Basal Forebrain and Hippocampus as Predictors of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment - A Multicenter DTI and Volumetry Study

TMS-derived short afferent inhibition discriminates cognitive status in older adults without dementia

Aging is a complex and diverse biological process characterized by progressive molecular, cellular, and tissue damage, resulting in a loss of physiological integrity and heightened vulnerability to pathology. This biological diversity corresponds with highly variable cognitive trajectories, which are further confounded by genetic and environmental factors that influence the resilience of the aging brain. Given this complexity, there is a need for neurophysiological indicators that not only discern physiologic and pathologic aging but also closely align with cognitive trajectories. Transcranial Magnetic Stimulation (TMS) may have utility in this regard as a non-invasive brain stimulation tool that can characterize features of cortical excitability. Particularly, as a proxy for central cholinergic function, short-afferent inhibition (SAI) dysfunction is robustly associated with cognitive deficits in the latter stages of Alzheimer's Disease and Related Dementia (ADRD). In this study, we evaluated SAI in healthy young adults and older adults who, though absent clinical diagnoses, were algorithmically classified as cognitively normal (CN) or cognitively impaired (CI) according to the Jak/Bondi actuarial criteria. We report that SAI is preserved in the Old-CN cohort relative to the young adults, and SAI is significantly diminished in the Old-CI cohort relative to both young and CN older adults. Additionally, diminished SAI was significantly associated with impaired sustained attention and working memory. As a proxy measure for central cholinergic deficits, we discuss the potential value of SAI for discerning physiological and pathological aging.

Clinically feasible automated MRI volumetry of the brain as a prognostic marker in subjective and mild cognitive impairment

Background/aims

The number of patients suffering from cognitive decline and dementia increases, and new possible treatments are being developed. Thus, the need for time efficient and cost-effective methods to facilitate an early diagnosis and prediction of future cognitive decline in patients with early cognitive symptoms is becoming increasingly important. The aim of this study was to evaluate whether an MRI based software, NeuroQuant® (NQ), producing volumetry of the hippocampus and whole brain volume (WBV) could predict: (1) conversion from subjective cognitive decline (SCD) at baseline to mild cognitive impairment (MCI) or dementia at follow-up, and from MCI at baseline to dementia at follow-up and (2) progression of cognitive and functional decline defined as an annual increase in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) score.

Methods

MRI was performed in 156 patients with SCD or MCI from the memory clinic at Oslo University Hospital (OUH) that had been assessed with NQ and had a clinical follow-up examination. Logistic and linear regression analyses were performed with hippocampus volume and WBV as independent variables, and conversion or progression as dependent variables, adjusting for demographic and other relevant covariates including Mini-Mental State Examination-Norwegian Revised Version score (MMSE-NR) and Apolipoprotein E ɛ4 (APOE ɛ4) carrier status.

Results

Hippocampus volume, but not WBV, was associated with conversion to MCI or dementia, but neither were associated with conversion when adjusting for MMSE-NR. Both hippocampus volume and WBV were associated with progression as measured by the annual change in CDR-SB score in both unadjusted and adjusted analyses.

Conclusion

The results indicate that automated regional MRI volumetry of the hippocampus and WBV can be useful in predicting further cognitive decline in patients with early cognitive symptoms.

Neuroticism polygenic risk predicts conversion from mild cognitive impairment to Alzheimer's disease by impairing inferior parietal surface area

The high prevalence of conversion from amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD) makes early prevention of AD extremely critical. Neuroticism, a heritable personality trait associated with mental health, has been considered a risk factor for conversion from aMCI to AD. However, whether the neuroticism genetic risk could predict the conversion of aMCI and its underlying neural mechanisms is unclear. Neuroticism polygenic risk score (N-PRS) was calculated in 278 aMCI patients with qualified genomic and neuroimaging data from ADNI. After 1-year follow-up, N-PRS in patients of aMCI-converted group was significantly greater than those in aMCI-stable group. Logistic and Cox survival regression revealed that N-PRS could significantly predict the early-stage conversion risk from aMCI to AD. These results were well replicated in an internal dataset and an independent external dataset of 933 aMCI patients from the UK Biobank. One sample Mendelian randomization analyses confirmed a potentially causal association from higher N-PRS to lower inferior parietal surface area to higher conversion risk of aMCI patients. These analyses indicated that neuroticism genetic risk may increase the conversion risk from aMCI to AD by impairing the inferior parietal structure.

Exploring sexual dimorphism in basal forebrain volume changes during aging and neurodegenerative diseases

Patients with neurodegenerative diseases exhibit diminished basal forebrain (BF) volume compared to healthy individuals. However, it's uncertain whether this difference is consistent between sexes. It has been reported that BF volume moderately atrophies during aging, but the effect of sex on BF volume changes during the normal aging process remains unclear. In the cross-sectional study, we observed a significant reduction in BF volume in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) compared to Healthy Controls (HCs), especially in the Ch4 subregion. Notably, significant differences in BF volume between MCI and HCs were observed solely in the female group. Additionally, we identified asymmetrical atrophy in the left and right Ch4 subregions in female patients with AD. In the longitudinal analysis, we found that aging seemed to have a minimal impact on BF volume in males. Our study highlights the importance of considering sex as a research variable in brain science.

A multi-cohort study of the hippocampal radiomics model and its associated biological changes in Alzheimer's Disease

There have been no previous reports of hippocampal radiomics features associated with biological functions in Alzheimer's Disease (AD). This study aims to develop and validate a hippocampal radiomics model from structural magnetic resonance imaging (MRI) data for identifying patients with AD, and to explore the mechanism underlying the developed radiomics model using peripheral blood gene expression. In this retrospective multi-study, a radiomics model was developed based on the radiomics discovery group (n = 420) and validated in other cohorts. The biological functions underlying the model were identified in the radiogenomic analysis group using paired MRI and peripheral blood transcriptome analyses (n = 266). Mediation analysis and external validation were applied to further validate the key module and hub genes. A 12 radiomics features-based prediction model was constructed and this model showed highly robust predictive power for identifying AD patients in the validation and other three cohorts. Using radiogenomics mapping, myeloid leukocyte and neutrophil activation were enriched, and six hub genes were identified from the key module, which showed the highest correlation with the radiomics model. The correlation between hub genes and cognitive ability was confirmed using the external validation set of the AddneuroMed dataset. Mediation analysis revealed that the hippocampal radiomics model mediated the association between blood gene expression and cognitive ability. The hippocampal radiomics model can accurately identify patients with AD, while the predictive radiomics model may be driven by neutrophil-related biological pathways.

Association of Basal Forebrain Volume with Amyloid, Tau, and Cognition in Alzheimer's Disease

Background

Degeneration of cholinergic basal forebrain (BF) neurons characterizes Alzheimer's disease (AD). However, what role the BF plays in the dynamics of AD pathophysiology has not been investigated precisely.

Objective

To investigate the baseline and longitudinal roles of BF along with core neuropathologies in AD.

Methods

In this retrospective cohort study, we enrolled 113 subjects (38 amyloid [Aβ]-negative cognitively unimpaired, 6 Aβ-positive cognitively unimpaired, 39 with prodromal AD, and 30 with AD dementia) who performed brain MRI for BF volume and cortical thickness, 18F-florbetaben PET for Aβ, 18F-flortaucipir PET for tau, and detailed cognitive testing longitudinally. We investigated the baseline and longitudinal association of BF volume with Aβ and tau standardized uptake value ratio and cognition.

Results

Cross-sectionally, lower BF volume was not independently associated with higher cortical Aβ, but it was associated with tau burden. Tau burden in the orbitofrontal, insular, lateral temporal, inferior temporo-occipital, and anterior cingulate cortices were associated with progressive BF atrophy. Lower BF volume was associated with faster Aβ accumulation, mainly in the prefrontal, anterior temporal, cingulate, and medial occipital cortices. BF volume was associated with progressive decline in language and memory functions regardless of baseline Aβ and tau burden.

Conclusions

Tau deposition affected progressive BF atrophy, which in turn accelerated amyloid deposition, leading to a vicious cycle. Also, lower baseline BF volume independently predicted deterioration in cognitive function.

Degeneration of cholinergic white matter pathways and nucleus basalis of Meynert in individuals with objective subtle cognitive impairment

We evaluated alterations in the nucleus basalis of Meynert (NBM) volume and integrity of cholinergic white matter pathways in objective subtle cognitive impairment (Obj-SCI) individuals. NBM segmentation and cholinergic pathways tracking were conducted at baseline, 12-, 24-, and 48-month follow-ups in 41 Obj-SCI individuals and 61 healthy controls (HC). The baseline and 4-year rate of change in NBM volume and cholinergic pathways mean diffusivity were compared. Associations between cholinergic index changes and pathological processes and cognitive performance were evaluated. After controlling for age, sex, APOE genotype, and total intracranial volume, Obj-SCI individuals exhibited reduced NBM volume and increased medial pathway mean diffusivity compared to HC at baseline. Furthermore, amyloid-positive Obj-SCI individuals exhibited a steeper longitudinal decline in NBM volume than HC. Additionally, decreases in NBM volume and cholinergic pathways integrity were associated with amyloid and vascular pathologies and cognitive decline. Overall, degeneration of the cholinergic system plays an important role in cognitive impairment during the preclinical stage of Alzheimer's disease, which may provide a significant target for early therapeutic interventions.

Neuroimaging modalities in the detection of Alzheimer's disease-associated biomarkers

Alzheimer's disease (AD) is the most common cause of dementia. Neuropathological changes in AD patients occur up to 10-20 years before the emergence of clinical symptoms. Specific diagnosis and appropriate intervention strategies are crucial during the phase of mild cognitive impairment (MCI) and AD. The detection of biomarkers has emerged as a promising tool for tracking the efficacy of potential therapies, making an early disease diagnosis, and prejudging treatment prognosis. Specifically, multiple neuroimaging modalities, including magnetic resonance imaging (MRI), positron emission tomography, optical imaging, and single photon emission-computed tomography, have provided a few potential biomarkers for clinical application. The MRI modalities described in this review include structural MRI, functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy, and arterial spin labelling. These techniques allow the detection of presymptomatic diagnostic biomarkers in the brains of cognitively normal elderly people and might also be used to monitor AD disease progression after the onset of clinical symptoms. This review highlights potential biomarkers, merits, and demerits of different neuroimaging modalities and their clinical value in MCI and AD patients. Further studies are necessary to explore more biomarkers and overcome the limitations of multiple neuroimaging modalities for inclusion in diagnostic criteria for AD.

Structural But Not Functional Connectivity Differences within Default Mode Network Indicate Conversion to Dementia

BACKGROUND

Malfunctioning of the default mode network (DMN) has been consistently related to mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, evidence on differences in this network between MCI converters (MCI-c) and non-converters (MCI-nc), which could mark progression to AD, is still inconsistent.

OBJECTIVE

To multimodally investigate the DMN in the AD continuum.

METHODS

We measured gray matter (GM) volume, white matter (WM) integrity, and functional connectivity (FC) at rest in healthy elderly controls, MCI-c, MCI-nc, and AD patients, matched on sociodemographic variables.

RESULTS

Significant differences between AD patients and controls were found in the structure of most of the regions of the DMN. MCI-c only differed from MCI-nc in GM volume of the left parahippocampus and bilateral hippocampi and middle frontal gyri, as well as in WM integrity of the parahippocampal cingulum connecting the left hippocampus and precuneus. We found significant correlations between integrity in some of those regions and global neuropsychological status, as well as an excellent discrimination ability between converters and non-converters for the sum of GM volume of left parahippocampus, bilateral hippocampi, and middle frontal gyri, and WM integrity of left parahippocampal cingulum. However, we found no significant differences in FC.

CONCLUSION

These results further support the relationship between abnormalities in the DMN and AD, and suggest that structural measures could be more accurate than resting-state estimates as markers of conversion from MCI to AD.

Determinants of approved acetylcholinesterase inhibitor response outcomes in Alzheimer's disease: relevance for precision medicine in neurodegenerative diseases

Acetylcholinesterase inhibitors (ChEI) are the global standard of care for the symptomatic treatment of Alzheimer's disease (AD) and show significant positive effects in neurodegenerative diseases with cognitive and behavioral symptoms. Although experimental and large-scale clinical evidence indicates the potential long-term efficacy of ChEI, primary outcomes are generally heterogeneous across outpatient clinics and regional healthcare systems. Sub-optimal dosing or slow tapering, heterogeneous guidelines about the timing for therapy initiation (prodromal versus dementia stages), healthcare providers' ambivalence to treatment, lack of disease awareness, delayed medical consultation, prescription of ChEI in non-AD cognitive disorders, contribute to the negative outcomes. We present an evidence-based overview of determinants, spanning genetic, molecular, and large-scale networks, involved in the response to ChEI in patients with AD and other neurodegenerative diseases. A comprehensive understanding of cerebral and retinal cholinergic system dysfunctions along with ChEI response predictors in AD is crucial since disease-modifying therapies will frequently be prescribed in combination with ChEI. Therapeutic algorithms tailored to genetic, biological, clinical (endo)phenotypes, and disease stages will help leverage inter-drug synergy and attain optimal combined response outcomes, in line with the precision medicine model.

Detecting Early Cognitive Decline in Alzheimer's Disease with Brain Synaptic Structural and Functional Evaluation

Early cognitive decline in patients with Alzheimer's (AD) is associated with quantifiable structural and functional connectivity changes in the brain. AD dysregulation of Aβ and tau metabolism progressively disrupt normal synaptic function, leading to loss of synapses, decreased hippocampal synaptic density and early hippocampal atrophy. Advances in brain imaging techniques in living patients have enabled the transition from clinical signs and symptoms-based AD diagnosis to biomarkers-based diagnosis, with functional brain imaging techniques, quantitative EEG, and body fluids sampling. The hippocampus has a central role in semantic and episodic memory processing. This cognitive function is critically dependent on normal intrahippocampal connections and normal hippocampal functional connectivity with many cortical regions, including the perirhinal and the entorhinal cortex, parahippocampal cortex, association regions in the temporal and parietal lobes, and prefrontal cortex. Therefore, decreased hippocampal synaptic density is reflected in the altered functional connectivity of intrinsic brain networks (aka large-scale networks), including the parietal memory, default mode, and salience networks. This narrative review discusses recent critical issues related to detecting AD-associated early cognitive decline with brain synaptic structural and functional markers in high-risk or neuropsychologically diagnosed patients with subjective cognitive impairment or mild cognitive impairment.

State-of-the-art imaging of neuromodulatory subcortical systems in aging and Alzheimer's disease: Challenges and opportunities

Primary prevention trials have shifted their focus to the earliest stages of Alzheimer's disease (AD). Autopsy data indicates that the neuromodulatory subcortical systems' (NSS) nuclei are specifically vulnerable to initial tau pathology, indicating that these nuclei hold great promise for early detection of AD in the context of the aging brain. The increasing availability of new imaging methods, ultra-high field scanners, new radioligands, and routine deep brain stimulation implants has led to a growing number of NSS neuroimaging studies on aging and neurodegeneration. Here, we review findings of current state-of-the-art imaging studies assessing the structure, function, and molecular changes of these nuclei during aging and AD. Furthermore, we identify the challenges associated with these imaging methods, important pathophysiologic gaps to fill for the AD NSS neuroimaging field, and provide future directions to improve our assessment, understanding, and clinical use of in vivo imaging of the NSS.

Alterations in theta-gamma coupling and sharp wave-ripple, signs of prodromal hippocampal network impairment in the TgF344-AD rat model

Alzheimer's disease (AD) is a severe neurodegenerative disorder caused by the accumulation of toxic proteins, amyloid-beta (Aβ) and tau, which eventually leads to dementia. Disease-modifying therapies are still lacking, due to incomplete insights into the neuropathological mechanisms of AD. Synaptic dysfunction is known to occur before cognitive symptoms become apparent and recent studies have demonstrated that imbalanced synaptic signaling drives the progression of AD, suggesting that early synaptic dysfunction could be an interesting therapeutic target. Synaptic dysfunction results in altered oscillatory activity, which can be detected with electroencephalography and electrophysiological recordings. However, the majority of these studies have been performed at advanced stages of AD, when extensive damage and cognitive symptoms are already present. The current study aimed to investigate if the hippocampal oscillatory activity is altered at pre-plaque stages of AD. The rats received stereotactic surgery to implant a laminar electrode in the CA1 layer of the right hippocampus. Electrophysiological recordings during two consecutive days in an open field were performed in 4-5-month-old TgF344-AD rats when increased concentrations of soluble Aβ species were observed in the brain, in the absence of Aβ-plaques. We observed a decreased power of high theta oscillations in TgF344-AD rats compared to wild-type littermates. Sharp wave-ripple (SWR) analysis revealed an increased SWR power and a decreased duration of SWR during quiet wake in TgF344-AD rats. The alterations in properties of SWR and the increased power of fast oscillations are suggestive of neuronal hyperexcitability, as has been demonstrated to occur during presymptomatic stages of AD. In addition, decreased strength of theta-gamma coupling, an important neuronal correlate of memory encoding, was observed in the TgF344-AD rats. Theta-gamma phase amplitude coupling has been associated with memory encoding and the execution of cognitive functions. Studies have demonstrated that mild cognitive impairment patients display decreased coupling strength, similar to what is described here. The current study demonstrates altered hippocampal network activity occurring at pre-plaque stages of AD and provides insights into prodromal network dysfunction in AD. The alterations observed could aid in the detection of AD during presymptomatic stages.

Altered basal forebrain function during whole-brain network activity at pre- and early-plaque stages of Alzheimer's disease in TgF344-AD rats

BACKGROUND

Imbalanced synaptic transmission appears to be an early driver in Alzheimer's disease (AD) leading to brain network alterations. Early detection of altered synaptic transmission and insight into mechanisms causing early synaptic alterations would be valuable treatment strategies. This study aimed to investigate how whole-brain networks are influenced at pre- and early-plague stages of AD and if these manifestations are associated with concomitant cellular and synaptic deficits.  METHODS: To this end, we used an established AD rat model (TgF344-AD) and employed resting state functional MRI and quasi-periodic pattern (QPP) analysis, a method to detect recurrent spatiotemporal motifs of brain activity, in parallel with state-of-the-art immunohistochemistry in selected brain regions.

RESULTS

At the pre-plaque stage, QPPs in TgF344-AD rats showed decreased activity of the basal forebrain (BFB) and the default mode-like network. Histological analyses revealed increased astrocyte abundance restricted to the BFB, in the absence of amyloid plaques, tauopathy, and alterations in a number of cholinergic, gaba-ergic, and glutamatergic synapses. During the early-plaque stage, when mild amyloid-beta (Aβ) accumulation was observed in the cortex and hippocampus, QPPs in the TgF344-AD rats normalized suggesting the activation of compensatory mechanisms during this early disease progression period. Interestingly, astrogliosis observed in the BFB at the pre-plaque stage was absent at the early-plaque stage. Moreover, altered excitatory/inhibitory balance was observed in cortical regions belonging to the default mode-like network. In wild-type rats, at both time points, peak activity in the BFB preceded peak activity in other brain regions-indicating its modulatory role during QPPs. However, this pattern was eliminated in TgF344-AD suggesting that alterations in BFB-directed neuromodulation have a pronounced impact in network function in AD.

CONCLUSIONS

This study demonstrates the value of rsfMRI and advanced network analysis methods to detect early alterations in BFB function in AD, which could aid early diagnosis and intervention in AD. Restoring the global synaptic transmission, possibly by modulating astrogliosis in the BFB, might be a promising therapeutic strategy to restore brain network function and delay the onset of symptoms in AD.

Fornix alterations induce the disruption of default mode network in patients with adamantinomatous craniopharyngiomas

Adamantinomatous craniopharyngioma (ACPs) are rare embryonic tumors and often involve the hypothalamus. The underlying neural substrate of the hypothalamic involvement (HI)-related cognitive decline in patients with ACP is still unclear. We aimed to combine the multi-modal neuroimaging and histological characteristics of the ACP to explore the potential neural substrate of the HI-related cognitive decline. 45 patients with primary ACPs (invasive, 23; noninvasive, 22) and 52 healthy control subjects (HCs) were admitted to the cross-sectional study. No significant difference in cognitive domains was observed between HCs and patients with noninvasive ACPs (NACP). Patients with invasive ACPs (IACP) showed significantly lower working memory performance (WM, p = 0.002) than patients with NACP. The WM decline was correlated with the disruption of the medial temporal lobe (MTL) subsystem in the default mode network (DMN) (r = 0.45, p = 0.004). The increased radial diffusivity of the fornix, indicating demyelinating process, was correlated with the disruption of the MTL subsystem (r = -0.48, p = 0.002). Our study demonstrated that the fornix alterations link DMN disruption to HI-related cognitive decline in patients with ACPs. ACPs that invade the hypothalamus can provide a natural disease model to investigate the potential neural substrate of HI-related cognitive decline.

A link between age, affect, and predictions?

The prevalence of depressive symptoms decreases from late adolescence to middle age adulthood. Furthermore, despite significant losses in motor and cognitive functioning, overall emotional well-being tends to increase with age, and a bias to positive information has been observed multiple times. Several causes have been discussed for this age-related development, such as improvement in emotion regulation, less regret, and higher socioeconomic status. Here, we explore a further explanation. Our minds host mental models that generate predictions about forthcoming events to successfully interact with our physical and social environment. To keep these models faithful, the difference between the predicted and the actual event, that is, the prediction error, is computed. We argue that prediction errors are attenuated in the middle age and older mind, which, in turn, may translate to less negative affect, lower susceptibility to affective disorders, and possibly, to a bias to positive information. Our proposal is primarily linked to perceptual inferences, but may hold as well for higher-level, cognitive, and emotional forms of error processing.

Hippocampal-subfield microstructures and their relation to plasma biomarkers in Alzheimer's disease

Hippocampal subfields exhibit differential vulnerabilities to Alzheimer's disease-associated pathology including abnormal accumulation of amyloid-β deposition and neurofibrillary tangles. These pathological processes extensively impact on the structural and functional interconnectivities of the subfields and may explain the association between hippocampal dysfunction and cognitive deficits. In this study, we investigated the degree of alterations in the microstructure of hippocampal subfields across the clinical continuum of Alzheimer's disease. We applied a grey matter-specific multi-compartment diffusion model (Cortical-Neurite orientation dispersion and density imaging) to understand the differential effects of Alzheimer's disease pathology on the hippocampal subfield microstructure. A total of 119 participants were included in this cross-sectional study. Participants were stratified into three categories, cognitively normal (n = 47), mild cognitive impairment (n = 52), and Alzheimer's disease (n = 19). Diffusion MRI, plasma biomarkers and neuropsychological test scores were used to determine the association between the microstructural integrity and Alzheimer's disease-associated molecular indicators and cognition. For Alzheimer's disease-related plasma biomarkers, we studied amyloid-β, total tau and neurofilament light; for Alzheimer's disease-related neuropsychological tests, we included the Trail Making Test, Rey Auditory Verbal Learning Test, Digit Span and Montreal Cognitive Assessment. Comparisons between cognitively normal subjects and those with mild cognitive impairment showed significant microstructural alterations in the hippocampal cornu ammonis (CA) 4 and dentate gyrus region, whereas CA 1-3 was the most sensitive region for the later stages in the Alzheimer's disease clinical continuum. Among imaging metrics for microstructures, the volume fraction of isotropic diffusion for interstitial free water demonstrated the largest effect size in between-group comparisons. Regarding the plasma biomarkers, neurofilament light appeared to be the most sensitive biomarker for associations with microstructural imaging findings in CA4-dentate gyrus. CA 1-3 was the subfield which had stronger correlations between cognitive performance and microstructural metrics. Particularly, poor performance on the Rey Auditory Verbal Learning Test and Montreal Cognitive Assessment was associated with decreased intracellular volume fraction. Overall, our findings support the value of tissue-specific microstructural imaging for providing pathologically relevant information manifesting in the plasma biomarkers and neuropsychological outcomes across various stages of Alzheimer's disease.

Biomarkers used in Alzheimer's disease diagnosis, treatment, and prevention

Alzheimer's disease (AD), being the number one in terms of dementia burden, is an insidious age-related neurodegenerative disease and is presently considered a global public health threat. Its main histological hallmarks are the Aβ senile plaques and the P-tau neurofibrillary tangles, while clinically it is marked by a progressive cognitive decline that reflects the underlying synaptic loss and neurodegeneration. Many of the drug therapies targeting the two pathological hallmarks namely Aβ and P-tau have been proven futile. This is probably attributed to the initiation of therapy at a stage where cognitive alterations are already obvious. In other words, the underlying neuropathological changes are at a stage where these drugs lack any therapeutic value in reversing the damage. Therefore, there is an urgent need to start treatment in the very early stage where these changes can be reversed, and hence, early diagnosis is of primordial importance. To this aim, the use of robust and informative biomarkers that could provide accurate diagnosis preferably at an earlier phase of the disease is of the essence. To date, several biomarkers have been established that, to a different extent, allow researchers and clinicians to evaluate, diagnose, and more specially exclude other related pathologies. In this study, we extensively reviewed data on the currently explored biomarkers in terms of AD pathology-specific and non-specific biomarkers and highlighted the recent developments in the diagnostic and theragnostic domains. In the end, we have presented a separate elaboration on aspects of future perspectives and concluding remarks.

Effects of Cigarette Smoking on Resting-State Functional Connectivity of the Nucleus Basalis of Meynert in Mild Cognitive Impairment

Background: Mild cognitive impairment (MCI) is the prodromal phase of Alzheimer’s disease (AD) and has a high risk of progression to AD. Cigarette smoking is one of the important modifiable risk factors in AD progression. Cholinergic dysfunction, especially the nucleus basalis of Meynert (NBM), is the converging target connecting smoking and AD. However, how cigarette smoking affects NBM connectivity in MCI remains unclear.

Objective: This study aimed to evaluate the interaction effects of condition (non-smoking vs. smoking) and diagnosis [cognitively normal (CN) vs. MCI] based on the resting-state functional connectivity (rsFC) of the NBM.

Methods: After propensity score matching, we included 86 non-smoking CN, 44 smoking CN, 62 non-smoking MCI, and 32 smoking MCI. All subjects underwent structural and functional magnetic resonance imaging scans and neuropsychological tests. The seed-based rsFC of the NBM with the whole-brain voxel was calculated. Furthermore, the mixed effect analysis was performed to explore the interaction effects between condition and diagnosis on rsFC of the NBM.

Results: The interaction effects of condition × diagnosis on rsFC of the NBM were observed in the bilateral prefrontal cortex (PFC), bilateral supplementary motor area (SMA), and right precuneus/middle occipital gyrus (MOG). Specifically, the smoking CN showed decreased rsFC between left NBM and PFC and increased rsFC between left NBM and SMA compared with non-smoking CN and smoking MCI. The smoking MCI showed reduced rsFC between right NBM and precuneus/MOG compared with non-smoking MCI. Additionally, rsFC between the NBM and SMA showed a significant negative correlation with Wechsler Memory Scale-Logical Memory (WMS-LM) immediate recall in smoking CN (r = −0.321, p = 0.041).

Conclusion: Our findings indicate that chronic nicotine exposure through smoking may lead to functional connectivity disruption between the NBM and precuneus in MCI patients. The distinct alteration patterns on NBM connectivity in CN smokers and MCI smokers suggest that cigarette smoking has different influences on normal and impaired cognition.

Nucleus basalis of Meynert damage and cognition in patients with multiple sclerosis

BACKGROUND

The nucleus basalis of Meynert (NBM), representing the major source of cerebral cholinergic innervations, is vulnerable to neurodegeneration in Alzheimer's and Parkinson's disease.

OBJECTIVE

To determine associations between NBM properties and cognitive outcomes in patients with multiple sclerosis (PwMS).

METHODS

84 PwMS and 19 controls underwent 3T MRI, the Paced Auditory Serial Addition Test (PASAT) and subtests of the Brief International Cognitive Assessment for MS (BICAMS). NBM volume, fractional anisotropy, mean diffusivity (MD), axial diffusivity and radial diffusivity (D⊥) were calculated. Analyses assessed relationships between cognition and NBM measures. Linear regressions evaluated the prognostic value of baseline measures in predicting cognitive change over 3 years of follow-up (n = 67).

RESULTS

Cognitive tests correlated with NBM diffusivity in PwMS (range r = - 0.29 to r = - 0.40, p < 0.05). After accounting for NBM volume, NBM MD and D⊥ explained additional variance (adjusted R2 range 0.08-0.20, p < 0.05). Correlations between NBM imaging metrics and cognitive tests remained significant when including imaging parameters of other cognitive key brain regions in the models. After controlling for age, education, and baseline cognitive test score, NBM measures predicted change in cognition over follow-up in 5 of 10 and 2 of 10 assessments in the relapsing-remitting sample (n = 43) (adjusted R2 range from 0.23 to 0.38, p < 0.05) and secondary progressive sample (adjusted R2 of 0.280 and 0.183), respectively.

CONCLUSIONS

NBM damage is linked to cognitive impairment in PwMS.

Prediction of Alzheimer's Disease Progression Based on Magnetic Resonance Imaging

The neuroimaging method of multimodal magnetic resonance imaging (MRI) can identify the changes in brain structure and function caused by Alzheimer's disease (AD) at different stages, and it is a practical method to study the mechanism of AD progression. This paper reviews the studies of methods and biomarkers for predicting AD progression based on multimodal MRI. First, different approaches for predicting AD progression are analyzed and summarized, including machine learning, deep learning, regression, and other MRI analysis methods. Then, the effective biomarkers of AD progression under structural magnetic resonance imaging, diffusion tensor imaging, functional magnetic resonance imaging, and arterial spin labeling modes of MRI are summarized. It is believed that the brain changes shown on MRI may be related to the cognitive decline in different prodrome stages of AD, which is conducive to the further realization of early intervention and prevention of AD. Finally, the deficiencies of the existing studies are analyzed in terms of data set size, data heterogeneity, processing methods, and research depth. More importantly, future research directions are proposed, including enriching data sets, simplifying biomarkers, utilizing multimodal magnetic resonance, etc. In the future, the study of AD progression by multimodal MRI will still be a challenge but also a significant research hotspot.

Medial Temporal Lobe Subregional Atrophy in Aging and Alzheimer's Disease: A Longitudinal Study

Medial temporal lobe (MTL) atrophy is a key feature of Alzheimer's disease (AD), however, it also occurs in typical aging. To enhance the clinical utility of this biomarker, we need to better understand the differential effects of age and AD by encompassing the full AD-continuum from cognitively unimpaired (CU) to dementia, including all MTL subregions with up-to-date approaches and using longitudinal designs to assess atrophy more sensitively. Age-related trajectories were estimated using the best-fitted polynomials in 209 CU adults (aged 19–85). Changes related to AD were investigated among amyloid-negative (Aβ−) (n = 46) and amyloid-positive (Aβ+) (n = 14) CU, Aβ+ patients with mild cognitive impairment (MCI) (n = 33) and AD (n = 31). Nineteen MCI-to-AD converters were also compared with 34 non-converters. Relationships with cognitive functioning were evaluated in 63 Aβ+ MCI and AD patients. All participants were followed up to 47 months. MTL subregions, namely, the anterior and posterior hippocampus (aHPC/pHPC), entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36 [as perirhinal cortex (PRC) substructures], and parahippocampal cortex (PHC), were segmented from a T1-weighted MRI using a new longitudinal pipeline (LASHiS). Statistical analyses were performed using mixed models. Adult lifespan models highlighted both linear (PRC, BA35, BA36, PHC) and nonlinear (HPC, aHPC, pHPC, ERC) trajectories. Group comparisons showed reduced baseline volumes and steeper volume declines over time for most of the MTL subregions in Aβ+ MCI and AD patients compared to Aβ− CU, but no differences between Aβ− and Aβ+ CU or between Aβ+ MCI and AD patients (except in ERC). Over time, MCI-to-AD converters exhibited a greater volume decline than non-converters in HPC, aHPC, and pHPC. Most of the MTL subregions were related to episodic memory performances but not to executive functioning or speed processing. Overall, these results emphasize the benefits of studying MTL subregions to distinguish age-related changes from AD. Interestingly, MTL subregions are unequally vulnerable to aging, and those displaying non-linear age-trajectories, while not damaged in preclinical AD (Aβ+ CU), were particularly affected from the prodromal stage (Aβ+ MCI). This volume decline in hippocampal substructures might also provide information regarding the conversion from MCI to AD-dementia. All together, these findings provide new insights into MTL alterations, which are crucial for AD-biomarkers definition.

Multilevel Survival Modeling with Structured Penalties for Disease Prediction from Imaging Genetics data

This paper introduces a framework for disease prediction from multimodal genetic and imaging data. We propose a multilevel survival model which allows predicting the time of occurrence of a future disease state in patients initially exhibiting mild symptoms. This new multilevel setting allows modeling the interactions between genetic and imaging variables. This is in contrast with classical additive models which treat all modalities in the same manner and can result in undesirable elimination of specific modalities when their contributions are unbalanced. Moreover, the use of a survival model allows overcoming the limitations of previous approaches based on classification which consider a fixed time frame. Furthermore, we introduce specific penalties taking into account the structure of the different types of data, such as a group lasso penalty over the genetic modality and a L2-penalty over the imaging modality. Finally, we propose a fast optimization algorithm, based on a proximal gradient method. The approach was applied to the prediction of Alzheimer's disease (AD) among patients with mild cognitive impairment (MCI) based on genetic (single nucleotide polymorphisms - SNP) and imaging (anatomical MRI measures) data from the ADNI database. The experiments demonstrate the effectiveness of the method for predicting the time of conversion to AD. It revealed how genetic variants and brain imaging alterations interact in the prediction of future disease status. The approach is generic and could potentially be useful for the prediction of other diseases.

Specific White Matter Tracts and Diffusion Properties Predict Conversion From Mild Cognitive Impairment to Alzheimer's Disease

Identifying biomarkers that can assess the risk of developing Alzheimer's Disease (AD) remains a significant challenge. In this study, we investigated the integrity levels of brain white matter in 34 patients with mild cognitive impairment (MCI) who later converted to AD and 53 stable MCI patients. We used diffusion tensor imaging (DTI) and automated fiber quantification to obtain the diffusion properties of 20 major white matter tracts. To identify which tracts and diffusion measures are most relevant to AD conversion, we used support vector machines (SVMs) to classify the AD conversion and non-conversion MCI patients based on the diffusion properties of each tract individually. We found that diffusivity measures from seven white matter tracts were predictive of AD conversion with axial diffusivity being the most predictive diffusion measure. Additional analyses revealed that white matter changes in the central and parahippocampal terminal regions of the right cingulate hippocampal bundle, central regions of the right inferior frontal occipital fasciculus, and posterior and anterior regions of the left inferior longitudinal fasciculus were the best predictors of conversion from MCI to AD. An SVM based on these white matter tract regions achieved an accuracy of 0.75. These findings provide additional potential biomarkers of AD risk in MCI patients.

Diffusion MRI detects basal forebrain cholinergic abnormalities in the 3xTg-AD mouse model of Alzheimer's disease

Degeneration of the basal forebrain (BF) is detected early in the course of Alzheimer's disease (AD). Reduction in the number of BF cholinergic (ChAT) neurons associated with age-related hippocampal cholinergic neuritic dystrophy is described in the 3xTg-AD mouse model; however, no prior diffusion MRI (dMRI) study has explored the presence of BF alterations in this model. Here we investigated the ability of diffusion MRI (dMRI) to detect abnormalities in BF microstructure for the 3xTg-AD mouse model, along with related pathology in the hippocampus (HP) and white matter (WM) tracks comprising the septo-hippocampal pathway. 3xTg-AD and normal control (NC) mice were imaged in vivo using the specific dMRI technique known as diffusional kurtosis imaging (DKI) at 2, 8, and 15 months of age, and 8 dMRI parameters were measured at each time point. Our results revealed significant lower dMRI values in the BF of 2 months-old 3xTg-AD mice compared with NC mice, most likely related to the increased number of ChAT neurons seen in this AD mouse model at this age. They also showed significant age-related dMRI changes in the BF of both groups between 2 and 8 months of age, mainly a decrease in fractional anisotropy and axial diffusivity, and an increase in radial kurtosis. These dMRI changes in the BF may be reflecting the complex aging and pathological microstructural changes described in this region. Group differences and age-related changes were also observed in the HP, fimbria (Fi) and fornix (Fx). In the HP, diffusivity values were significantly higher in the 2 months-old 3xTg-AD mice, and the HP of NC mice showed a significant increase in axial kurtosis after 8 months, reflecting a normal pattern of increased fiber density complexity, which was not seen in the 3xTg-AD mice. In the Fi, mean and radial diffusivity values were significantly higher, and fractional anisotropy, radial kurtosis and kurtosis fractional anisotropy were significantly lower in the 2 months-old 3xTg-AD mice. The age trajectories for both NC and TG mice in the Fi and Fx were similar between 2 and 8 months, but after 8 months there was a significant decrease in diffusivity metrics associated with an increase in kurtosis metrics in the 3xTg-AD mice. These later HP, Fi and Fx dMRI changes probably reflect the growing number of dystrophic neurites and AD pathology progression in the HP, accompanied by WM disruption in the septo-hippocampal pathway. Our results demonstrate that dMRI can detect early cytoarchitectural abnormalities in the BF, as well as related aging and neurodegenerative changes in the HP, Fi and Fx of the 3xTg-AD mice. Since DKI is widely available on clinical scanners, these results also support the potential of the considered dMRI parameters as in vivo biomarkers for AD disease progression.

Imaging Techniques in Alzheimer's Disease: A Review of Applications in Early Diagnosis and Longitudinal Monitoring

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting many individuals worldwide with no effective treatment to date. AD is characterized by the formation of senile plaques and neurofibrillary tangles, followed by neurodegeneration, which leads to cognitive decline and eventually death.

INTRODUCTION

In AD, pathological changes occur many years before disease onset. Since disease-modifying therapies may be the most beneficial in the early stages of AD, biomarkers for the early diagnosis and longitudinal monitoring of disease progression are essential. Multiple imaging techniques with associated biomarkers are used to identify and monitor AD.

AIM

In this review, we discuss the contemporary early diagnosis and longitudinal monitoring of AD with imaging techniques regarding their diagnostic utility, benefits and limitations. Additionally, novel techniques, applications and biomarkers for AD research are assessed.

FINDINGS

Reduced hippocampal volume is a biomarker for neurodegeneration, but atrophy is not an AD-specific measure. Hypometabolism in temporoparietal regions is seen as a biomarker for AD. However, glucose uptake reflects astrocyte function rather than neuronal function. Amyloid-β (Aβ) is the earliest hallmark of AD and can be measured with positron emission tomography (PET), but Aβ accumulation stagnates as disease progresses. Therefore, Aβ may not be a suitable biomarker for monitoring disease progression. The measurement of tau accumulation with PET radiotracers exhibited promising results in both early diagnosis and longitudinal monitoring, but large-scale validation of these radiotracers is required. The implementation of new processing techniques, applications of other imaging techniques and novel biomarkers can contribute to understanding AD and finding a cure.

CONCLUSIONS

Several biomarkers are proposed for the early diagnosis and longitudinal monitoring of AD with imaging techniques, but all these biomarkers have their limitations regarding specificity, reliability and sensitivity. Future perspectives. Future research should focus on expanding the employment of imaging techniques and identifying novel biomarkers that reflect AD pathology in the earliest stages.

Delusion and Delirium in Neurodegenerative Disorders: An Overlooked Relationship?

Delusions are part of the neuropsychiatric symptoms that patients suffering from neurodegenerative conditions frequently develop at some point of the disease course and are associated with an increased risk of cognitive and functional decline. Delirium is a syndrome characterized by acute onset of deficits in attention, awareness, and cognition that fluctuate in severity over a short time period. Delusions and delirium are frequently observed in the context of neurodegeneration, and their presence can easily mislead clinicians toward a misdiagnosis of psychiatric disorder further delaying the proper treatment. Risk factors for developing delusion and delirium in neurodegenerative conditions have been investigated separately while the possible interplay between these two conditions has not been explored so far. With this study, we aim to achieve a more comprehensive picture of the relationship between delusions and delirium in neurodegeneration by analyzing prevalence and subtypes of delusions in different neurodegenerative disorders; providing an overview of clinical tools to assess delusions in neurodegenerative patients and how delusions are covered by delirium assessment tools and discussing the possible common pathophysiology mechanisms between delusion and delirium in neurodegenerative patients. A more extensive characterization of the relationship between delusions and delirium may help to understand whether delusions may constitute a risk factor for delirium and may ameliorate the management of both conditions in patients with neurodegenerative disorders.

Multimodal MRI analysis of basal forebrain structure and function across the Alzheimer's disease spectrum

BACKGROUND

Dysfunction of the cholinergic basal forebrain (cBF) is associated with cognitive decline in Alzheimer's disease (AD). Multimodal MRI allows for the investigation of cBF changes in-vivo. In this study we assessed alterations in cBF functional connectivity (FC), mean diffusivity (MD), and volume across the spectrum of AD. We further assessed effects of amyloid pathology on these changes.

METHODS

Participants included healthy controls, and subjects with subjective cognitive decline (SCD), mild cognitive impairment (MCI), or AD dementia (ADD) from the multicenter DELCODE study. Resting-state functional MRI (rs-fMRI) and structural MRI data was available for 477 subjects, and a subset of 243 subjects also had DTI data available. Differences between diagnostic groups were investigated using seed-based FC, volumetric, and MD analyses of functionally defined anterior (a-cBF) and posterior (p-cBF) subdivisions of a cytoarchitectonic cBF region-of-interest. In complementary analyses groups were stratified according to amyloid status based on CSF Aβ42/40 biomarker data, which was available in a subset of participants.

RESULTS

a-cBF and p-cBF subdivisions showed regional FC profiles that were highly consistent with previously reported patterns, but there were only minimal differences between diagnostic groups. Compared to controls, cBF volumes and MD were significantly different in MCI and ADD but not in SCD. The Aβ42/40 stratified analyses largely matched these results.

CONCLUSIONS

We reproduced subregion-specific FC profiles of the cBF in a clinical sample spanning the AD spectrum. At least in this multicentric cohort study, cBF-FC did not show marked changes along the AD spectrum, and multimodal MRI did not provide more sensitive measures of AD-related cBF changes compared to volumetry.

Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment

BACKGROUND

Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic predementia phase of Alzheimer's disease dementia, characterised by cognitive and functional impairment not severe enough to fulfil the criteria for dementia. In clinical samples, people with amnestic MCI are at high risk of developing Alzheimer's disease dementia, with annual rates of progression from MCI to Alzheimer's disease estimated at approximately 10% to 15% compared with the base incidence rates of Alzheimer's disease dementia of 1% to 2% per year.

OBJECTIVES

To assess the diagnostic accuracy of structural magnetic resonance imaging (MRI) for the early diagnosis of dementia due to Alzheimer's disease in people with MCI versus the clinical follow-up diagnosis of Alzheimer's disease dementia as a reference standard (delayed verification). To investigate sources of heterogeneity in accuracy, such as the use of qualitative visual assessment or quantitative volumetric measurements, including manual or automatic (MRI) techniques, or the length of follow-up, and age of participants. MRI was evaluated as an add-on test in addition to clinical diagnosis of MCI to improve early diagnosis of dementia due to Alzheimer's disease in people with MCI.

SEARCH METHODS

On 29 January 2019 we searched Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases, MEDLINE, Embase, BIOSIS Previews, Science Citation Index, PsycINFO, and LILACS. We also searched the reference lists of all eligible studies identified by the electronic searches.

SELECTION CRITERIA

We considered cohort studies of any size that included prospectively recruited people of any age with a diagnosis of MCI. We included studies that compared the diagnostic test accuracy of baseline structural MRI versus the clinical follow-up diagnosis of Alzheimer's disease dementia (delayed verification). We did not exclude studies on the basis of length of follow-up. We included studies that used either qualitative visual assessment or quantitative volumetric measurements of MRI to detect atrophy in the whole brain or in specific brain regions, such as the hippocampus, medial temporal lobe, lateral ventricles, entorhinal cortex, medial temporal gyrus, lateral temporal lobe, amygdala, and cortical grey matter.

DATA COLLECTION AND ANALYSIS

Four teams of two review authors each independently reviewed titles and abstracts of articles identified by the search strategy. Two teams of two review authors each independently assessed the selected full-text articles for eligibility, extracted data and solved disagreements by consensus. Two review authors independently assessed the quality of studies using the QUADAS-2 tool. We used the hierarchical summary receiver operating characteristic (HSROC) model to fit summary ROC curves and to obtain overall measures of relative accuracy in subgroup analyses. We also used these models to obtain pooled estimates of sensitivity and specificity when sufficient data sets were available.

MAIN RESULTS

We included 33 studies, published from 1999 to 2019, with 3935 participants of whom 1341 (34%) progressed to Alzheimer's disease dementia and 2594 (66%) did not. Of the participants who did not progress to Alzheimer's disease dementia, 2561 (99%) remained stable MCI and 33 (1%) progressed to other types of dementia. The median proportion of women was 53% and the mean age of participants ranged from 63 to 87 years (median 73 years). The mean length of clinical follow-up ranged from 1 to 7.6 years (median 2 years). Most studies were of poor methodological quality due to risk of bias for participant selection or the index test, or both. Most of the included studies reported data on the volume of the total hippocampus (pooled mean sensitivity 0.73 (95% confidence interval (CI) 0.64 to 0.80); pooled mean specificity 0.71 (95% CI 0.65 to 0.77); 22 studies, 2209 participants). This evidence was of low certainty due to risk of bias and inconsistency. Seven studies reported data on the atrophy of the medial temporal lobe (mean sensitivity 0.64 (95% CI 0.53 to 0.73); mean specificity 0.65 (95% CI 0.51 to 0.76); 1077 participants) and five studies on the volume of the lateral ventricles (mean sensitivity 0.57 (95% CI 0.49 to 0.65); mean specificity 0.64 (95% CI 0.59 to 0.70); 1077 participants). This evidence was of moderate certainty due to risk of bias. Four studies with 529 participants analysed the volume of the total entorhinal cortex and four studies with 424 participants analysed the volume of the whole brain. We did not estimate pooled sensitivity and specificity for the volume of these two regions because available data were sparse and heterogeneous. We could not statistically evaluate the volumes of the lateral temporal lobe, amygdala, medial temporal gyrus, or cortical grey matter assessed in small individual studies. We found no evidence of a difference between studies in the accuracy of the total hippocampal volume with regards to duration of follow-up or age of participants, but the manual MRI technique was superior to automatic techniques in mixed (mostly indirect) comparisons. We did not assess the relative accuracy of the volumes of different brain regions measured by MRI because only indirect comparisons were available, studies were heterogeneous, and the overall accuracy of all regions was moderate.

AUTHORS' CONCLUSIONS

The volume of hippocampus or medial temporal lobe, the most studied brain regions, showed low sensitivity and specificity and did not qualify structural MRI as a stand-alone add-on test for an early diagnosis of dementia due to Alzheimer's disease in people with MCI. This is consistent with international guidelines, which recommend imaging to exclude non-degenerative or surgical causes of cognitive impairment and not to diagnose dementia due to Alzheimer's disease. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Future research should not focus on a single biomarker, but rather on combinations of biomarkers to improve an early diagnosis of Alzheimer's disease dementia.

Cognitive, Genetic, Brain Volume, and Diffusion Tensor Imaging Markers as Early Indicators of Dementia

BACKGROUND

Although associated with dementia and cognitive impairment, microstructural white matter integrity is a rarely used marker of preclinical dementia.

OBJECTIVE

We aimed to evaluate the individual and combined effects of multiple markers, with special focus on microstructural white matter integrity, in detecting individuals with increased dementia risk.

METHODS

A dementia-free subsample (n = 212, mean age = 71.33 years) included in the population-based Swedish National Study on Aging and Care (SNAC-K) underwent magnetic resonance imaging (T1-weighted, fluid-attenuated inversion recovery, diffusion tensor imaging), neuropsychological testing (perceptual speed, episodic memory, semantic memory, letter and category fluency), and genotyping (APOE). Incident dementia was assessed during six years of follow-up.

RESULTS

A global model (global cognition, APOE, total brain tissue volume: AUC = 0.920) rendered the highest predictive value for future dementia. Of the models based on specific markers, white matter integrity of the forceps major tract was included in the most predictive model, in combination with perceptual speed and hippocampal volume (AUC = 0.911).

CONCLUSION

Assessment of microstructural white matter integrity may improve the early detection of dementia, although the added benefit in this study was relatively small.

Diffusion Tensor Imaging Measures of Brain Connectivity for the Early Diagnosis of Alzheimer's Disease

The prognostic capacity of the diffusion tensor imaging measures fractional anisotropy (FA) and mean diffusivity (MD) to detect mild cognitive impairment (MCI) progression to Alzheimer's disease (AD) was assessed in 135 MCI patients and 72 healthy subjects over a median follow-up of 40 months. Forty-nine MCI patients (36.3%) developed AD. The factors MD left hippocampus, FA left cingulate, and FA left hippocampus emerged as predictors of progression. Age (hazard ratio [HR] 1.21), delayed text recall (HR 0.89), FA left uncinate (HR 1.90), FA left hippocampus (HR 2.21), and carrying at least one ApoE4 allele (HR 2.86) were associated with a high conversion rate. FA measures revealed the greatest discriminative capacity (Harrell's C = 0.73 versus 0.65 without FA; p = 0.034). The inclusion of FA structural connectivity data in our model improved discrimination between subjects with MCI progressing or not to dementia.

Neurobiological substrates underlying the effect of genomic risk for depression on the conversion of amnestic mild cognitive impairment

Depression increases the conversion risk from amnestic mild cognitive impairment to Alzheimer's disease with unknown mechanisms. We hypothesize that the cumulative genomic risk for major depressive disorder may be a candidate cause for the increased conversion risk. Here, we aimed to investigate the predictive effect of the polygenic risk scores of major depressive disorder-specific genetic variants (PRSsMDD) on the conversion from non-depressed amnestic mild cognitive impairment to Alzheimer's disease, and its underlying neurobiological mechanisms. The PRSsMDD could predict the conversion from amnestic mild cognitive impairment to Alzheimer's disease, and amnestic mild cognitive impairment patients with high risk scores showed 16.25% higher conversion rate than those with low risk. The PRSsMDD was correlated with the left hippocampal volume, which was found to mediate the predictive effect of the PRSsMDD on the conversion of amnestic mild cognitive impairment. The major depressive disorder-specific genetic variants were mapped into genes using different strategies, and then enrichment analyses and protein-protein interaction network analysis revealed that these genes were involved in developmental process and amyloid-beta binding. They showed temporal-specific expression in the hippocampus in middle and late foetal developmental periods. Cell type-specific expression analysis of these genes demonstrated significant over-representation in the pyramidal neurons and interneurons in the hippocampus. These cross-scale neurobiological analyses and functional annotations indicate that major depressive disorder-specific genetic variants may increase the conversion from amnestic mild cognitive impairment to Alzheimer's disease by modulating the early hippocampal development and amyloid-beta binding. The PRSsMDD could be used as a complementary measure to select patients with amnestic mild cognitive impairment with high conversion risk to Alzheimer's disease.

Predicting Imminent Progression to Clinically Significant Memory Decline Using Volumetric MRI and FDG PET

BACKGROUND

Brain imaging measurements can provide evidence of possible preclinical Alzheimer's disease (AD). Their ability to predict individual imminent clinical conversion remains unclear.

OBJECTIVE

To investigate the ability of pre-specified volumetric magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) measurements to predict which cognitively unimpaired older participants would subsequently progress to amnestic mild cognitive impairment (aMCI) within 2 years.

METHODS

From an apolipoprotein E4 (APOE4) enriched prospective cohort study, 18 participants subsequently progressed to the clinical diagnosis of aMCI or probable AD dementia within 1.8±0.8 years (progressors); 20 participants matched for sex, age, education, and APOE allele dose remained cognitively unimpaired for at least 4 years (nonprogressors). A complementary control group not matched for APOE allele dose included 35 nonprogressors. Groups were compared on baseline FDG-PET and MRI measures known to be preferentially affected in the preclinical and clinical stages of AD and by voxel-wise differences in regional gray matter volume and glucose metabolism. Receiver Operating Characteristic, binary logistic regression, and leave-one-out procedures were used to predict clinical outcome for the a priori measures.

RESULTS

Compared to non-progressors and regardless of APOE-matching, progressors had significantly reduced baseline MRI and PET measurements in brain regions preferentially affected by AD and reduced hippocampal volume was the strongest predictor of an individual's imminent progression to clinically significant memory decline (79% sensitivity/78% specificity among APOE-matched cohorts).

CONCLUSION

Regional MRI and FDG-PET measurements may be useful in predicting imminent progression to clinically significant memory decline.

Correlation Between Hippocampus MRI Radiomic Features and Resting-State Intrahippocampal Functional Connectivity in Alzheimer's Disease

Alzheimer’s disease (AD) is a neurodegenerative disease with main symptoms of chronic primary memory loss and cognitive impairment. The study aim was to investigate the correlation between intrahippocampal functional connectivity (FC) and MRI radiomic features in AD. A total of 67 AD patients and 44 normal controls (NCs) were enrolled in this study. Using the seed-based method of resting-state functional MRI (rs-fMRI), the whole-brain FC with bilateral hippocampus as seed was performed, and the FC values were extracted from the bilateral hippocampus. We observed that AD patients demonstrated disruptive FC in some brain regions in the left hippocampal functional network, including right gyrus rectus, right anterior cingulate and paracingulate gyri, bilateral precuneus, bilateral angular gyrus, and bilateral middle occipital gyrus. In addition, decreased FC was detected in some brain regions in the right hippocampal functional network, including bilateral anterior cingulate and paracingulate gyri, right dorsolateral superior frontal gyrus, and right precentral gyrus. Bilateral hippocampal radiomics features were calculated and selected using the A.K. software. Finally, Pearson’s correlation analyses were conducted between these selected features and the bilateral hippocampal FC values. The results suggested that two gray level run-length matrix (RLM) radiomic features and one gray level co-occurrence matrix (GLCM) radiomic feature weakly associated with FC values in the left hippocampus. However, there were no significant correlations between radiomic features and FC values in the right hippocampus. These findings present that the AD group showed abnormalities in the bilateral hippocampal functional network. This is a prospective study that revealed the weak correlation between the MRI radiomic features and the intrahippocampal FC in AD patients.

Secondary prevention of Alzheimer's dementia: neuroimaging contributions

BACKGROUND

In Alzheimer's disease (AD), pathological changes may arise up to 20 years before the onset of dementia. This pre-dementia window provides a unique opportunity for secondary prevention. However, exposing non-demented subjects to putative therapies requires reliable biomarkers for subject selection, stratification, and monitoring of treatment. Neuroimaging allows the detection of early pathological changes, and longitudinal imaging can assess the effect of interventions on markers of molecular pathology and rates of neurodegeneration. This is of particular importance in pre-dementia AD trials, where clinical outcomes have a limited ability to detect treatment effects within the typical time frame of a clinical trial. We review available evidence for the use of neuroimaging in clinical trials in pre-dementia AD. We appraise currently available imaging markers for subject selection, stratification, outcome measures, and safety in the context of such populations.

MAIN BODY

Amyloid positron emission tomography (PET) is a validated in-vivo marker of fibrillar amyloid plaques. It is appropriate for inclusion in trials targeting the amyloid pathway, as well as to monitor treatment target engagement. Amyloid PET, however, has limited ability to stage the disease and does not perform well as a prognostic marker within the time frame of a pre-dementia AD trial. Structural magnetic resonance imaging (MRI), providing markers of neurodegeneration, can improve the identification of subjects at risk of imminent decline and hence play a role in subject inclusion. Atrophy rates (either hippocampal or whole brain), which can be reliably derived from structural MRI, are useful in tracking disease progression and have the potential to serve as outcome measures. MRI can also be used to assess comorbid vascular pathology and define homogeneous groups for inclusion or for subject stratification. Finally, MRI also plays an important role in trial safety monitoring, particularly the identification of amyloid-related imaging abnormalities (ARIA). Tau PET to measure neurofibrillary tangle burden is currently under development. Evidence to support the use of advanced MRI markers such as resting-state functional MRI, arterial spin labelling, and diffusion tensor imaging in pre-dementia AD is preliminary and requires further validation.

CONCLUSION

We propose a strategy for longitudinal imaging to track early signs of AD including quantitative amyloid PET and yearly multiparametric MRI.

Microstructural brain changes track cognitive decline in mild cognitive impairment

Improved characterization of the microstructural brain changes occurring in the early stages of Alzheimer's disease may permit more timely disease detection. This study examined how longitudinal change in brain microstructure relates to cognitive decline in aging and prodromal Alzheimer's disease. At baseline and two-year follow-up, 29 healthy controls and 21 individuals with mild cognitive impairment or mild Alzheimer's disease underwent neuropsychological evaluation and restriction spectrum imaging (RSI). Microstructural change in the hippocampus, entorhinal cortex, and white matter tracts previously shown to be vulnerable to Alzheimer's disease, was compared between healthy controls and impaired participants. Partial correlations and stepwise linear regressions examined whether baseline RSI metrics predicted subsequent cognitive decline, or change in RSI metrics correlated with cognitive change. In medial temporal gray and white matter, restricted isotropic diffusion and crossing fibers were lower, and free water diffusion was higher, in impaired participants. Restricted isotropic diffusion in the hippocampus declined more rapidly for cognitively impaired participants. Baseline hippocampal restricted isotropic diffusion predicted cognitive decline, and change in hippocampal and entorhinal restricted isotropic diffusion correlated with cognitive decline. Within controls, changes in white matter restricted oriented diffusion and crossing fibers correlated with memory decline. In contrast, there were no correlations between rates of cortical atrophy and cognitive decline in the full sample or within controls. Changes in medial temporal lobe microarchitecture were associated with cognitive decline in prodromal Alzheimer's disease, and these changes were distinct from microstructural changes in normal cognitive aging. RSI metrics of brain microstructure may hold value for predicting cognitive decline in aging and for monitoring the course of Alzheimer's disease.

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Longitudinal diffusion MRI was conducted in individuals with MCI/AD and controls.

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Mean restricted diffusion in hippocampus declined more rapidly in MCI/AD.

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Baseline hippocampal restricted diffusion predicted cognitive decline.

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Change in medial temporal restricted diffusion correlated with cognitive decline.

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In healthy controls, white matter microstructure correlated with memory decline.

Magnetic resonance imaging in Alzheimer's disease and mild cognitive impairment

Research utilizing magnetic resonance imaging (MRI) has been crucial to the understanding of the neuropathological mechanisms behind and clinical identification of Alzheimer’s disease (AD) and mild cognitive impairment (MCI). MRI modalities show patterns of brain damage that discriminate AD from other brain illnesses and brain abnormalities that are associated with risk of conversion to AD from MCI and other behavioural outcomes. This review discusses the application of various MRI techniques to and their clinical usefulness in AD and MCI. MRI modalities covered include structural MRI, diffusion tensor imaging (DTI), arterial spin labelling (ASL), magnetic resonance spectroscopy (MRS), and functional MRI (fMRI). There is much evidence supporting the validity of MRI as a biomarker for these disorders; however, only traditional structural imaging is currently recommended for routine use in clinical settings. Future research is needed to warrant the inclusion for more advanced MRI methodology in forthcoming revisions to diagnostic criteria for AD and MCI.

Neuropsychiatric symptoms of cholinergic deficiency occur with degradation of the projections from the nucleus basalis of Meynert

This study aims to evaluate the relation between a cluster of neuropsychiatric symptoms related to cholinergic deficiency and degradation of the cortical cholinergic projections which project from the nucleus basalis of Meynert to the cerebral cortex. An atlas of the pathway from the nucleus basalis to the cortex (NbM cortical pathway) was constructed using diffusion tensor imaging and tractography in 87 memory clinic patients. Structural degradation was considered to be represented by lower fractional anisotropy (FA) and higher mean diffusivity (MD). Neuropsychiatric symptoms were assessed using the Neuropsychiatric Inventory. A predefined cluster including agitation, anxiety, apathy, delusions, hallucinations, and irritability was labeled as the cholinergic deficiency syndrome (CDS). In regression analyses, lower FA and higher MD in the NbM cortical pathway were associated with CDS symptoms but not with other neuropsychiatric symptoms. These associations were independent of cerebral atrophy and overall FA or MD. There was no association between interruption of the NbM cortical pathway by white matter hyperintensities and CDS symptoms. Cox regression suggested a trend for higher mortality with lower FA in the NbM cortical pathway may exist. These findings provide anatomical support for the hypothesis that degradation of the cholinergic projections from the nucleus basalis of Meynert may lead to a distinct clinical syndrome. Future studies could use our results to test the utility of assessing NbM projection integrity to identify patients who may benefit from cholinergic treatment or with a worse prognosis.

Effect of Alzheimer's disease risk and protective factors on cognitive trajectories in subjective memory complainers: An INSIGHT-preAD study

INTRODUCTION

Cognitive change in people at risk of Alzheimer's disease (AD) such as subjective memory complainers is highly variable across individuals.

METHODS

We used latent class growth modeling to identify distinct classes of nonlinear trajectories of cognitive change over 2 years follow-up from 265 subjective memory complainers individuals (age 70 years and older) of the INSIGHT-preAD cohort. We determined the effect of cortical amyloid load, hippocampus and basal forebrain volumes, and education on the cognitive trajectory classes.

RESULTS

Latent class growth modeling identified distinct nonlinear cognitive trajectories. Education was associated with higher performing trajectories, whereas global amyloid load and basal forebrain atrophy were associated with lower performing trajectories.

DISCUSSION

Distinct classes of cognitive trajectories were associated with risk and protective factors of AD. These associations support the notion that the identified cognitive trajectories reflect different risk for AD that may be useful for selecting high-risk individuals for intervention trials.

Hippocampus and Basal Forebrain Volumetry for Dementia and Mild Cognitive Impairment Diagnosis: Could It Be Useful in Primary Care?

BACKGROUND

Once a patient or a knowledgeable informant has noticed decline in memory or other cognitive functions, initiation of early dementia assessment is recommended. Hippocampus and cholinergic basal forebrain (BF) volumetry supports the detection of prodromal and early stages of Alzheimer's disease (AD) dementia in highly selected patient populations.

OBJECTIVE

To compare effect size and diagnostic accuracy of hippocampus and BF volumetry between patients recruited in highly specialized versus primary care and to assess the effect of white matter lesions as a proxy for cerebrovascular comorbidity on diagnostic accuracy.

METHODS

We determined hippocampus and BF volumes and white matter lesion load from MRI scans of 71 participants included in a primary care intervention trial (clinicaltrials.gov identifier: NCT01401582) and matched 71 participants stemming from a memory clinic. Samples included healthy controls and people with mild cognitive impairment (MCI), AD dementia, mixed dementia, and non-AD related dementias.

RESULTS

Volumetric measures reached similar effect sizes and cross-validated levels of accuracy in the primary care and the memory clinic samples for the discrimination of AD and mixed dementia cases from healthy controls. In the primary care MCI cases, volumetric measures reached only random guessing levels of accuracy. White matter lesions had only a modest effect on effect size and diagnostic accuracy.

CONCLUSIONS

Hippocampus and BF volumetry may usefully be employed for the identification of AD and mixed dementia, but the detection of MCI does not benefit from the use of these volumetric markers in a primary care setting.

Hippocampal volume and integrity as predictors of cognitive decline in intact elderly

The risk of Alzheimer's disease can be predicted by volumetric analyses of MRI data in the medial temporal lobe. The present study compared a volumetric measurement of the hippocampus with a novel measure of hippocampal integrity (HI) derived from the ratio of parenchyma volume over total volume. Participants were cognitively intact and aged 60 years or older at baseline, and were tested twice, roughly 3 years apart. Participants had been recruited for a study on late-life major depression (LLMD) and were evenly split between depressed patients and controls. Linear regression models were applied to the data with a cognitive composite score as the outcome, and HI and volume, together or separately, as predictors. Subsequent cognitive performance was predicted well by models that included an interaction between HI and LLMD status, such that lower HI scores predicted more cognitive decline in depressed patients. More research is needed, but tentative results from this study appear to suggest that the newly introduced measure HI is an effective tool for the purpose of predicting future changes in general cognitive ability, and especially so in individuals with LLMD.

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

CRISPR/Cas9-Correctable mutation-related molecular and physiological phenotypes in iPSC-derived Alzheimer's PSEN2 N141I neurons

Basal forebrain cholinergic neurons (BFCNs) are believed to be one of the first cell types to be affected in all forms of AD, and their dysfunction is clinically correlated with impaired short-term memory formation and retrieval. We present an optimized in vitro protocol to generate human BFCNs from iPSCs, using cell lines from presenilin 2 (PSEN2) mutation carriers and controls. As expected, cell lines harboring the PSEN2^N141I mutation displayed an increase in the Aβ42/40 in iPSC-derived BFCNs. Neurons derived from PSEN2^N141I lines generated fewer maximum number of spikes in response to a square depolarizing current injection. The height of the first action potential at rheobase current injection was also significantly decreased in PSEN2^N141I BFCNs. CRISPR/Cas9 correction of the PSEN2 point mutation abolished the electrophysiological deficit, restoring both the maximal number of spikes and spike height to the levels recorded in controls. Increased Aβ42/40 was also normalized following CRISPR/Cas-mediated correction of the PSEN2^N141I mutation. The genome editing data confirms the robust consistency of mutation-related changes in Aβ42/40 ratio while also showing a PSEN2-mutation-related alteration in electrophysiology.

Mean diffusivity in cortical gray matter in Alzheimer's disease: The importance of partial volume correction

Mean diffusivity (MD) measured by diffusion tensor imaging can reflect microstructural alterations of the brain's gray matter (GM). Therefore, GM MD may be a sensitive marker of neurodegeneration related to Alzheimer's Disease (AD). However, due to partial volume effects (PVE), differences in MD may be overestimated because of a higher degree of brain atrophy in AD patients and in cases with mild cognitive impairment (MCI). Here, we evaluated GM MD changes in AD and MCI compared with healthy controls, and the effect of partial volume correction (PVC) on diagnostic utility of MD. We determined region of interest (ROI) and voxel-wise group differences and diagnostic accuracy of MD and volume measures between matched samples of 39 AD, 39 MCI and 39 healthy subjects before and after PVC. Additionally, we assessed whether effects of GM MD values on diagnosis were mediated by volume. ROI and voxel-wise group differences were reduced after PVC. When using these ROIs for predicting group separation in logistic models, both PVE corrected and uncorrected GM MD values yielded a poorer diagnostic accuracy in single predictor models than regional volume. For the discrimination of AD patients and healthy controls, the effect of GM MD on diagnosis was significantly mediated by volume of hippocampus and posterior cingulate ROIs. Our results suggest that GM MD measurements are strongly confounded by PVE in the presence of brain atrophy, underlining the necessity of PVC when using these measurements as specific metrics of microstructural tissue degeneration. Independently of PVC, regional MD was not superior to regional volume in separating prodromal and clinical stages of AD from healthy controls.

Disrupted white matter structural networks in healthy older adult APOE ε4 carriers - An international multicenter DTI study

The ε4 allelic variant of the Apolipoprotein E gene (APOE ε4) is the best-established genetic risk factor for late-onset Alzheimer's disease (AD). White matter (WM) microstructural damages measured with Diffusion Tensor Imaging (DTI) represent an early sign of fiber tract disconnection in AD. We examined the impact of APOE ε4 on WM microstructure in elderly individuals from the multicenter European DTI Study on Dementia. Voxelwise statistical analysis of fractional anisotropy (FA), mean diffusivity, radial and axial diffusivity (MD, radD and axD respectively) was carried out using Tract-Based Spatial Statistics. Seventy-four healthy elderly individuals - 31 APOE ε4 carriers (APOE ε4+) and 43 APOE ε4 non-carriers (APOE ε4-) -were considered for data analysis. All the results were corrected for scanner acquisition protocols, age, gender and for multiple comparisons. APOE ε4+ and APOE ε4- subjects were comparable regarding sociodemographic features and global cognition. A significant reduction of FA and increased radD was found in the APOE ε4+ compared to the APOE ε4- in the cingulum, in the corpus callosum, in the inferior fronto-occipital and in the inferior longitudinal fasciculi, internal and external capsule. APOE ε4+, compared to APOE ε4- showed higher MD in the genu, right internal capsule, superior longitudinal fasciculus and corona radiate. Comparisons stratified by center supported the results obtained on the whole sample. These findings support previous evidence in monocentric studies indicating a modulatory role of APOE ɛ4 allele on WM microstructure in elderly individuals at risk for AD suggesting early vulnerability and/or reduced resilience of WM tracts involved in AD.

Cholinergic Receptor Binding in Alzheimer Disease and Healthy Aging: Assessment In Vivo with Positron Emission Tomography Imaging

OBJECTIVE

To compare regional nicotinic cholinergic receptor binding in older adults with Alzheimer disease (AD) and healthy older adults in vivo and to assess relationships between receptor binding and clinical symptoms.

METHODS

Using cross-sectional positron emission tomography (PET) neuroimaging and structured clinical assessment, outpatients with mild to moderate AD (N = 24) and healthy older adults without cognitive complaints (C group; N = 22) were studied. PET imaging of α4β2* nicotinic cholinergic receptor binding using 2-[¹⁸F]fluoro-3-(2(S)azetidinylmethoxy)pyridine (2FA) and clinical measures of global cognition, attention/processing speed, verbal memory, visuospatial memory, and neuropsychiatric symptoms were used.

RESULTS

2FA binding was lower in the AD group compared with the C group in the medial thalamus, medial temporal cortex, anterior cingulate, insula/opercula, inferior caudate, and brainstem (p < 0.05, corrected cluster), but binding was not associated with cognition. The C group had significant inverse correlations between 2FA binding in the thalamus (left: r_s = -0.55, p = 0.008; right: r_s = -0.50, p = 0.02; N = 22) and hippocampus (left: r_s = -0.65, p = 0.001; right: r_s = -0.55, p = 0.009; N = 22) and the Trails A score. The AD group had inverse correlation between 2FA binding in anterior cingulate (left: r_s = -0.50, p = 0.01; right: r_s = -0.50, p = 0.01; N = 24) and Neurobehavioral Rating Scale agitation/disinhibition factor score.

CONCLUSION

Cholinergic receptor binding is reduced in specific brain regions in mild to moderate AD and is related to neuropsychiatric symptoms. Among healthy older adults, lower receptor binding may be associated with slower processing speed. Cholinergic receptor binding in vivo may reveal links to other key brain changes associated with aging and AD and may provide a potential molecular treatment target.

Multi-modal MRI investigation of volumetric and microstructural changes in the hippocampus and its subfields in mild cognitive impairment, Alzheimer's disease, and dementia with Lewy bodies

BACKGROUND

Volumetric atrophy and microstructural alterations in diffusion tensor imaging (DTI) measures of the hippocampus have been reported in people with Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, no study to date has jointly investigated concomitant microstructural and volumetric changes of the hippocampus in dementia with Lewy bodies (DLB).

METHODS

A total of 84 subjects (23 MCI, 17 DLB, 14 AD, and 30 healthy controls) were recruited for a multi-modal imaging (3T MRI and DTI) study that included neuropsychological evaluation. Freesurfer was used to segment the total hippocampus and delineate its subfields. The hippocampal segmentations were co-registered to the mean diffusivity (MD) and fractional anisotropy (FA) maps obtained from the DTI images.

RESULTS

Both AD and MCI groups showed significantly smaller hippocampal volumes compared to DLB and controls, predominantly in the CA1 and subiculum subfields. Compared to controls, hippocampal MD was elevated in AD, but not in MCI. DLB was characterized by both volumetric and microstructural preservation of the hippocampus. In MCI, higher hippocampal MD was associated with greater atrophy of the hippocampus and CA1 region. Hippocampal volume was a stronger predictor of memory scores compared to MD within the MCI group.

CONCLUSIONS

Through a multi-modal integration, we report novel evidence that the hippocampus in DLB is characterized by both macrostructural and microstructural preservation. Contrary to recent suggestions, our findings do not support the view that DTI measurements of the hippocampus are superior to volumetric changes in characterizing group differences, particularly between MCI and controls.

Genetic and environmental influences on mean diffusivity and volume in subcortical brain regions

Increased mean diffusivity (MD) is hypothesized to reflect tissue degeneration and may provide subtle indicators of neuropathology as well as age-related brain changes in the absence of volumetric differences. Our aim was to determine the degree to which genetic and environmental variation in subcortical MD is distinct from variation in subcortical volume. Data were derived from a sample of 387 male twins (83 MZ twin pairs, 55 DZ twin pairs, and 111 incomplete twin pairs) who were MRI scanned as part of the Vietnam Era Twin Study of Aging. Quantitative estimates of MD and volume for 7 subcortical regions were obtained: thalamus, caudate nucleus, putamen, pallidum, hippocampus, amygdala, and nucleus accumbens. After adjusting for covariates, bivariate twin models were fitted to estimate the size and significance of phenotypic, genotypic, and environmental correlations between MD and volume at each subcortical region. With the exception of the amygdala, familial aggregation in MD was entirely explained by additive genetic factors across all subcortical regions with estimates ranging from 46 to 84%. Based on bivariate twin modeling, variation in subcortical MD appears to be both genetically and environmentally unrelated to individual differences in subcortical volume. Therefore, subcortical MD may be an alternative biomarker of brain morphology for complex traits worthy of future investigation. Hum Brain Mapp 38:2589-2598, 2017. © 2017 Wiley Periodicals, Inc.

MRI-Based Classification Models in Prediction of Mild Cognitive Impairment and Dementia in Late-Life Depression

Objective: Late-life depression (LLD) is associated with development of different types of dementia. Identification of LLD patients, who will develop cognitive decline, i.e., the early stage of dementia would help to implement interventions earlier. The purpose of this study was to assess whether structural brain magnetic resonance imaging (MRI) in LLD patients can predict mild cognitive impairment (MCI) or dementia 1 year prior to the diagnosis.

Methods: LLD patients underwent brain MRI at baseline and repeated clinical assessment after 1-year. Structural brain measurements were obtained using Freesurfer software (v. 5.1) from the T1W brain MRI images. MRI-based Random Forest classifier was used to discriminate between LLD who developed MCI or dementia after 1-year follow-up and cognitively stable LLD. Additionally, a previously established Random Forest model trained on 185 patients with Alzheimer’s disease (AD) vs. 225 cognitively normal elderly from the Alzheimer’s disease Neuroimaging Initiative was tested on the LLD data set (ADNI model).

Results: MCI and dementia diagnoses were predicted in LLD patients with 76%/68%/84% accuracy/sensitivity/specificity. Adding the baseline Mini-Mental State Examination (MMSE) scores to the models improved accuracy/sensitivity/specificity to 81%/75%/86%. The best model predicted MCI status alone using MRI and baseline MMSE scores with accuracy/sensitivity/specificity of 89%/85%/90%. The most important region for all the models was right ventral diencephalon, including hypothalamus. Its volume correlated negatively with the number of depressive episodes. ADNI model trained on AD vs. Controls using SV could predict MCI-DEM patients with 67% accuracy.

Conclusion: LDD patients developing MCI and dementia can be discriminated from LLD patients remaining cognitively stable with good accuracy based on baseline structural MRI alone. Baseline MMSE score improves prediction accuracy. Ventral diencephalon, including the hypothalamus might play an important role in preservation of cognitive functions in LLD.