Dataset Information

Effectiveness of imaging genetics analysis to explain degree of depression in Parkinson's disease.

ABSTRACT: Depression is one of the most common and important neuropsychiatric symptoms in Parkinson's disease and often becomes worse as Parkinson's disease progresses. However, the underlying mechanisms of depression in Parkinson's disease are not clear. The aim of our study was to find genetic features related to depression in Parkinson's disease using an imaging genetics approach and to construct an analytical model for predicting the degree of depression in Parkinson's disease. The neuroimaging and genotyping data were obtained from an openly accessible database. We computed imaging features through connectivity analysis derived from tractography of diffusion tensor imaging. The imaging features were used as intermediate phenotypes to identify genetic variants according to the imaging genetics approach. We then constructed a linear regression model using the genetic features from imaging genetics approach to describe clinical scores indicating the degree of depression. As a comparison, we constructed other models using imaging features and genetic features based on references to demonstrate the effectiveness of our imaging genetics model. The models were trained and tested in a five-fold cross-validation. The imaging genetics approach identified several brain regions and genes known to be involved in depression, with the potential to be used as meaningful biomarkers. Our proposed model using imaging genetic features predicted and explained the degree of depression in Parkinson's disease appropriately (adjusted R2 larger than 0.6 over five training folds) and with a lower error and higher correlation than with other models over five test folds.

SUBMITTER: Won JH

PROVIDER: S-EPMC6370199 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Effectiveness of imaging genetics analysis to explain degree of depression in Parkinson's disease.

Won Ji Hye JH Kim Mansu M Park Bo-Yong BY Youn Jinyoung J Park Hyunjin H

PloS one 20190211 2

Depression is one of the most common and important neuropsychiatric symptoms in Parkinson's disease and often becomes worse as Parkinson's disease progresses. However, the underlying mechanisms of depression in Parkinson's disease are not clear. The aim of our study was to find genetic features related to depression in Parkinson's disease using an imaging genetics approach and to construct an analytical model for predicting the degree of depression in Parkinson's disease. The neuroimaging and ge ...[more]

PMID: 30742647

Similar Datasets

Project description:Imaging genetics studies involving participants with major depressive disorder (MDD) have expanded. Nevertheless, findings have been inconsistent. Thus, we conducted a systematic review and meta-analysis of imaging genetics studies that enrolled MDD participants across major databases through June 30th, 2017. Sixty-five studies met eligibility criteria (N = 4034 MDD participants and 3293 controls), and there was substantial between-study variability in the methodological quality of included studies. However, few replicated findings emerged from this literature with only 22 studies providing data for meta-analyses (882 participants with MDD and 616 controls). Total hippocampal volumes did not significantly vary in MDD participants or controls carrying either the BDNF Val66Met 'Met' (386 participants with MDD and 376 controls) or the 5-HTTLPR short 'S' (310 participants with MDD and 230 controls) risk alleles compared to non-carriers. Heterogeneity across studies was explored through meta-regression and subgroup analyses. Gender distribution, the use of medications, segmentation methods used to measure the hippocampus, and age emerged as potential sources of heterogeneity across studies that assessed the association of 5-HTTLPR short 'S' alleles and hippocampal volumes. Our data also suggest that the methodological quality of included studies, publication year, and the inclusion of brain volume as a covariate contributed to the heterogeneity of studies that assessed the association of the BDNF Val66Met 'Met' risk allele and hippocampal volumes. In exploratory voxel-wise meta-analyses, MDD participants carrying the 5-HTTLPR short 'S' allele had white matter microstructural abnormalities predominantly in the corpus callosum, while carriers of the BDNF Val66Met 'Met' allele had larger gray matter volumes and hyperactivation of the right middle frontal gyrus compared to non-carriers. In conclusion, few replicated findings emerged from imaging genetics studies that included participants with MDD. Nevertheless, we explored and identified specific sources of heterogeneity across studies, which could provide insights to enhance the reproducibility of this emerging field.

Project description:AimIn this paper we aimed to systematically review the literature on physical activity's effect on depressive symptoms in Parkinson disease.BackgroundDepression is a common symptom of Parkinson's disease and is associated with increased disability, rapid progression of motor symptoms, mortality, and adverse effects on Quality of Life.DesignA systematic review of primary research was undertaken and conducted according to the Preferred Reporting Items for Systematic Reviews.Data sourcesDatabases Scopus, Psycho-info, CINAHL, PubMed, and ProQuest Cochrance were searched from January 2006 to June 2017. The language was restricted to English.Review methodsAbstracts were screened and reviewed against the eligibility criteria (participants' mean age were ? 60 with PD, PA interventions, depression as one of outcome variables, and Randomized Control Trail or quasi-experimental design). Two reviewers appraised the quality of the data extracted. The modified Jadad scale assessed the quality of the methodology of the published papers.ResultsThe database search yielded 769 abstracts, 11 of which were included in this review and awarded scores ranging from 3 to 8 (Scale scores range from 0 to 8 points, higher scores indicated better quality) by the raters. These 11 studies included 342 patients and executed 17 kinds of physical activity programs. Results of this review show empirical evidence to support the efficacy of physical activity for the population with Parkinson's disease. Aerobic training exercise significantly improved the participants' scores on the Unified Parkinson's Disease Rating Scale, the Beck Depression Inventory, and the Quality of Life of the patients. Qigong improved scores in UPDRS-III and decreased incidences of multiple non-motor symptoms and depression. Furthermore, a balance-training program, such as Tai Chi, can improve postural stability and Quality of Life.ConclusionsPhysical activity may assuage the degeneration of motor skills and depression as well as increase the Quality of Life of Parkinson's disease patients, with aerobic training producing the best results. These findings suggest that physical activity, notably aerobic training, could be a good exercise strategy for patients with Parkinson's disease.

Project description:Depressive disorders (DDs) are one of the most widespread forms of psychiatric pathology. According to the World Health Organization, about 350 million people in the world are affected by this condition. Family and twin studies have demonstrated that the contribution of genetic factors to the risk of the onset of DDs is quite large. Various methodological approaches (analysis of candidate genes, genome-wide association analysis, genome-wide sequencing) have been used, and a large number of the associations between genes and different clinical DD variants and DD subphenotypes have been published. However, in most cases, these associations have not been confirmed in replication studies, and only a small number of genes have been proven to be associated with DD development risk. To ascertain the role of genetic factors in DD pathogenesis, further investigations of the relevant conditions are required. Special consideration should be given to the polygenic characteristics noted in whole-genome studies of the heritability of the disorder without a pronounced effect of the major gene. These observations accentuate the relevance of the analysis of gene-interaction roles in DD development and progression. It is important that association studies of the inherited variants of the genome should be supported by analysis of dynamic changes during DD progression. Epigenetic changes that cause modifications of a gene's functional state without changing its coding sequence are of primary interest. However, the opportunities for studying changes in the epigenome, transcriptome, and proteome during DD are limited by the nature of the disease and the need for brain tissue analysis, which is possible only postmortem. Therefore, any association studies between DD pathogenesis and epigenetic factors must be supplemented through the use of different animal models of depression. A threefold approach comprising the combination of gene association studies, assessment of the epigenetic state in DD patients, and analysis of different "omic" changes in animal depression models will make it possible to evaluate the contribution of genetic, epigenetic, and environmental factors to the development of different forms of depression and to help develop ways to decrease the risk of depression and improve the treatment of DD.

Project description:In Parkinson's disease, a precursor phenomenon to visual hallucinations presents as 'pareidolias' which make ambiguous forms appear meaningful. To evoke and detect pareidolias in patients, a noise pareidolia test was recently developed, although its task-dependent mechanisms are yet to be revealed. When subjected to this test, we hypothesized that patients exhibiting pareidolias would show altered top-down influence of visual processing allowing us to demonstrate the influence of pareidolic illusionary behaviour in Parkinson's disease patients. To that end, we evaluated eye-movement strategies and fixation-related presaccadic activity on scalp EEG when participants performed the test. Twelve healthy controls and 21 Parkinson's disease patients, evaluated for cognitive, visuo-spatial and executive functions, took a modified computer-based version of the noise pareidolia test in a free-viewing EEG eye-tracking experiment. Eye-tracking metrics (fixation-related durations and counts) documented the eye movement behaviour employed in correct responses (face/noise) and misperceptions (pareidolia/missed) during early and late visual search conditions. Simultaneously, EEG recorded the presaccadic activity in frontal and parietal areas of the brain. Based on the noise pareidolia test scores, we found certain Parkinson's disease patients exhibited pareidolias whereas others did not. ANOVA on eye-tracking data showed that patients dwelled significantly longer to detect faces and pareidolias which affected both global and local search dynamics depending on their visuo-perceptual status. Presaccadic activity in parietal electrodes for the groups was positive for faces and pareidolias, and negative for noise, though these results depended mainly on saccade size. However, patients sensitive to pareidolias showed a significantly higher presaccadic potential on frontal electrodes independent of saccade sizes, suggesting a stronger frontal activation for pareidolic stimuli. We concluded with the following interpretations (i) the noise pareidolia test specifically characterizes visuo-perceptual inadequacies in patients despite their wide range of cognitive scores, (ii) Parkinson's disease patients dwell longer to converge attention to pareidolic stimuli due to abnormal saccade generation proportional to their visuo-perceptual deficit during early search, and during late search, due to time-independent alteration of visual attentional network and (iii) patients with pareidolias show increased frontal activation reflecting the allocation of attention to irrelevant targets that express the pareidolic phenomenon. While the disease per se alters the visuo-perceptual and oculomotor dynamics, pareidolias occur in Parkinson's disease due to an abnormal top-down modulation of visual processing that affects visual attention and guidance to ambiguous stimuli.

Dataset Information

Effectiveness of imaging genetics analysis to explain degree of depression in Parkinson's disease.

Publications

Effectiveness of imaging genetics analysis to explain degree of depression in Parkinson's disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets