The Protein Model Portal

Structural Genomics has been successful in determining the structures of many unique proteins in a high throughput manner. Still, the number of known protein sequences is much larger than the number of experimentally solved protein structures. Homology (or comparative) modeling methods make use of experimental protein structures to build models for evolutionary related proteins. Thereby, experimental structure determination efforts and homology modeling complement each other in the exploration of the protein structure space. One of the challenges in using model information effectively has been to access all models available for a specific protein in heterogeneous formats at different sites using various incompatible accession code systems. Often, structure models for hundreds of proteins can be derived from a given experimentally determined structure, using a variety of established methods. This has been done by all of the PSI centers, and by various independent modeling groups. The goal of the Protein Model Portal (PMP) is to provide a single portal which gives access to the various models that can be leveraged from PSI targets and other experimental protein structures. A single interface allows all existing pre-computed models across these various sites to be queried simultaneously, and provides links to interactive services for template selection, target-template alignment, model building, and quality assessment. The current release of the portal consists of 7.6 million model structures provided by different partner resources (CSMP, JCSG, MCSG, NESG, NYSGXRC, JCMM, ModBase, SWISS-MODEL Repository). The PMP is available at http://www.proteinmodelportal.org and from the PSI Structural Genomics Knowledgebase

Genetic Variants in CETP Increase Risk of Intracerebral Hemorrhage

OBJECTIVE: In observational epidemiologic studies, higher plasma high-density lipoprotein cholesterol (HDL-C) has been associated with increased risk of intracerebral hemorrhage (ICH). DNA sequence variants that decrease cholesteryl ester transfer protein (CETP) gene activity increase plasma HDL-C; as such, medicines that inhibit CETP and raise HDL-C are in clinical development. Here, we test the hypothesis that CETP DNA sequence variants associated with higher HDL-C also increase risk for ICH.METHODS: We performed 2 candidate-gene analyses of CETP. First, we tested individual CETP variants in a discovery cohort of 1,149 ICH cases and 1,238 controls from 3 studies, followed by replication in 1,625 cases and 1,845 controls from 5 studies. Second, we constructed a genetic risk score comprised of 7 independent variants at the CETP locus and tested this score for association with HDL-C as well as ICH risk.RESULTS: Twelve variants within CETP demonstrated nominal association with ICH, with the strongest association at the rs173539 locus (odds ratio [OR] = 1.25, standard error [SE] = 0.06, p = 6.0 × 10(-4) ) with no heterogeneity across studies (I(2) = 0%). This association was replicated in patients of European ancestry (p = 0.03). A genetic score of CETP variants found to increase HDL-C by ∼2.85mg/dl in the Global Lipids Genetics Consortium was strongly associated with ICH risk (OR = 1.86, SE = 0.13, p = 1.39 × 10(-6) ).INTERPRETATION: Genetic variants in CETP associated with increased HDL-C raise the risk of ICH. Given ongoing therapeutic development in CETP inhibition and other HDL-raising strategies, further exploration of potential adverse cerebrovascular outcomes may be warranted. Ann Neurol 2016;80:730-740

The mammalian gene function resource: The International Knockout Mouse Consortium

In 2007, the International Knockout Mouse Consortium (IKMC) made the ambitious promise to generate mutations in virtually every protein-coding gene of the mouse genome in a concerted worldwide action. Now, 5 years later, the IKMC members have developed highthroughput gene trapping and, in particular, gene-targeting pipelines and generated more than 17,400 mutant murine embryonic stem (ES) cell clones and more than 1,700 mutant mouse strains, most of them conditional. A common IKMC web portal (www.knockoutmouse.org) has been established, allowing easy access to this unparalleled biological resource. The IKMC materials considerably enhance functional gene annotation of the mammalian genome and will have a major impact on future biomedical research

Genome-wide meta-analysis of cerebral white matter hyperintensities in patients with stroke.

OBJECTIVE: For 3,670 stroke patients from the United Kingdom, United States, Australia, Belgium, and Italy, we performed a genome-wide meta-analysis of white matter hyperintensity volumes (WMHV) on data imputed to the 1000 Genomes reference dataset to provide insights into disease mechanisms. METHODS: We first sought to identify genetic associations with white matter hyperintensities in a stroke population, and then examined whether genetic loci previously linked to WMHV in community populations are also associated in stroke patients. Having established that genetic associations are shared between the 2 populations, we performed a meta-analysis testing which associations with WMHV in stroke-free populations are associated overall when combined with stroke populations. RESULTS: There were no associations at genome-wide significance with WMHV in stroke patients. All previously reported genome-wide significant associations with WMHV in community populations shared direction of effect in stroke patients. In a meta-analysis of the genome-wide significant and suggestive loci (p < 5 × 10(-6)) from community populations (15 single nucleotide polymorphisms in total) and from stroke patients, 6 independent loci were associated with WMHV in both populations. Four of these are novel associations at the genome-wide level (rs72934505 [NBEAL1], p = 2.2 × 10(-8); rs941898 [EVL], p = 4.0 × 10(-8); rs962888 [C1QL1], p = 1.1 × 10(-8); rs9515201 [COL4A2], p = 6.9 × 10(-9)). CONCLUSIONS: Genetic associations with WMHV are shared in otherwise healthy individuals and patients with stroke, indicating common genetic susceptibility in cerebral small vessel disease.Funding for collection, genotyping, and analysis of stroke samples was provided by Wellcome Trust Case Control Consortium-2, a functional genomics grant from the Wellcome Trust (DNA-Lacunar), the Stroke Association (DNA-lacunar), the Intramural Research Program of National Institute of Ageing (Massachusetts General Hospital [MGH] and Ischemic Stroke Genetics Study [ISGS]), National Institute of Neurological Disorders and Stroke (Siblings With Ischemic Stroke Study, ISGS, and MGH), the American Heart Association/Bugher Foundation Centers for Stroke Prevention Research (MGH), Deane Institute for Integrative Study of Atrial Fibrillation and Stroke (MGH), National Health and Medical Research Council (Australian Stroke Genetics Collaborative), and Italian Ministry of Health (Milan). Additional support for sample collection came from the Medical Research Council, National Institute of Health Research Biomedical Research Centre and Acute Vascular Imaging Centre (Oxford), Wellcome Trust and Binks Trust (Edinburgh), and Vascular Dementia Research Foundation (Munich). MT is supported by a project grant from the Stroke Association (TSA 2013/01). HSM is supported by an NIHR Senior Investigator award. HSM and SB are supported by the NIHR Cambridge University Hospitals Comprehensive Biomedical Research Centre. VT and RL are supported by grants from FWO Flanders. PR holds NIHR and Wellcome Trust Senior Investigator Awards. PAS is supported by an MRC Fellowship. CML’s research is supported by the National Institute for Health Research Biomedical Research Centre (BRC) based at Guy's and St Thomas' NHS Foundation Trust and King's College London, and the BRC for Mental Health at South London and Maudsley NHS Foundation Trust and King’s College London. This is the final version of the article. It first appeared from Wolters Kluwer via http://dx.doi.org/10.1212/WNL.000000000000226

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec

Effect of switching from cigarette smoking to the use of the tobacco heating system on periodontitis treatment outcome: Periodontal parameter results from a multicenter Japanese study

ObjectivesWe conducted a 6-month randomized clinical study to evaluate the impact of exposure to the aerosol of the Tobacco Heating System (THS), a smoke-free alternative to cigarettes, on changes in periodontal parameters after scaling and root planing (SRP) for periodontitis in subjects who were either continuing to smoke cigarettes or had switched to THS.Material and methodsSmokers with generalized periodontitis were randomized to continue smoking cigarettes or switch to THS use. They underwent SRP for up to 8 weeks, with dental assessments conducted at baseline and at 3 and 6 months after the first treatment.ResultsAfter SRP treatment, all groups showed improvements in the mean full-mouth probing depth (PD), full-mouth clinical attachment level (CAL), gingival inflammation score, plaque control record (PCR), and bleeding on probing (BoP). There were no statistically significant intergroup differences. However, as compared to smokers, THS users showed a trend toward more favorable outcomes in BoP, PCR, and PD improvement at sites with higher initial PD (≥7 mm).ConclusionsOur results indicate that SRP improves the course of periodontitis similarly in cigarette smokers and THS users. The beneficial effects of this treatment might mask the favorable changes that may occur upon modifying one of the several periodontitis risk factors, such as cigarette smoking.Clinical trial registrationClinicalTrials.gov, identifer: NCT03364751

Abstract W P126: Accurate Outcome Predictions for Intracerebral Hemorrhage Patients Are More Likely Than Inaccurate Predictions to Be Influenced by Co-morbidities Not Included in Clinical Scales

Introduction: Clinical scales for intracerebral hemorrhage (ICH), such as the ICH and FUNC Scores, utilize a limited number of variables for outcome prediction. The variables that physicians incorporate into subjective predictions of ICH outcome and how they relate to predictive accuracy are unknown. Hypothesis: Accurate physician predictions of functional outcome for ICH patients are more likely than inaccurate predictions to incorporate decision-making factors outside of the variables comprising the ICH and FUNC Scores. Methods: For each consecutive adult patient admitted with primary ICH at 5 centers, one physician on the treatment team was surveyed for a prediction of modified Rankin Scale (mRS) at 3 months. All predictions were prospectively collected within 24 hours of admission. Physicians were also asked to indicate up to 10 factors influencing their prediction. Accuracy was defined as an exact prediction of the mRS obtained for each patient at 3 months. The frequency of recurring factors listed by physicians were calculated for both the accurate and inaccurate predictions and compared using Fisher’s exact test. Results: We collected 38 accurate and 86 inaccurate predictions for 124 ICH patients. There was no difference between groups with regards to the proportion of respondents listing age, ICH volume, or general clinical exam on admission as factors. However, 16 (42.1%) of the accurate surveys listed the patient’s general co-morbidities as a factor in prediction, compared to 20 (23.3%) of inaccurate surveys (p = 0.05). Listing of pre-morbid functional status as a factor also trended towards a higher percentage in the accurate survey group (n = 7, 18.4%, versus n = 6, 7.0%; p = 0.11). Of note, all surveys that cited the etiology of the bleed (n = 5), the initial blood pressure (n= 4), and the presence or absence of an extraventricular drain (n = 7) as influencing factors contained either overly optimistic or pessimistic predictions. Conclusions: Accurate predictions of ICH outcome are more likely than inaccurate predictions to factor in general patient co-morbidities, which are not included in ICH or FUNC Score calculation

Abstract 211: Subjective Judgments of Physicians and Nurses Are More Accurate Than Formal Clinical Scales in Predicting Functional Outcome After Intracerebral Hemorrhage

Introduction: Providing an accurate prognosis is a fundamental responsibility of care providers for patients with intracerebral hemorrhage (ICH). The ICH and FUNC Scores are common clinical scales designed to predict functional outcome and mortality for ICH patients. Hypothesis: The ICH Score and FUNC Score have superior accuracy, compared to the early clinical judgment of physicians and nurses, with regards to the prediction of the Modified Rankin Scale (mRS) achieved by ICH patients at 3 months. Methods: We conducted a prospective study at 5 centers. For each consecutive adult patient admitted with primary ICH, one physician and one nurse on the treatment team were asked for prediction of mRS at 3 months. All predictions were collected within 24 hours of admission. ICH and FUNC Scores on admission and blinded outcome at 3 months were obtained for each patient, in part using data collected for the ongoing Ethnic/Racial Variations with ICH (ERICH) project. Predictive ability was measured by Spearman’s rank correlation (r). Results: For a total of 100 patients, 100 physicians (75 attendings, 25 trainees) and 100 nurses gave predictions. In order of strength of association with actual 3-month mRS, correlations were attending physicians r = 0.81, nurses r = 0.72, and trainees r = 0.66. Although suggestive, none of these groups were statistically superior (p > 0.10). However, nurses (p = 0.015) and attending physicians (p = 0.002), but not trainees (p = 0.57), were superior in their predictive ability over ICH Score (r = 0.55). Similarly, nurses (p = 0.0003) and attending physicians (p < 0.0001), but not trainees (p = 0.27), were superior over FUNC Score (r = -0.46). This accuracy advantage remained when examining predictions for (1) only those patients alive at 3 months (n = 65), and (2) only those patients for whom providers indicated that they would not recommend comfort care within the first 24 hours (n = 82). Conclusions: The ICH Score and FUNC Score did not have superior accuracy, compared to subjective clinical judgment, with regards to prediction of 3-month ICH outcome

Factors Considered by Clinicians when Prognosticating Intracerebral Hemorrhage Outcomes

The early subjective clinical judgment of clinicians outperforms formal prognostic scales for accurate determination of outcome after intracerebral hemorrhage (ICH), with the judgment of physicians and nurses having equivalent accuracy. This study assessed specific decisional factors that physicians and nurses incorporate into early predictions of functional outcome. This prospective observational study enrolled 121 ICH patients at five US centers. Within 24 h of each patient's admission, one physician and one nurse on the clinical team were each surveyed to predict the patient's modified Rankin Scale (mRS) at 3 months and to list up to 10 subjective factors used in prognostication. Factors were coded and compared between (1) physician and nurse and (2) accurate and inaccurate surveys, with accuracy defined as an exact prediction of mRS. Aside from factors that are components of the ICH or FUNC scores, surveys reported pre-existing comorbidities (40.0%), other clinical or radiographic factors not in clinical scales (43.0%), and non-clinical/radiographic factors (21.9%) as important. Compared to physicians, nurses more frequently listed neurologic examination components (Glasgow Coma Scale motor, 27.3 vs. 5.8%, p < 0.0001; GCS verbal, 12.4 vs. 0.0%, p < 0.0001) and non-clinical/radiographic factors (31.4 vs. 12.4%, p = 0.0005). Physicians more frequently listed neuroimaging factors (ICH location, 33.9 vs. 7.4%, p < 0.0001; intraventricular hemorrhage, 13.2 vs. 2.5%, p = 0.003). There was no difference in listed factors between accurate versus inaccurate surveys. Clinicians frequently utilize factors outside of the components of clinical scales for prognostication, with physician and nurses focusing on different factors despite having similar accuracy