Relationship between imaging biomarkers, age, progression and symptom severity in Alzheimer's disease

Cerebral glucose metabolism in Alzheimer's disease

18F-fluoro-deoxy-glucose positron emission tomography (FDG-PET) is a useful paraclinical exam for the diagnosis of Alzheimer's disease (AD). In this narrative review, we report seminal studies in clinically probable AD that have shown the importance of posterior brain metabolic decrease and the paradoxical variability of the hippocampal metabolism. The FDG-PET pattern was a sensitive indicator of AD in pathologically confirmed cases and it was used for differential diagnosis of dementia conditions. In prodromal AD, the AD FDG-PET pattern was observed in converters and predicted conversion. Automated data analysis techniques provided variable accuracy according to the reported indices and machine learning methods showed variable reliability of results. FDG-PET could confirm AD clinical heterogeneity and image data driven analyses identified hypometabolic subtypes with variable involvement of the hippocampus, reminiscent if the paradoxical FDG uptake. In studies dedicated to clinical and metabolic correlations, episodic memory was related to metabolism in the default mode network (and Papez's circuit) in prodromal and mild AD stages, and specific cognitive processes were associated to precisely distributed brain metabolism. Cerebral metabolic correlates of anosognosia could also be related to current neuropsychological models. AD FDG-PET pattern was reported in preclinical AD stages and related to cognition or to conversion to mild cognitive impairment (MCI). Using other biomarkers, the AD FDG-PET pattern was confirmed in AD participants with positive PET-amyloid. Intriguing observations reported increased metabolism related to brain amyloid and/or tau deposition. Preserved glucose metabolism sometimes appear as a compensation, but it was frequently detrimental and the nature of such a preservation of glucose metabolism remains an open question. Limbic metabolic involvement was frequently related to non-AD biomarkers profile and clinical stability, and it was reported in non-AD pathologies, such as the limbic predominant age-related encephalopathy (LATE). FDG-PET abnormalities observed in the absence of classical AD proteinopathies can be useful to search for pathological mechanisms and differential diagnosis of AD.

Efficacy and safety of acupuncture for cognitive impairment in Alzheimer's disease: a systematic review and meta-analysis

Objective

To systematically evaluate the efficacy of acupuncture in the treatment of cognitive impairment in Alzheimer's disease (AD) by meta-analysis, in order to provide evidence-based evidence for the application of acupuncture therapy in the clinical process of AD.

Methods

From the establishment of the database to December 31, 2022, China Biomedical Literature Database (CBM), China National Knowledge Network (CNKI), VIP database, WanFang Database, Pubmed, Embase and Cochrane Library Database were systematically searched. To collect published randomized controlled clinical trials (RCTS) of acupuncture in the treatment of cognitive impairment in AD. The subjects in the intervention group were given acupuncture alone or combined with other treatments the same as the control group; the control group received conventional Western medicine treatment. The main outcome indicators of the study were cognitive function assessment of subjects, including: Simple Mental State Examination Scale (MMSE), Assessment of daily Living Ability Scale (ADL), Alzheimer's Disease Cognitive Function Assessment Scale (ADAS-Cog), TCM syndrome score (SDSD), Montreal Cognitive Test (MoCA), Secondary outcome indicators were the occurrence of adverse reactions. Literature screening, data extraction, and quality evaluation of the included literature were performed independently by two researchers, according to bias risk assessment tools recommended in the Cochrane manual. Data were analyzed by RevMan5.3 software. Dichotomous variables were represented by risk ratio (OR) and 95% CI, and continuity variables were represented by mean difference (MD) and 95% CI. For heterogeneity analysis, when P > 0.1 and I 2 ≤ 50%, fixed effect model was applied. When P ≤ 0.1 and I 2 > 50%, the random effects model is applied.

Results

A total of 1,172 eligible subjects were included in 18 RCTS, including 595 in the intervention group and 577 in the control group. The results of meta-analysis are as follows: acupuncture intervention group improved MMSE [MD = 1.67, 95% CI (0.94, 2.41), P < 0.00001], ADL [MD = -1.18, 95% CI (-3.09, 0.72), P = 0.22], ADAS-Cog [MD = 3.31, 95% CI (5.84, 0.78), P = 0.01], SDSD [MD = 2.40, 95% CI (3.53, 1.26), P < 0.0001], MoCA [MD = 4.80, 95% CI (3.74, 5.86), P = 0.04] were better than the control group. No serious adverse reactions related to acupuncture were observed in the intervention group, and the incidence and severity of adverse reactions were lower than those in the control group, with statistical significance [OR = 0.17, 95% CI (0.04, 0.67), P = 0.01].

Conclusion

Existing data show that acupuncture therapy has certain advantages in improving cognitive dysfunction and improving self-care ability of patients with Alzheimer's disease. However, due to the small number of RCTS and cases evaluating the efficacy of acupuncture, and the possibility of measurement bias and selectivity bias in included studies, it is still unable to conduct high-intensity demonstration on its effectiveness. Further large-scale, high-quality randomized, double-blind controlled trials are needed to evaluate its efficacy.

Systematic Review Registration

https://inplasy.com/inplasy-2021-12-0125/, identifier: INPLASY2021120125.

The use of individual-based FDG-PET volume of interest in predicting conversion from mild cognitive impairment to dementia

BACKGROUND

Based on a longitudinal cohort design, the aim of this study was to investigate whether individual-based 18F fluorodeoxyglucose positron emission tomography (18F-FDG-PET) regional signals can predict dementia conversion in patients with mild cognitive impairment (MCI).

METHODS

We included 44 MCI converters (MCI-C), 38 non-converters (MCI-NC), 42 patients with Alzheimer's disease with dementia, and 40 cognitively normal controls. Data from annual cognitive measurements, 3D T1 magnetic resonance imaging (MRI) scans, and 18F-FDG-PET scans were used for outcome analysis. An individual-based FDG-PET approach was applied using seven volumes of interest (VOIs), Z transformed using a normal FDG-PET template. Hypometabolism was defined as a Z score < -2 of regional standard uptake value ratio. For the longitudinal cognitive test scores, generalized estimating equations were used. A linear mixed-effects model was used to compare the temporal impact of cortical hypometabolism and cortical thickness degeneration.

RESULTS

The clinical follow-up period was 6.6 ± 3.8 years (range 3.1 to 16.0 years). The trend of cognitive decline could differentiate MCI-C from MCI-NC after 3 years of follow-up. In the baseline 18F-FDG-PET scan of the patients with MCI, medial temporal lobe (MTL; 94.7% sensitivity, 80.5% specificity) and posterior cingulate cortex (PCC; 89.5% sensitivity, 73.1% specificity) hypometabolism predicted conversion with high accuracy. 18F-FDG-PET hypometabolism preceded dementia conversion at an interval of 3.70 ± 1.68 years and was earlier than volumetric changes, with the exception of the MTL.

CONCLUSIONS

Our finding supports the use of individual-based 18F-FDG-PET analysis to predict MCI conversion to dementia. Reduced FDG-PET metabolism in the MTL and PCC were strongly associated with future cognitive decline in the MCI-C group. Changes in 18F-FDG-PET occurred 1 to 8 years prior to conversion to dementia. Progressive hypometabolism in the PCC, precuneus and lateral temporal lobe, but not MTL, preceded MRI findings at the MCI stage.

3D convolutional neural networks uncover modality-specific brain-imaging predictors for Alzheimer's disease sub-scores

Different aspects of cognitive functions are affected in patients with Alzheimer's disease. To date, little is known about the associations between features from brain-imaging and individual Alzheimer's disease (AD)-related cognitive functional changes. In addition, how these associations differ among different imaging modalities is unclear. Here, we trained and investigated 3D convolutional neural network (CNN) models that predicted sub-scores of the 13-item Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog13) based on MRI and FDG-PET brain-imaging data. Analysis of the trained network showed that each key ADAS-Cog13 sub-score was associated with a specific set of brain features within an imaging modality. Furthermore, different association patterns were observed in MRI and FDG-PET modalities. According to MRI, cognitive sub-scores were typically associated with structural changes of subcortical regions, including amygdala, hippocampus, and putamen. Comparatively, according to FDG-PET, cognitive functions were typically associated with metabolic changes of cortical regions, including the cingulated gyrus, occipital cortex, middle front gyrus, precuneus cortex, and the cerebellum. These findings brought insights into complex AD etiology and emphasized the importance of investigating different brain-imaging modalities.

Adiponectin and resistin modulate the progression of Alzheimer´s disease in a metabolic syndrome model

Metabolic syndrome (MetS), a cluster of metabolic conditions that include obesity, hyperlipidemia, and insulin resistance, increases the risk of several aging-related brain diseases, including Alzheimer's disease (AD). However, the underlying mechanism explaining the link between MetS and brain function is poorly understood. Among the possible mediators are several adipose-derived secreted molecules called adipokines, including adiponectin (ApN) and resistin, which have been shown to regulate brain function by modulating several metabolic processes. To investigate the impact of adipokines on MetS, we employed a diet-induced model to induce the various complications associated with MetS. For this purpose, we administered a high-fat diet (HFD) to both WT and APP/PSN1 mice at a pre-symptomatic disease stage. Our data showed that MetS causes a fast decline in cognitive performance and stimulates Aβ42 production in the brain. Interestingly, ApN treatment restored glucose metabolism and improved cognitive functions by 50% while decreasing the Aβ42/40 ratio by approximately 65%. In contrast, resistin exacerbated Aβ pathology, increased oxidative stress, and strongly reduced glucose metabolism. Together, our data demonstrate that ApN and resistin alterations could further contribute to AD pathology.

Multi-modal graph neural network for early diagnosis of Alzheimer's disease from sMRI and PET scans

In recent years, deep learning models have been applied to neuroimaging data for early diagnosis of Alzheimer's disease (AD). Structural magnetic resonance imaging (sMRI) and positron emission tomography (PET) images provide structural and functional information about the brain, respectively. Combining these features leads to improved performance than using a single modality alone in building predictive models for AD diagnosis. However, current multi-modal approaches in deep learning, based on sMRI and PET, are mostly limited to convolutional neural networks, which do not facilitate integration of both image and phenotypic information of subjects. We propose to use graph neural networks (GNN) that are designed to deal with problems in non-Euclidean domains. In this study, we demonstrate how brain networks are created from sMRI or PET images and can be used in a population graph framework that combines phenotypic information with imaging features of the brain networks. Then, we present a multi-modal GNN framework where each modality has its own branch of GNN and a technique that combines the multi-modal data at both the level of node vectors and adjacency matrices. Finally, we perform late fusion to combine the preliminary decisions made in each branch and produce a final prediction. As multi-modality data becomes available, multi-source and multi-modal is the trend of AD diagnosis. We conducted explorative experiments based on multi-modal imaging data combined with non-imaging phenotypic information for AD diagnosis and analyzed the impact of phenotypic information on diagnostic performance. Results from experiments demonstrated that our proposed multi-modal approach improves performance for AD diagnosis. Our study also provides technical reference and support the need for multivariate multi-modal diagnosis methods.

Attention-based 3D CNN with Multi-layer Features for Alzheimer's Disease Diagnosis using Brain Images

Structural MRI and PET imaging play an important role in the diagnosis of Alzheimer's disease (AD), showing the morphological changes and glucose metabolism changes in the brain respectively. The manifestations in the brain image of some cognitive impairment patients are relatively inconspicuous, for example, it still has difficulties in achieving accurate diagnosis through sMRI in clinical practice. With the emergence of deep learning, convolutional neural network (CNN) has become a valuable method in AD-aided diagnosis, but some CNN methods cannot effectively learn the features of brain image, making the diagnosis of AD still presents some challenges. In this work, we propose an end-to-end 3D CNN framework for AD diagnosis based on ResNet, which integrates multi-layer features obtained under the effect of the attention mechanism to better capture subtle differences in brain images. The attention maps showed our model can focus on key brain regions related to the disease diagnosis. Our method was verified in ablation experiments with two modality images on 792 subjects from the ADNI database, where AD diagnostic accuracies of 89.71% and 91.18% were achieved based on sMRI and PET respectively, and also outperformed some state-of-the-art methods.

Early-onset Alzheimer's disease with depression as the first symptom: a case report with literature review

Background

Alzheimer's disease is a common neurodegenerative disease, and patients with early-onset Alzheimer's disease (onset age < 65 years) often have atypical symptoms, which are easily misdiagnosed and missed. Multimodality neuroimaging has become an important diagnostic and follow-up method for AD with its non-invasive and quantitative advantages.

Case presentation

We report a case of a 59-year-old female with a diagnosis of depression at the age of 50 after a 46-year-old onset and a 9-year follow-up observation, who developed cognitive dysfunction manifested by memory loss and disorientation at the age of 53, and eventually developed dementia. Combined with neuropsychological scales (MMSE and MOCA scores decreased year by year and finally reached the dementia criteria) and the application of multimodal imaging. MRI showed that the hippocampus atrophied year by year and the cerebral cortex was extensively atrophied. 18F-FDG PET image showed hypometabolism in right parietal lobes, bilateral frontal lobes, bilateral joint parieto-temporal areas, and bilateral posterior cingulate glucose metabolism. The 18F-AV45 PET image showed the diagnosis of early-onset Alzheimer's disease was confirmed by the presence of Aβ deposits in the cerebral cortex.

Conclusion

Early-onset Alzheimer's disease, which starts with depression, often has atypical symptoms and is prone to misdiagnosis. The combination of neuropsychological scales and neuroimaging examinations are good screening tools that can better assist in the early diagnosis of Alzheimer's disease. Graphical Abstract.

Insight and equality: A systematic review and meta-analysis of socio-demographic associations

BACKGROUND

Insight into illness is often used in clinical and legal contexts, for example, as evidence of decision-making capacity. However, it is unclear whether this disadvantages certain groups protected under equality legislation. To our knowledge, this question has yet to be addressed systematically. Therefore, the present study reviews empirical studies that look at the relationship between insight and sociodemographic variables.

METHODS

A systematic search of six bibliographic databases (CENTRAL, CINAHL, Cochrane Library of Systematic Reviews, EMBASE, MEDLINE and PsycINFO) was conducted, which yielded 6,192 results. Study characteristics and outcomes (associations between insight and socio-demographic variables) were then extracted from 207 eligible studies. This included protected characteristics under the Equality Act (2010): age, sex, ethnicity, marital status and religion. Weighted confidence estimates were calculated and relevant moderators included in a random effects meta-analysis. A study protocol was registered prospectively on PROSPERO, ID: CRD42019120117.

RESULTS

Insight was not strongly associated with any sociodemographic variable. Better insight was weakly but significantly associated with white ethnicity, being employed, younger age and more years of education. The age associations were mostly explained by relevant moderating variables. For people with schizophrenia, the associations between sociodemographic variables and insight were comparable to associations with decision making capacity.

CONCLUSIONS

Our results suggest that insight is not strongly associated with any sociodemographic variables. Further research is needed to clarify potential associations, particularly with non-white ethnicity and proxies for social support.

Interferon beta attenuates recognition memory impairment and improves brain glucose uptake in a rat model of Alzheimer's disease: Involvement of mitochondrial biogenesis and PI3K pathway

Interferon beta (IFNβ) is a cytokine with anti-apoptotic and anti-inflammatory properties, and its beneficial effects on Alzheimer's disease (AD) have been recently shown. The alterations in cerebral glucose uptake are closely linked to memory deficit and AD progression. The current study was designed to determine if IFNβ can improve recognition memory and brain glucose uptake in a rat model of AD. The lentiviruses expressing mutant human amyloid precursor protein were injected bilaterally to the rat hippocampus. From day 23 after virus injection, rats were intranasally treated with recombinant IFNβ protein (68,000 IU/rat) every other day until day 50. Recognition memory performance was evaluated by novel object recognition test on days 46-49. The 18F-2- fluoro-deoxy-d-glucose positron emission tomography (18F-FDG-PET) was used to determine changes in brain glucose metabolism on day 50. The expression of the PI3K/Akt pathway components, neurotrophins and mitochondrial biogenesis factors were also measured by qPCR in the hippocampus. Our results showed that IFNβ treatment improves recognition memory performance in parallel with increased glucose uptake and neuronal survival in the hippocampus of the AD rats. The neuroprotective effect of IFNβ could be attributed, at least partly, to activation of PI3K-Akt-mTOR signaling pathway, increased expression of NGF, and mitochondrial biogenesis. Taken together, our findings suggest the therapeutic potential of IFNβ for AD.

Importance of CSF-based Aβ clearance with age in humans increases with declining efficacy of blood-brain barrier/proteolytic pathways

The kinetics of amyloid beta turnover within human brain is still poorly understood. We previously found a dramatic decline in the turnover of Aβ peptides in normal aging. It was not known if brain interstitial fluid/cerebrospinal fluid (ISF/CSF) fluid exchange, CSF turnover, blood-brain barrier function or proteolysis were affected by aging or the presence of β amyloid plaques. Here, we describe a non-steady state physiological model developed to decouple CSF fluid transport from other processes. Kinetic parameters were estimated using: (1) MRI-derived brain volumes, (2) stable isotope labeling kinetics (SILK) of amyloid-β peptide (Aβ), and (3) lumbar CSF Aβ concentration during SILK. Here we show that changes in blood-brain barrier transport and/or proteolysis were largely responsible for the age-related decline in Aβ turnover rates. CSF-based clearance declined modestly in normal aging but became increasingly important due to the slowing of other processes. The magnitude of CSF-based clearance was also lower than that due to blood-brain barrier function plus proteolysis. These results suggest important roles for blood-brain barrier transport and proteolytic degradation of Aβ in the development Alzheimer’s Disease in humans.

To understand if brain interstitial fluid/cerebrospinal fluid (ISF/CSF) exchange, CSF turnover, blood-brain barrier function or proteolysis were affected by aging or the presence of β amyloid plaques, Elbert et al. develop a non-steady state physiological model using MRI-derived brain volumes, stable isotope labeling kinetics of Aβ, and lumbar CSF Aβ concentration. Their model suggests an important role for blood-brain barrier transport and proteolytic degradation of Aβ in the development Alzheimer’s Disease in humans.

Sex differences in Alzheimer's disease: metabolic reprogramming and therapeutic intervention

Studies on the sporadic form of Alzheimer's disease (AD) have revealed three classes of risk factor: age, genetics, and sex. These risk factors point to a metabolic dysregulation as the origin of AD. Adaptive alterations in cerebral metabolism are the rationale for the Metabolic Reprogramming (MR) Theory of the origin of AD. The theory contends that the progression toward AD involves three adaptive events: a hypermetabolic phase, a prolonged prodromal phase, and a metabolic collapse. This article exploits the MR Theory to elucidate the effect of hormonal changes on the origin and progression of AD in women. The theory invokes bioenergetic signatures of the menopausal transition to propose sex-specific diagnostic program and therapeutic strategies.

Impairments in Brain Bioenergetics in Aging and Tau Pathology: A Chicken and Egg Situation?

The brain is the most energy-consuming organ of the body and impairments in brain energy metabolism will affect neuronal functionality and viability. Brain aging is marked by defects in energetic metabolism. Abnormal tau protein is a hallmark of tauopathies, including Alzheimer's disease (AD). Pathological tau was shown to induce bioenergetic impairments by affecting mitochondrial function. Although it is now clear that mutations in the tau-coding gene lead to tau pathology, the causes of abnormal tau phosphorylation and aggregation in non-familial tauopathies, such as sporadic AD, remain elusive. Strikingly, both tau pathology and brain hypometabolism correlate with cognitive impairments in AD. The aim of this review is to discuss the link between age-related decrease in brain metabolism and tau pathology. In particular, the following points will be discussed: (i) the common bioenergetic features observed during brain aging and tauopathies; (ii) how age-related bioenergetic defects affect tau pathology; (iii) the influence of lifestyle factors known to modulate brain bioenergetics on tau pathology. The findings compiled here suggest that age-related bioenergetic defects may trigger abnormal tau phosphorylation/aggregation and cognitive impairments after passing a pathological threshold. Understanding the effects of aging on brain metabolism may therefore help to identify disease-modifying strategies against tau-induced neurodegeneration.

Brain SPECT as a Biomarker of Neurodegeneration in Dementia in the Era of Molecular Imaging: Still a Valid Option?

Biomarkers are playing a progressively leading role in both clinical practice and scientific research in dementia. Although amyloid and tau biomarkers have gained ground in the clinical community in recent years, neurodegeneration biomarkers continue to play a key role due to their ability to identify different patterns of brain involvement that sign the transition between asymptomatic and symptomatic stages of the disease with high sensitivity and specificity. Both ¹⁸F-FDG positron emission tomography (PET) and perfusion single photon emission computed tomography (SPECT) have proved useful to reveal the functional alterations underlying various neurodegenerative diseases. Although the focus of nuclear neuroimaging has shifted to PET, the lower cost and wider availability of SPECT make it a still valid alternative for the study of patients with dementia. This review discusses the principles of both techniques, compares their diagnostic performance for the diagnosis of neurodegenerative diseases and highlights the role of SPECT to characterize patients from low- and middle-income countries, where special care of additional costs is particularly needed to meet the new recommendations for the diagnosis and characterization of patients with dementia.

Experimental Evidence of the Benefits of Acupuncture for Alzheimer's Disease: An Updated Review

As the global population ages, the prevalence of Alzheimer's disease (AD), the most common form of dementia, is also increasing. At present, there are no widely recognized drugs able to ameliorate the cognitive dysfunction caused by AD. The failure of several promising clinical trials in recent years has highlighted the urgent need for novel strategies to both prevent and treat AD. Notably, a growing body of literature supports the efficacy of acupuncture for AD. In this review, we summarize the previously reported mechanisms of acupuncture's beneficial effects in AD, including the ability of acupuncture to modulate Aβ metabolism, tau phosphorylation, neurotransmitters, neurogenesis, synapse and neuron function, autophagy, neuronal apoptosis, neuroinflammation, cerebral glucose metabolism, and brain responses. Taken together, these findings suggest that acupuncture provides therapeutic effects for AD.

Ketones improves Apolipoprotein E4-related memory deficiency via sirtuin 3

Background: Apolipoprotein E4 (ApoE4) is the major genetic risk factor of Alzheimer’s disease (AD). ApoE4 carriers have cerebral hypometabolism which is thought as a harbinger of AD. Our previous studies indicated ketones improved mitochondria energy metabolism via sirtuin 3 (Sirt3). However, it is unclear whether ketones upregulate Sirt3 and improve ApoE4-related learning and memory deficits.

Results: Ketones improved learning and memory abilities of ApoE4 mice but not ApoE3 mice. Sirt3, synaptic proteins, the NAD⁺/ NADH ratio, and ATP production were significantly increased in the hippocampus and the cortex from ketone treatment.

Methods: Human ApoE3 and ApoE4 transgenic mice (9-month-old) were treated with either ketones or normal saline by daily subcutaneous injections for 3 months (ketones, beta-hydroxybutyrate (BHB): 600 mg/kg/day; acetoacetate (ACA): 150 mg/kg/day). Learning and memory ability of these mice were assessed. Sirt3 protein, synaptic proteins (PSD95, Synaptophysin), the NAD⁺/ NADH ratio, and ATP levels were measured in the hippocampus and the cortex.

Conclusion: Our current studies suggest that ketones improve learning and memory abilities of ApoE4 transgenic mice. Sirt3 may mediate the neuroprotection of ketones by increasing neuronal energy metabolism in ApoE4 transgenic mice. This provides the foundation for Sirt3’s potential role in the prevention and treatment of AD.

Associations of [18F]-APN-1607 Tau PET Binding in the Brain of Alzheimer's Disease Patients With Cognition and Glucose Metabolism

Molecular imaging of tauopathies is complicated by the differing specificities and off-target binding properties of available radioligands for positron emission tomography (PET). [18F]-APN-1607 ([18F]-PM-PBB3) is a newly developed PET tracer with promising properties for tau imaging. We aimed to characterize the cerebral binding of [18F]-APN-1607 in Alzheimer's disease (AD) patients compared to normal control (NC) subjects. Therefore, we obtained static late frame PET recordings with [18F]-APN-1607 and [18F]-FDG in patients with a clinical diagnosis of AD group, along with an age-matched NC group ([18F]-APN-1607 only). Using statistical parametric mapping (SPM) and volume of interest (VOI) analyses of the reference region normalized standardized uptake value ratio maps, we then tested for group differences and relationships between both PET biomarkers, as well as their associations with clinical general cognition. In the AD group, [18F]-APN-1607 binding was elevated in widespread cortical regions (P < 0.001 for VOI analysis, familywise error-corrected P < 0.01 for SPM analysis). The regional uptake in AD patients correlated negatively with Mini-Mental State Examination score (frontal lobe: R = -0.632, P = 0.004; temporal lobe: R = -0.593, P = 0.008; parietal lobe: R = -0.552, P = 0.014; insula: R = -0.650, P = 0.003; cingulum: R = -0.665, P = 0.002) except occipital lobe (R = -0.417, P = 0.076). The hypometabolism to [18F]-FDG PET in AD patients also showed negative correlations with regional [18F]-APN-1607 binding in some signature areas of AD (temporal lobe: R = -0.530, P = 0.020; parietal lobe: R = -0.637, P = 0.003; occipital lobe: R = -0.567, P = 0.011). In conclusion, our results suggested that [18F]-APN-1607 PET sensitively detected tau deposition in AD and that individual tauopathy correlated with impaired cerebral glucose metabolism and cognitive function.

Effects of Acupuncture on Alzheimer's Disease: Evidence from Neuroimaging Studies

As the worldwide population ages, the prevalence of Alzheimer's disease (AD) increases. However, the results of promising medications have been unsatisfactory. Chinese acupuncture has a long history of treating dementia, but lack of evidence from well-designed randomized controlled trials that validate its efficacy and safety, as well as its lack of clear underlying mechanisms, contribute to its limited application in clinical practice. In recent years, brain imaging technologies, such as functional magnetic resonance imaging and positron emission tomography, have been used to assess brain responses to acupuncture in a dynamic, visual, and objective way. These techniques are frequently used to explore neurological mechanisms of responses to acupuncture in AD and provide neuroimaging evidence as well as starting points to elucidate the possible mechanisms. This review summarizes the existing brain imaging evidence that explains the effects of acupuncture for AD and analyzes brain responses to acupuncture at cognitive-related acupoints [Baihui (GV 20), Shenmen (HT 7), Zusanli (ST 36), Neiguan (PC 6), and Taixi (KI 3)] from perspectives of acupoint specificity and acupoint combinations. Key issues and directions to consider in future studies are also put forward. This review should deepen our understanding of how brain imaging studies can be used to explore the underlying mechanisms of acupuncture in AD.

Association Between Hippocampus, Thalamus, and Caudate in Mild Cognitive Impairment APOEε4 Carriers: A Structural Covariance MRI Study

Objective: Although, the apolipoprotein E (APOE) genotype is widely recognized as one of the most important risk factors for Alzheimer's disease (AD) development, the neural mechanisms by which the ε4 allele promotes the AD occurring remain under debate. The aim of this study was to evaluate neurobiological effects of the APOE-genotype on the pattern of the structural covariance in mild cognitive impairment (MCI) subjects. Methods: We enrolled 95 MCI subjects and 49 healthy controls. According to APOE-genotype, MCI subjects were divided into three groups: APOEε4 non-carriers (MCIε4-/-, n = 55), APOEε4 heterozygous carriers (MCIε4+/-, n = 31), and APOEε4 homozygous carriers (MCIε4+/+, n = 9) while all controls were APOEε4 non-carriers. In order to explore their brain structural pattern, T1-weighted anatomical brain 1.5-T MRI scans were collected. A whole-brain voxel-based morphometry analysis was performed, and all significant regions (p < 0.05 family-wise error, whole brain) were selected as a region of interest for the structural covariance analysis. Moreover, in order to evaluate the progression of the disease, a clinical follow-up was performed for 2 years. Results: The F-test showed in voxel-based morphometry analysis a strong overall difference among the groups in the middle frontal and temporal gyri and in the bilateral hippocampi, thalami, and parahippocampal gyri, with a grading in the atrophy in these latter three structures according to the following order: MCIε4+/+ > MCIε4+/- > MCIε4-/- > controls. Structural covariance analysis revealed a strong structural association between the left thalamus and the left caudate and between the right hippocampus and the left caudate (p < 0.05 family-wise error, whole brain) in the MCIε4 carrier groups (MCIε4+/+ > MCIε4+/-), whereas no significant associations were observed in MCIε4-/- subjects. Of note, the 38% of MCIs enrolled in this study developed AD within 2 years of follow-up. Conclusion: This study improves the knowledge on neurobiological effect of APOE ε4 in early pathophysiological phenomena underlying the MCI-to-AD evolution, as our results demonstrate changes in the structural association between hippocampal formation and thalamo-striatal connections occurring in MCI ε4 carriers. Our results strongly support the role of subcortical structures in MCI ε4 carriers and open a clinical window on the role of these structures as early disease markers.

Sirtuin 3 attenuates amyloid-β induced neuronal hypometabolism

Alzheimer’s disease (AD) is manifested by regional cerebral hypometabolism. Sirtuin 3 (Sirt3) is localized in mitochondria and regulates cellular metabolism, but the role of Sirt3 in AD-related hypometabolism remains elusive. We used expression profiling and weighted gene co-expression network analysis (WGCNA) to analyze cortical neurons from a transgenic mouse model of AD (APPSwInd). Based on WGCNA results, we measured NAD⁺ level, NAD⁺/ NADH ratio, Sirt3 protein level and its deacetylation activity, and ATP production across both in vivo and in vitro models. To investigate the effect of Sirt3 on amyloid-β (Aβ)-induced mitochondria damage, we knocked down and over-expressed Sirt3 in hippocampal cells. WGCNA revealed Sirt3 as a key player in Aβ-related hypometabolism. In APP mice, the NAD⁺ level, NAD⁺/ NADH ratio, Sirt3 protein level and activity, and ATP production were all reduced compared to the control. As a result, learning and memory performance were impaired in 9-month-old APP mice compared to wild type controls. Using hippocampal HT22 cells model, Sirt3 overexpression increased Sirt3 deacetylation activity, rescued mitochondria function, and salvaged ATP production, which were damaged by Aβ. Sirt3 plays an important role in regulating Aβ-induced cerebral hypometabolism. This study suggests a potential direction for AD therapy.

Age-Related Changes in the Plasticity of Neural Networks Assessed by Transcranial Magnetic Stimulation With Electromyography: A Systematic Review and Meta-Analysis

Objective: The excitability of cerebral cortical cells, neural pathway, and neural networks, as well as their plasticity, are key to our exploration of age-related changes in brain structure and function. The combination of transcranial magnetic stimulation (TMS) with electromyography (EMG) can be applied to the primary motor cortex; it activates the underlying neural group and passes through the corticospinal pathway, which can be quantified using EMG. This meta-analysis aimed to analyze changes in cortical excitability and plasticity in healthy elderly individuals vs. young individuals through TMS-EMG.

Methods: The Cochrane Library, Medline, and EMBASE databases were searched to identify eligible trials published from database inception to June 3, 2019. The Cochrane Risk of Bias Tool and improved Jadad scale were used to assess the methodological quality. A meta-analysis of the comparative effects was conducted using the Review Manager 5.3 software and Stata 14.0 software.

Results: The pooled results revealed that the resting motor threshold values in the elderly group were markedly higher than those reported in the young group (mean difference [MD]: −2.35; 95% confidence interval [CI]: −3.69 to −1.02]; p < (0.00001). The motor evoked potential amplitude significantly reduced in the elderly group vs. the young group (MD: 0.18; 95% CI: 0.09–0.27; p < 0.0001). Moreover, there was significantly longer motor evoked potential latency in the elderly group (MD: −1.07; 95% CI: −1.77 to −0.37]; p =(0.003). There was no significant difference observed in the active motor threshold between the elderly and young groups (MD: −1.52; 95% CI: −3.47 to −0.42]; p =(0.13). Meanwhile, only two studies reported the absence of adverse events.

Conclusion: We found that the excitability of the cerebral cortex declined in elderly individuals vs. young individuals. The findings of the present analysis should be considered with caution owing to the methodological limitations in the included trials. Additional high-quality studies are warranted to validate our findings.

Ketogenic Diet in Alzheimer's Disease

At present, the prevalence of Alzheimer's disease, a devastating neurodegenerative disorder, is increasing. Although the mechanism of the underlying pathology is not fully uncovered, in the last years, there has been significant progress in its understanding. This includes: Progressive deposition of amyloid β-peptides in amyloid plaques and hyperphosphorylated tau protein in intracellular as neurofibrillary tangles; neuronal loss; and impaired glucose metabolism. Due to a lack of effective prevention and treatment strategy, emerging evidence suggests that dietary and metabolic interventions could potentially target these issues. The ketogenic diet is a very high-fat, low-carbohydrate diet, which has a fasting-like effect bringing the body into a state of ketosis. The presence of ketone bodies has a neuroprotective impact on aging brain cells. Moreover, their production may enhance mitochondrial function, reduce the expression of inflammatory and apoptotic mediators. Thus, it has gained interest as a potential therapy for neurodegenerative disorders like Alzheimer's disease. This review aims to examine the role of the ketogenic diet in Alzheimer's disease progression and to outline specific aspects of the nutritional profile providing a rationale for the implementation of dietary interventions as a therapeutic strategy for Alzheimer's disease.

Prognosis of conversion of mild cognitive impairment to Alzheimer's dementia by voxel-wise Cox regression based on FDG PET data

Aim

The value of ¹⁸F-fluorodeoxyglucose (FDG) PET for the prognosis of conversion from mild cognitive impairment (MCI) to Alzheimer's dementia (AD) is controversial. In the present work, the identification of cerebral metabolic patterns with significant prognostic value for conversion of MCI patients to AD is investigated with voxel-based Cox regression, which in contrast to common categorical comparisons also utilizes time information.

Methods

FDG PET data of 544 MCI patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were randomly split into two equally-sized datasets (training and test). Within a median follow-up duration of 47 months (95% CI: 46–48 months) 181 patients developed AD. In the training dataset, voxel-wise Cox regressions were used to identify regions associated with conversion of MCI to AD. These were compared to regions identified by a classical group comparison (analysis of covariance (ANCOVA) with statistical parametric mapping (SPM) 8) between converters and non-converters (both adjusted for apolipoprotein E (APOE) genotype, mini-mental state examination (MMSE) score, age, sex and education). In the test dataset, normalized FDG uptake within significant brain regions from voxel-wise Cox- and ANCOVA analyses (Cox- and ANCOVA- regions of interest (ROI), respectively) and clinical variables APOE status, MMSE score and education were tested in different Cox models (adjusted for age, sex) including: (1) only clinical variables, (2) only normalized FDG uptake in ANCOVA-ROI, (3) only normalized FDG uptake from Cox-ROI, (4) clinical variables plus FDG uptake in ANCOVA-ROI, (5) clinical variables plus FDG uptake from Cox-ROI.

Results

Conversion-related regions with relative hypometabolism comprised parts of the temporo-parietal and posterior cingulate cortex/precuneus for voxel-wise ANCOVA, plus frontal regions for voxel-wise Cox regression (both p < .01, false discovery rate (FDR) corrected). The clinical-only model (1) and the models based on normalized FDG uptake from Cox-ROI only (2) and ANCOVA-ROI only (3) all significantly predicted conversion to AD (Wald Test (WT): p < .001). The clinical model (1) was significantly improved by adding imaging information in model (4) (Akaike information criterion (AIC) relative likelihood (RL) (1) vs (4): RL < 0.018). There were no significant differences between models (2) and (3), as well as (4) and (5).

Conclusions

Voxel-wise Cox regression identifies conversion-related patterns of cerebral glucose metabolism, but is not superior to classical group contrasts in this regard. With imaging information from both FDG PET patterns, the prediction of conversion to AD was improved.

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Voxel-wise Cox regression identifies regions relevant for development AD.

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Hypometabolism of these regions poses a significant hazard for AD development.

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Inclusion of FDG PET data improves the accuracy of prognosis significantly.

Multi-Objective Genetic Algorithms to Find Most Relevant Volumes of the Brain Related to Alzheimer's Disease and Mild Cognitive Impairment

Computer-Aided Diagnosis (CAD) represents a relevant instrument to automatically classify between patients with and without Alzheimer's Disease (AD) using several actual imaging techniques. This study analyzes the optimization of volumes of interest (VOIs) to extract three-dimensional (3D) textures from Magnetic Resonance Image (MRI) in order to diagnose AD, Mild Cognitive Impairment converter (MCIc), Mild Cognitive Impairment nonconverter (MCInc) and Normal subjects. A relevant feature of the proposed approach is the use of 3D features instead of traditional two-dimensional (2D) features, by using 3D discrete wavelet transform (3D-DWT) approach for performing feature extraction from T-1 weighted MRI. Due to the high number of coefficients when applying 3D-DWT to each of the VOIs, a feature selection algorithm based on mutual information is used, as is the minimum Redundancy Maximum Relevance (mRMR) algorithm. Region optimization has been performed in order to discover the most relevant regions (VOIs) in the brain with the use of Multi-Objective Genetic Algorithms, being one of the objectives to be optimize the accuracy of the system. The error index of the system is computed by the confusion matrix obtained by the multi-class support vector machine (SVM) classifier. Principal Component Analysis (PCA) is used with the purpose of reducing the number of features to the classifier. The cohort of subjects used in the study consisted of 296 different patients. A first group of 206 patients was used to optimize VOI selection and another group of 90 independent subjects (that did not belong to the first group) was used to test the solutions yielded by the genetic algorithm. The proposed methodology obtains excellent results in multi-class classification achieving accuracies of 94.4% and also extracting significant information on the location of the most relevant points of the brain. This suggests that the proposed method could aid in the research of other neurodegenerative diseases, improving the accuracy of the diagnosis and finding the most relevant regions of the brain associated with them.

PET Imaging of Tau Pathology and Relationship to Amyloid, Longitudinal MRI, and Cognitive Change in Down Syndrome: Results from the Down Syndrome Biomarker Initiative (DSBI)

BACKGROUND

Adults with Down syndrome (DS) represent an enriched population for the development of Alzheimer's disease (AD), which could aid the study of therapeutic interventions, and in turn, could benefit from discoveries made in other AD populations.

OBJECTIVES

1) Understand the relationship between tau pathology and age, amyloid deposition, neurodegeneration (MRI and FDG PET), and cognitive and functional performance; 2) detect and differentiate AD-specific changes from DS-specific brain changes in longitudinal MRI.

METHODS

Twelve non-demented adults, ages 30 to 60, with DS were enrolled in the Down Syndrome Biomarker Initiative (DSBI), a 3-year, observational, cohort study to demonstrate the feasibility of conducting AD intervention/prevention trials in adults with DS. We collected imaging data with 18F-AV-1451 tau PET, AV-45 amyloid PET, FDG PET, and volumetric MRI, as well as cognitive and functional measures and additional laboratory measures.

RESULTS

All amyloid negative subjects imaged were tau-negative. Among the amyloid positive subjects, three had tau in regions associated with Braak stage VI, two at stage V, and one at stage II. Amyloid and tau burden correlated with age. The MRI analysis produced two distinct volumetric patterns. The first differentiated DS from normal (NL) and AD, did not correlate with age or amyloid, and was longitudinally stable. The second pattern reflected AD-like atrophy and differentiated NL from AD. Tau PET and MRI atrophy correlated with several cognitive and functional measures.

CONCLUSIONS

Tau accumulation is associated with amyloid positivity and age, as well as with progressive neurodegeneration measurable using FDG and MRI. Tau correlates with cognitive decline, as do AD-specific hypometabolism and atrophy.

Clinical validity of brain fluorodeoxyglucose positron emission tomography as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework

The use of Alzheimer's disease (AD) biomarkers is supported in diagnostic criteria, but their maturity for clinical routine is still debated. Here, we evaluate brain fluorodeoxyglucose positron emission tomography (FDG PET), a measure of cerebral glucose metabolism, as a biomarker to identify clinical and prodromal AD according to the framework suggested for biomarkers in oncology, using homogenous criteria with other biomarkers addressed in parallel reviews. FDG PET has fully achieved phase 1 (rational for use) and most of phase 2 (ability to discriminate AD subjects from healthy controls or other forms of dementia) aims. Phase 3 aims (early detection ability) are partly achieved. Phase 4 studies (routine use in prodromal patients) are ongoing, and only preliminary results can be extrapolated from retrospective observations. Phase 5 studies (quantify impact and costs) have not been performed. The results of this study show that specific efforts are needed to complete phase 3 evidence, in particular comparing and combining FDG PET with other biomarkers, and to properly design phase 4 prospective studies as a basis for phase 5 evaluations.

Early identification of MCI converting to AD: a FDG PET study

PURPOSE

Mild cognitive impairment (MCI) is a transitional pathological stage between normal ageing (NA) and Alzheimer's disease (AD). Although subjects with MCI show a decline at different rates, some individuals remain stable or even show an improvement in their cognitive level after some years. We assessed the accuracy of FDG PET in discriminating MCI patients who converted to AD from those who did not.

METHODS

FDG PET was performed in 42 NA subjects, 27 MCI patients who had not converted to AD at 5 years (nc-MCI; mean follow-up time 7.5 ± 1.5 years), and 95 MCI patients who converted to AD within 5 years (MCI-AD; mean conversion time 1.8 ± 1.1 years). Relative FDG uptake values in 26 meta-volumes of interest were submitted to ANCOVA and support vector machine analyses to evaluate regional differences and discrimination accuracy.

RESULTS

The MCI-AD group showed significantly lower FDG uptake values in the temporoparietal cortex than the other two groups. FDG uptake values in the nc-MCI group were similar to those in the NA group. Support vector machine analysis discriminated nc-MCI from MCI-AD patients with an accuracy of 89% (AUC 0.91), correctly detecting 93% of the nc-MCI patients.

CONCLUSION

In MCI patients not converting to AD within a minimum follow-up time of 5 years and MCI patients converting within 5 years, baseline FDG PET and volume-based analysis identified those who converted with an accuracy of 89%. However, further analysis is needed in patients with amnestic MCI who convert to a dementia other than AD.

Disentangling the neural correlates of corticobasal syndrome and corticobasal degeneration with systematic and quantitative ALE meta-analyses

Corticobasal degeneration is a scarce neurodegenerative disease, which can only be confirmed by histopathological examination. Reported to be associated with various clinical syndromes, its classical clinical phenotype is corticobasal syndrome. Due to the rareness of corticobasal syndrome/corticobasal degeneration and low numbers of patients included in single studies, meta-analyses are particularly suited to disentangle features of the clinical syndrome and histopathology. Using PubMed, we identified 11 magnetic resonance imaging studies measuring atrophy in 22 independent cohorts with 200 patients contrasted to 318 healthy controls. The anatomic likelihood estimation method was applied to reveal affected brain regions across studies. Corticobasal syndrome was related to gray matter loss in the basal ganglia/thalamus, frontal, parietal, and temporal lobes. In corticobasal degeneration patients, atrophy in the thalamus, frontal, temporal, and occipital lobes were found. Finally, in a conjunction analysis, the bilateral thalamus, the bilateral posterior frontomedian cortex, posterior midcingulate cortex and premotor area/supplementary motor area, and the left posterior superior and middle frontal gyrus/precentral gyrus were identified as areas associated with both, corticobasal syndrome and corticobasal degeneration. Remarkably, atrophy in the premotor area/supplementary motor area and posterior midcingulate/frontomedian cortex seems to be specific for corticobasal syndrome/corticobasal degeneration, whereas atrophy in the thalamus and the left posterior superior and middle frontal gyrus/precentral gyrus are also associated with other neurodegenerative diseases according to anatomic likelihood estimation method meta-analyses. Our study creates a new conceptual framework to understand, and distinguish between clinical features (corticobasal syndrome) and histopathological findings (corticobasal degeneration) by powerful data-driven meta-analytic approaches. Furthermore, it proposes regional-specific atrophy as an imaging biomarker for diagnosis of corticobasal syndrome/corticobasal degeneration ante-mortem.

Brain imaging could be used to distinguish between patients with corticobasal degeneration (CBD) and Parkinson's disease (PD). CBD is a rare condition caused by the gradual loss of brain cells in areas of the brain that link thinking to movement. The clinical features of CBD, referred to as corticobasal syndrome (CBS), are similar to those of patients with PD, but they progress differently. To aid earlier and more accurate diagnosis, Franziska Albrecht, at the Max Planck Institute for Human Cognitive and Brain Sciences, Germany, and colleagues reviewed 11 magnetic resonance imaging studies to find brain areas that are specifically affected in CBS/CBD patients. They show that cell loss in specific regions of the motor areas and frontomedian cortex is a hallmark of CBS/CBD, whereas cell loss in the thalamus and parts of the frontal/precentral gyrus were associated with other neurodegenerative diseases.

Medicare Expenditure Correlates of Atrophy and Cerebrovascular Disease in Older Adults

Background/Study Context: Magnetic resonance imaging (MRI) markers of cerebrovascular disease and atrophy are common in older adults and are associated with cognitive and medical burden. However, the extent to which they are related to health care expenditures has not been examined. We studied whether increased Medicare expenditures were associated with brain markers of atrophy and cerebrovascular disease in older adults.

METHODS

A subset of participants (n = 592; mean age = 80 years; 66% women) from the Washington Heights Inwood Columbia Aging Project (WHICAP), a community-based observational study of aging in upper Manhattan, received high-resolution MRI and had Medicare expenditure data on file. We examined the relationship of common markers of cerebrovascular disease (i.e., white matter hyperintensities and presence of infarcts) and atrophy (i.e., whole brain and hippocampal volume) with Medicare expenditure data averaged over a 10-year period. Main outcome measures were (a) mean Medicare payment per year across the 10-year interval; (b) mean payment for outpatient care per year; and (c) mean payment for inpatient care per year of visit. In addition, we calculated the ratio of mean inpatient spending to mean outpatient spending as well as the ratio of mean inpatient spending to mean total Medicare spending.

RESULTS

Increased Medicare spending was associated with higher white matter hyperintensity volume, presence of cerebral infarcts, and smaller total brain volume. When examining specific components of Medicare expenditures, we found that inpatient spending was strongly associated with white matter hyperintensity volume and that increased ratios of inpatient to outpatient and inpatient to total spending were associated with infarcts.

CONCLUSION

Medicare costs are related to common markers of "silent" cerebrovascular disease and atrophy.

Behavioral Changes and Hippocampus Glucose Metabolism in APP/PS1 Transgenic Mice via Electro-acupuncture at Governor Vessel Acupoints

Objective: Investigating the effects of electro-acupuncture (EA) treatment on mice with Alzheimer’s disease (AD), using Morris water maze (MWM) for spatial learning and memory behavior tests combined with micro-positron emission tomography (micro-PET) imaging for glucose metabolism in hippocampus.

Methods: Thirty seven-month-old APP/PS1 mice were randomly divided into AD Model group (AD group), medicine group (M group) and EA group, C57BL/6 mice were used for Normal control group (N group), n = 10 in each group. Mice in M group received donepezil intervention by gavage with dose at 0.92 mg/kg. EA was applied at Baihui (GV20) and Yintang (GV29) acupoints for 20 min then pricked at Shuigou (GV26) acupoint, while mice in N, M and AD groups were received restriction for 20 min, with all treatment administrated once a day for 15 consecutive days. After the treatment, MWM was performed to observe behavioral changes in mice, then hippocampus glucose metabolism level was tested by micro-PET imaging.

Results: Compared with that of AD group, the escape latency of M and EA groups declined significantly (P < 0.01), while the proportion of the platform quadrant swimming distance in total swimming distance showed an obvious increase (P < 0.01), and EA group occupied a higher percentage than that in M group. The micro-PET imaging showed that mice in AD group performed a lower glucose metabolic rate in hippocampus compared with N group (P < 0.01). Both M and EA groups presented a significant higher injected dose compared with AD group (P < 0.01), and the uptake rate of EA group was higher than M group.

Conclusion: Both donepezil and EA have therapeutic effects on AD mice. To a certain extent, EA shows a better efficacy in treatment of AD by improving the spatial learning and memory ability, while also enhancing glucose metabolism in hippocampus.

Long-term acupuncture treatment has a multi-targeting regulation on multiple brain regions in rats with Alzheimer's disease: a positron emission tomography study

The acute effect of acupuncture on Alzheimer's disease, i.e., on brain activation during treatment, has been reported. However, the effect of long-term acupuncture on brain activation in Alzheimer's disease is unclear. Therefore, in this study, we performed long-term needling at Zusanli (ST36) or a sham point (1.5 mm lateral to ST36) in a rat Alzheimer's disease model, for 30 minutes, once per day, for 30 days. The rats underwent ¹⁸F-fluorodeoxyglucose positron emission tomography scanning. Positron emission tomography images were processed with SPM2. The brain areas activated after needling at ST36 included the left hippocampus, the left orbital cortex, the left infralimbic cortex, the left olfactory cortex, the left cerebellum and the left pons. In the sham-point group, the activated regions were similar to those in the ST36 group. However, the ST36 group showed greater activation in the cerebellum and pons than the sham-point group. These findings suggest that long-term acupuncture treatment has targeted regulatory effects on multiple brain regions in rats with Alzheimer's disease.

Regional age differences in gray matter diffusivity among healthy older adults

Aging is associated with microstructural changes in brain tissue that can be visualized using diffusion tensor imaging (DTI). While previous studies have established age-related changes in white matter (WM) diffusion using DTI, the impact of age on gray matter (GM) diffusion remains unclear. The present study utilized DTI metrics of mean diffusivity (MD) to identify age differences in GM/WM microstructure in a sample of healthy older adults (N = 60). A secondary aim was to determine the functional significance of whole-brain GM/WM MD on global cognitive function using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Participants were divided into three age brackets (ages 50-59, 60-69, and 70+) to examine differences in MD and cognition by decade. MD was examined bilaterally in the frontal, temporal, parietal, and occipital lobes for the primary analyses and an aggregate measure of whole-brain MD was used to test relationships with cognition. Significantly higher MD was observed in bilateral GM of the temporal and parietal lobes, and in right hemisphere WM of the frontal and temporal lobes of older individuals. The most robust differences in MD were between the 50-59 and 70+ age groups. Higher whole-brain GM MD was associated with poorer RBANS performance in the 60-69 age group. Results suggest that aging has a significant and differential impact on GM/WM diffusion in healthy older adults, which may explain a modest degree of cognitive variability at specific time points during older adulthood.

Brain imaging evidence of early involvement of subcortical regions in familial and sporadic Alzheimer's disease

Recent brain imaging studies have found changes in subcortical regions in presymptomatic autosomal dominant Alzheimer's disease (ADAD). These regions are also affected in sporadic Alzheimer's disease (sAD), but whether such changes are seen in early-stage disease is still uncertain. In this review, we discuss imaging studies published in the past 12 years that have found evidence of subcortical involvement in early-stage ADAD and/or sAD. Several papers have reported amyloid deposition in the striatum of presymptomatic ADAD mutation carriers, prior to amyloid deposition elsewhere. Altered caudate volume has also been implicated in early-stage ADAD, but findings have been variable. Less is known about subcortical involvement in sAD: the thalamus and striatum have been found to be atrophied in symptomatic patients, but their involvement in the preclinical phase remains unclear, in part due to the difficulties of studying this stage in sporadic disease. Longitudinal imaging studies comparing ADAD mutation carriers with individuals at high-risk for sAD may be needed to elucidate the significance of subcortical involvement in different AD clinical stages.

Estimating Intracranial Volume in Brain Research: An Evaluation of Methods

Intracranial volume (ICV) is a standard measure often used in morphometric analyses to correct for head size in brain studies. Inaccurate ICV estimation could introduce bias in the outcome. The current study provides a decision aid in defining protocols for ICV estimation across different subject groups in terms of sampling frequencies that can be optimally used on the volumetric MRI data, and type of software most suitable for use in estimating the ICV measure. Four groups of 53 subjects are considered, including adult controls (AC, adults with Alzheimer's disease (AD), pediatric controls (PC) and group of pediatric epilepsy subjects (PE). Reference measurements were calculated for each subject by manually tracing intracranial cavity without sub-sampling. The reliability of reference measurements were assured through intra- and inter- variation analyses. Three publicly well-known software packages (FreeSurfer Ver. 5.3.0, FSL Ver. 5.0, SPM8 and SPM12) were examined in their ability to automatically estimate ICV across the groups. Results on sub-sampling studies with a 95 % confidence showed that in order to keep the accuracy of the inter-leaved slice sampling protocol above 99 %, sampling period cannot exceed 20 mm for AC, 25 mm for PC, 15 mm for AD and 17 mm for the PE groups. The study assumes a priori knowledge about the population under study into the automated ICV estimation. Tuning of the parameters in FSL and the use of proper atlas in SPM showed significant reduction in the systematic bias and the error in ICV estimation via these automated tools. SPM12 with the use of pediatric template is found to be a more suitable candidate for PE group. SPM12 and FSL subjected to tuning are the more appropriate tools for the PC group. The random error is minimized for FS in AD group and SPM8 showed less systematic bias. Across the AC group, both SPM12 and FS performed well but SPM12 reported lesser amount of systematic bias.

Non-invasive brain stimulation of the aging brain: State of the art and future perspectives

Favored by increased life expectancy and reduced birth rate, worldwide demography is rapidly shifting to older ages. The golden age of aging is not only an achievement but also a big challenge because of the load of the elderly on social and medical health care systems. Moreover, the impact of age-related decline of attention, memory, reasoning and executive functions on self-sufficiency emphasizes the need of interventions to maintain cognitive abilities at a useful degree in old age. Recently, neuroscientific research explored the chance to apply Non-Invasive Brain Stimulation (NiBS) techniques (as transcranial electrical and magnetic stimulation) to healthy aging population to preserve or enhance physiologically-declining cognitive functions. The present review will update and address the current state of the art on NiBS in healthy aging. Feasibility of NiBS techniques will be discussed in light of recent neuroimaging (either structural or functional) and neurophysiological models proposed to explain neural substrates of the physiologically aging brain. Further, the chance to design multidisciplinary interventions to maximize the efficacy of NiBS techniques will be introduced as a necessary future direction.

Making use of longitudinal information in pattern recognition

Longitudinal designs are widely used in medical studies as a means of observing within-subject changes over time in groups of subjects, thereby aiming to improve sensitivity for detecting disease effects. Paralleling an increased use of such studies in neuroimaging has been the adoption of pattern recognition algorithms for making individualized predictions of disease. However, at present few pattern recognition methods exist to make full use of neuroimaging data that have been collected longitudinally, with most methods relying instead on cross-sectional style analysis. This article presents a principal component analysis-based feature construction method that uses longitudinal high-dimensional data to improve predictive performance of pattern recognition algorithms. The method can be applied to data from a wide range of longitudinal study designs and permits an arbitrary number of time-points per subject. We apply the method to two longitudinal datasets, one containing subjects with mild cognitive impairment along with healthy controls, the other with early dementia subjects and healthy controls. Across both datasets, we show improvements in predictive accuracy relative to cross-sectional classifiers for discriminating disease subjects from healthy controls on the basis of whole-brain structural magnetic resonance image-based voxels. In addition, we can transfer longitudinal information from one set of subjects to make disease predictions in another set of subjects. The proposed method is simple and, as a feature construction method, flexible with respect to the choice of classifier and image registration algorithm. Hum Brain Mapp 37:4385-4404, 2016. © 2016 Wiley Periodicals, Inc.

An evidence-based algorithm for the utility of FDG-PET for diagnosing Alzheimer's disease according to presence of medial temporal lobe atrophy

BACKGROUND

Imaging biomarkers for Alzheimer's disease include medial temporal lobe atrophy (MTLA) depicted on computed tomography (CT) or magnetic resonance imaging (MRI) and patterns of reduced metabolism on fluorodeoxyglucose positron emission tomography (FDG-PET).

AIMS

To investigate whether MTLA on head CT predicts the diagnostic usefulness of an additional FDG-PET scan.

METHOD

Participants had a clinical diagnosis of Alzheimer's disease (n = 37) or dementia with Lewy bodies (DLB; n = 30) or were similarly aged controls (n = 30). We visually rated MTLA on coronally reconstructed CT scans and, separately and blind to CT ratings, abnormal appearances on FDG-PET scans.

RESULTS

Using a pre-defined cut-off of MTLA ⩾5 on the Scheltens (0-8) scale, 0/30 controls, 6/30 DLB and 23/30 Alzheimer's disease had marked MTLA. FDG-PET performed well for diagnosing Alzheimer's disease v DLB in the low-MTLA group (sensitivity/specificity of 71%/79%), but in the high-MTLA group diagnostic performance of FDG-PET was not better than chance.

CONCLUSIONS

In the presence of a high degree of MTLA, the most likely diagnosis is Alzheimer's disease, and an FDG-PET scan will probably not provide significant diagnostic information. However, in cases without MTLA, if the diagnosis is unclear, an FDG-PET scan may provide additional clinically useful diagnostic information.

Dissociation of Down syndrome and Alzheimer's disease effects with imaging

Introduction

Down Syndrome (DS) adults experience accumulation of Alzheimer's disease (AD)–like amyloid plaques and tangles and a high incidence of dementia and could provide an enriched population to study AD-targeted treatments. However, to evaluate effects of therapeutic intervention, it is necessary to dissociate the contributions of DS and AD from overall phenotype. Imaging biomarkers offer the potential to characterize and stratify patients who will worsen clinically but have yielded mixed findings in DS subjects.

Methods

We evaluated 18F fluorodeoxyglucose positron emission tomography (PET), florbetapir PET, and structural magnetic resonance (sMR) image data from 12 nondemented DS adults using advanced multivariate machine learning methods.

Results

Our results showed distinctive patterns of glucose metabolism and brain volume enabling dissociation of DS and AD effects. AD-like pattern expression corresponded to amyloid burden and clinical measures.

Discussion

These findings lay groundwork to enable AD clinical trials with characterization and disease-specific tracking of DS adults.

Regional Brain Glucose Hypometabolism in Young Women with Polycystic Ovary Syndrome: Possible Link to Mild Insulin Resistance

Objective

To investigate whether cerebral metabolic rate of glucose (CMR_glu) is altered in normal weight young women with polycystic ovary syndrome (PCOS) who exhibit mild insulin resistance.

Materials and methods

Seven women with PCOS were compared to eleven healthy female controls of similar age, education and body mass index. Regional brain glucose uptake was quantified using FDG with dynamic positron emission tomography and magnetic resonance imaging, and its potential relationship with insulin resistance assessed using the updated homeostasis model assessment (HOMA2-IR). A battery of cognitive tests was administered to evaluate working memory, attention and executive function.

Results

The PCOS group had 10% higher fasting glucose and 40% higher HOMA2-IR (p ≤ 0.035) compared to the Controls. The PCOS group had 9–14% lower CMR_glu in specific regions of the frontal, parietal and temporal cortices (p ≤ 0.018). A significant negative relation was found between the CMR_glu and HOMA2-IR mainly in the frontal, parietal and temporal cortices as well as in the hippocampus and the amygdala (p ≤ 0.05). Globally, cognitive performance was normal in both groups but scores on the PASAT test of working memory tended to be low in the PCOS group.

Conclusions

The PCOS group exhibited a pattern of low regional CMR_glu that correlated inversely with HOMA2-IR in several brain regions and which resembled the pattern seen in aging and early Alzheimer’s disease. These results suggest that a direct association between mild insulin resistance and brain glucose hypometabolism independent of overweight or obesity can exist in young adults in their 20s. Further investigation of the influence of insulin resistance on brain glucose metabolism and cognition in younger and middle-aged adults is warranted.

The Association of Glucose Metabolism and Eigenvector Centrality in Alzheimer's Disease

Both fluorine-18-labeled fluorodeoxyglucose ([(18)F]FDG) positron emission tomography, examining glucose metabolism, and resting-state functional magnetic resonance imaging (rs-fMRI), using covarying blood oxygen levels, can be used to explore neuronal dysfunction in Alzheimer's disease (AD). Both measures are reported to identify similar brain regions affected in AD patients. The spatial overlap and association of [(18)F]FDG with rs-fMRI in AD patients and controls were examined to investigate whether these two measures are associated, and if so, to what extent. For 24 AD patients and 18 controls, [(18)F]FDG and rs-fMRI data were available. [(18)F]FDG standardized uptake value ratios (SUVr), with cerebellar gray matter (GM) as reference tissue, were calculated. Eigenvector centrality (EC) mapping was used to spatially analyze the functional brain network. Group differences were calculated for [(18)F]FDG and eigenvector centrality mapping (ECM) values in four cortical regions (occipital, parietal, frontal, and temporal) and across voxels, with age, gender, and GM as covariates. Correlation of [(18)F]FDG with ECM was calculated within groups. Both lowered [(18)F]FDG SUVr and EC values were seen in the parietal and occipital cortex of AD patients. However, [(18)F]FDG yielded more robust and widespread brain areas affected in AD patients; hypometabolism was also observed in the temporal cortex and regions within frontal brain areas. Poor spatial overlap of both measures was observed. No associations were found between local [(18)F]FDG SUVr and ECM. In conclusion, agreement of [(18)F]FDG and ECM in AD patients seems moderate at best. [(18)F]FDG was most accurate in distinguishing AD patients from controls.

Insulin resistance predicts medial temporal hypermetabolism in mild cognitive impairment conversion to Alzheimer disease

Alzheimer disease (AD) is characterized by progressive hypometabolism on [(18)F]-fluorodeoxyglucose positron emission tomography (FDG-PET) scans. Peripheral insulin resistance (IR) increases AD risk. No studies have examined associations between FDG metabolism and IR in mild cognitive impairment (MCI) and AD, as well as MCI conversion to AD. We studied 26 cognitively normal (CN), 194 MCI (39 MCI-progressors, 148 MCI-stable, 2 years after baseline), and 60 AD subjects with baseline FDG-PET from the Alzheimer's Disease Neuroimaging Initiative. Mean FDG metabolism was derived for AD-vulnerable regions of interest (ROIs), including lateral parietal and posteromedial cortices, medial temporal lobe (MTL), hippocampus, and ventral prefrontal cortices (vPFC), as well as postcentral gyrus and global cerebrum control regions. The homeostasis model assessment of IR (HOMA-IR) was used to measure IR. For AD, higher HOMA-IR predicted lower FDG in all ROIs. For MCI-progressors, higher HOMA-IR predicted higher FDG in the MTL and hippocampus. Control regions showed no associations. Higher HOMA-IR predicted hypermetabolism in MCI-progressors and hypometabolism in AD in medial temporal regions. Future longitudinal studies should examine the pathophysiologic significance of the shift from MTL hyper- to hypometabolism associated with IR.

Florbetapir positron emission tomography and cerebrospinal fluid biomarkers

BACKGROUND

We evaluated the relationship between florbetapir-F18 positron emission tomography (FBP PET) and cerebrospinal fluid (CSF) biomarkers.

METHODS

Alzheimer's Disease Neuroimaging Initiative-Grand Opportunity and Alzheimer's Disease Neuroimaging Initiative 2 (GO/2) healthy control (HC), mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia subjects with clinical measures and CSF collected ±90 days of FBP PET data were analyzed using correlation and logistic regression.

RESULTS

In HC and MCI subjects, FBP PET anterior and posterior cingulate and composite standard uptake value ratios correlated with CSF amyloid beta (Aβ1-42) and tau/Aβ1-42 ratios. Using logistic regression, Aβ1-42, total tau (t-tau), phosphorylated tau181P (p-tau), and FBP PET composite each differentiated HC versus AD. Aβ1-42 and t-tau distinguished MCI versus AD, without additional contribution by FBP PET. Total tau and p-tau added discriminative power to FBP PET when classifying HC versus AD.

CONCLUSION

Based on cross-sectional diagnostic groups, both amyloid and tau measures distinguish healthy from demented subjects. Longitudinal analyses are needed.

A practical guideline for intracranial volume estimation in patients with Alzheimer's disease

Background

Intracranial volume (ICV) is an important normalization measure used in morphometric analyses to correct for head size in studies of Alzheimer Disease (AD). Inaccurate ICV estimation could introduce bias in the outcome. The current study provides a decision aid in defining protocols for ICV estimation in patients with Alzheimer disease in terms of sampling frequencies that can be optimally used on the volumetric MRI data, and the type of software most suitable for use in estimating the ICV measure.

Methods

Two groups of 22 subjects are considered, including adult controls (AC) and patients with Alzheimer Disease (AD). Reference measurements were calculated for each subject by manually tracing intracranial cavity by the means of visual inspection. The reliability of reference measurements were assured through intra- and inter- variation analyses. Three publicly well-known software packages (Freesurfer, FSL, and SPM) were examined in their ability to automatically estimate ICV across the groups.

Results

Analysis of the results supported the significant effect of estimation method, gender, cognitive condition of the subject and the interaction among method and cognitive condition factors in the measured ICV. Results on sub-sampling studies with a 95% confidence showed that in order to keep the accuracy of the interleaved slice sampling protocol above 99%, the sampling period cannot exceed 20 millimeters for AC and 15 millimeters for AD. Freesurfer showed promising estimates for both adult groups. However SPM showed more consistency in its ICV estimation over the different phases of the study.

Conclusions

This study emphasized the importance in selecting the appropriate protocol, the choice of the sampling period in the manual estimation of ICV and selection of suitable software for the automated estimation of ICV. The current study serves as an initial framework for establishing an appropriate protocol in both manual and automatic ICV estimations with different subject populations.

Effects of ketone bodies in Alzheimer's disease in relation to neural hypometabolism, β-amyloid toxicity, and astrocyte function

Diet supplementation with ketone bodies (acetoacetate and β-hydroxybuturate) or medium-length fatty acids generating ketone bodies has consistently been found to cause modest improvement of mental function in Alzheimer's patients. It was suggested that the therapeutic effect might be more pronounced if treatment was begun at a pre-clinical stage of the disease instead of well after its manifestation. The pre-clinical stage is characterized by decade-long glucose hypometabolism in brain, but ketone body metabolism is intact even initially after disease manifestation. One reason for the impaired glucose metabolism may be early destruction of the noradrenergic brain stem nucleus, locus coeruleus, which stimulates glucose metabolism, at least in astrocytes. These glial cells are essential in Alzheimer pathogenesis. The β-amyloid peptide Aβ interferes with their cholinergic innervation, which impairs synaptic function because of diminished astrocytic glutamate release. Aβ also reduces glucose metabolism and causes hyperexcitability. Ketone bodies are similarly used against seizures, but the effectively used concentrations are so high that they must interfere with glucose metabolism and de novo synthesis of neurotransmitter glutamate, reducing neuronal glutamatergic signaling. The lower ketone body concentrations used in Alzheimer's disease may owe their effect to support of energy metabolism, but might also inhibit release of gliotransmitter glutamate. Alzheimer's disease is a panglial-neuronal disorder with long-standing brain hypometabolism, aberrations in both neuronal and astrocytic glucose metabolism, inflammation, hyperexcitability, and dementia. Relatively low doses of β-hydroxybutyrate can have an ameliorating effect on cognitive function. This could be because of metabolic supplementation or inhibition of Aβ-induced release of glutamate as gliotransmitter, which is likely to reduce hyperexcitability and inflammation. The therapeutic β-hydroxybutyrate doses are too low to reduce neuronally released glutamate.

FDG-PET and amyloid-PET imaging: the diverging paths

PURPOSE OF REVIEW

The availability of PET neuroimaging tools for the in-vivo assessment of metabolic dysfunction and amyloid burden in Alzheimer's disease has opened important methodological and practical issues in the diagnostic design and the conduct of new clinical trials. This review, addressing the different molecular information that the amyloid-PET and fluorodeoxyglucose-PET (FDG-PET) tools can provide, highlights their diverging paths in Alzheimer's disease and possible new perspectives in research and clinical applications.

RECENT FINDINGS

Senile plaques and neurofibrillary tangles are prominent neuropathological hallmarks in Alzheimer's disease and are considered to be targets for therapeutic intervention and biomarkers for diagnostic in-vivo imaging agents. Alzheimer's disease is a slowly progressing disorder, in which pathophysiological abnormalities, detectable in vivo by PET biomarkers, precede clinical symptoms by many years to decades. The unitary view of Alzheimer's disease as a sequential pathological pathway, with beta-amyloid (Aβ) as the only initial and causal event (the 'amyloid cascade hypothesis'), is likely to be progressively replaced by a more complex picture, also on the basis of recent PET imaging findings showing that neuronal injury biomarkers and tau pathology can be independent of β-amyloid deposition.

SUMMARY

The different molecular paths that PET in-vivo biomarkers can reveal in the timeframe of Alzheimer's disease progression reflect the events leading to deposition of Aβ and phosphorylated tau, neuronal injury and neurodegeneration, which can run in parallel instead of in a sequential manner. The amyloid and neuronal injury paths may diverge along the Alzheimer's disease cascade and bear separate relationships with Alzheimer's disease symptoms and clinical phenotypes. All these evidences are crucial for the diagnosis and the development of new drugs aimed at slowing or preventing dementia.