Corrigendum: Potential genetic overlap between insomnia and sleep symptoms in major depressive disorder: A polygenic risk score analysis.

[This corrects the article DOI: 10.3389/fpsyt.2021.734077.].

Potential Genetic Overlap Between Insomnia and Sleep Symptoms in Major Depressive Disorder: A Polygenic Risk Score Analysis.

Background: The prevalence of insomnia and hypersomnia in depressed individuals is substantially higher than that found in the general population. Unfortunately, these concurrent sleep problems can have profound effects on the disease course. Although the full biology of sleep remains to be elucidated, a recent genome-wide association (GWAS) of insomnia, and other sleep traits in over 1 million individuals was recently published and provides many promising hits for genetics of insomnia in a population-based sample. Methods: Using data from the largest available GWAS of insomnia and other sleep traits, we sought to test if sleep variable PRS scores derived from population-based studies predicted sleep variables in samples of depressed cases [Psychiatric Genomics Consortium - Major Depressive Disorder subjects (PGC MDD)]. A leave-one-out analysis was performed to determine the effects that each individual study had on our results. Results: The only significant finding was for insomnia, where p-value threshold, p = 0.05 was associated with insomnia in our PGC MDD sample (R 2 = 1.75-3, p = 0.006). Conclusion: Our results reveal that <1% of variance is explained by the variants that cover the two significant p-value thresholds, which is in line with the fact that depression and insomnia are both polygenic disorders. To the best of our knowledge, this is the first study to investigate genetic overlap between the general population and a depression sample for insomnia, which has important treatment implications, such as leading to novel drug targets in future research efforts.

Genetic comorbidity between major depression and cardio-metabolic traits, stratified by age at onset of major depression.

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents.

Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression.

BACKGROUND: The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression. METHODS: We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10-6) and a candidate threshold (1.6 × 10-4). RESULTS: No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99). CONCLUSIONS: We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.

Diagnosis and management of bipolar disorder in primary care: a DSM-5 update.

This review discusses the diagnosis and detection of bipolar disorder in the primary care population with recent changes introduced by Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition and the pharmacotherapy and psychosocial management of this psychiatric condition.

The genetics of major depression: moving beyond the monoamine hypothesis.

Efforts to unlock the biology of major depressive disorder (MDD) are proceeding on multiple fronts. In this article, the authors review the current understanding of epidemiological evidence for a heritable component to MDD risk, as well as recent advances in linkage, candidate gene, and genome-wide association analyses of MDD and related disease subtypes and endophenotypes. While monoamine signaling has preoccupied the bulk of scientific investigation to date, nontraditional gene candidates such as PCLO and GRM7 are now emerging and beginning to change the landscape for future human and animal research on depression.

A genomewide association study of citalopram response in major depressive disorder.

BACKGROUND: Antidepressant response is likely influenced by genetic constitution, but the actual genes involved have yet to be determined. We have carried out a genomewide association study to determine whether common DNA variation influences antidepressant response. METHODS: Our sample is derived from Level 1 participants in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, all treated with citalopram. Association for the response phenotype included 883 responders and 608 nonresponders. For the remission phenotype, 743 subjects that achieved remission were compared with 608 nonresponders. We used a subset of single nucleotide polymorphisms (SNPs; n = 430,198) from the Affymetrix 500K and 5.0 Human SNP Arrays, and association analysis was carried out after correcting for population stratification. RESULTS: We identified three SNPs associated with response with p values less than 1 x 10(-5) near the UBE3C gene (rs6966038, p = 4.65 x 10(-7)), another 100 kb away from BMP7 (rs6127921, p = 3.45 x 10(-6)), and a third that is intronic in the RORA gene (rs809736, p = 8.19 x 10(-6)). These same SNPs were also associated with remission. Thirty-nine additional SNPs are of interest with p values < or = .0001 for the response and remission phenotypes. CONCLUSIONS: Although the findings reported here do not meet a genomewide threshold for significance, the regions identified from this study provide targets for independent replication and novel pathways to investigate mechanisms of antidepressant response. This study was not placebo controlled, making it possible that we are also observing associations to nonspecific aspects of drug treatment of depression.

Resequencing of serotonin-related genes and association of tagging SNPs to citalopram response.

Several reports have been published investigating the relationship between common variants in serotonin-related candidate genes and antidepressant response, and most of the results have been equivocal. We previously reported a significant association between variants in serotonin-related genes and response to the selective serotonin reuptake inhibitor fluoxetine. Here, we attempt to expand upon and replicate these results by (i) resequencing the exonic and putatively regulatory regions of five serotonin-related candidate genes (HTR1A, HTR2A, TPH1, TPH2, and MAOA) in our fluoxetine-treated sample to uncover novel variants; (ii) selecting tagging single nucleotide polymorphisms (SNPs) for these genes from the resequencing data; and (iii) evaluating these tagging SNPs for association with response to the selective serotonin reuptake inhibitor citalopram in an independent sample of participants who are enrolled in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) clinical study (N=1953). None of the variants associated previously with fluoxetine response were found to be associated with citalopram response in the STAR*D sample set. Nor were any of the additional tagging SNPs found to be associated with citalopram response. An additional SNP in HTR2A (rs7997012), previously reported to be associated with outcome of citalopram treatment in this sample, but not well tagged by any of the other SNPs we studied, was also genotyped, and was associated with citalopram response (P=0.0002), strongly supporting the previous observation in the same STAR*D sample. Our results suggest that resequencing the serotonin-related genes did not identify any additional common SNPs that have not been identified previously. It appears that genetic variation in these five genes has a marginal effect on response to citalopram, although a previously observed association was supported and awaits replication in an independent sample.

Serotonin and Go modulate functional states of neurons and muscles controlling C. elegans egg-laying behavior.

From nematodes to humans, animals employ neuromodulators like serotonin to regulate behavioral patterns and states. In the nematode C. elegans, serotonin has been shown to act in a modulatory fashion to increase the rate and alter the temporal pattern of egg laying. Though many candidate effectors and regulators of serotonin have been identified in genetic studies, their effects on specific neurons and muscles in the egg-laying circuitry have been difficult to determine. Using the genetically encoded Ca(2+) indicator cameleon, we found that serotonin acts directly on the vulval muscles to increase the frequency of Ca(2+) transients. In contrast, we found that the spontaneous activity of the egg-laying motorneurons was silenced by serotonin. Mutations in G protein alpha subunit genes altered the responses of both vulval muscles and egg-laying neurons to serotonin; specifically, mutations in the G(q)alpha homolog egl-30 blocked serotonin stimulation of vulval muscle Ca(2+) transients, while mutations in the G(o)alpha homolog goa-1 prevented the silencing of motorneuron activity by serotonin. These data indicate that serotonin stimulates egg laying by directly modulating the functional state of the vulval muscles. In addition, serotonin inhibits the activity of the motorneurons that release it, providing a feedback regulatory effect that may contribute to serotonin adaptation.