bluuebunny/crossref_metadata_2025_split huggingface dataset:
0009 Circadian Proteins and Circadian Phase Estimation in Healthy Adults
Authors: Specht Adrien , Saha Puja , Cederberg Katie , Bueno Flavia , Arrona-Palacios Arturo , Pardilla-Delgado Enmanuelle , Ruiz-Herrera Noelia , Zitting Kirsi-Marja , Kramer Achim , Zeitzer Jamie , Czeisler Charles , Duffy Jeanne , Mignot Emmanuel 
Published: April 2024

Abstract

Introduction
Circadian rhythms, which control sleep-wake cycles and metabolism, are fundamental to human health. Our study aimed to understand how these rhythms affect proteins in the body throughout the day, and to develop a tool that predicts the body's internal clock phase based on protein expression.

Methods
Plasma samples from 17 healthy adults were collected hourly under controlled conditions designed to unmask endogenous circadian rhythmicity; in a subset of 8 participants, we also collected samples across a day on a typical sleep-wake schedule. Using the SomaScan aptamer-based multiplexed platform, we analyzed a total of 6916 proteins were analyzed. We used differential rhythmicity analysis based on a cosinor model with mixed effects to identify a subset of proteins that demonstrates circadian rhythmicity. Finally, we trained a machine learning model to predict the Dim Light Melatonin Onset (DLMO) for a given protein sample.

Results
Four hundred and thirty-one (6.2%) proteins displayed consistent endogenous circadian rhythms on both a sleep-wake schedule and under controlled conditions. This subset not only aligns with the proteins selected by the elastic-net model but also maintains performance without diminishing it in comparison to using the complete set of available proteins. Overall, our circadian phase predictor reached a median absolute error (MdAE) of 1.2 hours when performing a leave-one-cross-out cross-validation subject-wise.

Conclusion
This research demonstrates that a considerable number of plasma proteins follow natural circadian rhythms within the human body. Furthermore, it establishes that the DLMO can be accurately predicted with a MdAE slightly over one hour using a single blood sample. More research with larger and more diverse datasets is essential to confirm our method, promising better treatments for circadian disorders and advancing personalized circadian health care.

Support (if any)
Collection, processing, and analysis of the samples were supported by National Institutes of Health (NIH) grant R01 HL148704 and unrestricted gifts. Collection of additional samples was supported by US Office of Naval Research grant N00014-15-1-2408. The BWH CCI is supported by Harvard Catalyst | The Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences, NIH Award UL1 TR002541) and financial contributions from Harvard University and its affiliated academic healthcare centers.
0011 Using Polygenic Scores for Circadian Rhythm to Predict Wellbeing, Depressive Symptoms, Chronotype, and Health
Authors: Landvreugd Anne , Pool René , Nivard Michel , Bartels Meike 
Published: April 2024

Abstract

Introduction
The association between the circadian rhythm and diseases has been well-established, while the association with mental health is less explored. Given the heritable nature of the circadian rhythm, this study aimed to investigate the relationship between genes underlying the circadian rhythm and mental health outcomes, as well as a possible gene-environment correlation for circadian rhythm.

Methods
In a sample from the Netherlands Twin Register (N = 14,021), polygenic scores (PGSs) were calculated for two circadian rhythm measures: Morningess and Relative Amplitude. The PGSs were used to predict mental health outcomes such as subjective happiness, quality of life, and depressive symptoms In addition, we performed the same prediction analysis in a within-family design in a subset of dizygotic twins.

Results
The PGS for Morningness significantly predicted Morningness (R2 = 1.55%,) and Depressive Symptoms (R2= 0.22%,). The PGS for Relative Amplitude significantly predicted General Health (R2 = 0.12%,) and Depressive Symptoms (R2 = 0.20%,). Item analysis of the depressive symptoms showed that 4/14 items were significantly associated with the PGSs. The within-family results hinted at a gene-environment correlation for Morningness.

Conclusion
Overall, the results showed that people with a genetic predisposition of being a morning person or a high relative amplitude are likely to have fewer depressive symptoms. Contrarily to our hypotheses, the four associated depressive symptoms described symptoms related to decision-making, energy, and feeling worthless, rather than sleep. Our findings plead for a substantial role for the circadian rhythm in depression research, and to further explore the gene-environment correlation in the circadian rhythm

Support (if any)
0016 In Search of Vitamin Sleep: Vitamin and Mineral Intake and Multimodal Sleep Outcomes in Adolescents
Authors: Broadbent Mary , Kamhout Sarah , Zhang Victoria , Martin McKenna , Homer Kate , Fisher Morgan , Reese Matthew , Duraccio Kara 
Published: April 2024

Abstract

Introduction
Previous studies suggest that under 15% of adolescents regularly consume vitamin- and mineral-rich foods such as leafy greens and legumes. In addition to experiencing poor dietary intake, this developmental group is also subject to high rates of insufficient sleep duration (~70%). Thus, adolescents may be especially susceptible to the influence on micronutrient deficiencies on poor sleep. This study seeks to generalize previous adult findings to an adolescent population who may especially benefit from multimodal therapies targeting poor sleep and diet in tandem.

Methods
Seventy-four adolescents (43 females) ages 14-18 submitted 2-3 dietary recalls on randomized weekends and weekdays. Additionally, participants completed a Dim-Light Melatonin Onset (DLMO) appointment, the Epworth Sleepiness Scale for Children and Adolescents (ESS-CHAD), and the Pittsburgh Sleep Quality Index (PSQI). Possible associations between vitamin (Folate, Folic Acid, Niacin, Retinol, Riboflavin, Thiamin, Vitamins A, B-6, B12, C, D, E, and K) and mineral (Calcium, Copper, Iron, Magnesium, Phosphorus, Potassium, Selenium, and Zinc) intake and melatonin onset time (DLMO, threshold 4 pg/mL), daytime sleepiness (ESS-CHAD total), and self-reported sleep duration (PSQI Item 4) were evaluated using multiple bivariate regression models.

Results
Following correction for multiple comparisons, no vitamins or minerals were found to be significant predictors of sleep quality outcomes. B12 approached significance for predicting DLMO time (beta=.337, t(64)=2.367, p=.021; R2 = .073, F(3,61)=2.684, p=.054) and daytime sleepiness (beta=.334, t(72)=2.517, p=.014; R2 = .065, F(3,69)= 2.662, p=.055), as did Magnesium for daytime sleepiness (beta=-.284, t(73)=-2.349, p=.022; R2 = .057, F(3,70)=2.481,p=.068) and Zinc for DLMO time (beta=.369, t(65)=2.562, p=.013; R2 = .083, F(3,62)=2.961, p=.039).

Conclusion
Vitamin and mineral intake was not significantly related to self-reported sleep outcomes and DLMO in adolescents. Future studies can examine dietary intake in conjunction with more objective physiological measures of sleep health. Failure to meet RDA in this age group presents limitations when studying the effects of increased consumption. Other study designs could incorporate B12, magnesium, and zinc measurement given potential signal.

Support (if any)
0019 Body Weight Reduction Following 8-weeks of Time-restricted Eating in Peri- and Postmenopausal Women with Obesity
Authors: Grant Leilah , Webb Jennifer , Bates Hailey , Carter Megan , Dressel Madeline , Williams Jonathan , Manson JoAnn , Mora Samia , Joffe Hadine , Rahman Shadab 
Published: April 2024

Abstract

Introduction
Many women experience weight gain due to hormonal changes during menopause. Time-restricted eating (TRE) has been proposed as a dietary intervention to reduce body weight but has not been studied extensively during the menopause transition. We aimed to test the effect of TRE on body weight and composition in peri- and recently (&lt; 5 yrs) postmenopausal women with obesity.

Methods
Participants were recruited from the New England area. To date, 23 women (mean age±SD: 51.9±4.1 yrs; mean BMI±SD: 34.9±3.2 kg/m2) have been randomized to 8-weeks of unrestricted eating (URE; n=11) or TRE (n=12), where participants were instructed to consume calories only during a self-selected 8-hour eating window each day (e.g., 10 am-6 pm). Outcomes included body weight, body composition [fat, fat-free and visceral adipose tissue (VAT) mass, measured via dual x-ray absorptiometry], and 7-day caloric intake [kCal/day; per MealloggerTM app with time-stamp]. Change from baseline to post-intervention was compared between the groups using t-tests.

Results
On average, the TRE eating window was 4.1±0.7 (95%CI 2.7 to 5.6) hours shorter than the URE group (p&lt; 0.001; 7.1±0.2 vs. 11.2±0.7 hours, respectively). Compliance with the daily 8-hour TRE eating window (average compliance 93±6.9% of days) and acceptability (11/12 planned to continue TRE after study completion) were high. Despite no statistically significant between-group difference in calorie intake (1515.8±561.7 vs 1430.0±419.6 kCal/day), the TRE group lost an average of 2.4±0.6 kg (SD), significantly more than the URE group who gained an average of 0.46±0.4 kg (p&lt; 0.01; mean difference=2.8±0.7, 95%CI -4.4 to -1.3). Furthermore, there was a trend toward a greater reduction in fat mass in the TRE (-0.7±0.4 kg) compared to URE group (0.65±0.6 kg) (p=0.059; mean difference=1.4±0.7 kg, 95%CI -2.8 to 0.06). Change in fat-free and VAT mass did not differ.

Conclusion
In this interim analysis of an ongoing trial, 8 weeks of TRE led to a reduction in body weight and possibly fat mass in peri- and postmenopausal women with obesity. Importantly, compliance and acceptability of the diet were high, suggesting that the intervention is feasible and sustainable in this population.

Support (if any)
BWH and Bayer Pharmaceuticals supporting U54AG062322; BWH Pollin Research Award; WHAM Edge Award
0021 Effects of Pharmacological Estradiol Suppression on Urinary 6-sulfatoxymelatonin Output in Premenopausal Women
Authors: Rahman Shadab , Lockley Steven , Cohn Aviva , Kim Hannah , Wiley Aleta , Joffe Hadine , Grant Leilah 
Published: April 2024

Abstract

Introduction
The relationship between the female sex steroid estradiol and the pineal hormone melatonin has been hypothesized to be reciprocal, whereby estradiol is low when melatonin is high and vice versa. Results from human studies have been mixed, however, which may be attributable to the large inter-individual differences in overall levels of melatonin secretion between individuals. Furthermore, menopause, characterized by declining levels of estradiol, has been associated with decreased levels of melatonin, although the contributions of ovarian aging versus chronological aging on melatonin levels is not clear. In the current within-subject experimental study of premenopausal women, we aimed to examine the effects of pharmacologically-induced estradiol suppression on the 24-hour output and circadian rhythm characteristics of the urinary melatonin metabolite, 6-sulfatoxymelatonin (aMT6s), thereby isolating estradiol-related effects from those if chronological aging.

Methods
Urine was collected every 3-4 hours during the daytime and 8-10 hours overnight over ~24 hours during a laboratory study from 12 premenopausal women (mean age±SD= 27.9±5.6 yrs) during their mid-to-late follicular phase when estradiol levels were high (i.e., estrogenized state), and again ~6 weeks later following pharmacologically-induced estradiol suppression (i.e., hypo-estrogenized state) due to administration of the gonadotrophin releasing hormone agonist, leuprolide (3.75mg intramuscular injection). Morning single-timepoint serum estradiol levels, 24-hour aMT6s output, and the cosinor analysis-derived mesor, amplitude and acrophase of the aMT6s rhythm were compared between the estradiol states using paired t-tests or non-parametric alternative.

Results
As expected, leuprolide suppressed estradiol levels by ~90% on average compared to levels in the mid-to-late follicular phase (p&lt; 0.001; 120.7±43.4 vs. 5.6±0.6 pg/mL, respectively, Cohen’s d= 1.1). On average, 24-h aMT6s output was 5.3% higher following estradiol suppression but this was not significantly different from the estrogenized state (p=0.4; 16.1±5.7 vs. 15.4±1.6 µg/24-h, respectively, Cohen’s d= 0.12). Similarly, there were no differences in any of the aMT6s rhythm characteristics between estradiol states.

Conclusion
In a within-subject analysis, pharmacologically-induced estradiol suppression did not influence the overall 24-h output or rhythm characteristics of urinary 6-sulphatoxmelatonin, suggesting that that melatonin and estradiol may not be reciprocal. Furthermore, these results suggest that the decline in melatonin observed across menopause may not be due to ovarian aging.

Support (if any)
R01AG053838
0022 Daily Rhythms of Fractal Motor Activity Regulation in Older Adults: Relevance to Prediction of Alzheimer’s Dementia
Authors: Sun Haoqi , Li Peng , Gao Lei , Yang Jingyun , Yu Lei , Buchman Aron , Bennett David , Westover M Brandon , Hu Kun 
Published: April 2024

Abstract

Introduction
Fractal motor activity regulation (FMAR), characterized by self-similar temporal correlations in activity fluctuations across different timescales, is robust in healthy young but degrades in patients with Alzheimer’s disease (AD). We recently discovered that disrupted FMAR predicted increased risk for AD dementia. It is unknown whether FMAR and its predictability for incident AD vary across the 24-h cycle.

Methods
We studied 1,077 participants in the Rush Memory and Aging Project who were cognitively normal at baseline, had baseline actigraphy, and had at least one follow-up clinical assessment until 2020. To assess the daily rhythm of FMAR, we obtained a scaling exponent α in each 1-h actigraphy data that estimates the temporal correlations in activity fluctuations across timescales of 1.5-10 min, using detrended fluctuation analysis (DFA). For each 1-hour bin across the 24-h cycle, we used a Cox regression model to examine the association of scaling exponent α with incident AD while adjusting for age at baseline, sex, and years of education. The p-values were corrected using Bonferroni correction for the 24 hourly comparisons.

Results
The scaling exponential α from DFA showed a daily rhythm with a trough at 3am (α=0.71) and a peak at 3pm (α=0.84). The hazard ratio (HR) for incident AD (per 1-SD increase in α) also showed a daily rhythm. Specifically, smaller α (indicating more random activity fluctuations) between 7am to 10pm was associated with an increased risk of incident AD (HR ranging from 0.59 [95% CI 0.50-0.70, p &lt; 0.001] to 0.79 [95%CI 0.69-0.91, p = 0.0013], lowest at 3pm); α between 11pm-6am was not significantly correlated with incident AD.

Conclusion
Fractal motor activity regulation in older adults exhibited a daily rhythm and more random activity fluctuations between 7am-10pm were predictive of higher risk for AD dementia.

Support (if any)
NIH RF1AG064312 and BrightFocus Foundation Alzheimer’s Research A2020886S.
0024 Measuring Melanopsin-driven Retinal Responses in Sleep and Circadian Health: Performance of the Pupil Light Reflex
Authors: Klevens Alison , Wescott Delainey , Taylor Maddison , Gamlin Paul , Franzen Peter , Hasler Brant , Siegle Greg , Roecklein Kathryn 
Published: April 2024

Abstract

Introduction
Alterations in the melanopsin-driven post-illumination pupil response (PIPR) may reflect a physiological vulnerability for circadian mood disruptions. However, the PIPR is confounded by other factors affecting retinal irradiance, like how much light reaches the retina. The pupil light reflex (PLR) measures effects on pupil responses that are nonspecific to melanopsin. Controlling for nonspecific factors related to retinal irradiance (i.e., age, entrance pupil diameter, iris pigmentation) is necessary to isolate melanopsin-driven retinal response in PIPR studies. The present study re-analyzed data using group, season, and a group-by-season interaction to predict the PIPR with different covariates testing nonspecific effects on the PIPR. We hypothesized that the PLR alone would explain more variance in the PIPR then the above set of indirect measures of nonspecific effects.

Methods
Participants ages 19-65 (M=34.9, SD=10.6) with seasonal depression (n=25) and non-depressed controls (n=22) completed assessments in the winter and summer months. The PLR was measured as the difference between baseline pupil diameter and the acute minimum constriction in millimeters and expressed as a percent of baseline. The Net PIPR was calculated as the difference between the red and blue trials averaged 10-40 seconds post-light stimulus. Iris pigmentation was rated using the Franssen (2008) scale. Model performance for different covariate sets was assessed using Akaike Information Criteria (AIC). All models included time of the PIPR relative to midsleep.

Results
Significant associations between group, season, and a group*season interaction in predicting the PIPR were found in every model. Model fit varied based on covariates included. The PLR following red light performed best in models predicting the PIPR (AIC=-161.63) compared to a model including age, entrance pupil diameter, and iris pigmentation (AIC=-144.98). The next best fit model included the PLR in response to blue light (AIC=-157.57).

Conclusion
Studies aiming to isolate melanopsin-driven retinal responsivity should adopt the PLR as an individually specific, objective, and contemporaneous measure of nonspecific influences of light on pupil responsivity. Methodology separating the effects of light incident on the retina (e.g., PLR) from melanopsin-driven retinal responses (e.g., PIPR) can inform treatments like bright light therapy, allowing titration of light intensity to account for individual differences in retinal irradiance.

Support (if any)
0031 Shared Genetic Mechanisms Underlying Association Between Sleep Disturbances and Depressive Symptoms
Authors: Moyses-Oliveira Mariana , Zamariolli Malú , Tempaku Priscila , Galduróz José , Andersen Monica , Tufik Sergio 
Published: April 2024

Abstract

Introduction
Although associations between insomnia and major depression disorder have been reported, little is known about the shared genetic mechanisms underlying their comorbidity. Polygenic scores (PGS) for sleep disturbances and depressive symptoms in an epidemiological cohort were calculated and correlated. Genes assigned to variants that compose the best-fit PGS predictions were overlapped to explore the shared genetic bases of sleep problems and depressive symptoms.

Methods
Human OmniExpress BeadChip genotyping was performed on the São Paulo Epidemiologic Sleep Study (EPISONO, N=1042), an adult epidemiological sample subjected to a sleep-based survey. PGS analysis was performed on 900 individuals with PRSice2. Summary statistics from a genome wide association study (GWAS) for depression (N=500,199, United Kingdom Biobank (UKBB) and Psychiatry Genetics Consortium) grounded the PGS calculations for Beck Depression Index (BDI), while insomnia GWAS (N=386,988, UKBB) based the PGS for Insomnia Severity Index (ISI) and Pittsburg Sleep Quality Index (PSQI) in EPISONO. Pearson’s correlation was applied to contrast PGS and clinical scores. Genes were assigned to SNPs using Ensembl Variant Effect Predictor and Fisher’s Exact test was used to test the overlap between gene lists. Pathway enrichment analysis was performed on sets of interest genes using Benjamin-Hochberg test.

Results
All PGS models were significant when individuals were divided as cases or controls according to BDI, PSQI and ISI scales. When clinical scales were used as continuous variables, the best-fit PGS models for BDI (p=0.0004, R2=1.56%) and PSQI scores (p=0.0058, R2=0.87%) reached statistical significance, but PGS calculations were unable to significantly predict ISI scores. PSQI and BDI scores were highly correlated, and the same observation was applied to PGS for sleep quality and depressive symptoms. Genes associated with the variants which compose the best-fit PGS predictions for sleep quality and depressive symptoms were significantly overlapped. Pathways enriched among the intersect genes are related to synapse function and formation.

Conclusion
The genetic bases of sleep quality and depressive symptoms are correlated; their implicated genes are significantly overlapped and converge on neural pathways. This data suggests that sleep complaints accompanying depressive symptoms are not secondary issues, but part of the core mental illness.

Support (if any)
AFIP, FAPESP, CNPq.
0032 Metabolomic Profile of Excessive Daytime Sleepiness in the Hispanic Community Health Study/Study of Latinos
Authors: Faquih Tariq , Yu Bing , Kaplan Robert , Isasi Carmen , Redline Susan , Sofer Tamar , Wang Heming 
Published: April 2024

Abstract

Introduction
Excessive daytime sleepiness (EDS) is a prevalent condition estimated to affect up to 33% of the United States population. EDS is a heterogeneous and complex symptom of various sleep disorders, insufficient sleep, and other chronic conditions and medications. EDS has also been associated with increased risk of cardiovascular and neuropsychiatric diseases, potentially through bidirectional causal pathways. In this study, we used metabolomic measurements in 6071 individuals from the Hispanic Community Health Study/Study of Latinos to elucidate the metabolomic factors associated with EDS.

Methods
EDS was assessed using the Epworth Sleepiness Score (a 24-point scale) at baseline (2008), continuously modeled. Metabolomics (877 metabolites) were quantified using the Metabolon platform—from blood assayed at baseline—and were log scaled. Our primary and sex stratified models adjusted for age, body mass index, ethnicity, recruitment center, alcohol, smoking, and physical activity. Secondary analysis further adjusted for insomnia, sleep duration, and sleep apnea. Significance threshold was set to 0.00013 to account for multiple testing. Finally, the interplay between metabolites, pathways, and genes was investigated through network and pathway enrichment analyses.

Results
Levels of seven metabolite were each associated with a decrease of the sleepiness score by approximately 0.4 points per one log unit increase in metabolite levels. Those metabolites were primarily categorized as fatty acids (Eicosadienoic acid, Docosadienoate), steroids (Pregnenolone sulphate, Tetrahydrocortisol-glucuronide), along with a sphingomyelin and two uncharacterized metabolites. Sex stratified analysis identified three additional metabolites associated with EDS in men: Tyramine O-sulfate and two phosphatidylcholines. Tyramine O-sulfate was particularly associated with an increased sleepiness score by 0.5 per log unit; with attenuation after adjusting for sleep traits. Network and pathway enrichment analysis indicated that changes in pathways related to cortisol metabolism, hormonal steroid metabolism, and melatonin metabolism were linked to EDS.

Conclusion
These results suggest that a combination of metabolomic factors, representing diet and steroid hormonal pathways dietary related metabolites, and some genetic factors contributes to the metabolic profile of EDS. Some associations appeared independent of common sleep disorders while a male-specific association was driven by sleep disturbances (insomnia).

Support (if any)
NIH R01HL153814 (to H.W.), R01HL161012 (to T.S.), and R35HL135818 (to SR).