scholarly journals Multidimensional Analysis of Major Depression: Association Between BDNF Methylation, Psychosocial and Cognitive Domains

2021 ◽  
Vol 12 ◽  
Author(s):  
María Marcela Velásquez ◽  
Yvonne Gómez-Maquet ◽  
Eugenio Ferro ◽  
Wilmer Cárdenas ◽  
Silvia González-Nieves ◽  
...  
Keyword(s):  
Major Depression ◽  
Childhood Maltreatment ◽  
Single Gene ◽  
Multivariate Logistic Regression Analysis ◽  
Mediating Effect ◽  
Multidimensional Analysis ◽  
Diagnostic Tools ◽  
Cognitive Schemas ◽  
Cpg Site ◽  
Multiple Variables

Major Depression is a complex disorder with a growing incidence worldwide and multiple variables have been associated with its etiology. Nonetheless, its diagnosis is continually changing and the need to understand it from a multidimensional perspective is clear. The purpose of this study was to identify risk factors for depression in a case-control study with 100 depressive inpatients and 87 healthy controls. A multivariate logistic regression analysis was performed including psychosocial factors, cognitive maladaptive schema domains, and specific epigenetic marks (BDNF methylation levels at five CpG sites in promoter IV). A family history of depression, the cognitive schemas of impaired autonomy/performance, impaired limits, other-directedness, and the methylation level of a specific CpG site were identified as predictors. Interestingly, we found a mediating effect of those cognitive schemas in the relationship between childhood maltreatment and depression. Also, we found that depressive patients exhibited hypomethylation in a CpG site of BDNF promoter IV, which adds to the current discussion about the role of methylation in depression. We highlight that determining the methylation of a specific region of a single gene offers the possibility of accessing a highly informative an easily measurable variable, which represents benefits for diagnosis. Following complete replication and validation on larger samples, models like ours could be applicable as additional diagnostic tools in the clinical context.

Partner violence in women - Associations with childhood maltreatment, attachment style and Major Depression

2019 ◽  
pp. 13-28
Author(s):  
Antonia Bifulco ◽  
Rachele Damiani ◽  
Catherine Jacobs ◽  
Amanda Bunn ◽  
Ruth Spence
Keyword(s):  
Major Depression ◽  
Attachment Style ◽  
Childhood Maltreatment ◽  
Partner Violence

scholarly journals Diffusion Tensor Imaging Along the Perivascular Space Index in Different Stages of Parkinson’s Disease

2021 ◽  
Vol 13 ◽  
Author(s):  
Xinxin Ma ◽  
Shuhua Li ◽  
Chunmei Li ◽  
Rui Wang ◽  
Min Chen ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Diffusion Tensor ◽  
Multivariate Logistic Regression Analysis ◽  
Perivascular Space ◽  
Periventricular White Matter ◽  
Perivascular Spaces ◽  
Glymphatic System ◽  
Multiple Variables ◽  
Association Fibers

Background: The aim of this study was to evaluate the glymphatic system activity in patients with Parkinson’s disease (PD) using the diffusion tensor image analysis along the perivascular space (DTI-ALPS) methods.Methods: In total, 71 patients with idiopathic PD and 36 age- and sex-matched normal controls (NCs) were involved. Patients with PD were divided into early (n = 35) and late (n = 36) subgroups, based on Hoehn and Yahr (HY) stages. We calculated the diffusivity along the perivascular spaces (ALPS), as well as projection fibers and association fibers separately, to acquire the ALPS index. Enlarged perivascular spaces (EPVS) and periventricular white matter hyperintensities were also rated. Differences in ALPS index between the PD group and NCs and between two PD subgroups and NCs were compared. In addition, a multivariate logistic regression analysis was conducted to investigate the association between ALPS index and clinical variables.Results: Patients with PD revealed lower ALPS index than NCs (p = 0.010). The late PD group exhibited significantly lower ALPS index than NCs (p = 0.006). However, there were no marked differences noticed in ALPS index between NCs and early PD group and between the two PD subgroups. In the early PD group, there was a significantly positive correlation between ALPS index and Mini-Mental State Examination (MMSE) score (β = 0.021, p = 0.029) and a negative correlation between ALPS index and EPVS score (β = −0.050, p = 0.034), after controlling for multiple variables. In the late PD group, ALPS index was inversely associated with age (β = −0.012, p = 0.004).Conclusion: Impairment of the glymphatic system is involved in PD. DTI-ALPS index could be a promising biomarker of glymphatic system in PD.

scholarly journals Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

2020 ◽  
Vol 21 (17) ◽  
pp. 6274
Author(s):  
Maria Vittoria Ristori ◽  
Stefano Levi Mortera ◽  
Valeria Marzano ◽  
Silvia Guerrera ◽  
Pamela Vernocchi ◽  
...  
Keyword(s):  
Autism Spectrum Disorders ◽  
Biomarker Discovery ◽  
Chromosomal Abnormalities ◽  
Single Gene ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Autism Spectrum ◽  
Added Value ◽  
Diagnostic Tools ◽  
Spectrum Disorders

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

Modifiable factors that influence colorectal cancer lymph nodes sampling and examination

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 4047-4047
Author(s):  
M. E. Valsecchi ◽  
J. Leighton ◽  
W. Tester
Keyword(s):  
Colorectal Cancer ◽  
Logistic Regression ◽  
Lymph Nodes ◽  
Medical Center ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
The United States ◽  
Routine Practice ◽  
Modifiable Factors ◽  
Multiple Variables

4047 Background: Colorectal cancer is the fourth most common malignancy in the United States. The single most important prognostic factor is lymph node involvement. Multiple guidelines recommend a minimum of 12 nodes should be sampled in order to insure accurate staging and treatment. However this standard of care requirement is not always achieved. The objective of this study is to identify potential modifiable factors that may explain this inadequacy between the optimal approach and routine practice. Methods: The medical charts of all patients treated for colorectal cancer stage I-III between 1999–2007 at Albert Einstein Medical Center were reviewed. The association between multiple variables and the presence of ≥12 lymph nodes reported were examined using logistic regression models. Results: A total of 337 patients were included; 173 (51%) had ≥12 lymph nodes retrieved with a mean of 12.7 (SD±7.6). Demographic characteristics: 78% older than 60 years old; 161 patients (47.8%) male; white (27%), black (67%) and other race (6%). Using a univariate analysis the following variables were statistically associated with ≥12 lymph nodes reported: Colon size (20.6±14.7 vs. 29.9±23.1 cm, P<.001); Mesocolon thickness (3.8±0.9 vs. 4.2±0.9 cm, P<.001); Tumor size (4.14±2.3 vs. 4.6±2.1, P=.03); Site of tumor (Right vs. Left, P<.001); Pathologist (P=.06); Pathologist's Assistant (P=.006); Type of surgery (Right or Sub-Total Colectomy vs. Others, P<.001), Individual Surgeon (P=.009). The results of the multivariate logistic regression analysis, adjusting for age, sex and race, are presented in the Table . Conclusions: This studied showed that multiple factors influence the number of lymph nodes sampled. The role of the surgeon, the pathologist and specially the pathologist's assistant are potentially improvable factors with appropriate education. [Table: see text] No significant financial relationships to disclose.

415. Childhood Maltreatment, Major Depression and the Dorsal Nexus

2017 ◽  
Vol 81 (10) ◽  
pp. S169
Author(s):  
Martin Teicher ◽  
Carl Anderson ◽  
Alaptagin Khan ◽  
Cynthia McGreenery ◽  
Elizabeth Bolger ◽  
...  
Keyword(s):  
Major Depression ◽  
Childhood Maltreatment

scholarly journals Progressively increased patterns of subclinical cortisol hypersecretion in adrenal incidentalomas differently predict major metabolic and cardiovascular outcomes: a large cross-sectional study

2012 ◽  
Vol 166 (4) ◽  
pp. 669-677 ◽  
Author(s):  
Guido Di Dalmazi ◽  
Valentina Vicennati ◽  
Eleonora Rinaldi ◽  
Antonio Maria Morselli-Labate ◽  
Emanuela Giampalma ◽  
...  
Keyword(s):  
Risk Factors ◽  
Potential Risk ◽  
Multivariate Logistic Regression Analysis ◽  
Cardiovascular Outcomes ◽  
Intermediate Phenotype ◽  
Diagnostic Tools ◽  
Subclinical Hypercortisolism ◽  
Intermediate Phenotypes ◽  
Free Cortisol ◽  
Potential Risk Factors

BackgroundSubclinical Cushing's syndrome (SCS) is defined as alterations in hypothalamic–pituitary–adrenal axis without classic signs/symptoms of glucocorticoid excess. Whether SCS leads to metabolic and cardiovascular diseases is still controversial.AimTo evaluate the prevalence of hypertension, type 2 diabetes (T2D), coronary heart disease (CHD), ischemic stroke, osteoporosis, and fractures, and their relationship to increasing patterns of subclinical hypercortisolism, in patients with nonsecreting adrenal adenomas (NSA) and SCS.MethodsUsing the 1 mg dexamethasone suppression test (DST), 348 patients were classified as follows: 203 were defined as NSA and 19 SCS, using the most stringent cutoff values (<50 and >138 nmol/l respectively). Patients with cortisol post-DST (50–138 nmol/l) were considered as intermediate phenotypes and classified as minor (n=71) and major (n=55) using plasma ACTH and/or urinary free cortisol as additional diagnostic tools.ResultsSCS patients showed higher prevalence of T2D, CHD, osteoporosis, and fractures with respect to NSA. Intermediate phenotypes also showed higher prevalence of CHD and T2D with respect to NSA. The prevalence of all clinical outcomes was not different between intermediate phenotype patients, which were therefore considered as a single group (IP) for multivariate logistic regression analysis: both IP and SCS-secreting patterns showed a significant association with CHD (odds ratio (OR), 4.09; 95% confidence interval (CI), 1.47–11.38 and OR, 6.10; 95% CI, 1.41–26.49 respectively), independently of other potential risk factors. SCS was also independently associated with osteoporosis (OR, 5.94; 95% CI, 1.79–19.68).ConclusionsPatterns of increasing subclinical hypercortisolism in adrenal adenomas are associated with increased prevalence of adverse metabolic and cardiovascular outcomes, independently of other potential risk factors.

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