Current advances in systems and integrative biology

Systems biology has gained a tremendous amount of interest in the last few years. This is partly due to the realization that traditional approaches focusing only on a few molecules at a time cannot describe the impact of aberrant or modulated molecular environments across a whole system. Furthermore, a hypothesis-driven study aims to prove or disprove its postulations, whereas a hypothesis-free systems approach can yield an unbiased and novel testable hypothesis as an end-result. This latter approach foregoes assumptions which predict how a biological system should react to an altered microenvironment within a cellular context, across a tissue or impacting on distant organs. Additionally, re-use of existing data by systematic data mining and re-stratification, one of the cornerstones of integrative systems biology, is also gaining attention. While tremendous efforts using a systems methodology have already yielded excellent results, it is apparent that a lack of suitable analytic tools and purpose-built databases poses a major bottleneck in applying a systematic workflow. This review addresses the current approaches used in systems analysis and obstacles often encountered in large-scale data analysis and integration which tend to go unnoticed, but have a direct impact on the final outcome of a systems approach. Its wide applicability, ranging from basic research, disease descriptors, pharmacological studies, to personalized medicine, makes this emerging approach well suited to address biological and medical questions where conventional methods are not ideal

Best Practices for a State Alzheimer\u27s Disease Registry: Lessons from Georgia

In May 2014, the Georgia General Assembly enacted legislation establishing the Alzheimer’s Disease Registry (“Registry”) in order to generate new data for research and policy planning. The Task Force bill followed similar federal legislation. This state action has not only drawn tremendous attention to the continued prevalence of Alzheimer’s disease among the population of Georgia but also raised a series of questions regarding the practicability, legality, and effectiveness of the Registry. The lessons learned in Georgia, as Registry implementation moves forward, will provide guidance for other states interested in collecting similar data. In Part I of this article we describe the legislative history and operation of the Registry. In Part II we compare the two other population-based Alzheimer’s disease registries in the United States. In Part III we identify legal and ethical problems that may arise as the Registry becomes fully operational. In Part IV we identify specific concerns regarding the data collection and other procedural rules of the Registry. Finally in Part V, we articulate best practices for the Registry, considering both the unique circumstances of Georgia as well as generalizable concerns for other states

Diagnostic and economic evaluation of new biomarkers for Alzheimer's disease: the research protocol of a prospective cohort study

Doc number: 72 Abstract Background: New research criteria for the diagnosis of Alzheimer's disease (AD) have recently been developed to enable an early diagnosis of AD pathophysiology by relying on emerging biomarkers. To enable efficient allocation of health care resources, evidence is needed to support decision makers on the adoption of emerging biomarkers in clinical practice. The research goals are to 1) assess the diagnostic test accuracy of current clinical diagnostic work-up and emerging biomarkers in MRI, PET and CSF, 2) perform a cost-consequence analysis and 3) assess long-term cost-effectiveness by an economic model. Methods/design: In a cohort design 241 consecutive patients suspected of having a primary neurodegenerative disease are approached in four academic memory clinics and followed for two years. Clinical data and data on quality of life, costs and emerging biomarkers are gathered. Diagnostic test accuracy is determined by relating the clinical practice and new research criteria diagnoses to a reference diagnosis. The clinical practice diagnosis at baseline is reflected by a consensus procedure among experts using clinical information only (no biomarkers). The diagnosis based on the new research criteria is reflected by decision rules that combine clinical and biomarker information. The reference diagnosis is determined by a consensus procedure among experts based on clinical information on the course of symptoms over a two-year time period. A decision analytic model is built combining available evidence from different resources among which (accuracy) results from the study, literature and expert opinion to assess long-term cost-effectiveness of the emerging biomarkers. Discussion: Several other multi-centre trials study the relative value of new biomarkers for early evaluation of AD and related disorders. The uniqueness of this study is the assessment of resource utilization and quality of life to enable an economic evaluation. The study results are generalizable to a population of patients who are referred to a memory clinic due to their memory problems. Trial registration: NCT0145089

The Relationship Between the Classification of Dementia and Social Policy and Consequent Delivery of Services

The American population is getting older, and with the aging of the population the prevalence of chronic illnesses will increase. Current social policies that are intended to assist elderly persons and their families in case of illness are no longer sufficient to meet that need, and will decline further as the number of older persons increases. This is especially true for patients who have developed dementia, including Alzheimer\u27s disease, because dementias are still considered that peculiar disease of the cerebral cortex described by Alois Alzheimer in 1907 that seems not to fit any current classification. This study was designed to explore how the classification of dementia has influenced the social policies that govern a variety of institutions and systems, and the ultimate outcome for the provision of care for dementia patients and their care givers. Its purpose is to describe the current reality faced by dementia patients and their families. The focus of the study was an exploration of written policies, rules, and regulations that govern existing systems, and how such written rules affect the patients based on the classification of their disorder. After an exploration of written material and description of the resulting services, interviews were conducted to complement the previously mentioned material with the experiences of those who are charged with the delivery of care based on such rules. The findings from this study lend support to the following conclusions: l) the classification of dementias as mental illness can lead to involuntary psychiatric hospitalization or reduced reimbursement if treated on an outpatient basis; 2) the classification as deterioration with aging that requires support only results in lack of formal support outside of institutionalization and almost no reimbursement by Medicare or Medicaid for treatment and care in home setting; 3) the seldom used classification as a physical illness allows for most but still insufficient support. All classifications frequently lead to the impoverishment of the patient which in turn often leads to institutionalization. It is concluded from this study that the classification and the social policies based on such classification have become dysfunctional for the original population of older and ill persons and their families, but have become functional for new industries, professions, and bureaucracies. Further studies should investigate how the policies can again become functional for the intended population, and whether re-evaluation of the classification for dementia can be a first step in that direction

Validity of GrayMatters: A Self-Administered Computerized Assessment of Alzheimer\u27s Disease

The need for early detection of Alzheimer’s disease has been well established in previous literature. As technology has spread across all professional fields, computerized screening instruments for the early detection of Alzheimer’s disease have begun to draw attention. Research has noted that computerized screeners of dementia should be implemented in primary care physician offices, as the majority of elderly persons see their PCP more frequently than other health professionals. Specifically, self-administered computerized screening instruments that have acceptable psychometric sturdiness are needed for these offices. GrayMatters is a self-administered computerized screening measure that has previously been shown to have acceptable reliability and validity. The aim of this study was to reevaluate the concurrent validity of GrayMatters. Reevaluation was needed in order to compare GrayMatters to the Wechsler Memory Scale-IV, rather than the Wechsler Memory Scale-III as previous research had done, and due to population changes over time. In order to evaluate the concurrent validity of GrayMatters, archival data from 149 female participants and 102 male participants was gathered from the Texas Neuropsychology Clinic. Data sets included participants GrayMatters scores, Wechsler Memory Scale-IV scores, Mini-Mental Status Examination scores, Trailmaking A and B scores, Boston Verbal Fluency Test scores, as well as the participant’s age, gender, race, and level of education. GrayMatters scores were compared to scores from the WMS-IV, MMSE, Trailmaking A and B, and Boston Verbal Fluency Test in order to examine concurrent validity. Results indicate that GrayMatters scores were compatible with scores from all previously mentioned measures. These findings are important because they indicate that GrayMatters can be used as a screening instrument of Alzheimer’s disease that can be used to measure cognitive impairment and guide decisions regarding patient care

Screening for Alzheimer’s Disease in Vermont Primary Care Practice

Introduction: • Alzheimer’s Disease (AD) is a form of progressive dementia that affects 5.3 million Americans and is the sixth leading cause of death in the US. • Age is a major risk factor for disease , and 1 in 8 Americans over 65 can expect to develop AD. • The U.S. healthcare system spends $172 billion/year on patients with AD and dementia, more than half of the Medicare budget. This cost is estimated to increase to over$1 trillion by 2050. • In 2003, the US Preventative Services Task Force (USPSTF) concluded that screening older adults for dementia is ineffective due to insufficient means of preventing or slowing its progression. • In 2011, the National Institute on Aging published new diagnostic criteria for AD. • In accordance with these guidelines the Centers for Medicare and Medicaid Services released rules for the new Annual Wellness Visit that include the detection of cognitive impairment. • Our goal was to identify the attitudes and practices of primary care physicians (PCPs) in Vermont (VT) related to screening for AD and dementia.https://scholarworks.uvm.edu/comphp_gallery/1063/thumbnail.jp

Data fusion of complementary information from parietal and occipital event related potentials for early diagnosis of Alzheimer\u27s disease

The number of the elderly population affected by Alzheimer\u27s disease is rapidly rising. The need to find an accurate, inexpensive, and non-intrusive procedure that can be made available to community healthcare providers for the early diagnosis of Alzheimer\u27s disease is becoming an increasingly urgent public health concern. Several recent studies have looked at analyzing electroencephalogram signals through the use of many signal processing techniques. While their methods show great promise, the final outcome of these studies has been largely inconclusive. The inherent difficulty of the problem may be the cause of this outcome, but most likely it is due to the inefficient use of the available information, as many of these studies have used only a single EEG source for the analysis. In this contribution, data from the event related potentials of 19 available electrodes of the EEG are analyzed. These signals are decomposed into different frequency bands using multiresolution wavelet analysis. Two data fusion approaches are then investigated: i.) concatenating features before presenting them to a classification algorithm with the expectation of creating a more informative feature space, and ii.) generating multiple classifiers each trained with a different combination of features obtained from various stimuli, electrode, and frequency bands. The classifiers are then combined through the weighted majority vote, product and sum rule combination schemes. The results indicate that a correct diagnosis performance of over 80% can be obtained by combining data primarily from parietal and occipital lobe electrodes. The performance significantly exceeds that reported from community clinic physicians, despite their access to the outcomes of longitudinal monitoring of the patients