Predicting invasive breast cancer versus DCIS in different age groups.

BackgroundIncreasing focus on potentially unnecessary diagnosis and treatment of certain breast cancers prompted our investigation of whether clinical and mammographic features predictive of invasive breast cancer versus ductal carcinoma in situ (DCIS) differ by age.MethodsWe analyzed 1,475 malignant breast biopsies, 1,063 invasive and 412 DCIS, from 35,871 prospectively collected consecutive diagnostic mammograms interpreted at University of California, San Francisco between 1/6/1997 and 6/29/2007. We constructed three logistic regression models to predict the probability of invasive cancer versus DCIS for the following groups: women ≥ 65 (older group), women 50-64 (middle age group), and women < 50 (younger group). We identified significant predictors and measured the performance in all models using area under the receiver operating characteristic curve (AUC).ResultsThe models for older and the middle age groups performed significantly better than the model for younger group (AUC = 0.848 vs, 0.778; p = 0.049 and AUC = 0.851 vs, 0.778; p = 0.022, respectively). Palpability and principal mammographic finding were significant predictors in distinguishing invasive from DCIS in all age groups. Family history of breast cancer, mass shape and mass margins were significant positive predictors of invasive cancer in the older group whereas calcification distribution was a negative predictor of invasive cancer (i.e. predicted DCIS). In the middle age group--mass margins, and in the younger group--mass size were positive predictors of invasive cancer.ConclusionsClinical and mammographic finding features predict invasive breast cancer versus DCIS better in older women than younger women. Specific predictive variables differ based on age

The role of body fat in multiple sclerosis susceptibility and severity: A Mendelian randomisation study

Objective: The objective of this study was to explore the potential causal associations of body mass index, height, weight, fat mass, fat percentage and non-fat mass in the whole body, arms, legs and trunk (henceforth, ‘anthropometric measures’) with multiple sclerosis (MS) risk and severity. We also investigated the potential for reverse causation between anthropometric measures and MS risk. Methods: We conducted a two-sample univariable, multivariable and bidirectional Mendelian randomisation (MR) analysis. Results: A range of features linked to obesity (body mass index, weight, fat mass and fat percentage) were risk factors for MS development and worsened the disease’s severity in MS patients. Interestingly, we were able to demonstrate that height and non-fat mass have no association with MS risk or MS severity. We demonstrated that the association between anthropometric measures and MS is not subject to bias from reverse causation. Conclusions: Our findings provide evidence from human genetics that a range of features linked to obesity is an important contributor to MS development and MS severity, but height and non-fat mass are not. Importantly, these findings also identify a potentially modifiable factor that may reduce the accumulation of further disability and ameliorate MS severity

Co-operative binding of human fibronectin to Sfbl protein triggers streptococcal invasion into respiratory epithelial cells.

Streptococcal fibronectin binding protein I (SfbI) mediates adherence to and invasion of Streptococcus pyogenes into human epithelial cells. In this study, we analysed the binding activity of distinct domains of SfbI protein towards its ligand, the extracellular matrix component fibronectin, as well as the biological implication of the binding events during the infection process. By using purified recombinant SfbI derivatives as well as in vivo expressed SfbI domains on the surface of heterologous organism Streptococcus gordonii, we were able to dissociate the two major streptococcal target domains on the human fibronectin molecule. The SfbI repeat region exclusively bound to the 30 kDa N-terminal fragment of fibronectin, whereas the SfbI spacer region exclusively bound to the 45 kDa collagen-binding fragment of fibronectin. In the case of native surface-expressed SfbI protein, an induced fit mode of bacteria-fibronectin interaction was identified. We demonstrate that binding of the 30 kDa fibronectin fragment to the repeat region of SfbI protein co-operatively activates the adjacent SfbI spacer domain to bind the 45 kDa fibronectin fragment. The biological consequence arising from this novel mode of fibronectin targeting was analysed in eukaryotic cell invasion assays. The repeat region of SfbI protein is mediating adherence and constitutes a prerequisite for subsequent invasion, whereas the SfbI spacer domain efficiently triggers the invasion process of streptococci into the eukaryotic cell. Thus, we were able to dissect bacterial adhesion from invasion by manipulating one protein. SfbI protein therefore represents a highly evolved prokaryotic molecule that exploits the host factor fibronectin not only for extracellular targeting but also for its subsequent activation that leads to efficient cellular invasion

Pneumococcal phosphoglycerate kinase interacts with plasminogen and its tissue activator

18 pags, 8 figs, 1 tabStreptococcus pneumoniae is not only a commensal of the nasopharyngeal epithelium, but may also cause life-threatening diseases. Immune- electron microscopy studies revealed that the bacterial glycolytic enzyme, phosphoglycerate kinase (PGK), is localised on the pneumococcal surface of both capsulated and non-capsulated strains and colocalises with plasminogen. Since pneumococci may concentrate host plasminogen (PLG) together with its activators on the bacterial cell surface to facilitate the formation of plasmin, the involvement of PGK in this process was studied. Specific binding of human or murine PLG to strain-independent PGK was documented, and surface plasmon resonance analyses indicated a high affinity interaction with the kringle domains 1-4 of PLG. Crystal structure determination of pneumococcal PGK together with peptide array analysis revealed localisation of PLG-binding site in the N-terminal region and provided structural motifs for the interaction with PLG. Based on structural analysis data, a potential interaction of PGK with tissue plasminogen activator (tPA) was proposed and experimentally confirmed by binding studies, plasmin activity assays and thrombus degradation analyses. © Schattauer 2014.The research leading to these results has received funding from the European Community’s Seventh Framework Program under Grant Agreement no. HEALTH-F3–2009–223111. This work was also supported by grants from the Spanish Ministry of Economy and Competitiveness (BFU2011–25326) and Comunidad Autónoma de Madrid (CAM) S2010-BMD-2457 (BIPEDD2). J.K. is funded by a grant from Ministerio de Economía y Competitividad (BFU2011–24595). A.M. also acknowledges CAM for financial support to the Fundación Severo Ochoa through the AMAROUTO progra

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease

Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-β deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker

Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease‐informed machine‐learning

Introduction Developing cross‐validated multi‐biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge. Methods We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid‐PET and fluorodeoxyglucose positron‐emission tomography (FDG‐PET) to predict rates of cognitive decline. Prediction models were trained in autosomal‐dominant Alzheimer's disease (ADAD, n = 121) and subsequently cross‐validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model‐based risk enrichment was estimated. Results A model combining all biomarker modalities and established in ADAD predicted the 4‐year rate of decline in global cognition (R2 = 24%) and memory (R2 = 25%) in sporadic AD. Model‐based risk‐enrichment reduced the sample size required for detecting simulated intervention effects by 50%–75%. Discussion Our independently validated machine‐learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD

Crucial Role of the CB3-Region of Collagen IV in PARF-Induced Acute Rheumatic Fever

Acute rheumatic fever (ARF) and rheumatic heart disease are serious autoimmune sequelae to infections with Streptococcus pyogenes. Streptococcal M-proteins have been implicated in ARF pathogenesis. Their interaction with collagen type IV (CIV) is a triggering step that induces generation of collagen-specific auto-antibodies. Electron microscopy of the protein complex between M-protein type 3 (M3-protein) and CIV identified two prominent binding sites of which one is situated in the CB3-region of CIV. In a radioactive binding assay, M3-protein expressing S. pyogenes and S. gordonii bound the CB3-fragment. Detailed analysis of the interactions by surface plasmon resonance measurements and site directed mutagenesis revealed high affinity interactions with dissociation constants in the nanomolar range that depend on the recently described collagen binding motif of streptococcal M-proteins. Because of its role in the induction of disease-related collagen autoimmunity the motif is referred to as “peptide associated with rheumatic fever” (PARF). Both, sera of mice immunized with M3-protein as well as sera from patients with ARF contained anti-CB3 auto-antibodies, indicating their contribution to ARF pathogenesis. The identification of the CB3-region as a binding partner for PARF directs the further approaches to understand the unusual autoimmune pathogenesis of PARF-dependent ARF and forms a molecular basis for a diagnostic test that detects rheumatogenic streptococci

Resting-State Functional Connectivity Disruption as a Pathological Biomarker in Autosomal Dominant Alzheimer Disease

AIM: Identify a global resting state functional connectivity (gFC) signature in mutation carriers (MC) from the Dominantly Inherited Alzheimer Network (DIAN). Assess the gFC with regards to amyloid (A), tau (T), and neurodegeneration (N) biomarkers and estimated years to symptom onset (EYO). INTRODUCTION: Cross-sectional measures were assessed in MC (n=171) and mutation non-carriers (NC) (n=70) participants. A FC matrix that encompassed multiple resting state networks (RSNs) was computed for each participant. METHODS: A gFC was compiled as a single index indicating functional connectivity strength. Global FC signature was modeled as a non-linear function of EYO. gFC was linearly associated with other biomarkers used for assessing the AT(N) framework including: cerebrospinal fluid (CSF), positron emission tomography (PET) molecular biomarkers, and structural magnetic resonance imaging. RESULTS: The gFC was reduced in MC compared to NC participants. When MC participants were differentiated by clinical dementia rating (CDR), the gFC was significantly decreased in MC CDR > 0 (demented) compared to either MC CDR 0 (cognitively normal) or NC participants. The gFC varied non-linearly with EYO and initially decreased at EYO = -24 years, followed by a stable period followed by a further decline near EYO =0 years. Irrespective of EYO, a lower gFC associated with values of amyloid PET, CSF Aβ1-42, CSF p-tau, CSF t-tau, FDG and hippocampal volume. CONCLUSIONS: The gFC correlated with biomarkers used for defining the AT(N) framework. A biphasic change in the gFC suggested early changes associated with CSF amyloid and later changes associated with hippocampal volume

Comparing amyloid-β plaque burden with antemortem PiB PET in autosomal dominant and late-onset Alzheimer disease

Pittsburgh compound B (PiB) radiotracer for positron emission tomography (PET) imaging can bind to different types of amyloid-β plaques and blood vessels (cerebral amyloid angiopathy). However, the relative contributions of different plaque subtypes (diffuse versus cored/compact) to in vivo PiB PET signal on a region-by-region basis is incompletely understood. Of particular interest is whether the same staging schemes for summarizing amyloid-β burden are appropriate for both late-onset and autosomal dominant forms of Alzheimer disease (LOAD and ADAD). Here we compared antemortem PiB PET with follow-up postmortem estimation of amyloid-β burden using stereologic methods to estimate the relative area fraction of diffuse and cored/compact amyloid-β plaques across 16 brain regions in 15 individuals with ADAD and 14 individuals with LOAD. In ADAD, we found that PiB PET correlated with diffuse plaques in the frontal, parietal, temporal, and striatal regions commonly used to summarize amyloid-β burden in PiB PET, and correlated with both diffuse and cored/compact plaques in the occipital lobe and parahippocampal gyrus. In LOAD, we found that PiB PET correlated with both diffuse and cored/compact plaques in the anterior cingulate, frontal lobe (middle frontal gyrus), and parietal lobe, and showed additional correlations with diffuse plaque in the amygdala and occipital lobe, and with cored/compact plaque in the temporal lobe. Thus, commonly used PiB PET summary regions predominantly reflect diffuse plaque burden in ADAD and a mixture of diffuse and cored/compact plaque burden in LOAD. In direct comparisons of ADAD and LOAD, postmortem stereology identified much greater mean amyloid-β plaque burdens in ADAD versus LOAD across almost all brain regions studied. However, standard PiB PET did not recapitulate these stereologic findings, likely due to non-trivial amyloid-β plaque burdens in ADAD within the cerebellum and brainstem – commonly used reference regions in PiB PET. Our findings suggest that PiB PET summary regions correlate with amyloid-β plaque burden in both ADAD and LOAD; however, they might not be reliable in direct comparisons of regional amyloid-β plaque burden between the two forms of AD