Progranulin Gene Variability and Plasma Levels in Bipolar Disorder and Schizophrenia

Basing on the assumption that frontotemporal lobar degeneration (FTLD), schizophrenia and bipolar disorder (BPD) might share common aetiological mechanisms, we analyzed genetic variation in the FTLD risk gene progranulin (GRN) in a German population of patients with schizophrenia (n = 271) or BPD (n = 237) as compared with 574 age-, gender- and ethnicity-matched controls. Furthermore, we measured plasma progranulin levels in 26 German BPD patients as well as in 61 Italian BPD patients and 29 matched controls

Predominant polarity in bipolar disorder and validation of the polarity index in a German sample

Background: A large number of patients with bipolar disorder (BD) can be characterized by predominant polarity (PP), which has important implications for relapse prevention. Recently, Popovic et al. (EUR NEUROPSYCHOPHARM 22(5): 339–346, 2012) proposed the Polarity Index (PI) as a helpful tool in the maintenance treatment of BD. As a numeric expression, it reflects the efficacy of drugs used in treatment of BD. In the present retrospective study, we aimed to validate this Index in a large and well characterized German bipolar sample. Methods: We investigated 336 bipolar patients (BP) according to their PP and calculated the PI for each patient in order to prove if maintenance treatment differs according to their PP. Furthermore, we analysed whether PP is associated with demographic and clinical characteristics of BP. Results: In our sample, 63.9% of patients fulfilled criteria of PP: 169 patients were classified as depressive predominant polarity (DPP), 46 patients as manic predominant polarity (MPP). The two groups differed significantly in their drug regime: Patients with DPP were more often medicated with lamotrigine and antidepressants, patients with MPP were more often treated with lithium, valproate, carbamazepine and first generation antipsychotics. However, patients with DPP and MPP did not differ significantly with respect to the PI, although they received evidence-based and guideline-driven treatment. Conclusion: The reason for this negative finding might well be that for several drugs, which were used frequently, no PI value is available. Nevertheless we suggest PP as an important concept in the planning of BD maintenance treatment

Antibiotic prescribing in Danish general practice in the elderly population from 2010 to 2017

OBJECTIVE: This study aimed to describe prescription of antibiotics to the elderly population in general practice in Denmark from 2010–2017. DESIGN: This is a national register-based observational study. SETTING: General practice, Denmark MAIN OUTCOME MEASURE: The main outcome measure was prescriptions/1,000 inhabitants/day (PrID) in relation to year, age and sex, indication, and antibiotic agent. SUBJECTS: In this study, we included inhabitants of Denmark, ≥65 years of age between 01st July 2010–30th June 2017. RESULTS: A total of 5,168,878 prescriptions were included in the study. Antibiotic prescriptions decreased from 2.2 PrID to 1.7 (-26.9%, CI95% [-31.1;-22.4]) PrID during the study. The decrease in PrID was most noticeable among 65–74-year-olds (-25%). The ≥85-year-olds were exposed to twice as many PrID than the 65–74-year-olds, but only accounted for 20% of the total use. Urinary tract infection (UTI) was the most common indication for antibiotic prescription and increased with advancing age. The most commonly prescribed antibiotics were pivmecillinam and phenoxymethylpenicillin. Prescribing with no informative indication was present in one third of all cases. CONCLUSION: The prescription of antibiotics in the elderly population in general practice decreased from 2010 to 2017. The oldest age group was exposed twice as frequently to antibiotic prescriptions as the 65–74-year-olds. The smallest reduction was observed for the ≥85-year-olds, suggesting targeting interventions at this group. KEY POINTS: High antibiotic use among elderly is well known and studies indicate mis- and overuse within this population. Our study shows. The prescription rate is decreasing within all age groups of the elderly population. The ≥85-year-olds receive twice as many prescriptions/1000/day as the 65–74-years-olds

A preliminary study on methylphenidate-regulated gene expression in lymphoblastoid cells of ADHD patients

OBJECTIVES: Methylphenidate (MPH) is a commonly used stimulant medication for treating attention-deficit/hyperactivity disorder (ADHD). Besides inhibiting monoamine reuptake there is evidence that MPH also influences gene expression directly. METHODS: We investigated the impact of MPH treatment on gene expression levels of lymphoblastoid cells derived from adult ADHD patients and healthy controls by hypothesis-free, genome-wide microarray analysis. Significant findings were subsequently confirmed by quantitative Real-Time PCR (qRT PCR) analysis. RESULTS: The microarray analysis from pooled samples after correction for multiple testing revealed 138 genes to be marginally significantly regulated due to MPH treatment, and one gene due to diagnosis. By qRT PCR we could confirm that GUCY1B3 expression was differential due to diagnosis. We verified chronic MPH treatment effects on the expression of ATXN1, HEY1, MAP3K8 and GLUT3 in controls as well as acute treatment effects on the expression of NAV2 and ATXN1 specifically in ADHD patients. CONCLUSIONS: Our preliminary results demonstrate MPH treatment differences in ADHD patients and healthy controls in a peripheral primary cell model. Our results need to be replicated in larger samples and also using patient-derived neuronal cell models to validate the contribution of those genes to the pathophysiology of ADHD and mode of action of MPH

Allelic and genotype frequencies given as %(n) in German cases compared with age-, gender- and ethnicity matched controls.

*<p><i>P</i><0.001, OR: 0.20, 95%CI: 0.09–0.14.</p>**<p><i>P</i> = 0.001, OR: 0.60, 95%CI: 0.44–0.81.</p>***<p><i>P</i> = 0.0002, OR: 0.35, 95%CI: 0.20–0.61.</p>****<p><i>P</i><0.001, OR: 0.28, 95%CI: 0.17–0.44.</p>*****<p><i>P</i><0.001, OR: 0.63, 95%CI: 0.49–0.80.</p>°<p><i>P</i> = 0.0003, OR: 0.37, 95%CI: 0.22–0.63.</p>°°<p><i>P</i> = 0.01, OR: 0.66, 95%CI: 0.49–0.90.</p>°°°<p><i>P</i> = 0.002, OR: 0.48, 95%CI: 0.31–0.77.</p>°°°°<p><i>P</i><0.001, OR: 0.43, 95%CI: 0.30–0.63.</p>°°°°°<p><i>P</i> = 0.005, OR: 0.70, 95%CI: 0.55–0.89.</p>•<p><i>P</i> = 0.01, OR: 0.51, 95%CI: 0.30–0.85.</p>••<p><i>P</i><0.0001, OR: 0.53, 95%CI: 0.39–0.72.</p>•••<p><i>P</i> = 0.019, OR: 0.62, 95%CI: 0.42–0.91.</p>••••<p><i>P</i> = 0.007, OR: 0.71, 95%CI: 0.56–0.91.</p

Characteristics of Italian (I) and German (G) subjects included in plasma level evaluation.

<p>Characteristics of Italian (I) and German (G) subjects included in plasma level evaluation.</p

Characteristics of German individuals included in the association study.

*<p> <b>age at disease onset.</b></p

Scattergram of progranulin plasma levels in BPD patients and controls.

<p>Black lines represent mean values. G = German. I = Italian. *<i>P</i><0.001, patients versus controls.</p