Genome-scale data have revealed daily rhythms in various species and tissues. However, current methods to assess rhythmicity largely restrict their focus to quantifying statistical significance, which may not reflect biological relevance. To address this limitation, we developed a method called LimoRhyde2 (the successor to our method LimoRhyde), which focuses instead on rhythm-related effect sizes and their uncertainty. For each genomic feature, LimoRhyde2 fits a curve using a series of linear models based on periodic splines, moderates the fits using an Empirical Bayes approach called multivariate adaptive shrinkage (Mash), then uses the moderated fits to calculate rhythm statistics such as peak-to-trough amplitude. The periodic splines capture non-sinusoidal rhythmicity, while Mash uses patterns in the data to account for different fits having different levels of noise. To demonstrate LimoRhyde2's utility, we applied it to multiple circadian transcriptome datasets. Overall, LimoRhyde2 prioritized genes having high-amplitude rhythms in expression, whereas a prior method (BooteJTK) prioritized "statistically significant" genes whose amplitudes could be relatively small. Thus, quantifying effect sizes using approaches such as LimoRhyde2 has the potential to transform interpretation of genomic data related to biological rhythms.

Biomedical research on mammals has traditionally neglected females, raising the concern that some scientific findings may generalize poorly to half the population. Although this lack of sex inclusion has been broadly documented, its extent within circadian genomics remains undescribed. To address this gap, we examined sex inclusion practices in a comprehensive collection of publicly available transcriptome studies on daily rhythms. Among 148 studies having samples from mammals in vivo, we found strong underrepresentation of females across organisms and tissues. Overall, only 23 of 123 studies in mice, 0 of 10 studies in rats, and 9 of 15 studies in humans included samples from females. In addition, studies having samples from both sexes tended to have more samples from males than from females. These trends appear to have changed little over time, including since 2016, when the US National Institutes of Health began requiring investigators to consider sex as a biological variable. Our findings highlight an opportunity to dramatically improve representation of females in circadian research and to explore sex differences in daily rhythms at the genome level.

Introduction: Insomnia is a significant co-morbidity for cancer survivors, and can independently reduce lifespan, but there is currently no objective biochemical measure of insomnia. Circadian rhythms are 24 hour cycles that control physiologic processes including sleep. Disrupted circadian rhythms have been proposed as a cause of insomnia. Here, we describe the use of a novel biomarker, BloodCCD, to assess circadian rhythms from RNA-sequencing of blood samples from two independent clinical trials and one observational study. BloodCCD was adapted from Clock Correlation Distance (CCD), which assesses normal progression of the molecular circadian clock from gene expression in tissue samples. We used BloodCCD to interrogate whether 1) cancer patients and survivors with insomnia have disrupted circadian rhythms compared to healthy good sleepers, and 2) whether the degree of circadian disruption correlates with severity of insomnia in survivors. Methods: For BloodCCD analysis, time-series RNA-sequencing of human blood from healthy subjects were used to construct a reference correlation matrix of 42 genes which oscillate with 24-hour rhythms. To assess the Aims, RNA-sequencing from patient and survivor blood samples were compared to this reference correlation matrix to generate a BloodCCD score. A higher score indicates a further distance from a healthy clock, and thus clock disruption. For the first Aim, blood RNA-sequencing from cancer patients undergoing active treatment and survivors at least 2-months post-treatment and with insomnia were compared to healthy good sleepers. For the second Aim, blood RNA-sequencing from cancer survivors with insomnia were assessed, stratified by Insomnia Severity Index (ISI) Score into mild (ISI 10-14), moderate (ISI 15-21), and severe (ISI 22-28) insomnia. Results: Patients (n=28, 100% prostate cancer) and cancer survivors (n=497, ~72% breast cancer) had higher BloodCCD scores, indicating disrupted circadian clock, compared to healthy good sleepers (n=14), with scores of 9.98, 7.99, and 4.13, respectively. When cancer survivors were stratified by insomnia severity, those with severe insomnia (ISI 22-28) had the highest BloodCCD, 9.00, while those with moderate insomnia (ISI 15-21) had a score of 8.24 and those with mild insomnia (ISI 10-14) had the lowest score of 7.93, indicating that survivors with severe insomnia had a more disrupted circadian clock. All BloodCCD values were p < 0.001 for each value compared to reference correlation. Conclusions: BloodCCD shows promise as a biomarker to biochemically detect disrupted circadian rhythms in cancer patients and survivors, and as a readout for insomnia severity. Future studies should investigate whether BloodCCD improves in cancer survivors receiving interventions for insomnia. Funding: UG1CA189961-07S1 (NCI BIQSFP Program), UG1CA189961 (URCC NCORP), T32CA102618 (URCC T32 program), K07CA221931 Citation Format: Brian J. Altman, Javier Bautista, Eva Culakova, Kristina M. Morris, Rachel E. DeRollo, Elliot Outland, Amber Kleckner, Ian R. Kleckner, Nikesha J. Gilmore, Benjamin T. Esparaz, Charles S. Kuzma, Amy C. Vander Woude, Po-Ju Lin, Jacob J. Hughey, Karen M. Mustian. BloodCCD is a novel biomarker to detect circadian rhythm disruption in cancer survivors with insomnia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3215.

Biomedical research on mammals has traditionally neglected females, raising the concern that some scientific findings may generalize poorly to half the population. Although this lack of sex inclusion has been broadly documented, its extent within circadian genomics remains undescribed. To address this gap, we examined sex inclusion practices in a comprehensive collection of publicly available transcriptome studies on daily rhythms. Among 148 studies having samples from mammals in vivo, we found strong underrepresentation of females across organisms and tissues. Overall, only 23 of 123 studies in mice, 0 of 10 studies in rats, and 9 of 15 studies in humans included samples from females. In addition, studies having samples from both sexes tended to have more samples from males than from females. These trends appear to have changed little over time, including since 2016, when the US NIH began requiring investigators to consider sex as a biological variable. Our findings highlight an opportunity to dramatically improve representation of females in circadian research and to explore sex differences in daily rhythms at the genome level.

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