Policy

Timely intervention: A circadian approach to medical diagnostics

  • Watch on YouTube!

  • Our bodies follow a natural 24-hour cycle called circadian rhythms, which affect how our biological processes work at different times of the day. Many disease markers, like those for cancer and diabetes, change throughout the day. Ignoring these changes can lead to misdiagnoses and ineffective treatments. Currently, most medical tests in Canada do not consider these time-based changes. For example, the number of tumor cells in the blood can vary by the time of day, affecting cancer diagnosis. Similarly, blood sugar levels can show signs of diabetes in the evening but appear normal in the morning. I propose the creation of a database that describes how disease markers change throughout the day. Using samples from existing biobanks, we can track these changes and help doctors make more accurate diagnoses. This would also help schedule medical tests at the best times to detect the disease, improving health outcomes. By considering the time of day in medical practice, we can move towards more precise treatments, benefiting patients across Canada.

  • Time will pass. Daylight will rise and darkness will fall. As an adaptation to this fixed 24-hour cycle, nearly all organisms have evolved circadian rhythms: variations in biological processes that oscillate in a time-dependent manner. I have dedicated my doctoral studies to researching the adverse health effects resulting from dysfunctional intrinsic circadian rhythms. My work has led me to significant findings which demonstrate that colitis disease activity varies at different times of day [1]. Based on these findings, we recommend colitis diagnosis is scheduled during the late evening hours, when disease severity is most prevalent. Observing these fluctuations firsthand underscored the critical role circadian rhythms play in disease pathogenesis. This inspired me to explore how incorporating time-of-day considerations into clinical diagnostics could enhance diagnostic accuracy and treatment efficacy. By aligning medical practices with circadian rhythms of patients, we can improve healthcare outcomes and progress towards personalized and precise medical interventions.

  • Problem/ Need/ Opportunity for action

    Nearly 40% of mammalian protein coding genes have been shown to be rhythmic [2]. As a result, circadian rhythms govern many aspects of our daily physiology. Despite the growing body of research in circadian biology, most current diagnostic protocols in Canada do not account for the significant impact of circadian rhythms on disease markers. This oversight can potentially lead to misdiagnosis or delayed diagnosis, as many biomarkers and symptoms oscillate throughout the day. For example, circulating tumour cell numbers, which are often used in the prognosis of many cancers, have been shown to fluctuate based on time of day [3, 4, 5]. This indicates that timing of biopsy collection is important to provide accurate cancer diagnosis and develop precise treatment plans based on disease progression. It has also been established that insulin and glucagon secretion are regulated by circadian rhythms [6,7]. An estimated 2% of Canadians over 20 years old live with undiagnosed high blood glucose [8]. While accessibility to screening could be a factor, we must also consider the efficacy of existing screening practices. The effects of circadian rhythms on diabetes diagnosis are significant to the point where a patient taking a glucose tolerance test can exhibit signs of pre-diabetes if the test is taken in the evening while simultaneously appearing normal if taken in the morning [9, 10]. Early day testing has also been shown to yield better detection of infectious diseases such as SARS-CoV2 [11, 12] indicating the need for circadian diagnostic considerations in public health settings. Ignoring these fluctuations can lead to misdiagnoses, inappropriate treatment plans, and suboptimal patient outcomes. There is a pressing need to integrate circadian biology insights into clinical diagnostics to enhance precision. In doing so, Canadian patients can have increased access to early medical interventions which will greatly improve treatment outcomes.

    Proposed solution/ Policy change

    To address the limitations of current diagnostic practices and harness the benefits of circadian biology, I suggest 1) the creation of a comprehensive diagnostic database that includes time-of-day readings for various biomarkers under baseline conditions and disease states, along with 2) the development of clinical guidelines to encourage appropriate diagnostic appointment scheduling and sample collection protocols. To achieve this, specimen in the existing Statistics Canada Biobank and Canadian Health Measures Survey, which include serum, plasma, whole blood, urine and DNA, can be analyzed for an array of established disease biomarkers in health and disease inflicted patients. A similar analysis of tumour biopsies can be conducted through the Canadian Tissue Repository Network. This data can then be organized based on time of collection in order to develop a detailed database outlining biomarker oscillations over a 24-hour period. This will serve as an important diagnostic tool which will allow clinicians to evaluate their patient samples based on the time of collection and increase the resolution and overall accuracy of their analysis. Through these efforts, the optimal time of detection for many diseases will be determined. Care should be taken to schedule patient appointments based on these recommendations. By ensuring that suspected tumour biopsies are collected at the peak time of screening biomarkers, cancer diagnosis is less likely to be missed in its initial stages. In most cancers (including breast, prostate, colon and rectal), a stage 1 diagnosis resulted in a 90% improvement in survival rate [13]. While it is unrealistic for an endocrinologist, for instance, to schedule the entirety of their diabetic patients in the morning when insulin levels are at their peak [6, 7], these time slots should be reserved for the highest risk patients. With the increased prevalence of at-home viral testing for infectious diseases, these recommendations become very important. By simply outlining the appropriate time that a test should be administered by the user, you can increase the efficacy of the test and ensure that positive cases can take the necessary precautions to prevent further spread of the disease. Furthermore, strides can be made towards personalized medicine based on individual circadian patterns. Some people naturally exhibit shorter or longer circadian periods which can be detected by differences in circadian gene expression [14]. By simply adjusting their appointments and diagnostic analysis accordingly, it can lead to an improvement in patient outcome. Once these measures have been established, it opens the doors for future work to determine the optimal timing for various treatments known as chronotherapy. By integrating these practices into the healthcare system, Canada can become a leader in circadian medicine, ultimately enhancing patient care and health outcomes nationwide.

    Novelty/Creativity of Proposed Solution/Policy Change

    It has always been human nature to keep track of time. Whether it be the creation of the sundial to the clerical reporting of patient sampling. In this proposal, I have provided a practical solution to increase precision medicine for Canadian patients which utilizes information on time which has always been noted but has yet to be considered. By simply harnessing the power of circadian rhythms and adjusting the time at which we make diagnostic appoints based on the time of day during which disease biomarkers are expected to be at their peak, we can improve diagnostic accuracy, optimize treatment plans, and enhance the overall efficiency of healthcare delivery.

  • [1]        Z. Taleb et al., “BMAL1 Regulates the Daily Timing of Colitis,” Frontiers in Cellular and Infection Microbiology, vol. 12, Feb. 2022, doi: https://doi.org/10.3389/fcimb.2022.773413.

    [2]        R. Zhang, N. F. Lahens, H. I. Ballance, M. E. Hughes, and J. B. Hogenesch, “A circadian gene expression atlas in mammals: Implications for biology and medicine,” Proceedings of the National Academy of Sciences, vol. 111, no. 45, pp. 16219–16224, Oct. 2014, doi: https://doi.org/10.1073/pnas.1408886111.

    [3]        Z. Diamantopoulou et al., “The metastatic spread of breast cancer accelerates during sleep,” Nature, vol. 607, no. 7917, pp. 156–162, Jul. 2022, doi: https://doi.org/10.1038/s41586-022-04875-y.

    [4]        X. Zhu et al., “In vivo flow cytometry reveals a circadian rhythm of circulating tumor cells,” Light: Science & Applications, vol. 10, no. 1, p. 110, May 2021, doi: https://doi.org/10.1038/s41377-021-00542-5.

    [5]        B. Paiva et al., “Detailed characterization of multiple myeloma circulating tumor cells shows unique phenotypic, cytogenetic, functional, and circadian distribution profile,” Blood, vol. 122, no. 22, pp. 3591–3598, Nov. 2013, doi: https://doi.org/10.1182/blood-2013-06-510453.

    [6]        B. Marcheva et al., “Disruption of the clock components CLOCK and BMAL1 leads to hypoinsulinaemia and diabetes,” Nature, vol. 466, no. 7306, pp. 627–631, Jun. 2010, doi: https://doi.org/10.1038/nature09253.

    [7]        G. Boden, J. Ruiz, J. L. Urbain, and X. Chen, “Evidence for a circadian rhythm of insulin secretion,” American Journal of Physiology-Endocrinology and Metabolism, vol. 271, no. 2, pp. E246–E252, Aug. 1996, doi: https://doi.org/10.1152/ajpendo.1996.271.2.e246.

    [8]        Public Health Agency of Canada, “Twenty Years of Diabetes surveillance using the Canadian Chronic Disese Surveillance System - Canada.ca,” Canada.ca, 2019. https://www.canada.ca/en/public-health/services/publications/diseases-conditions/20-years-diabetes-surveillance.html

    [9]        R. J. Jarrett, I. A. Baker, H. Keen, and N. W. Oakley, “Diurnal Variation in Oral Glucose Tolerance: Blood Sugar and Plasma Insulin Levels Morning, Afternoon, and Evening,” BMJ, vol. 1, no. 5794, pp. 199–201, Jan. 1972, doi: https://doi.org/10.1136/bmj.1.5794.199.

    [10]      K. Carroll and P. J. Nestel, “Diurnal Variation in Glucose Tolerance and in Insulin Secretion in Man,” Diabetes, vol. 22, no. 5, pp. 333–348, May 1973, doi: https://doi.org/10.2337/diab.22.5.333.

    [11]      A. Viloria Winnett et al., “Morning SARS-CoV-2 Testing Yields Better Detection of Infection Due to Higher Viral Loads in Saliva and Nasal Swabs upon Waking,” Microbiology Spectrum, vol. 10, no. 6, Dec. 2022, doi: https://doi.org/10.1128/spectrum.03873-22.

    [12]      C. D. McNaughton, N. M. Adams, C. Hirschie Johnson, M. J. Ward, J. E. Schmitz, and T. A. Lasko, “Diurnal Variation in SARS-CoV-2 PCR Test Results: Test Accuracy May Vary by Time of Day,” Journal of Biological Rhythms, vol. 36, no. 6, pp. 595–601, Dec. 2021, doi: https://doi.org/10.1177/07487304211051841.

    [13]      S. C. Government of Canada, “Five-year cancer survival by stage at diagnosis in Canada,” www150.statcan.gc.ca, Jan. 18, 2023. https://www150.statcan.gc.ca/n1/pub/82-003-x/2023001/article/00001-eng.htm

    [14]      N. W. Gentry, L. H. Ashbrook, Y.-H. Fu, and L. J. Ptáček, “Human circadian variations,” Journal of Clinical Investigation, vol. 131, no. 16, Aug. 2021, doi: https://doi.org/10.1172/jci148282.

Advancing Equitable Healthcare in Canada through Personalized Medicine

  • Canada's population has experienced substantial growth, surpassing 40 million as of June 2023 (Thirtieth Annual Report to the Prime Minister, 2023). Population growth between July 1, 2022 and July 1, 2023 was primarily driven by net international migration, contributing to about 98% of total increase. The presence of landed immigrants and permanent residents, comprising 23% of the Canadian population, reflects the nation's diverse and multiethnic makeup (Statistics Canada, 2023). This demographic evolution highlights the need for a healthcare system that accommodates the distinctive health needs of this changing population.

    In the evolving landscape of Canadian healthcare, personalized medicine emerges as a transformative paradigm. By leveraging innovations in genomic sequencing technologies, this revolutionary approach to medicine takes into account individual variability in patients' genes, environments, and lifestyles. It aims to tailor medical decisions and interventions to the specific characteristics of each patient, recognizing that individuals may respond differently to the same treatment based on their genetic makeup and other factors. By integrating genetic and molecular information, personalized medicine seeks to enhance the accuracy and effectiveness of diagnoses, treatment plans, and preventive measures, ultimately optimizing patient outcomes and minimizing adverse effects. Personalized medicine provides a departure from traditional standardized approaches and paves the way for a future defined by predictive, preventative and precision-focused care. At the core of this ground-breaking initiative is a collaborative endeavor that unites experts across biomedical research, clinical practice, population health, health economics, ethics, and policy (CIHR, 2023). The overarching goal is to identify and address healthcare challenges of genetic diseases through the lens of personalized medicine, fostering translational research that promises enhanced efficacy in prevention, diagnosis, and treatment.

  • Proposal:

    The following paper proposes the implementation of personalized medicine to adapt to the changing demographics of Canada's population. Recognizing that ethnic groups share common genetic ancestry, it is crucial to acknowledge the higher prevalence of certain genetic diseases within different ethnic population. For instance, sickle cell disease is more frequently observed in individuals of African, African American (Pagnier et al., 1984), or Mediterranean heritage (El-Hazmi et al., 2011). Among individuals of Ashkenazi Jewish or French Canadian ancestry, Tay-Sachs disease has a higher prevalence (Myerowitz et al., 1988). In harnessing the nuances of genetic diversity, personalized medicine not only provides a revolutionary strategy to disease management but also enhances our comprehension of preventive interventions.

    Recent advancements in genetic sequencing technology have opened avenues for healthcare professionals to delve into the realm of epigenetics, encompassing heritable changes to gene function that do not alter the DNA genetic code but can contribute to disease development. Epigenetic modifications play a role in generational adaptations, where ancestral experiences, such as surviving famines, can lead to modifications in genetic readout that may lead to a higher likelihood of disease. Studies examining individuals born during the Dutch famine, compared to their siblings born before or after this period, revealed higher rates of type 2 diabetes (Roseboom et al., 2006; Tobi et al., 2018), cardiovascular disease (Roseboom et al., 2006), and schizophrenia (Hoek, 1996) among those born during the famine. A recent announcement by the Honourable Marc Miller, Minister of Immigration, Refugees and Citizenship, outlined temporary immigration measures for reunifying Palestinian Canadians with their loved ones in Gaza (Immigration, Refugees and Citizenship Canada, 2023).  As of December, 2023, the World Health Organization claimed that an unprecedented 93% of the population faces crisis levels of hunger (WHO, 2023). In anticipation of welcoming these new Canadians, epigenetic screening could offer insights into predictive and preventative measures for individuals prone to diseases similar to those observed after the Dutch famine. This underscores the potential of epigenetic analysis in addressing health challenges and guiding preventative interventions to vulnerable populations.

    The current landscape of genomic research is marked by a significant focus on individuals of European descent, accounting for over 86% of total genome-wide association studies (Mills et al., 2020). This lack of diversity in genomic sequencing has resulted in critical oversights in the diagnosis and treatment of genetic disorders. Diagnostic screening, which relies on identifying abnormal biomarkers previously identified from genomic sequencing studies, often fails to consider the unique genetic makeup of non-European ethnic groups. To exemplify this issue, a recent case study presents a female baby from rural India with a borderline first-tier newborn screening result for Cystic Fibrosis, a disease historically associated with Caucasians (Shum et al., 2021). Genetic sequencing, however, uncovered ethnically distinct biomarkers of cystic fibrosis in this patient, challenging the conventional Eurocentric screening design. The repercussions of ethnically inequitable testing frameworks are evident, as non-Caucasians with Cystic Fibrosis face prolonged delays in diagnosis and associated harms compared to their Caucasian counterparts. This underscores the need for inclusive personalized medicine approaches to ensure fairness and equity in healthcare delivery.

    Existing Initiatives:

    The Canadian Institutes of Health Research (CIHR) has been a key player in advancing personalized medicine through substantial funding. Since 2013, CIHR has invested over $85 million in personalized medicine research, contributing to the integration of this approach into biomedical research (CIHR, 2023). Notably, personalized medicine is increasingly accepted as an integral means to treatment plans, especially in challenging cases. For instance, in 2011 the London Health Science Centre became the first to roll out hospital wide personalized medicine initiatives under the leadership of Dr. Richard Kim (LHSC, 2024). While their research specifically focuses on pharmacogenomics, the study of genetic effects on drug response, it showcases the successful integration of personalized medicine into mainstream healthcare practices (Subasri, 2021).

    However, despite these strides, there remains an unmet need for prioritizing the use of personalized medicine for equitable healthcare for the diverse Canadian population. The proposal emphasizes the importance of extending the benefits of personalized medicine to all segments of the population.

    Recommendations:

    1. Prioritize Personalized Medicine in Underrepresented Ethnic Groups:

      • Conduct a comprehensive analysis of epidemiological data to identify underrepresented ethnic groups facing a higher prevalence of specific genetic diseases. Collaborate with health agencies, research institutions, and community health organizations to gather accurate and up-to-date information.

      • Develop clear criteria for patient selection, considering factors such as ethnicity, genetic predispositions, and prevalence of specific diseases within these communities.

      • Ensure that the criteria encompass a wide range of ethnic backgrounds to capture the diversity present in the population.

      • Utilize advanced genetic sequencing technologies to identify and validate ethnicity-specific biomarkers associated with prevalent genetic diseases. Collaborate with geneticists, researchers, and bioinformatics experts to ensure the accuracy and reliability of biomarker identification.

      • Implement a continuous monitoring and evaluation framework to assess the impact of personalized medicine initiatives on healthcare outcomes within underrepresented ethnic groups. Adapt strategies based on real-time feedback and emerging data to enhance the effectiveness of personalized medicine interventions.

    2. Create a Comprehensive Database:

      • Establish a centralized database to house genetic sequencing information. This database should include patient information encompassing ethnic, socio-economic and environmental information which can provide evidence for correlative studies.

      • Open the database to the national healthcare system, enabling efficient access and utilization of genetic data for medical interventions.

      • Collaborate with computer software engineers and research ethics boards to establish clear protocols for data privacy, confidentiality, and the responsible use of genetic information to build trust within the communities.

    3. Recruit “Personalized Health Champions” in communities:

      • Develop community programs to educate the public and encourage trust in personalized medicine.

      • Inform Canadians from diverse ethnic groups on ongoing genetic sequencing studies, emphasizing the importance of early screening based on genetic predispositions.

    Limitations:

    While the implementation of personalized medicine in underrepresented ethnic groups holds immense promise, it is crucial to acknowledge and address certain limitations inherent to this innovative strategy. One primary limitation is the initial cost associated with genetic sequencing, demanding a strategic and phased approach aligned with epidemiological data sets. However, it is important to recognize that this initial investment is poised to yield substantial long-term savings to our Canadian health care system. By steering away from exploratory diagnostic and treatment plans during challenging medical cases, personalized medicine establishes a targeted approach to treatment options ensuring more cost-effective and precise interventions. Additionally, the need for qualified personnel, particularly skilled biotechnologists, poses another challenge. Acknowledging this, the growing field of biotechnology is poised to meet the demand. Furthermore, incorporating artificial intelligence to analyze the vast datasets generated by this initiative not only addresses the personnel shortage but also enhances the efficiency and accuracy of data interpretation. Overall, these limitations are navigable with careful planning, strategic investments, and leveraging advancements in technology.

    Conclusion:

    In response to Canada's evolving and diverse population, personalized medicine emerges as a crucial solution, utilizing genomic sequencing to customize healthcare interventions. This transformative approach, departing from traditional methods, envisions a future marked by predictive, preventative, and precision-focused care. The proposal prioritizes underrepresented ethnic groups, recognizing the correlation between shared genetic ancestry and the prevalence of certain diseases. Embracing personalized medicine and creating a comprehensive database based on the diverse genetic makeup of its population positions Canada at the forefront of global healthcare innovation, offering a unique multiethnic dataset for optimized disease prediction, precision treatment, and ground-breaking research.

  • References

    El-Hazmi, MohsenA. F., Warsy, A., & Al-Hazmi, A. (2011). Sickle cell disease in Middle East Arab countries. The Indian Journal of Medical Research, 134(5), 597. https://doi.org/10.4103/0971-5916.90984

    CIHR (2011). Personalized Medicine overview - CIHR. Cihr-Irsc.gc.ca. https://cihr-irsc.gc.ca/e/43707.html

    Immigration, Refugees and Citizenship Canada. (2023). Immigration measures to help people affected by the Israel–Hamas conflict. https://www.canada.ca/en/immigration-refugees-citizenship/news/2023/12/immigration-measures-to-help-people-affected-by-the-israelhamas-conflict.html

    LHSC | About us. (2024). https://www.lhsc.on.ca/personalized-medicine/about-us

    Hoek, H. W. (1996). Schizoid personality disorder after prenatal exposure to famine. American Journal of Psychiatry, 153(12), 1637–1639. https://doi.org/10.1176/ajp.153.12.1637

    Mills, M. C., & Rahal, C. (2020). The GWAS Diversity Monitor tracks diversity by disease in real time. Nature Genetics, 52(3), 242–243. https://doi.org/10.1038/s41588-020-0580-y

    Myerowitz, R., & Costigan, F. C. (1988). The major defect in Ashkenazi Jews with Tay-Sachs disease is an insertion in the gene for the alpha-chain of beta-hexosaminidase. Journal of Biological Chemistry, 263(35), 18587–18589. https://doi.org/10.1016/s0021-9258(18)37323-x

    Pagnier, J., Mears, J. G., Dunda-Belkhodja, O., Schaefer-Rego, K. E., Beldjord, C., Nagel, R. L., & Labie, D. (1984). Evidence for the multicentric origin of the sickle cell hemoglobin gene in Africa. Proceedings of the National Academy of Sciences, 81(6), 1771–1773. https://doi.org/10.1073/pnas.81.6.1771

    Roseboom, T., de Rooij, S., & Painter, R. (2006). The Dutch famine and its long-term consequences for adult health. Early Human Development, 82(8), 485–491. https://doi.org/10.1016/j.earlhumdev.2006.07.001

    Shum, B. O. V., Bennett, G., Navilebasappa, A., & Kumar, R. K. (2021). Racially equitable diagnosis of cystic fibrosis using next-generation DNA sequencing: a case report. BMC Pediatrics, 21(1). https://doi.org/10.1186/s12887-021-02609-z

    Statistic Canada (2023). The Daily — Canada’s demographic estimates for July 1, 2023: record-high population growth since 1957. www150.Statcan.gc.ca. https://www150.statcan.gc.ca/n1/daily-quotidien/230927/dq230927a-eng.htm

    Subasri, M., Barrett, D., Sibalija, J., Bitacola, L., & Kim, R. B. (2021). Pharmacogenomic‐based personalized medicine: Multistakeholder perspectives on implementational drivers and barriers in the Canadian healthcare system. Clinical and Translational Science, 14(6), 2231–2241. https://doi.org/10.1111/cts.13083

    Thirtieth Annual Report to the Prime Minister. (2023). Thirtieth Annual Report to the Prime Minister on the Public Service of Canada - Privy Council Office. Www.canada.ca. https://www.canada.ca/en/privy-council/corporate/transparency/annual-report-prime-minister-public-service/30th.html

    Tobi, E. W., Slieker, R. C., Luijk, R., Dekkers, K. F., Stein, A. D., Xu, K. M., Slagboom, P. E., van Zwet, E. W., Lumey, L. H., & Heijmans, B. T. (2018). DNA methylation as a mediator of the association between prenatal adversity and risk factors for metabolic disease in adulthood. Science Advances, 4(1), eaao4364. https://doi.org/10.1126/sciadv.aao4364

    WHO. (2023). Lethal combination of hunger and disease to lead to more deaths in Gaza. Www.who.int. https://www.who.int/news/item/21-12-2023-lethal-combination-of-hunger-and-disease-to-lead-to-more-deaths-in-gaza