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Brazilian Journal of Medical and Biological Research

Print version ISSN 0100-879XOn-line version ISSN 1414-431X

Braz J Med Biol Res vol.41 no.8 Ribeirão Preto Aug. 2008 

Braz J Med Biol Res, August 2008, Volume 41(8) 716-721 (Review)

The search for circadian clock components in humans: new perspectives for association studies

K.V. Allebrandt and T. Roenneberg

Centre for Chronobiology, Institute for Medical Psychology, University of Munich, Munich, Germany

Correspondence and Footnotes


Individual circadian clocks entrain differently to environmental cycles (zeitgebers, e.g., light and darkness), earlier or later within the day, leading to different chronotypes. In human populations, the distribution of chronotypes forms a bell-shaped curve, with the extreme early and late types _ larks and owls, respectively _ at its ends. Human chronotype, which can be assessed by the timing of an individual's sleep-wake cycle, is partly influenced by genetic factors - known from animal experimentation. Here, we review population genetic studies which have used a questionnaire probing individual daily timing preference for associations with polymorphisms in clock genes. We discuss their inherent limitations and suggest an alternative approach combining a short questionnaire (Munich ChronoType Questionnaire, MCTQ), which assesses chronotype in a quantitative manner, with a genome-wide analysis (GWA). The advantages of these methods in comparison to assessing time-of-day preferences and single nucleotide polymorphism genotyping are discussed. In the future, global studies of chronotype using the MCTQ and GWA may also contribute to understanding the influence of seasons, latitude (e.g., different photoperiods), and climate on allele frequencies and chronotype distribution in different populations.

Key words: Human clock genes; Chronotype; Morningness/eveningness; Association studies; Latitudinal hypothesis



When circadian rhythms are investigated under constant conditions, their endogenous periods often deviate from 24 h. Under natural conditions, circadian clocks are normally entrained by environmental signals (zeitgebers), predominantly by light. The underlying molecular mechanism generating the internal day is thought to be based upon a transcriptional regulatory loop of so-called clock genes and their products (1).

Circadian rhythms have been demonstrated in all phyla, from cyanobacteria to mammals (2) and species-specific dedicated clock genes have been identified in most model systems by reverse genetics (3-10). In humans, the assumptions about the mechanisms of the molecular clock remain hypothetical, as identification of human clock genes are predominantly based on their sequence similarity with those in other animals. Although many of the mammalian clock genes have been shown to oscillate in cultured human fibroblasts (11), experiments do not prove that these genes and their products are involved in the molecular rhythm generation in humans.

To characterize the relevance of mammalian clock genes in humans, association studies of a circadian phenotype with naturally occurring genetic variation have been conducted. So far, these efforts are based primarily on a phenotyping instrument that queries time-of-day preferences, resulting in a score (Horne-Østberg Morningness-Eveningness Questionnaire - MEQ) (12), rather than in actual timing (phase of entrainment, chronotype). Genetic variability in humans indeed reflects individual time-of-day preferences; a list of positive associations described over the last decade for 6 clock genes is given in Table 1.

Here, we review these studies and discuss inherent problems possibly responsible for inconsistencies of some results. We suggest alternative strategies based on new phenotyping and high-throughput genotyping methodologies. In addition, we propose studies investigating latitudinal clines in genetic variations related to circadian clock adaptation.

Family-based and association studies

The inter-individual differences of human time-of-day preferences (MEQ) or chronotype (Munich ChronoType Questionnaire, MCTQ) can be manifest in extreme cases as a rare familial syndrome. Thus, extreme morningness can result in the familial advanced sleep phase syndrome (ASPS) and extreme eveningness in the delayed sleep phase syndrome (DSPS). The association of several clock gene variants with morningness-eveningness scores but also with its extreme forms, ASPS or DSPS, have been investigated in various studies, however, with partly conflicting results. The monogenic autosomal dominant familial ASPS (13) has, for example, been associated with a mutation in the genes period 2 (Per2; Table 1). However, results are inconsistent across different pedigrees. Satoh et al. (14) characterized pedigrees with familial ASPS that were not carriers of the earlier described Per2 mutation, whereas a mutation at the casein kinase one delta (CKIδ) gene was later found to be leading to the same phenotype (Table 1).

Besides finding ASPS to be associated in isolated families with (rare) single nucleotide mutations, the same phenotype has also been associated in the general population with a length polymorphism in the period 3 (Per3) gene, in form of variable number of tandem repeats (VNTR; Table 1) (15,16). A long VNTR form (5-repeats) was associated with morningness, whereas a short form (4-repeats) was associated with eveningness. A replication of these findings in a Brazilian population found the long VNTR allele associated with eveningness rather than with morningness (17) (Table 1). The authors speculated that the discrepant findings could be due to the influence of different latitudes, as has been previously shown for clock genes in flies (18). However, the hypothesis of a latitudinal cline in distinct allele frequencies of this Per3 polymorphism could not be sustained (19). Another apparent conflict (not taking possible ethnic influences into account) was found for a rare haplotype of Per3 (G647, P864, 4-repeat, T1037, R1158). Whereas it associates with DSPS in Japanese patients (16) (Table 1), one of its alleles (G647) associates with morningness in Europeans (20).

Again, unequivocal associations have been found for a single nucleotide polymorphism (SNP) of the CLOCK gene 5'-UTR region (T3111C). It was found to associate with eveningness both in Europeans (21) (Table 1) and Japanese (22) (Table 1), but this association was not reproducible in other studies (23-25). Two gene variants, one of them actually responsible for the phenotype and the other being the one that is investigated, can often co-segregate (when they are in linkage disequilibrium, LD). LD between the investigated and the actual phenotype-causing variant could be one of the reasons for such a spurious association since LD levels vary among alleles in different populations. Thus, an association found in one population may not be reproducible in another. To investigate this hypothesis for the case of the T3111C polymorphism, Pedrazzoli et al. (25) investigated an exonic CLOCK variant (T257G), which showed almost complete LD with the T3111C SNP but found no association of either variant with time-of-day preferences or DSPS in the Brazilian population, indicating that neither was responsible for the phenotype.

The discrepant results of studies associating time-of-day preferences or sleep phase syndromes with clock gene mutations, SNPs, or VNTRs could have at least three reasons: i) population-specific LD levels between the investigated and the causal variant, as well as, population stratification. The first assumption will not hold for every investigated population because allele frequencies vary among different populations influencing the LD levels between loci. Therefore, it is essential to be aware of the ethnic composition of the populations for which findings are reported (Table 1). However, this information is not always clearly specified by authors. Admixture (miscegenation between populations) can dynamically generate LD among loci, because allele frequencies of ancestor populations will take several generations of recombination to achieve equilibrium. As a consequence, the confounding effect of stratification may take a long time to disappear. The results of association studies may be biased by heterogeneities; these can be generated either by mixing samples from different origins, or by samples from the same origin, but taken from an admixed population. ii) Insufficiently accurate phenotyping. Here, we discuss alternative strategies to reduce the ambiguity in phene-gene associations concerning the circadian clock in humans. iii) Gene-gene and gene-environment interactions. Chronotype is a multi-factorial trait; thus, simple straightforward associations between variants in a single gene cannot necessarily be used to predict the phenotype.

Population specificity and population stratification

Allele frequencies and LD levels between gene variants can vary drastically among subjects of distinct ancestry (26), so that association with a certain variant in LD with the causal variant for one population may not be found in other populations or may be undetectable or ambiguous in ethnically heterogeneous populations. To attenuate replication failures due to population-specific allele frequencies and LD levels, many more SNPs can be assessed with new high-throughput genotyping methodologies. The HapMap (dense maps of LD for a large number of SNPs; allows the selection of SNPs that tag haplotype blocks from populations either of African, Asian or European ancestry. This approach allows covering large regions of the genome with a relatively low number of SNPs, which are used as markers for other co-segregating variants. Designing association studies based on the HapMap drastically increases the chances of "tagging" the causal variant with an LD-based strategy, thus, preventing inconsistencies that may result in single SNP association studies. However, admixture can still affect the reliability of the LD mapping strategy. Population stratification can bias associations in studies based on a single SNP or on thousands of SNPs, consequently resulting in possible replication failures. Decreasing heterogeneity of the sample can minimize stratification problems. For this purpose, molecular markers for ethnicity can be used, a way of controlling, or rather correcting for admixture. This procedure is a routine strategy in genome-wide association studies; panels of ethnic markers are already published, revealing clear ethnic distinctions in particular allele frequencies even within European populations (27).

Improving phenotyping

Beyond the methodological improvements described above, the best prerequisite for unequivocal results in phene-gene association studies is optimal phenotyping. The MEQ, used in most circadian association studies so far, is an excellent psychological instrument that has been used extensively in research beyond trying to find human clock genes (28-32). However, the questions of the MEQ are mostly subjective, assessing time-of-day preferences based on a personal "feeling best rhythm" or on hypothetical situations (e.g., "approximately what time would you get up if you were entirely free to plan your day?") (33), or in relationship to the habits of others (e.g., "I get up later than most people.") (34). The MEQ yields plausible results, but does not explicitly assess actual times (e.g., of sleep or activity) nor does it distinguish between free and work days. In addition, age- and sex-specific changes in time-of-day preferences are not sufficiently quantified and are, thus, not easily incorporated into the phenotyping procedure, which would be essential for accurate phenotyping.

We have developed the MCTQ, which allows a quantitative assessment of entrained phase (chronotype) by taking all the considerations mentioned above into account (35-39). The MCTQ shows good correlation with the MEQ score (40). However, the best correlation exists between the MEQ score and a single question of the original version of the MCTQ (r = -0.80), essentially asking ("what chronotype are you _ extreme, moderate, slightly early or late?") (39). Sleep-timing on free days, which is the initial basis for chronotyping in the MCTQ, correlates less with the MEQ score (r = -0.74) and correlation decreases with every correction procedure, necessary for determining a quantitative value for an individual chronotype (see below).

The initial MCTQ determination of chronotype is based on the mid-sleep time on free days (MSF). Since many subjects accumulate a considerable amount of sleep-debt on workdays, which they compensate for on free days, MSF has to be corrected (MSFsc; correlation with the MEQ score: r = -0.66). Moreover, chronotype depends on sex and age (39). The large number of entries in our database (currently 65,000) allows us the determination of extremely accurate correction factors for the dependencies of MSFsc on age and sex (MSFsasc; correlation with the MEQ score: r = -0.59). These adjustments are a crucial prerequisite for epidemiological and genetic association studies profiting from a more accurate measure of chronotype (39).

Circadian gene networks

The current model of the clock has outgrown the single feedback-loop hypothesis presuming a network of molecular oscillator (41). In addition, chronotype will be influenced by more than just the molecular oscillator components. Phase of entrainment of the oscillator depends on input signals and when phase of entrainment is determined by an output variable of the circadian clock (e.g., timing of sleep or the melatonin profile), it additionally depends on how the output is coupled to the oscillator. Thus, chronotype is definitely a polygenic trait involving genes concerning input(s), oscillator(s) and output(s). In gene networks, the specific effect of a SNP can only be unambiguous when it is compared in an otherwise homogeneous genome. If, however, individuals differ in more than one single nucleotide or other polymorphisms, interpretations become difficult. The theory of entrainment (42) predicts, for example, that if one polymorphism results in a shorter free-running period (still being longer than 24 h) and another in reducing the sensitivity to the zeitgeber, chronotype may not change, although it would with either polymorphism alone (albeit in opposed directions). A polymorphism resulting in an increased zeitgeber transduction would result in a later chronotype, if the free-running period of the individual is shorter than 24 h and in an earlier chronotype if the period is longer. These are only two examples of many others highlighting the complications that arise when investigating a single polymorphism association with a complex phenotype. These complications can theoretically be dealt with in genome-wide association studies when using computations that involve the interactions of more than one polymorphism in determining chronotype.

Gene-environment interactions: expanding research on human clock genetics beyond finding clock genes

Once we can optimize the designs and methods of association studies, we can start to ask more complex biological questions, such as genetic adaptation to different latitudes and climates, relationships between light exposure, state of industrialization and genetic chronotype, or even whether food influences genetic chronotype dispositions.

Among these, the latitudinal question is probably the most amenable. Light plays a crucial role within the complexity of the circadian clock. Day length (photoperiod) depends on time of year and the amplitude of its seasonal changes on latitude. These geographical specificities of light could be relevant in adaptation processes strengthening or weakening the impact of components within the circadian network that should be detectable in the allele frequencies of populations living at different latitudes. We have recently shown that the human clock entrains to sun times (predominantly to dawn) even for different longitudes within a single time zone (36). Latitudinal clines related to human reproduction (43,44), human mortality (45) or genetic geographic variations between photoperiodic diapauses and the circadian eclosion rhythm in Drosophila (46-49) have been observed. In addition, synchronization of circadian clocks to natural light-dark cycles is challenged at very high latitudes due to the extreme photoperiods (50). Therefore, a relationship between an adaptive circadian system and fitness is likely. Comparing the genomes between indigenous and more recently immigrated populations might reveal clock genes that are important for adaptation to photoperiod.


Genome-wide studies of the genetic variability underlying chronotype and the circadian system in general will not only help us to identify those genes that are relevant for circadian regulation in humans (we may even find new genes which then can be looked for in other animals) but also how the circadian system has evolved. Understanding the mechanisms underlying chronotype will open new possibilities for identifying extreme chronotypes and how to help them to adjust better to social time. It will also open avenues to improve individual treatment in many diseases which are not caused by defects in the circadian system but the symptoms of which are strongly modulated by the clock and will pave the way to optimizing chrono-pharmacological interventions. The characterization of new genes and polymorphisms influencing chronotype will also strengthen in vitro functional studies investigating the molecular mechanisms controlling the period of free running rhythms in humans. Finally, the insights into the genetics behind chronotype may increase the appreciation of this phenomenon and may consequently lead to political changes facilitating more appropriate, flexible, or individualized social schedules (e.g., in school and work).

Table 1. Reports on variants of human clock genes associated with individual time-of-day preference (listed in chronological order).

[View larger version of this table (119 K JPG file)]


1. Young MW, Kay SA. Time zones: a comparative genetics of circadian clocks. Nat Rev Genet 2001; 2: 702-715.         [ Links ]

2. Roenneberg T, Merrow M. Circadian clocks - the fall and rise of physiology. Nat Rev Mol Cell Biol 2005; 6: 965-971.         [ Links ]

3. Vitaterna MH, King DP, Chang AM, Kornhauser JM, Lowrey PL, McDonald JD, et al. Mutagenesis and mapping of a mouse gene, Clock, essential for circadian behavior. Science 1994; 264: 719-725.         [ Links ]

4. Crosthwaite SK, Loros JJ, Dunlap JC. Light-induced resetting of a circadian clock is mediated by a rapid increase in frequency transcript. Cell 1995; 81: 1003-1012.         [ Links ]

5. Hunter-Ensor M, Ousley A, Sehgal A. Regulation of the Drosophila protein timeless suggests a mechanism for resetting the circadian clock by light. Cell 1996; 84: 677-685.         [ Links ]

6. Shen H, Watanabe M, Tomasiewicz H, Rutishauser U, Magnuson T, Glass JD. Role of neural cell adhesion molecule and polysialic acid in mouse circadian clock function. J Neurosci 1997; 17: 5221-5229.         [ Links ]

7. Bunger MK, Wilsbacher LD, Moran SM, Clendenin C, Radcliffe LA, Hogenesch JB, et al. Mop3 is an essential component of the master circadian pacemaker in mammals. Cell 2000; 103: 1009-1017.         [ Links ]

8. Bae K, Jin X, Maywood ES, Hastings MH, Reppert SM, Weaver DR. Differential functions of mPer1, mPer2, and mPer3 in the SCN circadian clock. Neuron 2001; 30: 525-536.         [ Links ]

9. Dudley CA, Erbel-Sieler C, Estill SJ, Reick M, Franken P, Pitts S, et al. Altered patterns of sleep and behavioral adaptability in NPAS2-deficient mice. Science 2003; 301: 379-383.         [ Links ]

10. Siepka SM, Yoo SH, Park J, Song W, Kumar V, Hu Y, et al. Circadian mutant Overtime reveals F-box protein FBXL3 regulation of cryptochrome and period gene expression. Cell 2007; 129: 1011-1023.         [ Links ]

11. Brown SA, Fleury-Olela F, Nagoshi E, Hauser C, Juge C, Meier CA, et al. The period length of fibroblast circadian gene expression varies widely among human individuals. PLoS Biol 2005; 3: e338.         [ Links ]

12. Horne JA, Ostberg O. A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int J Chronobiol 1976; 4: 97-110.         [ Links ]

13. Jones CR, Campbell SS, Zone SE, Cooper F, DeSano A, Murphy PJ, et al. Familial advanced sleep-phase syndrome: A short-period circadian rhythm variant in humans. Nat Med 1999; 5: 1062-1065.         [ Links ]

14. Satoh K, Mishima K, Inoue Y, Ebisawa T, Shimizu T. Two pedigrees of familial advanced sleep phase syndrome in Japan. Sleep 2003; 26: 416-417.         [ Links ]

15. Archer SN, Robilliard DL, Skene DJ, Smits M, Williams A, Arendt J, et al. A length polymorphism in the circadian clock gene Per3 is linked to delayed sleep phase syndrome and extreme diurnal preference. Sleep 2003; 26: 413-415.         [ Links ]

16. Ebisawa T, Uchiyama M, Kajimura N, Mishima K, Kamei Y, Katoh M, et al. Association of structural polymorphisms in the human period3 gene with delayed sleep phase syndrome. EMBO Rep 2001; 2: 342-346.         [ Links ]

17. Pereira DS, Tufik S, Louzada FM, Benedito-Silva AA, Lopez AR, Lemos NA, et al. Association of the length polymorphism in the human Per3 gene with the delayed sleep-phase syndrome: does latitude have an influence upon it? Sleep 2005; 28: 29-32.         [ Links ]

18. Sawyer LA, Hennessy JM, Peixoto AA, Rosato E, Parkinson H, Costa R, et al. Natural variation in a Drosophila clock gene and temperature compensation. Science 1997; 278: 2117-2120.         [ Links ]

19. Nadkarni NA, Weale ME, von Schantz M, Thomas MG. Evolution of a length polymorphism in the human PER3 gene, a component of the circadian system. J Biol Rhythms 2005; 20: 490-499.         [ Links ]

20. Johansson C, Willeit M, Smedh C, Ekholm J, Paunio T, Kieseppa T, et al. Circadian clock-related polymorphisms in seasonal affective disorder and their relevance to diurnal preference. Neuropsychopharmacology 2003; 28: 734-739.         [ Links ]

21. Katzenberg D, Young T, Finn L, Lin L, King DP, Takahashi JS, et al. A CLOCK polymorphism associated with human diurnal preference. Sleep 1998; 21: 569-576.         [ Links ]

22. Mishima K, Tozawa T, Satoh K, Saitoh H, Mishima Y. The 3111T/C polymorphism of hClock is associated with evening preference and delayed sleep timing in a Japanese population sample. Am J Med Genet B Neuropsychiatr Genet 2005; 133B: 101-104.         [ Links ]

23. Robilliard DL, Archer SN, Arendt J, Lockley SW, Hack LM, English J, et al. The 3111 Clock gene polymorphism is not associated with sleep and circadian rhythmicity in phenotypically characterized human subjects. J Sleep Res 2002; 11: 305-312.         [ Links ]

24. Iwase T, Kajimura N, Uchiyama M, Ebisawa T, Yoshimura K, Kamei Y, et al. Mutation screening of the human Clock gene in circadian rhythm sleep disorders. Psychiatry Res 2002; 109: 121-128.         [ Links ]

25. Pedrazzoli M, Louzada FM, Pereira DS, Benedito-Silva AA, Lopez AR, Martynhak BJ, et al. Clock polymorphisms and circadian rhythms phenotypes in a sample of the Brazilian population. Chronobiol Int 2007; 24: 1-8.         [ Links ]

26. Allebrandt KV, Souza RL, Chautard-Freire-Maia EA. Variability of the paraoxonase gene (PON1) in Euro- and Afro-Brazilians. Toxicol Appl Pharmacol 2002; 180: 151-156.         [ Links ]

27. Seldin MF, Shigeta R, Villoslada P, Selmi C, Tuomilehto J, Silva G, et al. European population substructure: clustering of northern and southern populations. PLoS Genet 2006; 2: e143.         [ Links ]

28. Paine SJ, Gander PH, Travier N. The epidemiology of morningness/eveningness: influence of age, gender, ethnicity, and socioeconomic factors in adults (30-49 years). J Biol Rhythms 2006; 21: 68-76.         [ Links ]

29. Russo PM, Bruni O, Lucidi F, Ferri R, Violani C. Sleep habits and circadian preference in Italian children and adolescents. J Sleep Res 2007; 16: 163-169.         [ Links ]

30. Hidalgo MP, Caumo W. Sleep disturbances associated with minor psychiatric disorders in medical students. Neurol Sci 2002; 23: 35-39.         [ Links ]

31. Hidalgo MP, de Souza CM, Zanette CB, Nunes PV. Association of daytime sleepiness and the morningness/eveningness dimension in young adult subjects in Brazil. Psychol Rep 2003; 93: 427-434.         [ Links ]

32. Kerkhof GA, Korving HJ, Willemse-vd Geest HM, Rietveld WJ. Diurnal differences between morning-type and evening-type subjects in self-rated alertness, body temperature and the visual and auditory evoked potential. Neurosci Lett 1980; 16: 11-15.         [ Links ]

33. Terman M, White TM. Mornigness-eveningness questionnaire - Self-assessment version (AutoMEQ-SA). http://www.         [ Links ]

34. Smith CS, Folkard S, Scmieder RA, Parra Luis F, Spelten Evelien, Almiral Helena, et al. Investigation of morning-evening orientation in six countries using the preference scale. Pers Individ Dif 2002; 32: 949-968.         [ Links ]

35. Roenneberg T, Wirz-Justice A, Merrow M. Life between clocks: daily temporal patterns of human chronotypes. J Biol Rhythms 2003; 18: 80-90.         [ Links ]

36. Roenneberg T, Kumar CJ, Merrow M. The human circadian clock entrains to sun time. Curr Biol 2007; 17: R44-R45.         [ Links ]

37. Wittmann M, Dinich J, Merrow M, Roenneberg T. Social jetlag: misalignment of biological and social time. Chronobiol Int 2006; 23: 497-509.         [ Links ]

38. Roenneberg T, Kuehnle T, Pramstaller PP, Ricken J, Havel M, Guth A, et al. A marker for the end of adolescence. Curr Biol 2004; 14: R1038-R1039.         [ Links ]

39. Roenneberg T, Kuehnle T, Juda M, Kantermann T, Allebrandt K, Gordijn M, et al. Epidemiology of the human circadian clock. Sleep Med Rev 2007; 11: 429-438.         [ Links ]

40. Zavada A, Gordijn MC, Beersma DG, Daan S, Roenneberg T. Comparison of the Munich Chronotype Questionnaire with the Horne-Ostberg's Morningness-Eveningness Score. Chronobiol Int 2005; 22: 267-278.         [ Links ]

41. Roenneberg T, Merrow M. The network of time: understanding the molecular circadian system. Curr Biol 2003; 13: R198-R207.         [ Links ]

42. Roenneberg T, Daan S, Merrow M. The art of entrainment. J Biol Rhythms 2003; 18: 183-194.         [ Links ]

43. Roenneberg T, Aschoff J. Annual rhythm of human reproduction: I. Biology, sociology, or both? J Biol Rhythms 1990; 5: 195-216.         [ Links ]

44. Roenneberg T, Aschoff J. Annual rhythm of human reproduction: II. Environmental correlations. J Biol Rhythms 1990; 5: 217-239.         [ Links ]

45. Aschoff J. Annual rhythms in man. In: Aschoff J (Editor), Handbook of behavioral neurobiology. New York: Plenum; 1981. p 475-487.         [ Links ]

46. Lankinen P, Forsman P. Independence of genetic geographical variation between photoperiodic diapause, circadian eclosion rhythm, and Thr-Gly repeat region of the period gene in Drosophila littoralis. J Biol Rhythms 2006; 21: 3-12.         [ Links ]

47. Tauber E, Zordan M, Sandrelli F, Pegoraro M, Osterwalder N, Breda C, et al. Natural selection favors a newly derived timeless allele in Drosophila melanogaster. Science 2007; 316: 1895-1898.         [ Links ]

48. Costa R, Peixoto AA, Barbujani G, Kyriacou CP. A latitudinal cline in a Drosophila clock gene. Proc Biol Sci 1992; 250: 43-49.         [ Links ]

49. Kyriacou CP, Hall JC. Circadian rhythm mutations in Drosophila melanogaster affect short-term fluctuations in the male's courtship song. Proc Natl Acad Sci U S A 1980; 77: 6729-6733.         [ Links ]

50. van Oort BE, Tyler NJ, Gerkema MP, Folkow L, Blix AS, Stokkan KA. Circadian organization in reindeer. Nature 2005; 438: 1095-1096.         [ Links ]

51. Toh KL, Jones CR, He Y, Eide EJ, Hinz WA, Virshup DM, et al. An hPer2 phosphorylation site mutation in familial advanced sleep phase syndrome. Science 2001; 291: 1040-1043.         [ Links ]

52. Takano A, Uchiyama M, Kajimura N, Mishima K, Inoue Y, Kamei Y, et al. A missense variation in human casein kinase I epsilon gene that induces functional alteration and shows an inverse association with circadian rhythm sleep disorders. Neuropsychopharmacology 2004; 29: 1901-1909.         [ Links ]

53. Carpen JD, Archer SN, Skene DJ, Smits M, von Schantz M. A single-nucleotide polymorphism in the 5'-untranslated region of the hPER2 gene is associated with diurnal preference. J Sleep Res 2005; 14: 293-297.         [ Links ]

54. Xu Y, Padiath QS, Shapiro RE, Jones CR, Wu SC, Saigoh N, et al. Functional consequences of a CKIdelta mutation causing familial advanced sleep phase syndrome. Nature 2005; 434: 640-644.         [ Links ]

55. Carpen JD, von Schantz M, Smits M, Skene DJ, Archer SN. A silent polymorphism in the PER1 gene associates with extreme diurnal preference in humans. J Hum Genet 2006; 51: 1122-1125.         [ Links ]


We thank Prof. Martha Merrow for scientific discussion.

Correspondence and Footnotes

Address for correspondence: K.V. Allebrandt, Centre for Chronobiology, Institute for Medical Psychology, University of Munich, Goethestrasse 31, 80336 Munich, Germany. Fax: +49-89-2180-75615. E-mail:

Presented at the XI Congresso Brasileiro do Sono. Fortaleza, CE, Brazil, November 11-14, 2007. Research supported by the EUCLOCK consortium. Received November 6, 2007. Accepted July 17, 2008.

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