Using genome-wide association data, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson's (PD) or Alzheimer's (AD) disease versus controls across ancestry groups. A shared genetic association was observed across diseases at rs601945 (PD: odds ratio (OR)=0.84; 95% confidence interval, [0.80; 0.88]; p=2.2x10-13; AD: OR=0.91[0.89; 0.93]; p=1.8x10-22), and with a protective HLA association recently reported in amyotrophic lateral sclerosis (ALS). Hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03, and absent for HLA-DRB1*04:05. The same signal was associated with decreased neurofibrillary tangles (but not neuritic plaque density) in postmortem brain and was more strongly associated with Tau levels than A{beta}42 levels in the cerebrospinal fluid. Finally, protective HLA-DRB1*04 subtypes strongly bound aggregation-prone Tau PHF6 sequence, but only when acetylated at K311, a modification central to aggregation. A HLA-DRB1*04-mediated adaptive immune response, potentially against Tau, decreases PD, AD and ALS risk, offering the possibility of new therapeutic avenues.

Cognitive frailty is a condition recently defined by operationalized criteria describing coexisting physical frailty and mild cognitive impairment, with two proposed subtypes: potentially reversible cognitive frailty (physical frailty/mild cognitive impairment) and reversible cognitive frailty (physical frailty/pre-mild cognitive impairment subjective cognitive decline). A relevant heterogeneity was suggested by several studies with prevalence estimates ranging 1.0%–39.7% (10.7%–39.7% in clinical-based settings and 1.0%–19.9% in population-based settings). Cross-sectional and longitudinal population-based studies showed that different cognitive frailty models may be associated with increased risk of functional disability, worsened quality of life, hospitalization, mortality, incidence of dementia, incidence of vascular dementia, and neurocognitive disorders. Multidomain interventions have the potential to be effective in preventing cognitive frailty. More reliable clinical and research criteria are needed, with clinical, biological, and imaging markers to implement intervention programs targeted to improve frailty, with an impact on prevention of cognitive disorders in older age.

We report a 82-year-old woman, who gradually started to present in 2015 cognitive impairment (forgetfulness, impaired attention) with fluctuating course and behavioural symptoms (auditory and visual hallucinations, apathy). Since Spring 2016, progressive slowness of movements was observed. Since Autumn 2016, she felt that another person was inside her and was telling her what to do. Neurological examination showed ipomimia, akinesia and rigidity in all limbs, postural abnormalities, difficulties in gait. The patient underwent an extensive neuropsychological assessment, MRI, Single Photon Emission Tomography (SPET) with dopamine transporter (DAT) scan. In July 2016, MRI scan showed cortical and subcortical atrophy and small areas of increased signal intensity in centrum semiovalis of both cerebral hemispheres on FLAIR sequences. In September 2016, neuropsychological testing documented cognitive impairment, mainly characterised by deficits of executive functions and episodic memory. In June 2017, about 2 years after disease onset, DAT-scan did not show decreased DAT striatal uptake. So far, the patient refused a repeat DAT-scan SPECT. According to current diagnostic criteria, a clinical diagnosis of probable Dementia with Lewy bodies can be made in this patient. The absence of abnormalities on DAT-scan, reported in a low percentage of patients with neuropathologically confirmed diagnosis of DLB, may arise from a less marked neuronal loss in the substantia nigra in such patients, who may show abnormal DAT-scan on follow-up. This case supports the view that DLB in early stages may show different patterns of presentation from clinical and neuropathological viewpoints.

IntroductionAccording to scientific literature, cognitive impairment is a disabling feature of the bipolar disorder (BD), present in all the phases of the disease. Obesity and metabolic disorders represent another risk factor for cognitive dysfunctions in BD, since the excess of weight could adversely influence several cognitive domains.ObjectiveTo highlight the presence of impairment of cognitive functions in a sample of subjects suffering from BD and obesity.AimsEvaluation of the cognitive performance in a sample of BD patients, considering their anthropometric measures (height and weight) and body mass index (BMI).MethodsThe neuropsychological battery MATRICS Consensus Cognitive Battery (MCCB) was administered by trained physicians for the evaluation of seven different cognitive domains in 46 patients (mean age: 43.17 years old; 39.13% male), affected by BD enrolled in the psychiatric unit of Azienda Sanitaria Locale and University of Foggia. In particular, cognitive functions assessed were speed of processing, attention/vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition. BMI was calculated, and patients were divided into a group of normal weight and another one of overweight or obese, on the base of BMI value (BMI cut-off = 25).ResultsThe obese patients amounted at 56.52%. We have found the presence of cognitive deficits in two of the seven domains assessed, that are speed of processing (P < 0.01) and reasoning and problem solving (P < 0.05) in the sample of overweight patients.ConclusionsCognitive deficits are clearly revealed in BD patients during the euthymic phase of the disorder. The obesity in BD could contribute to increase dysfunctions in cognitive domains.Disclosure of interestThe authors have not supplied their declaration of competing interest.

IntroductionSeveral studies have reported controversial links between swallowing disturbances (SD) and psychiatric disorders in older age. The available data on the epidemiology of SD in the general population are scarce and often conflicting, because of numerous methodological factors source of possible counfounders.ObjectivesWe aimed to screen the presence of psychiatric and cognitive disorders associated with SD in a random sampling of the general population ≥ 65.MethodsA sample of 1127 elderly individuals collected in a population-based study (GreatAGE) in Castellana Grotte (53,50% males, mean age 74.1 ± 6.3 years), South-East Italy, were mailed a validated self-report questionnaire to assess SD (Eating Assessment Tool-EAT10). Psychiatric disorders and symptoms [assessed with Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders, Geriatric Depression Scale-30 (GDS-30) and Symptom Checklist Revised-90 (SCL-90R)], cognitive functions were assessed with a comprehensive neuropsychological battery, neurological exam, and demographics were compared in participants with and without SD using t-tests and Mann–Whitney U-test.ResultsThe prevalence rates of SD amounted at 5.97%. Psychiatric diagnosis (24.22% of the sample) was statistically significant associated with SD (EAT ≥ 3, P = 0.038), and a trend was found for major depressive disorder and generalized anxiety disorder. Among SCL-90R domains, only anxiety showed a significant association with EAT ≥ 3 (P = 0.006). GDS-30 score was found to be higher in subjects with SD (P = 0.008). Cognitive functions did not differ between the two groups except for an increasing trend for Clinical Dementia Rating Scale in EAT ≥ 3 (P = 0.058).ConclusionsThese preliminary results showed an association between SD in older age and late-life major depression and anxiety disorders.Disclosure of interestThe authors have not supplied their declaration of competing interest.

IntroductionCognitive dysfunctions concerning working memory, attention, psychomotor speed, and verbal memory are a disabling feature of the bipolar disorder (BD). According to scientific literature, cognitive disturbances are present not only in depressive and manic phases of BD, but also during the euthymic period, without regard to whether or not drugs are assumed.ObjectiveTo determine the presence of one or more dysfunctions in cognitive domains in a sample of subjects suffering from BD, in euthymic phase, compared with healthy controls.AimsEvaluation of the following cognitive performances in subjects affected by BD: speed of processing, attention/vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition.MethodsForty-six patients affected by BD in the euthymic phase (mean age: 43.17 years old; 39.13% male), and 58 healthy controls (mean age: 39.21 years old; 51.72% male) were enrolled in the psychiatric unit of Azienda Sanitaria Locale, Foggia. The neuropsychological battery MATRICS Consensus Cognitive Battery (MCCB) was administered by trained psychiatrists.ResultsWe found the presence of cognitive impairment, affecting six out of seven of cognitive functions assessed (P < 0.001): speed of processing, attention/vigilance, working memory, verbal learning, visual learning, reasoning and problem solving.ConclusionsThese preliminary results from our case-control study show that cognitive deficits are clearly present also during the euthymic phases of subjects with bipolar disorder (mainly pertaining attention/vigilance domain). These cognitive abnormalities may represent a biomarker of bipolar disorder.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Introduction The validity of the 30-item Geriatric Depression Scale (GDS-30) in detecting late-life depression (LLD) requires a certain level of cognitive functioning. Further research is needed in population-based setting on other socio-demographic and cognitive variables that could potentially influence the accuracy of clinician rated depression. Objective To compare the diagnostic accuracy of two instruments used to assess depressive disorders [(GDS-30) and the Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders (SCID)] among three groups with different levels of cognitive functioning (normal, Mild Cognitive Impairment – MCI, Subjective Memory Complain – SMC) in a random sampling of the general population 65+ years. Methods The sample, collected in a population-based study (GreatAGE Study) among the older residents of Castellana Grotte, South-East Italy, included 844 subjects (54.50% males). A standardized neuropsychological battery was used to assess MCI, SMC and depressive symptoms (GDS-30). Depressive syndromes were diagnosed through the SCID IV-TR. Socio-demographic and cognitive variables were taken into account in influencing SCID performance. Results According to the SCID, the rate of depressive disorders was 12.56%. At the optimal cut-off score (≥ 4), GDS-30 had 65.1% sensitivity and 68.4% specificity in diagnosing depressive symptoms. Using a more conservative cut-off (≥ 10), the GDS-30 specificity reached 91.1% while sensitivity dropped to 37,7%. The three cognitive subgroups did not differ in the rate of depression diagnosis. Educational level is the only variable associated to the SCID diagnostic performance ( P = 0.015). Conclusions At the optimal cut-off, GDS-30 identified lower levels of screening accuracy for subjects with normal cognition rather than for SMC (AUC 0.792 vs. 0.692); educational attainment possibly may modulate diagnostic clinician performance. Disclosure of interest The authors have not supplied their declaration of competing interest.

Background: Behavioural changes may be an early manifestation of Fronto-Temporal Dementia (FTD).