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Tiivistelmä Elintavoilla ja lääkehoidolla voidaan vaikuttaa osaan muistisairauksien riskitekijöistä ja sairauksilta suojaavista tekijöistä. Sairastumisen todennäköisyyttä voidaan pienentää vaikuttamalla riskitekijöihin. Eteneviin muistisairauksiin ei ole parantavaa hoitoa, mutta varhainen diagnostiikka, tuki ja hoito ovat tärkeitä toimintakyvyn säilyttämiseksi. Diagnoosin jälkeen tehdään hoito- ja palvelusuunnitelma. Sen lähtökohtana on muistisairaan potilaan arvojen, elämäntavan ja itsemääräämisoikeuden kunnioittaminen. Suunnitelmaa päivitetään säännöllisesti.

Background: How the relationship between obesity and MRI-defined neural properties varies across distinct stages of cognitive impairment due to Alzheimer’s disease is unclear. Objective: We used multimodal neuroimaging to clarify this relationship. Methods: Scans were acquired from 47 patients clinically diagnosed with mild Alzheimer’s disease dementia, 68 patients with mild cognitive impairment, and 57 cognitively healthy individuals. Voxel-wise associations were run between maps of gray matter volume, white matter integrity, and cerebral blood flow, and global/visceral obesity. Results: Negative associations were found in cognitively healthy individuals between obesity and white matter integrity and cerebral blood flow of temporo-parietal regions. In mild cognitive impairment, negative associations emerged in frontal, temporal, and brainstem regions. In mild dementia, a positive association was found between obesity and gray matter volume around the right temporoparietal junction. Conclusion: Obesity might contribute toward neural tissue vulnerability in cognitively healthy individuals and mild cognitive impairment, while a healthy weight in mild Alzheimer’s disease dementia could help preserve brain structure in the presence of age and disease-related weight loss.

Accurate differentiation between neurodegenerative diseases is developing quickly and has reached an effective level in disease recognition. However, there has been less focus on effectively distinguishing the prodromal state from later dementia stages due to a lack of suitable biomarkers. We utilized the Disease State Index (DSI) machine learning classifier to see how well quantified metabolomics data compares to clinically used cerebrospinal fluid (CSF) biomarkers of Alzheimer’s disease (AD). The metabolic profiles were quantified for 498 serum and CSF samples using proton nuclear magnetic resonance spectroscopy. The patient cohorts in this study were dementia (with a clinical AD diagnosis) (N = 359), mild cognitive impairment (MCI) (N = 96), and control patients with subjective memory complaints (N = 43). DSI classification was conducted for MCI (N = 51) and dementia (N = 214) patients with low CSF amyloid-β levels indicating AD pathology and controls without such amyloid pathology (N = 36). We saw that the conventional CSF markers of AD were better at classifying controls from both dementia and MCI patients. However, quantified metabolic subclasses were more effective in classifying MCI from dementia. Our results show the consistent effectiveness of traditional CSF biomarkers in AD diagnostics. However, these markers are relatively ineffective in differentiating between MCI and the dementia stage, where the quantified metabolomics data provided significant benefit.

Background: In clinical practice, it is often difficult to predict which patients with cognitive complaints or impairment will progress or remain stable. We assessed the impact of using a clinical decision support system, the PredictND tool, to predict progression in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI) in memory clinics. Methods: In this prospective multicenter study, we included 429 patients with SCD (n = 230) and MCI (n = 199) (female 54%, age 67 ± 9, MMSE 28 ± 2) and followed them for at least 12 months. Based on all available patient baseline data (demographics, cognitive tests, cerebrospinal fluid biomarkers, and MRI), the PredictND tool provides a comprehensive overview of the data and a classification defining the likelihood of progression. At baseline, a clinician defined an expected follow-up diagnosis and estimated the level of confidence in their prediction using a visual analogue scale (VAS, 0–100%), first without and subsequently with the PredictND tool. As outcome measure, we defined clinical progression as progression from SCD to MCI or dementia, and from MCI to dementia. Correspondence between the expected and the actual clinical progression at follow-up defined the prognostic accuracy. Results: After a mean follow-up time of 1.7 ± 0.4 years, 21 (9%) SCD and 63 (32%) MCI had progressed. When using the PredictND tool, the overall prognostic accuracy was unaffected (0.4%, 95%CI − 3.0%; + 3.9%; p = 0.79). However, restricting the analysis to patients with more certain classifications (n = 203), we found an increase of 3% in the accuracy (95%CI − 0.6%; + 6.5%; p = 0.11). Furthermore, for this subgroup, the tool alone showed a statistically significant increase in the prognostic accuracy compared to the evaluation without tool (6.4%, 95%CI 2.1%; 10.7%; p = 0.004). Specifically, the negative predictive value was high. Moreover, confidence in the prediction increased significantly (∆VAS = 4%, p

Background: Internal motivation and good psychological capabilities are important factors in successful eating-related behavior change. Thus, we investigated whether general acceptance and commitment therapy (ACT) affects reported eating behavior and diet quality and whether baseline perceived stress moderates the intervention effects. Methods: Secondary analysis of unblinded randomized controlled trial in three Finnish cities. Working-aged adults with psychological distress and overweight or obesity in three parallel groups: (1) ACT-based Face-to-face (n = 70; six group sessions led by a psychologist), (2) ACT-based Mobile (n = 78; one group session and mobile app), and (3) Control (n = 71; only the measurements). At baseline, the participants' (n = 219, 85% females) mean body mass index was 31.3 kg/m2 (SD = 2.9), and mean age was 49.5 years (SD = 7.4). The measurements conducted before the 8-week intervention period (baseline), 10 weeks after the baseline (post-intervention), and 36 weeks after the baseline (follow-up) included clinical measurements, questionnaires of eating behavior (IES-1, TFEQ-R18, HTAS, ecSI 2.0, REBS), diet quality (IDQ), alcohol consumption (AUDIT-C), perceived stress (PSS), and 48-h dietary recall. Hierarchical linear modeling (Wald test) was used to analyze the differences in changes between groups. Results: Group x time interactions showed that the subcomponent of intuitive eating (IES-1), i.e., Eating for physical rather than emotional reasons, increased in both ACT-based groups (p = .019); the subcomponent of TFEQ-R18, i.e., Uncontrolled eating, decreased in the Face-to-face group (p = .020); the subcomponent of health and taste attitudes (HTAS), i.e., Using food as a reward, decreased in the Mobile group (p = .048); and both subcomponent of eating competence (ecSI 2.0), i.e., Food acceptance (p = .048), and two subcomponents of regulation of eating behavior (REBS), i.e., Integrated and Identified regulation (p = .003, p = .023, respect

BACKGROUND: PQ912 is an inhibitor of the glutaminyl cyclase enzyme that plays a central role in the formation of synaptotoxic pyroglutamate-A-beta oligomers. We report on the first clinical study with PQ912 in subjects with biomarker-proven Alzheimer's disease (AD). The aim was to determine the maximal tolerated dose, target occupancy and treatment-related pharmacodynamic effects. The exploratory efficacy readouts selected were tailored to the patient population with early AD. The therapeutic approach focuses on synaptic dysfunction as captured by various measures such as electroencephalography (EEG), synaptic biomarkers and sensitive cognitive tests. METHODS: This was a randomized, double-blind, placebo-controlled trial evaluating the safety, tolerability and efficacy of PQ912 800 mg twice daily (bid) for 12 weeks in subjects with mild cognitive impairment or mild dementia due to AD. The 120 enrolled subjects were treatment-naïve at the start of the study, had confirmed AD biomarkers in their cerebrospinal fluid at screening and had a Mini Mental State Examination score between 21 and 30. After 1 week of treatment with 400 mg bid, patients were up-titrated to 800 mg bid for 11 weeks. Patients were randomized 1:1 to either PQ912 or placebo. The primary composite endpoints were to assess safety and tolerability based on the number of patients who discontinued due to (serious) adverse events (safety), and based on dose adjustment during the treatment period and/or nonadherence to randomized treatment (tolerability). All randomized subjects who took at least one dose of the study treatment or placebo were used for safety analyses. RESULTS: There was no significant difference between treatments in the number of subjects with (serious) adverse events, although there were slightly more patients with a serious adverse event in the PQ912 group compared to placebo. More subjects treated with PQ912 discontinued treatment due to adverse events, mostly related to gastrointestin

Item does not contain fulltext, We investigated the use of Alzheimer's disease (AD) biomarkers in European Alzheimer's Disease Consortium centers and assessed their perceived usefulness for the etiologic diagnosis of mild cognitive impairment (MCI). We surveyed availability, frequency of use, and confidence in diagnostic usefulness of markers of brain amyloidosis (amyloid positron emission tomography [PET], cerebrospinal fluid [CSF] Abeta42) and neurodegeneration (medial temporal atrophy [MTA] on MR, fluorodeoxyglucose positron emission tomography [FDG-PET], CSF tau). The most frequently used biomarker is visually rated MTA (75% of the 37 responders reported using it "always/frequently") followed by CSF markers (22%), FDG-PET (16%), and amyloid-PET (3%). Only 45% of responders perceive MTA as contributing to diagnostic confidence, where the contribution was rated as "moderate". Seventy-nine percent of responders felt "very/extremely" comfortable delivering a diagnosis of MCI due to AD when both amyloid and neuronal injury biomarkers were abnormal (P < .02 versus any individual biomarker). Responders largely agreed that a combination of amyloidosis and neuronal injury biomarkers was a strongly indicative AD signature.

Background: We investigated dementia and Alzheimer disease (AD) diagnoses in three national registers in Finland: the Hospital Discharge Register (HDR), the Drug Reimbursement Register, and the Causes of Death Register (CDR). Methods: The Cardiovascular Risk Factors, Aging and Dementia (CAIDE) study was used as the gold standard. Participants were first evaluated in 1972 to 1987, and were reexamined in 1998 and in 2005 to 2008. Results: Two approaches were used for the HDR: with a time restriction (considering positive only those cases recorded in the HDR before CAIDE study evaluations) and without a time restriction. Sensitivity of the HDR was 13.7% with time restriction and 51% without time restriction (dementia), and 15.6% with time restriction 55.6% without time restriction (AD). The positive predictive value (PPV) was 87.5% with time restriction and 96.3% without time restriction (dementia), and 100% for AD. Sensitivity and PPV of the HDR were greater after 1998. For AD in the Drug Reimbursement Register alone, sensitivity was 63.5% and PPV was 97.1%; together with the HDR, sensitivity became 65.4% with time restriction and 71.1% without time restriction, and PPV was 100%. For dementia in the CDR, sensitivity was 62.2% and PPV was 100%. Conclusions: Diagnoses in registers have very good accuracy, but underestimation of dementia/AD occurrence may cause an underestimation of associations with risk/protective factors., AuthorCount:6

Mild cognitive impairment (MCI) is considered as a transition phase between normal aging and Alzheimer's disease (AD). MCI confers an increased risk of developing AD, although the state is heterogeneous with several possible outcomes, including even improvement back to normal cognition. We sought to determine the serum metabolomic profiles associated with progression to and diagnosis of AD in a prospective study. At the baseline assessment, the subjects enrolled in the study were classified into three diagnostic groups: healthy controls (n=46), MCI (n=143) and AD (n=47). Among the MCI subjects, 52 progressed to AD in the follow-up. Comprehensive metabolomics approach was applied to analyze baseline serum samples and to associate the metabolite profiles with the diagnosis at baseline and in the follow-up. At baseline, AD patients were characterized by diminished ether phospholipids, phosphatidylcholines, sphingomyelins and sterols. A molecular signature comprising three metabolites was identified, which was predictive of progression to AD in the follow-up. The major contributor to the predictive model was 2,4-dihydroxybutanoic acid, which was upregulated in AD progressors (P=0.0048), indicating potential involvement of hypoxia in the early AD pathogenesis. This was supported by the pathway analysis of metabolomics data, which identified upregulation of pentose phosphate pathway in patients who later progressed to AD. Together, our findings primarily implicate hypoxia, oxidative stress, as well as membrane lipid remodeling in progression to AD. Establishment of pathogenic relevance of predictive biomarkers such as ours may not only facilitate early diagnosis, but may also help identify new therapeutic avenues.

In this paper we present calibration and validation activities of European Space Agency’s SMOS mission, which utilize airborne interferomentric L-band radiometer system HUT-2D of the Aalto University. During spring 2010 the instrument was used to measure three SMOS validation target areas, one in Denmark and two in Germany. We present these areas shortly, and describe the airborne activities. We show some exemplary measurements of the radiometer system and demonstrate the studies using the data.

Item does not contain fulltext, A three-molecular-window approach for H-1 NMR spectroscopy of serum is presented to obtain specific molecular data on lipoproteins, Various low-molecular-weight metabolites, and individual lipid molecules together with their degree of (poly)(un)saturation. The multiple data were analysed with self-organising maps, illustrating the strength of the approach as a holistic metabonomics framework in solely data-driven metabolic phenotyping. We studied 180 serum samples of which 30% were related to mild cognitive impairment (MCI), a neuropsychological diagnosis with severely increased risk for Alzheimer's disease (AD). The results underline the association between MCI and the metabolic syndrome (MetS). Additionally, the low relative amount of omega-3 fatty acids appears more indicative of MCI than low serum omega-3 OF polyunsaturated fatty acid concentration as such. The analyses also feature the role of elevated glycoproteins in the risk for AD, Supporting the view that coexistence of inflammation and the MetS forms a high risk condition for cognitive decline.