Neuroimaging in aging and neurologic diseases

Multiple Early Biomarkers to Predict Cognitive Decline in Dementia-Free Older Adults

INTRODUCTION

Baseline olfactory impairment, poor performance on cognitive test, and medial temporal lobe atrophy are considered biomarkers for predicting future cognitive decline in dementia-free older adults. However, the combined effect of these predictors has not been fully investigated.

METHODS

A group of 110 participants without dementia were continuously recruited into this study, and underwent olfactory, cognitive tests and MRI scanning at baseline and 5-year follow-up. Olfactory function was assessed using the University of Pennsylvania Smell Identification Test (UPSIT). Participants were divided into the cognitive decliners and non-decliners.

RESULTS

Among 87 participants who completed the 5-year follow-up, cognitive decline was present in 32 cases and 55 remained stable. Compared with non-decliners, cognitive decliners presented lower scores on both the UPSIT and the Montreal Cognitive Assessment (MoCA), and smaller hippocampal volume at baseline (all P < .001). The logistic regression analysis revealed that lower scores on UPSIT and MoCA, and smaller hippocampal volume were strongly associated with subsequent cognitive decline, respectively (all P < .001). For the prediction of cognitive decline, lower score on UPSIT performed the sensitivity of 63.6% and specificity of 81.2%, lower score on MoCA with the sensitivity of 74.5% and specificity of 65.6%, smaller hippocampal volume with the sensitivity of 70.9% and specificity of 78.1%, respectively. Combining three predictors resulted in the sensitivity of 83.6% and specificity of 93.7%.

CONCLUSIONS

The combination of olfactory test, cognitive test with structural MRI may enhance the predictive ability for future cognitive decline for dementia-free older adults.

Dendrimers-Novel Therapeutic Approaches for Alzheimer's Disease

Dendrimers are covalently bonded globular nanostructures that may be used in the treatment of Alzheimer's disease (AD). Nowadays, AD therapies are focused on improving cognitive functioning and not causal treatment. However, this may change with the use of dendrimers, which are being investigated as a drug-delivery system or as a drug per se. With their ability to inhibit amyloid formation and their anti-tau properties, they are a promising therapeutic option for AD patients. Studies have shown that dendrimers may inhibit amyloid formation in at least two ways: by blocking fibril growth and by breaking already existing fibrils. Neurofibrillary tangles (NFTs) are abnormal filaments built by tau proteins that can be accumulated in the cell, which leads to the loss of cytoskeletal microtubules and tubulin-associated proteins. Cationic phosphorus dendrimers, with their anti-tau properties, can induce the aggregation of tau into amorphous structures. Drug delivery to mitochondria is difficult due to poor transport across biological barriers, such as the inner mitochondrial membrane, which is highly negatively polarized. Dendrimers may be potential nanocarriers and increase mitochondria targeting. Another considered use of dendrimers in AD treatment is as a drug-delivery system, for example, carbamazepine (CBZ) or tacrine. They can also be used to transport siRNA into neuronal tissue and to carry antioxidants and anti-inflammatory drugs to act protectively on the nervous system.

Spectrum of neurodegenerative disorders in neurology outpatient department: A cross-sectional study

Background and Aims

Neurodegenerative disorders (NDDs) are a growing global health concern with a rise in prevalence with the aging population, leading to increased healthcare utilization and costs. Understanding its prevalence is crucial for effective diagnostics and resource allocation, especially in developing nations with limited resources. This study aims to explore the frequency and types of NDDs, while also collecting demographic, clinical, and neuro-radiological data from patients with NDDs attending a tertiary care hospital in Nepal.

Methods

This was a single-center based cross-sectional descriptive study conducted at a Neurology outpatient department in a tertiary level hospital in Nepal in which patients aged 18 and above diagnosed with NDDs (May 2023-July 2023) were included. Data were collected and analyzed in SPSS Inc. This study has been presented by the STROBES guidelines.

Results

The mean age of the 71 patients included in the study was 65.6 ± 13.3 years. Parkinsonian disorder (n = 41, 57.7%) was the most common NDD diagnosed. Patients belonging to the age group 60-79 years represented 62% of all outpatient visits. Tremors of the upper extremity and impairment of memory were the most commonly encountered first symptoms at onset. Predominant cognitive changes in our study were memory impairment and mood changes. Extrapyramidal features such as gait disturbance, resting tremor, rigidity, and bradykinesia were present. More than half of the patients had age-related cerebral atrophy on neuroimaging followed by chronic small vessel ischemic changes.

Conclusion

Diagnosing NDDs poses challenges, and our study underscores Parkinsonian disorder, specifically Parkinson's disease, as the prevailing neurodegenerative condition in our population. Emphasizing its prevalence among the elderly, particularly with tremors as the primary presenting symptom, highlights the necessity for targeted interventions in this demographic.

Entorhinal cortex astrocytic atrophy in human frontotemporal dementia

The pathophysiology of Fronto Temporal Dementia (FTD) remains poorly understood, specifically the role of astroglia. Our aim was to explore the hypothesis of astrocytic alterations as a component for FTD pathophysiology. We performed an in-depth tri-dimensional (3-D) anatomical and morphometric study of glial fibrillary acidic protein (GFAP)-positive and glutamine synthetase (GS)-positive astrocytes in the human entorhinal cortex (EC) of FTD patients. The studies at this level in the different types of human dementia are scarce. We observed a prominent astrocyte atrophy of GFAP-positive astrocytes and co-expressing GFAP/GS astrocytes, characterised by a decrease in area and volume, whilst minor changes in GS-positive astrocytes in FTD compared to non-dementia controls (ND) samples. This study evidences the importance of astrocyte atrophy and dysfunction in human EC. We hypothesise that FTD is not only a neuropathological disease, but also a gliopathological disease having a major relevance in the understanding the astrocyte role in FTD pathological processes and development.

Genus Curcuma: chemical and ethnopharmacological role in aging process

Aging or senescence is part of human life development with many effects on the physical, mental, and physiological aspects which may lead to age-related deterioration in many organs. Genus Curcuma family Zingieraceae represents one of the well-studied and medically important genera with more than eighty species. The genus is reported to contain different classes of biologically active compounds that are mainly presented in diphenylheptanoids, diphenylpentanoids, diphenylalkanoids, phenylpropene derivatives, alkaloids, flavonoids, chromones, terpenoids, phenolic acids and volatile constituents. Rhizomes and roots of such species are rich with main phytoconstituents viz. curcumin, demethoxycurcumin and bis-demethoxycurcumin. A wide variety of biological activities were demonstrated for different extracts and essential oils of genus Curcuma members including antioxidant, anti-inflammatory, cytotoxic and neuroprotective. Thus, making them as an excellent safe source for nutraceutical products and as a continuous promising area of research on lead compounds that may help in the slowing down of the aging process especially the neurologic and mental deterioration that are usually experienced upon aging. In this review different species of the genus Curcuma were summarized with their phytochemical and biological activities highlighting their role as antiaging agents. The data were collected from different search engines viz. Pubmed®, Google Scholar®, Scopus® and Web of Science® limiting the search to the period between 2003 up till now.

Trajectories and contributing factors of neural compensation in healthy and pathological aging

Neural degeneration is a hallmark of healthy aging and can be associated with specific cognitive impairments. However, neural degeneration per se is not matched by unremitting declines in cognitive abilities. Instead, middle-aged and older adults typically maintain surprisingly high levels of cognitive functioning, suggesting that the human brain can adapt to structural degeneration by neural compensation. Here, we summarize prevailing theories and recent empirical studies on neural compensation with a focus on often neglected contributing factors, such as lifestyle, metabolism and neural plasticity. We suggest that these factors moderate the relationship between structural integrity and neural compensation, maintaining psychological well-being and behavioral functioning. Finally, we discuss that a breakdown in neural compensation may pose a tipping point that distinguishes the trajectories of healthy vs pathological aging, but conjoint support from psychology and cognitive neuroscience for this alluring view is still scarce. Therefore, future experiments that target the concomitant processes of neural compensation and associated behavior will foster a comprehensive understanding of both healthy and pathological aging.

Cognitive Dysfunction in Patients Treated with Androgen Deprivation Therapy: A Multimodality Functional Imaging Study to Evaluate Neuroinflammation

Background

Androgen deprivation therapy (ADT) for prostate cancer is implicated as a possible cause of cognitive impairment (CI). CI in dementia and Alzheimer's disease is associated with neuroinflammation. In this study, we investigated a potential role of neuroinflammation in ADT-related CI.

Methods

Patients with prostate cancer on ADT for ≥3 months were categorized as having ADT-emergent CI or normal cognition (NC) based on self-report at interview. Neuroinflammation was evaluated using positron emission tomography (PET) with the translocator protein (TSPO) radioligand [11C]-PBR28. [11C]-PBR28 uptake in various brain regions was quantified as standardized uptake value (SUVR, normalized to cerebellum) and related to blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) choice-reaction time task (CRT) activation maps.

Results

Eleven patients underwent PET: four with reported CI (rCI), six with reported NC (rNC), and one status unrecorded. PET did not reveal any between-group differences in SUVR regionally or globally. There was no difference between groups on brain activation to the CRT. Regardless of the reported cognitive status, there was strong correlation between PET-TSPO signal and CRT activation in the hippocampus, amygdala, and medial cortex.

Conclusions

We found no difference in neuroinflammation measured by PET-TSPO between patients with rCI and rNC. However, we speculate that the strong correlation between TSPO uptake and BOLD-fMRI activation in brain regions involved in memory and known to have high androgen-receptor expression mediating plasticity (hippocampus and amygdala) might reflect inflammatory effects of ADT with compensatory upregulated/increased synaptic functions. Further studies of this imaging readout are warranted to investigate ADT-related CI.

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis.

Neuroimaging in Dementia

OBJECTIVE

Neurodegenerative diseases are significant health concerns with regard to morbidity and social and economic hardship around the world. This review describes the state of the field of neuroimaging measures as biomarkers for detection and diagnosis of both slowly progressing and rapidly progressing neurodegenerative diseases, specifically Alzheimer disease, vascular cognitive impairment, dementia with Lewy bodies or Parkinson disease dementia, frontotemporal lobar degeneration spectrum disorders, and prion-related diseases. It briefly discusses findings in these diseases in studies using MRI and metabolic and molecular-based imaging (eg, positron emission tomography [PET] and single-photon emission computerized tomography [SPECT]).

LATEST DEVELOPMENTS

Neuroimaging studies with MRI and PET have demonstrated differential patterns of brain atrophy and hypometabolism in different neurodegenerative disorders, which can be useful in differential diagnoses. Advanced MRI sequences, such as diffusion-based imaging, and functional MRI (fMRI) provide important information about underlying biological changes in dementia and new directions for development of novel measures for future clinical use. Finally, advancements in molecular imaging allow clinicians and researchers to visualize dementia-related proteinopathies and neurotransmitter levels.

ESSENTIAL POINTS

Diagnosis of neurodegenerative diseases is primarily based on symptomatology, although the development of in vivo neuroimaging and fluid biomarkers is changing the scope of clinical diagnosis, as well as the research into these devastating diseases. This article will help inform the reader about the current state of neuroimaging in neurodegenerative diseases, as well as how these tools might be used for differential diagnoses.

The Emerging Role of Combined Brain/Heart Magnetic Resonance Imaging for the Evaluation of Brain/Heart Interaction in Heart Failure

Heart failure (HF) patients frequently develop brain deficits that lead to cognitive dysfunction (CD), which may ultimately also affect survival. There is an important interaction between brain and heart that becomes crucial for survival in patients with HF. Our aim was to review the brain/heart interactions in HF and discuss the emerging role of combined brain/heart magnetic resonance imaging (MRI) evaluation. A scoping review of published literature was conducted in the PubMed EMBASE (OVID), Web of Science, Scopus and PsycInfo databases. Keywords for searches included heart failure, brain lesion, brain, cognitive, cognitive dysfunction, magnetic resonance imaging cardiovascular magnetic resonance imaging electroencephalogram, positron emission tomography and echocardiography. CD testing, the most commonly used diagnostic approach, can identify neither subclinical cases nor the pathophysiologic background of CD. A combined brain/heart MRI has the capability of diagnosing brain/heart lesions at an early stage and potentially facilitates treatment. Additionally, valuable information about edema, fibrosis and cardiac remodeling, provided with the use of cardiovascular magnetic resonance, can improve HF risk stratification and treatment modification. However, availability, familiarity with this modality and cost should be taken under consideration before final conclusions can be drawn. Abnormal CD testing in HF patients is a strong motivating factor for applying a combined brain/heart MRI to identify early brain/heart lesions and modify risk stratification accordingly.

Dissecting the clinical heterogeneity of early-onset Alzheimer's disease

Early-onset Alzheimer's disease (EOAD) is a rare but particularly devastating form of AD. Though notable for its high degree of clinical heterogeneity, EOAD is defined by the same neuropathological hallmarks underlying the more common, late-onset form of AD. In this review, we describe the various clinical syndromes associated with EOAD, including the typical amnestic phenotype as well as atypical variants affecting visuospatial, language, executive, behavioral, and motor functions. We go on to highlight advances in fluid biomarker research and describe how molecular, structural, and functional neuroimaging can be used not only to improve EOAD diagnostic acumen but also enhance our understanding of fundamental pathobiological changes occurring years (and even decades) before the onset of symptoms. In addition, we discuss genetic variation underlying EOAD, including pathogenic variants responsible for the well-known mendelian forms of EOAD as well as variants that may increase risk for the much more common forms of EOAD that are either considered to be sporadic or lack a clear autosomal-dominant inheritance pattern. Intriguingly, specific pathogenic variants in PRNP and MAPT-genes which are more commonly associated with other neurodegenerative diseases-may provide unexpectedly important insights into the formation of AD tau pathology. Genetic analysis of the atypical clinical syndromes associated with EOAD will continue to be challenging given their rarity, but integration of fluid biomarker data, multimodal imaging, and various 'omics techniques and their application to the study of large, multicenter cohorts will enable future discoveries of fundamental mechanisms underlying the development of EOAD and its varied clinical presentations.

Combining PET with MRI to improve predictions of progression from mild cognitive impairment to Alzheimer's disease: an exploratory radiomic analysis study

Background

This study aimed to explore the potential of a combination of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) and magnetic resonance imaging (MRI) to improve predictions of conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD). The predictive performances and specific associated biomarkers of these imaging techniques used alone (single-modality imaging) and in combination (dual-modality imaging) were compared.

Methods

This study enrolled 377 patients with MCI and 94 healthy control participants from 2 medical centers. Enrolment was based on the patients' brain MRI and PET images. Radiomic analysis was performed to evaluate the predictive performance of dual-modality 18F-FDG PET and MRI scans. Regions of interest (ROIs) were determined using an a priori brain atlas. Radiomic features in these ROIs were extracted from the MRI and 18F-FDG PET scan data. These features were either concatenated or used separately to select features and construct Cox regression models for prediction in each modality. Harrell's concordance index (C-index) was then used to assess the predictive accuracies of the resulting models, and correlations between the MRI and 18F-FDG PET features were evaluated.

Results

The C-indices for the two test datasets were 0.77 and 0.80 for dual-modality 18F-FDG PET/MRI, 0.75 and 0.73 for single-modality 18F-FDG PET, and 0.74 and 0.76 for single-modality MRI. In addition, there was a significant correlation between the crucial image signatures of the different modalities.

Conclusions

These results indicate the value of imaging features in monitoring the progress of MCI in populations at high risk of developing AD. However, the incremental benefit of combining 18F-FDG PET and MRI is limited, and radiomic analysis of a single modality may yield acceptable predictive results.

Using radiomics-based modelling to predict individual progression from mild cognitive impairment to Alzheimer's disease

BACKGROUND

Predicting the risk of disease progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) has important clinical significance. This study aimed to provide a personalized MCI-to-AD conversion prediction via radiomics-based predictive modelling (RPM) with multicenter 18F-fluorodeoxyglucose positron emission tomography (FDG PET) data.

METHOD

FDG PET and neuropsychological data of 884 subjects were collected from Huashan Hospital, Xuanwu Hospital, and from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. First, 34,400 radiomic features were extracted from the 80 regions of interest (ROIs) for all PET images. These features were then concatenated for feature selection, and an RPM model was constructed and validated on the ADNI dataset. In addition, we used clinical data and the routine semiquantification index (standard uptake value ratio, SUVR) to establish clinical and SUVR Cox models for further comparison. FDG images from local hospitals were used to explore RPM performance in a separate cohort of individuals with healthy controls and different cognitive levels (a complete AD continuum). Finally, correlation analysis was conducted between the radiomic biomarkers and neuropsychological assessments.

RESULTS

The experimental results showed that the predictive performance of the RPM Cox model was better than that of other Cox models. In the validation dataset, Harrell's consistency coefficient of the RPM model was 0.703 ± 0.002, while those of the clinical and SUVR models were 0.632 ± 0.006 and 0.683 ± 0.009, respectively. Moreover, most crucial imaging biomarkers were significantly different at different cognitive stages and significantly correlated with cognitive disease severity.

CONCLUSION

The preliminary results demonstrated that the developed RPM approach has the potential to monitor progression in high-risk populations with AD.

Altered substrate metabolism in neurodegenerative disease: new insights from metabolic imaging

Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD), Parkinson's disease (PD) and multiple sclerosis (MS), are relatively common and devastating neurological disorders. For example, there are 6 million individuals living with AD in the United States, a number that is projected to grow to 14 million by the year 2030. Importantly, AD, PD and MS are all characterized by the lack of a true disease-modifying therapy that is able to reverse or halt disease progression. In addition, the existing standard of care for most NDs only addresses the symptoms of the disease. Therefore, alternative strategies that target mechanisms underlying the neuropathogenesis of disease are much needed. Recent studies have indicated that metabolic alterations in neurons and glia are commonly observed in AD, PD and MS and lead to changes in cell function that can either precede or protect against disease onset and progression. Specifically, single-cell RNAseq studies have shown that AD progression is tightly linked to the metabolic phenotype of microglia, the key immune effector cells of the brain. However, these analyses involve removing cells from their native environment and performing measurements in vitro, influencing metabolic status. Therefore, technical approaches that can accurately assess cell-specific metabolism in situ have the potential to be transformative to our understanding of the mechanisms driving AD. Here, we review our current understanding of metabolism in both neurons and glia during homeostasis and disease. We also evaluate recent advances in metabolic imaging, and discuss how emerging modalities, such as fluorescence lifetime imaging microscopy (FLIM) have the potential to determine how metabolic perturbations may drive the progression of NDs. Finally, we propose that the temporal, regional, and cell-specific characterization of brain metabolism afforded by FLIM will be a critical first step in the rational design of metabolism-focused interventions that delay or even prevent NDs.

Recent Developments in Diagnosis of Epilepsy: Scope of MicroRNA and Technological Advancements

Epilepsy is one of the most common neurological disorders, characterized by recurrent seizures, resulting from abnormally synchronized episodic neuronal discharges. Around 70 million people worldwide are suffering from epilepsy. The available antiepileptic medications are capable of controlling seizures in around 60-70% of patients, while the rest remain refractory. Poor seizure control is often associated with neuro-psychiatric comorbidities, mainly including memory impairment, depression, psychosis, neurodegeneration, motor impairment, neuroendocrine dysfunction, etc., resulting in poor prognosis. Effective treatment relies on early and correct detection of epileptic foci. Although there are currently a few well-established diagnostic techniques for epilepsy, they lack accuracy and cannot be applied to patients who are unsupportive or harbor metallic implants. Since a single test result from one of these techniques does not provide complete information about the epileptic foci, it is necessary to develop novel diagnostic tools. Herein, we provide a comprehensive overview of the current diagnostic tools of epilepsy, including electroencephalography (EEG) as well as structural and functional neuroimaging. We further discuss recent trends and advances in the diagnosis of epilepsy that will enable more effective diagnosis and clinical management of patients.

A single mode of population covariation associates brain networks structure and behavior and predicts individual subjects' age

Multiple human behaviors improve early in life, peaking in young adulthood, and declining thereafter. Several properties of brain structure and function progress similarly across the lifespan. Cognitive and neuroscience research has approached aging primarily using associations between a few behaviors, brain functions, and structures. Because of this, the multivariate, global factors relating brain and behavior across the lifespan are not well understood. We investigated the global patterns of associations between 334 behavioral and clinical measures and 376 brain structural connections in 594 individuals across the lifespan. A single-axis associated changes in multiple behavioral domains and brain structural connections (r = 0.5808). Individual variability within the single association axis well predicted the age of the subject (r = 0.6275). Representational similarity analysis evidenced global patterns of interactions across multiple brain network systems and behavioral domains. Results show that global processes of human aging can be well captured by a multivariate data fusion approach.

The influence of white matter hyperintensity on cognitive impairment in Parkinson's disease

The aim of this meta‐analysis was to review systematically and to identify the relationship between the severity and location of white matter hyperintensities (WMHs) and the degree of cognitive decline in patients with Parkinson’s disease (PD). We searched the PubMed, EMBASE, Web of Science, Ovid, and Cochrane Library databases for clinical trials of the severity and location of WMHs on the degree of cognitive impairment in PD through October 2020. We conducted the survey to compare the association of WMH burden in patients with PD with mild cognitive impairment (PD‐MCI) versus those with normal cognition (PD‐NC) and in patients with PD with dementia (PDD) versus those with PD without dementia (PD‐ND). Nine studies with PD‐MCI versus PD‐NC and 10 studies with PDD versus PD‐ND comparisons were included. The WMH burden in PD‐MCI patients was significantly different compared to that in PD‐NC patients (standard mean difference, SMD = 0.39, 95% CI: 0.12 to 0.66, p = 0.005), while there was no correlation shown in the age‐matched subgroup of the comparison. In addition, PDD patients had a significantly higher burden of WMHs (SMD = 0.8, 95% CI: 0.44 to 1.71, p < 0.0001), especially deep white matter hyperintensities (SMD = 0.54, 95% CI: 0.36 to 0.73, p < 0.00001) and periventricular hyperintensities (SMD = 0.70, 95% CI: 0.36 to 1.04, p < 0.0001), than PD‐NC patients, regardless of the adjustment of age. WMHs might be imaging markers for cognitive impairment in PDD but not in PD‐MCI, regardless of age, vascular risk factors, or race. Further prospective studies are needed to validate the conclusions.

Differentiating dementia with Lewy bodies from Alzheimer's disease and Parkinson's disease dementia: an update on imaging modalities

Dementia with Lewy bodies is the second most common cause of neurodegenerative dementia after Alzheimer's disease. Dementia with Lewy bodies can provide a diagnostic challenge due to the frequent overlap of clinical signs with other neurodegenerative conditions, namely Parkinson's disease dementia, and Alzheimer's disease. Part of this clinical overlap is due to the neuropathological overlap. Dementia with Lewy bodies is characterized by the accumulation of aggregated α-synuclein protein in Lewy bodies, similar to Parkinson's disease and Parkinson's disease dementia. However, it is also frequently accompanied by aggregation of amyloid-beta and tau, the pathological hallmarks of Alzheimer's disease. Neuroimaging is central to the diagnostic process. This review is an overview of both established and evolving imaging methods that can improve diagnostic accuracy and improve management of this disorder.

A novel variant c.3706C>T p.(Avg 1236Cys) in the ABCA7 gene in a Saudi patient with susceptibility to Alzheimer's disease 9

Alzheimer's disease (AD) is the most common cause of dementia with around 50 million people suffering from this disease worldwide. Mutations in the ATP-binding cassette sub-family A member 7 (ABCA7) have been reported to cause susceptibility to AD 9 (OMIM #608907). In this study, we report a novel variant in ABCA7 in a Saudi patient with susceptibility to AD 9 and a strong family history of neurodegenerative disorders, which may be explained by the same variant. We studied a single 57-year-old female patient with typical symptoms of AD supported by MRI findings from a Saudi family with a positive history of a similar disease in multiple individuals. The case study was conducted in King Abdulaziz Medical City in Jeddah, Saudi Arabia. Whole-exome sequencing identified the novel heterozygous variant c.3706C>T p.(Avg 1236Cys) in the ABCA7 gene, which leads to an amino acid exchange. Furthermore, bioinformatics in silico programs predict a pathogenic effect for this variant. To the best of our knowledge, the variant has not been described in the literature so far as evidenced by a thorough literature review using multiple databases such as Ovid, Medline, EMBASE, ProQuest, Science Direct, Google Scholar, and PubMed. In this article, we reported a middle-aged Saudi woman with a novel variant in ABCA7 who had clinical features of both AD and Parkinson's disease. Given the reported function of this gene, it is most likely that it is etiological and pathological because of the presenting complex neurological disease due to decreased clearance of β-amyloid and α-Synuclein. We illustrate the importance of this interesting gene that could be implicated in several neurodegenerative disorders.