 80 health care districts, a random sample of individuals was drawn using the data provided by Population Register Centre. Its population information system contains the official information for the whole country on the Finnish citizens and aliens residing permanently in Finland. All the persons aged 30 and over (n = 8028) who were identified from the nationally representative sample by The Social Insurance Institution of Finland were contacted in person. Interviewers attended training sessions on the specific themes that were to be covered in the computer-assisted interviews. Of the final sample of 7979 persons, 6986 (88%) were interviewed at home or institution face to face and 6354 (80%) attended the health status examination in a local health center or equal setting, while 416 took part in the health status examination at home or in an institution. Overall, 84% participated either in the health status examination proper or in the examination at home. All the methods are reported in more detail on the Internet site of the Health 2000 .

The allele frequencies and genotype distributions of the SNPs are shown in Table 1. The first 100 samples genotyped indicated that in our Finnish study population four SNPs were not polymorphic, including Arntl2 rs35878285, Cry2 rs2863712, Ncoa3 rs2230783 and Per2 S662G, so these were excluded from further analysis. Each polymorphic SNP was then analyzed in relation to seasonality and to metabolic syndrome risk factors. The significant results are presented in Table 2.

We found associations with circadian clock genes and the risk factors for metabolic syndrome. Npas rs11541353 was associated with hypertension, the minor allele being protective against hypertension (T vs. C, OR = 0.54, Corrected P-value = 0.02). The results almost the same when people getting treatment for their hypertension were included in group (T vs. C, OR = 0.53, Corrected P-value = 0.015). Per2 10870 was associated with glucose metabolism. 10870 minor allele reduced the risk of raised plasma glucose (G vs. A, Beta coefficient = -0.010, Corrected P-value = 0.049).

Our main results herein are that Npas2 is linked to hypertension and that Per2 is associated with blood glucose levels.

Seasonality and disruption of circadian molecular clockwork are risk factors for metabolic syndrome ([12,20]. We now found that the common risk factors for metabolic syndrome are associated with polymorphisms in circadian clock genes. Npas2 rs11541353 was associated with hypertension in the Finnish population. Earlier, Arntl was linked to hypertension and type 2 diabetes mellitus [29]. Now, we demonstrate herein the associations of Npas2 with hypertension and of Per2 with blood glucose levels.

Together these earlier findings and those of ours emphasize the importance of the circadian system and its core genes in regulation of blood pressure, and point to a role in pathological situations. Moreover, they parallel to SAD in which there is a strong metabolic component and with which this unit of ARNTL, NPAS2 and PER2 is associated [30]. There are often not only disturbances in the metabolic networks [31] but also disruptions of the circadian rhythms [32] together with pronounced seasonal changes in mood and behavior [33] in individuals having affective disorders. Now, this may concern the general population as well.

Npas2 rs11541353 is a missense mutation, leading to substitution of serine with leusine in the amino acid position 471. Npas2 rs11541353 minor allele was protective against hypertension and heterozygosity of Npas2 rs11541353 is protective against Seasonal affective disorder (SAD) [30]. These findings reveal that protection from seasonal variations and protection from high blood pressure go hand in hand in some cases. However, Partonen et al. also found that homozygosity for both Npas2 rs11541353 minor and major alleles was a major risk factor for SAD. Combining these results, persons with two major alleles of Npas2 rs11541353 have substantially increased risk not only for SAD but also for hypertension. However, when a person has two Npas2 rs11541353 minor alleles, the results are difficult to interpret, as the homozygosity increases the odds for SAD, but protects against hypertension. Next, the phenotypes in terms of SAD and hypertension in Npas2 rs11541353 homozygous and heterozygous persons need to be analyzed.

Our results indicate, that Per2 10870 contributed to changes in glucose metabolism. Per2 10870 is an intronic mutation originally found by Spanagel et al (2005), when searching for the Per2 SNPs modulating alcohol intake in mice. Its minor allele G was protective against high alcohol intake in humans [34] but increased the odds for SAD [30]. In our current study, the minor allele G reduced the risk for raised plasma glucose levels. Lamia et al. previously demonstrated that Per1-/-;Per2-/- mice have altered blood glucose homeostasis [35]. Another recent study demonstrated that administration of metformin, one of the most commonly used drugs for type 2 diabetes, leads to the degradation of PER2 and to a phase advance in the circadian gene expression [36]. It remains to be elucidated whether PER proteins are independently important for glucose homeostasis or does their role in the circadian clock lead to the effects seen.

Woon et al. found association between Arntl and hypertension and type 2 diabetes mellitus [29]. Our SNP selection did not include the SNPs used in their study, which can explain why we failed to see any associations. Recent studies have also found association between Clock-gene polymorphism and the metabolic syndrome in man [13,14]. It is of note that we did not find support to these links in our study. We did, however, find several interesting associations, which failed to show statistically significant p-values after correction (Table 3). These include associations between DRD2 rs6277 and blood glucose levels, PLCB4 rs6077510 and Per2 SNP rs934945 and waist circumference, and Vipr2 rs885863 and low HDL cholesterol level. In addition, Per2 SNP rs934945 was associated with the metabolic syndrome.

There are some limitations in our study. We relied on a self-report questionnaire when assessing the seasonal variations in mood and behavior. However, this questionnaire has been reported to have high sensitivity and specificity [37] and can be regarded as valid for the lifetime-retrospective assessment of routine seasonal variations in mood and behavior.

Our study bears several strengths. This was a population-based and nation-wide study. Its sample size was relatively big and representative of the general population aged over 30 living in a northern European country, Finland. Hence, these data can be generalized directly to concern the whole adult population of Finland, or any population having similar living conditions. We had rich phenotype data with reliable laboratory tests and valid assessments of syndromes on our focus. The single-nucleotide polymorphisms used were selected for their potential role in the function of the gene, which augments the possibility that the genotype seen here contributes to the phenotype although experimental analysis is needed for verification.

Our findings herein link the circadian gene variants and risk factors of the metabolic syndrome. Npas2 was associated with hypertension and Per2 with blood glucose levels. Our findings give support to the view that there are relevant relationships between circadian clocks and metabolic syndrome.

JH has served as consultant to Janssen-Cilag, other authors have no conflicts of interests.

AE drafted the manuscript. LK carried out the genotyping and helped to draft the manuscript. AE, LK, JH and TP participated in the design of the study and performed the statistical analysis. TP, STS, JL, AR and AA conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.