Sze Ying, Peiyan Wong
Photo credit: Fechi Fajardo/Flickr/CC
With the global population aging and increasing life expectancy, the occurrence of dementia is increasing. Worldwide, the number of people with dementia stands at 35.7 million, and is projected to double every 20 years (World Health Organization, 2012). In Singapore, the prevalence rate of people with dementia aged 65 years and above is currently 6.2%, and is expected to rise as the population ages (Alzheimer's Disease Association (Singapore), 2010). Dementia is a chronic and progressive disease that is characterized by an accelerated rate of cognitive decline compared to that of normal aging. Multiple aspects of cognition are affected, including memory, orientation, problem solving, comprehension, learning, language and judgment. In the late-stage of the disease, patients lose the ability to have a conversation with others, control movement, and even respond to their environment. At this stage, patients will require help for many daily tasks, such as eating, bathing or sitting up. Due to its chronic and debilitating nature, dementia not only places a huge physical and emotional burden on the immediate caregivers, but is also a substantial economic burden on the society. Today, dementia is one of the costliest diseases in developed countries. In 2010, the global cost of dementia is estimated to be US$605 billion, amounting to 1% of the worldwide gross domestic product.
Paradigm Shift in Research
As patients usually live an average of seven years after diagnosis, a significant portion of the healthcare costs of dementia is spent on long-term, and mostly palliative, treatments. For instance, current treatments for one of the most common subtypes of dementia, Alzheimer's disease, only slows down disease progression, but does not cure it. This is because at the time of diagnosis, which is when mental decline is obvious, 40-50% of the patient's brain would already have suffered damage too extensive to be rescued by the drugs that are currently available. Increasing evidence shows that dementia has a pre-clinical phase, which can last for years, during which pathological processes are occurring before the patient shows the first signs of dementia (Figure 1). By administering therapeutic interventions during this critical window, the onset of dementia may be prevented or delayed. This will result in a reduction of disease prevalence and an alleviation of the associated socioeconomic burden. This has resulted in a paradigm shift in dementia research; from finding a cure for symptomatic dementia patients, to identifying and administering intervening therapies to at-risk, pre-clinical individuals.
Currently, individuals who exhibit "mild cognitive impairment" (MCI), defined as a mild but abnormal form of cognitive decline, will be considered as at risk for developing dementia. This is because almost all dementia patients will have had experienced MCI before being diagnosed for dementia. However, the progression from MCI to dementia is not absolute, as only 10-15% of MCI individuals will eventually develop dementia. Thus, a significant proportion of the identified individuals will not deteriorate beyond MCI. Therein lies
the challenge of developing a set of sensitive and comprehensive diagnostic criteria, which can reliably identify individuals with MCI who will develop dementia, as inaccurate identification may cause undue alarm and concern, and also increase the cost of erroneous healthcare.
There is currently a worldwide effort to identify effective biomarkers for early detection of dementia. Biomarkers are physiological, biochemical or anatomical parameters that can be measured in vivo, to reflect specific features of a pathological process. An example of a well-established biomarker for the development of coronary heart disease is the presence of high cholesterol levels. For the progression to dementia, promising biomarkers have been identified in multiple domains, such as genetics, neuroimaging and serum and cerebral spinal fluid measurements. Genetic studies have revealed a number of variations in genes associated with Alzheimer's disease. For example, individuals in families that carry the ApoE4 allele are shown to have increased risk of developing Alzheimer's disease. In the brains of patients with Lewy body dementia, the second cause of dementia after Alzheimer's disease, scientists have also found alternations in a gene that controls the expression of the enzyme butyrylcholinesterase. As such, the ApoE4 allele and the altered form of butyrylcholinesterase gene can be genetic biomarkers for the various subtypes of dementia. In the field of neuroimaging, functional imaging methods are also used to observe dysregulated neuronal networks, and in vivo imaging probes have been developed to visualize the build-up of beta-amyloid protein, which is responsible for plaque formation in Alzheimer's disease. Neuroimaging is thus an important tool for the assessment and monitoring of the pathological changes in the brain before dementia symptoms develop, and allows for the longitudinal assessment of the disease progression. With increased understanding of the underlying biochemical processes of dementia, measurements of cerebrospinal fluid markers can now be used to reflect the subtle biochemical dysregulations that occur in the brain as the disease progresses. The cerebrospinal fluid (CSF) is readily accessible and can be obtained with a minimally invasive spinal tap that is done outpatient. Thus far, the most promising CSF biomarkers are elevated levels of two proteins, beta-amyloid and phosphorylated tau, which are responsible for plaque and tangle formation in Alzheimer's disease. These two proteins have been shown to be elevated in patients 10 to 15 years before clinical symptoms appear, and its presence may indicate the possible progression of MCI to Alzheimer's disease.
Neurosteroids are a novel group of candidate CSF biomarkers that have been recently identified. Endogenously present in the central nervous system, neurosteroids are a large family of steroids that are synthesized de novo, and include pregnenolone, allopregnanolone and dehydroepiandrosterone. They play an important role in the normal functioning of the nervous system through the modulation of various neurotransmitter systems, and also have neuroenhancing and neuroprotective properties. There is mounting evidence that neurosteroids may play a role in cognitive aging and the levels of some neurosteroids are dysregulated in diseased states. In a post-mortem study done on Alzheimer's disease patients, levels of allopregnanolone, and the sulphated forms of pregnenolone and dehydroepiandrosterone were found to be significantly lower in diseased than in healthy control brains (Marx et al., 2006). Additionally, altered levels of neurosteroids were observed in regions of the brain where an accumulation of beta-amyloid and phosphorylated tau proteins occurred (Weill-Engerer et al., 2002). In animal studies, aged rats had significantly lowered levels of pregnenolone sulfate compared to their young counterparts, which was correlated with poor cognitive performance (Vallée et al., 1997). Furthermore, mice that were genetically engineered to show Alzheimer's disease pathogenesis had poor performance in cognitive tests, and this was accompanied by decreased levels of neurosteroids.
More importantly, the appeal of neurosteroids lies in the fact that, apart from being a possible biomarker that can reflect an increased risk of progressing to dementia, it also has therapeutic potential. Researchers have found that neurosteroids can enhance cognitive performances in rodent models of aging. The mechanisms in which neurosteroids exert their cognitive enhancement effects vary, as they modulate both excitatory and inhibitory signaling pathways in the brain. Furthermore, neurosteroids have been found to improve cognition through the regeneration of neural cells. In both aged mice and mice modelling Alzheimer's disease, allopregnanolone not only rescued impaired learning and memory functions, it also induced the generation and survival of new neurons in the hippocampus, an area of the brain involved in memory formation (Wang et al., 2010). With respect to Alzheimer's disease, allopregnanolone has been found to directly target disease pathology by preventing the formation of beta-amyloid plaques, through a complex interplay between transcription factors (Brinton, 2013). Although the results from neurosteroid research are promising, neurosteroids, as with most intervening therapies, can only be effective within a window of therapeutic efficacy. This window of therapeutic efficacy is when neuronal loss and plaque formation are not extensive, and coincides with the pre-clinical stage.
Even though neurosteroids hold much unexplored potential, like any other therapeutic intervention, it is not a magic bullet that can cure dementia. This is because dementia is a disease with complex etiologies, and patients may have differential responses to therapies. It is therefore imperative to generate a biomarker-defined risk profile to more accurately identify individuals with MCI who will progress to dementia. This risk-profile will be based on a combination of clinical features, cognitive tests, genetic profiling, serum or cerebral spinal fluid biomarkers and neuroimaging. Currently, additional work needs to be done to discover more biomarkers that are reliable and robust. A comprehensive biomarker-defined risk profile will reduce false positive diagnoses, and allow clinicians to stratify patients into biomarker-defined subgroups. Treatments can then be administered in a more targeted and individualized manner, that is in accordance with the domains of dysfunctions the patient has. With continued research into biomarkers and intervening therapies like neurosteroids, there is hope that dementia can be tackled and managed like other chronic diseases, such as coronary heart disease, where patients can live without compromising their quality of life.
About the Authors
Sze Ying is currently a research assistant in the Laboratory of Molecular Neuroscience at Duke-NUS. Sze Ying obtained her Bachelor's degree in Life Sciences from National University of Singapore in 2012, after completing her Honours Project on gut immunity at the Singapore Immunology Network (A*STAR). Upon graduation, she joined Duke-NUS and is currently taking on projects primarily related to mouse models of psychiatric diseases such as depression and schizophrenia, and is involved in various aspects of mouse behavioural testing at the Behavioural Phenotyping Core Facility.
Peiyan Wong is a Senior Research Fellow in the Laboratory of Molecular Neuroscience and a Research Scientist in the Behavioral Phenotyping Core Facility at Duke-NUS. She is currently working towards elucidating the underlying neurobiology of neuropsychiatric disorders, with the hopes of contributing to the development of better therapeutic agents. Peiyan graduated from Imperial College, UK in 2004, with a B.Sc. (Hons) in Biochemistry. She went on to obtain her Ph.D. in Psychology (Neuroscience) in 2009, from Vanderbilt University, where she trained in systems neuroscience and comparative neuroanatomy with Professor Jon H. Kaas. She joined A/Professor Xiaodong Zhang's laboratory at Duke-NUS in the same year to work on mouse models of neuropsychiatric disorders. She has also received training in running mouse behavioral paradigms as a postdoctoral fellow with A/Professor William Wetsel at the Mouse Behavior and Neuroendocrine Core Facility at Duke University from 2009 to 2011. As of 2011, Peiyan has been in charge of running the Behavioral Phenotyping Core Facility at Duke-NUS that she had set up with Assistant Professor Xiaodong Zhang. Aside from her scientific pursuits, she is also a course coordinator for a pre-medical freshman seminar module at NUS and NTU.
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