Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS guideline for the diagnosis and management of patients with stable ischemic heart disease

The recommendations listed in this document are, whenever possible, evidence based. An extensive evidence review was conducted as the document was compiled through December 2008. Repeated literature searches were performed by the guideline development staff and writing committee members as new issues were considered. New clinical trials published in peer-reviewed journals and articles through December 2011 were also reviewed and incorporated when relevant. Furthermore, because of the extended development time period for this guideline, peer review comments indicated that the sections focused on imaging technologies required additional updating, which occurred during 2011. Therefore, the evidence review for the imaging sections includes published literature through December 2011

The impact of dementia, age and sex on category fluency: Greater deficits in women with Alzheimer's disease

Original article can be found at: http://www.sciencedirect.com/science/journal/00109452 Copyright Elsevier Masson DOI: 10.1016/j.cortex.2007.11.008A category specific effect in naming tasks has been reported in patients with Alzheimer's dementia. Nonetheless, naming tasks are frequently affected by methodological problems, e.g., ceiling effects for controls and “nuisance variables” that may confound results. Semantic fluency tasks could help to address some of these methodological difficulties, because they are not prone to producing ceiling effects and are less influenced by nuisance variables. One hundred and thirty-three participants (61 patients with probable AD; and 72 controls: 36 young and 36 elderly) were evaluated with semantic fluency tasks in 14 semantic categories. Category fluency was affected both by dementia and by age: while in nonliving-thing categories there were differences among the three groups, in living thing categories larger lexical categories produced bigger differences among groups. Sex differences in fluency emerged, but these were moderated both by age and by pathology. In particular, fluency was smaller in female than male Alzheimer patients for almost every subcategory.Peer reviewe

Group-constrained sparse fMRI connectivity modeling for mild cognitive impairment identification

Emergence of advanced network analysis techniques utilizing resting-state functional Magnetic Resonance Imaging (R-fMRI) has enabled a more comprehensive understanding of neurological disorders at a whole-brain level. However, inferring brain connectivity from R-fMRI is a challenging task, particularly when the ultimate goal is to achieve good control-patient classification performance, owing to perplexing noise effects, curse of dimensionality, and inter-subject variability. Incorporating sparsity into connectivity modeling may be a possible solution to partially remedy this problem since most biological networks are intrinsically sparse. Nevertheless, sparsity constraint, when applied at an individual level, will inevitably cause inter-subject variability and hence degrade classification performance. To this end, we formulate the R-fMRI time series of each region-of-interest (ROI) as a linear representation of time series of other ROIs to infer sparse connectivity networks that are topologically identical across individuals. This formulation allows simultaneous selection of a common set of ROIs across subjects so that their linear combination is best in estimating the time series of the considered ROI. Specifically, l(1)-norm is imposed on each subject to filter out spurious or insignificant connections to produce sparse networks. A group-constraint is hence imposed via multi-task learning using a l(2)-norm to encourage consistent non-zero connections across subjects. This group-constraint is crucial since the network topology is identical for all subjects while still preserving individual information via different connectivity values. We validated the proposed modeling in mild cognitive impairment (MCI) identification and promising results achieved demonstrate its superiority in disease characterization, particularly greater sensitivity to early stage brain pathologies. The inferred group-constrained sparse network is found to be biologically plausible and is highly associated with the disease-associated anatomical anomalies. Furthermore, our proposed approach achieved similar classification performance when finer atlas was used to parcellate the brain space

Brain imaging of neurovascular dysfunction in Alzheimer’s disease

Neurovascular dysfunction, including blood–brain barrier (BBB) breakdown and cerebral blood flow (CBF) dysregulation and reduction, are increasingly recognized to contribute to Alzheimer’s disease (AD). The spatial and temporal relationships between different pathophysiological events during preclinical stages of AD, including cerebrovascular dysfunction and pathology, amyloid and tau pathology, and brain structural and functional changes remain, however, still unclear. Recent advances in neuroimaging techniques, i.e., magnetic resonance imaging (MRI) and positron emission tomography (PET), offer new possibilities to understand how the human brain works in health and disease. This includes methods to detect subtle regional changes in the cerebrovascular system integrity. Here, we focus on the neurovascular imaging techniques to evaluate regional BBB permeability (dynamic contrast-enhanced MRI), regional CBF changes (arterial spin labeling- and functional-MRI), vascular pathology (structural MRI), and cerebral metabolism (PET) in the living human brain, and examine how they can inform about neurovascular dysfunction and vascular pathophysiology in dementia and AD. Altogether, these neuroimaging approaches will continue to elucidate the spatio-temporal progression of vascular and neurodegenerative processes in dementia and AD and how they relate to each other

Etrolizumab as induction and maintenance therapy for ulcerative colitis in patients previously treated with tumour necrosis factor inhibitors (HICKORY): a phase 3, randomised, controlled trial

Background: Etrolizumab is a gut-targeted, anti-β7 integrin, monoclonal antibody. In an earlier phase 2 induction study, etrolizumab significantly improved clinical remission compared with placebo in patients with moderately to severely active ulcerative colitis. We aimed to evaluate the efficacy and safety of etrolizumab in patients with moderately to severely active ulcerative colitis who had been previously treated with anti-tumour necrosis factor (TNF) agents. Methods: HICKORY was a multicentre, phase 3, double-blind, placebo-controlled study in adult (18–80 years) patients with moderately to severely active ulcerative colitis (Mayo Clinic total score [MCS] of 6–12 with an endoscopic subscore of ≥2, a rectal bleeding subscore of ≥1, and a stool frequency subscore of ≥1) previously treated with TNF inhibitors. Patients were recruited from 184 treatment centres across 24 countries in North America, South America, Europe, Asia, Oceania, and the Middle East. Patients needed to have an established diagnosis of ulcerative colitis for at least 3 months, corroborated by both clinical and endoscopic evidence, and evidence of disease extending at least 20 cm from the anal verge. In cohort 1, patients received open-label etrolizumab 105 mg every 4 weeks for a 14-week induction period. In cohort 2, patients were randomly assigned (4:1) to receive subcutaneous etrolizumab 105 mg or placebo every 4 weeks for the 14-week induction phase. Patients in either cohort achieving clinical response to etrolizumab induction were eligible for the maintenance phase, in which they were randomly assigned (1:1) to receive subcutaneous etrolizumab 105 mg or placebo every 4 weeks through to week 66. Randomisation was stratified by baseline concomitant treatment with corticosteroids, concomitant treatment with immunosuppressants (induction randomisation only), baseline disease activity, week 14 MCS remission status (maintenance randomisation only), and induction cohort (maintenance randomisation only). All patients and study site personnel were masked to treatment assignment. Primary endpoints were remission (Mayo Clinic total score [MCS] ≤2, with individual subscores of ≤1 and a rectal bleeding subscore of 0) at week 14, and remission at week 66 among patients with a clinical response (MCS with ≥3-point decrease and ≥30% reduction from baseline, plus ≥1 point decrease in rectal bleeding subscore or absolute rectal bleeding score of 0 or 1) at week 14. Efficacy was analysed using a modified intent-to-treat population. Safety analyses included all patients who received at least one dose of study drug during the induction phase. This study is registered at ClinicalTrials.gov, NCT02100696. Findings: HICKORY was conducted from May 21, 2014, to April 16, 2020, during which time 1081 patients were screened, and 609 deemed eligible for inclusion. 130 patients were included in cohort 1. In cohort 2,479 patients were randomly assigned to the induction phase (etrolizumab n=384, placebo n=95). 232 patients were randomly assigned to the maintenance phase (etrolizumab to etrolizumab n=117, etrolizumab to placebo n=115). At week 14, 71 (18·5%) of 384 patients in the etrolizumab group and six (6·3%) of 95 patients in the placebo group achieved the primary induction endpoint of remission (p=0·0033). No significant difference between etrolizumab and placebo was observed for the primary maintenance endpoint of remission at week 66 among patients with a clinical response at week 14 (27 [24·1%] of 112 vs 23 [20·2%] of 114; p=0·50). Four patients in the etrolizumab group reported treatment-related adverse events leading to treatment discontinuation. The proportion of patients reporting at least adverse event was similar between treatment groups for induction (etrolizumab 253 [66%] of 384; placebo 63 [66%] of 95) and maintenance (etrolizumab to etrolizumab 98 [88%] of 112; etrolizumab to placebo 97 [85%] of 114). The most common adverse event in both groups was ulcerative colitis flare. Most adverse events were mild or moderate. During induction, the most common serious adverse event was ulcerative colitis flare (etrolizumab ten [3%] of 384; placebo: two [2%] of 95). During maintenance, the most common serious adverse event in the etrolizumab to etrolizumab group was appendicitis (two [2%] of 112) and the most common serious adverse events in the etrolizumab to placebo group were ulcerative colitis flare (two [2%] of 114) and anaemia (two [2%] of 114). Interpretation: HICKORY demonstrated that a significantly higher proportion of patients with moderately to severely active ulcerative colitis who had been previously treated with anti-TNF agent were able to achieve remission at week 14 when treated with etrolizumab compared with placebo; however, there was no significant difference between groups in remission at week 66 among patients with a clinical response at week 14. Funding: F Hoffmann-La Roche