Genome-Wide Association Study of Sleep Disturbances in Depressive Disorders.
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ABSTRACT:
SUBMITTER: Melhuish Beaupre LM
PROVIDER: S-EPMC7206592 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Sleep disorders tend to be complex diseases, with multiple genes and environmental factors interacting to contribute to phenotypes. Our understanding of the genetic underpinnings of sleep disorders has benefited from recent genome-wide association studies (GWAS). We review principles underlying GWAS and discuss recent GWAS for restless legs syndrome and narcolepsy. These studies have identified four gene variants associated with restless legs syndrome (BTBD9, MEIS1, MAP2K5/LBXCOR1, and PTPRD) and two variants associated with narcolepsy (one in the T-cell receptor ? locus and another between CPT1B and CHKB). These discoveries have opened new lines of research to understand the pathophysiology of these disorders. In addition to GWAS, we expect that new technologies, such as next-generation sequencing, and continued use of animal models will provide important contributions to our understanding of the genetic basis of sleep disorders.
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Project description:BACKGROUND:Depression is a heritable trait that exists on a continuum of varying severity and duration. Yet, the search for genetic variants associated with depression has had few successes. We exploit the entire continuum of depression to find common variants for depressive symptoms. METHODS:In this genome-wide association study, we combined the results of 17 population-based studies assessing depressive symptoms with the Center for Epidemiological Studies Depression Scale. Replication of the independent top hits (p<1×10(-5)) was performed in five studies assessing depressive symptoms with other instruments. In addition, we performed a combined meta-analysis of all 22 discovery and replication studies. RESULTS:The discovery sample comprised 34,549 individuals (mean age of 66.5) and no loci reached genome-wide significance (lowest p = 1.05×10(-7)). Seven independent single nucleotide polymorphisms were considered for replication. In the replication set (n = 16,709), we found suggestive association of one single nucleotide polymorphism with depressive symptoms (rs161645, 5q21, p = 9.19×10(-3)). This 5q21 region reached genome-wide significance (p = 4.78×10(-8)) in the overall meta-analysis combining discovery and replication studies (n = 51,258). CONCLUSIONS:The results suggest that only a large sample comprising more than 50,000 subjects may be sufficiently powered to detect genes for depressive symptoms.
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Project description:BackgroundSleep is a highly conserved behavior, yet its duration and pattern vary extensively among species and between individuals within species. The genetic basis of natural variation in sleep remains unknown.ResultsWe used the Drosophila Genetic Reference Panel (DGRP) to perform a genome-wide association (GWA) study of sleep in D. melanogaster. We identified candidate single nucleotide polymorphisms (SNPs) associated with differences in the mean as well as the environmental sensitivity of sleep traits; these SNPs typically had sex-specific or sex-biased effects, and were generally located in non-coding regions. The majority of SNPs (80.3%) affecting sleep were at low frequency and had moderately large effects. Additive models incorporating multiple SNPs explained as much as 55% of the genetic variance for sleep in males and females. Many of these loci are known to interact physically and/or genetically, enabling us to place them in candidate genetic networks. We confirmed the role of seven novel loci on sleep using insertional mutagenesis and RNA interference.ConclusionsWe identified many SNPs in novel loci that are potentially associated with natural variation in sleep, as well as SNPs within genes previously known to affect Drosophila sleep. Several of the candidate genes have human homologues that were identified in studies of human sleep, suggesting that genes affecting variation in sleep are conserved across species. Our discovery of genetic variants that influence environmental sensitivity to sleep may have a wider application to all GWA studies, because individuals with highly plastic genotypes will not have consistent phenotypes.
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Project description:There are multiple disorders of neurodevelopment that present with co-occurring sleep disturbances. Many of these neurodevelopmental disorders (NDD) include sleep disturbances in their diagnostic criteria. Neurobiological, genetic, and environmental factors overlap to cause different sleep disorders in individuals with NDD. Caregivers often present reporting either insomnia or hypersomnia, and based on the clinical history and findings from diagnostic tests, an appropriate diagnosis can be made. It is crucial that clinicians understand the different presentations of sleep disturbances in individuals with NDD.
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Project description:A genome-wide association study was carried out in 1020 case subjects with recurrent early-onset major depressive disorder (MDD) (onset before age 31) and 1636 control subjects screened to exclude lifetime MDD. Subjects were genotyped with the Affymetrix 6.0 platform. After extensive quality control procedures, 671?424 autosomal single nucleotide polymorphisms (SNPs) and 25?068 X chromosome SNPs with minor allele frequency greater than 1% were available for analysis. An additional 1?892?186 HapMap II SNPs were analyzed based on imputed genotypic data. Single-SNP logistic regression trend tests were computed, with correction for ancestry-informative principal component scores. No genome-wide significant evidence for association was observed, assuming that nominal P<5 × 10(-8) approximates a 5% genome-wide significance threshold. The strongest evidence for association was observed on chromosome 18q22.1 (rs17077540, P=1.83 × 10(-7)) in a region that has produced some evidence for linkage to bipolar-I or -II disorder in several studies, within an mRNA detected in human brain tissue (BC053410) and approximately 75?kb upstream of DSEL. Comparing these results with those of a meta-analysis of three MDD GWAS data sets reported in a companion article, we note that among the strongest signals observed in the GenRED sample, the meta-analysis provided the greatest support (although not at a genome-wide significant level) for association of MDD to SNPs within SP4, a brain-specific transcription factor. Larger samples will be required to confirm the hypothesis of association between MDD (and particularly the recurrent early-onset subtype) and common SNPs.
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Project description:Depression and alcohol dependence (AD) are common psychiatric disorders that often co-occur. Both disorders are genetically influenced, with heritability estimates in the range of 35-60%. In addition, evidence from twin studies suggests that AD and depression are genetically correlated. Herein, we report results from a genome-wide association study of a comorbid phenotype, in which cases meet the Diagnostic and Statistical Manual of Mental Disorders-IV symptom threshold for major depressive symptomatology and the Diagnostic and Statistical Manual of Mental Disorders-IV criteria for AD.Samples (N=467 cases and N=407 controls) were of European-American descent and were genotyped using the Illumina Human 1M BeadChip array.Although no single-nucleotide polymorphism (SNP) meets genome-wide significance criteria, we identified 10 markers with P values less than 1 × 10(-5), seven of which are located in known genes, which have not been previously implicated in either disorder. Genes harboring SNPs yielding P values less than 1 × 10(-5) are functionally enriched for a number of gene ontology categories, notably several related to glutamatergic function. Investigation of expression localization using online resources suggests that these genes are expressed across a variety of tissues, including behaviorally relevant brain regions. Genes that have been previously associated with depression, AD, or other addiction-related phenotypes - such as CDH13, CSMD2, GRID1, and HTR1B - were implicated by nominally significant SNPs. Finally, the degree of overlap of significant SNPs between a comorbid phenotype and an AD-only phenotype is modest.These results underscore the complex genomic influences on psychiatric phenotypes and suggest that a comorbid phenotype is partially influenced by genetic variants that do not affect AD alone.
| S-EPMC3241912 | biostudies-literature
Project description:Several aspects of sleep behavior such as timing, duration and quality have been demonstrated to be heritable. To identify common variants that influence sleep traits in the population, we conducted a genome-wide association study of six sleep phenotypes assessed by questionnaire in a sample of 2,323 individuals from the Australian Twin Registry. Genotyping was performed on the Illumina 317, 370, and 610K arrays and the SNPs in common between platforms were used to impute non-genotyped SNPs. We tested for association with more than 2,000,000 common polymorphisms across the genome. While no SNPs reached the genome-wide significance threshold, we identified a number of associations in plausible candidate genes. Most notably, a group of SNPs in the third intron of the CACNA1C gene ranked as most significant in the analysis of sleep latency (P = 1.3 × 10??). We attempted to replicate this association in an independent sample from the Chronogen Consortium (n = 2,034), but found no evidence of association (P = 0.73). We have identified several other suggestive associations that await replication in an independent sample. We did not replicate the results from previous genome-wide analyses of self-reported sleep phenotypes after correction for multiple testing.
| S-EPMC4083458 | biostudies-literature
Project description:Major depressive disorder (MDD) is a complex, heritable psychiatric disorder. Advanced statistical genetics for genome-wide association studies (GWASs) have suggested that the heritability of MDD is largely explained by common single nucleotide polymorphisms (SNPs). However, until recently, there has been little success in identifying MDD-associated SNPs. Here, based on an empirical Bayes estimation of a semi-parametric hierarchical mixture model using summary statistics from GWASs, we show that MDD has a distinctive polygenic architecture consisting of a relatively small number of risk variants (~17%), e.g., compared to schizophrenia (~42%). In addition, these risk variants were estimated to have very small effects (genotypic odds ratio ? 1.04 under the additive model). Based on the estimated architecture, the required sample size for detecting significant SNPs in a future GWAS was predicted to be exceptionally large. It is noteworthy that the number of genome-wide significant MDD-associated SNPs would rapidly increase when collecting 50,000 or more MDD-cases (and the same number of controls); it can reach as much as 100 SNPs out of nearly independent (linkage disequilibrium pruned) 100,000 SNPs for ~120,000 MDD-cases.
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Project description:Depression, which is characterized by a pervasive and persistent low mood and anhedonia, greatly impacts patients, their families, and society. The associated and recurring sleep disturbances further reduce patient's quality of life. However, therapeutic sleep deprivation has been regarded as a rapid and robust antidepressant treatment for several decades, which suggests a complicated role of sleep in development of depression. Changes in neural plasticity are observed during physiological sleep, therapeutic sleep deprivation, and depression. This correlation might help us to understand better the mechanism underlying development of depression and the role of sleep. In this review, we first introduce the structure of sleep and the facilitated neural plasticity caused by physiological sleep. Then, we introduce sleep disturbances and changes in plasticity in patients with depression. Finally, the effects and mechanisms of antidepressants and therapeutic sleep deprivation on neural plasticity are discussed.
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Project description:BackgroundMenstrual disturbances harm women's health, and general well-being. As growing evidence highlights the relationship between sleep and menstrual disturbances, it is imperative to comprehensively examine the association between sleep and menstrual disturbance considering the multiple dimensions of sleep. This systematic review aims to identify the association between sleep and menstrual disturbances by evaluating using Buysse's sleep health framework.MethodsA comprehensive search of the literature was conducted in PubMed, EMBASE, psychINFO, and CINAHL to identify publications describing any types of menstrual disturbances, and their associations with sleep published between January 1, 1988 to June 2, 2022. Quality assessment was conducted using the Joanna Briggs Institute Critical Appraisal Checklist for Analytical Cross-Sectional Studies. The findings were iteratively evaluated menstrual disturbances and their association with sleep using Buysse's sleep health framework. This framework understands sleep as multidimensional concept and provides a holistic framing of sleep including Satisfaction, Alertness during waking hours, Timing of sleep, Efficiency, and Sleep duration. Menstrual disturbances were grouped into three categories: premenstrual syndrome, dysmenorrhea, and abnormal menstrual cycle/heavy bleeding during periods.ResultsThirty-five studies were reviewed to examine the association between sleep and menstrual disturbances. Premenstrual syndrome and dysmenorrhea were associated with sleep disturbances in sleep health domains of Satisfaction (e.g., poor sleep quality), Alertness during waking hours (e.g., daytime sleepiness), Efficiency (e.g., difficulty initiating/maintaining sleep), and Duration (e.g., short sleep duration). Abnormal menstrual cycle and heavy bleeding during the period were related to Satisfaction, Efficiency, and Duration. There were no studies which investigated the timing of sleep.Conclusions/implicationsSleep disturbances within most dimensions of the sleep health framework negatively impact on menstrual disturbances. Future research should longitudinally examine the effects of sleep disturbances in all dimensions of sleep health with the additional objective sleep measure on menstrual disturbances. This review gives insight in that it can be recommended to provide interventions for improving sleep disturbances in women with menstrual disturbance.
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