Associations Between High Plasma Methylxanthine Levels, Sleep Disorders and Polygenic Risk Scores of Caffeine Consumption or Sleep Duration in a Swiss Psychiatric Cohort

Objective: We first sought to examine the relationship between plasma levels of methylxanthines (caffeine and its metabolites) and sleep disorders, and secondarily between polygenic risk scores (PRS) of caffeine consumption or sleep duration with methylxanthine plasma levels and/or sleep disorders in a psychiatric cohort.Methods: Plasma levels of methylxanthines were quantified by ultra-high performance liquid chromatography/tandem mass spectrometry. In inpatients, sleep disorder diagnosis was defined using ICD-10 “F51.0,” sedative drug intake before bedtime, or hospital discharge letters, while a subgroup of sedative drugs was used for outpatients. The PRS of coffee consumption and sleep duration were constructed using publicly available GWAS results from the UKBiobank.Results: 1,747 observations (1,060 patients) were included (50.3% of observations with sleep disorders). Multivariate analyses adjusted for age, sex, body mass index, setting of care and psychiatric diagnoses showed that patients in the highest decile of plasma levels of methylxanthines had more than double the risk for sleep disorders compared to the lowest decile (OR = 2.13, p = 0.004). PRS of caffeine consumption was associated with plasma levels of caffeine, paraxanthine, theophylline and with their sum (β = 0.1; 0.11; 0.09; and 0.1, pcorrected = 0.01; 0.02; 0.02; and 0.01, respectively) but not with sleep disorders. A trend was found between the PRS of sleep duration and paraxanthine levels (β = 0.13, pcorrected = 0.09).Discussion: Very high caffeine consumption is associated with sleep disorders in psychiatric in- and outpatients. Future prospective studies should aim to determine the benefit of reducing caffeine consumption in high caffeine-consuming patients suffering from sleep disorders.

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Prenatal smoking, alcohol and caffeine exposure and ADHD risk in childhood: parental comparisons and polygenic risk score (PRS) analyses

10.1101/2021.03.25.21254087 ◽

2021 ◽

Author(s):

Elis Haan ◽

Hannah M Sallis ◽

Luisa Zuccolo ◽

Jeremy Labrecque ◽

Eivind Ystrom ◽

...

Keyword(s):

Substance Use ◽

Coffee Consumption ◽

Negative Control ◽

Sensitivity Analyses ◽

Risk Scores ◽

Prenatal Smoking ◽

Polygenic Risk Score ◽

Caffeine Consumption ◽

Polygenic Risk ◽

Prenatal Substance Use

Background and aims: Several studies have indicated that maternal prenatal substance use may be associated with offspring ADHD via intrauterine effects. We investigated associations between maternal prenatal smoking, alcohol and caffeine consumption with childhood ADHD risk accounting for shared familial factors. Design: First, we used a negative control design comparing maternal and paternal substance use. Three models were used for negative control analyses: unadjusted (without confounders); adjusted (including confounders) and mutually adjusted (including confounders and partners substance use). The results were meta-analysed across the cohorts. Second, we used polygenic risk scores (PRS) as proxies for exposures. Maternal PRS for genetic variants of smoking, alcohol and coffee consumption were regressed against ADHD risk. We triangulated the results across the two approaches to infer causality. Setting: We used data from three longitudinal pregnancy cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC) in the UK, Generation R study (GenR) in the Netherlands and Norwegian Mother, Father and Child Cohort study (MoBa) in Norway. Participants: Phenotype data available for children was: N(ALSPAC)=7,850; N(GENR)=3,849 and N(MOBA)=43,512. Genotype data available for mothers was: N(ALSPAC)=7,074 and N(MOBA)=14,583. Measurements: Offspring ADHD risk around age 7-8 was derived by dichotomising symptom scores from multiple questionnaires and parental self-reported substance use was measured at the 2nd pregnancy trimester. Findings: The pooled estimate for maternal prenatal substance use showed an association with ADHD risk (OR_SMOKING=1.11, 95%CI 1.00-1.23; OR_ALCOHOL=1.27, 95%CI 1.08-1.49; OR_CAFFEINE=1.05, 95%CI 1.00-1.11), while not for fathers (OR_SMOKING=1.03, 95%CI 0.95-1.13; OR_ALCOHOL=0.83, 95%CI 0.47-1.48; OR_CAFFEINE=1.02, 95%CI 0.97-1.07). However, maternal associations did not persist in sensitivity analyses (substance use before pregnancy, adjustment for maternal ADHD in MoBa). The PRS analyses did not show evidence of association in ALSPAC or MoBa. Conclusions: Our results do not provide support for a causal intrauterine effect of maternal prenatal substance use on offspring attention-deficit hyperactivity disorder risk.

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Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank

PLoS Medicine ◽

10.1371/journal.pmed.1003782 ◽

2021 ◽

Vol 18 (10) ◽

pp. e1003782

Author(s):

Michael Wainberg ◽

Samuel E. Jones ◽

Lindsay Melhuish Beaupre ◽

Sean L. Hill ◽

Daniel Felsky ◽

...

Keyword(s):

Bipolar Disorder ◽

Sleep Duration ◽

Sleep Efficiency ◽

Risk Scores ◽

Psychiatric Diagnoses ◽

Uk Biobank ◽

Major Depressive ◽

Cross Sectional ◽

Polygenic Risk ◽

The Uk

Background Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort. Methods and findings In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures—bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration—were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = −0.11 (95% confidence interval −0.13 to −0.10, p = 3 × 10−56, FDR = 6 × 10−55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry. Conclusions In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.

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Plasma levels of corticotropin-releasing hormone in hypothalamic—pituitary—adrenal disorders and chronic renal failure

Acta Endocrinologica ◽

10.1530/acta.0.1280503 ◽

1993 ◽

Vol 128 (6) ◽

pp. 503-507 ◽

Cited By ~ 10

Author(s):

Kozo Hashimoto ◽

Tatsuya Nishioka ◽

Yukiko Numata ◽

Takashi Ogasa ◽

Jingo Kageyama ◽

...

Keyword(s):

Renal Failure ◽

Chronic Renal Failure ◽

Plasma Levels ◽

High Performance ◽

High Plasma ◽

Reversed Phase ◽

Corticotropin Releasing Hormone ◽

Hypothalamic Pituitary Adrenal ◽

Releasing Hormone ◽

The Mean

Plasma levels of corticotropin-releasing hormone (CRH) were measured in hypothalamic-pituitary-adrenal disorders and chronic renal failure to investigate the clinical significance of plasma CRH. The mean plasma CRH level in normal subjects (N=26) was 1.64±0.43 pmol/l (normal range 0.77–2.5 pmol/l). Four of six patients with hypothalamic disorders receiving hydrocortisone supplementation had a low plasma CRH level. Two of six patients with Sheehan's syndrome had a low plasma CRH level whereas one patient had a high plasma CRH level. Two patients with Cushing's syndrome had a low plasma CRH level whereas two patients with Cushing's disease had a normal plasma CRH level. Six of 19 patients receiving prednisolone therapy had a low plasma CRH level. The mean plasma CRH level in this group was 0.97±0.34 pmol/l, which is significantly lower than that in the normal group. In this group, significant correlation was seen between plasma CRH and adrenocorticotropin levels. Eleven of 21 patients with chronic renal failure undergoing hemodialysis had a high plasma CRH level. Just after hemodialysis the plasma CRH levels decreased in 15 of 20 patients, while plasma adrenocorticotropin and cortisol levels increased in 13 of 19 patients and in 15 of 20 patients, respectively. Immunoreactive CRH in plasma measured both before and after hemodialysis eluted similarly on reversed-phase high-performance liquid chromatography. These results suggest that the plasma CRH level is at least partially suppressed by a chronically elevated plasma glucocorticoid level and that CRH in plasma is partially removed by hemodialysis.

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Sleep Deficits and Cannabis Use Behaviors: An Analysis of Shared Genetics Using Linkage Disequilibrium Score Regression and Polygenic Risk Prediction

10.1101/2020.05.02.053983 ◽

2020 ◽

Author(s):

Evan A. Winiger ◽

Jarrod M. Ellingson ◽

Claire L. Morrison ◽

Robin P. Corley ◽

Joëlle A. Pasman ◽

...

Keyword(s):

Linkage Disequilibrium ◽

Sleep Duration ◽

Association Studies ◽

Genetic Correlations ◽

Cannabis Use ◽

European Ancestry ◽

Risk Scores ◽

Genome Wide Association Studies ◽

Short Sleep Duration ◽

Polygenic Risk

AbstractStudy ObjectivesEstimate the genetic relationship of cannabis use with sleep deficits and eveningness chronotype.MethodsWe used linkage disequilibrium score regression (LDSC) to analyze genetic correlations between sleep deficits and cannabis use behaviors. Secondly, we generated sleep deficit polygenic risk scores (PRSs) and estimated their ability to predict cannabis use behaviors using logistic regression. Summary statistics came from existing genome wide association studies (GWASs) of European ancestry that were focused on sleep duration, insomnia, chronotype, lifetime cannabis use, and cannabis use disorder (CUD). A target sample for PRS prediction consisted of high-risk participants and participants from twin/family community-based studies (n = 796, male = 66%; mean age = 26.81). Target data consisted of self-reported sleep (sleep duration, feeling tired, and taking naps) and cannabis use behaviors (lifetime use, number of lifetime uses, past 180-day use, age of first use, and lifetime CUD symptoms).ResultsSignificant genetic correlation between lifetime cannabis use and eveningness chronotype (rG = 0.24, p < 0.01), as well as between CUD and both short sleep duration (<7 h) (rG = 0.23, p = 0.02) and insomnia (rG = 0.20, p = 0.02). Insomnia PRS predicted earlier age of first cannabis use (β = −0.09, p = 0.02) and increased lifetime CUD symptom count use (β = 0.07, p = 0.03).ConclusionCannabis use is genetically associated with both sleep deficits and an eveningness chronotype, suggesting that there are genes that predispose individuals to both cannabis use and sleep deficits.

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High performance pipeline for the calculation of polygenic risk scores

Bioinformatics of Genome Regulation and Structure/ Systems Biology ◽

10.18699/bgrs/sb-2020-047 ◽

2020 ◽

Keyword(s):

High Performance ◽

Risk Scores ◽

Polygenic Risk

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W2. THE EFFECT OF POLYGENIC RISK SCORES OF INSOMNIA, SLEEP DURATION AND CHRONOTYPE ON ADHD GENETIC SUSCEPTIBILITY IN CHILDREN FROM A BRAZILIAN SAMPLE

European Neuropsychopharmacology ◽

10.1016/j.euroneuro.2021.08.094 ◽

2021 ◽

Vol 51 ◽

pp. e147

Author(s):

Brenda Barbon Fraga ◽

Thais Martins-Silva ◽

Marina Xavier Carpena ◽

Julia P. Genro ◽

Angélica Salatino-Oliveira ◽

...

Keyword(s):

Genetic Susceptibility ◽

Sleep Duration ◽

Risk Scores ◽

Polygenic Risk ◽

Brazilian Sample

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Maternal and child genetic liability for smoking and caffeine consumption and child mental health: An intergenerational polygenic risk score analysis in the ALSPAC cohort

10.1101/2020.09.07.20189837 ◽

2020 ◽

Author(s):

Laura Schellhas ◽

Elis Haan ◽

Kayleigh Easey ◽

Robyn E Wootton ◽

Hannah Sallis ◽

...

Keyword(s):

Mental Health ◽

Health Outcomes ◽

Sensation Seeking ◽

Mental Health Outcomes ◽

Risk Scores ◽

Polygenic Risk Score ◽

Caffeine Consumption ◽

Polygenic Risk ◽

Childhood Mental Health ◽

Parents And Children

Background and aims: Previous studies suggest an association between maternal tobacco and caffeine consumption during and outside of pregnancy and offspring mental health. We used an intergenerational polygenic risk scores (PRS) approach to disentangle effects of the maternal environment (intrauterine or postnatal) and pleiotropic genetic effects. Specifically, we 1) validated smoking and caffeine PRS derived from published GWAS for use during pregnancy, 2) compared estimated effects of maternal and offspring PRS on childhood mental health outcomes, and 3) tested associations between maternal and offspring PRS on their own outcomes. Design: PRS were created for smoking and caffeine consumption for 8,196 mothers and 8,237 offspring from the Avon Longitudinal Study of Parents and Children (ALSPAC). Outcomes included mostly mental health and some non-mental health phenotypes (I.e. substance use, personality, BMI and sociodemographic variables). For mothers, 79 phenotypes assessed during and outside of pregnancy, and for offspring, 71 phenotypes assessed in childhood (<10 years) and adolescence (11-18 years) were included. Linear and logistic regressions were run to assess PRS in relation to maternal and offspring phenotypes. Findings: First, the maternal smoking and caffeine PRS were associated with these behaviours during pregnancy. Second, the maternal and offspring smoking PRS both showed evidence (permutation corrected P < 0.05) of association with reduced anxiety symptoms in childhood (βmaternal = -0.033; βoffspring= -0.031) and increased conduct disorder symptoms (βmaternal= 0.024; βoffspring= 0.030). Finally, the maternal and offspring smoking PRS were associated with own sensation seeking phenotypes in mothers and adolescence (e.g. increased symptoms of externalising disorders, extraversion, and monotony avoidance), but the caffeine PRS showed weaker evidence for associations with mental health outcomes. Our results indicate that the smoking PRS is most likely pleiotropic with sensation seeking personality traits. However, these results need replication in independent samples, using techniques more robust to pleiotropy.

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Clinical validation, implementation, and reporting of polygenic risk scores for common diseases

10.21203/rs.3.rs-743779/v1 ◽

2021 ◽

Author(s):

Jason Vassy ◽

Limin Hao ◽

Peter Kraft ◽

Gabriel Berriz ◽

Elizabeth Hynes ◽

...

Keyword(s):

Breast Cancer ◽

High Performance ◽

Genomic Medicine ◽

Risk Scores ◽

Polygenic Risk ◽

Clinical Assay ◽

Common Diseases ◽

Reporting Decisions ◽

Multiple Conditions

Abstract Implementation of polygenic risk scores (PRS) may improve disease prevention and management but requires the construction and validation of clinical assays, interpretation, and reporting pipelines. We developed a clinical genotype array-based assay for published PRS for 6 common diseases. First, we calculated PRS for 36,423 Mass General Brigham Biobank (MGBB) participants. Finding significant variation in the PRS distributions by race, we implemented adjustment for population structure with ancestry-informative principal components. We replicated published thresholds for odds ratio (OR)>2 in MGBB overall [ranging from 1.75 (1.57, 1.95) for Type 2 diabetes to 2.38 (2.07, 2.73) for breast cancer]. After confirming the high performance and robustness of the pipeline for use as a clinical assay, we analyzed the first 141 prospective samples from the Genomic Medicine at VA Study; frequency of PRS corresponding to published OR>2 ranged from 5/141 (3.6%) for colorectal cancer to 8/48 (16.7%) for breast cancer. Our development of a clinical PRS assay for multiple conditions illustrates the generalizability of this process and necessary technical and reporting decisions for meaningful clinical PRS implementation.

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