Heart failure (HF) is a systemic illness with grave implications for bodily functions. The brain, among other vital organs, often suffers insults as a result of HF, and both anatomic and functional brain abnormalities were found in the HF population. This injury was demonstrated across a wide range of clinical conditions and cardiac functions and was shown to affect patients' outcomes. Although reduced cardiac output and high burden of cardiovascular risk factors are the prevailing explanations for these findings, there are data showing the involvement of neurohormonal, nutritional, and inflammatory mechanisms in this complex process. Here, the authors review the suggested pathophysiology behind brain injury in HF, describe its effect on patients' outcomes, offer a diagnostic approach, and discuss possible therapeutic options.

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IMPORTANCE Mutations in the glucocerebrosidase (GBA) gene are a risk factor for the development of dementia with Lewy bodies (DLB). These mutations are common among Ashkenazi Jews (AJ) and appear to have an effect on the natural history of the disease. OBJECTIVES To evaluate the clinical and genetic characteristics of an AJ cohort of patients diagnosed with DLB, assess the association of phenotype of DLB with GBA mutations, and explore the effects of these mutations on the clinical course of the disease. DESIGN, SETTING, AND PARTICIPANTS Thirty-five consecutively recruited AJ patients with newly diagnosed clinically probable or possible DLB underwent genotyping for the 7 known AJ GBA mutations and the LRRK2 G2019S mutation. Two patients with the LRRK2 G2019S mutation were excluded from the final analysis. Data were collected from July 1, 2013, to July 31, 2015. MAIN OUTCOMES AND MEASURES Assessment of clinical markers included the following standardized scales: Autonomic Scale for Outcomes in Parkinson's Disease (SCOPA-AUT), REM (Rapid Eye Movement) Sleep Behavior Disorder Single-Question Screen, Geriatric Depression Scale, and Montreal Cognitive Assessment. Motor symptoms were assessed with the Unified Parkinson's Disease Rating Scale motor part III. A subset of 15 patients also underwent assessment with the Color Trail Making Test, FAS verbal fluency, Digit Span, Hooper Visual Organization Test, and Stroop test. RESULTS Among the 35 patients with DLB (23 men [66%] and 12 women [34%]; mean [SD], 69.6 [8.2] years), 11 (31%) were carriers of mutations in the GBA gene. Among the 33 patients undergoing further analysis, the GBA mutation carriers were younger at symptom onset (mean [SD] age, 65.7 [11.7] vs 72.1 [5.1] years; P = .03), had more frequent visual hallucinations that did not achieve significance (9 of 11 [82%] compared with 12 of 22 [55%]; P = .052), and had higher scores on the RBD questionnaire (mean [SD], 7.8 [2.2] vs 5.1 [3.3]; P = .03). After adjusting for age and duration of symptoms, testing revealed that GBA mutation carriers had poorer cognition as assessed by the Montreal Cognitive Assessment Battery (mean [SD] score, 18.75 [5.99] vs 23.23 [3.16]; P = .03), lower scores on tests of verbal fluency (adjusted z scores, 0.50 vs −2.02; P = .02), worse scores on tests of visuospatial function (adjusted t scores, 68.55 vs 79.57; P = .046), and higher mean (SD) scores on the Unified Parkinson's Disease Rating Scale motor part

The population of adults with Alzheimer's disease (AD) varies in needs and outcomes. The heterogeneity of current AD diagnostic subgroups impedes the use of data analytics in clinical trial design and translation of findings into improved care. The purpose of this project was to define more clinicallyhomogeneous groups of AD patients and link clinical characteristics with biological markers. We used an innovative big data analysis strategy, the 3C strategy, that incorporates medical knowledge into the data analysis process. A large set of preprocessed AD Neuroimaging Initiative (ADNI) data was analyzed with 3C. The data analysis yielded 6 new disease subtypes, which differ from the assigned diagnosis types and present different patterns of clinical measures and potential biomarkers. Two of the subtypes, "Anosognosia dementia" and "Insightful dementia", differentiate between severe participants based on clinical characteristics and biomarkers. The "Uncompensated mild cognitive impairment (MCI)" subtype, demonstrates clinical, demographic and imaging differences from the "Affective MCI" subtype. Differences were also observed between the "Worried Well" and "Healthy" clusters. The use of data-driven analysis yielded sub-phenotypic clinical clusters that go beyond current diagnoses and are associated with biomarkers. Such homogenous subgroups can potentially form the basis for enhancement of brain medicine research. Alzheimer's disease (AD) is a degenerative brain disease and the most common cause of dementia 1 according to the 2018 Alzheimer's association report 2 an estimated 5.7 million Americans of all ages are living with AD in 2018. The percentage of people with AD increases with age: 3% of people age 65-74, 17% of people age 75-84, and 32% of people age 85 and older have AD 3. Symptoms vary among people with AD, and the differences between typical age-related cognitive changes and early signs of AD can be subtle. The definite diagnosis of AD, requiring histopathological examination, is characterized by the accumulation of β-amyloid (Aβ) plaques and neurofibrillary tangles composed of tau amyloid fibrils associated with brain cell damage and neurodegeneration 4. In clinical practice, the diagnosis of AD is based on clinical criteria, while laboratory and imaging examinations are used to exclude other diagnoses. Sub classification of AD has been previously attempted, mostly based on a small set of parameters or on a single modality 5,6 , and in some studies has relied only on previous knowledge. Current diagnostic subgroupings are informative, however, they are quite crude as they are based on rough criteria 7,8. This may lead astray supervised data mining tools that rely solely on these definitions while trying to predict or associate disease manifestation with clinical and biological markers. Thus, for the search of new insights, it is essential to use unsupervised processes, which do not rely on the current diagnostic subgroupings, Nevertheless, despite numerous attempts to use unsupervised processes as progn...

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Background: Aerobic training has been shown to promote structural and functional neurocognitive plasticity in cognitively intact older adults. However, little is known about the neuroplastic potential of aerobic exercise in individuals at risk of Alzheimer’s disease (AD) and dementia. Objective: We aimed to explore the effect of aerobic exercise intervention and cardiorespiratory fitness improvement on brain and cognitive functions in older adults with amnestic mild cognitive impairment (aMCI). Methods: 27 participants with aMCI were randomized to either aerobic training (n = 13) or balance and toning (BAT) control group (n = 14) for a 16-week intervention. Pre- and post-assessments included functional MRI experiments of brain activation during associative memory encoding and neural synchronization during complex information processing, cognitive evaluation using neuropsychological tests, and cardiorespiratory fitness assessment. Results: The aerobic group demonstrated increased frontal activity during memory encoding and increased neural synchronization in higher-order cognitive regions such as the frontal cortex and temporo-parietal junction (TPJ) following the intervention. In contrast, the BAT control group demonstrated decreased brain activity during memory encoding, primarily in occipital, temporal, and parietal areas. Increases in cardiorespiratory fitness were associated with increases in brain activation in both the left inferior frontal and precentral gyri. Furthermore, changes in cardiorespiratory fitness were also correlated with changes in performance on several neuropsychological tests. Conclusion: Aerobic exercise training may result in functional plasticity of high-order cognitive areas, especially, frontal regions, among older adults at risk of AD and dementia. Furthermore, cardiorespiratory fitness may be an important mediating factor of the observed changes in neurocognitive functions.

Cerebral atrophy has been detected in patients with Parkinson's disease (PD) both with and without dementia, however differentiation based on genetic status has thus far not yielded robust findings. We assessed cortical thickness and subcortical volumes in a cohort of PD patients and healthy controls carriers of the G2019S mutation in the LRRK2 gene and the common GBA mutations, in an attempt to determine whether genetic status influences structural indexes. Cortical thickness and subcortical volumes were computed and compared between six groups of participants; idiopathic PD, GBA-PD, LRRK2-PD, non-manifesting non-carriers (NMNC), GBA-non-manifesting carriers (NMC) and LRRK2-NMC utilizing the FreeSurfer software program. All participants were cognitively intact based on a computerized cognitive assessment battery. Fifty-seven idiopathic PD patients, 9 LRRK2-PD, 12 GBA-PD, 49 NMNC, 41 LRRK2-NMC and 14 GBA-NMC participated in this study. Lower volumes among patients with PD compared to unaffected participants were detected in bilateral hippocampus, nucleus accumbens, caudate, thalamus, putamen and amygdala and the right pallidum (p = 0.016). PD patients demonstrated lower cortical thickness indexes in a majority of regions assessed compared with non-manifesting participants. No differences in cortical thickness and subcortical volumes were detected within each of the groups of participants based on genetic status. Mutations in the GBA and LRRK2 genes are not important determinants of cortical thickness and subcortical volumes in both patients with PD and non-manifesting participants. PD is associated with a general reduction in cortical thickness and sub-cortical atrophy even in cognitively intact patients.

Mutations in the GBA and LRRK2 genes account for one-third of the prevalence of Parkinson's disease (PD) in Ashkenazi Jews. Non-manifesting carriers (NMC) of these mutations represent a population at risk for future development of PD. PD patient who carry mutations in the GBA gene demonstrates more significant cognitive decline compared to idiopathic PD patients. We assessed cognitive domains using fMRI among NMC of both LRRK2 and GBA mutations to better understand pre-motor cognitive functions in these populations. Twenty-one LRRK2-NMC, 10 GBA-NMC, and 22 non-manifesting non-carriers (NMNC) who participated in this study were evaluated using the standard questionnaires and scanned while performing two separate cognitive tasks; a Stroop interference task and an N-Back working memory task. Cerebral activation patterns were assessed using both whole brain and predefined region of interest (ROI) analysis. Subjects were well matched in all demographic and clinical characteristics. On the Stroop task, in spite of similar behavior, GBA-NMC demonstrated increased task-related activity in the right medial frontal gyrus and reduced task-related activity in the left lingual gyrus compared to both LRRK2-NMC and NMNC. In addition, GBA-NMC had higher activation patterns in the incongruent task compared to NMNC in the left medial frontal gyrus and bilateral precentral gyrus. No whole-brain differences were noted between groups on the N-Back task. Paired cognitive and task-related performance between GBA-NMC, LRRK2-NMC, and NMNC could indicate that the higher activation patterns in the incongruent Stroop condition among GBA-NMC compared to LRRK2-NMC and NMNC may represent a compensatory mechanism that enables adequate cognitive performance.