The diagnostic accuracy of late-life depression is influenced by subjective memory complaints and educational level in an older population in Southern Italy.

The prevalence of late-life depression (LLD) depends on the study sample, measurements, and diagnostic approaches. We estimated the 30 item-Geriatric Depression Scale (GDS-30) accuracy against the gold standard LLD diagnosis made with the Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders, focusing on the prevalence of a late-life major depressive disorder (MDD), in a population-based sample of 843 subjects aged>65 years, subdivided into three groups: normal cognition, subjective memory complaints, and mild cognitive impairment. At the optimal cut-off score (≥4), the GDS-30 showed 65.1% sensitivity and 68.4% specificity for LLD (63% and 66% for late-life MDD, respectively). Using the standard cut-off score (≥10), the GDS-30 specificity reached 91.2%, while sensitivity dropped to 37.7%, indicating a lower screening accuracy [area under the curve(AUC):0.728, 95% confidence interval(CI):0.67-0-78]. The GDS-30 performance was associated with educational level, but not with age, gender, cognition, apathy, and somatic/psychiatric multimorbidity. For subjective memory complaints subjects, at the optimal cut-off score (≥7), the GDS-30 showed better discrimination performances (AUC=0.792,95%CI:0.60-0.98), but again the educational level affected the diagnostic performance. In subjective memory complaints subjects, symptom-based scales like the GDS-30 may feature a better performance for diagnosing depression in older age, but the GDS-30 seems to require adjustment to the patient's educational level.

Evidence of an interaction between FXR1 and GSK3ß polymorphisms on levels of Negative Symptoms of Schizophrenia and their response to antipsychotics.

BACKGROUND: Genome-Wide Association Studies (GWASs) have identified several genes associated with Schizophrenia (SCZ) and exponentially increased knowledge on the genetic basis of the disease. In addition, products of GWAS genes interact with neuronal factors coded by genes lacking association, such that this interaction may confer risk for specific phenotypes of this brain disorder. In this regard, fragile X mental retardation syndrome-related 1 (FXR1) gene has been GWAS associated with SCZ. FXR1 protein is regulated by glycogen synthase kinase-3ß (GSK3ß), which has been implicated in pathophysiology of SCZ and response to antipsychotics (APs). rs496250 and rs12630592, two eQTLs (Expression Quantitative Trait Loci) of FXR1 and GSK3ß, respectively, interact on emotion stability and amygdala/prefrontal cortex activity during emotion processing. These two phenotypes are associated with Negative Symptoms (NSs) of SCZ suggesting that the interaction between these SNPs may also affect NS severity and responsiveness to medication. METHODS: To test this hypothesis, in two independent samples of patients with SCZ, we investigated rs496250 by rs12630592 interaction on NS severity and response to APs. We also tested a putative link between APs administration and FXR1 expression, as already reported for GSK3ß expression. RESULTS: We found that rs496250 and rs12630592 interact on NS severity. We also found evidence suggesting interaction of these polymorphisms also on response to APs. This interaction was not present when looking at positive and general psychopathology scores. Furthermore, chronic olanzapine administration led to a reduction of FXR1 expression in mouse frontal cortex. DISCUSSION: Our findings suggest that, like GSK3ß, FXR1 is affected by APs while shedding new light on the role of the FXR1/GSK3ß pathway for NSs of SCZ.

Antipsychotic Drug Responsiveness and Dopamine Receptor Signaling; Old Players and New Prospects.

Antipsychotic drugs targeting dopamine neurotransmission are still the principal mean of therapeutic intervention for schizophrenia. However, about one third of people do not respond to dopaminergic antipsychotics. Genome wide association studies (GWAS), have shown that multiple genetic factors play a role in schizophrenia pathophysiology. Most of these schizophrenia risk variants are not related to dopamine or antipsychotic drugs mechanism of action. Genetic factors have also been implicated in defining response to antipsychotic medication. In contrast to disease risk, variation of genes coding for molecular targets of antipsychotics have been associated with treatment response. Among genes implicated, those involved in dopamine signaling mediated by D2-class dopamine receptor, including DRD2 itself and its molecular effectors, have been implicated as key genetic predictors of response to treatments. Studies have also reported that genetic variation in genes coding for proteins that cross-talk with DRD2 at the molecular level, such as AKT1, GSK3B, Beta-catenin, and PPP2R2B are associated with response to antipsychotics. In this review we discuss the relative contribution to antipsychotic drug responsiveness of candidate genes and GWAS identified genes encoding proteins involved in dopamine responses. We also suggest that in addition of these older players, a deeper investigation of new GWAS identified schizophrenia risk genes such as FXR1 can provide new prospects that are not clearly engaged in dopamine function while being targeted by dopamine-associated signaling molecules. Overall, further examination of genes proximally or distally related to signaling mechanisms engaged by medications and associated with disease risk and/or treatment responsiveness may uncover an interface between genes involved in disease causation with those affecting disease remediation. Such a nexus would provide realistic targets for therapy and further the development of genetically personalized approaches for schizophrenia.

Innovative biomarkers in psychiatric disorders: a major clinical challenge in psychiatry.

INTRODUCTION: Currently, the diagnosis of psychiatric illnesses is based upon DSM-5 criteria. Although endophenotype-specificity for a particular disorder is discussed, the identification of objective biomarkers is ongoing for aiding diagnosis, prognosis, or clinical response to treatment. We need to improve the understanding of the biological abnormalities in psychiatric illnesses across conventional diagnostic boundaries. The present review investigates the innovative post-genomic knowledge used for psychiatric illness diagnostics and treatment response, with a particular focus on proteomics. Areas covered: This review underlines the contribution that psychiatric innovative biomarkers have reached in relation to diagnosis and theragnosis of psychiatric illnesses. Furthermore, it encompasses a reliable representation of their involvement in disease through proteomics, metabolomics/pharmacometabolomics and lipidomics techniques, including the possible role that gut microbiota and CYP2D6 polimorphisms may play in psychiatric illnesses. Expert opinion: Etiologic heterogeneity, variable expressivity, and epigenetics may impact clinical manifestations, making it difficult for a single measurement to be pathognomonic for multifaceted psychiatric disorders. Academic, industry, or government's partnerships may successfully identify and validate new biomarkers so that unfailing clinical tests can be developed. Proteomics, metabolomics, and lipidomics techniques are considered to be helpful tools beyond neuroimaging and neuropsychology for the phenotypic characterization of brain diseases.

Bipolar Disorder and Frontotemporal Dementia: An Intriguing Association.

Bipolar disorder (BD) could represent a prodromal state of frontotemporal dementia (FTD). Two patients affected by lifelong BD with a progressive decline of cognitive functions, behavioral, and neurological signs, reached the early diagnosis of FTD before the age of 60. They were diagnosed as affected by primary progressive aphasia and FTD with parkinsonism, respectively. A diagnosis of FTD should therefore be taken into account, in case of unexpected cognitive and behavioral decline in patients with a long history of BD. Follow-up studies with genetic, neuropsychological, and neuroimaging markers of these BD/FTD patients could further explore some of the underlying association, opening new viable therapeutic options.

Examination of level of knowledge in Italian general practitioners attending an education session on diagnosis and management of the early stage of Alzheimer's disease: pass or fail?

BACKGROUND: We detected the general level of knowledge about the early diagnosis of Alzheimer's disease (AD) and subsequent care in general practitioners (GPs) from Southern Italy. We explored also the GP perception about their knowledge and training on diagnosis and management of AD. METHODS: On a sample of 131 GPs, we administered two questionnaires: the GP-Knowledge, evaluating GPs' expertise about AD epidemiology, differential diagnosis, and available treatments, and the GP-QUestionnaire on Awareness of Dementia (GP-QUAD), assessing the GPs' attitudes, awareness, and practice regarding early diagnosis of dementia. RESULTS: Specific screening tests or protocols to diagnose and manage dementia were not used by 53% of our GPs. The training on the recognition of early AD signs and symptoms was considered inadequate by 55% of the participants. Females were more likely to consider their training insufficient (58%) compared to males (53%). Female GPs were less likely to prescribe antipsychotic drugs to control neuropsychiatric symptoms (NPS) and suggest specialist advice in late stage of cognitive impairment. Multiple Correspondence Analysis (MCA) performed only on GP-QUAD suggested two dimensions explaining 26.1% ("GP attitude") and 20.1% ("GP knowledge") of the inertia for a total of 46.2%, CONCLUSION: In our survey on GP clinical practice, several problems in properly recognizing early AD symptoms and subsequently screening patients to be referred to secondary/tertiary care centers for diagnosis confirmation have emerged. In the future, specific training programs and educational projects for GPs should be implemented also in Italy to improve detection rates and management of dementia in primary care.

Advances in meta-analysis: examples from internal medicine to neurology.

OBJECTIVE: We review the state of the art in meta-analysis and data pooling following the evolution of the statistical models employed. METHODS: Starting from a classic definition of meta-analysis of published data, a set of apparent antinomies which characterized the development of the meta-analytic tools are reconciled in dichotomies where the second term represents a possible generalization of the first one. Particular attention is given to the generalized linear mixed models as an overall framework for meta-analysis. Bayesian meta-analysis is discussed as a further possibility of generalization for sensitivity analysis and the use of priors as a data augmentation approach. RESULTS: We provide relevant examples to underline how the need for adequate methods to solve practical issues in specific areas of research have guided the development of advanced methods in meta-analysis. CONCLUSIONS: We show how all the advances in meta-analysis naturally merge into the unified framework of generalized linear mixed models and reconcile apparently conflicting approaches. All these complex models can be easily implemented with the standard commercial software available.