Are Small Hyperbolic Universes Observationally Detectable?

Using recent observational constraints on cosmological density parameters, together with recent mathematical results concerning small volume hyperbolic manifolds, we argue that, by employing pattern repetitions, the topology of nearly flat small hyperbolic universes can be observationally undetectable. This is important in view of the facts that quantum cosmology may favour hyperbolic universes with small volumes, and from the expectation coming from inflationary scenarios, that $\Omega_0$ is likely to be very close to one.Comment: 5 pages, 1 figure, LaTeX2e. A reference and two footnotes added. To appear in Class. Quantum Grav. 18 (2001) in the present for

Author Correction: Enhanced NF-κB signaling in type-2 dendritic cells at baseline predicts non-response to adalimumab in psoriasis.

Funder: Department of HealthBiologic therapies have transformed the management of psoriasis, but clinical outcome is variable leaving an unmet clinical need for predictive biomarkers of response. Here we perform in-depth immunomonitoring of blood immune cells of 67 patients with psoriasis, before and during therapy with the anti-TNF drug adalimumab, to identify immune mediators of clinical response and evaluate their predictive value. Enhanced NF-κBp65 phosphorylation, induced by TNF and LPS in type-2 dendritic cells (DC) before therapy, significantly correlates with lack of clinical response after 12 weeks of treatment. The heightened NF-κB activation is linked to increased DC maturation in vitro and frequency of IL-17+ T cells in the blood of non-responders before therapy. Moreover, lesional skin of non-responders contains higher numbers of dermal DC expressing the maturation marker CD83 and producing IL-23, and increased numbers of IL-17+ T cells. Finally, we identify and clinically validate LPS-induced NF-κBp65 phosphorylation before therapy as a predictive biomarker of non-response to adalimumab, with 100% sensitivity and 90.1% specificity in an independent cohort. Our study uncovers important molecular and cellular mediators underpinning adalimumab mechanisms of action in psoriasis and we propose a blood biomarker for predicting clinical outcome

Cross-disorder analysis of schizophrenia and 19 immune-mediated diseases identifies shared genetic risk.

Many immune diseases occur at different rates among people with schizophrenia compared to the general population. Here, we evaluated whether this phenomenon might be explained by shared genetic risk factors. We used data from large genome-wide association studies to compare the genetic architecture of schizophrenia to 19 immune diseases. First, we evaluated the association with schizophrenia of 581 variants previously reported to be associated with immune diseases at genome-wide significance. We identified five variants with potentially pleiotropic effects. While colocalization analyses were inconclusive, functional characterization of these variants provided the strongest evidence for a model in which genetic variation at rs1734907 modulates risk of schizophrenia and Crohn’s disease via altered methylation and expression of EPHB4—a gene whose protein product guides the migration of neuronal axons in the brain and the migration of lymphocytes towards infected cells in the immune system. Next, we investigated genome-wide sharing of common variants between schizophrenia and immune diseases using cross-trait LD score regression. Of the 11 immune diseases with available genome-wide summary statistics, we observed genetic correlation between six immune diseases and schizophrenia: inflammatory bowel disease (rg = 0.12 ± 0.03, P = 2.49 × 10−4), Crohn’s disease (rg = 0.097 ± 0.06, P = 3.27 × 10−3), ulcerative colitis (rg = 0.11 ± 0.04, P = 4.05 × 10–3), primary biliary cirrhosis (rg = 0.13 ± 0.05, P = 3.98 × 10−3), psoriasis (rg = 0.18 ± 0.07, P = 7.78 × 10–3) and systemic lupus erythematosus (rg = 0.13 ± 0.05, P = 3.76 × 10–3). With the exception of ulcerative colitis, the degree and direction of these genetic correlations were consistent with the expected phenotypic correlation based on epidemiological data. Our findings suggest shared genetic risk factors contribute to the epidemiological association of certain immune diseases and schizophrenia.This research was supported in part by a number of funding sources. This research uses resources provided by the Genetic Association Information Network (GAIN), obtained from the database of Genotypes and Phenotypes (dbGaP) found at http://www.ncbi.nlm.nih.gov/gap through dbGaP accession number phs000021.v3.p2; samples and associated phenotype data for this study were provided by the Molecular Genetics of Schizophrenia Collaboration (PI: Pablo V. Gejman, Evanston Northwestern Healthcare and Northwestern University, Evanston, IL, USA). Fulbright Canada, the Weston Foundation, and Brain Canada through the Canada Brain Research Fund—a public-private partnership established by the Government of Canada (to J.G.P.); the National Research Foundation of Korea (NRF) [grant 2016R1C1B2013126 to B.H.] and the Bio & Medical Technology Development Program of the NRF [grant 2017M3A9B6061852 to B.H.] funded by the Korean government, Ministry of Science and ICT; the Finnish Cultural Foundation and Academy of Finland [grant 309643 to H.M.O.]; the Spanish Ministry of Economy and Competitiveness and P12-BIO-1395 from Consejería de Innovación, Ciencia y Tecnología, Junta de Andalucía (Spain) [grant SAF2015-66761-P to J.M.]; the US National Institutes of Health (NIH) [grants R01AR045584, R01AR056292, X01HG007484 and P30AR057212 to Y.J., S.A.S. and R.S.]; the US NIH [grants N01AR02251 and R01AR05528 to M.D.M.]; the US NIH [grants 1R01AR063759, 1R01AR062886, 1UH2AR067677-01 and U19AI111224-01 to S.R.] and Doris Duke Charitable Foundation [grant 2013097 to S.R.]. Funding for the GAIN schizophrenia sample was provided by the US NIH [grants R01 MH67257, R01 MH59588, R01 MH59571, R01 MH59565, R01 MH59587, R01 MH60870, R01 MH59566, R01 MH59586, R01 MH61675, R01 MH60879, R01 MH81800, U01 MH46276, U01 MH46289, U01 MH46318, U01 MH79469 and U01 MH79470] and the genotyping of samples was provided through GAIN. The funding sources did not influence the study design, data analysis or writing of this manuscript

Defining the therapeutic range for adalimumab and predicting response in psoriasis: a multicenter prospective observational cohort study

Biologics have transformed management of inflammatory diseases. To optimize outcomes and reduce costs, dose adjustment informed by circulating drug levels has been proposed. We aimed to determine the real-world clinical utility of therapeutic drug monitoring in psoriasis. Within a multicenter (n=60) prospective observational cohort, 544 psoriasis patients were included who were on adalimumab monotherapy, with at least one serum sample and PASI (Psoriasis Area and Severity Index) score available within the first year. We present models giving individualized probabilities of response for any given drug level: a minimally effective drug level of 3.2 μg/ml discriminates responders (PASI75: 75% improvement in baseline PASI) from non-responders and gives an estimated PASI75 probability of 65% (95% CI 60-71%). At 7ug/ml, PASI75 probability is 81% (95% CI 76-86%); beyond 7ug/ml, the drug level/response curve plateaus. Crucially, drug levels are predictive of response 6 months later, whether sampled early or at steady state. We confirm serum drug level to be the most important factor determining treatment response, highlighting the need to take drug levels into account when searching for biomarkers of response. This real-world study with pragmatic drug level sampling provides evidence to support the proactive measurement of adalimumab levels in psoriasis to direct treatment strategy, and is relevant to other inflammatory diseases

Defining trajectories of response in patients with psoriasis treated with biologic therapies

From Wiley via Jisc Publications RouterHistory: accepted 2021-04-03, pub-electronic 2021-06-04Article version: VoRPublication status: PublishedFunder: Medical Research Council; Id: http://dx.doi.org/10.13039/501100000265; Grant(s): MR/K006665/1, MR/L011808/1, MR/N00583X/1Summary: Background: The effectiveness and cost‐effectiveness of biologic therapies for psoriasis are significantly compromised by variable treatment responses. Thus, more precise management of psoriasis is needed. Objectives: To identify subgroups of patients with psoriasis treated with biologic therapies, based on changes in their disease activity over time, that may better inform patient management. Methods: We applied latent class mixed modelling to identify trajectory‐based patient subgroups from longitudinal, routine clinical data on disease severity, as measured by the Psoriasis Area and Severity Index (PASI), from 3546 patients in the British Association of Dermatologists Biologics and Immunomodulators Register, as well as in an independent cohort of 2889 patients pooled across four clinical trials. Results: We discovered four discrete classes of global response trajectories, each characterized in terms of time to response, size of effect and relapse. Each class was associated with differing clinical characteristics, e.g. body mass index, baseline PASI and prevalence of different manifestations. The results were verified in a second cohort of clinical trial participants, where similar trajectories following the initiation of biologic therapy were identified. Further, we found differential associations of the genetic marker HLA‐C*06:02 between our registry‐identified trajectories. Conclusions: These subgroups, defined by change in disease over time, may be indicative of distinct endotypes driven by different biological mechanisms and may help inform the management of patients with psoriasis. Future work will aim to further delineate these mechanisms by extensively characterizing the subgroups with additional molecular and pharmacological data

Association of Serum Ustekinumab Levels With Clinical Response in Psoriasis

Importance: High-cost biologic therapies have transformed the management of immune-mediated inflammatory diseases. To optimize outcomes and reduce costs, dose adjustment informed by measurement of circulating drug levels has been shown to be effective in various settings. However, limited evidence exists for this approach with the interleukin 12 and interleukin 23 inhibitor ustekinumab. Objective: To evaluate clinical utility of therapeutic drug monitoring for ustekinumab in patients with psoriasis. Design, Setting, and Participants: A prospective observational cohort of 491 adults with psoriasis was recruited to the multicenter Biomarkers of Systemic Treatment Outcomes in Psoriasis study within the British Association of Dermatologists Biologic and Immunomodulators Register from June 2009 to December 2017; samples from some patients were taken between 2009 and 2011 as part of a pilot study with the same inclusion criteria. Exposure: Serum ustekinumab level measured at any point during the dosing cycle using an enzyme-linked immunosorbent assay. Main Outcomes and Measures@ Disease activity measured using the Psoriasis Area and Severity Index (PASI) score. Treatment response outcomes were PASI75 (75% reduction in PASI score from baseline [primary outcome]), PASI90 (90% reduction of PASI score from baseline), and absolute PASI score of 1.5 or less. Results: A total of 491 patients (171 women and 320 men; mean [SD] age, 45.7 [12.8] years) had 1 or more serum samples (total, 853 samples obtained 0-56 weeks from start of treatment) and 1 or more PASI scores within the first year of treatment. Antidrug antibodies were detected in only 17 of 490 patients (3.5%). Early measured drug levels (1-12 weeks after starting treatment) were associated with PASI75 response 6 months after starting treatment (odds ratio, 1.38; 95% CI, 1.11-1.71) when adjusted for baseline PASI score, age, and ustekinumab dose. However, this finding was not consistent across the other PASI outcomes (PASI90 and PASI score of ≤1.5). Conclusions and Relevance: This real-world study provides evidence that measurement of early serum ustekinumab levels could be useful to direct the treatment strategy for psoriasis. Adequate drug exposure early in the treatment cycle may be particularly important in determining clinical outcome

Genome-wide meta-analysis implicates mediators of hair follicle development and morphogenesis in risk for severe acne

Acne vulgaris is a highly heritable common, chronic inflammatory disease of the skin for which five genetic risk loci have so far been identified. Here, we perform a genome-wide association study of 3823 cases and 16,144 controls followed by meta-analysis with summary statistics from a previous study, with a total sample size of 26,722. We identify 20 independent association signals at 15 risk loci, 12 of which have not been previously implicated in the disease. Likely causal variants disrupt the coding region of WNT10A and a P63 transcription factor binding site in SEMA4B. Risk alleles at the 1q25 locus are associated with increased expression of LAMC2, in which biallelic loss-of-function mutations cause the blistering skin disease epidermolysis bullosa. These findings indicate that variation affecting the structure and maintenance of the skin, in particular the pilosebaceous unit, is a critical aspect of the genetic predisposition to severe acne