Challenges and Opportunities with Causal Discovery Algorithms: Application to Alzheimer’s Pathophysiology

© 2020, The Author(s). Causal Structure Discovery (CSD) is the problem of identifying causal relationships from large quantities of data through computational methods. With the limited ability of traditional association-based computational methods to discover causal relationships, CSD methodologies are gaining popularity. The goal of the study was to systematically examine whether (i) CSD methods can discover the known causal relationships from observational clinical data and (ii) to offer guidance to accurately discover known causal relationships. We used Alzheimer’s disease (AD), a complex progressive disease, as a model because the well-established evidence provides a “gold-standard” causal graph for evaluation. We evaluated two CSD methods, Fast Causal Inference (FCI) and Fast Greedy Equivalence Search (FGES) in their ability to discover this structure from data collected by the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We used structural equation models (which is not designed for CSD) as control. We applied these methods under three scenarios defined by increasing amounts of background knowledge provided to the methods. The methods were evaluated by comparing the resulting causal relationships with the “gold standard” graph that was constructed from literature. Dedicated CSD methods managed to discover graphs that nearly coincided with the gold standard. For best results, CSD algorithms should be used with longitudinal data providing as much prior knowledge as possible

No Effect of One-Year Treatment with Indomethacin on Alzheimer's Disease Progression: A Randomized Controlled Trial

Contains fulltext : 71117.pdf (publisher's version ) (Open Access)BACKGROUND: The objective of this study was to determine whether treatment with the nonselective nonsteroidal anti-inflammatory drug (NSAID) indomethacin slows cognitive decline in patients with Alzheimer's disease (AD). METHODOLOGY/PRINCIPAL FINDINGS: This double-blind, randomized, placebo-controlled trial was conducted between May 2000 and September 2005 in two hospitals in the Netherlands. 51 patients with mild to moderate AD were enrolled into the study. Patients received 100 mg indomethacin or placebo daily for 12 months. Additionally, all patients received omeprazole. The primary outcome measure was the change from baseline after one year of treatment on the cognitive subscale of the AD Assessment Scale (ADAS-cog). Secondary outcome measures included the Mini-Mental State Examination, the Clinician's Interview Based Impression of Change with caregiver input, the noncognitive subscale of the ADAS, the Neuropsychiatric Inventory, and the Interview for Deterioration in Daily life in Dementia. Considerable recruitment problems of participants were encountered, leading to an underpowered study. In the placebo group, 19 out of 25 patients completed the study, and 19 out of 26 patients in the indomethacin group. The deterioration on the ADAS-cog was less in the indomethacin group (7.8+/-7.6), than in the placebo group (9.3+/-10.0). This difference (1.5 points; CI -4.5-7.5) was not statistically significant, and neither were any of the secondary outcome measures. CONCLUSIONS/SIGNIFICANCE: The results of this study are inconclusive with respect to the hypothesis that indomethacin slows the progression of AD

Effects of traumatic brain injury and posttraumatic stress disorder on development of Alzheimer's disease in Vietnam Veterans using the Alzheimer's Disease Neuroimaging Initiative: Preliminary report

Introduction Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) have previously been reported to be associated with increased risk of Alzheimer's disease (AD). We are using biomarkers to study Vietnam Veterans with/without mild cognitive impairment with a history of at least one TBI and/or ongoing PTSD to determine whether these contribute to the development of AD. Methods Potential subjects identified by Veterans Administration records underwent an initial telephone screen. Consented subjects underwent clinical evaluation, lumbar puncture, structural magnetic resonance imaging, and amyloid positron emission tomography (PET) scans. Results We observed worse cognitive functioning in PTSD and TBI + PTSD groups, worse global cognitive functioning in the PTSD group, lower superior parietal volume in the TBI + PTSD group, and lower amyloid positivity in the PTSD group, but not the TBI group compared to controls without TBI/PTSD. Medial temporal lobe atrophy was not increased in the PTSD and/or TBI groups. Discussion Preliminary results do not indicate that TBI or PTSD increase the risk for AD measured by amyloid PET. Additional recruitment, longitudinal follow-up, and tau-PET scans will provide more information in the future

Genome-wide association study of Alzheimer's disease

In addition to apolipoprotein E (APOE), recent large genome-wide association studies (GWASs) have identified nine other genes/loci (CR1, BIN1, CLU, PICALM, MS4A4/MS4A6E, CD2AP, CD33, EPHA1 and ABCA7) for late-onset Alzheimer's disease (LOAD). However, the genetic effect attributable to known loci is about 50%, indicating that additional risk genes for LOAD remain to be identified. In this study, we have used a new GWAS data set from the University of Pittsburgh (1291 cases and 938 controls) to examine in detail the recently implicated nine new regions with Alzheimer's disease (AD) risk, and also performed a meta-analysis utilizing the top 1% GWAS single-nucleotide polymorphisms (SNPs) with P<0.01 along with four independent data sets (2727 cases and 3336 controls) for these SNPs in an effort to identify new AD loci. The new GWAS data were generated on the Illumina Omni1-Quad chip and imputed at ∼2.5 million markers. As expected, several markers in the APOE regions showed genome-wide significant associations in the Pittsburg sample. While we observed nominal significant associations (P<0.05) either within or adjacent to five genes (PICALM, BIN1, ABCA7, MS4A4/MS4A6E and EPHA1), significant signals were observed 69–180 kb outside of the remaining four genes (CD33, CLU, CD2AP and CR1). Meta-analysis on the top 1% SNPs revealed a suggestive novel association in the PPP1R3B gene (top SNP rs3848140 with P=3.05E–07). The association of this SNP with AD risk was consistent in all five samples with a meta-analysis odds ratio of 2.43. This is a potential candidate gene for AD as this is expressed in the brain and is involved in lipid metabolism. These findings need to be confirmed in additional samples

Predicting Amyloid Burden to Accelerate Recruitment of Secondary Prevention Clinical Trials

Background: Screening to identify individuals with elevated brain amyloid (Aβ+) for clinical trials in Preclinical Alzheimer’s Disease (PAD), such as the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s disease (A4) trial, is slow and costly. The Trial-Ready Cohort in Preclinical/Prodromal Alzheimer’s Disease (TRC-PAD) aims to accelerate and reduce costs of AD trial recruitment by maintaining a web-based registry of potential trial participants, and using predictive algorithms to assess their likelihood of suitability for PAD trials. Objectives: Here we describe how algorithms used to predict amyloid burden within TRC-PAD project were derived using screening data from the A4 trial. Design: We apply machine learning techniques to predict amyloid positivity. Demographic variables, APOE genotype, and measures of cognition and function are considered as predictors. Model data were derived from the A4 trial. Setting: TRC-PAD data are collected from web-based and in-person assessments and are used to predict the risk of elevated amyloid and assess eligibility for AD trials. Participants: Pre-randomization, cross-sectional data from the ongoing A4 trial are used to develop statistical models. Measurements: Models use a range of cognitive tests and subjective memory assessments, along with demographic variables. Amyloid positivity in A4 was confirmed using positron emission tomography (PET). Results: The A4 trial screened N=4,486 participants, of which N=1323 (29%) were classified as Aβ+ (SUVR ≥ 1.15). The Area under the Receiver Operating Characteristic curves for these models ranged from 0.60 (95% CI 0.56 to 0.64) for a web-based battery without APOE to 0.74 (95% CI 0.70 to 0.78) for an in-person battery. The number needed to screen to identify an Aβ+ individual is reduced from 3.39 in A4 to 2.62 in the remote setting without APOE, and 1.61 in the remote setting with APOE. Conclusions: Predictive algorithms in a web-based registry can improve the efficiency of screening in future secondary prevention trials. APOE status contributes most to predictive accuracy with cross-sectional data. Blood-based assays of amyloid will likely improve the prediction of amyloid PET positivity

The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement

INTRODUCTION: The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI-3, which began on August 1, 2016, is a 5-year renewal of the current ADNI-2 study. METHODS: ADNI-3 will follow current and additional subjects with normal cognition, mild cognitive impairment, and AD using innovative technologies such as tau imaging, magnetic resonance imaging sequences for connectivity analyses, and a highly automated immunoassay platform and mass spectroscopy approach for cerebrospinal fluid biomarker analysis. A Systems Biology/pathway approach will be used to identify genetic factors for subject selection/enrichment. Amyloid positron emission tomography scanning will be standardized using the Centiloid method. The Brain Health Registry will help recruit subjects and monitor subject cognition. RESULTS: Multimodal analyses will provide insight into AD pathophysiology and disease progression. DISCUSSION: ADNI-3 will aim to inform AD treatment trials and facilitate development of AD disease-modifying treatments

Impact of the Alzheimer's Disease Neuroimaging Initiative, 2004 to 2014

INTRODUCTION: The Alzheimer's Disease Neuroimaging Initiative (ADNI) was established in 2004 to facilitate the development of effective treatments for Alzheimer's disease (AD) by validating biomarkers for AD clinical trials. METHODS: We searched for ADNI publications using established methods. RESULTS: ADNI has (1) developed standardized biomarkers for use in clinical trial subject selection and as surrogate outcome measures; (2) standardized protocols for use across multiple centers; (3) initiated worldwide ADNI; (4) inspired initiatives investigating traumatic brain injury and post-traumatic stress disorder in military populations, and depression, respectively, as an AD risk factor; (5) acted as a data-sharing model; (6) generated data used in over 600 publications, leading to the identification of novel AD risk alleles, and an understanding of the relationship between biomarkers and AD progression; and (7) inspired other public-private partnerships developing biomarkers for Parkinson's disease and multiple sclerosis. DISCUSSION: ADNI has made myriad impacts in its first decade. A competitive renewal of the project in 2015 would see the use of newly developed tau imaging ligands, and the continued development of recruitment strategies and outcome measures for clinical trials

Clinical and biomarker changes in dominantly inherited Alzheimer\u27s disease

BACKGROUND: The order and magnitude of pathologic processes in Alzheimer\u27s disease are not well understood, partly because the disease develops over many years. Autosomal dominant Alzheimer\u27s disease has a predictable age at onset and provides an opportunity to determine the sequence and magnitude of pathologic changes that culminate in symptomatic disease. METHODS: In this prospective, longitudinal study, we analyzed data from 128 participants who underwent baseline clinical and cognitive assessments, brain imaging, and cerebrospinal fluid (CSF) and blood tests. We used the participant\u27s age at baseline assessment and the parent\u27s age at the onset of symptoms of Alzheimer\u27s disease to calculate the estimated years from expected symptom onset (age of the participant minus parent\u27s age at symptom onset). We conducted cross-sectional analyses of baseline data in relation to estimated years from expected symptom onset in order to determine the relative order and magnitude of pathophysiological changes. RESULTS: Concentrations of amyloid-beta (Aβ) 42 in the CSF appeared to decline 25 years before expected symptom onset. Aβ deposition, as measured by positron-emission tomography with the use of Pittsburgh compound B, was detected 15 years before expected symptom onset. Increased concentrations of tau protein in the CSF and an increase in brain atrophy were detected 15 years before expected symptom onset. Cerebral hypometabolism and impaired episodic memory were observed 10 years before expected symptom onset. Global cognitive impairment, as measured by the Mini-Mental State Examination and the Clinical Dementia Rating scale, was detected 5 years before expected symptom onset, and patients met diagnostic criteria for dementia at an average of 3 years after expected symptom onset. CONCLUSIONS: We found that autosomal dominant Alzheimer\u27s disease was associated with a series of pathophysiological changes over decades in CSF biochemical markers of Alzheimer\u27s disease, brain amyloid deposition, and brain metabolism as well as progressive cognitive impairment. Our results require confirmation with the use of longitudinal data and may not apply to patients with sporadic Alzheimer\u27s disease. (Funded by the National Institute on Aging and others; DIAN ClinicalTrials.gov number, NCT00869817.

Brain iron accumulation in unexplained fetal and infant death victims with smoker mothers-The possible involvement of maternal methemoglobinemia

<p>Abstract</p> <p>Background</p> <p>Iron is involved in important vital functions as an essential component of the oxygen-transporting heme mechanism. In this study we aimed to evaluate whether oxidative metabolites from maternal cigarette smoke could affect iron homeostasis in the brain of victims of sudden unexplained fetal and infant death, maybe through the induction of maternal hemoglobin damage, such as in case of methemoglobinemia.</p> <p>Methods</p> <p>Histochemical investigations by Prussian blue reaction were made on brain nonheme ferric iron deposits, gaining detailed data on their localization in the brainstem and cerebellum of victims of sudden death and controls. The Gless and Marsland's modification of Bielschowsky's was used to identify neuronal cell bodies and neurofilaments.</p> <p>Results</p> <p>Our approach highlighted accumulations of blue granulations, indicative of iron positive reactions, in the brainstem and cerebellum of 33% of victims of sudden death and in none of the control group. The modified Bielschowsky's method confirmed that the cells with iron accumulations were neuronal cells.</p> <p>Conclusions</p> <p>We propose that the free iron deposition in the brain of sudden fetal and infant death victims could be a catabolic product of maternal methemoglobinemia, a biomarker of oxidative stress likely due to nicotine absorption.</p