MRC Integrative Epidemiology Unit
MRC Integrative Epidemiology Unit
Araujo F.A.,University of Porto |
Severo M.,University of Porto |
Alegrete N.,Centro Hospitalar Sao Joao |
Alegrete N.,University of Porto |
And 3 more authors.
Physical Therapy | Year: 2017
Background. Sagittal postural patterns are associated with back pain in adolescents and adults. However, whether postural patterns are already observable during childhood is unknown. Such a finding would confirm childhood as a key period for posture differentiation and thus for chronic pain etiology. Objective. The aims of this study were to identify and describe postural patterns in girls and boys of school age. Design. This was a cross-sectional study. Methods. Eligible children were evaluated at age 7 in the population-based birth cohort Generation XXI in Portugal. Posture was assessed through right-side photographs during habitual standing with retroreflective markers placed on body landmarks. Postural patterns were defined from trunk, lumbar, and sway angles with model-based clusters, and associations with anthropometric measures were assessed by multinomial logistic regression. Results. Posture was evaluated in 1,147 girls and 1,266 boys. Three postural patterns were identified: sway (26.9%), flat (20.9%), and neutral to hyperlordotic (52.1%) in girls and sway to neutral (58.8%), flat (36.3%), and hyperlordotic (4.9%) in boys. In girls, a higher body mass index was associated with a sway pattern (versus a flat pattern: odds ratio=1.21; 95% CI=1.12, 1.29), whereas in boys, a higher body mass index was associated with a hyperlordotic pattern (versus a flat pattern: odds ratio=1.30; 95% CI=1.17, 1.44). Limitations. Photogrammetry as a noninvasive method for posture assessment may have introduced some postural misclassifications. Conclusions. Postural patterns in 7-year-old children were consistent with those previously found in adults, suggesting that childhood is a sensitive period for posture differentiation. Sagittal morphology differed between girls and boys, emphasizing sex-specific biomechanical loads during a habitual upright position even in prepubertal ages. © 2017 American Physical Therapy Association.
PubMed | Karolinska Institutet, University of Bristol, University of Turku, University Institute of Health Sciences and 49 more.
Type: Journal Article | Journal: Human molecular genetics | Year: 2015
Common genetic variants have been identified for adult height, but not much is known about the genetics of skeletal growth in early life. To identify common genetic variants that influence fetal skeletal growth, we meta-analyzed 22 genome-wide association studies (Stage 1; N = 28 459). We identified seven independent top single nucleotide polymorphisms (SNPs) (P < 1 10(-6)) for birth length, of which three were novel and four were in or near loci known to be associated with adult height (LCORL, PTCH1, GPR126 and HMGA2). The three novel SNPs were followed-up in nine replication studies (Stage 2; N = 11 995), with rs905938 in DC-STAMP domain containing 2 (DCST2) genome-wide significantly associated with birth length in a joint analysis (Stages 1 + 2; = 0.046, SE = 0.008, P = 2.46 10(-8), explained variance = 0.05%). Rs905938 was also associated with infant length (N = 28 228; P = 5.54 10(-4)) and adult height (N = 127 513; P = 1.45 10(-5)). DCST2 is a DC-STAMP-like protein family member and DC-STAMP is an osteoclast cell-fusion regulator. Polygenic scores based on 180 SNPs previously associated with human adult stature explained 0.13% of variance in birth length. The same SNPs explained 2.95% of the variance of infant length. Of the 180 known adult height loci, 11 were genome-wide significantly associated with infant length (SF3B4, LCORL, SPAG17, C6orf173, PTCH1, GDF5, ZNFX1, HHIP, ACAN, HLA locus and HMGA2). This study highlights that common variation in DCST2 influences variation in early growth and adult height.
PubMed | University of Ulsan, Sungkyunkwan University, Center for Cohort Studies, MRC Integrative Epidemiology Unit and Seoul National University
Type: | Journal: International journal of epidemiology | Year: 2017
We examined whether alcohol flushing could be used as an instrumental variable (IV) and investigated the effect of alcohol consumption on coronary calcification using alcohol flushing status as an IV.We analysed cross-sectional data from 24681 Korean adults (20696 men and 3985 women) who had been administered a questionnaire assessing alcohol consumption and alcohol flushing, as well as a coronary artery calcium (CAC) measurement. The associations of alcohol flushing status with potential confounders and alcohol consumption were examined. We employed two-stage predictor substitution methodology for the IV analysis.The prevalence of alcohol flushing did not differ depending on gender, education, household income, cigarette smoking or physical activity. Balanced levels of confounders were observed between alcohol flushers and non-flushers. Alcohol flushing was closely related to alcohol consumption and levels of liver enzymes. In men, a doubling in alcohol consumption was associated with increased odds of coronary calcification in both the IV analysis [odds ratio (OR) of CAC scores of 1 or over = 1.11; 95% confidence interval (CI) = 1.03-1.20) and the multivariable regression analysis (OR=1.04; 95% CI=1.01-1.07). For cardiovascular risk factors, the IV analysis showed a positive association between alcohol consumption and blood pressure and high-density lipoprotein-cholesterol.Alcohol flushing can be used as an IV in studies evaluating the health impact of alcohol consumption, especially in East Asian countries. Through such an analysis, we found that increased alcohol consumption was associated with an increased risk of subclinical coronary atherosclerosis.
News Article | February 15, 2017
Suzanne Gage, a scientist whose podcast, "Say Why To Drugs," has received over 264,000 listens, has been chosen by the American Association for the Advancement of Science (AAAS) to receive the 2016 Early Career Award for Public Engagement with Science. Gage recently completed her post-doctoral research in the MRC Integrative Epidemiology Unit at the University of Bristol, and is now a scientist at the University of Liverpool. She also founded "Sifting the Evidence," a blog on The Guardian's website in which she examines epidemiology, mental health and substance abuse. She is being honored by AAAS for "her evidence-based approach to public engagement activities and targeting audiences who may not be actively seeking science information." Gage is a "highly talented, enthusiastic and energetic young researcher who promises to be a real star of the future," wrote Marcus Munafò, a professor of biological psychology at the University of Bristol, where Gage was a post-doctoral research associate until December. Through her blog and podcast, Munafò wrote, "Suzi has worked tirelessly to provide information to the general public about the scientific evidence surrounding the effects of recreational drugs." Her podcast, which she was inspired to produce after appearing on rapper Scroobius Pip's podcast, discusses a different recreational drug in each episode. Gage aims to counter misinformation and myths surrounding various substances. Munafò noted that Pip's involvement in the podcast has helped Gage reach an audience of young adults who might not otherwise receive the information. Pip emphasized that the program is not meant to condone drug use. "This is not a pro-drugs podcast, this is not anti-drugs podcast," Pip explained, "this is pro-truth and anti-myth." The podcast has topped the Science and Medicine chart in the iTunes store and has received support on Twitter, including from Virgin Group founder Richard Branson. It also won the Skeptic Magazine 2016 Ockham Award for Best Podcast. Munafò wrote that the show has also been used by teachers to introduce their students to evidence-based thinking. Gage has also traveled across the United Kingdom, speaking at "Skeptics in the Pub," evening events hosted by local organizations to promote critical thinking. She has spoken at the Royal Institution of Great Britain and music festivals in the UK. She engaged with younger audiences in 2011 by participating in "I'm a Scientist, Get Me Out of Here," an online event where students meet and interact with scientists. The scientists compete with one other, answering questions about science and their research that are provided by students, who then vote for their favorite scientist. Gage won in the "Brain Zone" category and used the winnings to start her podcast. Gage's work in public engagement was recognized in 2012, when she won the UK Science Blog Prize, and in 2013, when she received the British Association for Psychopharmacology Public Communication Award. She has also written for The Economist, The Telegraph and The Lancet Psychiatry. Gage's recent scientific work in studying the relationship between health behaviors and mental health outcomes has included investigating causal associations from observational studies, with particular emphasis on substance use and mental health. She earned a Master of Science degree in cognitive neuropsychology from University College London in 2005 and a Ph.D. in translational epidemiology from the University of Bristol in 2014. Her research also earned her the European College of Neuropsychopharmacology Travel Award in 2012. More recently, she received the Society for Research in Nicotine and Tobacco's 2015 Basic Science Network Travel Award. The AAAS Early Career Award for Public Engagement with Science was established in 2010 to recognize "early-career scientists and engineers who demonstrate excellence in their contribution to public engagement with science activities." The recipient receives a monetary prize of $5,000, a commemorative plaque, complimentary registration to the AAAS Annual Meeting and reimbursement for reasonable travel and hotel expenses to attend the AAAS Annual Meeting to receive the prize. The award will be bestowed upon Gage during the 183rd AAAS Annual Meeting in Boston, Massachusetts, Feb. 16-20, 2017. The AAAS Awards Ceremony and Reception will be held at 6:30 p.m. on Friday, Feb. 17, in the Republic Ballroom of the Sheraton Boston Hotel. The American Association for the Advancement of Science (AAAS) is the world's largest general scientific society and publisher of the journal Science as well as Science Translational Medicine, Science Signaling, a digital, open-access journal, Science Advances, Science Immunology, and Science Robotics. AAAS was founded in 1848 and includes nearly 250 affiliated societies and academies of science, serving 10 million individuals. Science has the largest paid circulation of any peer-reviewed general science journal in the world. The non-profit AAAS is open to all and fulfills its mission to "advance science and serve society" through initiatives in science policy, international programs, science education, public engagement, and more. For the latest research news, log onto EurekAlert!, the premier science-news Web site, a service of AAAS. See http://www. . For more information on AAAS awards, see http://www. .
Varbo A.,Copenhagen University |
Benn M.,Copenhagen University |
Smith G.D.,MRC Integrative Epidemiology Unit |
Smith G.D.,University of Bristol |
And 4 more authors.
Circulation Research | Year: 2015
Rationale: Obesity leads to increased ischemic heart disease (IHD) risk, but the risk is thought to be mediated through intermediate variables and may not be caused by increased weight per se. Objective: To test the hypothesis that the increased IHD risk because of obesity is mediated through lipoproteins, blood pressure, glucose, and C-reactive protein. Methods and Results: Approximately 90 000 participants from Copenhagen were included in a Mendelian randomization design with mediation analyses. Associations were examined using conventional measurements of body mass index and intermediate variables and using genetic variants associated with these. During ≤22 years of follow-up 13 945 participants developed IHD. The increased IHD risk caused by obesity was partly mediated through elevated levels of nonfasting remnant cholesterol and low-density lipoprotein cholesterol, through elevated blood pressure, and possibly also through elevated nonfasting glucose levels; however, reduced high-density lipoprotein cholesterol and elevated C-reactive protein levels were not mediators in genetic analyses. The 3 intermediate variables that explained the highest excess risk of IHD from genetically determined obesity were low-density lipoprotein cholesterol with 8%, systolic blood pressure with 7%, and remnant cholesterol with 7% excess risk of IHD. Corresponding observational excess risks using conventional body mass index were 21%, 11%, and 20%, respectively. Conclusions: The increased IHD risk because of obesity was partly mediated through elevated levels of nonfasting remnant and low-density lipoprotein cholesterol and through elevated blood pressure. Our results suggest that there may be benefit to gain by reducing levels of these risk factors in obese individuals not able to achieve sustained weight loss. © 2014 American Heart Association, Inc.
PubMed | University of Bristol and MRC Integrative Epidemiology Unit
Type: Journal Article | Journal: International journal of epidemiology | Year: 2016
Risk-of-bias assessments are now a standard component of systematic reviews. At present, reviewers need to manually identify relevant parts of research articles for a set of methodological elements that affect the risk of bias, in order to make a risk-of-bias judgement for each of these elements. We investigate the use of text mining methods to automate risk-of-bias assessments in systematic reviews. We aim to identify relevant sentences within the text of included articles, to rank articles by risk of bias and to reduce the number of risk-of-bias assessments that the reviewers need to perform by hand.We use supervised machine learning to train two types of models, for each of the three risk-of-bias properties of sequence generation, allocation concealment and blinding. The first model predicts whether a sentence in a research article contains relevant information. The second model predicts a risk-of-bias value for each research article. We use logistic regression, where each independent variable is the frequency of a word in a sentence or article, respectively.We found that sentences can be successfully ranked by relevance with area under the receiver operating characteristic (ROC) curve (AUC)> 0.98. Articles can be ranked by risk of bias with AUC > 0.72. We estimate that more than 33% of articles can be assessed by just one reviewer, where two reviewers are normally required.We show that text mining can be used to assist risk-of-bias assessments.
PubMed | University of Queensland, University of Bristol and MRC Integrative Epidemiology Unit
Type: Journal Article | Journal: Human molecular genetics | Year: 2015
Previous studies have identified 63 single-nucleotide polymorphisms (SNPs) associated with bone mineral density (BMD) in adults. These SNPs are thought to reflect variants that influence bone maintenance and/or loss in adults. It is unclear whether they affect the rate of bone acquisition during adolescence. Bone measurements and genetic data were available on 6397 individuals from the Avon Longitudinal Study of Parents and Children at up to five follow-up clinics. Linear mixed effects models with smoothing splines were used for longitudinal modelling of BMD and its components bone mineral content (BMC) and bone area (BA), from 9 to 17 years. Genotype data from the 63 adult BMD associated SNPs were investigated individually and as a genetic risk score in the longitudinal model. Each additional BMD lowering allele of the genetic risk score was associated with lower BMD at age 13 [per allele effect size, 0.002 g/cm(2) (SE = 0.0001, P = 1.24 10(-38))] and decreased BMD acquisition from 9 to 17 years (P = 9.17 10(-7)). This association was driven by changes in BMC rather than BA. The genetic risk score explained 2% of the variation in BMD at 9 and 17 years, a third of that explained in adults (6%). Genetic variants that putatively affect bone maintenance and/or loss in adults appear to have a small influence on the rate of bone acquisition through adolescence.
PubMed | University of Bristol, University College London and MRC Integrative Epidemiology Unit
Type: Journal Article | Journal: International journal of epidemiology | Year: 2016
Many questions in life course epidemiology involve mediation and/or interaction because of the long latency period between exposures and outcomes. In this paper, we explore how mediation analysis (based on counterfactual theory and implemented using conventional regression approaches) links with a structured approach to selecting life course hypotheses. Using theory and simulated data, we show how the alternative life course hypotheses assessed in the structured life course approach correspond to different combinations of mediation and interaction parameters. For example, an early life critical period model corresponds to a direct effect of the early life exposure, but no indirect effect via the mediator and no interaction between the early life exposure and the mediator. We also compare these methods using an illustrative real-data example using data on parental occupational social class (early life exposure), own adult occupational social class (mediator) and physical capability (outcome).
News Article | December 19, 2016
The study from the University of Bristol comes on the back of public health warnings issued earlier this year by scientists who voiced concerns about the increased risk of psychosis for vulnerable people who use the drug. Those warnings followed evidence to suggest an increased use of particularly high potency strains of cannabis among young people. However, experts cautioned that the risks should not be overstated given the need for greater research into links between mental health and illicit drugs. This latest study from Bristol's School of Experimental Psychology sheds fresh light on the issue, while still cautioning that the results ought to be considered in the wider context of other contributing factors of mental health. While some evidence was found to support hypotheses that cannabis use is a contributory factor in increasing the risk of schizophrenia, the researchers were surprised to find stronger evidence that the opposite was also likely. This adds weight to the idea that the drug may be used as a form of self-medication. "The evidence suggested that schizophrenia risk predicts the likelihood of trying cannabis," said Dr Suzi Gage, Research Associate with the MRC Integrative Epidemiology Unit. "However, the relationship could operate in both directions. Our results don't really allow us to accurately predict the size of the effect - they're more about providing evidence that the relationship is actually causal, rather than the result of confounding or common risk factors." The study used Mendelian Randomization (MR) techniques to examine publicly available data from genome-wide association studies. MR is a form of instrumental variable analysis, using genetic variants that predict either cannabis use risk, or risk of developing schizophrenia. MR was used as an alternative to traditional observational epidemiology in an attempt to account for other variants that may affect the association, given that people who choose to use cannabis are likely to be different from those who don't in lots of other ways. Dr Gage added: "Our results use a novel method to attempt to untangle the association between cannabis and schizophrenia. While we find stronger evidence that schizophrenia risk predicts cannabis use, rather than the other way round, it doesn't rule out a causal risk of cannabis use on schizophrenia. What will be interesting is digging deeper in to the potential sub-populations of cannabis users who may be at greater risk, and getting a better handle on the impact of heavy cannabis use. "In this study we could only look at cannabis initiation. What would really help progress this research is to use genetic variants that predict heaviness of cannabis use, as it seems that heavy cannabis use is most strongly associated with risk of schizophrenia. Once genetic variants are identified that predict heaviness of cannabis use we'll be able to do this."
News Article | December 22, 2016
People at increased risk of schizophrenia are more likely to use marijuana, reports a recent study. Earlier this year, experts warned on the elevated risk of psychosis in people who use cannabis, especially those who are mentally vulnerable. International drugs experts noted that even if not everyone who smokes marijuana develops psychosis, there are high chances for vulnerable ones to develop the condition, which could be huge public health concern. Meanwhile, the researchers from the University of Bristol recently found an opposite association between cannabis use and schizophrenia. With caution for the need of in depth research on the topic, the investigators revealed that people at high risk of schizophrenia tend to try marijuana. It is also noted that such an association adds to the growing body of evidence that people may depend on drugs as means of self-medication. Dr Suzi Gage, Research Associate with the MRC Integrative Epidemiology Unit said that the findings suggest that individuals with schizophrenia risk are more likely to use cannabis. The investigator also added that the association could be functioning in both the directions. It is also noted that the study doesn't accurately relate the risk of schizophrenia with marijuana use but provides valuable evidence on the possibility. For the purpose of the study, the researchers analyzed a number of genome-wide association studies conducted earlier with the help of Mendelian Randomization (MR) techniques. The mentioned instrumental variable analysis technique was used to analyze the two risk factors with the help of genetic variants. It is to be noted that the researchers used MR for the study in place of widely used observational epidemiology considering other factors that could affect the association. It is also underscored that people inclined to marijuana could be different in a number of ways from their counterparts who don't use the drug. With the help of the novel technique a strong evidence for the association between schizophrenia risk and marijuana use is found in the study, noted Gage. Given that the study doesn't rule out the contribution of marijuana use in elevating the risk of schizophrenia. Further research warrants in depth idea on the topic. "In this study we could only look at cannabis initiation," said Gage in a press release. "What would really help progress this research is to use genetic variants that predict heaviness of cannabis use, as it seems that heavy cannabis use is most strongly associated with risk of schizophrenia." The study is published in the journal Psychological Medicine. © 2017 Tech Times, All rights reserved. Do not reproduce without permission.