Multidimensional predictors of antidepressant responses: Integrating mitochondrial, genetic, metabolic and environmental factors with clinical outcomes
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ABSTRACT:
SUBMITTER: Nasca C
PROVIDER: S-EPMC8592929 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundA significant proportion of patients with major depressive disorder (MDD) failed to respond to antidepressant medications. Repetitive transcranial magnetic stimulation (rTMS) is an effective option for treating such treatment-resistant patients with MDD (TRD). Reliable clinical predictors for antidepressant responses to rTMS remain elusive.MethodsIn total, 212 patients with MDD who failed to respond to at least one adequate antidepressant trial and had a detailed evaluation before rTMS were recruited for chart review. Demographic data, clinical characteristics, psychiatric comorbidities, symptom ratings [e.g., objective and subjective depression, life stress, depression refractoriness by Maudsley Staging Method (MSM)], and antidepressant treatment responses were analyzed.ResultsMSM-subitem1 (duration of current depressive episode; Beta = 0.209, p = 0.004), MSM-subitem5 (a history of ECT treatment; Beta = -0.210, p = 0.004), and psychiatric admissions (Beta = 0.241, p = 0.001) predicted antidepressant response of rTMS treatment. ECT was underutilized (only 3.3%). Psychiatric admissions [Exp(B) = 1.382, p = 0.021], a comorbidity of OCD [0.047, 0.005], and life stress level [0.984, 0.029] predicted the history of ECT treatment.ConclusionSeveral clinical variables (e.g., number of psychiatric admissions, OCD as a comorbidity, and life stress level) were reliable clinical factors associated with antidepressant responses of rTMS treatment and may be utilized in combination with MSM subitems to evaluate levels of TRD.
| S-EPMC9757691 | biostudies-literature
Project description:BackgroundThere is growing evidence about the role of nurses in patient outcomes in several healthcare settings. However, there is still a lack of evidence about the transitional care setting. We aimed to assess the association between patient characteristics identified in a multidimensional nursing assessment and outcomes of mortality and acute hospitalization during community hospital stay.MethodsA retrospective observational study was performed on patients consecutively admitted to a community hospital (CH) in Loreto (Ancona, Italy) between January 1st, 2018 and May 31st, 2019. The nursing assessment included sociodemographic characteristics, functional status, risk of falls (Conley Score) and pressure damage (Norton scale), nursing diagnoses, presence of pressure sores, feeding tubes, urinary catheters or vascular access devices and comorbidities. Two logistic regression models were developed to assess the association between patient characteristics identified in a multidimensional nursing assessment and outcomes of mortality and acute hospitalization during CH stay.ResultsWe analyzed data from 298 patients. The mean age was 83 ± 9.9 years; 60.4% (n = 180) were female. The overall mean length of stay was 42.8 ± 36 days (32 ± 32 days for patients who died and 33.9 ± 35 days for patients who had an acute hospitalization, respectively). An acute hospitalization was reported for 13.4% (n = 40) of patients and 21.8% (n = 65) died. An increased risk of death was related to female sex (OR 2.25, 95% CI 1.10-4.62), higher Conley Score (OR 1.19; 95% CI 1.03-1.37) and having a vascular access device (OR 3.64, 95% CI 1.82-7.27). A higher Norton score was associated with a decreased risk of death (OR 0.71, 95% CI 0.62-0.81). The risk for acute hospitalization was correlated with younger age (OR 0.94, 95% CI 0.91-0.97), having a vascular access device (OR 2.33, 95% CI 1.02-5.36), impaired walking (OR 2.50, 95% CI 1.03-6.06) and it is inversely correlated with a higher Conley score (OR 0.84, 95% CI 0.77-0.98).ConclusionUsing a multidimensional nursing assessment enables identification of risk of nearness of end of life and acute hospitalization to target care and treatment. The present study adds further knowledge on this topic and confirms the importance of nursing assessment to evaluate the risk of patients' adverse outcome development.
| S-EPMC8049226 | biostudies-literature
Project description:In multidimensional cancer omics studies, one subject is profiled on multiple layers of omics activities. In this article, the goal is to integrate multiple types of omics measurements, identify markers, and build a model for cancer outcome. The proposed analysis is achieved in two steps. In the first step, we analyze the regulation among different types of omics measurements, through the construction of linear regulatory modules (LRMs). The LRMs have sound biological basis, and their construction differs from the existing analyses by modeling the regulation of sets of gene expressions (GEs) by sets of regulators. The construction is realized with the assistance of regularized singular value decomposition. In the second step, the proposed cancer outcome model includes the regulated GEs, "residuals" of GEs, and "residuals" of regulators, and we use regularized estimation to select relevant markers. Simulation shows that the proposed method outperforms the alternatives with more accurate marker identification. We analyze the The Cancer Genome Atlas data on cutaneous melanoma and lung adenocarcinoma and obtain meaningful results.
| S-EPMC5031941 | biostudies-literature
Project description:Although there is a wide variety of antidepressants with different mechanisms of action available, the efficacy of treatment is not satisfactory. Genetic factors are presumed to play a role in differences in medication response; however, available evidence is controversial. Even genome-wide association studies failed to identify genes or regions which would consequently influence treatment response. We conducted a literature review in order to uncover possible mechanisms concealing the direct effects of genetic variants, focusing mainly on reports from large-scale studies including STAR*D or GENDEP. We observed that inclusion of environmental factors, gene-environment and gene-gene interactions in the model improves the probability of identifying genetic modulator effects of antidepressant response. It could be difficult to determine which allele of a polymorphism is the risk factor for poor treatment outcome because depending on the acting environmental factors different alleles could be advantageous to improve treatment response. Moreover, genetic variants tend to show better association with certain intermediate phenotypes linked to depression because these are more objective and detectable than traditional treatment outcomes. Thus, detailed modeling of environmental factors and their interactions with different genetic pathways could significantly improve our understanding of antidepressant efficacy. In addition, the complexity of depression itself demands a more comprehensive analysis of symptom trajectories if we are to extract useful information which could be used in the personalization of antidepressant treatment.
| S-EPMC4106212 | biostudies-literature
Project description:Current methods for detecting genetic associations lack full consideration of the background effects of environmental exposures. Recently proposed methods to account for environmental exposures have focused on logistic regressions with gene-environment interactions. In this report, we developed a test for genetic association, encompassing a broad range of risk models, including linear, logistic and probit, for specifying joint effects of genetic and environmental exposures. We obtained the test statistics by maximizing over a class of score tests, each of which involves modified standard tests of genetic association through a weight function. This weight function reflects the potential heterogeneity of the genetic effects by levels of environmental exposures under a particular model. Simulation studies demonstrate the robust power of these methods for detecting genetic associations under a wide range of scenarios. Applications of these methods are further illustrated using data from genome-wide association studies of type 2 diabetes with body mass index and of lung cancer risk with smoking.
| S-EPMC4575251 | biostudies-literature
Project description:To understand the mechanisms involved in the control and regulation of mitochondrial reactive oxygen species (ROS) levels, a two-compartment computational mitochondrial energetic-redox (ME-R) model accounting for energetic, redox, and ROS metabolisms is presented. The ME-R model incorporates four main redox couples (NADH/NAD(+), NADPH/NADP(+), GSH/GSSG, Trx(SH)(2)/TrxSS). Scavenging systems-glutathione, thioredoxin, superoxide dismutase, catalase-are distributed in mitochondrial matrix and extra-matrix compartments, and transport between compartments of ROS species (superoxide: O(2)(?-), hydrogen peroxide: H(2)O(2)), and GSH is also taken into account. Model simulations are compared with experimental data obtained from isolated heart mitochondria. The ME-R model is able to simulate: i), the shape and order of magnitude of H(2)O(2) emission and dose-response kinetics observed after treatment with inhibitors of the GSH or Trx scavenging systems and ii), steady and transient behavior of ??(m) and NADH after single or repetitive pulses of substrate- or uncoupler-elicited energetic-redox transitions. The dynamics of the redox environment in both compartments is analyzed with the model following substrate addition. The ME-R model represents a useful computational tool for exploring ROS dynamics, the role of compartmentation in the modulation of the redox environment, and how redox regulation participates in the control of mitochondrial function.
| S-EPMC3552263 | biostudies-literature
Project description:Background: Numerous studies have focused on the PI3K/AKT/mTOR pathway in estrogen receptor positive (ER) breast cancer (BC), as a linear signal transduction pathway and reported its association with worse clinical outcomes. To gain better insight into the relative contribution of each of the signalling pathways which lie downstream to PI3K (namely AKT and mTOR) to BC outcomes, we have developed a novel in silico approach which assessed the activation of each of these signalling pathways separately. Methods: By analysing gene expression and matched proteomic data in ER-positive patients from the TCGA repository, we developed gene signatures that reflect the level of expression of phosphorylated-Serine473-AKT (pAKT) and phosphorylated-Serine2448-mTOR (p-mTOR) separately, capturing their corresponding level of pathway activation. Using pooled analysis of gene-expression data from over 7,000 patients with ER-positive early BC, we then investigated the association between pathway activation and outcomes. Results: Our analysis revealed that the pAKT pathway activation (as measured by the developed signature) was associated with luminal A BC while the p-mTOR pathway activation was more associated with luminal B BC (Kruskal-Wallis test p<10-10). pAKT pathway activation was significantly associated with better outcomes (multivariable HR, 0.79; 95% CI, 0.74 to 0.85; p=2.5x10-10) whereas p-mTOR pathway activation showed worse outcomes (multivariable HR, 1.1; 95% CI, 1.1 to 1.2; p=9.9x10-4). Similar associations between activation and outcomes were obtained when the analysis was performed in patients who were treated with hormonal therapy. Additionally, pAKT pathway activation predicted better outcomes irrespective of the BC molecular subtypes (luminal A multivariable HR, 0.85; 95% CI, 0.75 to 0.96; p=0.01; luminal B HR, 0.91; 95% CI, 0.83 to 0.99; p=0.033). pAKT pathway activation was associated with PIK3CA mutations (p=0.0001) while p-mTOR pathway activation was associated with p53 mutations (p=0.04). Finally, we show that pAKT pathway activation was associated with less response to Everolimus. Conclusions: Our data show that pAKT and p-mTOR pathway activation have differing impact on prognosis and suggest that they are not linearly connected in luminal breast cancers. These findings add to our understanding of signalling through the PI3K pathway and could have important implications for the treatment of luminal BC.
2018-12-14 | GSE123831 | GEO
Project description:Since 2018, adolescents have been included as a target group for tuberculosis (TB) surveillance by the WHO. However, they are considered a neglected population, as there are considerable gaps in information about them. We aimed to analyze the risk factors for unfavorable TB treatment outcomes among adolescents in Rio de Janeiro, a Brazilian city with a high burden of TB. This is a retrospective study of adolescents (10-18 years) with TB notified in Rio de Janeiro, from four national database systems, covering 2014-2016. "Extreme vulnerability" was defined as adolescents who presented one of the following characteristics: homelessness, incarceration, tobacco use, illicit drug use, or alcohol abuse. Logistic regression analysis was used to identify factors associated with favorable (cure/completed treatment) and unfavorable outcomes (lost to follow-up, death, and treatment failure). A total of 725 adolescents with TB were included: 610 (84.1%) were cured, 94 (13%) were lost to follow-up, six (0.8%) died because of TB, 13 (1.8%) died because of other causes, and two (0.3%) failed treatment. Unfavorable outcomes were associated with retreatment (adjusted odds ratio [aOR]: 4.51; 95% CI: 2.23-9.17), TB-HIV coinfection (aOR: 10.15; 95% CI: 4.15-25.34), extreme vulnerability (aOR: 3.01; 95% CI: 1.70-5.33), and living in the two districts (3.1 and 3.3) with worst conditions: large population and rates of homicides and shantytowns (aOR: 4.11; 95% CI: 1.79-9.46 and aOR: 5.35; 95% CI: 2.20-13.03, respectively). Our findings underscore the need for strengthening early identification and interventions for adolescents at high risk of unfavorable outcomes, especially those living in shantytowns.
| S-EPMC7695073 | biostudies-literature
Project description:BACKGROUND:Since 1981, we have used the term metabolic syndrome to describe an association of a dysregulation in lipid metabolism (high triglycerides, low high-density lipoprotein cholesterol, disturbed glucose homeostasis (enhanced fasting and/or prandial glucose), gout, and hypertension), with android obesity being based on a common soil (overnutrition, reduced physical activity, sociocultural factors, and genetic predisposition). We hypothesized that main traits of the syndrome occur early and are tightly connected with hyperinsulinemia/insulin resistance, procoagulation, and cardiovascular diseases. METHODS:To establish a close link between the traits of the metabolic vascular syndrome, we focused our literature search on recent original work and comprehensive reviews dealing with the topics metabolic syndrome, visceral obesity, fatty liver, fat tissue inflammation, insulin resistance, atherogenic dyslipidemia, arterial hypertension, and type 2 diabetes mellitus. RESULTS:Recent research supports the concept that the metabolic vascular syndrome is a multidimensional and interactive network of risk factors and diseases based on individual genetic susceptibility and epigenetic changes where metabolic dysregulation/metabolic inflexibility in different organs and vascular dysfunction are early interconnected. CONCLUSION:The metabolic vascular syndrome is not only a risk factor constellation but rather a life-long abnormality of a closely connected interactive cluster of developing diseases which escalate each other and should continuously attract the attention of every clinician.
| S-EPMC5122997 | biostudies-literature
Project description:Differences in susceptibility to immune-mediated diseases are determined by variability in immune responses. In three studies within the Human Functional Genomics Project, we assessed the effect of environmental and non-genetic host factors of the genetic make-up of the host and of the intestinal microbiome on the cytokine responses in humans. We analyzed the association of these factors with circulating mediators and with six cytokines after stimulation with 19 bacterial, fungal, viral, and non-microbial metabolic stimuli in 534 healthy subjects. In this first study, we show a strong impact of non-genetic host factors (e.g., age and gender) on cytokine production and circulating mediators. Additionally, annual seasonality is found to be an important environmental factor influencing cytokine production. Alpha-1-antitrypsin concentrations partially mediate the seasonality of cytokine responses, whereas the effect of vitamin D levels is limited. The complete dataset has been made publicly available as a comprehensive resource for future studies. PAPERCLIP.
| S-EPMC5787854 | biostudies-literature