Linking discrimination and sleep with biomarker profiles: An investigation in the MIDUS study.
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ABSTRACT:
SUBMITTER: Yip T
PROVIDER: S-EPMC8321117 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:This study aimed to (1) provide a comprehensive characterization of depressive symptoms profiles, and (2) examine the cross-sectional association between depressive symptom profiles and cardio-metabolic outcomes, including metabolic syndrome and obesity, while controlling for sociodemographic variables, health behaviors and inflammation.Our sample was comprised of 1085 participants (55.80% female) enrolled in the MIDUS-II biomarker study. Latent profile analysis (LPA) was used to derive depressive symptom profiles using subscales of the Mood and Anxiety Symptom Questionnaire (MASQ) and the Center for Epidemiologic Studies Depression Scale (CES-D) subscales as well as Pittsburgh Sleep Quality Index (PSQI) global score. Metabolic syndrome was defined according to the Interim Joint Statement definition. CRP was used as a marker of inflammation.Four depressive symptom profiles were identified. The "No Symptoms" subgroup (60.65% of the sample) had the lowest overall scores across subscales. The "Mild Symptoms" subgroup (26.73%) was characterized by lower scores across indicators, with subscales measuring somatic symptoms being the highest within group. The "Moderate Symptoms" subgroup (10.32%) had higher scores across subscales (1 SD above the mean), with subscales measuring negative affect/loss of interest being the highest within group. Finally, the "Acute symptoms" subgroup (2.30%) was characterized by the highest overall scores (1.5-3 SD above the mean) on all indicators. After controlling for sociodemographic characteristics and health behaviors, the "Moderate Symptoms" subgroup was significantly associated with metabolic syndrome (OR=1.595, p=0.035) and obesity (OR=1.555, p=0.046). Further, there was a trend between the "Mild Symptoms" subgroup and the presence of obesity (OR=1.345, p=0.050). Inflammation attenuated these associations.Four depressive symptom profiles were identified among healthy mid-life individuals in the US. These profiles are differentially associated with cardio-metabolic outcomes. Future work should examine whether distinct symptom profiles may reflect differential pathways to increased risk, and whether tailored management of symptoms is needed.
| S-EPMC5833295 | biostudies-literature
Project description:Ethnic/racial discrimination is associated with negative psychosocial outcomes, and this study considered sleep disturbance as a mediating pathway. Employing a combination of daily diary and biannual surveys, multilevel structural equation models estimated the indirect effects of sleep/wake concerns on negative, anxious, and positive mood, rumination, and somatic symptoms. In a sample of 350 urban Asian (74% Chinese, 8% Korean, 4% Indian, 1% Filipinx, 1% Vietnamese, and 12% other), Black, and Latinx (25% Dominican, 24% South American, 22% Mexican, 15% Puerto Rican, 5% Central American, and 9% other) youth (M = 14.27 years, 69% female, 77% U.S. born, 76% monoethnic/racial, data collected from 2015 to 2018), there was evidence for sleep disturbances mediating the impact of ethnic/racial discrimination on adjustment. Nighttime disturbance, daytime dysfunction, and daytime sleepiness evidenced partial or full mediation for daily- and person-level outcomes (υ = 0.1%-17.9%). Reciprocal associations between sleep disturbances and negative mood and rumination were also observed.
| S-EPMC9546209 | biostudies-literature
Project description:The use of DNA microarrays to identify nucleotide variation is almost 20 years old. A variety of improvements in probe design and experimental conditions have brought this technology to the point that single-nucleotide differences can be efficiently detected in unmixed samples, although developing reliable methods for detection of mixed sequences (e.g. heterozygotes) remains challenging. Surprisingly, a comprehensive study of the probe design parameters and experimental conditions that optimize discrimination of single nucleotide polymorphisms (SNPs) has yet to be reported, so the limits of this technology remain uncertain. By targeting 24,549 SNPs that differ between two Saccharomyces cerevisiae strains, we studied the effect of SNPs on hybridization efficiency to DNA microarray probes of different lengths under different hybridization conditions. We found that the critical parameter for optimization of sequence discrimination is the relationship between probe melting temperature (Tm) and the temperature at which the hybridization reaction is performed. This relationship can be exploited through the design of microarrays containing probes of equal Tm by varying the length of probes. We demonstrate that using such a microarray we detect >90% homozygous SNPs and >80% heterozygous SNPs using the SNPScanner algorithm. The optimized design and experimental parameters determined in this study should guide DNA microarray designs for applications that require sequence discrimination such as mutation detection, genotyping of unmixed and mixed samples and allele-specific gene expression. Moreover, designing microarray probes with optimized sensitivity to mismatches should increase the accuracy of standard microarray applications such as copy number variation detection and gene expression analysis. Keyword(s): MutationDetection_CGH
2009-12-10 | GSE19319 | GEO
Project description:The use of DNA microarrays to identify nucleotide variation is almost 20 years old. A variety of improvements in probe design and experimental conditions have brought this technology to the point that single-nucleotide differences can be efficiently detected in unmixed samples, although developing reliable methods for detection of mixed sequences (e.g. heterozygotes) remains challenging. Surprisingly, a comprehensive study of the probe design parameters and experimental conditions that optimize discrimination of single nucleotide polymorphisms (SNPs) has yet to be reported, so the limits of this technology remain uncertain. By targeting 24,549 SNPs that differ between two Saccharomyces cerevisiae strains, we studied the effect of SNPs on hybridization efficiency to DNA microarray probes of different lengths under different hybridization conditions. We found that the critical parameter for optimization of sequence discrimination is the relationship between probe melting temperature (Tm) and the temperature at which the hybridization reaction is performed. This relationship can be exploited through the design of microarrays containing probes of equal Tm by varying the length of probes. We demonstrate that using such a microarray we detect >90% homozygous SNPs and >80% heterozygous SNPs using the SNPScanner algorithm. The optimized design and experimental parameters determined in this study should guide DNA microarray designs for applications that require sequence discrimination such as mutation detection, genotyping of unmixed and mixed samples and allele-specific gene expression. Moreover, designing microarray probes with optimized sensitivity to mismatches should increase the accuracy of standard microarray applications such as copy number variation detection and gene expression analysis. Keyword(s): MutationDetection_CGH Comparison of polymorphic vs non-polymorphic genomes when hybridrized to short probe microarrays
2010-05-18 | E-GEOD-19319 | biostudies-arrayexpress
Project description:BackgroundAbnormalities in heart rate during sleep linked to impaired neuro-cardiac modulation may provide new information about physiological sleep signatures of depression. This study assessed the validity of an algorithm using patterns of heart rate changes during sleep to discriminate between individuals with depression and healthy controls.MethodsA heart rate profiling algorithm was modeled using machine-learning based on 1203 polysomnograms from individuals with depression referred to a sleep clinic for the assessment of sleep abnormalities, including insomnia, excessive daytime fatigue, and sleep-related breathing disturbances (n = 664) and mentally healthy controls (n = 529). The final algorithm was tested on a distinct sample (n = 174) to categorize each individual as depressed or not depressed. The resulting categorizations were compared to medical record diagnoses.ResultsThe algorithm had an overall classification accuracy of 79.9% [sensitivity: 82.8, 95% CI (0.73-0.89), specificity: 77.0, 95% CI (0.67-0.85)]. The algorithm remained highly sensitive across subgroups stratified by age, sex, depression severity, comorbid psychiatric illness, cardiovascular disease, and smoking status.ConclusionsSleep-derived heart rate patterns could act as an objective biomarker of depression, at least when it co-occurs with sleep disturbances, and may serve as a complimentary objective diagnostic tool. These findings highlight the extent to which some autonomic functions are impaired in individuals with depression, which warrants further investigation about potential underlying mechanisms.
| S-EPMC6554996 | biostudies-literature
Project description:BACKGROUND:Disturbed sleep has been associated with increased insulin resistance and elevated inflammation. Although there is growing body of evidence that activation of inflammatory pathways plays a crucial role in the development of insulin resistance, the mediational model whereby sleep disturbances influence inflammation that drives insulin resistance has not been fully assessed in general population studies with objectively measured sleep. This study aimed to examine associations between objectively measured sleep, inflammatory markers, and insulin resistance simultaneously and in a mediational analysis, thereby offering insights into the possible causal model. METHODS:Cross-sectional data collected from 2004 to 2009 during the Midlife Development in the United States II biomarker project were used. The study population included 374 community-based participants (138 men and 236 women) who completed seven nights of wrist actigraphy. Multiple regressions controlling for age and statistically significant variables in univariate regressions were performed to evaluate the associations between actigraphy-assessed sleep measures, inflammatory cytokines, and insulin resistance. RESULTS:The regression models showed that in women, higher sleep onset latency (SOL) was associated with higher insulin resistance after controlling for age, smoking, obesity, diabetes, depression, and inflammatory cytokines. Higher SOL was also associated with higher interleukin (IL)-6 and C-reactive protein (CRP) levels in women, but no association was found in men. Using mediation models in women, the association between SOL and insulin resistance was partially explained by the indirect effect of inflammatory cytokines. CONCLUSION:A combination of inflammation and other unidentified pathways may contribute to the relationship between disturbed sleep and glucose homeostasis.
| S-EPMC5206915 | biostudies-literature
Project description:The first step in crop introduction-or breeding programmes-requires cultivar identification and characterisation. Rapid identification methods would therefore greatly improve registration, breeding, seed, trade and inspection processes. Metabolomics has proven to be indispensable in interrogating cellular biochemistry and phenotyping. Furthermore, metabolic fingerprints are chemical maps that can provide detailed insights into the molecular composition of a biological system under consideration. Here, metabolomics was applied to unravel differential metabolic profiles of various oat (Avena sativa) cultivars (Magnifico, Dunnart, Pallinup, Overberg and SWK001) and to identify signatory biomarkers for cultivar identification. The respective cultivars were grown under controlled conditions up to the 3-week maturity stage, and leaves and roots were harvested for each cultivar. Metabolites were extracted using 80% methanol, and extracts were analysed on an ultra-high performance liquid chromatography (UHPLC) system coupled to a quadrupole time-of-flight (qTOF) high-definition mass spectrometer analytical platform. The generated data were processed and analysed using multivariate statistical methods. Principal component analysis (PCA) models were computed for both leaf and root data, with PCA score plots indicating cultivar-related clustering of the samples and pointing to underlying differential metabolic profiles of these cultivars. Further multivariate analyses were performed to profile differential signatory markers, which included carboxylic acids, amino acids, fatty acids, phenolic compounds (hydroxycinnamic and hydroxybenzoic acids, and associated derivatives) and flavonoids, among the respective cultivars. Based on the key signatory metabolic markers, the cultivars were successfully distinguished from one another in profiles derived from both leaves and roots. The study demonstrates that metabolomics can be used as a rapid phenotyping tool for cultivar differentiation.
| S-EPMC8001698 | biostudies-literature
Project description:This study examines how the social environment is related to allostatic load (AL), a multisystem index of biological risk.A national sample of adults (N = 949) aged 34-84 rated their relationships with spouse, family, and friends at 2 time points 10 years apart. At the second time point, participants completed a biological protocol in which indices of autonomic, hypothalamic-pituitary-adrenal axis, cardiovascular, inflammatory, and metabolic function were obtained and used to create an AL summary score. Generalized estimating equations were used to examine the associations among 3 aspects of social relationships-social support, social negativity, and frequency of social contact-and AL.Higher levels of spouse negativity, family negativity, friend contact, and network level contact were each associated with higher AL, and higher levels of spouse support were associated with lower AL, independent of age, sociodemographic factors, and health covariates. Tests for age interactions suggested that friend support and network support were each associated with higher AL among older adults, but at younger ages there appeared to be no association between friend support and AL and a negative association between network support and AL. For network negativity, there was a marginal interaction such that network negativity was associated with higher AL among younger adults but there was no association among older adults.These findings demonstrate that structural and functional aspects of the social environment are associated with AL, and extend previous work by demonstrating that these associations vary based on the type of relationship assessed and by age.
| S-EPMC4104264 | biostudies-literature
Project description:An increasing body of literature indicates that discrimination has a negative impact on health; poor sleep may be an underlying mechanism. The primary objective of this review was to examine existing studies on the relationship between discrimination and sleep to clarify (a) the potential role of discrimination in shaping population patterns of sleep and sleep disparities, and (b) the research needed to develop interventions at individual and institutional levels. We identified articles from English-language publications in PubMed and EBSCO databases from inception through July 2014. We employed a broad definition of discrimination to include any form of unfair treatment and all self-reported and objectively assessed sleep outcomes, including duration, difficulties, and sleep architecture. Seventeen studies were identified: four prospective, 12 cross-sectional, and one that utilized a daily-diary design. Fifteen of the 17 studies evaluated interpersonal discrimination as the exposure and the majority of studies included self-reported sleep as the outcome. Only four studies incorporated objective sleep assessments. All 17 studies identified at least one association between discrimination and a measure of poorer sleep, although studies with more detailed consideration of either discrimination or sleep architecture revealed some inconsistencies. Taken together, existing studies demonstrate consistent evidence that discrimination is associated with poorer sleep outcomes. This evidence base can be strengthened with additional prospective studies that incorporate objectively measured aspects of sleep. We outline important extensions for this field of inquiry that can inform the development of interventions to improve sleep outcomes, and consequently promote well-being and reduce health inequities across the life course.
| S-EPMC4699868 | biostudies-literature
Project description:Study objectivesTo determine the effect of light exposure on subsequent sleep characteristics under ambulatory field conditions.MethodsTwenty healthy participants were fitted with ambulatory polysomnography (PSG) and wrist-actigraphs to assess light exposure, rest-activity, sleep quality, timing, and architecture. Laboratory salivary dim-light melatonin onset was analyzed to determine endogenous circadian phase.ResultsLater circadian clock phase was associated with lower intensity (R2 = 0.34, ?2(1) = 7.19, p < .01), later light exposure (quadratic, controlling for daylength, R2 = 0.47, ?2(3) = 32.38, p < .0001), and to later sleep timing (R2 = 0.71, ?2(1) = 20.39, p < .0001). Those with later first exposure to more than 10 lux of light had more awakenings during subsequent sleep (controlled for daylength, R2 = 0.36, ?2(2) = 8.66, p < .05). Those with later light exposure subsequently had a shorter latency to first rapid eye movement (REM) sleep episode (R2 = 0.21, ?2(1) = 5.77, p < .05). Those with less light exposure subsequently had a higher percentage of REM sleep (R2 = 0.43, ?2(2) = 13.90, p < .001) in a clock phase modulated manner. Slow-wave sleep accumulation was observed to be larger after preceding exposure to high maximal intensity and early first light exposure (p < .05).ConclusionsThe quality and architecture of sleep is associated with preceding light exposure. We propose that light exposure timing and intensity do not only modulate circadian-driven aspects of sleep but also homeostatic sleep pressure. These novel ambulatory PSG findings are the first to highlight the direct relationship between light and subsequent sleep, combining knowledge of homeostatic and circadian regulation of sleep by light. Upon confirmation by interventional studies, this hypothesis could change current understanding of sleep regulation and its relationship to prior light exposure.Clinical trial detailsThis study was not a clinical trial. The study was ethically approved and nationally registered (NL48468.042.14).
| S-EPMC5806586 | biostudies-literature