Temporal dynamics in laboratory medicine: cosinor analysis and real-world data (RWD) approaches to population chronobiology
Abstract
Objectives
Chronobiology is the science that studies biological rhythms based on direct methods and empirical time series of individual subjects. In laboratory medicine, the factor of time is often underestimated, and no methods currently exist to study biological rhythms in population databases of point-like, real-world data (RWD).
Methods
Retrospective databases (24 months, 2022–2023) were extracted for four measurands (sodium, potassium, chloride and leukocytes) from the emergency laboratory. Two different strategies for data grouping were applied: data clouds (with or without outliers) and population-averaged profiles. Cosinor regression analysis was performed on the grouped data to derive circadian parameters. The parameters obtained here were compared to results from the literature, using direct methods and time series.
Results
A total of 409,719 data points were analyzed. All measurands exhibited symmetrical data distributions, except for leukocytes. The data clouds did not visually display rhythmicity, but cosinor analysis revealed a significant circadian rhythm. The removal of outliers had minimal impact on the results. In contrast, population-averaged profiles showed visible rhythmicity, which was confirmed by cosinor analysis with a better goodness-of-fit compared to the data clouds.
Conclusions
Population-averaged profiles have advantages over data clouds in characterizing circadian rhythms and deriving circadian parameters. Population chronobiology, based on RWD, is presented as an alternative to classical individual chronobiology, based on time series and overcomes the limitations of direct methods. Utilizing RWD provides new insights into the relationship between chronobiology and clinical laboratory practice.
Funding source: DGAPA-UNAM
Award Identifier / Grant number: PAPIIT IN115124
-
Research ethics: Protocol approved PI-21-034.
-
Informed consent: Not applicable.
-
Author contributions: FMG: Conceived and designed the analysis; Contributed data or analysis tools; Performed the analysis; Wrote the paper. CMB: Conceived and designed the analysis; Contributed data or analysis tools; Performed the analysis; Wrote the paper. XTG: Contributed data or analysis tools; Wrote the paper. RF: Conceived and designed the analysis; Contributed data or analysis tools; Performed the analysis; Wrote the paper. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Use of Large Language Models, AI and Machine Learning Tools: None declared.
-
Conflict of interest: The authors state no conflict of interest.
-
Research funding: Financial funding for this work was supplied by the Dirección General de Asuntos del Personal Académico (DGAPA) from the Universidad Nacional Autónoma de México (UNAM) with grant PAPIIT IN115124.
-
Data availability: Not applicable.
References
1. El, HMA, Delvin, E, Elnenaei, MO, Hoffman, B. Diurnal rhythm in clinical chemistry: an underrated source of variation. Crit Rev Clin Lab Sci 2018;55:1–19.10.1080/10408363.2018.1519522Search in Google Scholar
2. Coskun, A, Zarepour, A, Zarrabi, A. Physiological rhythms and biological variation of biomolecules: the road to personalized laboratory medicine. Int J Mol Sci 2023;24:6275. https://doi.org/10.3390/ijms24076275.Search in Google Scholar PubMed PubMed Central
3. Fossion, R, Rivera, AL, Estañol, B. A physicist’s view of homeostasis: how time series of continuous monitoring reflect the function of physiological variables in regulatory mechanisms. Physiol Meas 2018;39:084007. https://doi.org/10.1088/1361-6579/aad8db.Search in Google Scholar PubMed
4. Fossion, R, Fossion, JPJ, Rivera, AL, Lecona, OA, Toledo-Roy, JC, García-Pelagio, KP, et al.. Homeostasis from a time-series perspective: an intuitive interpretation of the variability of physiological variables. In: Quiroz, O, Resendis, AO, editors. Quantitative models for microscopic to macroscopic biological macromolecules and tissues. Springer International Publishing; 2018:87 p.10.1007/978-3-319-73975-5_5Search in Google Scholar
5. Pittendrigh, CS. Circadian rhythms and the circadian organization of livings systems. Cold Spring Harbor Symp Quant Biol 1960;25:159–84. https://doi.org/10.1101/sqb.1960.025.01.015.Search in Google Scholar PubMed
6. Miller, BH, McDearmon, EL, Panda, S, Hayes, KR, Zhang, J, Andrews, JL, et al.. Circadian and CLOCK-controlled regulation of the mouse transcriptome and cell proliferation. Proc Natl Acad Sci U S A 2007;104:3342–7. https://doi.org/10.1073/pnas.0611724104.Search in Google Scholar PubMed PubMed Central
7. De la Iglesia, HO, Schwartz, WJ. Minireview: timely ovulation: circadian regulation of the female hypothalamo-pituitary-gonadal axis. Endocrinology 2006;147:1148–53. https://doi.org/10.1210/en.2005-1311.Search in Google Scholar PubMed
8. Allada, R, Bass, J. Circadian mechanisms in medicine. N Engl J Med 2021;384:550–61. https://doi.org/10.1056/nejmra1802337.Search in Google Scholar PubMed PubMed Central
9. Beale, AD, Hayter, EA, Crosby, P, Valekunja, UK, Edgar, RS, Chesham, JE, et al.. Mechanisms and physiological function of daily haemoglobin oxidation rhythms in red blood cells. EMBO J 2023;42:e114164. https://doi.org/10.15252/embj.2023114164.Search in Google Scholar PubMed PubMed Central
10. Hardeland, R, Madrid, JA, Dun-Xian, T, Reiter, R. Melatonin, the circadian multioscillator system and health: the need for detailed analyses of peripheral melatonin signaling. J Pineal Res 2012;52:139–66. https://doi.org/10.1111/j.1600-079X.2011.00934.x.Search in Google Scholar PubMed
11. Baum, L, Johns, M, Poikela, M, Möller, R, Ananthasubramaniam, B, Prasser, F. Data integration and analysis for circadian medicine. Acta Physiol 2023;237:e13951. https://doi.org/10.1111/apha.13951.Search in Google Scholar PubMed
12. Golombek, DA, Rosenstein, RE. Physiology of circadian entrainment. Physiol Rev 2010;90:1063–102. https://doi.org/10.1152/physrev.00009.2009.Search in Google Scholar PubMed
13. Patke, A, Young, MW, Axelrod, S. Molecular mechanisms and physiological importance of circadian rhythms. Nat Rev Mol Cell Biol 2020;21:67–84. https://doi.org/10.1038/s41580-019-0179-2.Search in Google Scholar PubMed
14. Martínez-Nicolás, A, Ortiz-Tudela, E, Madrid, JA, Rol, MA. Crosstalk between environmental light and internal time in humans. Chronobiol Int 2011;28:617–29. https://doi.org/10.3109/07420528.2011.593278.Search in Google Scholar PubMed
15. Yildirim, E, Curtis, R, Hwangbo, DS. Roles of peripheral clocks: lessons from the fly. FEBS Lett 2022;596:263–93. https://doi.org/10.1002/1873-3468.14251.Search in Google Scholar PubMed PubMed Central
16. Wey, D, Bohn, A, Menna-Barreto, L. Daily rhythms of native Brazilians in summer and winter. Physiol Behav 2012;105:613–20. https://doi.org/10.1016/j.physbeh.2011.10.006.Search in Google Scholar PubMed
17. Morelli, D, Bartoloni, L, Rossi, A, Clifton, DA. A computationally efficient algorithm to obtain an accurate and interpretable model of the effect of circadian rhythm on resting heart rate. Physiol Meas 2019;40:095001. https://doi.org/10.1088/1361-6579/ab3dea.Search in Google Scholar PubMed
18. Fossion, R, Rivera, AL, Toledo-Roy, JC, Ellis, J, Angelova, M. Multiscale adaptive analysis of circadian rhythms and intradaily variability: application to actigraphy time series in acute insomnia subjects. PLoS One 2017;12:e0181762. https://doi.org/10.1371/journal.pone.0181762.Search in Google Scholar PubMed PubMed Central
19. García-Iglesias, L, Rivera, AL, Fossion, R. Circadian cycles: a time-series approach. Rev Mex Fís 2023;69:051101. https://doi.org/10.31349/RevMexFis.69.051101.Search in Google Scholar
20. Sennels, HP, Jørgensen, HL, Hansen, AL, Goetze, JP, Fahrenkrug, J. Diurnal variation of hematology parameters in healthy young males: the Bispebjerg study of diurnal variations. Scand J Clin Lab Invest 2011;71:532–41. https://doi.org/10.3109/00365513.2011.602422.Search in Google Scholar PubMed
21. Sennels, HP, Jørgensen, HL, Goetze, JP, Fahrenkrug, J. Rhythmic 24-hour variations of frequently used clinical biochemical parameters in healthy young males- the Bispebjerg study of diurnal variations. Scand J Clin Lab Invest 2012;72:287–95. https://doi.org/10.3109/00365513.2012.662281.Search in Google Scholar PubMed
22. Golombek, D. La máquina del tiempo. In: Golombek D, compilador. Cronobiología Humana: Ritmos y relojes biológicos en la salud y en la enfermedad. Quilmes, Argentina: Universidad Nacional de Quilmes; 2007;21–31 pp.Search in Google Scholar
23. Martinez-Sanchez, L, Marques-Garcia, F, Ozarda, Y, Blanco, A, Brouwer, N, Canalias, F, et al.. Big data and reference intervals: rationale, current practices, harmonization and standardization prerequisites and future perspectives of indirect determination of reference intervals using routine data. Adv Lab Med 2021;2:9–16. https://doi.org/10.1515/almed-2020-0034.Search in Google Scholar PubMed PubMed Central
24. Marqués-García, F, Nieto-Librero, A, González-García, N, Galindo-Villardón, P, Martínez-Sánchez, LM, Tejedor-Ganduxé, X, et al.. Within-subject biological variation estimates using an indirect data mining strategy. Spanish multicenter pilot study (BiVaBiDa). Clin Chem Lab Med 2022;60:1804–12. https://doi.org/10.1515/cclm-2021-0863.Search in Google Scholar PubMed
25. Lorenzo-Lozano, MC, Blázquez-Manzanera, AL, Carnicero, JA. How kidney clock works: circadian pattern of eGFR based on a population data group. J Physiol Biochem 2023;79:543–54. https://doi.org/10.1007/s13105-023-00948-2.Search in Google Scholar PubMed
26. Ma, C, Wang, J, Wu, J, Cheng, X, Xia, L, Xue, F, et al.. Real-world big-data studies in laboratory medicine: current status, application, and future considerations. Clin Biochem 2020;84:21–30. https://doi.org/10.1016/j.clinbiochem.2020.06.014.Search in Google Scholar PubMed
27. Miller, WG, Jones, GRD, Horowitz, GL, Weykamp, C. Proficiency testing/external quality assessment: current challenges and future directions. Clin Chem 2011;57:1670–80. https://doi.org/10.1373/clinchem.2011.168641.Search in Google Scholar PubMed
28. Barnett, V, Lewis, T. Outliers in statistical data. Chichester (UK): Wiley; 1978.Search in Google Scholar
29. Lund, F, Petersen, PH, Fraser, CG, Sölétormos, G. Calculation of limits for significant bidirectional changes in two or more serial results of a biomarker based on a computer simulation model. Ann Clin Biochem 2015;52:434–40. https://doi.org/10.1177/0004563214555163.Search in Google Scholar PubMed
30. Aarsand, AK, Fernandez-Calle, P, Webster, C, Coskun, A, Gonzales-Lao, E, Diaz-Garzon, J, et al.. The EFLM biological variation database. https://biologicalvariation.eu/ [Accessed September 2024].Search in Google Scholar
31. Halberg, F, Tong, YL, Johnson, EA. Circadian system phase-an aspect of temporal morphology; procedures and illustrative examples. In: Mayersbach, H, editor. The cellular aspects of biorhythms, 1st ed. Berlin (GER): Springer; 1967:20–48 pp.10.1007/978-3-642-88394-1_2Search in Google Scholar
32. Cornelissen, G. Cosinor-based rhythmometry. Theor Biol Med Model 2014;11:11–6. https://doi.org/10.1186/1742-4682-11-16.Search in Google Scholar PubMed PubMed Central
33. Spiess, AN, Neumeyer, N. An evaluation of R2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: a Monte Carlo approach. BMC Pharmacol 2010;10:6. https://doi.org/10.1186/1471-2210-10-6.Search in Google Scholar PubMed PubMed Central
34. Hutchison, AL, Allada, R, Dinner, AR. Bootstrapping and empirical Bayes methods improve rhythm detection in Sparsely sampled data. J Biol Rhythm 2018;33:339–49. https://doi.org/10.1177/0748730418789536.Search in Google Scholar PubMed PubMed Central
35. De los Santos, H, Collins, EJ, Mann, C, Sagan, AW, Jankowski, MS, Bennett, KP, et al.. ECHO: an application for detection and analysis of oscillators identifies metabolic regulation on genome-wide circadian output. Bioinformatics 2020;36:773–81. https://doi.org/10.1093/bioinformatics/btz617.Search in Google Scholar PubMed PubMed Central
Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/cclm-2024-1198).
© 2025 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Editorials
- The journey to pre-analytical quality
- Manual tilt tube method for prothrombin time: a commentary on contemporary relevance
- Reviews
- From errors to excellence: the pre-analytical journey to improved quality in diagnostics. A scoping review
- Advancements and challenges in high-sensitivity cardiac troponin assays: diagnostic, pathophysiological, and clinical perspectives
- Opinion Paper
- Is it feasible for European laboratories to use SI units in reporting results?
- Perspectives
- What does cancer screening have to do with tomato growing?
- Computer simulation approaches to evaluate the interaction between analytical performance characteristics and clinical (mis)classification: a complementary tool for setting indirect outcome-based analytical performance specifications
- Genetics and Molecular Diagnostics
- Artificial base mismatches-mediated PCR (ABM-PCR) for detecting clinically relevant single-base mutations
- Candidate Reference Measurement Procedures and Materials
- Antiphospholipid IgG Certified Reference Material ERM®-DA477/IFCC: a tool for aPL harmonization?
- General Clinical Chemistry and Laboratory Medicine
- External quality assessment of the manual tilt tube technique for prothrombin time testing: a report from the IFCC-SSC/ISTH Working Group on the Standardization of PT/INR
- Simple steps to achieve harmonisation and standardisation of dried blood spot phenylalanine measurements and facilitate consistent management of patients with phenylketonuria
- Inclusion of pyridoxine dependent epilepsy in expanded newborn screening programs by tandem mass spectrometry: set up of first and second tier tests
- Analytical performance evaluation and optimization of serum 25(OH)D LC-MS/MS measurement
- Towards routine high-throughput analysis of fecal bile acids: validation of an enzymatic cycling method for the quantification of total bile acids in human stool samples on fully automated clinical chemistry analyzers
- Analytical and clinical evaluations of Snibe Maglumi® S100B assay
- Prevalence and detection of citrate contamination in clinical laboratory
- Reference Values and Biological Variations
- Temporal dynamics in laboratory medicine: cosinor analysis and real-world data (RWD) approaches to population chronobiology
- Establishing sex- and age-related reference intervals of serum glial fibrillary acid protein measured by the fully automated lumipulse system
- Hematology and Coagulation
- Performance of the automated digital cell image analyzer UIMD PBIA in white blood cell classification: a comparative study with sysmex DI-60
- Cancer Diagnostics
- Flow-cytometric MRD detection in pediatric T-ALL: a multicenter AIEOP-BFM consensus-based guided standardized approach
- Impact of biological and genetic features of leukemic cells on the occurrence of “shark fins” in the WPC channel scattergrams of the Sysmex XN hematology analyzers in patients with chronic lymphocytic leukemia
- Assessing the clinical applicability of dimensionality reduction algorithms in flow cytometry for hematologic malignancies
- Cardiovascular Diseases
- Evaluation of sex-specific 0-h high-sensitivity cardiac troponin T thresholds for the risk stratification of non-ST-segment elevation myocardial infarction
- Retraction
- The first case of Teclistamab interference with serum electrophoresis and immunofixation
- Letters to the Editor
- Is this quantitative test fit-for-purpose?
- Reply to “Is this quantitative test fit-for-purpose?”
- Short-term biological variation of coagulation and fibrinolytic measurands
- The first case of Teclistamab interference with serum electrophoresis and immunofixation
- Imlifidase: a new interferent on serum protein electrophoresis looking as a rare plasma cell dyscrasia
- Research on the development of image-based Deep Learning (DL) model for serum quality recognition
- Interference of hypertriglyceridemia on total cholesterol assay with the new CHOL2 Abbott method on Architect analyser
- Congress Abstracts
- 10th Annual Meeting of the Austrian Society for Laboratory Medicine and Clinical Chemistry (ÖGLMKC)
Articles in the same Issue
- Frontmatter
- Editorials
- The journey to pre-analytical quality
- Manual tilt tube method for prothrombin time: a commentary on contemporary relevance
- Reviews
- From errors to excellence: the pre-analytical journey to improved quality in diagnostics. A scoping review
- Advancements and challenges in high-sensitivity cardiac troponin assays: diagnostic, pathophysiological, and clinical perspectives
- Opinion Paper
- Is it feasible for European laboratories to use SI units in reporting results?
- Perspectives
- What does cancer screening have to do with tomato growing?
- Computer simulation approaches to evaluate the interaction between analytical performance characteristics and clinical (mis)classification: a complementary tool for setting indirect outcome-based analytical performance specifications
- Genetics and Molecular Diagnostics
- Artificial base mismatches-mediated PCR (ABM-PCR) for detecting clinically relevant single-base mutations
- Candidate Reference Measurement Procedures and Materials
- Antiphospholipid IgG Certified Reference Material ERM®-DA477/IFCC: a tool for aPL harmonization?
- General Clinical Chemistry and Laboratory Medicine
- External quality assessment of the manual tilt tube technique for prothrombin time testing: a report from the IFCC-SSC/ISTH Working Group on the Standardization of PT/INR
- Simple steps to achieve harmonisation and standardisation of dried blood spot phenylalanine measurements and facilitate consistent management of patients with phenylketonuria
- Inclusion of pyridoxine dependent epilepsy in expanded newborn screening programs by tandem mass spectrometry: set up of first and second tier tests
- Analytical performance evaluation and optimization of serum 25(OH)D LC-MS/MS measurement
- Towards routine high-throughput analysis of fecal bile acids: validation of an enzymatic cycling method for the quantification of total bile acids in human stool samples on fully automated clinical chemistry analyzers
- Analytical and clinical evaluations of Snibe Maglumi® S100B assay
- Prevalence and detection of citrate contamination in clinical laboratory
- Reference Values and Biological Variations
- Temporal dynamics in laboratory medicine: cosinor analysis and real-world data (RWD) approaches to population chronobiology
- Establishing sex- and age-related reference intervals of serum glial fibrillary acid protein measured by the fully automated lumipulse system
- Hematology and Coagulation
- Performance of the automated digital cell image analyzer UIMD PBIA in white blood cell classification: a comparative study with sysmex DI-60
- Cancer Diagnostics
- Flow-cytometric MRD detection in pediatric T-ALL: a multicenter AIEOP-BFM consensus-based guided standardized approach
- Impact of biological and genetic features of leukemic cells on the occurrence of “shark fins” in the WPC channel scattergrams of the Sysmex XN hematology analyzers in patients with chronic lymphocytic leukemia
- Assessing the clinical applicability of dimensionality reduction algorithms in flow cytometry for hematologic malignancies
- Cardiovascular Diseases
- Evaluation of sex-specific 0-h high-sensitivity cardiac troponin T thresholds for the risk stratification of non-ST-segment elevation myocardial infarction
- Retraction
- The first case of Teclistamab interference with serum electrophoresis and immunofixation
- Letters to the Editor
- Is this quantitative test fit-for-purpose?
- Reply to “Is this quantitative test fit-for-purpose?”
- Short-term biological variation of coagulation and fibrinolytic measurands
- The first case of Teclistamab interference with serum electrophoresis and immunofixation
- Imlifidase: a new interferent on serum protein electrophoresis looking as a rare plasma cell dyscrasia
- Research on the development of image-based Deep Learning (DL) model for serum quality recognition
- Interference of hypertriglyceridemia on total cholesterol assay with the new CHOL2 Abbott method on Architect analyser
- Congress Abstracts
- 10th Annual Meeting of the Austrian Society for Laboratory Medicine and Clinical Chemistry (ÖGLMKC)