Repeated Low-Grade Infections Predict Antidepressant-Resistant Depression

Jeng, Jia-Shyun; Li, Cheng Ta; Chen, Mu Hong; Lin, Wei Chen; Bai, Ya Mei; Tsai, Shih Jen; Su, Tung Ping; Chang, Wen Hang; Sung, Yen Jen

doi:10.4088/jcp.17m11540

Cited by 12 publications

(8 citation statements)

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“…29,71 It remains unclear how detrimental the use of peripheral blood DNAm is for identifying genomic regions associated with a psychiatric phenotype like depression. On one hand, specific brain regions hold intuitive appeal for MD-DNAm studies, and the cross-tissue similarity between brain and blood appears to be modest and tied to allelic variation; 72 however, given the well-established link between MD pathophysiology and aberrant immune system functioning, [34][35][36]73 peripheral blood may be the best and most feasible option for large or longitudinal studies of stress-related psychiatric traits. Many of the biomarkers associated with MD are transported in the blood (e.g., IL-1, IL-2, IL-6, TNFa, haptoglobin), and some of these immune-related differences appear to persist after depressive episode remission.…”

Section: Discussionmentioning

confidence: 99%

DNA Methylation Associated with Postpartum Depressive Symptoms Overlaps Findings from a Genome-wide Association Meta-Analysis of Depression

Lapato

Roberson‐Nay

Kirkpatrick

et al. 2019

Preprint

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Background: Perinatal depressive symptoms have been linked to adverse maternal and infant health outcomes. The etiology associated with perinatal depressive psychopathology is poorly understood, but accumulating evidence suggests that understanding inter-individual differences in DNA methylation (DNAm) patterning may provide insight regarding the genomic regions salient to the risk liability of perinatal depressive psychopathology.Results: Genome-wide DNAm was measured in maternal peripheral blood using the Infinium MethylationEPIC microarray. Ninety-two participants (46% African-American) had DNAm samples that passed all quality control metrics, and all participants were within seven months of delivery. Linear models were constructed to identify differentially methylated sites and regions, and permutation testing was utilized to assess significance. Differentially methylated regions (DMRs) were defined as genomic regions of consistent DNAm change with at least two probes within 1kb of each other. Maternal age, current smoking status, estimated cell-type proportions, ancestry-relevant principal components, days since delivery, and chip position served as covariates to adjust for technical and biological factors. Current postpartum depressive symptoms were measured using the Edinburgh Postnatal Depression Scale. Ninety-eight DMRs were significant (False Discovery Rate < 5%) and overlapped 92 genes. Synaptic signaling, neural development, and platelet formation were the most represented biological processes in gene set analysis, and comparison to the 44 loci discovered in the latest Psychiatric Genomics Consortium meta-analysis of depression revealed 3 overlapping regions and significant enrichment (p<0.03).Conclusions: Many of the genes identified in this analysis corroborate previous allelic, transcriptomic, and DNAm association results related to depressive phenotypes. Future work should integrate data from multi-omic platforms to understand the functional relevance of these DMRs and refine DNAm association results by limiting phenotypic heterogeneity and clarifying if DNAm differences relate to the timing of onset, severity, duration of perinatal mental health outcomes of the current pregnancy or to previous history of depressive psychopathology.

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Section: Discussionmentioning

confidence: 99%

DNA Methylation Associated with Postpartum Depressive Symptoms Overlaps Findings from a Genome-wide Association Meta-Analysis of Depression

Lapato

Roberson‐Nay

Kirkpatrick

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…Chronic inflammation can lead to the development of metabolic disease, resulting in even greater levels of inflammation within the body culminating in further disease development [1]. Similarly, patients with a history of repeated low-grade infections (evidence of a high inflammatory profile) are more likely to develop mood disorder in later life [15]. Other proposed mechanisms include dysregulation of the hypothalamic-pituitary-adrenal axis; cytokine-mediated neuronal destruction; altered concentrations of monoamine neurotransmitters; and decreased gray matter density in the brain [1,[16][17][18].…”

Section: Introductionmentioning

confidence: 99%

The association between C-reactive protein, mood disorder, and cognitive function in UK Biobank

et al. 2021

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Background Systemic inflammation has been linked with mood disorder and cognitive impairment. The extent of this relationship remains uncertain, with the effects of serum inflammatory biomarkers compared to genetic predisposition toward inflammation yet to be clearly established. Methods We investigated the magnitude of associations between C-reactive protein (CRP) measures, lifetime history of bipolar disorder or major depression, and cognitive function (reaction time and visuospatial memory) in 84,268 UK Biobank participants. CRP was measured in serum and a polygenic risk score for CRP was calculated, based on a published genome-wide association study. Multiple regression models adjusted for sociodemographic and clinical confounders. Results Increased serum CRP was significantly associated with mood disorder history (Kruskal–Wallis H = 196.06, p < 0.001, η2 = 0.002) but increased polygenic risk for CRP was not (F = 0.668, p = 0.648, η2 < 0.001). Compared to the lowest quintile, the highest serum CRP quintile was significantly associated with both negative and positive differences in cognitive performance (fully adjusted models: reaction time B = −0.030, 95% CI = −0.052, −0.008; visuospatial memory B = 0.066, 95% CI = 0.042, 0.089). More severe mood disorder categories were significantly associated with worse cognitive performance and this was not moderated by serum or genetic CRP level. Conclusions In this large cohort study, we found that measured inflammation was associated with mood disorder history, but genetic predisposition to inflammation was not. The association between mood disorder and worse cognitive performance was very small and did not vary by CRP level. The inconsistent relationship between CRP measures and cognitive performance warrants further study.

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“…It remains unclear how detrimental the use of peripheral blood DNAm is for identifying genomic regions associated with a psychiatric phenotype like depression. On one hand, specific brain regions hold intuitive appeal for MD-DNAm studies, and the cross-tissue similarity between brain and blood appears to be modest and tied to allelic variation [68]; however, given the well-established link between MD pathophysiology and aberrant immune system functioning [34–36, 69], peripheral blood may be the best and most feasible option for large or longitudinal studies of stress-related psychiatric traits. Many of the biomarkers associated with MD are transported in the blood (e.g., IL-1, IL-2, IL-6, TNFa, and haptoglobin), and some of these immune-related differences appear to persist after depressive episode remission.…”

Section: Discussionmentioning

confidence: 99%

DNA methylation associated with postpartum depressive symptoms overlaps findings from a genome-wide association meta-analysis of depression

et al. 2019

View full text Add to dashboard Cite

BackgroundPerinatal depressive symptoms have been linked to adverse maternal and infant health outcomes. The etiology associated with perinatal depressive psychopathology is poorly understood, but accumulating evidence suggests that understanding inter-individual differences in DNA methylation (DNAm) patterning may provide insight regarding the genomic regions salient to the risk liability of perinatal depressive psychopathology.ResultsGenome-wide DNAm was measured in maternal peripheral blood using the Infinium MethylationEPIC microarray. Ninety-two participants (46% African-American) had DNAm samples that passed all quality control metrics, and all participants were within 7 months of delivery. Linear models were constructed to identify differentially methylated sites and regions, and permutation testing was utilized to assess significance. Differentially methylated regions (DMRs) were defined as genomic regions of consistent DNAm change with at least two probes within 1 kb of each other. Maternal age, current smoking status, estimated cell-type proportions, ancestry-relevant principal components, days since delivery, and chip position served as covariates to adjust for technical and biological factors. Current postpartum depressive symptoms were measured using the Edinburgh Postnatal Depression Scale. Ninety-eight DMRs were significant (false discovery rate < 5%) and overlapped 92 genes. Three of the regions overlap loci from the latest Psychiatric Genomics Consortium meta-analysis of depression.ConclusionsMany of the genes identified in this analysis corroborate previous allelic, transcriptomic, and DNAm association results related to depressive phenotypes. Future work should integrate data from multi-omic platforms to understand the functional relevance of these DMRs and refine DNAm association results by limiting phenotypic heterogeneity and clarifying if DNAm differences relate to the timing of onset, severity, duration of perinatal mental health outcomes of the current pregnancy or to previous history of depressive psychopathology.

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Repeated Low-Grade Infections Predict Antidepressant-Resistant Depression

Cited by 12 publications

References 0 publications

DNA Methylation Associated with Postpartum Depressive Symptoms Overlaps Findings from a Genome-wide Association Meta-Analysis of Depression

DNA Methylation Associated with Postpartum Depressive Symptoms Overlaps Findings from a Genome-wide Association Meta-Analysis of Depression

The association between C-reactive protein, mood disorder, and cognitive function in UK Biobank

DNA methylation associated with postpartum depressive symptoms overlaps findings from a genome-wide association meta-analysis of depression

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