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Background: The characterizing symptom of Alzheimer disease (AD) is cognitive deterioration. While much recent work has focused on defining AD as a biological construct, most patients are still diagnosed, staged, and treated based on their cognitive symptoms. But the cognitive capability of a patient at any time throughout this deterioration reflects not only the disease state, but also the effect of the cognitive decline on the patient's pre-disease cognitive capability. Patients with high pre-disease cognitive capabilities tend to score better on cognitive tests that are sensitive early in disease relative to patients with low pre-disease cognitive capabilities at a similar disease stage. Thus, a single assessment with a cognitive test is often not adequate for determining the stage of an AD patient. Repeated evaluation of patients' cognition over time may improve the ability to stage AD patients, and such longitudinal assessments in combinations with biomarker assessments can help elucidate the time dynamics of biomarkers. In turn, this can potentially lead to identification of markers that are predictive of disease stage and future cognitive decline, possibly before any cognitive deficit is measurable. Methods and Findings: This article presents a class of statistical disease progression models and applies them to longitudinal cognitive scores. These non-linear mixed-effects disease progression models explicitly model disease stage, baseline cognition, and the patients' individual changes in cognitive ability as latent variables. Maximum-likelihood estimation in these models induces a data-driven criterion for separating disease progression and baseline cognition. Applied to data from the Alzheimer's Disease Neuroimaging Initiative, the model estimated a timeline of cognitive decline that spans ~15 years from the earliest subjective cognitive deficits to severe AD dementia. Subsequent analyses demonstrated how direct modeling of latent factors that modify the observed data patterns provides a scaffold for understanding disease progression, biomarkers, and treatment effects along the continuous time progression of disease. Conclusions: The presented framework enables direct interpretations of factors that modify cognitive decline. The results give new insights to the value of biomarkers for staging patients and suggest alternative explanations for previous findings related to accelerated cognitive decline among highly educated patients and patients on symptomatic treatments.
The Parkinson's Disease Progressive Neuroimaging Initiative (PDPNI) is a longitudinal observational clinical study. In PDPNI, the clinical and imaging data of patients diagnosed with Parkinsonian syndromes and Idiopathic rapid eye movement sleep behavior disorder (RBD) were longitudinally followed every two years, aiming to identify progression biomarkers of Parkinsonian syndromes through functional imaging modalities including FDG-PET, DAT-PET imaging, ASL MRI, and fMRI, as well as the treatment conditions, clinical symptoms, and clinical assessment results of patients. From February 2012 to March 2019, 224 subjects (including 48 healthy subjects and 176 patients with confirmed PDS) have been enrolled in PDPNI. The detailed clinical information and clinical assessment scores of all subjects were collected by neurologists from Huashan Hospital, Fudan University. All subjects enrolled in PDPNI were scanned with 18F-FDG PET, 11C-CFT PET, and MRI scan sequence. All data were collected in strict accordance with standardized data collection protocols.
Alzheimer's disease (AD) is prevalent throughout the world and is the leading cause of dementia in older individuals (aged ≥ 65 years). To gain a deeper understanding of the recent literature on the epidemiology of AD and its progression, we conducted a review of the PubMed-indexed literature (2014-2021) in North America, Europe, and Asia. The worldwide toll of AD is evidenced by rising prevalence, incidence, and mortality due to AD-estimates which are low because of underdiagnosis of AD. Mild cognitive impairment (MCI) due to AD can ultimately progress to AD dementia; estimates of AD dementia etiology among patients with MCI range from 40% to 75% depending on the populations studied and whether the MCI diagnosis was made clinically or in combination with biomarkers. The risk of AD dementia increases with progression from normal cognition with no amyloid-beta (Aβ) accumulation to early neurodegeneration and subsequently to MCI. For patients with Aβ accumulation and neurodegeneration, lifetime risk of AD dementia has been estimated to be 41.9% among women and 33.6% among men. Data on progression from preclinical AD to MCI are sparse, but an analysis of progression across the three preclinical National Institute on Aging and Alzheimer's Association (NIA-AA) stages suggests that NIA-AA stage 3 (subtle cognitive decline with AD biomarker positivity) could be useful in combination with other tools for treatment decision-making. Factors shown to increase risk include lower Mini-Mental State Examination (MMSE) score, higher Alzheimer's Disease Assessment Scale (ADAS-cog) score, positive APOE4 status, white matter hyperintensities volume, entorhinal cortex atrophy, cerebrospinal fluid (CSF) total tau, CSF neurogranin levels, dependency in instrumental activities of daily living (IADL), and being female. Results suggest that use of biomarkers alongside neurocognitive tests will become an important part of clinical practice as new disease-modifying therapies are introduced.
Improved treatment strategies for sarcoma rely on clarification of the molecular mediators of disease progression. Recently, we reported that the secreted glycoprotein NELL-1 modulates osteosarcoma (OS) disease progression in part via altering the sarcomatous extracellular matrix (ECM) and cell-ECM interactions. Of known NELL-1 interactor proteins, Contactin-associated protein-like 4 (Cntnap4) encodes a member of the neurexin superfamily of transmembrane molecules best known for its presynaptic functions in the central nervous system. Here, CRISPR/Cas9 gene deletion of CNTNAP4 reduced OS tumor growth, sarcoma-associated angiogenesis, and pulmonary metastases. CNTNAP4 knockout (KO) in OS tumor cells largely phenocopied the effects of NELL-1 KO, including reductions in sarcoma cell attachment, migration, and invasion. Further, CNTNAP4 KO cells were found to be unresponsive to the effects of NELL-1 treatment. Transcriptomic analysis combined with protein phospho-array demonstrated notable reductions in the MAPK/ERK signaling cascade with CNTNAP4 deletion, and the ERK1/2 agonist isoproterenol restored cell functions among CNTNAP4 KO tumor cells. Finally, human primary cells and tissues in combination with sequencing datasets confirmed the significance of CNTNAP4 signaling in human sarcomas. In summary, our findings demonstrate the biological importance of NELL-1/CNTNAP4 signaling axis in disease progression of human sarcomas and suggest that targeting the NELL-1/CNTNAP4 signaling pathway represents a strategy with potential therapeutic benefit in sarcoma patients.
Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β and misfolded tau proteins causing synaptic dysfunction and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. Increases in neural synchrony in the delta-theta band and decreases in the alpha and beta bands showed progressive changes along the EBM stages. Decreases in alpha and beta-band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.
Disease progression originates from the concept that an individual disease may go through different changes as it evolves, and such changes can cause new diseases. It is important to find a progression between diseases since knowing the prior-posterior relationship beforehand can prevent further complications or evolutions to other diseases. Furthermore, the series of progressions can be represented in the form of a chain, which enables us to readily infer successive influences from one disease to another after many passages through other diseases.
Moyamoya disease (MMD) is a progressive stenosis at the terminal portion of internal carotid artery and frequently occurs in East Asian countries. The etiology of MMD is still largely unknown. We performed a case-control design with whole-exome sequencing analysis on 31 sporadic MMD patients and 10 normal controls with matched age and gender. Patients clinically diagnosed with MMD was determined by digital subtraction angiography (DSA). Twelve predisposing mutations on seven genes associated with the sporadic MMD patients of Chinese ancestry (CCER2, HLA-DRB1, NSD-1, PDGFRB, PHACTR1, POGLUT1, and RNF213) were identified, of which eight single nucleotide variants (SNVs) were deleterious with CADD PHRED scaled score > 15. Sanger sequencing of nine cases with disease progression and 22 stable MMD cases validated that SNV (c.13185159G>T, p.V265L) on PHACTR1 was highly associated with the disease progression of MMD. Finally, we knocked down the expression of PHACTR1 by transfection with siRNA and measured the cell survival of human coronary artery endothelial cell (HCAEC) cells. PHACTR1 silence reduced the cell survival of HCAEC cells under serum starvation cultural condition. Together, these data identify novel predisposing mutations associated with MMD and reveal a requirement for PHACTR1 in mediating cell survival of endothelial cells.
To develop a disease progression model of Alzheimer's disease (AD) that shows cognitive decline from subjective cognitive impairments (SCI) to the end stage of AD dementia (ADD) and to investigate the effect of education level on the whole disease spectrum, we enrolled 565 patients who were followed up more than three times and had a clinical dementia rating sum of boxes (CDR-SB). Three cohorts, SCI (n = 85), amnestic mild cognitive impairment (AMCI, n = 240), and ADD (n = 240), were overlapped in two consecutive cohorts (SCI and AMCI, AMCI and ADD) to construct a model of disease course, and a model with multiple single-cohorts was estimated using a mixed-effect model. To examine the effect of education level on disease progression, the disease progression model was developed with data from lower (≤ 12) and higher (> 12) education groups. Disease progression takes 274.3 months (22.9 years) to advance from 0 to 18 points using the CDR-SB. Based on our predictive equation, it takes 116.5 months to progress from SCI to AMCI and 56.2 months to progress from AMCI to ADD. The rate of CDR-SB progression was different according to education level. The lower-education group showed faster CDR-SB progression from SCI to AMCI compared to the higher-education group, and this trend disappeared from AMCI to ADD. In the present study, we developed a disease progression model of AD spectrum from SCI to the end stage of ADD. Our disease modeling provides us with more understanding of the effect of education on cognitive trajectories.
Using surrogate biomarkers for disease progression as endpoints in neuroprotective clinical trials may help differentiate symptomatic effects of potential neuroprotective agents from true slowing of the neurodegenerative process. A systematic review was undertaken to determine what biomarkers for disease progression in Alzheimer's disease exist and how well they perform.
Studies regarding different viruses of the herpes family, such as cytomegalovirus (CMV), Epstein-Barr virus (EBV), or human herpes virus 6 (HHV-6) in Alzheimer's disease (AD) are scarce. DNA from peripheral blood leukocytes (PBL) and brain samples were analyzed for the presence of CMV, EBV, or HHV-6. All samples were negative for CMV. EBV positivity was 6% in AD brains, whereas 45% of PBL samples from AD patients and 31% from controls were positive for EBV (p = 0.05). HHV-6 showed a 23% positivity in PBL samples from AD and 4% from controls (p = 0.002). 17% of AD brains were HHV-6 positive. Within a group of elderly individuals, followed up for 5 years, EBV-positive or HHV-6-positive PBL increased in those who developed clinical AD. Virus serological positivity was also investigated, and IgG levels for CMV and EBV antigens were also increased in those subjects who developed AD during the follow-up. Our findings suggest that EBV and HHV-6 may be environmental risk factors for cognitive deterioration and progression to AD in elderly persons.
The anticipation of progression of Alzheimer's disease (AD) is crucial for evaluations of secondary prevention measures thought to modify the disease trajectory. However, it is difficult to forecast the natural progression of AD, notably because several functions decline at different ages and different rates in different patients. We evaluate here AD Course Map, a statistical model predicting the progression of neuropsychological assessments and imaging biomarkers for a patient from current medical and radiological data at early disease stages. We tested the method on more than 96,000 cases, with a pool of more than 4,600 patients from four continents. We measured the accuracy of the method for selecting participants displaying a progression of clinical endpoints during a hypothetical trial. We show that enriching the population with the predicted progressors decreases the required sample size by 38% to 50%, depending on trial duration, outcome, and targeted disease stage, from asymptomatic individuals at risk of AD to subjects with early and mild AD. We show that the method introduces no biases regarding sex or geographic locations and is robust to missing data. It performs best at the earliest stages of disease and is therefore highly suitable for use in prevention trials.
Dysregulated signaling cascades alter energy metabolism and promote cell proliferation and cyst expansion in polycystic kidney disease (PKD). Here we tested whether metabolic reprogramming towards aerobic glycolysis ("Warburg effect") plays a pathogenic role in male heterozygous Han:SPRD rats (Cy/+), a chronic progressive model of PKD. Using microarray analysis and qPCR, we found an upregulation of genes involved in glycolysis (Hk1, Hk2, Ldha) and a downregulation of genes involved in gluconeogenesis (G6pc, Lbp1) in cystic kidneys of Cy/+ rats compared with wild-type (+/+) rats. We then tested the effect of inhibiting glycolysis with 2-deoxyglucose (2DG) on renal functional loss and cyst progression in 5-week-old male Cy/+ rats. Treatment with 2DG (500 mg/kg/day) for 5 weeks resulted in significantly lower kidney weights (-27%) and 2-kidney/total-body-weight ratios (-20%) and decreased renal cyst index (-48%) compared with vehicle treatment. Cy/+ rats treated with 2DG also showed higher clearances of creatinine (1.98±0.67 vs 1.41±0.37 ml/min), BUN (0.69±0.26 vs 0.40±0.10 ml/min) and uric acid (0.38±0.20 vs 0.21±0.10 ml/min), and reduced albuminuria. Immunoblotting analysis of kidney tissues harvested from 2DG-treated Cy/+ rats showed increased phosphorylation of AMPK-α, a negative regulator of mTOR, and restoration of ERK signaling. Assessment of Ki-67 staining indicated that 2DG limits cyst progression through inhibition of epithelial cell proliferation. Taken together, our results show that targeting the glycolytic pathway may represent a promising therapeutic strategy to control cyst growth in PKD.
To characterize the course of Alzheimer's disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with AD continuum and investigated the effects of apolipoprotein E ε4 (APOE ε4) and sex on disease progression. To develop a model of progression from preclinical AD to AD dementia, we estimated Alzheimer's Disease Assessment Scale-Cognitive Subscale 13 (ADAS-cog 13) scores. When calculated as the median of ADAS-cog 13 scores for each cohort, the estimated time from preclinical AD to MCI due to AD was 7.8 years and preclinical AD to AD dementia was 15.2 years. ADAS-cog 13 scores deteriorated most rapidly in women APOE ε4 carriers and most slowly in men APOE ε4 non-carriers (p < 0.001). Our results suggest that disease progression modelling from preclinical AD to AD dementia may help clinicians to estimate where patients are in the disease course and provide information on variation in the disease course by sex and APOE ε4 status.
Multiple sclerosis (MS) is associated with chronic degeneration of the central nervous system and may cause permanent neurological problems and considerable disability. While its causes remain unclear, its extensive phenotypic variability makes its prognosis and treatment difficult. The identification of serum proteomic biomarkers of MS progression could further our understanding of the molecular mechanisms related to MS disease processes. In the current study, we used isobaric tagging for relative and absolute protein quantification (iTRAQ) methodology and advanced multivariate statistical analysis to quantify and identify potential serum biomarker proteins of MS progression. We identified a panel of 11 proteins and combined them into a classifier that best classified samples into the two disease groups. The estimated area under the receiver operating curve of this classifier was 0.88 (p-value=0.017), with 86% sensitivity and specificity. The identified proteins encompassed processes related to inflammation, opsonization, and complement activation. Results from this study are in particular valuable to design a targeted Multiple Reaction Monitoring mass spectrometry based (MRM-MS) assay to conduct an external validation in an independent and larger cohort of patients. Validated biomarkers may result in the development of a minimally-invasive tool to monitor MS progression and complement current clinical practices.
Commensal organisms with the potential to cause disease pose a challenge in developing treatment options. Using the example featured in this study, pneumococcal disease begins with Streptococcus pneumoniae colonization, followed by triggering events that prompt the release of a virulent subpopulation of bacteria. Current vaccines focus on colonization prevention, which poses unintended consequences of serotype niche replacement. In this study, noncovalent colocalization of two classes of complementary antigens, one to prevent the colonization of the most aggressive S. pneumoniae serotypes and another to restrict virulence transition, provides complete vaccine effectiveness in animal subjects and the most comprehensive coverage of disease reported to date. As a result, the proposed vaccine formulation offers universal pneumococcal disease prevention with the prospect of effectively managing a disease that afflicts tens to hundreds of millions globally. The approach more generally puts forth a balanced prophylactic treatment strategy in response to complex commensal-host dynamics.
Alzheimer's disease (AD) is characterized by the progressive alterations seen in brain images which give rise to the onset of various sets of symptoms. The variability in the dynamics of changes in both brain images and cognitive impairments remains poorly understood. This paper introduces AD Course Map a spatiotemporal atlas of Alzheimer's disease progression. It summarizes the variability in the progression of a series of neuropsychological assessments, the propagation of hypometabolism and cortical thinning across brain regions and the deformation of the shape of the hippocampus. The analysis of these variations highlights strong genetic determinants for the progression, like possible compensatory mechanisms at play during disease progression. AD Course Map also predicts the patient's cognitive decline with a better accuracy than the 56 methods benchmarked in the open challenge TADPOLE. Finally, AD Course Map is used to simulate cohorts of virtual patients developing Alzheimer's disease. AD Course Map offers therefore new tools for exploring the progression of AD and personalizing patients care.
Little is known about the genetic factors modulating the progression of Huntington's disease (HD). Dopamine levels are affected in HD and modulate executive functions, the main cognitive disorder of HD. We investigated whether the Val158Met polymorphism of the catechol-O-methyltransferase (COMT) gene, which influences dopamine (DA) degradation, affects clinical progression in HD. We carried out a prospective longitudinal multicenter study from 1994 to 2011, on 438 HD gene carriers at different stages of the disease (34 pre-manifest; 172 stage 1; 130 stage 2; 80 stage 3; 17 stage 4; and 5 stage 5), according to Total Functional Capacity (TFC) score. We used the Unified Huntington's Disease Rating Scale to evaluate motor, cognitive, behavioral and functional decline. We genotyped participants for COMT polymorphism (107 Met-homozygous, 114 Val-homozygous and 217 heterozygous). 367 controls of similar ancestry were also genotyped. We compared clinical progression, on each domain, between groups of COMT polymorphisms, using latent-class mixed models accounting for disease duration and number of CAG (cytosine adenine guanine) repeats. We show that HD gene carriers with fewer CAG repeats and with the Val allele in COMT polymorphism displayed slower cognitive decline. The rate of cognitive decline was greater for Met/Met homozygotes, which displayed a better maintenance of cognitive capacity in earlier stages of the disease, but had a worse performance than Val allele carriers later on. COMT polymorphism did not significantly impact functional and behavioral performance. Since COMT polymorphism influences progression in HD, it could be used for stratification in future clinical trials. Moreover, DA treatments based on the specific COMT polymorphism and adapted according to disease duration could potentially slow HD progression.
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