Identifying social distress: a cross-sectional survey of social outcomes 12 to 36 months after colorectal cancer diagnosis

Purpose: To establish the prevalence and determinants of poor social outcomes after a diagnosis of colorectal cancer (CRC). Patients and Methods: All 12- to 36-month survivors of CRC (International Classification of Diseases [10th revision] codes C18 to C20) diagnosed in 2010 or 2011 and treated in the English National Health Service were identified and sent a questionnaire from their treating cancer hospital. This included the Social Difficulties Inventory, a 16-item scale of social distress (SD) comprising everyday living, money matters, and self and others subscales, plus five single items. Sociodemographic and clinical data were also collected. Analyses using descriptive statistics, 2 tests, and logistic regression models were conducted. Results: Response rate was 63.3% (21,802 of 34,467). Of the 21,802 participants, 17,830 (81.8%) completed all SD items; 2,688 (15.1%) of these 17,830 respondents were classified as experiencing SD (everyday living, 19.5%; money matters, 15.6%; self and others, 18.1%). Multivariable analysis demonstrated having three long-term conditions was the strongest predictor of SD (odds ratio [OR], 6.64; 95% CI, 5.67 to 7.77 compared with no long-term conditions), followed by unemployment (OR, 5.11; 95% CI, 4.21 to 6.20 compared with being employed), having recurrent or nontreatable disease (OR, 2.75; 95% CI, 2.49 to 3.04 compared with being in remission), and having a stoma (OR, 2.10; 95% CI, 1.86 to 2.36 compared with no stoma). Additional predictors of SD were young age (< 55 years), living in a more deprived area, nonwhite ethnicity, having advanced-stage disease, having undergone radiotherapy, and being a carer. Conclusion: Although it is reassuring a majority do not experience social difficulties, a minority reported significant SD 12 to 36 months after diagnosis of CRC. The identified clinical and social risk factors are easy to establish and should be used to target support

Exploring the Role of Plasma Lipids and Statins Interventions on Multiple Sclerosis Risk and Severity: A Mendelian Randomization Study

BACKGROUND: There has been considerable interest in statins due to their pleiotropic effects beyond their lipid-lowering properties. Many of these pleiotropic effects are predominantly ascribed to Rho small guanosine triphosphatases (Rho GTPases) proteins. We aimed to genetically investigate the role of lipids and statin interventions on multiple sclerosis (MS) risk and severity. METHOD: We employed two-sample Mendelian randomization (MR) to investigate: (1) the causal role of genetically mimic both cholesterol-dependent (via low-density lipoprotein cholesterol (LDL-C) and cholesterol biosynthesis pathway) and cholesterol-independent (via Rho GTPases) effects of statins on MS risk and MS severity, (2) the causal link between lipids (high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG)) levels and MS risk and severity; and (3) the reverse causation between lipid fractions and MS risk. We used summary statistics from the Global Lipids Genetics Consortium (GLGC), eQTLGen Consortium and the International MS Genetics Consortium (IMSGC) for lipids, expression quantitative trait loci and MS, respectively (GLGC: n = 188,577; eQTLGen: n = 31,684; IMSGC (MS risk): n = 41,505; IMSGC (MS severity): n =7,069). RESULTS: The results of MR using the inverse variance weighted method show that genetically predicted RAC2, a member of cholesterol-independent pathway, (OR 0.86 (95% CI 0.78 to 0.95), p-value 3.80E-03) is implicated causally in reducing MS risk. We found no evidence for the causal role of LDL-C and the member of cholesterol biosynthesis pathway on MS risk. MR results also show that lifelong higher HDL-C (OR 1.14 (95% CI 1.04 to1.26), p-value 7.94E-03) increase MS risk but TG was not. Furthermore, we found no evidence for the causal role of lipids and genetically mimicked statins on MS severity. There is no evidence of reverse causation between MS risk and lipids. CONCLUSION: Evidence from this study suggests that RAC2 is a genetic modifier of MS risk. Since RAC2 has been reported to mediate some of the pleiotropic effects of statins, we suggest that statins may reduce MS risk via a cholesterol-independent pathway (i.e., RAC2-related mechanism(s)). MR analyses also support a causal effect of HDL-C on MS risk

Youth daily exposure to tobacco outlets and cigarette smoking behaviors: does exposure within activity space matter?

Aims: To examine whether daily exposure to tobacco outlets within activity spaces is associated with cigarette smoking and with the number of cigarettes smoked by youth that day. Design: The study used geographic ecological momentary assessment (GEMA) data that combined daily surveys with ecological momentary assessment of global positioning systems (GPS) using geographic information systems (GIS) to allow for real-time data collection of participants' environments and behaviors. Setting: Eight mid-sized California (USA) city areas. Participants: The analytical sample included 1065 days, which were clustered within 100 smoker and non-smoker participants (aged 16–20 years, 60% female). Measurements: Any cigarette smoking and number of cigarettes smoked on a given day, the number of tobacco outlets within 100 m of activity space polylines each day, the number of minutes participants spent within 100 m of tobacco outlets each day and demographic characteristics (age, sex, race/ethnicity and perceived socio-economic status). Findings: Controlling for demographic characteristics, the findings of multi-level mixed effects logistic models were inconclusive, whether or not the number of tobacco outlets within 100 m of youths' activity space polylines or the number of minutes spent within 100 m of tobacco outlets were associated with whether the participant smoked cigarettes on a given day [odds ratio (OR) = 1.05, P = 0.24; OR = 0.99, P = 0.81, respectively]. However, in multi-level zero-inflated negative binomial models, the risk of smoking an additional cigarette on a given day increased with each additional tobacco outlet [incidence rate ratio (IRR) = 1.04, P < 0.05] and each additional minute spent within 100 m of tobacco outlets (IRR = 1.01, P < 0.001) each day. Conclusions: Among young people in urban California, differences in day-to-day exposure to tobacco outlets within activity spaces does not seem to be significantly associated with whether a person smokes a cigarette on a given day, but higher exposure to tobacco outlets appears to be positively associated with the number of cigarettes smoked on that day

Finding genetically-supported drug targets for Parkinson's disease using Mendelian randomization of the druggable genome

There is currently no disease-modifying treatment for Parkinson's disease, a common neurodegenerative disorder. Here, the authors use genetic variation associated with gene and protein expression to find putative drug targets for Parkinson's disease using Mendelian randomization of the druggable genome. Parkinson's disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson's disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson's disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson's disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson's disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson's disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson's disease drug development.Peer reviewe

Finding genetically-supported drug targets for Parkinson's disease using Mendelian randomization of the druggable genome

There is currently no disease-modifying treatment for Parkinson's disease, a common neurodegenerative disorder. Here, the authors use genetic variation associated with gene and protein expression to find putative drug targets for Parkinson's disease using Mendelian randomization of the druggable genome. Parkinson's disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson's disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson's disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson's disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson's disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson's disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson's disease drug development.Peer reviewe

Druggable proteins influencing cardiac structure and function: Implications for heart failure therapies and cancer cardiotoxicity

Dysfunction of either the right or left ventricle can lead to heart failure (HF) and subsequent morbidity and mortality. We performed a genome-wide association study (GWAS) of 16 cardiac magnetic resonance (CMR) imaging measurements of biventricular function and structure. Cis-Mendelian randomization (MR) was used to identify plasma proteins associating with CMR traits as well as with any of the following cardiac outcomes: HF, non-ischemic cardiomyopathy, dilated cardiomyopathy (DCM), atrial fibrillation, or coronary heart disease. In total, 33 plasma proteins were prioritized, including repurposing candidates for DCM and/or HF: IL18R (providing indirect evidence for IL18), I17RA, GPC5, LAMC2, PA2GA, CD33, and SLAF7. In addition, 13 of the 25 druggable proteins (52%; 95% confidence interval, 0.31 to 0.72) could be mapped to compounds with known oncological indications or side effects. These findings provide leads to facilitate drug development for cardiac disease and suggest that cardiotoxicities of several cancer treatments might represent mechanism-based adverse effects

Glucagon-like peptide 1 (GLP-1).

BACKGROUND: The glucagon-like peptide-1 (GLP-1) is a multifaceted hormone with broad pharmacological potential. Among the numerous metabolic effects of GLP-1 are the glucose-dependent stimulation of insulin secretion, decrease of gastric emptying, inhibition of food intake, increase of natriuresis and diuresis, and modulation of rodent β-cell proliferation. GLP-1 also has cardio- and neuroprotective effects, decreases inflammation and apoptosis, and has implications for learning and memory, reward behavior, and palatability. Biochemically modified for enhanced potency and sustained action, GLP-1 receptor agonists are successfully in clinical use for the treatment of type-2 diabetes, and several GLP-1-based pharmacotherapies are in clinical evaluation for the treatment of obesity. SCOPE OF REVIEW: In this review, we provide a detailed overview on the multifaceted nature of GLP-1 and its pharmacology and discuss its therapeutic implications on various diseases. MAJOR CONCLUSIONS: Since its discovery, GLP-1 has emerged as a pleiotropic hormone with a myriad of metabolic functions that go well beyond its classical identification as an incretin hormone. The numerous beneficial effects of GLP-1 render this hormone an interesting candidate for the development of pharmacotherapies to treat obesity, diabetes, and neurodegenerative disorders