Hasil untuk "Neurosciences. Biological psychiatry. Neuropsychiatry"

Apoorva Mathur, Vanessa Regina Miranda, Ariane Nunes-Alves

While experiments and computer simulations to study biological phenomena are usually performed in diluted in vitro conditions, such phenomena happen inside the cellular cytoplasm, an environment densely packed with diverse macromolecules. Here, we revise recent computational methods to investigate crowded and cellular environments. Protein crowders, inert crowders and small molecules were used to mimic crowding. Simulations were performed for models of the cytoplasm. New methods were developed to simulate crowded systems. Apart from the challenges, modeling and simulations to investigate biological phenomena inside cells is a growing field, and has a lot of potential to improve our understanding of how such phenomena happen in vivo.

Aida de la Cruz-Gambra, Aida de la Cruz-Gambra, Jimena Baleriola et al.

The synaptic proteome can be shaped by proteins transported from the neuronal soma and/or by mRNAs that are delivered to synapses where proteins are locally synthesized. This last mechanism is known as local translation. Local translation has been extensively studied in neurons in physiological conditions and, more recently, in neurological disorders, in which local transcriptomes and translatomes become dysregulated. It is widely believed that in neurons, the main source of localized transcripts is the neuronal soma and that localized translation is primarily regulated by the neuron itself. However, we wondered whether glial cells, especially astrocytes, could contribute to the modulation of synaptic local protein synthesis. To address this question, we compared levels of proteins produced in synaptic compartments in neuronal and neuron–astrocyte co-cultures using modified Boyden chambers or astrocyte-conditioned medium. We developed a methodology to measure local protein synthesis by puromycin labeling of isolated synaptosomes devoid of somatic input. Our results show that synaptic local translation is enhanced or retained when neurons are cultured in the presence of astrocytes and in response to astrocyte-conditioned medium. Puromycin labeling coupled with proximity ligation identified Rpl26 as one of the proteins whose local synthesis is regulated by astrocyte-secreted factors. Our results thus unravel the contribution of glia to synaptic protein synthesis and point to a previously unexplored extra layer of complexity in the regulation of local translation in neurons.

Romain Reboux, Silvia Napuri

Abstract Dravet syndrome (DS) is a rare and severe form of epilepsy, characterised by recurrent seizures that begin during the first year of life, leading to motor, cognitive and behavioural impairments. This article provides the perspectives of a parent of a child with DS (‘Ethan’) and the treating neuropaediatrician. Ethan’s seizures began when he was 9 months old, and were a mixture of focal seizures and status epilepticus. Numerous treatments were tried, including standard anti-seizure medications (such as levetiracetam, clobazam and fenfluramine), other medications (cannabidiol) and nonpharmacological approaches (ketogenic diet), with little success. When Ethan was 3 years old, a prolonged episode of status epilepticus precipitated by coronavirus disease 2019 (COVID-19) led to brain damage. Rehabilitation allowed Ethan to regain some of his previous functioning and, at the age of 38 months, combination therapy with clobazam, sodium valproate and stiripentol was begun and has successfully controlled Ethan’s seizures. Ethan’s father describes the stress that the diagnosis of DS, interactions with the healthcare system, and the search for effective treatment imposed on the family. Since Ethan’s seizures have been better controlled, the family has been able to lead a more normal life, and is now focused on supporting Ethan and looking to the future. Ethan’s neuropaediatrician outlines the approach she takes to the diagnosis and management of DS, including the importance of the clinician–parent relationship in imparting the diagnosis and making initial and ongoing treatment decisions. The preferred first-line treatment is sodium valproate, which is followed by sodium valproate–clobazam–stiripentol combination therapy, topiramate or a ketogenic diet as second-line options. In children > 2 years, cannabidiol and fenfluramine can also be considered. The aim of maintenance treatment (which will invariably be polytherapy) is to reduce the number of seizures, particularly status epilepticus, given the significant impact of this seizure type on patients and caregivers.

Boyang Su, Zhengqing He, Luyao Shi et al.

Abstract Background Myasthenia gravis (MG) is an autoimmune disorder of the neuromuscular junction. Increasing evidence has suggested inflammation is involved in the pathogenesis of MG, but whether it is the cause or a downstream effect remains unclear. In this study, a two-sample Mendelian randomization (TSMR) analysis was performed to explore the causal relationship between 91 circulating inflammatory cytokines and MG. Method In this study, the data of 91 circulating inflammatory cytokines from 4824 Europeans and the largest GWAS database of MG (1873 patients and 36370 controls) were used to screen instrumental variables (IVs). Inverse variance weighting (IVW), Bayesian weighted MR (BWMR), MR-Egger regression, weighted median (WM), simple mode and weighted mode were used to evaluate the association between MG and inflammatory cytokines. The MR-Egger intercept test and Cochran’s Q test were used to test the pleiotropy and heterogeneity of IVs. Result Our results showed that adenosine deaminase (ADA) and CD40 Ligand‌ (CD40L) are positively associated with the risk of MG (OR = 1.16, 95%CI: 1.00-1.33, P = 0.041; OR = 1.20, 95%CI: 1.02–1.40, P = 0.025), while interleukin-1-alpha (IL-1α), glial-cell-line-derived neurotrophic factor (GDNF), Osteoprotegerin (OPG) and tumor necrosis factor-beta (TNF-β) are negatively associated with the risk of MG (OR = 0.80, 95% CI: 0.64 ~ 0.99, P = 0.042; OR = 0.74, 95%CI:0.58 ~ 0.0.96, P = 0.022; OR = 0.76, 95% CI: 0.61 ~ 0.94, P = 0.013; OR = 0.76, 95% CI: 0.61 ~ 0.94, P = 0.012; OR = 0.80, 95% CI: 0.68 ~ 0.93, P = 0.006). In addition, genetically predicted MG affected the expression of seven cytokines. Sensitivity analysis showed no horizontal pleiotropy and significant heterogeneity of all results. Conclusions Our results provided promising clues for the treatment of MG. We evaluated the association between inflammatory cytokines and the disease by genetic informatics approach, which may help to better understand the underlying mechanisms of MG.

Isabella Caranzano, Corrado Pancotti, Cesare Rollo et al.

Biologically-informed neural networks typically leverage pathway annotations to enhance performance in biomedical applications. We hypothesized that the benefits of pathway integration does not arise from its biological relevance, but rather from the sparsity it introduces. We conducted a comprehensive analysis of all relevant pathway-based neural network models for predictive tasks, critically evaluating each study's contributions. From this review, we curated a subset of methods for which the source code was publicly available. The comparison of the biologically informed state-of-the-art deep learning models and their randomized counterparts showed that models based on randomized information performed equally well as biologically informed ones across different metrics and datasets. Notably, in 3 out of the 15 analyzed models, the randomized versions even outperformed their biologically informed counterparts. Moreover, pathway-informed models did not show any clear advantage in interpretability, as randomized models were still able to identify relevant disease biomarkers despite lacking explicit pathway information. Our findings suggest that pathway annotations may be too noisy or inadequately explored by current methods. Therefore, we propose a methodology that can be applied to different domains and can serve as a robust benchmark for systematically comparing novel pathway-informed models against their randomized counterparts. This approach enables researchers to rigorously determine whether observed performance improvements can be attributed to biological insights.

Xiangzheng Cheng, Haili Huang, Ye Su et al.

In multicellular organisms, cells coordinate their activities through cell-cell communication (CCC), which is crucial for development, tissue homeostasis, and disease progression. Recent advances in single-cell and spatial omics technologies provide unprecedented opportunities to systematically infer and analyze CCC from these omics data, either by integrating prior knowledge of ligand-receptor interactions (LRIs) or through de novo approaches. A variety of computational methods have been developed, focusing on methodological innovations, accurate modeling of complex signaling mechanisms, and investigation of broader biological questions. These advances have greatly enhanced our ability to analyze CCC and generate biological hypotheses. Here, we introduce the biological mechanisms and modeling strategies of CCC, and provide a focused overview of more than 140 computational methods for inferring CCC from single-cell and spatial transcriptomic data, emphasizing the diversity in methodological frameworks and biological questions. Finally, we discuss the current challenges and future opportunities in this rapidly evolving field, and summarize available methods in an interactive online resource (https://cellchat.whu.edu.cn) to facilitate more efficient method comparison and selection.

Siqing Chen, He Xua, Xueyu Zhang et al.

This paper proposes a biomimetic design framework based on biological strategy inversion, aiming to systematically map solutions evolved in nature to the engineering field. By constructing a "Function-Behavior-Feature-Environment" (F-B-Cs in E) knowledge model, combined with natural language processing (NLP) and multi-criteria decision-making methods, it achieves efficient conversion from biological strategies to engineering solutions. Using underwater soft robot design as a case study, the effectiveness of the framework in optimizing drive mechanisms, power distribution, and motion pattern design is verified. This research provides scalable methodological support for interdisciplinary biomimetic innovation.

Xiang Ji, Qiwei Dong, Zhanxu Liu et al.

Brain lateralization is known to enhance cognitive efficiency by reducing redundant processing. Theories such as HAROLD and CRUNCH propose that cognitive decline with age can be compensated by the recruitment of additional bilateral brain regions. However, cognitive compensation is not always effective, and the underlying mechanisms remain unclear, particularly those not related to aging. Low-frequency oscillation (LFO) may be a potential factor in this process. This study investigated the relationship between LFO and cognitive compensation in the prefrontal cortex (PFC) of 28 young adults during a visual verbal working memory task, utilizing functional near-infrared spectroscopy (fNIRS). The participants were categorized into high- and low-performance groups. Changes in oxygenated hemoglobin (Δ[oxy-Hb]), deoxygenated hemoglobin (Δ[deoxy-Hb]), and total hemoglobin (Δ[tot-Hb]) were measured. Both groups exhibited reduced lateralization and increased PFC activation under cognitive load. The results show that only the high-performance group displayed enhanced Δ[oxy-Hb] LFO power, which correlated with behavioral performance. In conclusion, this study found that insufficient LFO is associated with a lack of cognitive resources, which may be due to a deficiency in cerebral autoregulation (CA). This deficiency results in an absence of low-frequency rhythms during cognitive processes, hindering effective coordination between distant brain regions. This provides new insights into the non-aging-related cognitive compensation mechanism.

Elias Paolo Casula, Maria Concetta Pellicciari, Sonia Bonnì et al.

Gan Gao, Fang‐bin Hao, Qian‐Nan Wang et al.

Abstract Introduction This study investigated the effect of indirect revascularization surgery in adult patients with moyamoya disease (MMD) complicated with hyperhomocysteinemia (HHcy), and the effect of HHcy on the progression of adult MMD. Methods A retrospective case‐control study was conducted in patients with MMD, with or without HHcy (n = 123). Postoperative collateral angiogenesis was evaluated using the Matsushima grading system and disease progression using the Suzuki staging system. Cerebral blood flow was evaluated before and after surgery using dynamic susceptibility contrast magnetic resonance imaging (DSC‐MRI) and neurological function prognosis using the improved Rankin score (mRS). Univariate and multivariate logistic regression analyses were performed to determine risk factors for the clinical outcomes. Results There was no significant difference in the Suzuki stage composition ratios between the HHcy group and the non‐HHcy group before and after surgery. Non‐HHcy patients were more likely to grow new collateral circulating vessels after encephaloduroarteriosynangiosis (EDAS). Moreover, postoperative DSC‐MRI indicated that the time to peak significantly improved. Conclusions HHcy level may be a specific predictor of adverse clinical outcomes after EDAS in patients with MMD and a risk factor for poor collateral circulation and poor prognosis. Patients with MMD complicated with HHcy need to strictly control homocysteine levels before EDAS surgery.

A. L. Wenger, A. L. Wenger, A. L. Wenger et al.

IntroductionThe presence of focal cortical and white matter damage in patients with multiple sclerosis (pwMS) might lead to specific alterations in brain networks that are associated with cognitive impairment. We applied microstructure-weighted connectomes to investigate (i) the relationship between global network metrics and information processing speed in pwMS, and (ii) whether the disruption provoked by focal lesions on global network metrics is associated to patients’ information processing speed.Materials and methodsSixty-eight pwMS and 92 healthy controls (HC) underwent neuropsychological examination and 3T brain MRI including multishell diffusion (dMRI), 3D FLAIR, and MP2RAGE. Whole-brain deterministic tractography and connectometry were performed on dMRI. Connectomes were obtained using the Spherical Mean Technique and were weighted for the intracellular fraction. We identified white matter lesions and cortical lesions on 3D FLAIR and MP2RAGE images, respectively. PwMS were subdivided into cognitively preserved (CPMS) and cognitively impaired (CIMS) using the Symbol Digit Modalities Test (SDMT) z-score at cut-off value of −1.5 standard deviations. Statistical analyses were performed using robust linear models with age, gender, and years of education as covariates, followed by correction for multiple testing.ResultsOut of 68 pwMS, 18 were CIMS and 50 were CPMS. We found significant changes in all global network metrics in pwMS vs HC (p < 0.05), except for modularity. All global network metrics were positively correlated with SDMT, except for modularity which showed an inverse correlation. Cortical, leukocortical, and periventricular lesion volumes significantly influenced the relationship between (i) network density and information processing speed and (ii) modularity and information processing speed in pwMS. Interestingly, this was not the case, when an exploratory analysis was performed in the subgroup of CIMS patients.DiscussionOur study showed that cortical (especially leukocortical) and periventricular lesions affect the relationship between global network metrics and information processing speed in pwMS. Our data also suggest that in CIMS patients increased focal cortical and periventricular damage does not linearly affect the relationship between network properties and SDMT, suggesting that other mechanisms (e.g. disruption of local networks, loss of compensatory processes) might be responsible for the development of processing speed deficits.

Lauren E. McCollum, Sandhitsu R. Das, Long Xie et al.

Mild cognitive impairment (MCI) can be an early manifestation of Alzheimer’s disease (AD) pathology, other pathologic entities [e.g., cerebrovascular disease, Lewy body disease, LATE (limbic-predominant age-related TDP-43 encephalopathy)], or mixed pathologies, with concomitant AD- and non-AD pathology being particularly common, albeit difficult to identify, in living MCI patients. The National Institute on Aging and Alzheimer’s Association (NIA-AA) A/T/(N) [β-Amyloid/Tau/(Neurodegeneration)] AD research framework, which classifies research participants according to three binary biomarkers [β-amyloid (A+/A-), tau (T+/T-), and neurodegeneration (N+/N-)], provides an indirect means of identifying such cases. Individuals with A+T-(N+) MCI are thought to have both AD pathologic change, given the presence of β-amyloid, and non-AD pathophysiology, given neurodegeneration without tau, because in typical AD it is tau accumulation that is most tightly linked to neuronal injury and cognitive decline. Thus, in A+T-(N+) MCI (hereafter referred to as “mismatch MCI” for the tau-neurodegeneration mismatch), non-AD pathology is hypothesized to drive neurodegeneration and symptoms, because β-amyloid, in the absence of tau, likely reflects a preclinical stage of AD. We compared a group of individuals with mismatch MCI to groups with A+T+(N+) MCI (or “prodromal AD”) and A-T-(N+) MCI (or “neurodegeneration-only MCI”) on cross-sectional and longitudinal cognition and neuroimaging characteristics. β-amyloid and tau status were determined by CSF assays, while neurodegeneration status was based on hippocampal volume on MRI. Overall, mismatch MCI was less “AD-like” than prodromal AD and generally, with some exceptions, more closely resembled the neurodegeneration-only group. At baseline, mismatch MCI had less episodic memory loss compared to prodromal AD. Longitudinally, mismatch MCI declined more slowly than prodromal AD across all included cognitive domains, while mismatch MCI and neurodegeneration-only MCI declined at comparable rates. Prodromal AD had smaller baseline posterior hippocampal volume than mismatch MCI, and whole brain analyses demonstrated cortical thinning that was widespread in prodromal AD but largely restricted to the medial temporal lobes (MTLs) for the mismatch and neurodegeneration-only MCI groups. Longitudinally, mismatch MCI had slower rates of volume loss than prodromal AD throughout the MTLs. Differences in cross-sectional and longitudinal cognitive and neuroimaging measures between mismatch MCI and prodromal AD may reflect disparate underlying pathologic processes, with the mismatch group potentially being driven by non-AD pathologies on a background of largely preclinical AD. These findings suggest that β-amyloid status alone in MCI may not reveal the underlying driver of symptoms with important implications for enrollment in clinical trials and prognosis.

Kate Beecher, Ignatius Alvarez Cooper, Joshua Wang et al.

Sugar has become embedded in modern food and beverages. This has led to overconsumption of sugar in children, adolescents, and adults, with more than 60 countries consuming more than four times (>100 g/person/day) the WHO recommendations (25 g/person/day). Recent evidence suggests that obesity and impulsivity from poor dietary habits leads to further overconsumption of processed food and beverages. The long-term effects on cognitive processes and hyperactivity from sugar overconsumption, beginning at adolescence are not known. Using a well-validated mouse model of sugar consumption, we found that long-term sugar consumption, at a level that significantly augments weight gain, elicits an abnormal hyperlocomotor response to novelty and alters both episodic and spatial memory. Our results are similar to those reported in attention deficit and hyperactivity disorders. The deficits in hippocampal-dependent learning and memory were accompanied by altered hippocampal neurogenesis, with an overall decrease in the proliferation and differentiation of newborn neurons within the dentate gyrus. This suggests that long-term overconsumption of sugar, as that which occurs in the Western Diet might contribute to an increased risk of developing persistent hyperactivity and neurocognitive deficits in adulthood.

Renee M. Hendricks, Mohammad T. Khasawneh

Parkinson’s disease (PD) is the second most common, neurodegenerative disorder. It is a chronic, disabling, and progressive disease, and no treatment stops its progression. Rating scales are utilized to quantify PD progression and severity. The most conventional scale is the Unified Parkinson’s Disease Rating Scale (UPDRS) and its modified version, Movement Disorder Society- (MDS-) UPDRS. An analytical investigation into the use and meaning of these clinical scale scores was conducted to determine if gaps exist in quantifying disease progression and severity. A series of discrepancies were identified including confusion among patients regarding the score meaning and misuse of the scores among clinicians and researchers to define disease progression. The scales are of an ordinal type and hence the resulting scores are ordinal, not providing a quantifiable progression nor severity level, but a categorical value and survey total. The knowledge that the scores are ordinal and the scales are subjective is mentioned in very limited publications, not the focus of these papers, but a brief introduction and a thoroughly researched, analytical investigation into the scales and scores have not been found. Therefore, the continuous misunderstanding and misuse of these scales and resulting scores warrant a comprehensive assessment and evaluation of these scales and scores to identify the gaps.

Endre T. Somogyi, Jeffery Coulter, Fanbo Sun et al.

Modeling and simulation (M&S) has revolutionized the way modern engineered products are designed, tested and evaluated. Yet modeling and simulation is much less frequently applied in the study of natural biological and active matter systems. Two of the greatest challenges in applying M\&S approaches to natural biological systems are (1) difficulty in specifying a model, and developing a simulation from it, and (2) tuning and optimizing parameters. Here we address the first challenge directly, and develop a software library that can lead to progress in the second.

Mia Illman, Kristina Laaksonen, Mia Liljeström et al.

Modulation of the ~20-Hz brain rhythm has been used to evaluate the functional state of the sensorimotor cortex both in healthy subjects and patients, such as stroke patients. The ~20-Hz brain rhythm can be detected by both magnetoencephalography (MEG) and electroencephalography (EEG), but the comparability of these methods has not been evaluated. Here, we compare these two methods in the evaluating of ~20-Hz activity modulation to somatosensory stimuli.Rhythmic ~20-Hz activity during separate tactile and proprioceptive stimulation of the right and left index finger was recorded simultaneously with MEG and EEG in twenty-four healthy participants.Both tactile and proprioceptive stimulus produced a clear suppression at 300–350 ​ms followed by a subsequent rebound at 700–900 ​ms after stimulus onset, detected at similar latencies both with MEG and EEG. The relative amplitudes of suppression and rebound correlated strongly between MEG and EEG recordings. However, the relative strength of suppression and rebound in the contralateral hemisphere (with respect to the stimulated hand) was significantly stronger in MEG than in EEG recordings.Our results indicate that MEG recordings produced signals with higher signal-to-noise ratio than EEG, favoring MEG as an optimal tool for studies evaluating sensorimotor cortical functions. However, the strong correlation between MEG and EEG results encourages the use of EEG when translating studies to clinical practice. The clear advantage of EEG is the availability of the method in hospitals and bed-side measurements at the acute phase.

Miina Koskela, Roshan Chudal, Terhi Luntamo et al.

Abstract Background Selective mutism (SM) is nowadays considered a relatively rare anxiety disorder characterized by children failing to speak in certain situations. Research on risk factors for SM are limited in comparison to other psychiatric disorders. The aim of this study was to examine several potential risk factors for SM in a large nationwide cohort, namely parental psychopathology, parental age, maternal SES, urbanicity, maternal marital status and parental immigration status. Methods This nested case-control study comprised 860 cases with SM, identified from the Finnish Hospital Discharge Register and 3250 controls matched for sex and age from the Finnish Central Population Register. Conditional logistic regression was used to examine the association between the risk factors and SM. Results If both parents had any psychiatric disorder, this almost tripled their odds of having a child with SM (OR 2.8, 95% CI 2.0–4.0). There were increased rates of all types of psychiatric disorders in the parents of the children with SM, with a wider range of diagnoses among the mothers than fathers. Fathers over 35 years (OR 1.4, 95% CI 1.1–1.8) were significantly more likely to have children with SM. Offspring of a single mother had a 2-fold (OR = 2.0, 95% CI 1.4–3.0) increased odds of SM than mothers who were married or in a relationship. Conclusions Several parental psychiatric disorders were associated with offspring SM. This points towards a shared aetiology of psychiatric disorders. Findings on paternal age and single motherhood help to improve our understanding of risk factors for SM.

Jordan D. Dworkin, Kristin A. Linn, Erin G. Teich et al.

Like many scientific disciplines, neuroscience has increasingly attempted to confront pervasive gender imbalances within the field. While much of the conversation has centered around publishing and conference participation, recent research in other fields has called attention to the prevalence of gender bias in citation practices. Because of the downstream effects that citations can have on visibility and career advancement, understanding and eliminating gender bias in citation practices is vital for addressing inequity in a scientific community. In this study, we sought to determine whether there is evidence of gender bias in the citation practices of neuroscientists. Using data from five top neuroscience journals, we find that reference lists tend to include more papers with men as first and last author than would be expected if gender were not a factor in referencing. Importantly, we show that this overcitation of men and undercitation of women is driven largely by the citation practices of men, and is increasing over time as the field becomes more diverse. We develop a co-authorship network to assess homophily in researchers' social networks, and we find that men tend to overcite men even when their social networks are representative. We discuss possible mechanisms and consider how individual researchers might address these findings in their own practices.

Andrew W. E. McDonald, Sean Grimes, David E. Breen

Ortus is a simple virtual organism that also serves as an initial framework for investigating and developing biologically-based artificial intelligence. Born from a goal to create complex virtual intelligence and an initial attempt to model C. elegans, Ortus implements a number of mechanisms observed in organic nervous systems, and attempts to fill in unknowns based upon plausible biological implementations and psychological observations. Implemented mechanisms include excitatory and inhibitory chemical synapses, bidirectional gap junctions, and Hebbian learning with its Stentian extension. We present an initial experiment that showcases Ortus' fundamental principles; specifically, a cyclic respiratory circuit, and emotionally-driven associative learning with respect to an input stimulus. Finally, we discuss the implications and future directions for Ortus and similar systems.

Yuchen Zheng, Francesca Severino, Li Hui et al.

Introduction: It is common that personality disorder (PD) co-occurs with major depressive disorder (MDD). In the current literature, there is a dearth of information on the co-occurrence of PD and MDD among Chinese population.Materials and Methods: 609 individuals were randomly sampled from outpatients diagnosed as MDD in Shanghai Mental Health Center. Co-morbidity of PDs was assessed using the Personality Diagnostic Questionnaire Fourth Edition Plus (PDQ-4+) and eligible subjects were interviewed with the Structured Clinical Interview for DSM-IV Axis II (SCID-II). The score of PDQ-4+ and the rate of SCID-II PD between subjects diagnosed with MDD and those with anxiety disorders (AD) were compared.Results: Two hundred fifty-eight outpatients (42.36%) with MDD were recognized to possess at least one criterion of diagnosis for PD, according to the DSM-IV. The most prevalent PD was depressive PD (14.61%), followed by avoidant (11.49%) and borderline (11.49%) PD. Cluster C PDs (anxious and panic PD) were the most common PD types (12.12%) when compared to other clusters. Compared to patients with AD, individuals with MDD were significantly more likely to have paranoid PD (6.6% vs. 3.3%, p = 0.011), borderline PD (11.5% vs. 3.7%, p = 0.000), passive-aggressive PD (5.6% vs. 2.4%, p = 0.007), and depressive PD (14.6% vs. 7.8%, p = 0.000).Discussion: The finding indicates that there is a high prevalence of PD among patients with MDD. More significant co-morbidity rates of PDs in MDD have been found when compared with AD. Further studies for the longitudinal impact of the PD-MDD co-morbidity are in need.