Magnetic resonance imaging of Alzheimer's disease

Polygenic risk for Alzheimer's disease shapes hippocampal scene-selectivity

Preclinical models of Alzheimer's disease (AD) suggest APOE modulates brain function in structures vulnerable to AD pathophysiology. However, genome-wide association studies now demonstrate that AD risk is shaped by a broader polygenic architecture, estimated via polygenic risk scoring (AD-PRS). Despite this breakthrough, the effect of AD-PRS on brain function in young individuals remains unknown. In a large sample (N = 608) of young, asymptomatic individuals, we measure the impact of both (i) APOE and (ii) AD-PRS on a vulnerable cortico-limbic scene-processing network heavily implicated in AD pathophysiology. Integrity of this network, which includes the hippocampus (HC), is fundamental for maintaining cognitive function during ageing. We show that AD-PRS, not APOE, selectively influences activity within the HC in response to scenes, while other perceptual nodes remained intact. This work highlights the impact of polygenic contributions to brain function beyond APOE, which could aid potential therapeutic/interventional strategies in the detection and prevention of AD.

Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease (Review)

Alzheimer's disease (AD) is a complex and multifactorial disease. In order to understand the genetic influence in the progression of AD, and to identify novel pharmaceutical agents and their associated targets, the present study discusses computational modeling and biomarker evaluation approaches. Based on mechanistic signaling pathway approaches, various computational models, including biochemical and morphological models, are discussed to explore the strategies that may be used to target AD treatment. Different biomarkers are interpreted on the basis of morphological and functional features of amyloid β plaques and unstable microtubule‑associated tau protein, which is involved in neurodegeneration. Furthermore, imaging and cerebrospinal fluids are also considered to be key methods in the identification of novel markers for AD. In conclusion, the present study reviews various biochemical and morphological computational models and biomarkers to interpret novel targets and agonists for the treatment of AD. This review also highlights several therapeutic targets and their associated signaling pathways in AD, which may have potential to be used in the development of novel pharmacological agents for the treatment of patients with AD. Computational modeling approaches may aid the quest for the development of AD treatments with enhanced therapeutic efficacy and reduced toxicity.

Dementia in Down's syndrome: an MRI comparison with Alzheimer's disease in the general population

BACKGROUND

Down's syndrome (DS) is the most common genetic cause of intellectual disability. People with DS are at an increased risk of Alzheimer's disease (AD) compared to the general population. Neuroimaging studies of AD have focused on medial temporal structures; however, to our knowledge, no in vivo case-control study exists comparing the anatomy of dementia in DS to people with AD in the general population. We therefore compared the in vivo brain anatomy of people with DS and dementia (DS+) to those with AD in the general population.

METHOD

Using MRI in 192 adults, we compared the volume of whole brain matter, lateral ventricles, temporal lobes and hippocampus in DS subjects with and without dementia (DS+, DS-), to each other and to three non-DS groups. These included one group of individuals with AD and two groups of controls (each age-matched for their respective DS and general population AD cohorts).

RESULTS

AD and DS+ subjects showed significant reductions in the volume of the whole brain, hippocampus and temporal lobes and a significant elevation in the volume of the lateral ventricle, compared to their non-demented counterparts. People with DS+ had a smaller reduction in temporal lobe volume compared to individuals with AD.

CONCLUSIONS

DS+ and AD subjects have a significant reduction in volume of the same brain regions. We found preliminary evidence that DS individuals may be more sensitive to tissue loss than others and have less 'cognitive reserve'.

Prediction of Alzheimer's disease in mild cognitive impairment: a prospective study in Taiwan

The relationship between apolipoprotein E (ApoE) and clinical manifestations of mild cognitive impairment (MCI) has not been investigated in non-Caucasian populations. This prospective study was conducted in an ethnic Chinese population to evaluate the correlations of ApoE genotype, cognitive performance, medial temporal structure volumes, and clinical outcome in amnestic MCI. Twenty normal elders, 58 MCI, and 20 mild Alzheimer's disease (AD) patients received neuropsychological, MRI, and ApoE genotype assessments at baseline. Patients with MCI had intermediate cognitive performance and hippocampal volumes between those in normal and AD groups. In each diagnostic group, epsilon4 carriers (E4+) consistently had smaller hippocampal volume than non-carriers (E4-) did. Nineteen MCI subjects (32.7%) converted to AD during the 3-year study period. Compared with MCI non-converters and E4- MCI converters, E4+ MCI converters had the smallest hippocampal volume. However, epsilon4 was not a predictor for AD. Both cognitive performance and hippocampal volume were predictive for progression to AD. However, stepwise Cox regression model integrating both neuropsychological and radiological variables showed that global cognitive performance was the only significant predictor for AD. A poor global cognitive score may be more crucial than a small hippocampal volume in the prediction of AD.

Alzheimer's disease: models of computation and analysis of EEGs

In a recent article the authors presented a comprehensive review of research performed on computational modeling of Alzheimer's disease (AD) and its markers with a focus on computer imaging, classification models, connectionist neural models, and biophysical neural models. The popularity of imaging techniques for detection and diagnosis of possible AD stems from the relative ease with which neurological markers can be converted to visual markers. However, due to the expense of specialized experts and equipment involved in the use of imaging techniques, a subject of significant research interest is detecting markers in EEGs obtained from AD patients. In this article, the authors present a state-of-the-art review of models of computation and analysis of EEGs for diagnosis and detection of AD. This review covers three areas: time-frequency analysis, wavelet analysis, and chaos analysis. The vast number of physiological parameters involved in the poorly understood processes responsible for AD yields a large combination of parameters that can be manipulated and studied. A combination of parameters from different investigation modalities seems to be more effective in increasing the accuracy of detection-and diagnosis.

Functional neuroimaging in Alzheimer's type dementia

This article aims to review the role of the functional neuroimaging modality of positron emission tomography (PET) in the early diagnosis of Alzheimer's disease (AD). Clinical diagnosis in the early disease stages is difficult and treatments are emerging which rather than reversing structural damage are likely to slow or halt the disease process. While currently no routine diagnostic test confirms AD presence, imaging techniques are an important expanding field in biological neuropsychiatry. The challenge for neuroimaging methods is to achieve high specificity and sensitivity in early disease stages. Glucose metabolic PET imaging with fluorodeoxyglucose (FDG) has the potential to detect very early neocortical dysfunction before even abnormal neuropsychological testing is obtainable. The implications are for the identification of minimally symptomatic patients that could benefit most from treatment strategies, as well as the monitoring of treatment response and possible therapeutic deceleration of the disease. FDG PET correlates with AD neuropathology and is able to indicate disease progression or severity, meeting both functional neuroimaging prerequisites in diagnosing AD. A combination of functional neuroimaging with different techniques should be able to provide highest diagnostic specificity in diagnosing dementia. This may even lead to a new classification of dementias according to differences in the causative aetiology.

Alzheimer Disease: evaluation of a functional MR imaging index as a marker

PURPOSE

To measure changes in functional synchrony in the hippocampus in patients with mild cognitive impairment (MCI) and Alzheimer disease (AD).

MATERIALS AND METHODS

Three subject groups (nine cognitively healthy elderly control subjects, 10 patients with probable AD, and five subjects with MCI) underwent resting-state functional magnetic resonance (MR) imaging for measurement of functional synchrony in the hippocampus. Functional synchrony was defined and quantified as the mean of the cross-correlation coefficients of spontaneous low frequency (COSLOF) components between possible pairs of voxel time courses in a brain region, or the COSLOF index. The two-tailed Student t test was used to determine differences in the COSLOF index between the control group, the probable AD group, and the MCI group. An operating characteristic curve was calculated to graphically depict the tradeoff between sensitivity and specificity of the COSLOF index.

RESULTS

Functional synchrony quantified with the COSLOF index was obtained in AD, MCI, and control subjects. COSLOF index values were significantly lower in AD patients than in control subjects (t = 4.32, P <.0012). For MCI subjects, COSLOF index values were significantly higher than those of AD patients (t = -2.4052, P <.047) but significantly lower than those of control subjects (t = 2.257, P <.043). The exponential-class curve significantly fits the relationship between the COSLOF index and the Mini-Mental Status Examination score (chi(2) = 20.4), indicating the rapid decrease in cognitive capacity below a threshold of the COSLOF index.

CONCLUSION

Our results suggest that the COSLOF index could be used as a noninvasive quantitative marker for the preclinical stage of AD.

Clinical trials in AD: are current formats and outcome measures adequate?

Great strides have been made in the measurement of outcomes and treatment efficacy in clinical trials of Alzheimer disease (AD) drugs during the past 25 years. Several sensitive, reliable, and valid clinical outcome measures have been developed. The methodology, trial design, and outcome measures for demonstrating symptomatic benefits of an AD drug are now established. However, a greater challenge lies ahead. Major advances in fundamental knowledge about the pathophysiology of the disease and in animal models have transformed the focus of current efforts to developing and testing therapies that may actually slow disease progression, delay the onset of symptoms, and even ultimately prevent the disease. The long-duration trials that will likely be necessary to demonstrate an effect on disease progression will be costly and difficult. Proof-of-concept trials and subsequent long-term trials could gain power and efficiency from use of biologic markers of underlying disease severity, but currently available biologic markers are not ideal. A major barrier to such trials is their size and cost. One approach to reducing the cost would be to recruit "enriched" samples of subjects who are at greater risk of developing AD during the trial than the general, elderly population. The major effort required to screen and recruit large numbers of subjects for such trials also contributes to the cost. Probably the biggest problem currently is the enormous effort and cost of conducting periodic clinical evaluations to determine if subjects have declined or developed dementia. Research to develop more efficient assessment methods is clearly needed. Data acquisition over the Internet is potentially efficient and attractive and may become practical as Internet accessibility increases.

MR signal intensity of gray matter/white matter contrast and intracranial fat: effects of age and sex

Signal intensity (SI) values of gray- and white-matter brain regions of interest (ROIs) were obtained from T(2)- and proton density-weighted magnetic resonance (MR) images of 58 normal subjects aged 22-82 years (31 females, 52.3+/-18.8 years; 27 males, 54.1+/-18.1 years). Sampled ROIs included the caudate, putamen, thalamus, orbitofrontal gyrus, gyrus rectus, uncus, frontal white matter, anterior and posterior corpus callosum, cranial-cervical junction fat, and retroorbital fat. Effects of age and sex on SI were examined using repeated-measures analysis of covariance. For both T(2)- and proton density-weighted acquisitions, a significant inverse relationship between age and SI was observed for the ratio of all summed gray-matter ROIs divided by summed white-matter ROIs. This relationship was additionally observed for ratios of both subcortical gray/white matter and cortical gray/white matter. Females compared with males had significantly lower cortical gray/white matter ratios on T(2)-weighted scans. Differences in SI were observed between cranial-cervical junction fat and retroorbital fat on both acquisitions, with females showing significantly higher values for cranial-cervical junction fat and males showing higher values for retroorbital fat. Implications for brain morphometry, the use of fat as a reference standard, and other issues in neuroimaging are discussed.

Hippocampal formation glucose metabolism and volume losses in MCI and AD

We used MRI volume sampling with coregistered and atrophy corrected FDG-PET scans to test three hypotheses: 1) hippocampal formation measures are superior to temporal neocortical measures in the discrimination of normal (NL) and mild cognitive impairment (MCI); 2) neocortical measures are most useful in the separation of Alzheimer disease (AD) from NL or MCI; 3) measures of PET glucose metabolism (MRglu) have greater diagnostic sensitivity than MRI volume. Three groups of age, education, and gender matched NL, MCI, and AD subjects were studied. The results supported the hypotheses: 1) entorhinal cortex MRglu and hippocampal volume were most accurate in classifying NL and MCI; 2) both imaging modalities identified the temporal neocortex as best separating MCI and AD, whereas widespread changes accurately classified NL and AD; 3) In most between group comparisons regional MRglu measures were diagnostically superior to volume measures. These cross-sectional data show that in MCI hippocampal formation changes exist without significant neocortical changes. Neocortical changes best characterize AD. In both MCI and AD, metabolism reductions exceed volume losses.

Magnetic resonance imaging and magnetic resonance spectroscopy in dementias

This article reviews recent studies of magnetic resonance imaging and magnetic resonance spectroscopy in dementia, including Alzheimer's disease, frontotemporal dementia, dementia with Lewy bodies, idiopathic Parkinson's disease, Huntington's disease, and vascular dementia. Magnetic resonance imaging and magnetic resonance spectroscopy can detect structural alteration and biochemical abnormalities in the brain of demented subjects and may help in the differential diagnosis and early detection of affected individuals, monitoring disease progression, and evaluation of therapeutic effect.

Functional neuroimaging

Functional neuroimaging represents an area of brain imaging that has undergone tremendous advancements in the last decade. It is now possible to design experiments that elucidate the functional interplay between brain regions that give rise to specific human cognitive processes. Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) form the core technologies that have allowed such studies. This article reviews the basis of these techniques, their strengths and limitations, the underlying neurophysiology, and the future of functional neuroimaging.

Metabolic brain mapping in Alzheimer's disease using proton magnetic resonance spectroscopy

Alzheimer's disease (AD) is a progressive disorder associated with disruption of neuronal function and neuronal loss. N-acetylaspartate (NAA) is a marker of neuronal content and can be assessed using proton (1H) magnetic resonance spectroscopy (MRS). We utilized 1H-MRS (two-dimensional chemical-shift imaging) to assess amplitudes and areas of NAA, as well as choline moieties (Cho), creatine (Cr) and myo-inositol (mI), in 15 AD patients compared with 14 control subjects. Voxels were classified as predominantly cortical gray matter (CGM), subcortical gray matter (SGM), or white matter (WM). Compared with control subjects, AD patients exhibited decreased NAA/Cho and NAA/Cr amplitudes, whereas an increase was observed in Cho/Cr and in amplitude ratios involving mI. Area ratios were significant in the same direction for NAA/Cho, NAA/Cr, mI/Cr and mI/NAA. No significant effects of tissue type were observed; however, significant group x tissue type interactions were noted for Cho/Cr and mI/Cr amplitudes. Our study confirms that 1H-MRS can identify distinct physicochemical alterations in AD patients, reflecting membrane changes and diminished neuronal function. These alterations can be used as longitudinal markers for the disease.

Evolution in the conceptualization of dementia and Alzheimer's disease: Greco-Roman period to the 1960s

Most histories of senile dementia commence with Alois Alzheimer's description in 1906 of the first case of Alzheimer's disease, yet the history of senile dementia before 1906 is quite rich, dating back to the ancient Greek and Roman philosophers and physicians. Over the 2500 years since ancient times, the concept of senile dementia has evolved from a rather vague notion that mental decline occurred inevitably in old age, to become defined today by a distinct set of clinical and pathological features with the potential for treatment and prevention within grasp. Throughout history, many elderly individuals with unpredictable behavior were sequestered in institutions, and the line between mental disorders and senile dementia was hazy at best. The identification of Alzheimer's disease at the onset of the 20th century was a turning point for the understanding of senile dementia, and the concepts and histological findings presented by the early researchers of Alzheimer's disease remain relevant still today. Indeed, these early findings are proving to be a continuing source of insight, as many of the issues debated at the turn of the century remain unresolved still today. This paper thus traces the history of the evolution of our current conceptualization of Alzheimer's disease from the amorphous Greco-Roman concept of age-associated dementia.