PLA2G6-associated neurodegeneration is a major subtype of neurodegeneration with brain iron accumulation. Patients with PLA2G6-associated neurodegeneration usually present degenerative motor symptoms with neuropsychiatric disturbance. This report presents a patient with PLA2G6-related dystonia-parkinsonism, who had neuropsychiatric symptoms preceding movement symptoms. Antipsychotic drug was prescribed, and he developed parkinsonism years later. Differential diagnosis between drug-induced parkinsonism and PLA2G6-related dystonia-parkinsonism could be challenging. PLA2G6 sequencing has to be considered facing a patient with adulthood parkinsonism, especially when it is associated with initial psychiatric symptoms. Our case highlights a common problem treating psychiatric symptoms in neurodegenerative diseases that lead to parkinsonism. The use of antipsychotics requires a special caution in these patients because it may cause extrapyramidal symptoms. Aripiprazole had therapeutic effect on both mood and psychotic symptoms and less impact on motor features, which may be considered an ideal pharmacological approach in treating these patients.

Aim Bipolar disorder and major depressive disorder (MDD) have been demonstrated to be associated with proinflammatory states and cognitive function deficits. We aimed to investigate the differences of cognitive function and proinflammatory cytokines between patients with bipolar I disorder (BDI), bipolar II disorder (BDII), and MDD. Methods Thirty‐seven patients with BDI, 33 with BDII, 25 with MDD, and 54 age‐, sex‐matched controls were enrolled. All patients had a clinical global impression‐severity scale ≤2. Serum levels of proinflammatory markers, including soluble interleukin‐6 receptor, C‐reactive protein, and soluble tumor necrosis factor receptor 1 (sTNF‐αR1) were measured. Performance in the Word List Memory Task (WLMT), Wisconsin Card Sorting Task (WCST), 2‐back task, Go/No‐Go task, and divided attention task was assessed. Results Patients with BDI had higher levels of sTNF‐αR1 than patients with MDD and controls (P < 0.001). Patients with BDI performed worse on WLMT, WCST, 2‐back task, divided attention_visual and divided attention_auditory tasks than the other three groups (all P < 0.05). Furthermore, sTNF‐αR1 levels were negatively correlated with cognitive function measured using the WLMT and divided attention_auditory (all P < 0.05). Conclusions Patients with BDI had higher levels of sTNF‐αR1 and cognitive function impairments than the remaining groups. Future studies are needed to explore the pathophysiology of sTNF‐αR1 in the contribution of cognitive alterations.

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Background: This study investigated the determinants and use of Taiwan's longterm care (LTC) Plan Version 2.0 (LTC 2.0) services by persons with dementia (PWDs) and their caregivers. Methods: In total, 1268 PWD-caregiver dyads were enrolled for analysis from a national dementia registry. Andersen's Behavioral Model of Health Services Use was used to investigate the association of LTC service use with several factors, namely the demographic data of PWDs and their caregivers, migrant caregiver employment, monthly household income, caregiver burden as determined by the Zarit Burden Interview (ZBI), Mini-Mental State Examination score, Clinical Dementia Rating

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Background: Because of a relative dearth of longitudinal studies, the directionality of the relationship between mood and inflammation among patients with bipolar disorder (BD) is still unclear. We aimed to investigate the longitudinal associations of pro-inflammatory markers with mood symptom severity in BD. Methods: Hundred and thirty-two adult patients with BD were enrolled. At the baseline and 1-year follow-up visit, all participants received mood assessment with Montgomery Åsberg depression rating scale (MADRS) and Young mania rating scale, and underwent blood draws to quantify metabolic profile and serum levels of the pro-inflammatory markers, including soluble interleukin-6 receptor, soluble tumor necrosis factor-α receptor type 1 (sTNF-αR1), monocyte chemoattractant protein-1, and C-reactive protein. A four-factor model of MADRS, consisting of sadness, negative thoughts, detachment, and neurovegetative symptoms, were applied. Results: At baseline, 65 patients with BD were in depressed state, and 67 patients with BD were in euthymic state. Among patients in depressed state, baseline MADRS total score positively correlated with sTNF-αR1 level at follow-up. While baseline sTNF-αR1 level positively predicted sadness symptom in euthymic patients with BD who later developed depression (n = 22), sadness in patients with bipolar depression predicted later increase in serum sTNF-αR1 level even after remission (n = 17). Moreover, lithium had a stronger effect of lowering peripheral sTNF-αR1 level as compared with other mood stabilizers. Conclusion:Our results indicate the bidirectional inflammation-depression relationship in BD.

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Objectives: To investigate potential risk factors for mild behavioral impairment (MBI) among non-demented geriatrics. Design: Population-based, cross-sectional survey. Setting: Taiwan Alzheimer Disease Association (TADA) Database. Participants: Participants were selected by multistage random sampling of all Taiwan counties. They received in-person interviews between December 2011 and March 2013. Measurements: Demographic data, lifestyle and habits, medical comorbidities, cognitive status measured by the Taiwanese Mini-Mental Status Examination (TMSE) and presence of MCI of the participants were collected. Subjects were distributed to the MBI and non-MBI groups. These factors had been evaluated for their effects on MBI in the univariate and multivariable logistic regression models. Results: In total, 6,196 non-demented participants aged 65 years or older, including 409 MBI and 5,787 non-MBI participants, were recruited. After adjustment for age, sex, education, body mass index, lifestyle and habits, medical comorbidities, and MCI, good sleep was associated with lower risk of MBI (OR 0.09, 95% CI 0.07 – 0.12). Low body weight (OR 2.01, 95% CI 1.21–3.33), low-to-medium education (OR 1.40, 95%CI 1.06–1.85; OR 2.32, 95% CI 1.67–3.21), medical comorbidities of hypertension (OR 1.56, 95% CI 1.25–1.95), hyperlipidemia (OR 1.29, 95% CI 1.00–1.67), cancer (OR 2.05, 95% CI 1.37–3.06) were significantly associated with increased MBI risk. MCI neither increased nor decreased risk of MBI (OR 1.00, 95% CI 0.76–1.32). Conclusions: Good sleep was associated with lower MBI risk. Underweight, lower education, medical comorbidities of cancer, hypertension, hyperlipidemia were predictive of MBI.