A Bayesian Model for the Prediction and Early Diagnosis of Alzheimer's Disease

Alzheimer's disease treatment is still an open problem. The diversity of symptoms, the alterations in common pathophysiology, the existence of asymptomatic cases, the different types of sporadic and familial Alzheimer's and their relevance with other types of dementia and comorbidities, have already created a myth-fear against the leading disease of the twenty first century. Many failed latest clinical trials and novel medications have revealed the early diagnosis as the most critical treatment solution, even though scientists tested the amyloid hypothesis and few related drugs. Unfortunately, latest studies have indicated that the disease begins at the very young ages thus making it difficult to determine the right time of proper treatment. By taking into consideration all these multivariate aspects and unreliable factors against an appropriate treatment, we focused our research on a non-classic statistical evaluation of the most known and accepted Alzheimer's biomarkers. Therefore, in this paper, the code and few experimental results of a computational Bayesian tool have being reported, dedicated to the correlation and assessment of several Alzheimer's biomarkers to export a probabilistic medical prognostic process. This new statistical software is executable in the Bayesian software Winbugs, based on the latest Alzheimer's classification and the formulation of the known relative probabilities of the various biomarkers, correlated with Alzheimer's progression, through a set of discrete distributions. A user-friendly web page has been implemented for the supporting of medical doctors and researchers, to upload Alzheimer's tests and receive statistics on the occurrence of Alzheimer's disease development or presence, due to abnormal testing in one or more biomarkers.

[1]  M. Culpin,et al.  PREVENTION OF ACCIDENTS , 1938, British medical journal.

[2]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[3]  W. K. Hastings,et al.  Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .

[4]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  C. Osmond,et al.  INFANT MORTALITY, CHILDHOOD NUTRITION, AND ISCHAEMIC HEART DISEASE IN ENGLAND AND WALES , 1986, The Lancet.

[6]  David J. Spiegelhalter,et al.  Local computations with probabilities on graphical structures and their application to expert systems , 1990 .

[7]  A. Harris,et al.  Carboplatin/cisplatin , 2012, Reactions Weekly.

[8]  D. Barker,et al.  WEIGHT IN INFANCY AND DEATH FROM ISCHAEMIC HEART DISEASE , 1989, The Lancet.

[9]  J. Dobbing,et al.  Fetal nutrition and cardiovascular disease in adult life , 1993, The Lancet.

[10]  P. Gluckman,et al.  Fetal nutrition and cardiovascular disease in adult life , 1993, The Lancet.

[11]  Andrew Thomas,et al.  WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility , 2000, Stat. Comput..

[12]  Y. Christen,et al.  Oxidative stress and Alzheimer disease. , 2000, The American journal of clinical nutrition.

[13]  J. Trojanowski,et al.  Increase of brain oxidative stress in mild cognitive impairment: a possible predictor of Alzheimer disease. , 2002, Archives of neurology.

[14]  J. C. Torre,et al.  Alzheimer Disease as a Vascular Disorder: Nosological Evidence , 2002 .

[15]  P. Modrego,et al.  Depression in patients with mild cognitive impairment increases the risk of developing dementia of Alzheimer type: a prospective cohort study. , 2004, Archives of neurology.

[16]  Peter Congdon,et al.  Bayesian Models for Categorical Data: Peter Congdon/Bayesian Models for Categorical Data , 2006 .

[17]  Nairanjana Dasgupta,et al.  Bayesian Models for Categorical Data , 2007, Technometrics.

[18]  P. Scheltens,et al.  Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria , 2007, The Lancet Neurology.

[19]  Simon Lovestone,et al.  p53 is upregulated in Alzheimer's disease and induces tau phosphorylation in HEK293a cells , 2007, Neuroscience Letters.

[20]  J. Stone.  What initiates the formation of senile plaques? The origin of Alzheimer-like dementias in capillary haemorrhages. , 2008, Medical hypotheses.

[21]  V. Lee,et al.  Mechanism of Ca2+ Disruption in Alzheimer's Disease by Presenilin Regulation of InsP3 Receptor Channel Gating , 2008, Neuron.

[22]  C. Robert,et al.  Bayesian Modeling Using WinBUGS , 2009 .

[23]  L. Farrer,et al.  Hypertension Increases the Probability of Alzheimer’s Disease and of Mild Cognitive Impairment in an Arab Community in Northern Israel , 2009, Neuroepidemiology.

[24]  C. Jack,et al.  MRI of hippocampal volume loss in early Alzheimer's disease in relation to ApoE genotype and biomarkers , 2008, Brain : a journal of neurology.

[25]  A. Fagan,et al.  Cerebrospinal fluid biomarkers and rate of cognitive decline in very mild dementia of the Alzheimer type. , 2009, Archives of neurology.

[26]  George Perry,et al.  Impaired Balance of Mitochondrial Fission and Fusion in Alzheimer's Disease , 2009, The Journal of Neuroscience.

[27]  Brani Vidakovic,et al.  Statistics for Bioengineering Sciences , 2011 .

[28]  K. Yaffe,et al.  The projected effect of risk factor reduction on Alzheimer's disease prevalence , 2011, The Lancet Neurology.

[29]  G. Mansoori,et al.  Nanotechnology for Alzheimer’s disease detection and treatment , 2011 .

[30]  B. Hyman,et al.  Neuropathological alterations in Alzheimer disease. , 2011, Cold Spring Harbor perspectives in medicine.

[31]  A. Bush,et al.  Role of amyloid-β–metal interactions in Alzheimer’s disease , 2011 .

[32]  Kristine Yaffe,et al.  The Projected impact of risk factor reduction on Alzheimer's disease prevalence , 2011, Alzheimer's & Dementia.

[33]  Nick C Fox,et al.  The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[34]  Nick C Fox,et al.  The Diagnosis of Mild Cognitive Impairment due to Alzheimer’s Disease: Recommendations from the National Institute on Aging-Alzheimer’s Association Workgroups on Diagnostic Guidelines for Alzheimer’s Disease , 2011 .

[35]  T. Bird.  Early-Onset Familial Alzheimer Disease , 2012 .

[36]  S. Correia,et al.  Alzheimer disease as a vascular disorder: Where do mitochondria fit? , 2012, Experimental Gerontology.

[37]  Søren Højsgaard,et al.  Graphical Independence Networks with the gRain Package for R , 2012 .

[38]  C. Phillips,et al.  Combining PET Images and Neuropsychological Test Data for Automatic Diagnosis of Alzheimer's Disease , 2014, PloS one.

[39]  Bianca Zadrozny,et al.  A Bayesian network decision model for supporting the diagnosis of dementia, Alzheimer's disease and mild cognitive impairment , 2014, Comput. Biol. Medicine.

[40]  Hajime Takano,et al.  Suppression of InsP3 Receptor-Mediated Ca2+ Signaling Alleviates Mutant Presenilin-Linked Familial Alzheimer's Disease Pathogenesis , 2014, The Journal of Neuroscience.

[41]  Karen M Rodrigue,et al.  Prevalence of amyloid PET positivity in dementia syndromes: a meta-analysis. , 2015, JAMA.

[42]  C. Jack,et al.  APOE effect on Alzheimer's disease biomarkers in older adults with significant memory concern , 2015, Alzheimer's & Dementia.

[43]  A. Fagan,et al.  Autosomal Dominant Alzheimer Disease: A Unique Resource to Study CSF Biomarker Changes in Preclinical AD , 2015, Front. Neurol..

[44]  R. Llinás,et al.  Thalamocortical Dysrhythmia: A Theoretical Update in Tinnitus , 2015, Front. Neurol..

[45]  Chengjie Xiong,et al.  Longitudinal Cerebrospinal Fluid Biomarker Changes in Preclinical Alzheimer Disease During Middle Age. , 2015, JAMA neurology.

[46]  C. Ritchie,et al.  Metal Ions in Alzheimer ’ s Disease Brain , 2015 .

[47]  Y. Kitagishi,et al.  BRCA1 and p53 Tumor Suppressor Molecules in Alzheimer’s Disease , 2015, International journal of molecular sciences.

[48]  A. Alexiou,et al.  An Overview on Global Trends in Nanotechnological Approaches for Alzheimer Therapy. , 2015, Current drug metabolism.

[49]  K. Blennow,et al.  Preclinical cerebrospinal fluid and volumetric magnetic resonance imaging biomarkers in Swedish familial Alzheimer's disease. , 2014, Journal of Alzheimer's disease : JAD.

[50]  Martin Rossor,et al.  Early behavioural changes in familial Alzheimer's disease in the Dominantly Inherited Alzheimer Network. , 2015, Brain : a journal of neurology.

[51]  Asad Ali Siyal,et al.  Applications of Nanotechnology in Diagnostics and Therapeutics of Alzheimer's and Parkinson's Disease. , 2015, Current drug metabolism.

[52]  Xi Chen,et al.  Serum MicroRNA Profiles Serve as Novel Biomarkers for the Diagnosis of Alzheimer's Disease , 2015, Disease markers.

[53]  Yong Xia,et al.  Automated identification of dementia using medical imaging: a survey from a pattern classification perspective , 2015, Brain Informatics.

[54]  D. Y. Lee,et al.  Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis. , 2015, JAMA.

[55]  M. Pérez,et al.  Mitochondrial Dysfunction Contributes to the Pathogenesis of Alzheimer's Disease , 2015, Oxidative medicine and cellular longevity.

[56]  Nathan D. Price,et al.  IL-10 Alters Immunoproteostasis in APP Mice, Increasing Plaque Burden and Worsening Cognitive Behavior , 2015, Neuron.

[57]  Kevin L. Boehme,et al.  Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study , 2015, PLoS medicine.

[58]  Michel Goedert,et al.  Alzheimer’s and Parkinson’s diseases: The prion concept in relation to assembled Aβ, tau, and α-synuclein , 2015, Science.

[59]  J. Laks,et al.  d-serine levels in Alzheimer's disease: implications for novel biomarker development , 2015, Translational Psychiatry.

[60]  G. Chételat,et al.  Cognitive and Brain Profiles Associated with Current Neuroimaging Biomarkers of Preclinical Alzheimer's Disease , 2015, The Journal of Neuroscience.

[61]  Kewei Chen,et al.  Brain Imaging and Blood Biomarker Abnormalities in Children With Autosomal Dominant Alzheimer Disease: A Cross-Sectional Study. , 2015, JAMA neurology.

[62]  P. Coupé,et al.  Structural imaging biomarkers of Alzheimer's disease: predicting disease progression , 2015, Neurobiology of Aging.

[63]  M. Frasier,et al.  Perspective: Data sharing for discovery , 2016, Nature.

[64]  Christine Van Broeckhoven,et al.  The genetic landscape of Alzheimer disease: clinical implications and perspectives , 2015, Genetics in Medicine.

[65]  A. Montpetit,et al.  Screening of dementia genes by whole-exome sequencing in early-onset Alzheimer disease: input and lessons , 2015, European Journal of Human Genetics.

[66]  A. Abbott,et al.  Failed Alzheimer’s trial does not kill leading theory of disease , 2016, Nature.

[67]  E. Mufson,et al.  Cerebrospinal Fluid proNGF: A Putative Biomarker for Early Alzheimer's Disease. , 2016, Current Alzheimer research.

[68]  P. Sachdev,et al.  Structural MRI Biomarkers of Mild Cognitive Impairment from Young Elders to Centenarians. , 2016, Current Alzheimer research.

[69]  Athanasios Alexiou,et al.  Biomarkers for Alzheimer’s Disease Diagnosis , 2017, Current Alzheimer research.